New Trends in Networking, Computing, E-learning, Systems Sciences, and Engineering

This paper presents two systems and knowledge modelling techniques that may be used as a tool to coordinate the communication between researchers and users from the agriculture problem domain. The paper is focused on th eusage of a general approach UML (Unified Modelling Language) and an innovative approach BORM-II (Bussiness Object Relation Modelling, second generation) as communication standards within research projects. The first part of this paper describes the framework, laying out the main aspects of both notations, metamodel and theoretical background as well as their advantages and disadvantages. The paper analyses practical examples from agriculture, rural and organization modelling domains. These innovation processes in both approaches are aplied on the same business process description and evaluates the impact on researchers and users of research. The main part is focused on the transformation model to model based on BORM-II. The transformation is in line with UML and SBVR (Semantics of Business Vocabulary and Rules) standards from OMG (Object Management Group). My predecessor worked on model transformation BORM to UML. This work follows Petr Šplíchals work and goes further. This transformation will be composed into a modelling tool and will be based on approach HOT (High Order Transformation). The objective of this research is to achieve documentation output like SBVR, and bridge the gap between business people (users) and designers (researchers) of information systems (IS). The paper concludes that the gap between IS designers (software engineers) and domain experts can be bridged by automated transformation of previously mentioned models. The main goal is to achieve a documentation output similar to SBVR, and ICT Accessibility for business people.

In the realm of mobile applications a significant effort has been made to develop recommender systems that customize results based off of one’s current location and more recently even their inferred current activity. While this aspect of context has been shown to be quite successful, we suggest anticipating what they are currently planning for the future may help further improve the relevancy of the results as well. This work examines this problem as one of trying to predict the user’s planning context, defined as what activities are currently being planned and how far in the future the event they are planning is going to be. An empirical analysis is made of the predictability of planning context and a discussion of the potential implications of this for mobile context aware recommenders.

The paper highlights the issue of the Trade-off between Software Deliverability and Complexity. It uses the technique of Messy Algorithm to generate chromosomes containing Fuzzy rules derived under various combinations. The proposed system makes the combination of Complexity and Deliverability more transparent and interoperable.

In this paper, we present a reactive vision based autonomous behavior on a humanoid robot. This perception action scheme enables the robot to walk toward a desired position or to track a given target and grasp it.

The proposed solution uses visual servoing as a reactive sensor based technique to address the problem of perception, thus to ensure reachability of the target object by generating appropriate motion commands. An omnidirectional velocity tracking gait generator is considered to solve the locomotion and balance problem. It is based on the framework developed by Herdt et al. (Advanced Robotics 24(5–6): 719–737, 2010;

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

, pp. 190–195, 2010), which has been extended for instantaneous rotational velocity in this work. The redundancy problem due to the high number of degrees of freedom associated with the mobility in operational space is handled by a task sequencing technique. This allows the improvement of reachability and manipulability while accounting for joints limits and obstacles avoidance. Finally, simulations on the humanoid robot NAO are shown to evaluate the effectiveness of the proposed scheme.

This paper presents a method for identifying and classifying agents. Likewise, it also shows a method for identifying entities and attributes based on the definition of the KAOS goal model. The starting point is the specification of software requirements expressed in Spanish. The works presented in the literature fail to identify the traceability that should exist between the natural language and the components of the KAOS goal diagram. The method proposed in this paper makes it possible to achieve the consistency that should exist between natural language and the components (entities with attributes and agents) of the KAOS goal diagram. In other words, said method guarantees coherence between the elements that are being modeled and the natural language. This process serves as a starting point for: (i) identifying the other components of the KAOS goal diagram, and (ii) automatically creating said diagram.

Antivirus software programs use specific techniques to detect computer viruses, malware and other network threats. The basic, most common and oldest antivirus detection technique is “virus signature scanning”, whereby antivirus programs use unique byte sequences for each virus so as to identify potential presence of malicious code in each file investigation procedure. Despite its advantages, this technique has many weaknesses that are highlighted in this paper. In lieu, this paper proposes a new hybrid security model for optimized protection and better virus detection, which merges the “Sandboxing Method”, “System-Changes-based Signatures” and “Cloud Computing”.

RSS (Rich Site Summary)/News Reader is a web-based Android OS application developed by using PhoneGap framework. HTML5, CSS and JavaScript are basically used for implementation, instead of native Android programming language. This application has a production process like a web application because it is actually a fully working web program which is wrapped by PhoneGap framework. This means the application could be used on almost every mobile platform with making some basic arrangements.

RSS/News Reader mobile application takes advantage of both flexibility of web design and built-in features of the device it is installed. This combination provides a complete mobile application which eliminates the need to use different native languages with its hybrid form. This hybrid structure makes mobile programming faster and easier to implement.

In this new generation operating system-based mobile application, a combination of PhoneGap framework, HTML5, CSS3, JavaScript, jQuery Mobile, Python and Django is used for implementation.

When faced with emergency situations there might be several critical factors that could preclude the possibility for the victims to call for the help. In situations like kidnapping, rape, robbery making use of the traditional voice based methods to call for the help might alert the offenders and put the victim’s life at a greater risk. This paper proposes an Emergency Response System (ERS), which focuses on developing an alternate mechanism through human computer interaction whereby the help can be called through a single press of a button and the locations of the callers are tracked in real time by the police vehicles. In the proposed system, the administrator can view the performance of all the police vehicles at any time through a web portal. The system used traditional data mining algorithms in order to analyze crimes in different areas of a city and at different times of the day. Based on this crime mapping, the administrator assigns patrol schedules for different police vehicles throughout the day. The proposed system would make it very easy for people to call for the help, and the police authorities to know the locations of the callers and identify crime hot spots and the administrator to keep track of the performance of each police vehicle.

Road traffic controlling is one of the prime issues of any busy town in the world. The situation is worst in the junction point of multiple roads. It is not always possible to predict upcoming traffic pressure intensity and direction with prior information. An adaptive approach is needed to solve this problem in real time. In this paper an efficient method of controlling traffic signal duration is proposed. Here cascade object detection technique is used to recognize and count the number of moving vehicles towards a junction from various directions through static video camera installed in each direction. Using the static camera, the proposed system senses the current traffic pressure of each connecting road towards the junction and thereby takes sensible decision of setting traffic signal duration in each road.

In this paper we present an advanced model for power consumption in communications and study its effect on the lifetime of the wireless sensor networks in underground communications for wet sand. The power communications model is incorporated in the life time model of wireless sensor networks. The life time model takes into consideration several parameters such as the total number of sensors, network size, percentage of sink nodes, location of sensors, the mobility of sensors, power consumption when nodes move and the power consumption of communications. The new model for power consumption in communications shows more accurate results about the lifetime of the sensor network in comparison with previously published results.

