Advances in Computing, Communication and Control

In the line clipping procedures if the line is not completely inside the clipping window then we have no option but to divide the line into segments at the intersections of the line and clipping window edges and then identify which segment is inside and which segment is outside the clipping window. But if the line is completely outside the clipping window, the line is eligible for total clipping or trivial rejection. There exist total 26 possible cases for trivial rejection of a line. Out of these 26 cases only 12 cases were solved without dividing the line into segments in the Cohen-Sutherland line clipping algorithm. Remaining 14 cases were solved by dividing the line into segments. But if the line is totally outside the clipping window, we don’t require any segmentation. This paper presents the mechanism by which the remaining 14 cases can be solved without dividing the line into segments.

Greedy view selection, in each iteration, selects the most beneficial view for materialization. Algorithm HRUA, the most fundamental greedy based algorithm, uses the size of the views to select the top-k beneficial views from a multidimensional lattice. HRUA does not take into account the query frequency of each view and as a consequence it may select views which may not be beneficial in respect of answering future queries. As a result, the selected views may not contain relevant and required information for answering queries leading to an unnecessary space overhead. This problem is addressed by the algorithm proposed in this paper, which considers both the size and the query frequency of each view to select the top-k views. The views so selected are profitable with respect to size and are capable of answering large number of queries. Further, experiments show that the views selected using the proposed algorithm, in comparison to those selected using HRUA, are able to answer comparatively greater number of queries at the cost of a slight drop in the total cost of evaluating all the views. This in turn aids in reducing the query response time and facilitates decision making.

Differential evolution (DE) is a population based evolutionary algorithm widely used for solving multidimensional global optimization problems over continuous spaces. On the other hand, a variation of the original quantum-inspired evolutionary algorithm (QEA), bloch quantum-inspired evolutionary algorithm (BQEA), is a promising concept which very well suitable for handling global optimization problem of low dimensionality. BQEA applies several quantum computing techniques such as qubit representation based on bloch sphere and rotation gate operator, etc. This paper extends the concept of differential operators to the quantum paradigm and proposes the bloch quantum-inspired differential evolution algorithm (BQDE). The performance of BQDE is found to be significantly superior as compared to BQEA on several benchmark functions.

Now days, there is an increasing level of interest in the application of argumentation within the artificial agent societies. This paper extends the operational semantics to speech-act based communication messages received by an AgentSpeak(L) agent in order to enable argumentation in cognitive agents. The aim is to give semantics and implementation as logic-based plans for some key illocutionary forces, used for argumentation in the Belief-Desire-Intention (BDI) agent communication language ‘AgentSpeak(L)’. The extension allows agents engaged in a dialogue to put forward their arguments, question beliefs of other agents more expressively. Therefore, using extended speech-act based communication; an agent can share its internal state with other agents and influence other agents’ states. This work also provides a new dimension to argumentation based negotiation in BDI agents as this would enable the agents to negotiate using argumentation. Argumentation based negotiation can provide a powerful tool for the agents communicating to fix a deal using the electronic commerce services.

Intelligent agents are a new paradigm for developing software applications. Intelligent Agent (IA) can be defined to be an autonomous, problem-solving computational entity capable of effective operation in dynamic and open environments. Intelligent Agents are often deployed in environments in which they can interact, can cooperate, with other agents, including both people and software. In this paper Intelligent Agent architecture is proposed. The proposed architecture is capable to percept the dynamically changing environment. Based upon the perception, historical knowledge and internal design, the Intelligent Agent infers the action effecting the environment and updates the knowledgebase according to the action taken. Based upon the proposed Intelligent Agent architecture an Intelligent Medical Diagnosis System (IMDS) is given.

Petri net is a well-established paradigm, where new algorithms with a sound biological understanding have been evolving. We have developed a new algorithm for modeling and analyzing gene expression levels. This algorithm uses fuzzy Petri net to transform Boolean network into qualitative descriptors that can be evaluated by using a set of fuzzy rules. By recognizing the fundamental links between Boolean network (two-valued) and fuzzy Petri net (multi-valued), effective structural fuzzy rules is achieved through the use of well-established methods of Petri net. For evaluation, the proposed technique has been tested using the nutritional stress response in

E.Coli

cells and the experimental results shows that the use of Fuzzy Reasoning Boolean Petri Nets (FRBPNs) based technique in gene expression data analysis can be quite effective and describe the dynamic behavior of genes.

We propose a novel solution for determining the confidence of a particular called genetic base within a sequence being called correctly. This has made measures of confidence of base call important and fuzzy methods have recently been used to approximate confidence by responding to data quality at the calling position. A fuzzy Petri net (FPN) approach to modeling fuzzy rule-based reasoning is proposed to determining confidence values for bases called in DNA sequencing. The proposed approach is to bring DNA bases-called within the framework of a powerful modeling tool FPN. The FPN components and functions are mapped from the different type of fuzzy operators of If-parts and Then-parts in fuzzy rules. The validation was achieved by comparing the results obtained with the FPN model and fuzzy logic using the MATLAB Toolbox; both methods have the same reasoning outcomes. Our experimental results suggest that the proposed models, can achieve the confidence values that matches, of available software.

Image classification plays an important part in the fields of Remote sensing, Image analysis and Pattern recognition. Digital image classification is the process of sorting all the pixels in an image into a finite number of individual classes. The conventional statistical approaches for land cover classification use only the gray values. However, they lead to misclassification due to strictly convex boundaries. Textural features can be included for better classification but are inconvenient for conventional methods. Artificial neural networks can handle non-convex decisions. The uses of textural features help to resolve misclassification. This paper describes the design and development of a hierarchical network by incorporating textural features. The effect of inclusion of textual features on classification is also studied.

