017075   Prabhadevi S;Jayavel S;Kapoor R (NO, Nandha Engineering College, Erode, Tamil Nadu, Email: senthil.j@vit.ac.in ) : Algorithm of sentiment analysis for computing machines. J scient ind Res 2015, 74(12), 670-4.

Emotions are a way to think which tune the machinery of the brain. People without emotions are less effective thinkers and decision makers. The concept of artificial intelligence was introduced so that machines can behave just like humans but they remain incomplete without emotions. This study brings out an algorithm for sentiment analysis which may deduce emotional state of the object, it is interacting with. A statistical and probabilistic approach is proposed in this paper to teach the model the essence of emotions using context based learning.

3 illus, 1 tables, 10 ref

017074   Nguyen H V (School of Computer and Communiction, Human Univ, Changsha-410 081, China) : Performance of theory analysis on cost-effective DD-OFDM system for ROF links. J Optics 2015, 44(2), 151-8.

Performance of theory analysis on DD-OFDM system for ROF links has been investigated. The theoretical model of DD Optical OFDM transmission system has been discussed. It consists of fundamentals and mathematical analysis of a typical DD-OFDM system. A typical low-cost DD-OFDM system has been simulated. The results show that the simple structure and low-cost of the DD-OFDM system is attractive for the future cost-effective broadband access networks.

7 illus, 28 ref

017073   Jegatha Deborah L;Sathiyaseelan R;Audithan S;Vijayakumar P (Computer Science and Engineering Dep, Univ College of Engineering Tindivanam, Melapakkam-604 001, Email: sathiyaseelanrec@gmail.com) : Fuzzy-logic based learning style prediction in e-learning using web interface information. Sadhana 2015, 40(2), 379-94.

E-learners' excellence can be improved by recommending suitable e-contents available in e-learning servers that are based on investigating their learning styles. The learning styles had to be predicted carefully, because the psychological balance is variable in nature and the e-learners are diversified based on the learning patterns, environment, time and their mood. Moreover, the knowledge about the learners used for learning style prediction is uncertain in nature. This paper identifies Felder-Silverman learning style model as a suitable model for learning style prediction, especially in web environments and proposes to use Fuzzy rules to handle the uncertainty in the learning style predictions. The evaluations have used the Gaussian membership function based fuzzy logic for 120 students and tested for learning of C programming language and it has been observed that the proposed model improved the accuracy in prediction significantly.

3 illus, 6 tables, 52 ref

017072   Behera U K;Rana D S (Agronomy Div, Indian Agricultural Research Institute, New Delhi-110 012, Email: ukb2008@gmail.com) : Multi-objective optimization and design of integrated farming systems using goal programming. Indian J Agron 2014, 59(3), 460-67.

In the present study, the farmers' problem and their multi-objectives were incorporated in the model by considering a case study under north Indian situations. A generalized farm problem with respect to various physical and socioeconomic constraints under irrigated ecosystem of north India was used for designing the integrated farming systems through goal programming - constraint method of modeling techniques. Maximization of farm income is selected as the main objective of the constraint method of multiobjective optimization and other two objectives, viz. capital requirement and labour employment were used as the additional constraints in the constraint set. Thirty three non-dominated set of alternatives/strategies were formulated by parametrically changing the values of additional constraints. The study revealed that the maximum farm net return of Rs. 6,59,623 was obtained, while the other two objectives, capital requirement and labour requirement were fixed as constraints at Rs. 5,24,926 and 966 man days, respectively. Goal programming can be used as tool for designing individual integrated farming system on scientific basis considering the resource availability at the farm level. The single objective IFS models were developed using linear programming technique for marginal, small and medium farm situations, which proved potential to replace existing rice (Oryza sativa L.)-wheat [Triticum aestivum (L.) emend. Fiori & Paol] system with higher profitability.

1 illus, 2 tables, 19 ref

016059   Tavassoli M;Faramarzi G R;Saen R F (Industrial Engineering Dep, Faculty of Engineering, Khorramabad Branch, Islamic Azad Univ,Khorramabad, Iran, Email: mohammad.tavassoli@ymail.com) : Joint measurement of efficiency and effectiveness using network data envelopment analysis approach in the presence of shared input. Opsearch 2015, 52(1), 490-504.