Massification of Slovak higher education system requires new ways how to organize educational process. That was why we decided to introduce formative assessment in our course. We immediately registered attempts to cheat during this type of assessment. This inspired us to find effective ways how to discover such attempts. Using timestamps associated with each activity carried out in the Moodle tests helped us to gather relevant data and analyze them. Paper presents approaches we proposed to recognize students suspect for cheating.

A feed-forward control structure adapted from Vilanova and Serra (IEEE Proc- Control theory for Electrical Engineers 144 (6):103–104, 1997). was investigated through both simulation and application to demonstrate how it could enhance the performance of closed-loop systems. In addition its ability to handle with ease right-half plane (RHP) zeros, unstable poles and dead-time that may exist in the plant will be investigated. Design of the components of structure is shown to be both non-complex and simple to implement.

The novel feed-forward control loop and the traditional PID feedback will be compared using Pareto Fronts to quantify the performance trade-offs. An application will be used to validate the simulation results and conclusions.

This paper presents on a reactive planning model, to organize, design and adapt from composing of learning objects (LO), learning routes in virtual environments and real time. The characteristics of these environments include not being controlled by just one participant; hence, compositions here proposed, used a planning algorithm to handle uncertain events on the building of learning routes must face uncertain changes originated in an environment in base to three cases: i) when a LO is no longer available, ii) when a LO is modified, or iii) when the goal state of learning changes depending on the original requirements of the problem. This solution ensures finding a long learning route. Although the first option is the convenience LO student profile, if one is not available replaced by another or others which ensure achieving the desired knowledge.

The biodiesel production was performed in stirred tank chemical reactor by numerical simulation. The main results are that the percentage of conversion from triglyceride to biodiesel is approximately of 82 % when the molar flow ratio between triglyceride/alcohol is 1:5. This system displays only one equilibrium point. Since there are imaginary eigenvalues in the Jacobian matrix analysis, the equilibrium point is unstable. The biodiesel production in stirred tank chemical reactor is good because the settling time is short, and has higher conversion.

This paper presents an evaluation of an optimal control-based deformable image registration model and compares it to four well-known variational-based models, namely,

elastic, fluid, diffusion

and

curvature

models. Using similarity and deformation quality measures as performance indices, Non-dominated Sorting Genetic Algorithm (NSGA-II) is applied to approximate Pareto Fronts for each model to facilitate proper evaluation. The Pareto Fronts are also visualized using Level diagrams.

Curvature has a great effect on fringing field of a microstrip antenna. Consequently, the fringing field affects the effective dielectric constant and then all antenna parameters. A new mathematical model for return loss mutual coupling coefficient as a function of curvature for two element array antenna is introduced in this paper. These parameters are given for TM10 mode and using three different substrate materials RT/duroid-5880 PTFE, K-6098 Teflon/Glass and Epsilam-10 ceramic-filled Teflon.

A novel all-optical variable delay buffer for next generation optical networks is reported. This buffer can store the contending packets for a relatively long time by using fiber Bragg gratings (FBGs). The proposed design is characterized by the ability to extract the delayed packets as soon as the contention is resolved.

Outsourcing means using factors which are external to an organization to perform its functions whereas offshore outsourcing relies on using foreign resources to perform those functions. We focus in this paper on offshore outsourcing of information systems (ISs). We have conducted an exploratory case study of outsourcing IS support services. The services have been outsourced by a supplier organization which has been based in Finland. Main parts of its customer support services have been allocated to so-called production centers, which have been located in three countries; Latvia, India, and the Philippines. We have gathered qualitative data from nine experts via theme-based interviews. The empirical data gathering has focused on revealing problems in the outsourcing practices. There were 74 mentions of different kinds of confronted problems. The differences between the studied countries in terms of the typical outsourcing problems have been noted and the results compared to the most important related works. The presented results on the studied thematic issues can be useful in their part for better understanding typical problems related to initiating and organizing similar IS-related offshore outsourcing activities.

Amongst the critical actions needed to be undertaken before system testing, software fault prediction is imperative. Prediction models are used to identify fault-prone classes and contribute considerably to reduce the testing time, project risks, and resource and infrastructure costs. In the development of a prediction model, the interaction of metrics results in an improved predictive capability, accruing to the fact that metrics are often correlated and do not have a strict additive effect in a regression model.

Even though the interaction amongst metrics results in the model’s improved prediction capability, it also gives rise to a large number of predictors. This leads to Multiple Linear Regression (MLR) exhibiting a reduced level of performance, since a single predictive formula occupies the entire data space. The M5’ model tree has an edge over MLR in managing such interactions, by partitioning the data space into smaller regions.

The resulting hypothesis empirically establish that the M5’ model tree, when applied to these interactions, provides a greater degree of accuracy and robustness of the model as a whole when compared with MLR models.

In this paper, a classifier based on a combination of Rough Set and 1-v-1 (one-versus-one) Support Vector Machine for Content Based Image Retrieval system is presented. Some problems of 1-v-1 Support Vector Machine can be reduced using Rough Set. With Rough Set, a 1-v-1 Support Vector Machine can provide good results when dealing with incomplete and uncertain data and features. In addition, boundary region in Rough Set can reduce the error rate. Storage requirements are reduced when compared to the conventional 1-v-1 Support Vector Machine. This classifier has better semantic interpretation of the classification process. We compare our Content Based Image Retrieval system with other image retrieval systems that uses neural network, K-nearest neighbour and Support Vector Machine as the classifier in their methodology. Experiments are carried out using a standard Corel dataset to test the accuracy and robustness of the proposed system. The experiment results show the proposed method can retrieve images more efficiently than other methods in comparison.

The cloud is currently a ubiquitous facility used in global data storage. The cloud technology offers users an ability to store and retrieve data from disparate applications and devices. In order to utilize this data technology efficiently and to reduce the associated costs, we introduce a technique to minimize the space used for data storage. Storing data on a cloud server may not be efficient because multiple uploads of the same file may produce redundant data in the cloud. Currently, this technology is not utilizing matching algorithms which could determine the changes in the new version of a previously uploaded file. Use of such an algorithm could save storage space by only requiring modification of the previous version already stored in the cloud. In this paper we will check several different, and difficult, problems and see what affects the automatic load-balancing and asynchrony have on the speed of resolution of problems.