Data-warehousing is the computer application system that transforms a traditional intuitive decision making body into informed decision making organization. It provides key factors/facts across different chosen dimensions for ready consumption to the managers. The flexibility, provided by the data-warehouses for OLAP (On-line Analytical Processing) applications, offers a distinct edge to its practitioners over those who follow traditional way of browsing through conventional static reports for decision-making. However, the development and deployment of a proper data-warehousing solution in any industry is fraught with many challenges and more so in manufacturing industry in view of its complex processes and huge investments. Another important aspect is of identifying the right product to ensure that data-warehousing application can be built successfully for its effective use for on-line Analytical processing. This paper introduces the concept of data-warehousing, importance of it in a manufacturing industry, exploration of different types of solutions, and finally, the challenges faced in implementing the solution.

The groups of companies are categorized due to the splitting of financial markets into diverse sectors. The market scenario much is directory related to the rates of share prices that are expected to move up or down. There are several factors that influence the individual share prices.

A profitable share market always witnesses the trend of the rates plunging down. Within the market sector, there is anticipation for the shares to move for the most part, mutually. In this case ,our aim is to identify the groups of shares that do move collectively and identifiable in conditions of corporate activity. A hierarchical clustering algorithm, tree GNG, have identified groups of companies that cluster in clearly identifiable sectors. This categorization of sector scheme is accepted all over the world.

Choosing an optimum location of a distribution substation and grouping the various load points to be fed from a particular distribution substation has always been a concern to the distribution planners. A lot of work has been carried out in this regards but all have made either the use of man machine interface or have made some approximations. Here in this paper we present a Hard Clustering method for grouping the various load points as per the number of distribution transformers available. The method further gives an optimum location of the distribution substation taking into aspects the distances of the various load points that it is feeding. The results of the discussed techniques will lead to a configuration of substations that will minimize substation construction cost. It will further lower long range distribution expenses as it will lead to optimum feeder path.

Searching for information on the Webhas attracted great attention in many research com-communities. Due to the enormous size of the Web and low precision of user queries, results returned from present web search engines can reach hundreds or even hundreds of thousands documents. Therefore, finding the right information can be difficult if not impossible. One approach that tries to solve this problem is by using clustering techniques for grouping similar document together in order to facilitate presentation of results in more compact form and enable thematic browsing of the results set. Web Search Results clustering is about efficient identification of meaningful, thematic groups of documents in a search result and their concise presentation. This paper is an introduction to the problem of web search results clustering and we have a brief survey of previous work on web search results clustering and existing commercial search engines using this technique, and propose the possibility of future research direction.

Intelligent evaluation as an important branch in the field of artificial intelligence is a decision-making process of simulating the domain experts to solve complex problems. In this paper, we put forward a kind of intelligent evaluation method based on clustering, which can be used to mine different groups of teachers and evaluate the teaching quality automatically. Clustering analysis method is one of the main analytical methods in data mining, which influences the clustering results directly. In this paper Firstly, we do some improvement on traditional K-means clustering due to its shortcomings. Secondly, we propose a model or teaching quality evaluation based on improved K-means clustering.

In this paper, we propose consensus based load balancing algorithm for network of heterogeneous workstations. Load balancing is a critical issue in parallel and distributed computing in order to carry out efficient utilization of computational resources. The focus of this work is to design a dynamic decentralized load balancing algorithm for a network of heterogeneous workstations using consensus theory and graph partitioning. Simulation results show that the proposed load balancing algorithm is scalable, reliable, fault tolerant and maintains a balance between communication overhead and load balancing time.

As the technology increases day by day, human dependency increases on technologies. In present scenario everyone wants to do their work, business etc with the help of computer or with internet. Hence this increases the possibility of large-scale unauthorized copying which may lead to undermine the music, film, book and software industries. These concerns over protecting copyright have triggered significant research to find ways to hide copyright messages and serial number into digital media. An important sub discipline of information hiding is Watermarking. Digital Watermarking is an authentication technique which permanently embeds a digital signal (watermark) in text, image, audio, video files (any Data) by slightly modifying the data but in such a way that there are no harmful effects on the data. In this paper, we present audio watermarking technique that utilized the manipulation in high frequency of an audio signal to hide secret message The experimented result developed through MATLAB show that the usefulness of this technique.

This paper describes the implementation of Web usage mining for DSpace server of NIT Rourkela. The DSpace log files have been preprocessed to convert the data stored in them into a structured format. Thereafter, the general procedures for bot-removal and session-identification from a Web log file have been applied with certain modifications pertaining to the DSpace log files. Furthermore, analysis of these log files using a subjective interpretation of recently proposed algorithm EIN-WUM has also been conducted.

This research work presents a Genetic Algorithm (GA) heuristic approach to solve the static Routing and Wavelength Assignment (RWA) problem in Wavelength Division Multiplexing (WDM) networks under wavelength continuity constraint. The RWA problem is modeled as an Integer Linear Programming (ILP) problem with the optimization objective to balance the network load among the connection requests. We consider ARPANET as the standard simulation network and use Genetic Algorithm technique to solve the formulated ILP on such network to produce a near optimal solution in polynomial time. We state three different fitness functions, all of them aim at balancing the network load among individuals and compare them while optimizing different network parameters.

Service Oriented Architecture is used to achieve loose coupling among diverse interacting software applications. SOA is used for reduction in development time and cost. Web services standards used for SOA are distributed software components that provide information to applications rather than to humans, through an application-oriented interface. SOA with web services standards provide greater interoperability. It also provides protection from lock-in to proprietary vendor software. Using XML based orchestration business process execution language (BPEL) enables task sharing across multiple enterprises using a combination of Web services. Web services combine the advantages of the component-oriented methods and web techniques. Maintaining Web service quality requires more effort to manage overall Web service framework than each of Web service. Web Services Manager is a security administrator’s environment designed to secure access to Web services and monitor activities performed on protected Web services. Web services provide platform independence for the service oriented communication. This way data integration can be done providing the service as a request and service as provider.