This paper proposes a novel network data envelopment analysis (NDEA) approach to measure both technical efficiency and service effectiveness of railway transportation services. In particular, railway transportation systems consume varying amounts of shared inputs to produce outputs. The proposed NDEA model represents both the non-storable feature of transportation service and production technologies in a unified framework in the presence of shared inputs. Hence, the proposed model not only measures the overall efficiency of the railways, but also estimates passenger and freight technical efficiency, service effectiveness, and technical effectiveness, simultaneously. A case study validates the proposed model.

3 illus, 4 tables, 34 ref

016058   Musaddiq A;Hashim F;Ujang A B C;Ali B M (Computer and Communication System Engineering Dep, Faculty of Engineering, Univ Putra Malaysia, 43400 UPM Serdang Selangor, Malaysia) : Survey of channel assignment algorithms for multi-radio multi-channel wireless mesh networks. IETE Tech Rev 2015, 12(3), 164-82.

Over the past few years, the wireless mesh network (WMN) with a multi-radio multi-channel (MR-MC) has attracted increasingly high attention because of its wider coverage area. The use of multiple radios and the function of multi-hop forwarding allows WMN to achieve a greater capacity and coverage area. MR-MC can be used to utilize the radio spectrum efficiently. However, the performance of WMN is highly affected by several radios operating at frequencies close to each other. This problem can be solved using one of the key techniques called channel assignment (CA). In this paper, we first present the six main constraints of CA algorithms, i.e., interference, delay, routing, connectivity, congestion, and link scheduling. Then, various CA techniques proposed in the literature to improve the performance of WMN are discussed in detail.

5 illus, 7 tables, 63 ref

016057   Malgwi Y M;Blamah N V (Computer Science Dep, Modibbo Adama Univ of Technology, Yola, Adamawa State, Nigeria) : Multi-agent based agile (XP) software development process scheduling model. Int J pure appl Sci Technol 2015, 29(2), 54-63.

User requirements during software development keep changing due to evolving business needs. Most Users do not have clear vision about the specification of their requirements at the early stage. In such changing environment agile development methodology is suited. In this paper, a multiagent based approach to process scheduling was adopted, where each activity is viewed as an autonomous and flexible agent process. Crucial for the multiagent based system in project scheduling, is the availability of an effective model and algorithm for scheduling of task. The developed model (Multi-agent based System) provides an optimized and flexible agile process scheduling and reduces overheads in the software process as it responds quickly to changing requirements without excessive rework in project scheduling.

5 illus, 2 tables, 9 ref

016056   Kwon J B (Computer Science and Engineering Dep, Sun Moon Univ, Asan-336 708) : Exploiting storage class memory for future computer systems. IETE Tech Rev 2015, 12(3), 218-26.

Various emerging resistive memory technologies, such as phase change memory, have drawn attention in recent decades because they provide persistency, byte-addressability, low latency near that of DRAM, and high density. Storage-class memory (SCM) is the class of these memory technologies that have the best memory and storage properties. SCM can be accessed directly via load and store instructions because it is placed on a memory bus. In this paper, we introduce SCM in the context of emerging non-volatile memory technologies and review the efforts that have been made to utilize SCM in computer systems and exploit it for performance or reliability purposes. We also discuss the challenges and opportunities that accompany adopting SCM in computer systems. We focus more on issues of exploiting SCM because its potential for computer systems and applications is substantial, and accordingly, many more studies are expected.

4 illus, 52 ref

016055   Emam O E;Salama S E;Youssef A M (Information System Dep, Faculty of Computers and Information, Helwan Univ, P.O. Box 11795, Egypt) : Decomposition algorithm for solving chance constrain bi level multi objective large scale quadratic programming problem. Int J pure appl Sci Technol 2015, 28(2), 77-87.

This paper solves a bi-level multi objective large scale quadratic programming problem with stochastic parameters in the constraints (SBLMOLSQPP). We solve this problem usingan algorithm that begins with transforming the probabilistic nature to equivalent deterministic of this problem, thenTaylor series is used to overcome the complexity of the quadratic problem. Finally, an illustrative numerical example is given to clarify the developed theory.

1 table, 13 ref

016054   Emam O E;Abdel-Fattah M A;Suleiman H A (Information Systems Dep, Faculty of Computers and Information, Helwan Univ, P.O. Box 11795, Egypt, Email: emam_o_e@yahoo.com) : On bi-level multi-objective large scale quadratic programming problem. Int J pure appl Sci Technol 2015, 29(1), 31-41.