This paper introduces the Music Clustering by Directions (MCBD) algorithm. The algorithm is designed to support users of query by humming systems in formulating queries. This kind of systems makes it possible to retrieve songs and tunes on the basis of a melody recorded by the user. The Music Clustering by Directions algorithm is a kind of an interactive query expansion method. On the basis of query, the algorithm provides suggestions that may be used to enhance the query. The MCBD algorithm is bases on the Clustering by Directions (CBD) that was designed to support users of web search engines in information retrieval. The MCBD algorithm is used for retrieval of music documents similarly as the CBD algorithm is used with text documents. This paper also introduces a new kind of interface designed to perform interactive query expansion in query by humming systems. The interface is a kind of tag cloud applied to music information retrieval systems.

The system catalog of a database with explicit schemas contains among other things information about the structure of the database. Queries based on the system catalog allow us to search occurrences of database design antipatterns (database design flaws). In this paper, we present the results of an evaluation of a set of SQL databases. We used the queries that were presented in the previous paper on this topic. A goal of the research is to further experimentally evaluate the queries. We present findings about the queries as well as evaluated databases. In addition, we propose more questions about the design of conceptual schemas of SQL databases that can be answered by querying their system catalogs. The use of the queries would allow us to partially automate the process of evaluating structure and constraints of existing databases and detecting design flaws.

Laboratory experiences are a vital component within science education. This paper is a report on the findings of a study conducted on undergraduate level laboratory science courses. A causal-comparative quantitative study was conducted with 150 learners enrolled at a 2-year community college, to determine the effects of simulation laboratory experiments on Higher-Order Learning, Critical Thinking Skills, and Cognitive Load. The treatment population used simulated experiments, while the non-treatment sections performed traditional experiments. Comparisons were made using the Revised Two-Factor Study Process survey, Motivated Strategies for Learning Questionnaire, and the Scientific Attitude Inventory survey, using a Repeated Measures ANOVA test for treatment or non-treatment.

The vertical handover is the ability for a device, such as a smartphone, to change between cellular data and Wireless LANs without losing any established connections. Previous approaches rely on tunneling to achieve this. This research aims to demonstrate a new approach to the problem, without tunneling, using a new intermediate layer 4 protocol running on top of TCP. The newly developed concept was tested through three scenarios that proved the mechanism works.

In this paper we present the implementation and analysis of a morphological algorithm for the attributes opening and closing on grayscale images. We investigated the application of this algorithm to different types of images. As a result we determined the range of the algorithm applicability and obtained recommendations for choosing it’s parameters.

Unlike most morphological algorithms this one solves both tasks: removing grayscale peaks and retaining image structure.

This makes the image more simple for subsequent processing. At the same time we retained all significant image features for solving the segmentation problem.

Automated document clustering is an important text mining task especially with the rapid growth of the number of online documents present in Arabic language. Text clustering aims to automatically assign the text to a predefined cluster based on linguistic features. This research proposes an enhanced grid based clustering algorithm. The main purpose of this algorithm is to divide the data space into clusters with arbitrary shape. These clusters are considered as dense regions of points in the data space that are separated by regions of low density representing noise. Also it deals with making clustering the data set with multi-densities and assigning noise and outliers to the closest category. This will reduce the time complexity. Unclassified documents are preprocessed by removing stops words and extracting word root used to reduce the dimensionality of feature vectors of documents. Each document is then represented as a vector of words and their frequencies. The accuracy is presented according to time consumption and the percentage of successfully clustered instances. The results of the experiments that were carried out on an in-house collected Arabic text have proven its effectiveness of the enhanced clustering algorithm with average accuracy 89 %.

The mobile telephony system has become popular due to its wide coverage, resulting in near-universal roaming service to its subscribers. However, when it comes to data transfer rates, the WLANs lead the way. WLANs have much restricted hot-spot coverage compared to mobile telephony systems, but provide better data rates at lower costs. Combining the two, results in best of both the worlds. Thus, 3GPP has proposed 3GPP-WLAN architecture to bring in this synergy between the two systems. From the subscriber’s perspective, one of the issues to be taken care of is “identity privacy”—how the identity of the subscriber be hidden from the eavesdroppers wanting to track the subscriber. 3GPP has devised a scheme for taking care of this in 3GPP-WLAN, which is different from that followed in other 3GPP systems. However, the said scheme does have certain vulnerabilities, and cannot guarantee the desired privacy. In this paper, we put forward an extension to the existing scheme to take care of these vulnerabilities. Also, this can be implemented without changes to intermediary networks or components, allowing for an easier transition.

As RFID technology becomes ever more affordable, its large scale implementation has been a growing trend in recent years. While current protocols allow for non-unique tag IDs, most existing implementations largely optimize RFID system’s performance based on the assumption of unique tag IDs and treat the existence of non-unique tag IDs within reader’s range as a rare occurrence. Nevertheless, unless formally evaluated, it is not clear, what is the degree of performance degradation in the presence of non-unique tag IDs . We evaluate the behavior of Basic Frame Slotted ALOHA (BFSA) collision resolution for an RFID system using OPNET Modeler 14.5 as both simulation, as well as, analytical results visualization platform. The system is built assuming muting of tags by the reader and contains a mix of unique and non-unique tag IDs. Our findings are compared with results obtained from the evaluation of a similar model for a system consisting solely of unique tag IDs . The comparison of total census delay and throughput under variable frame sizes showed an increase in total census delay with an increase in number of tags and a decrease in network throughput with increase in the number of tags for the system allowing non-unique IDs.

Software projects are complex endeavors that quite often fail to satisfy their initial objectives. As such the need to systematically study and assess the complexity of software projects is quite important. This study presents a systematic framework for assessing complexity of software projects that is based on the study of project management subject areas as defined in Project Management Body of Knowledge (PMBOK). The presented framework is based on a model that combines the concepts of project, complexity model, complexity factor etc. is an attempt to systematically assess and compare the complexity of software projects. The whole concept has been implemented within Project Management Complexity Assessment Tool (PMCAT) and it is available as a software service over the web.

WiGig is incorporating in the group of wireless standards which tend to release users from being tethered to their devices. It employs 60 GHz frequencies to achieve transfer rate up to 7 Gbps, ten times faster than current fastest Wi-Fi network based on IEEE 802.11n. This new standard, labeled as 802.11ad is an exclusive technology for instant data transfer.

Higher frequencies allow higher data rates, which leads to inter symbol interference problem. This obstacle in WiGig is exceeded by employing OFDM modulation technique elaborated in this paper, with attention focused on receiver—what are the limitations, appropriate transfer synchronization and utilization of FFT required for signal demodulation.

LEON3 processing core is a synthesized VHDL model of 32-bit processor compliant with SPARC V8 architecture. The purpose of this paper is to determine the efficiency of this type of IP core in WiGig environment, by testing LEON3s’ performances on algorithms for FFT implementation, since modulation is the essential factor in OFDM deployment. An effort was made to discover an optimal algorithm (with features obedient to the 802.11ad requirements) which escalates LEON3 IP Core performances for receiving side.