Search engines are the online services available, which are used to locate necessary information on World Wide Web. As the web is growing at a very rapid rate, the pages that are similar to each other are also increasing. Hence, it is better to have a system that can discover similar web pages. In this paper, A Meta search approach is applied for the information retrieval purpose which retrieves pages from the result list of different search engines and content present in the web pages is analyzed on the basis of which system finds similarity between them. Web pages are represented in vector space which represents each web document as a vector and the terms present in that webpage as its components. Similarity is computed by using different similarity measures i.e. Cosine Similarity, Jaccards Coefficient and Dice Coefficient. A comparative analysis of these similarity measures is done to find out which measure performs better in terms of precision as well as recall.

Cost Estimation for distributed systems is a major challenge nowadays. Estimating the cost of development for distributed systems is based on a prediction of the size for future systems. A lot of cost estimation models were reported in the literature but many of these models became obsolete because of the rapid changes in technology. Reliable estimations are difficult to obtain because of the lack of detailed information about the future system at an early stage as well as due to the distributed location of various components of the developed software. Cost models like COCOMO(COnstructive COst MOdel)[5,6] and sizing methods like Function Point analysis are well known and in widespread use in Software Engineering. These models were applicable only to procedural paradigm, and are not directly applicable to software products developed using the object oriented methodology or distributed systems. It is this idea that gave birth to the creation of Use Case Point (UCP) metrics, originally developed by Gustav Karner[3]. UCP uses use cases as the primary factor, use case model is the first model developed in an object-oriented design process using UML. In this paper we extend the UCP to estimate the cost of development for distributed systems. We propose a novel approach to map the distributed systems from their function points and converting use case point counts on the basis of actor interaction with the actors present at other locations to the software and to estimate cost of development by using Distributed Synthesized UCP (ds-UCP) model with additional information obtained from distributed synthesized use case attributes.

With today’s increasing trend of cloud computing world, most of the organizations prefer to outsource and share their data by the means of cloud service providers. Cloud computing plays a major role by providing different resources in the form of web services which is based on pay-as-per-usage model. Along with benefits of reduced cost, dynamic resource availability, consumption based cost it also brings new challenges for data security and access control when users outsource sensitive data for sharing on cloud servers. This paper takes a glance on the different cloud computing model based on their access and deployment of clouds, also it provides two cryptographic approaches for the data security. The first approach is software based data security model and another is hardware based data security model. In software based model the cryptographic approach is used to build the software for the security of data. In hardware based model it is embedded in the hardware itself, thus providing more robustness. Thought hardware based model provides more robustness; the software based model provides more flexibility for the data correction and data recovery.

Today’s competitive market demands immediate attention on security issues for developing secure software system. Security must be an integral part of any application development methodology. It becomes more challenging when developers design projects according to agile methodology. Traditional ways of development are sequential considering major changes during analysis. Agile methodology is required as there is a need for an iterative approach which encourages changes in requirements at any stage in software development lifecycle. In this paper, we are presenting a framework which effectively implements security practices in agile development and adopts additional features proposed by other researchers. The key point in our framework is that we are embedding a hybrid technique for requirement elicitation with Agile Software Development (ASD). This technique would combine abuser stories and attack trees drawing best features of each of their individual methods. This hybrid technique maps security threats found during security requirements effectively as compared to individual techniques.

Prediction is growing area of research which is attracting many researchers. Prediction is applied to almost all the sectors. Much commercial Business Intelligence software is available in which prediction is one of the features. With the advent of Open Source Technologies, it has become possible for education sector which normally has low IT budget, to take maximum advantage of Information and Communication Technologies(ICT). This paper describes the use of Open source Software Knime for prediction of students result based upon various independent(predictor) variables and value of dependent variable can be predicted using decision tree , SOTA (Self Organizing Tree Algorithm) and Naive Bayes This paper compares these three predictive algorithms present in Knime in terms of accuracy. Predicted results are compared with the actual result in order to measure accuracy and recommends best Predictive algorithm for forecasting. This paper also demonstrates the use of Moodle - Open Source Learning Management System (LMS) Logs as one of the attributes in predicting the student results.

Service Oriented Architecture recommends a better flexibility & increase efficiency by reusing the services. But it also increases the complexity w.r.t. Security. In today’s era Orchestration is basic requirement for the service based security. Orchestration is a key control mechanism that invokes Services to work, as well as to provide control. In this paper we are going to represent the service interface for security constraints which will make their composition safe. Main aim is to the increase reusability and quickness, bring down difficulty, increase advanced extensibility and improved scalability and reliability.

In this paper we are introducing a new model which consists of Services, security and Orchestration together to improve the Security services.

This paper gives the performance analysis of Interleave Division Multiple Access (IDMA) with different coding techniques. Convolutional coding and Zigzag coding techniques are used to improve the capacity of a channel.A new multiple access scheme has been introduced which employs the chip level interleaving as the only means of user separation. Coded IDMA is compared with un coded IDMA in this paper.

Breadth First Search Channel Assignment(BFSCA) is a hybrid channel assignment algorithm that utilize multiple radio interfaces to improve the throughput and minimize the interference within the wireless mesh network and between the mesh network and co-located wireless mesh networks. This new channel assignment scheme allow different nodes in the same network to communicate with each other without causing too much interference to their neighbors. It is introducing Multiradio Conflict Graph(MCG) to model interference in the wireless mesh network. Breadth First Search Channel Assignment considers both the fixed channels(static) and the dynamic channels to reduce interference of the network. BFSCA will increase the network throughput greatly.

