Emerging Technologies for Information Systems, Computing, and Management

To solve the problems that the large Doppler shift makes satellite signals difficult to be captured and the high dynamic stress damages the health of the tracking loop, a novel design is proposed for high dynamic GPS receiver, which can rapidly capture signals against the large Doppler shift and has high tolerance of the high dynamic stress in its tracking loop. The satellite signals are captured by means of linear search method. The carrier wave is tracked by carrier tracking loop using Frequency-locked loop (FLL) assisted by phase-locked loop (PLL). The form of Carrier wave aided is adopted in the pseudo-code tracking loop. The experiment shows the receiver prototype can track 100 g/s high dynamic signal, which indicates that the receiver prototype could satisfy the error limits of the tracking loop, and it also can capture the visible satellite signals with a good effect of real-time tracking lock.

In order to evaluate and optimize the performance of service composition, a formal description of Grid workflow activity and a model of grid workflow service based on Generalized Stochastic Colored Petri Net are presented in this paper. The token of color of GSCPN can be used to stimulate the different events of message types of business processes. Moreover, Grid workflow service composition algorithm and reduction algorithm based on GSCPN are proposed. Empirical results show that the reduced model reduces the complexity of the qualitative and quantitative analysis of the generated grid workflow service model. The grid workflow service model based on GSCPN can be used for performance prediction and to guide the optimization.

This paper aims to study independent and complete characterization of speaker-specific voice characteristics. Thus, the authors conduct a method on the separation between voice characteristics and linguistic content in speech and carry out voice conversion from the point of information separation. In this paper, authors take full account of the K-means singular value decomposition (K-SVD) algorithm which can train the dictionary to contain the personal characteristics and inter-frame correlation of voice. With this feature, the dictionary which contains the personal characteristics is extracted from training data through the K-SVD algorithm. Then the authors use the trained dictionary and other content information to reconstruct the target speech. Compared to traditional methods, the personal characteristics can be better preserved based on the proposed method through the sparse nature of voice and can easily solve the problems encountered in feature mapping methods and the voice conversion improvements are to be expected. Experimental results using objective evaluations show that the proposed method outperforms the Gaussian Mixture Model and Artificial Neural Network based methods in the view of both speech quality and conversion similarity to the target.

The paper aims to develop a computer terminal solution which suits with the status of the company to eliminate risks of information security caused by the huge amount of computer terminals. The research carries out analysis on Intranet access, standard configuration, information data management, etc. through introduction of standards fit with national information security requirements. To make the analysis smooth, the author uses a real example of computer terminal configuration in a nuclear power plant. Results of implementing the solution in the real example show that security risk of computer terminals are eliminated, and the information security level of the company is significantly improved. The configuration solution is scientific and effective. It is capable of reducing risks from computer terminals to enterprise information security, and it can provide reference to information security construction in companies of the similar situations.

Specifically for quantify and extract meridian information, a comprehensive multi-acupoint feature index was given. The feature parameters of single acupoint were extracted and reconstructed based on AR parameter model. Then feature weight was obtained by objective weighting method and feature matrix was weighted. The ideal feature vector was built based on orthogonal transformation of eigenvalues in meridian feature space. Based on PCP, the distance between each feature vector and the ideal model vector was calculated, and the projection value of fixed-weighted feature matrix on ideal feature vector was obtained. The simulation results show that the method can be more stability and higher around 3 % in the recognition rate than the main acupoint in human multi-acupoint system. The same results also show that the recognition rates can be coincided with sort results.

In order to support those companies which use SAP as their ERP management software to develop the Finance Share Service Center (SSC), the centralized maintenance mode is strongly recommended. In this paper, by introducing the disadvantage of common decentralized maintenance mode, elaborating the structure of the SAP centralized maintenance mode and analyzing this mode’s effectiveness, the SAP centralized maintenance mode is proved to be a better solution to resolve the conflicts and difficulties between SSC and the companies accepting SSC services. Thus, SAP centralized maintenance mode is able to provide a better and safer SAP maintenance service to SSC.

In order to solve the large amount of data of polyphase filter banks channelization, a new method is used in this paper. The method greatly simplifies the complexity of the channel filter banks channelization, in the extraction rate to the original 2 times and reduces the need for processing data transmission rate. This method has a better signal real-time processing ability and good application prospect. Through the simulation experiment, this method proves to have a good feasibility.

Conventional multimedia information retrieval systems use a central system to store and index multimedia data. Inherent limitations of such a central approach surface many problems, such as insufficient bandwidth, server overloading and failures. In order to retain the original system and control the cost, the paper shares the access pressure of central servers by constructing a peer-to-peer network based on interests. A user’s interest is computed by mining this user’s search behaviour periodically. Then researcher form a peer-to-peer network based on interests by clustering peers with similar interests. Centralized server will push relevant multimedia information to certain communities on time. By this way, uses can further clear what they want, and useless retrievals on servers will be dramatically decreased. The experimental results evaluate the average search path length of unstructured P2P network, semi-distribution P2P network and the P2P network based on interest community and demonstrate the efficiency of the approach.

Among all the anonymous communication systems, Onion Routing is most widely used. Tor affords users with anonymous service in communication. It can be used in running anonymous web browsing and announcement, real-time communications, IRC, SSH and other TCP applications. After analyzing the source code of the Tor system, this paper introduced the network layout, working flow, the RouterUpdate method of establishing a virtual circuit and data sending or receiving in Tor system. The method helps Tor client using the relay nodes which have been stored to connect the internet of Tor without connecting the list server. Then the paper introduced a method to help the Tor client using all the applications whether or not using the SOCKS.

As construction projects becoming increasingly large and complex, the traditional methods of schedule management largely undermine the improvement of management level. However, the integration of Building Information Modeling (BIM) and scheduling information can help maintain control of scheduling goals and enhance project performance. This paper proposes a BIM-based construction schedule management framework and establishes a model to integrate scheduling information in life cycle. Moreover, information retrieval and integration and core supports for realizing the model are also examined. The study extends the existing research of construction schedule management, and can be used as guidance for BIM-based schedule management practice.

This paper innovates the p-hub airline network median design method. Researchers present a new mathematical programming model, which incorporates the interaction between elastic demand in air passenger market and airline network structure. The model optimizes both the ticket prices and the profit of airline company, and subsequently determines the passenger volume influenced by different network structure. The effectiveness and practicability of the model are demonstrated by a realistic example of Chinese airline network which includes 15 major airports. Numerical analysis result indicates that hub locations tend to select the airports which have bigger passenger volume.

In this paper, authors propose a fast and efficient ranking method for interval grey numbers based on the idea of mean value and mean square deviation in statistics. If the degree of greyness of grey number is very small, the interval grey number is then big when the kernels of the interval grey numbers are equals. Authors extend data information weighted arithmetic averaging (WAA) operator, ordered weighted averaging (OWA) operator and hybrid weighted averaging operator (HWA) operator, meanwhile they propose interval grey numbers WAA operator, interval grey numbers OWA operator, and interval grey numbers HWA operator. According to these operators, authors develop an approach to solve grey multi-attribute multi-person decision-making problems, in which the attributive weights are completely known and the attributor values are interval grey numbers. Finally, an illustrative example is given.

Aiming at the problem of low query efficiency and delay of Object Naming Service (ONS), an improved Chord algorithm is used in this paper. By introducing an improved Chord algorithm for information discovery service of EPC network, this paper classifies neighboring nodes into a group, stratifies all the nodes according to the different performance, and selects more powerful nodes as the super nodes to manage ordinary nodes in the same region. The results of simulation experiments show that the query hops and network delay are both reduced while query efficiency is improved to a certain extent. Improved Chord algorithm can effectively solve the problem of ONS query bottlenecks, thus the query efficiency in information discovery service of EPC network is improved.

In order to construct goals model completely, a heuristic way is proposed in this paper based on multiple views. A meta-model is proposed for guidance of modeling of organizational view, business view and goal view. In the meta-model, the relationship among actor, task and goal in meta-model shapes an iron triangle and establishes basis of the heuristic way for goal modeling. In this way, goals can not only be constructed directly by decomposition of goals, but also be elicited indirectly by analysis of the purpose of every task appearing in business view and by asking actors appearing in organizational view why they do the work they undertake. For illustration, a case about a hospital management information system is offered to illustrate idea of this method. This heuristic way is very practical for goal modeling, which can be seen as a helpful complement for directly goal modeling.

In order to obtain the remote environmental parameters, the sensor module and the mobile software is designed for a new environment monitoring system based on Internet of Things (IOT) in this paper. SHT10 digital humidity, temperature sensor and TSL2561 light-to-digital converter are used to get the environmental parameters such as the temperature, the humidity and the luminance. IOT technology is used to transform the parameters data to remote server through GPRS network, and SIM900 chip is opted to accomplish GPRS function. Ajax and mobile platform are combined to make sure that the environment data on the server can be easily accessed. Experiments demonstrated that by using Ajax in the web application, the time to reach the information reduced a lot, and the users can monitor the environmental parameters easiest via their mobile cell.

Convergence of heterogeneous products and services is now a leading phenomenon of telecommunications industry. These new and innovative converged applications are able to meet the diversified but pooled demands of the subscribers, so their demand is rapidly increasing. In this paper researchers have done both qualitative and quantitative analysis to find out subscriber satisfaction levels for these services. This analysis is based on utility theory, probability theory and Bayes theorem. The aim of this analysis is to find out subscribers’ satisfaction levels and their willingness to pay for converged applications for decision making by manufacturers and service providers. The research found that cost effective converged application with maximum satisfaction is preferred by consumers and will play leading role in expansion of this market in future.

Previous research suggests the great importance of scrutinizing the information technology (IT) artifact itself. Yet, there is still limited attention to meet that goal. In this research, authors employed multiple research methods to investigate the technological characteristics dimensions, mainly including grounded theory method, focus group in-depth interview, content analysis, panel expert judgments and survey method. The results indicate that the complexity, utilitarian, hedonic, communication, flexibility, reliability, integration, accessibility, timeliness, accuracy, completeness, currency, format and stability are the critical and universal technological characteristics dimensions. Corresponding measurement items were also developed and illustrated. The findings have the potential to be applied in future investigations on the technological characteristics of IT artifact.

The high side lobe level is a serious problem for the circular array pattern. In order to solve this problem, a new method for the pattern synthesis of circular array is proposed in this paper. It makes the location of the array element and the coefficient as joint variables for its optimization model based on the niche genetic algorithm, which can overcome the shortcomings of premature and bad local searching capability existing in simple genetic algorithm. This approach can not only enhance the variables freedom degree but also accord with the academic global optimization. A measure is proposed to alleviate the dependence of convergence on the initial population, in which two reproduction operations of different types are alternatively used in generating chromosomes. The simulation results show the efficiency of this method.