In this research different clustering techniques are applied for grouping transcribed textual documents obtained out of audio streams. Since audio transcripts are normally highly erroneous, it is essential to reduce the negative impact of errors gained at the speech recognition stage. In attempt to overcome some of these errors, different stemming techniques are applied on the transcribed text. The goal of this research is to achieve automatic topic clustering of transcribed speech documents, and investigate the impact of applying stemming techniques in combination with a Chi-square similarity measure on the accuracy of the selected clustering algorithms. The evaluation—using F-Measure—showed that using root-based stemming in combination of spectral clustering technique achieved the highest accuracy.

An electroencephalogram (EEG) is a record of the electric signal generated by the cooperative action of brain cells, that is, the time course of extracellular field potentials generated by their synchronous action. EEG is widely used in medicine for diagnostic and analysis of several conditions. In this paper, we present a system based on neural networks and wavelet analysis, able to identify epilepsy seizures using EEG as inputs. This work is part of a research looking for novel models able to obtain classification rates better that the state-of-the-art, for the identification of normal and epileptic patients using EEG. Here we present results using a Discrete Wavelet Transform (DWT) and the Maximal Overlap Discrete Wavelet Transform (MODWT) for feature extraction and Feed-Forward Artificial Neural Networks (FF-ANN) for classification. By using the benchmark database provided by the University of Bonn, our approach obtains an average accuracy of 99.26 % tested using threefold cross-validation, which is better than other works using similar strategies.

The services landscape is changing with the growing acceptation of cloud computing and the proliferation of smartphones and Internet-enabled handheld devices. Users are increasingly demanding services that can adapt to their current context. Hence, context-aware services need up-to-date context information to be able to adapt their behavior to current situations of users. We propose, in this paper, a framework for context information dissemination, which relies on negotiated Context Level Agreements (CLAs) between context consumers and context providers. A Context Broker (CB) helps context consumers select suitable context providers that can offer their required context information and fulfill their quality-of-context (QoC) requirements. Furthermore, the CB is in charge of negotiating the CLA terms—using a multi-attributes negotiation model—with a selected context provider on behalf of the context consumer.

This paper describes a new method for decouple systems with an automatic generator of decoupling blocks using genetic programming and shows that the decoupling of MIMO systems by this method is easier and more powerful than the results obtained using a regular decoupling state feedback technique in a paper production machine process and an irrigation of fields process.

MEMS accelerometers have been used in air bag deployment system and other applications. Most MEMS accelerometer devices are sensitive to acceleration input along one direction. In this paper, a dual-axis MEMS accelerometer which can simultaneously measure acceleration inputs along X and Y directions is proposed. The proposed MEMS accelerometer utilizes two sets of folded beams perpendicular to each other to sense acceleration inputs along X and Y directions within the device plane. The working principle of the dual-axis MEMS accelerometer is analyzed. A theoretical model is developed to predict the performance of the accelerometer. A set of example design parameters of the device is obtained based on the analysis. ANSYS simulation is used to verify the function of MEMS accelerometer. The fabrication flow of the MEMS accelerometer is suggested. Combined with a Z-axis accelerometer, the proposed dual-axis MEMS accelerometer can be used for acceleration measurement along complete X, Y and Z directions for 3D inertial navigation system.

Data Mining (DM) projects are implemented by following the knowledge discovery process. Several techniques for detecting and handling data quality problems such as missing data, outliers, inconsistent data or time-variant data, can be found in the literature of DM and Data Warehousing (DW). Tasks that are related to the quality of data are mostly in the Data Understanding and in the Data Preparation phases of the DM process. The main limitation in the application of the data quality management techniques is the complexity caused by a lack of anticipation in the detection and resolution of the problems. A DM process model designed for the prior management of data quality is proposed in this work. In this model, the DM process is defined in relation to the Software Engineering (SE) process; the two processes are combined in parallel. The main contribution of this DM process is the anticipation and the automation of all activities necessary to remove data quality problems.

The importance of e-education in the modern world is not debatable as sufficiently increases the auditorium and improves the students per teacher ratio. It also may serve the re-educational needs of a state and therefore should be recognized as an important part of public services that government provides via e-channels. The digital intelligence concept required building e-government is also based on educating citizens to be able to consume, process and formulate a feedback to government via IT channels. Unfortunately the lack of a general approach to the system in majority of states (countries) holds back the process of implementing such e-educational services. In order to bridge this gap the paper defines first areas of interest followed by expanded list of requirements needed to unify and improve such services. The paper also proposes technical solutions in form of hybrid SaaS (cloud) and the id-cards based identification system that satisfy all earlier stated requirement including reducing the cost of implementation.

Time-stamped digital signature scheme can be employed to derive a new solution that improves the authentication, non-repudiation and data integrity of current payment gateway. This paper suggests designing a new method to process online payment transactions by adding an additional step to the current payment gateway which will verify the bank cardholder’s identity through a trusted third party, a certificate authority (CA). Therefore, a new Time-Stamped Digital Card (TSDC), which relies on the concept of asymmetrical key algorithm to accomplish its task, will be proposed. Time stamp is examined to determine how old the TSDC is and whether it has been previously used or not. It will also be used to prevent replay attack. The protocol of TSDC consists of five steps and has been analyzed. TSDC needs to be generated, signed and submitted to the payment gateway along with the credit card information by the customer prior to processing any online transaction for identification purposes. Therefore, TSDC aims to reduce the high volume of fraud transactions and suspicious activities currently experienced during payment gateway due to lack of identity verification of bank cardholders.

VLSI continues to shrink the feature size of transistors. Nowadays the technology is advancing to deep submicron level in which leakage power becomes dominant in VLSI power consumption. Traditional logic shut-down technique only eliminates dynamic power when circuit is idling, but leakage power cannot be eliminated. To eliminate leakage power, the voltage source (V

dd

) should be completely shut down when circuit is idle. However, shutting down and enabling V

dd

in a large circuit results in a large transient current, which may lead to error of circuit. Block-wise shut-down technique has been reported by researchers to avoid this issue. It shuts down and recovers back V

dd

of blocks in a pipelined circuit sequentially when circuit is idle. This totally eliminates leakage power, while avoiding the large transient current in circuit, hence resulting in less glitches. To verify its effectiveness in power saving, we implemented block-wise logic shut-down in an 8 × 8 pipelined Booth multiplier. Whenever the multiplier is idle, supply voltage is turned off block-by-block, eliminating both dynamic and static power. The schematic of the circuit is designed using PSPICE. Simulation results verify the correct function and the expected shut-down of the designed Booth multiplier. PSPICE power simulation demonstrates effective power saving of the Booth multiplier for the given input pattern sequence.