This paper presents a bi level large scale multi objective quadratic programming problem (BLLSMOQPP) with fuzzy parameters in the objective functions problem. In the first phase convert the fuzzy parameters of the problem to equivalent crisp problem to make it easy in solving. In the second phase use Taylor series to convert the quadratic problem to linear problem to be easy for solving with the decomposition algorithm that deals with large scale constraint. In addition, a numerical example is provided to demonstrate the correctness of the proposed solution.

16 ref

016053   Das P;Roy T (Applied Mathematics Dep, Indian Institute of Engineering Science and Technology, Shibpur, Howrah-711 103, Email: mepintudas@yahoo.com) : Generalized riser design by parametric fuzzy geometric programming. Int J pure appl Sci Technol 2015, 27(1), 11-16.

Optimal design of risers for castings has been the subject of numerous investigations and this paper determines the optimal dimensions when Chvorinov's rule for solidification is obeyed by both the riser and casting and solidification time is the only constraint involved. This problem can be formulated to minimize the riser volume subject to the constraint that the riser solidification time is greater than or equal to the casting solidification time. The problem is solved using the Fuzzy geometric programming technique and generalized expressions were obtained for H_R, D_R and V_R. These expressions were applied to a cylindrical top riser, cylindrical side riser, hemispherical riser and modified hemispherical riser.

1 table, 19 ref

016052   Ayokunle T B;Ogah U S;Binitie A P (Computer Sciences Dep, Federal Polytechnic, Mubi, Adamawa State, Nigeria, Email: philphat4@gmail.com) : Encryption and decryption of messages using advanced encryption standard and system of nonlinear equations. Int J pure appl Sci Technol 2015, 27(1), 1-10.

Encryption which is the coding or scrambling of information so that it can only be decoded and read by someone who has the correct decoding key has been in existence in various forms for thousands of years. Businesses, Government, Individuals, use encryption to protect their personal or secret information against unauthorized users. Despite the existence of various means of safeguarding our data against unauthorized users, Cooperate bodies, Individuals, Government agencies and parastatals kept losing their personal and secret data to Fraudsters. The study deals with encrypting and decrypting messages using Advanced Encryption Standard and System of Nonlinear Equations. In this study, Advanced Encryption Standard (AES) was introduced, which uses 128-block size as its key size. An algorithm was developed to secure messages transmission and then converted the messages into nonlinear algebraic systems of equations, which are then solved by Gaussian elimination method. The results obtained were compared with those produced by Direct Jahick Symmetric Key Algorithm (DJSA) and it was observed that they produced better result. Also it is almost impossible to break the Encryption algorithm without knowing the exact key value. This method is recommended for sending confidential data in any type of public application. Also it provides alternative to all unsecured methods of sending messages across the network.

7 ref

015032   Zhou M;He S;Hu B;Zhang Q (Control Science and Engineering Dep, College of Communication Engineering, Jilin Univ, Changchun, China) : Modified KP model for hysteresis of magnetic shape memory alloy actuator. IETE Tech Rev 2015, 32(1), 29-36.

Hysteresis characteristic can significantly decrease the control accuracy of magnetic shape memory alloy actuator. To describe the hysteresis between input signal and the output signal of the magnetic shape memory alloy actuator, a modelling method based on the modified Krasnosel'skii-Pokrovskii kernel is developed in this paper. The density parameters of the adopted hysteresis model are identified by the recursive least square method. The simulation results reveal that the proposed method has a good performance in describing the hysteresis modelling of magnetic shape memory alloy actuator and the modelling accuracy can be further improved by adjusting the number of Krasnosel'skii-Pokrovskii kernel. The result showed that the adopted modelling method can accurately describe the hysteresis characteristic of the magnetic shape memory alloy actuator, and the maximum modelling error can be reduced to 0.0022 mm when the number of discretization lines is selected as L = 15.

15 illus, 28 ref

015031   Wang J;Li Y (School of Communication and Information Engineering, Univ of Electronic Science and Technology of China, ChengDu, China) : Novel model of computation for software synthesis based on data frame driving. IETE Tech Rev 2015, 32(1), 70-8.

Software synthesis is a useful technology to accelerate the design of digital systems, and the MoC (model of computation) is the foundation of software synthesis. Current researches on MoC mainly focus on the situations that the produced data frames are used only once by its downstream module. However, for some applications with loops, the data frame produced by upstream module needs to be reused and thus the current MoCs cannot be directly used to synthesize these applications' DFG (data flow graph). To solve this problem, a novel MoC based on data frame driving is proposed for software synthesis in this paper. In our MoC, the DFG with loops is first transformed into an acyclic DFG and modules in the acyclic DFG are divided into different levels that define the priority of modules. Then, the schedule can be generated according to the modules' level. The proposed MoC is verified under both random generated DFG and real-world application's DFG. The experimental results show that by using the proposed MoC, the schedule for DFG with reused data frame can be generated for both single processor system and multi-processors system, and it thus can be used as a useful tool to aid the software synthesis.