Based on the relationship between coronary artery blockages and heart sound signals, a novel processing method on heart sound signal of early diagnosis of coronary heart disease was proposed. With the wavelet analysis, the heart sound signal was decomposed and reconstructed, and the coefficient of each layer was extracted. The information content of the first and the second heart sound signal (S1, S2) was calculated from Shannon entropy. The time threshold was applied to obtain the interval between S1 and S2. All the characteristic values were combined into a matrix containing nine elements, which was regarded as the input of a BP neural network for the identification of heart sound signal. The results show that the proposed algorithm is highly accurate for the early diagnosis of coronary heart disease. The recognition rate of the simple aortic regurgitation, the aortic regurgitation, the mitral valve stenosis and mitral valve insufficiency were 73.33, 80.00, 86.67 and 93.33 % respectively. It provides a non-invasive early diagnosis method of coronary heart disease.

In the initialization of the traditional semi-supervised k-means, the mean of some labeled data belonging to one same class was regarded as one initial center and the number of the initial centers is equal to the number of clusters. However, this initialization method using a small amount of labeled data also called seeds which are not appropriate for the semi-supervised k-harmonic means clustering insensitive to the initial centers. In this paper, a novel semi-supervised k-harmonic means clustering is proposed. Some seeds with one same class are divided into several groups and the mean of all data is viewed as one initial center in every group. Therefore, the number of the initial centers is more than the number of clusters in the new method. To investigate the effectiveness of the approach, several experiments are done on three datasets. Experimental results show that the presented method can improve the clustering performance compared to other traditional semi-supervised clustering algorithms.

Non Uniform Memory Access (NUMA) architecture becomes more and more popular as it has better scalability than Uniform Memory Access (UMA). However, all previous work on the operation system scheduler assumed that the underlying system is UMA. As a result, the performance degrades on NUMA machines due to lacking of consideration to the underlying hardware. Researchers discover that the Completely Fair Scheduler (CFS) does not work smoothly on NUMA machines and even interfere performance relative to the O (1) scheduler. In this paper researchers investigate the causes for the performance decline and devise an architecture aware task-bound approach for NUMA system, which can help the CFS scheduler works efficiently on NUMA platforms. The evaluation shows that the approach can upgrade the system performance by more than 60 % on average. The research has great significance to the development and popularity of domestic operating system.

This paper describes a novel technique for crawling Ajax-based applications through “event-driven” crawling in web browsers. The algorithm uses the browser context to analyse the DOM, scans the DOM-tree, detects elements that are capable of changing the state, triggers events on those elements and extracts dynamic DOM content. For illustration, an AJAX web application is utilized as an example to explain the approach. Additionally, the authors implement the concepts and algorithms discussed in this paper in a tool. Finally, the authors report a number of empirical studies in which they apply their approach to a number of representative AJAX applications. The results show that their method has a better performance often with a faster rate of state discovery. The “event-driven” crawling can effectively and accurately crawl dynamic content from Ajax-based applications.

This study presents some class of feedforward neural networks to investigate the universal approximation capability of continuous flexible functions. Based on the flexible approximate identity, some theorems are constructed. The results are provided to demonstrate the universal approximation capability of flexible approximate identity neural networks to any continuous flexible function.

The shortcoming of traditional spectral clustering algorithm is its dependence on initial value. This paper proposes a spectral clustering algorithm based on the particle swarm optimization, considering the characteristic of the good global and local optimization capability and the randomization of initial population. According to the example analysis, the spectral clustering algorithm based on the particle swarm optimization has overcome the shortcoming of excessive dependence on initial value of the traditional spectral clustering algorithm. The accuracy of the cluster is improved.

In order to make the Linux operating system available on a cache coherence NUMA (cc-NUMA) server based on Loongson processors, a family of general-purpose MIPS64 CPUs developed by the Institute of Computing Technology in China, this paper proposes a framework for porting Linux operating system to this cc-NUMA server. Researchers present the overall port scheme after analyzing the framework of the Linux kernel and the architecture of the hardware platform, and then they discuss the transplantation in details with processor-level transplantation, memory management transplantation, interrupt and trap transplantation. The performance evaluation shows that the whole system works stable and the ported operating system could reach about 30 % of the theoretical peak value of floating-point calculation. The method could port Linux OS to the target board successfully and can be used on other platforms. The research has great significance to the development of the domestic Loongson processor and the cc-NUMA platform based on Loongson processors.

To solve the problems of high cost and unreasonable location layout that the self-built logistics system of a B2C E-commerce company has, a B2C logistics distribution optimization solution is proposed. The solution established a mathematical model based on the construction costs of the regional distribution centers, the operation costs of the whole logistics distribution network, the transportation costs of the whole supply chain and the penalty cost for the situations of delivery overtime. The model considers the factors of economies of scale and standard service level. As the model has NP-Hard complexity, a mixed genetic and simulated annealing algorithm is proposed to solve the problem. And at last, a case of a B2C e-commerce company verifies the correctness of the whole theory.

In order to properly solve multi-objective optimization problem, an improved multi-objective differential evolutionary algorithm with an adaptive crossover rate is proposed in this paper. To adjust the evolution adaptively, an adaptive crossover rate is integrated into the differential evolution. The new strategy can diverse pareto individuals and further to pareto front, which avoids the local convergence that traditional differential evolution always trapped in. In addition, combining with great ability of searching local optima of differential evolution, evolutionary speed and diversity can be simultaneously improved by the modified crossing operator. The simulation on these benchmark problems verifies the efficiency of the proposed algorithm with convergence metric and diversity metric, and the obtained results also reveal that the proposed method can be a promising alternative in solving multi-objective optimization problems.

In order to reduce the network communication cost of the discovery of distributed services and improve the search efficiency and recall performance, researchers put forward a distributed service discovery strategy based on semantic in P2P environment. Firstly, they constructed an ontology model to describe the types of services, and then located the starting point of the search process on the associated Peer node based on semantic service classification. Secondly, a double layer parallel service discovery method was put forward. In UDDI layer, they used the classic keyword matching to search services in UDDI center. In the semantic layer, researchers used the semantic query and reasoning on the service ontology model. Finally, the performance of the proposed method was verified by experiment.

String matching is a fundamental problem in computer science. In order to gain higher performance online exact single pattern string matching algorithms, the authors improved the Skip algorithm which is a comparison based exact single pattern string matching algorithm. By introducing the

q

-grams method in the sliding window and the comparing window of Skip respectively, the branch prediction failure and the average branch cost are reduced. Meanwhile, the greedy jump method is introduced in Skip. Greedy jump is a common accelerating method for string matching, while there are some waste reads for algorithms with unfixed jump distance. Since Skip has fixed jump distance, greedy jump is more suitable for Skip. Therefore, the authors presented the HGQS algorithm. Experiments results have indicated that HGQS has higher practical performance and it is more efficient in some cases than other known algorithms in many cases on the platform.

This paper proposed a new algorithm for burst signal sorting. The proposed algorithm can be used to identify and locate TDMA users based on the continuity of carrier phase. In the proposed algorithm, the continuity of carrier phase between TDMA burst signals is evaluated according to their frequency deviations, initial phases and initial positions. Then burst signals are sorted based on their degree of continuity. The proposed algorithm is effective when researchers do not know the information which the burst carries. Some simulations and experiments in this paper show that the accurate rate of the proposed sorting algorithm is greater than 0.9 when the ES/N0 > 6 dB. Specially, and the performance is stable when the frequency deviation changes.

GNSS signal acquisition is the most important process in a receiver followed by tracking and extraction of navigation bits. Partial Matching Filter (PMF) and Fast Fourier Transform (FFT) algorithm has advantages in acquisition speed and hardware complexity. In general, GNSS navigation data acquisition needs a common frame synchronization algorithm, which takes one sub-frame period of time for a determination. This means the receiver will take at least 6 s to reposition after the signal lost lock and recapture. In this paper, the design of PMF-FFT based receiver is described. A fast method of solving the long-time frame synchronization problems is proposed. The method uses the α-β filter algorithm to correct local time and estimate signal sending time. Experimental results show that the proposed methods for the PMF-FFT based receiver are able to perform faster and reliable acquisition and reposition.

In a multi-factor comprehensive evaluation, the factors related to objects are always various and most of them have the characteristics of uncertainty. Taking the mapping between qualitative and quantitative knowledge of cloud model, a high dimensional cloud model with core space was built. And then based on a sample set of maintenance and management of the 55 bridges in Chongqing and an index system with six first-level indices, parameters of the high dimensional cloud model with core space and mean membership of every bridge sample were computed and gotten. Compared with the results of cloud model, experts experience and support vector machine for this sample, it indicated the cloud model with core space could be applied to a multi-attribute evaluation well. Finally, according to the evaluation, some suggestion was given.

A Hadoop MapReduce cluster is an environment where multi-users, multi-jobs and multi-tasks share the same physical resources. Because of the competitive relationship among the jobs, we need to select the most suitable job to be sent to the cluster. In this paper we consider this problem as a two-level scheduling problem based on a detailed cost model. Then we abstract these scheduling problems into two games. And we solve these games in using some methods of game theory to achieve the solution. Our strategy improves the utilization efficiency of each type of the resources. And it can also avoid the unnecessary transmission of data.

On account of the closed products and other defective products in the current market, this paper puts forward and carries out the Dynamic USBKEY System. This system is based on Multiple Verification Algorithm and is able to verify the validity of users’ identity in a high-strength dynamic channel. Firstly, the security of the entire system is based on the strength of the random key. The overall design and the adopted algorithm are open. Secondly, it can solve the problems within the channel, the verification method and the program’s self-preservation. Thirdly, the system provides a more secure solution under the rapid programming mode. The developers can apply the system on their own programs through the opened cross-language interface. As a result, the development cycle can be shortened and the security strength of their program can be improved.

Anomaly detection in a time series has attracted a lot of attentions in the last decade, and is still a hot topic in time series mining. In this paper, an anomaly detection algorithm based on pattern density is proposed. The proposed algorithm uses the anomaly factor to identify top

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anomaly patterns. Firstly, a time series is represented based on its key points. Secondly, the represented time series is partitioned into patterns set. Thirdly, anomaly factor of each pattern is calculated, and anomaly factor is presented to measure the anomalous degree of a pattern by taking into account the characters of its neighbors. Finally, Top

$$ k $$

k

anomaly patterns are identified. The effectiveness of the anomaly detection algorithm is demonstrated with standard and artificial time series, and the experimental results show that the algorithm can find out all anomaly patterns with different lengths.

Equivalent surrogate experiments are important information sources when the prototype experiment is limited to do. To explore the design methodology for the experiments with multiple sources, the optimal design of experiment for damage assessment is studied as an example and the following works are done. Firstly, the discrepancy between the prototype experiment and the four equivalent surrogate experiments, which are reduced scale test, test with surrogate drones, static test and simulation, is analyzed. Secondly, the parameter model about the discrepancy is constructed, and so does the fusion model. Thirdly, the integrative optimal design is developed, and then the iterative algorithm for constructing the integrative Dn-optimal design is also discussed. Lastly, an example about the integrative Dn-optimal design of the flight and static experiments about the projectile penetrating into the concrete is given, and the example shows that the proposed method is more efficient than the standard Dn-optimal design.