Cloud is the recent emerging technology in all aspects. The basic concern with the usage of this cloud technology is security. Security poses a major drawback with data storage, resource utilization, virtualization, etc. In the highly competitive environment the assurances are insufficient for the customers to identify the trust worthy cloud service providers. In a nut shell all the entities in cloud and cloud computing environment should be trusted by each other and the entities that have communication should be trusted by each other. This paper throws light on different Trust Models developed and their drawback with respect to resource security. A strong Trust Model is recommended to enhance the security of the resources in Cloud.

Today’s institutions are facing major security issues; consequently, they need several specially trained personnel to attain the desired security. These personnel, as human beings, make mistakes that might affect the level of security.

A proposed solution to the aforementioned matter is a Face Recognition Security System, which can detect intruders to restricted or high-security areas, and help in minimizing human error. This system is composed of two parts: hardware part and software part. The hardware part consists of a camera, while the software part consists of face-detection and face-recognition algorithms software. When a person enters to the zone in question, a series of snapshots are taken by the camera and sent to the software to be analyzed and compared with an existing database of trusted people. An alarm goes off if the user is not recognized.

Wireless technology has been introduced and growing since early twentieth century, but there are still environments the current technologies find it difficult to penetrate. The dense jungle terrain, for example, pose a huge challenge for the 0.12 m wavelength of the Wi-Fi signals, but the FM radio frequency signals at a wavelength of 3 m function a lot better. This paper studies the possibility of using a very low frequency, down to the range of audible frequencies to try and identify the frequency band that can be used, ubiquitously and unobtrusively. Sound can be considered as a ubiquitous signal due to obvious reasons and the search is to find the unobtrusive frequency band that can be a candidate frequency for data carrier signals. The paper is presented in two sections, the first section does a geographically and age neutral survey to identify the unobtrusive signal and second section analyses the noise profiles in these frequency bands.

Grains parameters like volume, surface area or shape factor are important in geological issues connected with rocks and coal mining. For quick and efficient way to calculate that parameters are use some complicated algorithms which are based on source data written in flat 2D images. Almost always raw images need to be filtered and always need to be transformed into 3D images and process in 3D space to obtain reliable results. Even if algorithms which can do that operations are run on efficient computers, operations performed in 3D space consumes a lot of processing time. Authors made attempt of parallelization procedures performed in 3D space to improve efficiency on computers equipped in widely used, multi core processors and presents results.

Contract-Aware Software Development (CASD) process combines the Model Driven Engineering (MDE) approach with the Design by Contract ideas performed at the modeling level. Software engineering solutions need empirical investigation on the impact of methodology on the developed products. Therefore we have designed and performed a controlled experiment analyzing the crucial parts of the process. We focused on the CASD process specialized for UML models with contracts specified in the Object Constraint Language (OCL). Models with contracts are automatically transformed into C# code. In the experiment different development phases and their products were evaluated. As a result a high consistency between contract specification at a model and a code level was confirmed. The evidences stressed very high requirements on the tool support, and some inconveniences that still limit widespread application of the MDE paradigm.

Petri Nets is a family of modeling formalisms, consisting of various types of Petri nets with different interpretations and abstraction levels. General Purpose Petri Net Simulator (GPenSIM) is a new Petri Net simulator that implements many of the Petri Net types. This paper presents first a short introduction to the various types of Petri Nets; second, GPenSIM is tested for its implementation of various Petri Net types, using the classical benchmark known as the problem of “Buffered Producers-Consumers with shared channel (BPC)”; the modeling and simulations given in this paper show that the classical BPC problem can be solved by a variety of Petri Net extensions implemented in GPenSIM. In addition to the Petri Net extensions, some facilities are also provided in GPenSIM (e.g. resources), with which some specific problems can be conveniently solved.

In recent years, the growth of the Internet and communications networks for mobile phones have led to the development of services to provide tourism information via mobile information devices at tourist sites. In Japan, various tourism-related organizations are conducting field tests to improve tourist satisfaction through the provision of appropriate information.

In this research, we propose a tourism information system using augmented reality. The proposed system uses image recognition type augmented reality to superimpose tourism-related video content on photo images taken with a smartphone. Field experimentation of this system was conducted with tourists walking through the Otaru Canal area. As a result, a basically good evaluation was obtained regarding the ease of operation and appeal.

Information in organizations is managed efficiently by adopting data warehouses. Organizations are using data warehouses for integrating data from various heterogeneous sources in order to do analysis and make decision. Data warehouse quality is crucial because lack of quality in data warehouse may lead to rejection of the decision support system or may result in non-productive decision. A set of metrics have been defined and validated to measure the quality of the conceptual data model for data warehouse. In this paper, we first summarize the set of metrics for measuring the understand ability of conceptual data model for data warehouses. We focus on providing empirical validation by the family of experiments performed by us. The whole empirical work showed us that the subset of proposed metrics can be used as an indicator of conceptual model of data warehouses.

Model Driven Engineering (MDE) aims to make face to the development, maintenance and evolution of complex software systems, focusing in models and model transformations. This approach can be employed in other domains such as database schema integration. In this paper, we propose a framework based on MDE to integrate database schema. In MDE context, database schema are viewed as database model. A metamodel for creating database models, an algorithm for database model matching and an algorithm for database model merging are presented. We provide a prototype that extends the MT4MDE and SAMT4MDE tools in order to demonstrate the implementation of our proposed framework. An illustrative example helps to understand our proposed framework.

With the advance of online Learning Management Systems (LMS) it is easier than ever to provide students content providing multiple types of media. Many contend that this generation of students prefers video to text. This paper proposes a study that will examine if first year engineering students learn more about given case studies using the recommended textbook or the video prepared by the text publisher. Students are required to learn about the wonders of the industrial world in their first year engineering course. Students are tasked to learn about the wonders from the recommended text. Sometimes students choose to use to learn about the wonders from the video that is being available from the publisher of the book. In this study, it is planned to assess how much the students learn depending on their choice of media as well as study style and time on task. The students’ performance in the reflective assessment item will be combined with the survey results to determine if there are any significant effects on student learning. The results of this study are not yet known. It could be that students learn better with the video vs. the text or vice-versa. It may be that the most influential aspect is how long the student spent studying or if the student reviewed notes before taking the assessment. Regardless of the specific outcome of the results, the overall conclusions will be useful in helping future first year engineering course students be successful in this particular assignment and in the course over all. This Work In Progress paper is presented with the intention of receiving feedback on the study and survey design.