An electrical substation is a subsidiary station of an electricity generation, transmission and distribution system where voltage is transformed from high to low or the reverse using transformers. Substation communication plays a vital role in power system operation. The power industry is changing; there is more or less a global electrical power market with international power companies. Thus, national differences in for example communication protocols, special substation automation solutions etc, are an economic obstacle when the international electric companies are seeking even better productivity and economic performance. It is therefore necessary to design Substation Automation Systems that are more cost effective to operate and maintain and that ensure quicker returns on investment than in the past. It is therefore necessary to design Substation Automation Systems that are more cost effective to operate and maintain and that ensure quicker returns on investment than in the past. This new perspective with reference to the conceptual design and engineering of modern control systems, has been the driving force for the new standard IEC 61850, with a global approach on communication and information handling.

GOOSE is an acronym for Generic Object Orientated System-wide Events. It aims to replace the conventional hardwired logic necessary for intra-IED coordination with station bus communications. Upon detecting an event, the IED(s) use a multi-cast transmission to notify those devices that have registered to receive the data. The performance requirements are stringent – no more than 4ms is allowed to elapse from the time an event occurs to the time of message transmission. The main objective of the paper is to provide a framework for Substation Engineers to simulate GOOSE messages for fast transmission of substation events, such as commands, alarms, indications, as messages which take advantage of Ethernet and supports real-time behavior with Motor protection Relay using KALKI protocol Gateway Lite for Substation Automation project. To generate GOOSE messages with Embedded Artists LPC2468 OEM Board.

In the present paper, the performance of various energy efficient algorithms is being analyzed. In the previous papers, we have developed some energy efficient algorithm for MANET and analysis there performances. In [1] and [2], we have developed energy constraint gossip based protocol (ECG_AODV) and analyzed its energy performance as compared with AODV. Energy constraint Node cache based algorithm called ECNC_AODV were developed in [3]. In [4] and [5], we have proposed Energy based Gossip algorithm called EBG_AODV for MANET. In all the above work, we have analyzed the behavior of proposed algorithm and compare it with AODV under CBR as well Pareto traffic sources. With the help of simulation results, we have concluded that with above algorithm, there is an energy as well as overhead reduction up to 15%-35% without affecting the delivery ratio as compared to AODV. In this paper, we have simulated the above algorithm with new algorithm which is based on node cache plus gossip. The overall performance of EBG protocol is better as compared to other protocols in terms of energy consumption and routing overhead without affecting the delivery ratio as per simulation result.

In this paper, a transform based methodology is presented for compression of electrocardiogram (ECG) signal. The methodology employs different transforms such as Discrete Wavelet Transform (DWT), Fast Fourier Transform (FFT) and Discrete Cosine Transform (DCT). A comparative study of performance of different transforms for ECG signal is made in terms of Compression ratio (

CR

), Percent root mean square difference (

PRD

), Mean square error (

MSE

), Maximum error (

ME

) and Signal-to-noise ratio (

SNR

). The simulation results included illustrate the effectiveness of these transforms in biomedical signal processing. When compared, Discrete Cosine Transform and Fast Fourier Transform give better compression ratio, while Discrete Wavelet Transform yields good fidelity parameters with comparable compression ratio.

Researchers are working on Content Based Video Retrieval (CBVR) for many years. But the available techniques for CBVR are not performing well for CBVR of Animal Videos. Thus in this paper we have proposed a new technique for CBVR of Animal Videos and experimental results are also provided with this paper to support it.

Orthogonal Frequency Division Modulation (OFDM) is an efficient multi-carrier modulation scheme. This results in the optimal usage of bandwidth. It is used in many wireless communication systems due to its robustness towards fading channel behavior and a relative ease of implementation coming from computationally efficient Inverse Fast Fourier Transforms (IFFT). OFDM techniques form the basis of the physical layer of many broadband high data rate technologies including Digital Subscriber Lines (xDSL), Wi-Fi (IEEE802.11a/g/n) etc. One major problem with OFDM is synchronization between transmitter and receiver. This paper has been discussing the synchronization issues through data randomization.

The increasing complexity of optical processing algorithm has led to the need of developing the algorithms specifications using software implementation that became in practice the reference implementation. Adapting the algorithm specified by such software models into architectures becomes a very resource consuming and memory intensive task. The key objective in this paper is to develop analytical models to analyze the effects of various parameters such as propagation distance, chirping factor on the received power at the receiver end. SSF algorithm is simulated using MATLAB

TM

on Intel[R]

TM

Core[TM] 2 Duo CPU T5470 @ 1.60GHz, 0.99GB of RAM. Analysis show the received output power reduces by 61.1% with 5 time increase in chirping factor. Increase in chirp decreases the received power and broadens the received pulse. A reduction of 82% of received power is observed as the propagation distance increases by 50Kms. Mapping of SSFM algorithm to architecture is done with this analysis. The algorithm is synthesized using Xilinx design Manager. The hardware is implemented using virtex XC5VLX30TFF655 FPGA device family with speed grade -6. The complete hardware operates with maximum frequency 20.982

Mhz

which uses total memory of 523564

Kbytes

.

This paper discusses the error performance of Space- Time Trellis Code system over fading channels. Multiple-input multiple-output (MIMO) technology constitutes a breakthrough in the design of wireless communications systems, and is already at the core of several wireless standards. It offers high data rate and excellent throughput of wireless communication system. Trellis-code modulation (TCM) is one of the bandwidth efficient coding modulation techniques used in digital communications system. Here we discuss the design criteria for fading channels, employs that transmit and receive antenna diversity. It is observed from the simulation results that the code performance is improved by increasing the number of states. Also it provided the coding advantage as the number of states and receives antennas increases. The simulation have been conducted for 4 Phase Shift Keying (PSK) with data rate 2 b/Hz/s for two transmit and two receive antennas (N

T

=N

R

=2) system, provided better performance using 64 states STTC encoder.