Radio tomographic imaging is an emerging technology of imaging the attenuation by the objects in the area surrounded by the wireless sensor nodes to locate and track the objects. So it’s significant to reconstruct the image in real-time to track the motion of the objects and also with good enough imaging quality. Tikhonov regularization can achieve the real-time requirement with acceptable imaging results by one-step multiplication. Landweber iteration can obtain better imaging quality but need many times of iteration. This paper use pre-iteration method to complete the iteration process of Landweber iteration offline and reconstruct the image online by one-step multiplication, just like Tikhonov regularization. Simulation and experiments show this method can get better imaging results than Tikhonov regularization and imaging the objects in real-time.

Global Navigation Satellite Systems (GNSS), including GPS, BeiDou, GLONASS, Galileo and other systems, are becoming more and more widely used in our today life. As a result, multi-constellation receiver that compatible with more than one system will take the place of single-constellation receiver that only uses GPS or BeiDou system. Reliability monitoring algorithm in single-constellation receiver has some limitations when applied in multi-constellation receiver. Therefore, an enhanced reliability monitoring algorithm based on weighted and statistic schemes is designed for multi-constellation receiver that compatible with GPS and BeiDou in this paper. The experiment results show that the algorithm improves the performance in both static and dynamic scenes, especially about 31 % in static scene than the BeiDou/GPS multi-constellation receiver without it.

Model checking is a promising automated verification technique. The state space explosion is the major difficulty of model checking. To deal with this problem, researchers present a new model checking algorithm for the temporal logic CTL based on MapReduce framework. And the algorithm’s data structure is defined for the Kripke structure. This MapReduce algorithm outputs the set of states of the model that satisfies the formula by giving a model and a CTL formula. Researchers justify its correctness by an example with the EU formula. Finally, an example illustrates the validity of this algorithm, and the result shows this method is feasible.

Resource load balancing problem of the large-scale and heterogeneous network was studied. The problem was modeled and analyzed theoretically at first, and an objective function which satisfied the host and network constraints was designed. Then, a multi-objective minimum spanning tree problem was researched, and then a multi-objective genetic algorithm was devised. At last, a dynamic load balancing scenario was proposed. The simulation results show that, LBSG can balance the load effectively between the light-load nodes and the overload ones. Besides, the performance of the scenario is obviously better in a larger scale network.

Using the basic ant colony algorithm to solve the constrained vehicle routing problem (CVRP) has some drawbacks such as slow convergence speed and easily getting into local optimum. To effectively solve the CVRP, this paper has proposed a new ant colony algorithm (ACA-CVRP) based on the dynamic update of local and global pheromone and improved transfer rule. In order to shorten the process, the authors introduced the candidate list and 2-opt searching strategy. The experiment result shows that ACA-CVRP achieves better performance in optimum solution compared with other five main meta-heuristic algorithms.

Active Queue Management is the key to congestion control and enhancing IP QoS. MRED can support MPLS networks and take advantage of classifying mechanism of DiffServ and mark different businesses with different drop precedence. However, it has several limitations. In this paper, I-AMRED is proposed in order to reduce packet loss ratio and raise throughput in MPLS networks based on DiffServ and MRED. Thus, it can also adaptively control average queue length, and diminish sensitiveness to control parameters and improve stability with the service flow bursts. Two experimental schemes are designed and implemented on NS-2. Experimental results show that I-AMRED algorithm increases throughput of networks and largely decreases packet loss ratio of AF PHB traffic. When data traffic is very large or sharply increased, the performance of throughput and packet loss ratio is improved greatly, and has better stability.

To guarantee the running of system without collapse when deal with the complex changes of personnel and departments and implement the compatibility of the workflow system within different kinds of enterprises under certain regulations, Workflow with Partition Algorithm on Finite Field denoted in this paper provides an efficient solution. According to the performance of the eventually practice, this strategy completely solve the problem of addressing the issues of personnel position and department architecture changes in an enterprise as well as the requirement of enforcing the compatibility of the workflow system when deploying on different enterprises and also reduce the cost of system designing and new user importing time.

Recently the Electric Power Enterprise have many problems showing up. Combining the characters of Electric power enterprise supplies, researchers build an optimized network model to solve the irrationality of warehouse network, the simplex distribution and the high storage cost. This new model uses a method different from gravity and radius method which usually used by the general models. Researchers also discuss the penalty costs, construction costs and the operation costs in this paper. They use simulated annealing algorithm based on a mixed MCPSO (Multi-swarm Cooperative Particle Swarm Optimizer) in the new model. Fortunately, in an actual project of Power Supply Company, this optimized scheme is verified to be rational and effective.

In this paper, the Bi-level programming model with random prize is presented to solve the industrial location problem. In terms of the binary coding, and controlling the location numbers on the operation of neighborhood, three kinds of neighbor domain are proposed by introducing the taboo search algorithm. In order to improve the taboo search algorithm for the efficiency and effectiveness of the addressed algorithm, the research utilizes a penalty function to deal with the constraints of the total amount of investment as well as introducing the principal of the model and TS. The representative example is used to illustrate the correctness of the optimal algorithm.

The aim of the study was to investigate temporal changes of brain to visual stimuli in earthquake-exposed survivors using event-related potentials (ERPs). The present study used ERP to explore whether trauma event and experience had much greater influence on earthquake-exposed survivors than controls, which could provide neuroscience evidences in the psychotherapy for earthquake-exposed survivors. After filling out a series of psychometric questionnaires, 13 earthquake-exposed middle school students and 13 healthy age and sex matched unexposed controls were investigated by using a visual oddball paradigm. One thousand visual stimuli trials were randomly presented with “target” stimuli occurring at a probability of 10 %, “novelty” earthquake-related stimuli 10 %, and “frequent” stimuli 80 %. Participants were asked to respond to “target” stimuli while ignoring other stimuli. Electroencephalogram (EEG) was continually recorded in order to assess P300 responses, an event-related potential (ERP) associated with attention processes. The results showed that the earthquake-exposed group had significantly reduced more P1 and P300 compared to the non earthquake-exposed control group. It indicated that the trauma event and experience had much greater influence on earthquake-exposed survivors than controls.

According to the actual needs of equipment training, function and structure of simulation system present themselves by comparing past training systems. The ideas are elaborated which include solid modeling, 3D terrain rendering, fault databases generation and control rules setting. The system was realized based on 3D interactive devices and programming language. By using forces, the system meets the design requirements and the training needs.

Sparse projection is an effective way to reduce the exposure to radiation during X-ray CT imaging. However, reconstruction of images from sparse projection data is challenging. In this paper, a novel method called reweight total variation (WTV) is applied to solve the challenging problem. And based on WTV, an iteration algorithm which allows the image to be reconstructed accurately is also proposed. The experimental results on both simulated and real images have consistently shown that, compared to the popular total variation (TV) method and the classical Algebra Reconstruction Technique (ART), the proposed method achieves better results when the projection is sparse, and performs comparably with TV and ART when the number of projections is relatively high. Therefore, the application of the proposed reconstruction algorithm may permit reduction of the radiation exposure without trade-off in imaging performance.

The paper aims to solve the radio altitude signal mixed with sea wave noise which should be filtered as the helicopter executing the antisubmarine task. The sea wave is modeled based on the rational spectral approach and obtained in the form of white noise shaping filter as the sea wave color noise is changed into white noise. For the measurement equation and state equation can be formed including the estimated value, the sea wave filter is brought out according to the continuous Kalman filtering theory and added to the altitude channel. Lastly, the cable-height control system has taken radio altitude and normal acceleration which have been filtered as feedback signals. The effects of the filter in different wind speeds are separately verified by the digital simulations, and the results show the design approach is available and effective.

In order to increase the embedding capacity when one hides information in 2D vector maps in a reversible way, researchers present a novel algorithm based on prediction-error expansion. In two neighboring coordinate values, researchers use the latter as the predicted value of the former. The difference between the original value and the predicted one is the prediction error. Then, the prediction error is expanded to hide one watermark bit. To control the distortion, researchers preset a threshold. Only those satisfying the threshold condition are selected for embedding. The others are shifted so that the decoder can identify the marked coordinate values by the range that their prediction errors fall into. Experiment results show that bits per coordinate (bpc) on the test river map is 0.7. The algorithm has good performance in capacity and RMSE value. The proposed algorithm can be used in 2D vector maps for data integrity protection, etc.

Robust visual tracking has become an important topic in the field of computer vision. The integration of cues such as color, shape features has proved to be a promising approach to robust visual tracking. In this paper, an algorithm is presented which integrates Hu moments and color histogram. Moreover, this paper integrates the ABCshift algorithm to overcome color features drawbacks which easily lead to loss of target object when the color of object is similar to the color of background. The proposed algorithm has been compared with other trackers using challenging video sequences. Experimental work demonstrates that the proposed algorithm has strong robust and improves the tracking performance.

Coded exposure photography makes the traditional ill-posed motion deblurring problem well posed. However, how to accurately derive the motion blur length confused many researchers because of the non-smooth blur of the coded exposure image. This chapter proposes a novel approach to automatic estimate the motion blur length by analyzing the image statistics for coded exposure photography. The researchers analyze the image power spectrum statistics and observe that the motion blur length has some relations with the residual sums of squares (RSS) of the image power spectrum statistics in a least squares sense. That is, the power spectrum statistics of the obtained deblurred image using the correct estimated blur length corresponds to the lowest value of the RSS. Given an initial blur length, and using the high-speed direct deconvolution approach, researchers can easily find the correct blur length using a global search method. The experimental results demonstrate the validity of the proposed method.

A novel wavelet sub-band selection scheme for medical image fusion, based on the Parameterized Logarithmic Image Processing (PLIP) model, is presented in this chapter which takes the characteristics of human visual system (HVS) and the spatial distribution of wavelet coefficients into account. The different fusion schemes are applied for the different frequency sub-bands. The visibility weighted average method is selected for coefficients in low-frequency band and a variance based weighted method is selected for coefficients in high-frequency bands. Subsequently, the fused coefficients are processed with consistency verification to guarantee the homogeneity of the fused image. Computer simulations illustrate that the proposed image fusion algorithms with the PLIP model is superior to some existing fusion methods, and can get satisfactory fusion results.

Color Channel Comparison Method is an effective method to transform color images into gray ones. This method can enhance pests’ characteristics and remove the background to some extent. However, some interfering background cannot be removed. In order to solve this problem, an improvement on Color Channel Comparison Method is realized in this paper. Comparisons between gray brightness and a threshold value determine whether the pixel is the interfering background. And the threshold value is determined according to the brightness of the image. Empirical results show that the interfering background in black or white pests’ photo is effectively cleared, and black or white pests can be more effectively separated from the colored background by using the improved method. The improved color channel comparison method can effectively solve the interfering background problem of Color Channel Comparison Method.