Universities such as Brigham Young offer a central facility for computerized testing. Michigan Technological University is following this model with the establishment of the Michigan Tech Testing Center (MTTC) in 2012. The center creates a space that supports flexible, high integrity computerized exams. This paper focuses on the pilot testing of a spreadsheet lab practical using file submission through Canvas and Jotform.

More popular principles of neural networks distribution are trainset parallel processing, matrix operations parallel processing or parallel processing of neural networks collections. This paper describes architecture of asynchronous distributed system for training and simulating multilayer perceptron based on the actor model. Usual backpropagation training algorithms for multilayer perceptrons, such as gradient training, Levenberg-Marquardt training, RPROP training have a common disadvantage: all of them are partially synchronous. Global optimization algorithms (genetic training, annealing algorithm etc.) are more appropriate for distributed processing but most of them are slow and inefficient. Gravitation search algorithm is new global optimization procedure combining good convergence, efficiency and algorithm step dispensability. The paper develops asynchronous distributed modification of this algorithm and presents the results of experiments. The proposed architecture shows the performance increase for distributed systems with different environment parameters (high-performance cluster and local network with a slow interconnection bus).

Metallographic image processing focuses primarily on image segmentation, edge detection, and approximating grain size. This paper presents the results of applying a radial basis function neural network to the image texture data obtained from steel metallographic specimens to determine the feasibility of the automated recognition of steel phases.

Aspect-oriented modeling (AOM) has been developed to modularize crosscutting concerns appropriately in UML models. In software engineering, aspects are concerns that cut across multiple modules. In requirements modeling, we analyze interactions and potential inconsistencies. We use UML to model requirements in a use case driven approach. During requirements specification a structural model of the problem domain is captured with a class diagram. Use cases refined by activities are the join points to compose crosscutting concerns. Graph transformation systems provide analysis support for detecting potential conflicts and dependencies between rule-based transformations.

The orientation image estimation is a critical step in fingerprint image processing and feature extraction. The computation of local ridge orientation in low quality fingerprints is still a difficult task. A simple and reliable method for estimating the fingerprint orientation image in the frequency domain is proposed. The results of the experiments conducted on a collection of fingerprints, in order to evaluate the performance of the proposed method, are also presented.

This paper addresses the significance of affordance in association with cultural conventions in the design of voice user interfaces (VUI) for orally grounded users in the global South (i.e., developing countries of the world). The paper demonstrates that sensitivity towards cultural conventions which subsequently bring about affordance has more credence than the objective usability measures of effectiveness and efficiency as defined by the International Standards Organization (ISO). This demonstration is done with the aid of two case studies of Interactive Voice Response (IVR) systems that were developed for users in developing countries of Southern Africa. The paper specifically presents the concept of taking into consideration the shift between the standard cultural norm and the situational norm experienced during the usage of the IVR system. We have established that orally grounded technology users prefer a VUI that allows them to transfer easily from their standard cultural norms to the situational norm that is determined by the context of use of the presented technology.

The goal of this paper is to design equalizer for a Single Carrier (SC) system operating in the 60 GHz frequency band. The main focus is to emphasize the important considerations that have to be investigated when implementing an equalizer in the millimeter wave technology, as well as to demonstrate its simplified design when it is being implemented in the frequency domain. In order to accomplish this task, the calculation of the needed coefficients has to be investigated, and therefore the channel characteristics. These coefficients would enable us to implement a simple form of an equalizer, using VHDL, which for the 60 GHz technology is an important module on the receiver side of the communication. At the end of the paper the results of the performed synthesis are being presented.

In this paper we have discussed the progress of research in the area of video quality model standardization and the future challenges in that area. First we have discussed the various projects completed by VQEG to evaluate the performances of various video quality models. The video databases used by VQEG projects are discussed briefly. Based upon the proposals of VQEG, ITU has proposed the standardized recommendations for various video communication services. The video quality assessment related various ITU recommendations are presented. After discussing the application areas of video quality assessment, the recent research trends in that area are discussed. In this paper, the role of audio is not discussed and only the issues related to video are discussed for video quality assessment.

This paper presents the process of designing a 64-point IFFT hardware module, as a 2D structure of 8-point IFFT pipeline modules. The proposed 64-point IFFT module utilizes only two 8-point IFFT modules, which include minimal number of multiplications and additions, and as well provides parallel processing of eight symbols in each pipeline phase. This allows high throughput performances of the proposed 64-point IFFT module and chip area savings of its hardware implementation on Virtex 5 FPGA. The realized hardware design can be easily applied in a high-speed real-time system, such as OFDM-based communication system.

During a survey based study, it has been revealed that psychological distress is reflected in the way computer users interact with computers. Based on the feedback of the subjects, the types of stress-reflector interactions were also identified. However, the specific interactions related to the stress, the nature of the relationship between the identified ‘stress-reflectors’ and the actual level of psychological distress was yet to be investigated. Accordingly, the initial survey was then followed by a series of activities with the objective of uncovering the nature of the relationship exists between the two. Initially, the most frequented interaction behaviors of computer users under stress were identified. Secondly these behaviors were recorded using a background analyzer together with a simultaneous measure of the distress level of the relevant computer user. Finally, behavior measures of individuals were mapped with their personal distress scores, producing the dataset using which the nature of correlations were explored. This paper presents the work carried out during this exploration, keeping the initial focus on linear methods, and provides justifications for the claim: The relationship between the distress score and the human computer interaction parameters is non-linear.

The purpose of this paper is to provide information to support a change in the curriculum and promote the inclusion of new advances in study programs. The resources of this paper come from the shared experiences of the authors working in strategic management at the university, and also from audits from the Slovak Higher Education Institution (HEI) and several projects in the field of education and innovation. The Paper describes a project to develop an advanced general method of improving and innovating study programs according to the expected development of advances in the field. The overall findings have shown study programs required change, it is appropriate to use the Study Program Leading Innovation (SPLI) model and apply it to the creative existing curriculum. The diversity of ideas was and still is limited about the quality benchmark and how to achieve change and improvement.

We created and implemented an algebraic framework to automatically generate component variants out of specifications. In this paper we provide the definition of this approach with its operators and operands, and show how expressions can be parsed, translated and processed for production of component variants. We created a Java application which is widely based on sets, to show the approach can be implemented properly and efficiently.