6 illus, 8 tables, 19 ref

015030   Vobugari S;Somayajulu D V L N;Subaraya B M (Computer Science and Engineering Dep, National Institute of Technology, Warangal) : Dynamic replication algorithm for data replication to improve system availability: a performance engineering approach. IETE J Res 2015, 61(2), 132-41.

Information technology systems deployed by enterprises should not only fulfil their business functionalities but also cater to Quality of Service concerns such as Availability, Scalability, and Performance. To enhance the system performance, the system availability is an important factor and to improve the system availability, one of the strategies is replicating the frequently accessed data to multiple suitable locations which is a practical choice as the users can access the data from a nearby site. This is, however, not the case for replicas which must have a preset number of copies on several locations. How to decide a sensible number and right location for replicas have become an important issue in cloud computing. In this paper, we show a dynamic data replication strategy to enhance the performance of software system. To identify the suitable file to replicate and to decide respective number of replicas, we calculate popularity degree and replica factor. We use the fuzzy logic system to identify the system to place the replicas and we use the round robin method to place the replicas in the identified systems. We compare the performance of our technique with the existing technique.

7 illus, 28 ref

015029   Sood R;Garg A (M M Institute of Computer Technology and Business Management, Maharishi Markandeshwar Univ, Mullana, Ambala, Haryana, Email: roopalisood@yahoo.com) : Adaptive retransmission scheme for traffic steering in wireless networks. Int J appl Res Inf Technol Comput 2016, 6(2), 124-32.

Drastic increase in mobile broadband traffic is leading to the voluminous demand of growing size and speed of networks. There exists a paradigm shift in network communication and technologies. Thus network coverage is not the prime problem rather capacity management is a prime issue to be tackled by operators. The paper focusses on flow control mechanism based on fuzzy logic. It analyses the dynamic real-life environment for different traffic flows (video, image and data) and calculates the sending rate. It is very important to predict and model the rate at which the packets are being transferred in heterogeneous networks. An intelligent algorithm, fuzzy-controlled traffic steering (FCTS) is introduced in the paper which would help in making a decision for controlling flow rate depending on packet loss thereby controlling packet retransmissions and switching or redirecting traffic to smaller cells based on the flow rate and traffic load on the existing network.

10 illus, 2 table, 10 ref

015028   Sheshasaayee A;Angela Deepa V R (PG and Reseach, Computer Science Dep, Quaid-E-Millath Governement COllege for Women, Chennai-600 002, Email: angelrajan.research@gmail.com) : Relative analysis on machine learning approach for effective POS tagging of Tamil language. Int J appl Res Inf Technol Comput 2016, 6(2), 118-23.

Process of identifying a suitable tag for each word in a document which articulates an analogous meaning in a particular context is termed as part-of-speech (POS). This process plays a key role in building an effective natural language processing (NLP) application. Morphological complexity and the varying grammatical constructs lead to a variety of approaches for tagging. For a highly agglutinative language like Tamil different approaches have been used for POS tagging, which include rule-based, stochastic or transformation-based learning approaches. This article deals with memory-based language processing (MBLP), a novice approach to NLP based on a symbolic machine learning method termed as memory-based learning (MBL). MBLP is like a support vector machine (SVM) in which the approach is language processing based on the idea guided by the direct reuse of memory traces of earlier language experiences rather than by rules extracted from such experiences. This article reflects the scope of differences that narrate the new way of dealing with taggers in Tamil language through a comparative study of the MBLP and SVM used in languages like Dutch and Malayalam.

3 illus, 15 ref

015027   Shaikh R A;Thayananthan V (Computer Science Dep, King Abdulaziz Univ, Jeddah, Saudi Arabia) : Hop-by-hop trust evaluation algorithm for identity anonymous sensor networks. IETE J Res 2015, 61(2), 154-9.

Most of the existing trust models that are proposed for wireless sensor networks are based on the assumption that the sensor nodes have unique identities. Evaluating trust in an identity anonymous resource constraint environment is an open research problem. In this work, we propose a first novel hop-by-hop trust evaluation algorithm (H-TEA) that operates in the identity anonymous wireless sensor network environment. Simulation results show that the H-TEA scheme reduces communication overhead and energy consumption of sensor nodes at the cost of increased delay in the network. That makes it suitable to use for non-time-critical applications.