Multi-modal remote sensing image registration is to align images acquired by different sensors and modalities. It is the fundamental step for following image analysis. Previous multi-resolution methods use spatial pyramids to achieve hierarchical registration with little consideration of the characteristics of pyramid transforms or robust point set registration methods after feature detection. Targeting at both problems, this paper proposes a novel image registration method by combining steerable pyramid and Gaussian mixture models. Steerable pyramid has been proved to be shift-invariant and outperforms traditional pyramid transform. Point set registration methods using Gaussian mixture model has been lately proposed and proved to be more robust and accurate than traditional point set registration methods. Experiments on real multi-modal remote sensing image pair demonstrate the feasibility of proposed method.

This paper presented an offset modify method in histogram testing of ADC based on sine wave. The method of using histogram to estimate the code transition level is introduced firstly. Then the paper presented the modify method that use the difference between the cumulative histogram of low codes and the cumulative histogram of high codes. Simulation result demonstrated that the method introduced by this paper is efficient.

In order to extract text regions in the color image, this paper proposes an image text extraction method based on morphology and color layering. Firstly, we extract the edges with Sobel operator, and then extract rectangular regions and non-rectangular regions according to text features by using morphological methods. Finally, we handle these two types of regions respectively where in Color Layering Algorithm is implemented when dealing with non-rectangular regions. This paper also proposes Large Characters Repair Algorithm so that the method can also be applied to the images with texts of different fonts. During the research, we have found that Color Layering Algorithm can separate text from complex background effectively, which makes background removed more easily. The experimental results show that the proposed method has a high accuracy rate.

In the presence of unequal lighting conditions and complex backgrounds, this paper proposes a novel face detection algorithm for color images which consists of four pivotal parts primarily: image preprocessing based on color balance and light equalization, skin region segmentation and extraction based on CbrCbgCgr ellipsoid skin model, image post-processing based on morphology, as well as face and facial feature detection based on AdaBoost classifier and facial geometry. Experimental results demonstrate that the algorithm can be effectively applied to the cases of unequal light, complex background and multi-face conditions.

Emergency resource is too huge to make quick decision of pre-warning issues. Aiming at this problem, ontology and Swrl (Semantic Web-Rule Language) rules are introduced in emergency pre-warning decision support system to express and integrate the pre-warning resource. And intelligent reasoning is also provided in this system. The validity of ontology model and Swrl rules are verified feasible in experimental results. The shortage of this system is also exposed in practice. Improvement is needed in future research.

Feature reduction is an important issue in pattern recognition. Lower feature dimensionality reduces the classifier complexity and enhances the generalization ability of classifiers. In this paper, researchers proposed a new method for feature dimensionality reduction based on Locally Linear Embedding (LLE) and Distance Metric Learning (DML). Researchers first adopt metric learning method to enhance the class separability, and map the original data to a new space. They use a transformation learned from the data via metric learning method, and then utilize the LLE method to generate an embedding from the transformed data to a lower dimensional manifold. Thus they achieving feature dimensionality reduction, where the final mapping for feature reduction is the composition of the above two transformations learned via DML and LLE method respectively. The method introduces the LLE method traditionally used in unsupervised tasks into the supervised learning domain via a proper and natural way. Experiment results clearly demonstrate the efficiency of the proposed feature reduction method in supervised learning tasks.

One of the goals of planetary exploration is to cache rock samples for subsequent return to Earth in the future Mars Sample Return (MSR) mission. Rock segmentation is significant for the achievement of MSR mission and its scientific studies. The paper presents a new approach to detect and determine the locations of the rocks in the pair of images. This new method consists of two major processing procedures: Rock Rough Boundary Detection and Template Dilatation Edge Linking (TDEL). The first processing block rock rough detection has been designed to find a rock’s closed rough contour using the OTSU algorithm (maximum between-class variance method) for background removal and using Canny algorithm for discontinuous contours of the rocks from the original stereo image pairs. TDEL is an algorithm of edge linking for obtaining accurate contours of the rocks in the image of multiple levels of a multi-scale image pyramid. Current work is in preparation for the eventual grasping of a rock using our developed technique. Researchers are currently testing the program code (OpenCV) by using image data acquired from the Aberystwyth University Pan-Cam Emulator (AUPE) instrument of the Trans-National Planetary Analogue Terrain Laboratory (PATLab). Experimentation results are presented and show the validity of the method which can effectively detect rocks in this paper.

A Recognition method of CD4 cell images and the principle of support vector machines are studied in this paper. The recognition method based on SVM is proposed to solve Microscopic image recognition of CD4 cell with a small sample size and less prior knowledge. An improved parallel grid search method is used to choose the parameters of OSU_SVM classifier, so the computation time is significantly reduced. Cross validation is employed to test the performance of SVM classification. With this new method, the recognition rate of CD4 cell image reaches to 95 % which higher than that of conventional methods. The tests show that the OSU_SVM approach is better than the conventional methods such as Fisher classifier, BP neural networks and LS-SVM.

Regression Testing is an extremely efficient technique used to ensure the quality of changed program. For feature-based systems, the traditional approaches rely on engineer’s empirical practice. Therefore, the regression scope will vary from person to person. To improve those unstable methods, the authors presented an algorithm which could automatically select the retest features. The method was based on the building of weighted features digraph and the calculation of dependence values. Meanwhile, the authors proposed some “selection rules” as criteria for these retested features. Besides, a tool “FeaNetwork” had been built to evaluate the performance of our algorithm, and the result was better than empirical methods.

Vehicle detector is the key technology of Intelligent Transportation System (ITS), and the data receiving and processing host is the important part of wireless vehicle detector. This essay focuses on developing the wireless vehicle detector data receiving and processing host system based on MPS430F1161 ultra-low power microcontroller and nRF905 wireless remote control module. The system is superior to the traditional ring type coil vehicle detection system on performance, real-time, cost, life circle, and maintenance and so on.

The feature extraction method of rolling bearing fault was presented based on the combination of wavelet packet-EMD (empirical mode decomposition) and kurtosis rule. Its first step is to reduce the signal noise by the wavelet packet, and then do EMD decomposition. Based on the characteristic that the kurtosis is very sensitive to impact the biggest IMF component of kurtosis is selected to do Hilbert envelope demodulation. As a result, the fault feature information of rolling bearing was obtained. The implementation process of this method was analyzed by simulation signal and the method was successfully applied in inner race of rolling bearing fault diagnosis.

In this paper we tend to investigate an optimal model through the application of three well known techniques of computational intelligence; neural net work, fuzzy logic and Support Vector Regression (SVR). An attempt has been made to get a stochastic model of the contact force of a robot with its environment. The model is provided by an identification process based on supervised learning. The utility of this model lies in a high quality perception and allowing us to implement an intelligent control of industrial tasks performed by a robot. The objective behind using the computational intelligence techniques is to improve the performance of the industrial robot’s tasks such as: welding, painting, pieces insertion, etc. The findings of the investigation have showed that the SVR is the most suitable technique for achieving a high accurate model.

In order to solve the difficulty of simulating the satellite signal with the complexity of the structure of hardware signal source and the variability of the environment, an IF signal model architecture is used in this paper. By producing navigation message and observational data with the mathematical simulation system offline, these data are modulated by the pseudo-random code and the IF carrier to produce the IF analog signal. Then the IF analog signal becomes the IF digital signal after further sampled and Quantify. The GPS IF signal is produced by the use of Matlab simulation and then is further located though the receiver. Simulation result shows that receiver positioning result is basically the same as observational data which is generated by the mathematical simulation system, proving that the scheme is of good reason. The IF signal model can effectively solve the disadvantage of hardware simulation equipment and thus a class of problems including High input and Low output which hardware simulation attributes are solved.

Nowadays, there are many mature image denoising methods, such as linear filtering and nonlinear filtering. In order to improve the denoising effect, a novel signal denoising method based on fractional wavelet transform (FRWT) is proposed in this paper. It combines the advantages of the fractional Fourier transform (FRFT) and the wavelet transforms (WT). By the simulation experiment, the optimal fractional order of FRWT is obtained with an iterative algorithm according to the PSNR of output signals. This method takes output peak signal to noise ratio (PSNR) and information entropy (IE) as the denoising evaluation index. The results of experiment show that the novel methods could effectively remove noise, and maintain information quantity maximally at the same time by adjusting the fractional order p and wavelet scale.

Proper representation of Role and Task in access control mechanism can be a solution for privacy invasion problem. In this paper, authors have designed the Role and Task based access control (RTBAC) model and developed the XML schema for representing the schema of the model. Basic conceptions and entities of RTBAC model include user, role, permission, privilege, task, dependency, application data, data object, and operation. The relationships among entities include user/role assignment (RU), role/privilege assignment (RP), task/role assignment (TR), and task/permission assignment (TP) etc. This model supports object privacy since it introduces a new constraint called Role and Task between subject and object. It supports more constraints on object’s policy than current Role-based Access Control Model does.

An immersive display system based on single projector and curved surface reflector is presented in this paper. In this system, the light illuminated by one projector is reflected by a curved surface reflector to a cylindrical rear projection screen. This system implements uniform enlargement of the projected image on both the horizontal and vertical direction and displays virtual scene of large continuous field of view. With the help of the curved surface reflector, the image distortion caused by curvature of the screen can be eliminated without using complicated image transformation algorithms. Additionally, seamless image can be obtained by using single projector. The projection experiment proves that this system can achieve satisfactory immersive display quality.

As an integral part of Computer Graphics, cloth simulation technology has been extensively applied in many fields, such as computer games, entertainments, film special effects and computer animation productions. The cloth simulation technology can realize efficient and vivid simulation as it draws upon the latest achievements in computer graphics, applied mathematics and engineering mechanics. In this paper, researchers adopt finite element method to simulate cloth simulation model, and make an in-depth discussion and study on self-adaptive time step and human body collision processing. Researchers have improved cloth simulation implicit integration method and proposed a collision detection algorithm based on human ring data, which achieved a faster and more realistic result.

Datasets in real world are often predominately composed of normal examples with only a small percentage of interesting or abnormal examples. A new approach is applied in this paper to address the imbalance problem by combining SVM ensembles and resampling method. Through empirical analysis, researchers cluster majority classes by k-means algorithm into subclass which decreases the imbalance ratio. Additionally, they use resampling method which concludes oversampling and undersampling techniques to deal with the problem of long training time and low training efficiency in SVM ensembles. Experimental results show that the SVM ensembles with resampling method outperform individual SVM classifiers. The proposed combination approach can effectively solve the imbalance problem.