Scalable performance analysis of routing protocols for ad-hoc network reveals the hidden problems of routing protocols in terms of performances. Wireless nodes in ad-hoc networks may exhibit non-cooperation because of limited resources or security concerns. In this paper we model a non-cooperative scenario and evaluate the performance of a reinforcement learning based routing algorithm and compare it with ad-hoc on-demand distance vector a de facto routing standard in ad-hoc networks. Mobility models play an important role in ad-hoc network protocol simulation. In our paper we consider a realistic optimized group mobility model to aid the performance of the reinforcement learning based routing algorithm under scalable non-cooperative conditions.

Vehicular Ad hoc network is a special case of Mobile Ad hoc networks, with high nodes mobility specification and a large energy resource which could extend coverage and system lifetime. Providing reliable and efficient routing in presence of relative movement motivates the introduction of movement awareness to improve performance of existing position-based routing schemes in Vehicular Ad hoc networks. Dramatic increase in the number of vehicles equipped with computing technologies and wireless communication devices has created new application scenarios. In order to meet performance goals in VANET, several routing protocols have been formulated. Each of the existing routing protocols comes with their pros and cons. In our work we propose a new routing protocol, A Speedy Routing Protocol for Vehicular Ad hoc Network. In this routing protocol we try to reduce overhead of maintaining routing data and traverse preferred distance through shortest path.

Failure handling and recovery under real-time conditions is very crucial. MPLS fast reroute was designed to meet the needs of real-time applications, such as voice over IP. Few of existing solutions handle failure based on single-link failure assumption. Few talk about multiple link failure handling but for a single service path. The proposed solution, MLNF (Simultaneous Multiple Link/Node Failure handling for different service-paths) presents a dynamic solution, which handles simultaneous multiple-link failures as well as node failure that may occur on different service paths. An algorithm and metric is proposed for optimized and prioritized backup path computation. A novel dynamic metric calculation for service path computation is also proposed. Our proposed algorithms are simulated using ns2. The simulation results show that MLNF provides an improvement over existing LDP Reroute method.

Researchers generally believe that nodes in wireless sensor networks (WSNs) are homogeneous, but some sensor nodes of higher energy can be used to prolong the lifetime and reliability of WSNs. This gives birth to the concept of Heterogeneous Wireless Sensor Networks (HWSNs). Clustering is an important technique to prolong the lifetime of WSN and to reduce energy consumption as well, by topology management and routing. HWSNs are very popular in real deployments [1], and have a large area of coverage. In such scenarios, for better connectivity, the need of multilevel clustering protocols arises. In this paper we propose an energy efficient protocol called heterogeneous multilevel clustering and aggregation (HMCA) for HWSNs. We simulate and compare HMCA with existing multilevel clustering protocol EEMC [2] for homogeneous WSN. Simulation results demonstrate that our proposed protocol performs better.

Anomaly detection attempts to recognize abnormal behavior to detect intrusions. We have concentrated to design a prototype UNIX Anomaly Detection System. Neural Networks are tolerant of imprecise data and uncertain information. A tool has been devised for detecting such intrusions into the network. The tool uses the machine learning approaches ad clustering techniques like Self Organizing Map and compares it with the

K

-means approach. Our system is described for applying hierarchical unsupervised neural network to intrusion detection system.

Most existing routing techniques are designed to reduce routing cost by optimizing one goal. In wireless sensor networks one parameter cannot satisfies all requirements of these networks. Therefore, it’s required to consider multiple parameters simultaneously in the routing process for improving performance of the routing protocols. However, the multiple-criteria routing process leads to some increases in complexity f the routing protocol. Recently heuristic methods specially the learning automata were used in the optimization problem. Hence, in this paper, we propose a multi-criteria routing method which uses learning automata to choose the optimum route between the available routes. Results of our simulation present high improvement in compared to the other routing methods.

In Mobile Ad hoc Networks (MANETs) obstruction occurs due to the packet failure and it can be successfully reduced by involving congestion control scheme which includes routing algorithm and a flow control at the network layer. In this paper, we propose to framework and implimentationan agent based congestion control technique for MANETs. In our technique, the information about network obstruction is collected and disseminated by mobile agents (MA). The nodes are classified into four categories based on its traffic class. The MA measures the get in line length of the various traffic classes and the channel disagreement and estimates the total congestion metric to find the minimum congestion level in the network. The congestion metric is applied in the routing protocol to select the minimum congested route. By simulation results, we show that our proposed technique attains high delivery ratio and throughput with reduced delay when compared with the presented technique.

Remote sensing is the most relevant science that permits us to acquire information about the surface of the land, without having actual contact with the area being observed. Amongst the multiple uses of remote sensing, one of the most important has been its use in solving the problem of land cover mapping. Multi spectral classification of remotely sensed data has been widely used to generate thematic Land-Use/Land-Cover maps. Two of the extensively used algorithms for image classification are Self Organizing Feature Maps (SOFM) and Ant Colony Optimization. Although both are bio-inspired optimization techniques, however combining them is a challenging task, especially in the field of remote sensing. In this paper, we have used a Self Organizing Ant Algorithm for Classification of remotely sensed data. Also, we have suggested a new reinforcement factor for the pheromone updation. A test of algorithm is conducted by classifying a high resolution, multi-spectral satellite image of Alwar Region. Results obtained are encouraging.