The designing and implementation of an agent-based model for a system called complex are often guided by clear objectives and often meet a need. Such kinds of models are often used to help for understanding real systems mechanisms and to be at last a decision support. The evolution of a theory that is supported by validation stages through a simulation needs to be guided by a methodology. This one will make possible to organize the work and communicate with the end users in order to achieve the objectives with a reasonable time. We propose here a methodology that extends the Unified process. It provides a set of tools to carry out the modeling work successfully. This methodology is iterative and incremental and is guided by a collaborative approach based on communicating with the end users in one side and specialist in another side. The communication is also supported by tools and a common ontology. The present method formalism is based on Agent UML combined with GAIA. A practical case is also presented with an agent based model on the Rift valley fever.

A simple dynamic model of the swing phase of the lower body of a NAO robot is developed and the frictional model for its hip joint is determined experimentally. Thereby a friction compensation technique is proposed to obtain a ‘free’ moving joint that is important for passive dynamic walking.

For the last two decades, software architecture has been adopted as one of the main viable solutions to address the ever-increasing demands in the design and development of complex software systems. Nevertheless, the rapidly growing utilization of communication networks and interconnections among software systems have introduced some critical challenges, which need to be handled in order to fully unleash the potential of these systems. In this respect, digital ecosystems, generally considered as a distributed adaptive open socio-technical system, have gained considerable attention, since their scale is incomparable to the traditional systems. The scale of socio-technical ecosystems makes drastic changes in various aspects of system development. As a result, it requires that we broaden our understanding of software architectures and the ways we structure them. In this paper, we investigate the lack of an architectural model framework for digital ecosystems interoperability, and propose an architectural model framework to improve digital ecosystems interoperability based on complex system theory.

This paper explores the possibility of achieving multi-gigabit data throughput over wireless networks, by using the FPGA technology. It focuses on the implementation complexity of an Orthogonal Frequency-Division Multiplexing (OFDM) modulation, as the most complex part of a physical layer in an 802.11 wireless network.

The calculations are performed for a typical OFDM system, as synthesized in the Xilinx ISE Studio for the most popular Xilinx FPGA architectures. The results present the upper processing speeds that can be expected from an FPGA implementation of an OFDM modem.

The purpose of the paper is to describe how the structure of knowledge, innovation and technologies’ cluster should be formed. The structure of the cluster is understood as a set of interacting components of the system. The authors synthesize the existing opinions and also reveal their own opinion about the possibility to determine the interaction among knowledge, innovation and technologies in the context of value creation or resource management, pursuing the preparation of the project for country universally sustainable development. The paper presents the original evaluation performed by the authors in order to optimally allocate the investment resources for knowledge, innovation and technologies among distinctive subsystems of universally sustainable development, as well as to optimally allocate the investment resources inside the cluster among the creation and development of knowledge, innovation and technologies. For the solution of the mentioned problem the methods of stochastic informative expertize and the adequate investment portfolio have been used.

Innovative education of natural sciences consider learning with dynamic image, films and 3D technologies. In the research article we discuss impact and importance of documentaries on the knowledge level of students and their reactions. The research article describes the importance of integrating films into education through documentary films. Evidence of the effectiveness of innovative elements mentioned are the conclusions of the research which is presented in this paper. Currently we continue this research in teaching by watching documentaries on cinema pre-selected topic.

Use cases have become an important technique for capturing user requirements in software development projects. Likewise, increasingly adopted the workflow models represent the business processes of a company. Recently the standardization of BPMN v2, by the OMG, has given rise to modeling tools and execution of business processes that enable rapid prototyping applications, integrating the requirements to business. One of the most critical problems of software development is to create solid models and consistent with the company’s business. Thus, this work presents an approach for developing systems based on the detailed use cases in BPMN in order to refine and validate executable prototypes produced during the development.

This paper presents a SCADA system based on Siemens WINCC implemented on a Web server to drive an Allen Bradley PLC to control temperature in two tanks, the first tank simulates a tank for collecting oil from several locations with different temperatures, and the second tank simulates an oil tank which is heated and used to defreeze the pipeline during winter. A tuned cascade PID is used to control the process. This has two advantages; firstly, this controller saves on fuel consumption and secondly, it eliminates the effect of feed tank temperature. The system could be controlled locally or remotely through the web server. The system could also send text messages using GSM to an IPHONE.

With the increasing number of mobile users and the high volume of traffic that exists in modern mobile networks, it is evident that new methods for uncovering the patterns that exist within the usage data need to be developed. We present an algorithm called Prefix-based Mobility Mining (PRIMO) that combines frequent sequential pattern mining and association rules to build a system that can be used to improve traffic handling and predict the future actions of users in a network. We also introduce an application called AndroidMiner that explores the applicability of pattern mining to the mobile computing environment. When a mobile user interacts with a network they are often in contact with multiple cell towers. Employing the sequential nature with which the identifiers of these towers can be collected, we can effectively generate frequent sequences that represent the towers a user or group of users are most frequently interacting with. By representing the interactions of mobile users with networks as frequent sequences, we can effectively develop an understanding of traffic patterns that exist within a mobile network. An understanding of the trends of mobile networks can easily be applied to load balancing or improving location-based services.

Now-a-days ranking of universities and institutions has become an appealing topic to study or research, and it has got wide attention to all over the world to recognize the top higher education institutes. Therefore, study on the strategies of the ranking system is vital to ensure the acceptability. There are number of strategies have been developed to rank higher education institutions worldwide. This Study has focused to critically evaluate the potential shortcomings of the top four widely accepted ranking systems. These are the Times World University Rankings, QS World University Rankings, Academic Ranking of World Universities (ARWU) and Webometrics Ranking. We critically reviewed and analyzed these four higher education ranking systems to identify potential shortcomings in their strategies. Based on our investigation, it was observed that none of these ranking systems can provide satisfactory evaluation in terms of their construct validity and other parameters related to disputation. Nevertheless, these ranking systems are the most popular for what they have been doing over the decades but unfortunately each and every one of them has to some extent lacking as far as ranking excellency is concerned. Lack of availability of data and publications through which ranking is done is one major obstacle faced to determine the authenticity of ranking systems. Overall observation of these four ranking systems reflects the fact that generic challenges include adjustment for institutional size, differences between average and extreme, defining the institutions, measurement of time frame, credit allocation, excellency factors as well as adjustment for scientific fields. Misinterpretation of measurement data is also responsible for some of the ranking disputes. We have proposed a number of recommendations that could address the identified inadequacy and considerably improve the ranking system as well as incorporate more participation of higher education institutes form developing world.

This paper presents the proposed architecture that provides platform for implementation of intelligent software agents (Multi-Agent System) used for information retrieval based on user-oriented model. The existing architectures based on multi-agents as usual lack the ability for adaption to user requirements. Thus, the principal goal is to develop standard reusable scalable infrastructure based on intelligent multi-agents that incorporates particular user model providing relevant information to user queries taking into account his profile, operational patterns and preferences. The evaluation of the proposed architecture has been done comparing it with existing approaches taking into account relevant criteria such as used communication standards for information exchange between agents, available scalable layered structure and ability of adapting information or services to user habits, personal data and requirements. This approach has sufficient merit to be used as a reference for development of applications for user-oriented and adaptive information retrieval systems.