As the coming of the big data age, there is a new hot spot on how to handle and process huge amounts of data. The MapReduce parallel computing framework is increasingly being used in large-scale data analysis. Although there have been many studies about the join operation in the traditional relational database, join algorithms in MapReduce are inefficient. In this paper, we describe a number of well-known join algorithms in MapReduce, and present an experimental comparison of these join algorithms based on Hadoop cluster. An optimization algorithm for map side chain is proposed.

The speed and quality of data preparation become one of the bottlenecks of the execution of large-scale simulation systems, which has not gained enough attention so far. The paper discusses the intrinsic characteristics of three types of simulation data, that is, relational data, hierarchical data and spatial data. It expounds the following three key technologies of data preparation for simulation systems. For efficient management of hierarchical data, XML is proposed and the XML-based component is developed for reuse. For seamless management of heterogeneous data, the three-tied architecture is put forward. To improve data quality, quality of simulation data is divided into applicability, effectiveness and validity, and the theoretical framework for quality assurance of data preparation for simulation systems is given. Research results are of great significance to improve the efficiency of data preparation for simulation systems.

Modern data centers provide good performance and many kinds of services accompanying considerable power consumption. Reducing power consumption becomes essential for decreasing the operating costs. Unlike conventional ways, authors propose the novel Suspend-to-PCM hibernation strategy to provide rapid suspending and resuming of the operating system (OS). Characterized by its low access latency and low energy consumption, Phase change memory (PCM) is a kind of non-volatile flash media. Strategy in the paper is to suspend OS from memory to PCM rather than disk, and vice versa for the resuming. Since PCM owns much better property of access speed and power utilization than traditional storage media, the Suspend-to-PCM strategy is able to achieve improved performance of system suspending and low power consumption.

How to choose an appropriate releasing strategy for site content, and which one caters to user’s habits, have become the main challenges. This article provides a provenance-aware model to design the content of the website. Based on the user’s browsing history data, it constructs timed automaton that can trace the provenance of the data to find what the user may be interested in, and it establishes a Markov chain model to determine the content of the link relationship. Experiments show this model not only meets the dynamic needs of users when they browses the site, but also gives certain options to the administrator of site content. It provides recommending result efficiently and should have a bright application prospect.

In order to solve the display problem with massive data atlas, researchers propose five kinds of visualization strategy to improve the display efficiency in this paper. By using the strategy of establishing the atlas map frame index, hierarchical visualization, real-time dynamic projection, double buffering + multi-threading data dynamic annotation, local cache based on spatial data mining visualization, researchers basically solve the problems existing in the process of multi-source heterogeneous mass data atlas display. The strategy has achieved on the MapGIS K9-based platform and successfully applied to the basis of the outcome of mapping system of the national fundamental geographic information center. Researchers found that the display strategy is significantly more efficient than traditional visualization strategy. Thus, the effectiveness and accuracy of the algorithm are verified.

The Internet topology can be analyzed from four different granularities. This paper aims at the Internet AS level topology. Firstly, it introduces some current related researches about this project, and summarizes the hierarchy structure of AS topology. Then it analyses the obtaining method of three possible data sources which are BGP route info, IRR data and traceroute probing data. According to the different characteristic of each data source, researchers list the advantages and disadvantages when using these data to build AS topology. Due to the excellence of BGP route info in node perfectibility and recognizing correctness, a new AS level topology build algorithm is put forward based on BGP route info, and fused with IRR data and traceroute data. Each step of algorithm is discussed in detail. To prove the algorithm validity, three types of real data were collected to build an AS topology in experiment. The node count and link count are calculated by each step, and the node degree distribution curves of our result are compared with related research, which show that our algorithm is effective in building a more comprehensive AS topology.

The early warning of saltwater intrusion is an important work for ensuring the drinking water supplies. To forecast and predict the daily maximum salinity for the water withdrawn for the waterworks located along the Qiantang River, the nonlinear autoregressive networks with exogenous inputs (NARX) model was applied. Since the multivariate time series of flow, the tide range, the salinities and the water levels observed at 8 gauging stations have great impact on the salt concentration in the river, this will bring in a large number of inputs when these variables directly fed into the NARX model and add unnecessary model complexity and poor performance. Therefore, the dynamic principal component analysis (DPCA) was used to reduce the data redundancy. Simulation predicted results show that the NARX model using DPCA can predict salinity in the river accurately, moreover, this method not only reduces the input dimension and over-fit the equation, but also enhances the model performance and the generalization ability considerably.

P2P video streaming over WMN includes different multimedia applications such as IPTV, video surveillance and video conferencing. It also introduces some challenges such as required level of QoS. Packet loss recovery methods can improve the experienced amount of QoS which leads to better video quality on peers. Although ARQ and FEC methods have been used in many video streaming applications, they are unable to provide enough level of QoS in P2P video streaming over WMN. Hybrid methods improve the performances of packet loss recovery schemes. But they do not carefully consider the characteristics of the source and the destination nodes, thus are not suitable for P2P video streaming over WMN. Therefore, in this study, an adaptive packet loss recovery method is proposed to select the loss recovery policy according to the source and the destination characteristics and loss probability of communication.

After the metal sheet forming, the strain change should be known through some ways in order to conduct the stress analysis of forming process. To achieve this goal, some special circle marks are imprinted on the sheet surface, and after forming, the deformed circle marks should be measured. The previous method uses a Vernier Caliper to manually measure the stretched rope, which is highly laborious and inaccurate. To overcome this disadvantage, a non-contacting method is adopted to achieve all the coordinates’ data based on the structure-light principle. Then the achieved coordinates’ data of spatial surface are fitted to be a CAD model through reverse engineering (RE). In RE, the CAD surface is unfolded to be a plane or two orthogonal lines are projected on the CAD surface, so the deformed circle marks—spatial ellipses could be measured in size completely at one time. The experiments prove that the measured accuracy is about 0.01 mm, higher than the previous manual one.

The software development workload is subject to such factors as field, staff, technique, environment and strategy. Thus it is difficult to measure the workload accurately, especially the measurement conducted by a third party after the completion of a project. With the gait characteristic database as a subject, this paper puts forwards a new post hoc evaluation model for workload by using workload algorithm model and expert review method based on full understanding of the system’s basic information. Practices have proven that this model increases evaluation flexibility and effects and corrects the subjective bias of experts. It is quite applicable to the post hoc evaluation of software development workload.

This paper focuses on shortening the mean time to acquire for initial cell search in the 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) system. Exact result of mean time of the cell search is obtained by use of a state transition diagram of discrete-time Markov process for the acquisition process. From the deduced mean time formula, it can be seen that the false alarm probability plays a more important role in the acquisition time performance. In order to perform the initial cell search quickly, a new PSS detection structure which includes a verification module to suppress the false alarm is developed. Simulations show that the new structure can decrease the false alarm probability, and reduce the total acquisition time especially in the low SNR circumstance.

In order to search out the useful resources about software maintainability requirement from the huge contents in the rapid development of Internet, an intelligent decision-making model in software maintainability design is used in this paper. By introducing the Agent technique, intelligent decision-making model can rationally evaluate the affections between all indexes to select the best design scheme. The model mainly consists of two steps: The first one is Data-Mining and building information warehouse about software maintainability analysis. The second one is reasoning based on cases and evaluates the maintainability index. Giving the task to main-Agent, the main Agent communicates with the sub-Agents and allocates the task to all of them. The precedent warehouse not only instructs Agent to cooperate with other Agents, but also supplies it with the datum of intelligent actions. The Agent technology applied in software maintainability design. It’s proved that it’s an effective way to evaluate the scheme of maintainability design.

Reliable video transmission is very challenging over wireless network. Efficient coding and transmission control techniques are required to meet the requirements of Qos. This paper designs the model of video transmission system based on WIFI, which achieves a real-time wireless video transmission system. The RTP encapsulation and real-time control methods of wireless video transmission based on H.264 encoding have been focused on. An adaptive control model of video transmission based on WIFI is presented in this paper. Experiment results shows that the proposed the adaptive control method of video transmission can gain good Qos so that the stability and good qualities of video transmission are ensured.

In order to improve the efficiency of taxi dispatching, we build a center-controlled, real-time management system. With the help of the real-time data collected by recorders in taxis and the wavelet neural network utilized to predict passenger current, the whole system can work more precisely. Besides, the exceptional situations are also taken into consideration in this system. Thus, the whole system is able to distribute taxis efficiently in any situation. Simulation results indicate that the wavelet neural network could make more accurate prediction than former methods and the self-adapting distribution strategy can increase load rate effectively.

Component interaction graph is used to describe the interrelation of components, which provides an objective basis and technology to test component composition. However, the traditional component interaction graph cannot serve as a basis to test a component itself and the state transition between components for lacking of description of states of individual component. Therefore, a novel model, named Contract-Based Combined Component Interaction Graph (CBCCIG) is put forward in this paper. CBCCIG combined the thought of contract test with the UML state diagram which is introduced in the paper. The proposed model can not only support the quick assembly of the software system depending on developer’s own willing, but also the automatic or semi-automatic generation of test cases which are the state transition and information interaction between components. Thus, CBCCIG improves the efficiency of development and testing.

D-S evidence theory is an important mathematical tool for uncertainty reasoning. However, it may lead to counterintuitive conclusions when combining conflicting evidences. In order to overcome this disadvantage, one can modify the evidences before Dempster’s rule of combination. One representative method is to assign a weight to each evidence according to its credibility degree based on the concept of distance (or similarity) between two evidences. This method can gain more robust fusion results than many other known methods. However, it may fail to correctly converge according to the cardinality of the sets in the evidence. When evidence conflicts with other evidences, the evidence may lose impact on the combination result. Moreover, the combined mass is nonmonotonic even though evidence varies monotonically. Therefore, the method still leads to counterintuitive or confusing results. This paper brings forward an improved weighted averaging method involving a new similarity measure between evidences and a new combination rule. The numerical examples show the proposed method well solves the above problems.

In order to help consumers adapt to electricity consumption in real-time electricity pricing environment, an energy consumption scheme is proposed in this paper. This scheme focuses on the prediction, modeling and optimization for family energy consumption. A method based on support-vector machine (SVM) is used to predict the real-time price (RTP) and the optimization model divides every hour into equal time slots and thus provides more opportunities to schedule household appliances in proper working time. Then the simulation results show that the proposed optimal control model reduces the daily electricity expenditures.

Nowadays, the electronic power industry is improving the level of information, and the data security of the internal network is arousing more and more attention. The domestic units and enterprises implemented relatively comprehensively. Most of them deployed firewall, intrusion detection and vulnerability scanning systems which allow them to reduce the risk of network boundaries greatly. However, as to the network terminal management within the network of the enterprise, the current risk prevention measures are far from enough because the internal network security issues come out easily. Combined with the extensive practical application of the electric power enterprise, this paper puts forward the secure desktop idea so as to solve the terminal security of the internal network computers. This measure can achieve the aim of a further control of the terminal security of the internal network computers. Thereby, it realizes a better controlled data security within the internal network and provides a good security network solution of the protection with the electric power business.