The demand of security is getting higher in these days due to the development of computers and Internet. In this paper, we proposed a novel image authentication scheme in frequency domain using SHA-1 that allows two parties to exchange images while guaranteeing image authentication, integrity and nonrepudiation from the image sender, over an unsecured channel. The main idea is that at sender end, an image hash of the authenticating image of size 160 bits is generated using SHA-1 and this 160 bits then encrypted by sender’s public key to produce a signature. Then the signature is embedded into cover image in frequency domain along with the authenticating image and creates stego-image with a minimum amount of perceivable degradation to the “cover” media.

Text detection in a color images is a very challenging problem. This paper gives an algorithm for detecting text in images. Experimental results on indoor, outdoor, captcha and Video frames images show that this method can detect text characters accurately. In this paper the proposed algorithm define the unite effect of the advantages of various previous approaches to find out the text, and focus on finding the text. Our experimental result on four different type images show that the technique based on line edge detection is reasonably better than the existing approach. This algorithm has 95.29% recall rate and average computed time is 3.645 second for English text. This is quicker than other existing methods and is robust to language, font- color and size.

Multimedia contents have received a sharp attention now a day as a result of massive development of cyber crime. Illegal replication, violation of authentication, misappropriation of digital content has achieved an enigmatic growth. In this respect we’ve already proposed different schemes for invisible watermarking for color image authentication in fragile domain. In current communication we are going to propose a chip-based framework for color image authentication in accordance with our prescribed LSB scheme. In this watermarking scheme, a secret key will be given to the user and with the help of a particular hash function the user can authenticate the ownership of an image. With the aforesaid secret key and hash function the secured communication is guaranteed. The original watermark will not be retrieved if any intruder tries to perform watermark extraction with an inappropriate key and a incorrect hash function. We named our proposed chip as BLIND CHIP, because we’ve used blind method for watermark extraction where neither the host image nor the watermark image is needed at the time of watermark extraction.

Filtering method is applied to the images corrupted at the time of transmission due to several noises, with varying strengths and different noise probability. Neural network based image filter is one of the most important example of adaptive image filter. Adaptive neural network filter remove various types of noise such as Gaussian noise and impulsive noise. Neural networks are based on the concept of training or learning by examples and have already been applied in several domains of image processing including image filtering. But training of those neural networks consume much time before it is actually tested on such as image filtering. Applying parallelism to image processing is increasingly practical and necessary, as our desktops are becoming multicore machines replacing single core. Therefore, this paper proposes a parallel approach named image decomposition parallel approach to train FLANN (Functional Link Artificial Neural Network). Well trained FLANN is used for rectifying the corrupted pixels to restore the image. Experimental results obtained through SPMD(Single Program Multiple Data) simulation environment show that the proposed parallel approach to train the FLANN is feasible as it substantially reduces the training period and also make it an efficient filter to restore the image fairly well maintaining the quality of the filtered image. Hence, this method is suitable for real time image restoration applications.

Today worldwide, security and data hiding concerns are increasing day by day. Various security devices, systems and algorithms are used at places for the same. Most of these systems are implemented at places like airports, military areas, private or government offices.

Steganography means covered or hidden writing. The objective of steganography is to send message through some innocuous carrier. The message to be sent could be a text, an image or an audio file. Steganography techniques prevent the fact that a secret message is being sent at all.

Steganographic security is mostly influenced by the type of cover media; the method for selection of places within the cover that might be modified; the type of embedding operation; and the number of embedding changes that is a quantity closely related to the length of the embedded data. Given two embedding schemes that share the first three attributes, the scheme that introduces fewer embedding changes will be less detectable.

In India, bilingual documentation is very common especially in government forms and formats, technical documents, reports, postal documents, railways reservation forms etc., Printed documents having a single Indian language often contain English words and numerals since English is considered as a link language in India. The proposed system is designed to recognize bilingual script having Malayalam and English interspersed at word-level. This problem was considered as it is more realistic. Here, a combined database approach is employed, the scripts involved are treated alike and hence a single OCR is sufficient for recognition of bilingual script. The inherent advantage of the system is that the recognition of Malayalam, English words and numerals present in a bilingual document was achieved without performing script identification initially. This method avoids the script identification process which is computationally expensive. The proposed system achieves a recognition rate of 97.5% and 98.5 % for the two feature extraction approaches respectively.

Handoff is an inherent drawback of mobile communication, especially in urban areas, due to the limited coverage of access points (APs) or base stations (BS). It is essential to minimize this delay to provide the user with seamless network coverage. Many people have applied efficient location management techniques in the literature of next generation wireless system (NGWS). However, seamless handoff management still remains an open matter of research. Here we propose to minimize the handoff failure probability by effectively placing a wireless local area network (WLAN) AP in the handoff region between two neighboring cells. The WLAN coverage, on one hand, provides an additional coverage in the low signal strength region, and on the other hand, relieves the congestion in the cellular network. Moreover, we perform the channel scanning within the WLAN coverage area, thus minimizing the handoff failure due to scanning delay.

Remote access of data using off-the-shelf technologies like internet and GSM/GPRS, is one of the fast growing application areas in industries, customer services, banking, entertainment services etc. This paper presents design and implementation of an auto-responder for educational institute. The design is based on GSM Short Message Service and is used for remote access to data related to examination, results and student’s attendance to be accessed by students or any stack holder, at their own wish. The complete application software, including database management, GSM communication and interactive GUI, is designed in MATLAB. The application provides a good example of the use of Information and Communication Technology (ICT) and illustrates how low cost off-the-shelf technologies like GSM can be meaningfully used for remote data access.