Every year more engineering programs are looking at online courses as a way to expand their programs and facilitate the educational goals of working professionals. This case study summarizes specific challenges faced by two faculty members in preparing and presenting six mechanical engineering classes, all core classes at either the graduate or undergraduate level, in a fully online format. The challenges discussed involve course preparation and planning, interaction with and among students, lack of student preparation, and exams.

A formal correctness proof of code containing loops such as while statements typically uses the technique of proof-by-induction, and often the most difficult part of carrying out an inductive proof is formulating a correct induction hypothesis, a specification for a loop statement. An incorrect induction hypothesis will surely lead to a proof failure. In this paper we propose a systematic way for identifying specifications of while statements. The key idea of our approach is to categorize and document common patterns of while statements along with their specifications. This is based on our observation that similarly-structured while statements frequently have similarly-structured specifications. Thus, a catalog of code and specification patterns can be used as a good reference for finding and formulating a specification of a while statement. We explain our approach using functional program verification in which a program is viewed as a mathematical function from one program state to another, and a correctness proof is done by comparing two functions, the implemented and the specified. However, we believe our approach is applicable to other verification techniques such as Hoare logic using pre- and post-conditions.

Most capacitive MEMS (Microelectromechanical Systems) accelerometers sense capacitance gap change due to inertial force. Since capacitance is inversely proportional to capacitance gap, this results in nonlinearity of its output response. In this paper, a high-linearity and high-sensitivity capacitive MEMS accelerometer based on overlap length change instead of capacitance gap change has been reported. Since capacitance is directly proportional to the overlap length, the proposed accelerometer has inherent high-linear relationship between its differential capacitance output and input acceleration. The proposed accelerometer utilizes threefold beam structure, which leads to improved device sensitivity. The working principle of the accelerometer is discussed. Theoretical analysis was performed to guide the device design optimization. The proposed MEMS accelerometer is to be fabricated with bulk-micromachining using silicon DRIE (deep reactive ion etching) and silicon-glass anodic bonding techniques. ANSYS simulation is used to verify the function of the designed MEMS accelerometer.

The proliferation of Web services over the Web today has led to an increasingly complex and time consuming task for effectively discovery relevant services. One approach to improve the discovery process is considering the behavior of such services under certain conditions or considering their overall quality in accomplishing the expected functionality. In this manner, clients utilize their time more efficiently to find services of interest. In this paper, a quality-driven approach for effectively finding relevant Web services, which we call Quality of Web Service (QWS) is introduced. Results from our proposed solution demonstrate high success rate in discovering Web services of interest and that our quality-driven ranking technique outperforms current state-of-the-art keyword-based methods by at least 36.25 % in terms of precision improvement.

While many technologies have been adopted in hospitals for preventing adverse events that could result in patient’s injury or death, detecting the precursors at early stages is yet a common problem and is often neglected due to improper patient monitoring mechanisms. Traditional continuous patient monitoring equipment (i.e. in ICU) lack wearability, portability and cost effectiveness. In this paper we introduce RFIDTrack, a mobile monitoring solution that allows wearable, continuous observation of many patient vital signs to be used inside hospitals. RFIDTrack offers a robust distributed system that is capable of alerting medical staff (i.e. nurses or doctors) in case of early detection of adverse events. The paper presents some experimental validation results, and analysis of the proposed ideas.

Transliteration detection (TD) is a natural language processing (NLP) subtask that is used to find matching Named Entities (NEs) from parallel or comparable text where each language text is in a different writing system. The task is aimed at building high quality transliteration lexicons for improving performance in cross language applications like machine translation (MT) and cross language information retrieval (CLIR). Recent evaluations of TD methods (for example those from the NEWS 2010 transliteration mining shared task (Kumaran et al., 2010)) underscore the need for more methods that can improve TD performance. This paper contributes to this need by evaluating the use of source-target language n-gram correspondences for TD. We present TD experiments that use three different classes of n-gram correspondence models on standard transliteration datasets from the 2009 and 2010 shared tasks on transliteration generation (Li et al. (Report of NEWS 2009 machine transliteration shared task. Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration, 2009); Li et al. (Report of NEWS 2010 transliteration generation shared task. Proceedings of the 2010 Named Entities Workshop, 2010)). Results show relatively significant TD performance improvements between the use of lower order and higher order n-gram correspondence models, and between the different classes of n-gram correspondence models. We show that our TD experimental setup is more complex than that in related work (Li et al. (Report of NEWS 2010 transliteration generation shared task. Proceedings of the 2010 Named Entities Workshop, 2010)) in terms of the search effort required, and that the best TD performances from the n-gram correspondence models in this paper are comparable to those from state-of-the-art methods. Our results also show that the n-gram size that should be used for developing high quality transliteration models in different languages and writing systems varies. Our work therefore serves to provide preliminary insight to the n-gram sizes required to model related high quality TD models for different language pairs and writing systems.

Tower cranes, have always the centerpiece of production, hoisting and transporting of a variety of loads on a construction site. Occasionally tower cranes operate with overlapping work zones and Crane positioning in any construction site follows a complicated procedure. Factors that have to be taken under consideration are building size and type, obstruction type, material yard location. Each project is unique and different from the other and thus location of the cranes in every situation.

A new developed application named Crane Locator is designed to facilitate the crane locating process by converting the engineer’s expert knowledge to computerized System embedded knowledge. The application gives engineers the right location of where the crane should be positioned, the number, model(s) and type(s) of cranes.

Android Smartphones are widely used nowadays. They have a lot of capabilities that made our life easier and more comfort. They opened the area of Android programming used to develop applications suitable for these smartphones. Our target, in this paper, is to propose an application that helps in collision avoidance between moving vehicles (especially trains) by tracking their routes. This application is a modified version of Route Tracker Application [Harvey and Deitel (Android for programmers an app-driven approach, 2011)], we use the Route Tracker Application on each smartphone that installed in the moving vehicle, to track its route. Then we save all trains points in a database, construct a map shows these points. In this map, a different color is assigned to each vehicle to distinguish it. This map is shown on a smartphone found in a control room. Using points in this map, the distance between vehicles is calculated (distance between points of vehicles). When two vehicles, for example, become too closer to each other, the inspector, in the control (monitoring) room, must take an action, he generates an alarm to warn the drivers of both vehicles so they can adjust their speed to avoid collision.