In order to make the fuzzy information more accurate, Vague Set is used to represent the fuzzy attribute of the database in this paper. Each data and tuple in the database based on Vague Set can be reflected from the three sides of true, false and the unknown extent. For illustration, a vague relationship instance teacher1 is utilized to show the basic theory of vague relation. Results show that if the database model based on Vague Set and the fuzzy relational data model are compared, the former has a more fuzzy ability to express. The further expansion of vague database model which is temporal database based on Vague Set is proposed. In order to better explain vague temporal data, a time dimension ‘duty period’ is added into table teacher1, which constitutes vague temporal relation teacher2. The study lays the foundation for the further research into data model, data theory, and database management system of vague temporal database.

In order to promote micro business and sell their products and services, a new proposed system by web mining technology is used to discover new regional investment project. Project information published on the government websites of Huaian, Jiangsu province is extracted to utilize the proposed method. Python language, MySQL database and Django web framework are used to develop the application system, and the multi-factor matching algorithm is provided to collect key information of the project name, time, address, contact, domain and URL by web mining. Furthermore, the location and statistics functions are accomplished in the proposed system which can meet application requirements of micro business.

Test case prioritization is a technique to schedule the test case in order to maximize some objective function. Early fault detection can provide a faster feedback generating a scope for debuggers to carry out their task at an early stage. In this paper, a method is proposed to prioritize the test cases for testing component dependency in a Component Based Software Development (CBSD) environment using Greedy Approach. The OIG (Object Interaction Graph) is traversed to calculate the total number of inter component object interactions and intra component object interactions. Depending upon the number of interactions, the objective function is calculated and the test cases are ordered accordingly. This technique is applied to the components developed in Java for a software system and found to be very effective in early fault detection as compared with non-prioritize approach.

Nowadays, with the development of multi-core and cloud computing technology, the deployment of virtual machine faces opportunities as well as challenges in the process of virtualization. However, most virtualization deployment only considers the concept of combining single vCPUs with multi-core CPU. Aiming at solving those known problems based on experience, this paper proposes a new method of deployment of virtual machine in a decomposed way. The result shows that optimized method is more reasonable for resource allocation. It can provide a good principle to expand future datacenter virtualization.

The paper aims to solve the repeated work problem existing in multi-platform widget development and supply a widget development environment which can support for cross-platform development or cross-standards development. A widget development framework called Model-driven Widget Development Framework (MWDF) is proposed. By using MDA, the MWDF can make developer get a visual programming and model driven development environment, and the generated widget can be deployed on many platforms supported by MWDF. For illustration, the architecture of MWDF and implementation of model driven development module are shown to describe the framework. MWDF abstracts the implement in widget development which saves a lot of time for the developer and increases the expandability of the widget.

The existing fire protection safety management systems are difficult to expect an efficient rescue, because the rescuers cannot confirm the status information of evacuees. They just provide fire and evacuation information. Therefore, this paper suggests a vision based real-time fire evacuees’ state information verification system through inputted images from CCTV in the building.

In order to guarantee the effective communication mode under any circumstances in nuclear power plants, Mobile Ad Hoc network will be introduced to achieve the goal. In this paper, a detecting algorithm is provided to study unidirectional links. With the emulation experiment which results in the occurrence rate of both unidirectional and bidirectional links, analyses of unidirectional links which originates from diversity in transmission power and signal interference is presented, hoping that it will provide assistance in routing protocol of Mobile Ad Hoc Network.

Motion Detection is a fundamental problem in visual surveillance systems, and is especially challenging in dynamic scenes. Temporal difference methods are not robust for dynamic regions, and nonparametric models have preferable results. But nonparametric models have high computational and memory resource requirements. In this paper, a real-time motion detection approach is proposed based on joint space and color model in dynamic regions. Firstly, a simple temporal difference is used in the whole scene. And then nonparametric model is used to reconfirm the motion occurrence in dynamic scene regions with jumping changes. The joint space and color model is built in the variable region of the surveillance scene in order to improve the adaption of dynamic outdoor environment. Experimental results show that the computational complexity and memory requirement of the proposed method are largely reduced, whereas it greatly decreases fault rates in comparison with the temporal difference and achieves the comparable detection accuracy to the original nonparametric model.

The historical traffic data is in fact capable of proving abundant of information that can aid in the development of improved current traffic control. Time-of-day (TOD) control system is the most widely used one in the world with the limited funding and system maturity, so it is important to use data mining tools that demonstrate the value of traffic data to enhance the performance of TOD systems. Kohonen cluster approach is very useful for determining TOD break points for better traffic signal control within unsupervised neural network. A case study using an intersection corridor was conducted to identify TOD break points to support the design of signal timing plan by using kohonen cluster. The results of this research indicate that the proposed method can identify TOD break points successfully without deploying multiple signal timing plans on the basis of the subjective judgment.

Botnet Emulation is an emerging method to research on Botnet which is attracting widespread attention. It is referred to build a closed Botnet with virtualization technology to do analysis on Botnet. Although superior to other traditional methods for its flexibility, reproducibility, validity as well as lawfulness, Botnet Emulation is facing challenges from security, transparency, scale and so on. In this paper, we shed light on some of the key challenges in building Botnet Emulation systems. Furthermore, we discuss various techniques used to address or alleviate these problems, along with the pros and cons of each technique. We hope to motivate future research in this area to develop practical solutions to these challenges.

In order to solve the problems in the process of artificial scheduling for taxis, which include expensive labor cost, limited service time and concurrency, a new self-help taxi service schema is proposed. The schema is composed of mobile phone, intelligent server and taxis equipped with GPS. Based on the schema we designed a new system for summoning and scheduling taxis. In the system, three ways, including searching, GPS, electronic map, are available for passengers to locate themselves using mobile phones. And on the server side, we introduced Geographic Information System (GIS) and adopted the ant colony algorithm based on taxi drivers’ driving habits. As a result, passengers can get their locations easily with almost all kinds of mobile phones, and the server can identify passengers’ requests by itself and give a consistent route with the one adopted by taxi drivers. Finally, the system has the advantages of wide applicable scope, low labor cost, and large concurrency.

Due to the deficiency of the social relationship in many synthetic models such as RPGM and RWP in ad hoc network simulations, a new mobility model based on the interest indicator is proposed in this paper. By analyzing the moving gathering relationship among individuals, the authors propose the concept of interest indicator as well as the interest distance and then further propose a social interest indicator based mobility model for ad hoc network. Simulation result shows that the proposed model is more realistic than RPGM and RWP and the authors also analyze the influence of the model on DSDV and AODV. This proposed model can be used in circumstances such as exhibition, party and battle.

The Multiple-Plane and Multiple-Stage packet switching fabric is one of novel scalable switching technologies in Internet and new generation of information network. As lack of theoretical basis, many important MPMS technical problems were still not resolved currently. In this paper, researchers studied the universal topology and the logical mapping graph. Based on the directed graph theory, the directed graph model (DGM) and probability model of the MPMS packet switching fabric are provided. The primary theoretical basis is built for MPMS fabric. Simulation experiments show that the probabilities of the proposed probability model are quite stable with a deviation less than 2 %, which is much better than present results.

In order to compensate for the scarcity of currently available early rehabilitation training means of spinal cord injury (SCI) patients, a method of early spinal cord injury rehabilitation training based on virtual reality and robot is pointed out through analysis of nervous system plasticity of patients. A rehabilitation robot system with eight degrees of freedom (DOF) is established, which is based on a six DOF parallel platform. A virtual reality training scene is built. The hardware and software environment of rehabilitation training is studied, meanwhile the match among the virtual reality scene, robot and muscle training in patients is completed. And then, the relevant training mode is formulated. Finally, the implementation of rehabilitation training program is designed. As a result, a new rehabilitation training method for early patients with SCI is formed.

Spatial relations are the main part of geographical information in natural language. Their extraction and semantic interpretation play a significant role in bridging the gap between geographical information system and natural language. Normally spatial relations are described with certain spatial terms and syntactic rules in natural language. To overcome the disadvantage of manual induction of syntactic rules, this paper proposes a new machine learning approach based on a sequence alignment algorithm. Firstly, the description instances of spatial relations in a large-scale annotated corpus are extracted and analyzed, and the sequence alignment algorithm is used to calculate the pattern similarity between instances of spatial relations. Then, the instances with high similarity are generalized aspopularly used syntactic rules. Finally, these rules are used for extraction spatial relations in a test data to evaluate their validation. The experimental results indicate that the generalized rules can achieve better performance than those rules induced according to occurrence frequency in the corpus.

Cosine similarity measure is an efficient plagiarism detection algorithm for documents. However, it may be misled if the document is not properly preprocessed. Furthermore, the weight for the words in the document should depend on its occurrence frequency in the whole digital library. Otherwise, cosine similarity measure may not accurate enough. This paper aims to enhance the accuracy of similarity measure. A preprocessing method and a model to adjust word’s weight according to occurrence frequency are proposed in this paper. The paper also develops a sample to illustrate how to preprocess documents, adjust the weight for the words and calculate the similarity. The sample shows that it gets better result after applying the model in this paper.

With the acceleration in the construction of TaiShan Nuclear Power Plant, there is also a dramatic increase in related application systems, server and storage amount. The traditional I/O framework can no longer meet the needs and it frequently encounters such problems as the severe shortage of servers integrated after virtualization, restrictions in Virtual Manufacturing (VM) performance, etc., which are the disadvantages of the stable operation of the production system. Therefore, the I/O virtualization framework is based on cloud delivery concept emerges, with simple and explicit topology, convenient deploy, bandwidth on demand, high utilization rate and QoS guarantee. It can also boost the transmission speed of data drastically and guarantee the stability in the operation of the nuclear power production system.

Three-dimensional (3-D) virtual reality has proved to be an effective and efficient training tool to impart plant knowledge. In order to enhance users’ understandings of the nuclear reactor principles, a virtual reality system based on simulator has been developed to interface with the scenarios in nuclear power plant (NPP). Physical characteristics are calculated by simulation codes, such as pressure, temperature, flow and void. The simulator transmits physical characteristics to virtual reality system for three dimension dynamic visualization of these parameters. It is useful to help analyzers understand the conditions of nuclear power plant. This paper introduces the basic concept, framework of the virtual reality system and its functions.

New storage-class memory (SCM) technologies, such as phase-change memory, are fast, non-volatile and byte-addressable. SCM provides a new realm for researchers to boost the performance of system. But most of SCM devices are not available on the market, which hindered further software research on leveraging the full feature of SCM. In this paper we design and implement a SCM device simulator on BOCHS named SCM-BSIM. SCM-BSIM can mimic full feature of SCM such as non-volatility and different access latency. Also it will gather life span statistics during simulation to support endurance relevant research. With a BOCHS-based interface, SCM-BSIM is easy to use.