Handoff has become a drastic drawback in mobile communication system especially in urban areas owing to the limited coverage area of access points (AP). When a mobile node (MN) moves outside a range of its current access point it needs to perform a link layer handoff. This causes data loss and interruption in communication. In this paper we have proposed a process to minimize the handoff latency with the aid of GPS by minimizing the number of APs to be scanned by the MN during each handoff procedure. We have introduced a new algorithm based on the simplest concept of area. From GPS we can get an idea about the trajectory of motion of the MN and also the position of the neighbor APs. So taking these two factors into consideration we can reduce the scanning delay of the handoff to a great extent and thereby reducing the entire handoff latency.

This paper investigates the distributed self diagnosis problem for wireless sensor networks (WSN). One of the fundamental algorithm design issue for WSN is conservation of energy at each sensor node. A heartbeat comparison based diagnosis model is proposed, which is shown to be energy efficient. Analytical studies and simulation results show that the performance of proposed algorithm is comparable to that of the existing known algorithms in both delay and message count prospective. At the same time, the per-node message overhead is substantially reduced and becomes scalable.

MANET, a multihop mobile adhoc network is comprised of mobile nodes which communicate over radio. Each host is equipped with a CSMA/CA (carrier sense multiple access with collision avoidance) transceiver. Mobile ad-hoc networks are suitable for temporary communication links as they do not require fixed infrastructure. The communication among routers is difficult due to its frequent changing network topology and requires efficient and dynamic routing protocol. This presents comparison of popular broadcast based proactive, reactive and hybrid adhoc routing protocols. Further, the performance of Dynamic Source Routing (DSR), an on-demand, routing protocol based on IEEE 802.11 is examined on performance metrics throughput, end-to-end packet delay, jitter and salvaged packets using QualNet 5.0.2 network simulator.

We propose the Transmitter Based Capacity Enhancement Algorithm for Wireless Ad-hoc Networks using Cross-Layer Design Approach (TCECLD) by dynamically adapting the data rate. The proposed algorithm uses the attributes of Auto-Rate Fallback (ARF) [1] and Receiver Based Auto-Rate (RBAR) [2] control mechanisms with additional practical features to facilitate multipath fading. Like ARF, Acknowledgement (ACK) feedback count is used along with received signal strength for dynamic rate selection. Unlike RBAR, no modification of the Medium Access Control (MAC) frame format is necessary for feedback control since the channel state information is conveyed through Cross-Layer interface. The mechanisms are described to implement the proposal on top of the existing Auto-Rate adaptation scheme in a nearly IEEE 802.11 compliant manner. We also analytically study and characterize the gains in throughput as a function of the channel conditions. Finally an extensive set of simulations are performed on IEEE 802.11b media access protocols to observe the system throughput.

A Wireless Sensor Network (WSN) is an ad-hoc wireless network formed of spatially distributed autonomous sensor nodes which possess the ability of performing computations, communication & executing different sensing tasks. The design & development of wireless sensor nodes is carried out using Bluetooth as wireless networking technology. The use of Bluetooth helps to utilise many features of Bluetooth enabled devices, which could be used as an infrastructure gateways, actuators or user interfaces. A modular design approach is adapted for design & development of wireless sensor node thus making it easy to add, remove or modifying the sensor with much shorter development cycles while also supporting WSN-behavior in terms of power consumption & node operational lifetime. WSN architecture supports different network topologies like Star, mesh & hybrid Star-mesh network. An embedded wireless sensor node is designed & successfully tested for two different Star network formations.

This paper presents WiMAX physical layer threats jamming and scrambling. The performance of the system was found out to greatly differ with the use of different jamming signals, allowing central areas to be identified, where system development should be focused on. In addition, from the basic theory point of view, rather surprising results were also found. The work should give a clear picture of how the studied WiMAX system performs under jamming as well as without the presence of jamming. The results show that some forms of interference degrade the performance of the system rapidly, thus the form of incoming jamming should be known and considered before deploying the system. Noise jamming, multi-carrier jamming and scrambling are discussed here. The issues related to jamming and jamming reduction techniques are also covered. Jamming and scrambling can destroy communication in the targeted area. Multi-carrier jamming is challenge in WiMAX because WiMAX is having OFDM based physical layer. Simulation approach is main concern here. OPNET MODELER is the software used for the simulation purpose.

Orthogonal Frequency Division Multiplexing (OFDM) is a multi-carrier modulation technique having multiple subcarriers which can be overlapped. It finds various applications in wireless communication networks. The main advantages of OFDM are in high rate data communications; but the major hurdle is that is suffers from the Peak-to-Average Power Ratio (PAPR) problem. These causes inter modulation distortion as well as out-of-band spectral growth. Constant envelope OFDM (CE-OFDM) transforms the OFDM signal, to a signal with nearly

zero

dB PAPR. The performance of conventional OFDM system improves with constant envelope OFDM system.

Inspite of K-Means algorithm of clustering problems being widely used, it suffers from problem of initialization of centroids being done randomly. In this paper, we propose a hybrid approach to solve the problem of random initialization of cluster centers or centroids using BBO – a population based evolutionary algorithm motivated by migration mechanism of ecosystems. The paper further determines the optimal number of clusters using different cluster validity indexes such as Rand, Mirkin, Hubert, Jaccard and FM indexes. Experimental results demonstrate that proposed approach outperforms the K-Means, K-Mediod and Gustafson- Kessel clustering algorithms in terms of precision, recall and G-measure.

We introduced a real time Image Processing technique using modern programmable Graphic Processing Units (GPU) in this paper. GPU is a SIMD (Single Instruction, Multiple Data) device that is inherently data-parallel. By utilizing NVIDIA’s new GPU Programming framework, “Compute Unified Device Architecture” (CUDA) as a computational resource, we realize significant acceleration in the computations of different Image processing Algorithms. Here we present an efficient implementation of algorithms on the NVIDIA GPU. Specifically, we demonstrate the efficiency of our approach by a parallelization and optimization of the algorithm. In result we show time comparison between CPU and GPU implementation.