4 illus, 11 ref

015026   Ravisankar H;Subbaiah Y;Murthy T G K (NO, Central Tobacco Research Institute, Rajahmundry, Andhra Pradesh-533 105, Email: hravisankar@india.com) : Decision support system for transfer of technology on FCV tobacco production. Int J appl Res Inf Technol Comput 2016, 6(2), 94-9.

Decision support systems (DSS) play an important role in tobacco production and trade which has been valued more for its farm income, employment and revenue generating potential. Tobacco production depends on the internal and export demands and quality requirements of the importing countries. The primary goal of DSS research is to provide information to researchers, decision makers and farmers, so that they can make better decisions in order to take advantage of market opportunities and manage continuous changes in their production systems. Though information and communication technology (ICT) offers many options for improving extension efficiency, the challenge seems to be 'How to find quickly the most relevant and reliable knowledge and information suitable to specific situations'. Emerging information needs of Flue Cured Virginia (FCV) tobacco farmers are many including profitable technological options, crop diversification, quality specifications, decision on resource use and feasible off-farm income generation options. Keeping this in view, a DSS was developed which is broadbased, demand driven and farmer accountable for effective transfer of technology in FCV tobacco production. This system is useful for the extension workers and farmers to retrieve instant information on various technologies developed under different agro-climatic conditions and their implementation in detail. The DSS will enable farmers to become part of the information flow process rather than waiting for the information to be presented through other ICT.

4 illus, 10 ref

015025   Rahman M M;Bhuiyan M A A (Computer Science and Engineering Dep, Jatiya Kabi Nazrul Islam Univ, Bangladesh, Email: mijankkniu@gmail.com) : Comparison study and result analysis of improved back-propagation algorithms in Bangla speech recognition. Int J appl Res Inf Technol Comput 2016, 6(2), 107-17.

This research is concerned with the study of different improved and faster back-propagation (BP) algorithms of neural networks and the analysis of recognition result in continuous Bangla speech. For speech recognition, a comparison study on neural networks and speech recognition result analysis with different improved and faster BP algorithms (such as, BP with momentum, variable learning rate BP, resilient BP, conjugate gradient BP and Levenberg-Marquardt BP algorithms) have been done. In this research, the MATLAB Neural Network Toolbox 7.12.0 is used to create, train and simulate the feedforward neural network with the BP learning algorithm. The convergence obtained from standard BP algorithm is very slow; that's why, this research proposes different improved and faster BP algorithms to solve the speech recognition problems. The developed system has been justified by several networks trained with different Bangla speech words. To test the performance of the system, 20 samples of 50 Bangla speech words have been used; from which 10 samples of 50 words are used as training pattern and another 10 samples of 50 words are used as testing pattern in the network. The binary features of speech words have been generated using dynamic thresholding algorithm. The recognition system has been achieved recognition rate of 83% using resilient BP algorithm, 90% using conjugate gradient BP algorithm and 90% using Levenberg-Marquardt BP algorithm, respectively, for recognising 50 speech words.

6 illus, 1 table, 35 ref

015024   Mohbey K K;Thakur G S (Computer Application Dep, Maulana Azad National Institute of Technology, Bhopal) : Interesting user behaviour prediction in mobile E-commerce environment using constraints. IETE Tech Rev 2015, 32(1), 16-28.

Mobile e-commerce has become a more emerging topic these days and is speedily increasing with the growth of internet. It is playing an essential role in our life as it helps us by using new trends and technologies to improve business and thus providing quicker information. Behaviour analysis and sequence pattern prediction provide scope for more advanced research topics. If a user finds various interesting sequences in mobile e-commerce environment, then she/he can predict lots of new information. This predicted information may be useful for defining various new services or improving on existing and may also be useful to manage service infrastructure to offer quicker responses. Today, user behaviour sequence mining is an emerging issue in mobile e-commerce environment which considers mobile user services, accessing sequences at various locations on different times. In the current scenario, the user may only be interested in the service sequences with some specific constraints. The constraint may define to the type of service or importance of a particular service. Here, we consider important or useful services for particular user in mobile e-commerce environment. We proposed an efficient framework, namely CIUBSM (Constraint based Interesting User Behaviour Sequence Mining) which deals with important constraint of services and generates an interesting behaviour sequence of mobile users. Experimental results show that the proposed framework is better than previous constraint-based frameworks.