According to the life cycle of technological alliance, a three-stage model about energy efficiency of horizontal technological alliance is presented in this paper. The influence of cooperative technology innovation on technological alliance and the influence of operation mode of technological alliance on its energy efficiency are discussed. The necessary conditions of improving energy efficiency of technological alliance are proved by researching the relation between energy efficiency of enterprise member and energy efficiency of technological alliance. And here are the conclusions: the ratio between differences of income and differences of cost, the operation mode of technological alliance are important factors for improving the member’s energy efficiency. Energy efficiency of technological alliance decreases when member’s ratio between income increment and cost increment is lower than energy efficiency of other members set. The result of it can be applied to establish technological alliance of industrial groups in China.

Most of Mobile Social Network (MSN) sites may go through a process from emergence to disappearance, and have their own life-cycle in the market. To evaluate the life-cycle of MSN, a life-cycle model with four growth stages for MSN was proposed on the basis of BCG-like matrix in this article. Instead of employing the traditional market shares and growth rates, model in this paper is innovative for consulting two parameters which can be easily and rapidly derived from MSN user behavior pattern. Therefore, it provides a simple but effective way to identify which life-cycle stage an MSN could be, and helps choose prospective market stars for commercial purpose. Based on real click-stream data set collected from a Mobile Telecom Carrier in Chongqing, the authors evaluate the model and show the performance analyses.

Based on improved Griliches-Jaffe knowledge production function, this paper analyzes the effect of government regulation on environmental innovation by employing a panel dataset that covers 30 Chinese provinces from 1998 to 2006. We find that the regulation pressure (as measured by the investment in the treatment of industrial pollution) has significant and positive impact on environmental innovation (as measured by environmental patent applications) at the national level. We also find that there are distinct regional disparities between effects of environmental regulation on innovation. Only the regulation pressure in eastern China has positive and statistically significant impact on environmental innovation, while the regulation pressure in western and central China has insignificant effect on environmental innovation. More importantly, we show that the regional innovation conditions such as innovation input, export pressure, economic growth rate, and educational expenditure share are more important factors to affect environmental innovation than environmental regulation.

The effective implementation of the organizational innovation path is the key element to promote the enterprise performance value. But how to locate the accurate path for organizational innovation within innovative-oriented enterprises is the urgent issue. This paper is based on the effect elements of the innovative-oriented enterprises organizational innovation path formation period; it constructs the theoretical model of the effect elements impact on the formation of the innovative-oriented enterprises organizational innovation path. And then it uses the partial least squares structure equation model (PLS-SEM) method to verify the model path and hypothesis. The research can fulfill the organizational innovation theories and provide the guidance for the enterprise to precede the organizational innovation path activities.

The analysis based on neoclassical growth theories shows that calculations of Contribution Rate of S&T Progress on China provincial economy growth could not provide exact explanation on economic effect of S&T progress. This study established a new growth accounting model based on endogenous growth theory with output of GDP and inputs of capital, labor, human capital and S&T progress. Empirical study based on panel data shows that this method can get better understanding on practical contribution of S&T progress on China’s provincial economy growth.

Enterprise alliance network is considered to have scale-free property. This paper aims to study the correlation between scale-free property and enterprise innovation performance. Networks of alliances in automobile industry are constructed, and then researchers utilize Maximum Likelihood Estimation and KS-test to calculate the p value of the network’s scale-free property. Negative binomial regression model is used to analyze the relevance between enterprise innovative performance and the scale-free property of alliance network, with patents number that firms have applied as the indicator of firms’ innovative performance. Experiment result shows that scale-free attribute of enterprise alliance network has quite a significant positive effect upon enterprise innovative performance.

Sustainable innovation is very important for innovation enterprise’s development and also difficult to obtain for the risk which is complex and changeful, especially in strategic transformation period. In order to help the innovation enterprise get deeper understanding about dynamic changeable significant risks in the process of enterprise sustainable innovation, this paper constructs innovative enterprise’s sustainable innovation strategic transition process model process model, analyzes the main factors of significant risks during the strategic process of innovative enterprise and summarizes the significant risks of innovative enterprise into three categories—innovation strategic risk, manager risk and major innovation projects risk. By dividing the stages of strategic management into strategic analysis phase, strategic selection phase and strategic implementation phase, the paper analyzes the significant risk of innovative enterprise, and reveals the dynamic variation regulation of the three significant risks during the strategic transformation period.

This paper provided a model framework to differentiate industry clustering. Based on CD production function with external science and technology progress efficiency, the study investigated geographical concentration of production factors and increasing return to scale in High-tech Zones in China. Result shows that there is industry clustering in the zones. However, the returns to scale of industry clusters differ greatly between the zones.

In order to evaluate person-job fit on knowledge workers effectively, an evaluation method integrating analytic hierarchy process and BP neural network are proposed in this paper. The method is to get the evaluation results by calculating weighted sums of the evaluation results based on analytic hierarchy process and the evaluation results based on the trained BP neural network. A case is applied to demonstrate the method by MATLAB. The results show that the method can effectively evaluate person-job fit on knowledge workers. The method has the advantages of both analytic hierarchy process and BP neural network.

The paper aims to improve the chaotic situation of human resource management within Chinese enterprises, especially some family business and state-owned enterprises, and to optimize their internal human resource structures to maximize the staff value. The paper introduces the ITM human resource management theory, for an integrated and systematic human resource management research of Chinese enterprises. Based on the ITM human resources information needs analysis, the writer specifically introduces the concrete application of ITM in Chinese enterprises taking example of W company, and reveals that ITM will improve the structure of human resources and improve the resource efficiency to achieve the maximized human capital value of the whole enterprises.

With an increasing gap among current incomes, the Chinese sci-tech personnel’s income satisfaction does not just depend on the income itself. By controlling some demographic variants such as gender, age, work seniority, etc., this study conducted a thorough analysis of the influence of some factors on the income satisfaction via optimal scaling regression and some other regression methods. The influencing factors include the income itself, the income gap, and the allocation system and so on. It was found that the inter-industry income gap, to which the income satisfaction is majorly attributed, can more easily cause discontent among the sci-tech personnel than the income itself. The allocation system can exert stronger influence on the income satisfaction among the sci-tech personnel than the intra-regional income gap, yet not as strong as that caused by inter-industry income disparity.

Virtual Academic Community, as a type of Learning Community, features on the exchange of academic-related ideas, experience, documents, comments and feedbacks. Although there is a growing interest in Learning Community and Virtual Communities of Practice, few studies have examined the influencing factors of knowledge sharing in Virtual Academic Community from an integrated viewpoint including personal and cultural perspectives. This paper conducts a survey study on the influencing factors of college students’ knowledge sharing willingness in Virtual Academic Community. The results indicate that self-efficacy, personal outcome expectation, guanxi and gaining face have positive effects on knowledge sharing willingness. Additionally, self-efficacy has a positive effect on community-related outcome expectation. Finally, research limitations are drawn and discussed.

For avoiding the waste of entrepreneurship resources and resolving the problem of lacking pertinence in entrepreneurship education, as well as to realize the value of the limited resources to the greatest degree, fifty students who have established their own enterprises are surveyed with questionnaires to find the eighteen main factors influencing the entrepreneurship. Taking the correlation between these factors into account, the principal component analysis method was applied and five main components representing the different indicators characteristics of entrepreneurs were filtered out. Finally the score model in college student entrepreneurship can be constructed. Through this model, entrepreneurial aspirations of college students and the groups with higher scores can be obtained, which can improve the pertinence of entrepreneurship education. Therefore, this model provides a reasonable basis for the effective delivery of entrepreneurship education resources.

It is difficult for students who major in economics and management to learn object-oriented approach based on Unified Modeling Language (UML) in Management Information Systems (MIS) curriculum. To solve this problem, four methods about how to teach this approach are offered to teachers as follows. Summarizing consistency rules helps students to understand logical relationships between UML diagrams. Defining the core of UML helps students to grasp emphases. Designing creative experiments helps students to understand concepts and notations of UML deeply. With the help of specific program codes, abstract UML diagrams can be explained for students more clearly. These methods are proved to be effective to teach this approach in MIS curriculum.

The materials are the basis of the nuclear power plant construction. Effective nuclear power engineering material management can accelerate the construction and reduce project cost of the nuclear power plant. In order to put the design of the source data into engineering material management, regulate the process of material procurement management and provide material procurement data and design drawings data in real-time for site management, this paper proposed the solution of the engineering material EPC (engineering, procurement, construction) based on VPRM system and SAP system and finally realized it. This solution also solved the main problems existing in engineering material management business of the nuclear power plant construction, and meets the meticulous management concept at the same time.

As today’s society is experiencing a rapid progress, it is far more important for customers to pursue better service than other factors like price, taste, etc. at the same premise. So it is obvious that the establishment of customer service system is a top priority for any company. And enhancing the quality of service for each customer is a crucial segment because it will directly affect the finance situation of any company. Thus, it is quite necessary to set up an effective customer service system for enterprises under the help of continuous improvement and development of social and economic system. The focus of this paper is how to improve the quality of customer service on the base of working experience in the Large Enterprise Group and the current trend of modern society.

With the purpose of solving the lack of real-time monitoring of nuclear power business problem and controlling the resources operational state, four layer model of monitoring system is designed. In accordance with the computer room, system equipment, safety equipment, network equipment, application system of specialization, it realizes the centralized monitoring and integrated display of the dependent elements of nuclear power station service system. The design and application of the monitoring system can provide a lot of equipment monitoring and operation monitoring index. Aiming to greatly improve the fault timely discovery rate and running trend and to predict the hazard events, this paper includes focus on the improvement of reliability and serviceability of monitoring center and provides an all-around centralized control mode for the future of monitoring center of electric power companies.

In the information environment, resources of communication equipment become increasingly varied and complex. Except for common information management systems, equipment resources can be organized in connection. Equipment resources can form a work order. The work order has at least one object and can be broken down into smaller ones. So the work order can be separated into large numbers of subtasks in order to form hierarchical structure. The Management System is designed to break down these tasks and assign its task nodes. As a result of decomposition, all equipment resources can be managed by this system.

In order to analyze the influence of institutional factors on listed company’s equity financing preference, this paper collects the data of manufacturing companies during 2003–2010 in China’s A-share market, which has begun to take shape after several years of rapid development. The paper mainly analyzes the role of control properties, equity structure and price earnings ratio in the company’s financing preference. The statistical regression results show that different control property will result in different financing preferences of the listed companies. And only equity structure and price earnings ratio are combined with control property. They would play a role in company’s financial structure. It argues that this is mainly because of the main body of the listed company is restructured state-owned enterprises, which are controlled by state capital. So the choice of financing mode reflects the will of the managers. This paper provides important reference to the whole stock market and capital market.