Designing modern circuits comprised of millions of gates is a very challenging task. Therefore new directions are investigated for efficient modeling and verification of such systems. In this paper,we first present the concept of modeling multiple valued ALU. We demonstrate that the approach allows for efficient simulation of complex multiple valued logic systems. Secondly, we show how VHDL can be used to ensure functional correctness. A generalization of binary toggle coverage for the multiple valued logic domains is presented and evaluated. As a test case, a scalable multiple valued logic arithmetic unit is modeled and experimental results for multiple valued logic toggle coverage are given.

Voltage Control Oscillator (VCO) is an integral part of many electronic applications like PLL, clock generation in microprocessors & carrier synthesis in cellular telephones etc. Such applications require different topologies which gives robust high performance. Consequently, VCO design in CMOS technology continues to pose interesting challenges. This paper presents the design of Voltage Control Ring Oscillator with the oscillation frequency up to 1 GHz. The circuit is implemented using Cadence tool in 0.18

μ

m CMOS technology (UMC180) with 1.8V supply. The designed VCO is generating a frequency of 1.06GHz over a temperature range from -40

o

C to 125

o

C, & the linearity is achieved over a range of frequency from 970MHz to 1.03GHz.

Many practical systems are characterized by high uncertainty which makes it difficult to maintain good stability margins and performance properties for closed loop system. In case of conventional control, if plant parameter changes we can not assure about the system performance hence it is necessary to design robust control for uncertain plant. Among the various strategies proposed to tackle this problem, Quantitative Feedback Theory (QFT) has proved its superiority especially in the face of significant parametric uncertainty. The feature of QFT is that it can take care of large parametric uncertainty along with phase information. For the purpose of QFT, the feedback system is normally described by the two-degrees-of freedom structure. A PID controller is a generic control loop feedback mechanism widely used in industrial control systems. A flexible transmission system that has uncertainties in the frictional losses, stiffness of spring and inertial constant is presented using robust PID controller.

In this paper, we use a different viewpoint of flatness which uses a coordinate change based on a Lie-Backlund approach to equivalence in developing flatness-based feedback linearization and its application to the design of controller for formation of Non Holonomic Vehicle. The flat output provides the framework to derive the endogenous feedback compensator, which can result in a constant linear controllable system, for a given nonlinear system. The key contribution of paper is to propose and develop a novel strategy of flatness-based feedback linearization to enhance the stability of formation of the Non Holonomic Vehicle. The proposed flatness-based controller is validated using MATLAB simulation. The simulation results shows that the individual systems maintains the specified geometric pattern and tracks the desired trajectory.

In the general composite nonlinear feedback procedure the control input is assumed to be computed and applied at the same instant. However, the input delay adversely affects the performance of the system. In this paper the high performance controller design based on the predicted states for discrete-time input delay system with disturbance is presented and simulation of yaw angular displacement control of mini-helicopter is illustrated.

The Controller Area Network (CAN) is an asynchronous serial CSMA/CD+AMP communication protocol for microcontrollers networks, supporting distributed real-time control (bit rate up to 1Mbps) with a very high level of security. CAN communication protocol is based on a distributed scheme, there is no central unit, allowing a direct data transfer between any two or more nodes without a master node mediation. A Building Automation System (BAS) is an example of a distributed control system. In this paper, the CAN bus lighting network is implemented with a reliable two wire control which is required for saving energy consumption or, creating precision lighting effects as a subunit of a BAS. Security systems is also interlocked to a building automation system to monitor the secure premises, control the operation of the overall system, and authorize legal entries as well as to trigger the alarm.

A new mixed-mode quadrature oscillator circuit using two dual-X current conveyors (DXCCIIs) and grounded passive components is presented. In the proposed circuit, two quadrature voltage-mode signals and a current-mode sinusoidal waveform are simultaneously available. The oscillation condition and oscillation frequency are independently controllable. Further, electronic tunability i.e. voltage control of the circuit is also discussed. The use of only grounded capacitors makes the proposed circuit suitable for integrated circuit implementation. Results of PSPICE simulation confirm the proposed theory.

In this paper, we present an approach for a 3D building reconstruction from stereo images using local matching techniques. The approach starts with local intensity based stereo matching techniques which utilizes, sum of square differences (SSD) and gradient-based matching techniques. The obtained disparities (left and right disparity) using these matching techniques are filtered out by applying cross-checking algorithm i.e. by comparing left-to-right and right-to-left disparity maps for increasing the reliability of the disparity map. After the aggregation process, the winner-take-all optimization is used to find the optimal disparity map. Furthermore, in order to obtain better disparity, a median filter is adopted for preserving boundary of image and effective removal of noise. The results show that the proposed scheme is reliable, accurate and robust to high resolution aerial images. Results are also compared with the ground data.

Automated fingerprint identification systems (AFIS) are based on techniques to identify an unknown fingerprint with those present in the database. These techniques can be either localized (generally minutiae-based) or globalized (generally transform-based). The current day applications have to deal with large databases and fast processing and hence new techniques with less processing time need to be developed. In this paper we develop a new technique for fingerprint identification which reduces the processing time considerably as compared to standard existing techniques. This techniques is in the frequency domain where coefficients (feature vectors) are generated using Walsh transform. Sectionization techniques are used to reduce the number of feature vectors. Proposed method is evaluated on standard database. The experimental results show that this algorithm could correctly identify fingerprints with accuracy more than 93% in case of larger number of sectors.