The paper aims to research positive feedback trading behaviour and its effect on the market fluctuations in Chinese stock market, and the relation between the level of market fluctuations and autocorrelation coefficient of market yields. It uses the data of daily close price of Shenzhen Component from August 22, 1996 to May 16, 2012 and finds severe boom and slump in Shenzhen stock market, notable non-normal distribution and ARCH effect. By combining the positive feedback trading model and EGARCH Model, the ARCH Regression result suggests: (1) there exists positive feedback traders in Chinese stock market who makes market returns fluctuate severely; (2) the relation is negative between the market fluctuation and autocorrelation coefficient of market yields; (3) the asymmetry and leverage effect will make Chinese stock market have greater fluctuation during descendant periods than rising periods.

This study investigates the impact of asymmetry foreign exchange risk on listed commercial banks and makes a comparative analysis on differences of foreign exchange rate exposure between introducing asymmetry and not introducing. Firstly, foreign exchange rate exposure of single bank is studied by GARCH model. Moreover, using unbalanced panel model to study the entire banking which includes both the exchange rate variable and the market variable. Empirical results indicate that listed commercial banks and the whole banking industry show different exchange rate exposure, while facing different exchange rate changes. For both single banks and the whole banking, the exchange rate exposure becomes more significant after asymmetry is considered. Exchange rate exposure can be described more accurately after considering asymmetry.

Foreign trade contains business flow activities and logistics flow activities. With rapid e-commerce growth, the impact of logistics on foreign trade is increasing. As the infrastructure of logistics, the importance of highway is self-evident. Based on Heilongjiang’s highway construction and foreign trade situation, the paper used the method of multiple regression analysis and analyzed the impact of highway construction on foreign trade in Heilongjiang and discussed the highway construction direction in Heilongjiang under the premise of enhancing the level of foreign trade, according to the analysis of paper, highway has a very important influence on total volume of imports and exports.

Judging by the fact that the forest product information features strong timeliness and other characteristics, the integration of existing e-commerce system has become the key to the development of forest product processing industry. In this paper, SOA employed to reorganize the existing resources in the manner of services. And loosely coupled architecture will be designed so as to tackle with the problems occurring in the forest product processing e-commerce system.

This study examines and compares multiple global enterprise operations in China. Business ownership arrangement, business products and services, and IT support for those agreements and products are considered. Findings indicate business ownership as a moderator impacts the relationship between business processes and IT support choices. All global enterprises in the study were found to use the SAP enterprise software for their transaction processing and reporting. Furthermore, enterprises also use proprietary software in the creation or delivery of their primary product or service. Wholly-owned businesses are more likely to use proprietary software for their key businesses or specialty.

Ensuring effective business/IT alignment is considered a critical task for the contemporary IT managers. One of the ways to achieve better results is to use a service-based approach. However, existing methods such as ITIL or Enterprise Architecture frameworks are very extensive and broadly oriented. General lack of appropriate methods and tools limits the use of the approach among organizations. This paper presents a service-based IT management model named SPSPR which represents a lightweight solution suitable for a variety industries and business segments including the small and medium-sized enterprises. The main goal of the proposed model is to assist with aligning business and the IT within the whole organization, and to enable effective IT support of business processes using ICT services. This paper describes a view on outsourcing areas and on their relation to the presented SPSPR model. Within the analysis, it maps these areas onto specific layers and thus supports the potential use of the SPSPR model within organizations that decide to utilize outsourcing in any of its available forms.

In order to gain new insights into the determinants of behavioral intention to use LIS, this paper proposes a theoretical model that augments the technology acceptance model (TAM) with three new constructs: trust, flow experience and social influence. The paper examines issues related to behavioral intention to use LIS from the viewpoint of customers. Also within the model framework, the paper investigates the effect of behavioral attitude on behavioral intention. To test the model, structural equation modeling is employed to analyze data collected from 248 respondents in Korea. Empirical results show that consumer’s attitude in LISs’ use is determined by technology and social factors. There is also a significant impact of customer’s attitude on customer’s intention. This research provides a theoretical foundation for academics and also practical guidelines for logistics service providers in dealing with LIS aspects.

In order to measure the degree and trend of gender segregation in Chinese industry, the paper uses five occupational segregation measure methods, D index, Ds index, Ip index, Square Root index and A index, to measure Chinese urban units’ industry gender segregation from 2000 to 2010, and to obtain gender segregation index of Chinese urban units industry. Studies have shown that Chinese industry gender segregation degree is far below the world average, gender segregation of Chinese industries is on the rise, and is becoming larger. The industries of the highest gender segregation in China are construction, manufacturing, education, public management and social organization, sanitation, social security and social welfare. The lowest industries are information transfer, computer and software, resident services and other services, culture, sports and entertainment, agriculture, forestry, farming of animals and fishery. It shows that gender segregation is more easily formed in the gender-dominated industry.

Detecting real time corporate merger and acquisition information from publicly available text data and feeding it to the decision-making module are essential for an applicable e-business management system. There are plenty of machine learning algorithms in text categorization and information extraction to address the problem, requiring different feature selection methods. Among them, linguistic features are key issues to accomplish this task. The acquisition of IBM’s PC division by Lenovo in 2004 was chosen as a case, and news reports of this event were gathered from the Internet to build a Corporate Merger and Acquisition (M&A) mini-corpus. Comparing the M&A corpus with larger general corpora, we constructed a feature word list by applying Term Frequency and Inverse Document Frequency strategies and augmented it by introduction of the word groups from thesauri. Typical patterns, which highlighted the event of M&A, were collected by employing regular expression matching on these words acquired in the former step. By means of the accumulated language resources, the precision and recall for predicting the amount of the M&A in Chinese and English texts are 61.76 %, 65.22 % and 84 %, 71.43 % respectively.

Based on the theory of ecology, enterprise is viewed as life entity in the social environment. What enterprise bionics concern most is how to measure the vitality of those enterprises. This article modifies the original index system based on the theory of enterprise bionics, and chooses the real estate industry to do the empirical research. Analyzing enterprises’ business age is a warning to those enterprises whose vitality is weak. From the comparison of enterprises’ business age and nature age, this article has found that the business age of some enterprises like Vanke, Shenzhen special Economic Zong Real Estate, AVIC and Gemdale are between 30 and 40, and those enterprises’ life vitality is strong and competitive; but some enterprises’ business age like RongAn, DingLi Technology and Yihua are between 60 and 70, which means those enterprises’ life vitality is weak and not competitive. The warning is serious.

An obvious seasonality appears in customer demand of many industries. It can have a repetition period from a month to a year. In this paper, researchers use a hybrid learning method to improve sales forecast and supply chain management. This hybrid method combines Stable Seasonal Pattern (SSP) and Support Vector Regression (SVR) analysis. It provides a flexible approach which gives accurate forecast for budget and manufacture planning of companies.

To establish effective and efficient project management practices, the capability maturity model integrated (CMMI) is being developed to help companies improve project management. A CMMI model for small and medium scale software companies is established in this paper. The main stages of CMMI establishment are shown specifically. Both advantages and disadvantages are introduced. And then this model applies to Victory Soft Corporation, as an example. This model provides a reference template for Chinese small and medium scale software companies who are seeking appropriate software development project management model.

Several conference proceedings have been infiltrated by fake submissions generated by the SCIgen computer program. Due to the fictional content the chapter “Refining the Producer–Consumer Problem and Lamport Clocks” by “Yanchun Ma” has been retracted by the publisher. Measures are being taken to avoid similar breaches in the future.

Traditional risk assessment method for elevator in use only focuses on objective factor, but many accidents in elevator are caused by subjective factors. This paper proposed an risk assessment method focusing on all the subjective and objective factors such as the design, manufacture, installation, maintenance, use, inspection elements, an weighted coefficient for considering the influence of different elements to the risk has been obtained by using the statistical experts opinions, then the risk level of the analyzed elevator can be obtained with the expert system, some suggestions are given according to the risk assessment results for improving the safety level of elevator in use. An example is given to illustrate how the proposed system is applied.

In order to make the user-level service composition feasible, a real-time service integration based on Business Process Execution Language (BPEL) is put forward, which could execute a BPEL process by user’s selection. By designing a system structure of real-time service integration based on BPEL, the difficulty waiting to figure out is summarized as the one-off recipient and keeping the business logic order unchanged. For illustration, the authors propose solutions on three aspects as message dependency, converting directed acyclic graph to workflow and the implicit message dependency. The results show that achieving one-off recipient should be accompanied by automatic processing all the data items entry inputting and listing the relevant recipients, together with real-time returning to the client after all the processes were completed. And if there is no data dependency between the processes selected, it should take the principle of parallel processing to reduce the overall process cycle; otherwise, it should be executed in order.

With the increasing consumer demand of online shopping, the necessity and significance of research on city logistics network are implicated. In this study, a model is developed to describe urban distribution network problem and minimize the costs of network logistics construction. Based on the order needs and distribution service level people proposed, the urban distribution system model is built, with taking consideration of the order density and distribution station service radius. The principle of the genetic algorithm combined with taboo search algorithm is described and proposed to find the solution to the model. The results of calculation indicate that the distribution system developed in this study is more economical and effective than the original one, and the validity of the proposed methods is demonstrated.

In order to study the evolution process of agri-products supply chain system of “company & farmer”, a self-organization dynamic model is established on the basis of block growth model. Then the research analyzes the stability of the model and simulates the evolutionary process. The results show that cooperative and competitive effects have a close relationship with the system evolution directions. The system can be optimized by magnifying the cooperative effects. The farmer, as the initial smaller side in the system, will be going to die when the cooperative effect is negative. So in order to protect the farmers’ interests, it is necessary for the government to encourage the organization of the farmers to amplify their scale.

In order to improve efficiency, meet diversified demands of stores; satisfy customers and perfect distribution activities, performance evaluation of distribution in the distribution center of chain supermarket is conducted. Firstly, the key factors which affect the performance of distribution center of chain supermarket are analyzed and evaluation indexes system is established in the paper. Then the index weights are determined by Analytic Hierarchical Model (AHM) and comprehensive evaluation is conducted with the help of unascertained measure theory. Finally, the method which is a probe into performance evolution of distribution center, has been proved applicable and reasonable with the example.

China, as a big clothing consumer and producer in the world, has made great progress in clothing field in the past several decades. However, Chinese clothing supply chain management is still at a low level. Because of several characteristics such as strong seasonal difference and fast changes in consumer demand, clothing industry needs a high efficient supply chain to satisfy these changes in demand. Radio-Frequency Identification (RFID) technology can provide technical support for this efficient supply chain. Radio-Frequency Identification (RFID) technology is a wireless automatic identification technology that uses radio-frequency electromagnetic fields to transfer data between a RFID tag and its reader without any contact. Applying RFID technology in clothing supply chain can not only improve its efficiency, but also achieve the goal of real-time tracking products and solve many tough problems. In this paper, a practical RFID system application in Chinese clothing supply chain is provided, including the application framework, selection of RFID tags and configuration of RFID system.