8 illus, 11 tables, 50 ref

015023   Kolivand H;Alhajhamad H;Sunar M S (NO, MaGIC-X (Media and Games Innovation Centre of Excellence) UTM-IRDA Di, 81310 Skudai, Johor, Malaysia, Email: shahrizal@utm.my) : Shadow generation in mixed reality: a comprehensive survey. IETE Tech Rev 2015, 32(1), 3-15.

This paper provides an overview of the issues and techniques involved in shadow generation in mixed reality environments. Shadow generation techniques in virtual environments are explained briefly. The key factors characterizing the well-known techniques are described in detail and the pros and cons of each technique are discussed. The conceptual perspective, the improvements, and future techniques are also investigated, summarized, and analysed in depth. This paper aims to provide researchers with a solid background on the state-of-the-art implementation of shadows in mixed reality. Thus, this could make it easier to choose the most appropriate method to achieve the aims. It is also hoped that this analysis will help researchers find solutions to the problems facing each technique.

8 illus, 1 table, 63 ref

015022   Harsimran Kaur;Sharma A (CEA, GLA Univ, Mathura, Uttar Pradesh, Email: harsimaran.31@gmail.com) : Extended use case for specification of NFRs. Int J appl Res Inf Technol Comput 2016, 6(2), 100-6.

Evolution of unified modelling language (UML) is absolutely required to make sure that UML will stay up to date with the latest developments in the software industry like modeling non-functional requirements (NFRs). In the past NFR literature many techniques have been identified that have used UML for modelling NFR. Because of great diversity in number and types of NFR it is difficult to be handled by common modelling techniques. So we think of extension of Use Case so that it can more effectively address the changing needs of many different classes of users and NFRs which further assists in specification and quantification of NFR.

4 illus, 3 tables, 23 ref

015021   Anjaneyulu G S G N;Gayathri M;Gopinath G (SAS, VIT Univ, Vellore) : Analysis of advanced issues in mobile security in android operating system. Archiv appl Sci Res 2015, 7(2), 34-8.

Today's era mobile security has become a big issue in day today life. Most of the people want to use smart phones for communication, planning and organizing their schedule for their private life. These technologies are causing profound changes in the organization of information system. Android has been changed in mobile market. Now most of the people are using smart phones for their digital life - email, social networking, important messaging, photo and video sharing and etc. Smartphone are very attractive for users as well as attackers. Most of the attackers are using hacking techniques to get private information about their personal life that is directly generated money for the attackers. It is up to the Smartphone operating system to ensure the security of data in device. In last two years Android became a most popular operating system in the mobile market. For these mobile device is activating over 1.5 million as per day. Android is expected to cross the 1 billion active device barriers in 2013. It covers 70% percent of the mobile market. In this paper we discuss about Android operating system security which has been developed for mobile phones. Android Application development, layered Approach and details of security information for android also an Android Application Sandbox. Which is used for perform both static and dynamic analysis on android programs.

4 ref

015020   Amandeep Kaur;Josan G S (NO, , Computer Engineering Dep, Patiala, Punjab, Email: amandhillon83@yahoo.co.in ) : Nested named entity recognition in Punjabi text. Int J appl Res Inf Technol Comput 2016, 6(2), 84-93.

Nested named entities are very useful in named entity recognition (NER) research as they help in identifying entity relationships and internal semantics of entities. But still the recognition of nested structures has been highly ignored in NER research. This paper presents nested NER research conducted for Punjabi language. As there is no standardised nested named entity (NE) tagset defined in literature so a nested NE tagset comprising of 22 nested cases have been formulated from the annotated corpus prepared for Punjabi NER research. This annotated corpus was re-annotated with nested NEs using proposed nested tagset with a joined label tagging and various experiments have been conducted using different feature combinations. The feature set that has shown the highest f-score value of 91.30% consists of context word window 7, POS (parts of speech) information, length of word, digits information, prefixes and suffixes, gazetteers, and context patterns as features.

4 tables, 12 ref

014016   Padmanabhan J;Premkumar M J J (Computer Technology Dep, MIT, Anna Univ, Chennai) : Machine learning in automatic speech recognition: a survey. IETE Tech Rev 2015, 32(4), 240-51.

Over the past few decades, there has been tremendous development in machine learning paradigms used in automatic speech recognition (ASR) for home automation to space exploration. Though commercial speech recognizers are available for certain well-defined applications like dictation and transcription, many issues in ASR like recognition in noisy environments, multilingual recognition, and multi-modal recognition are yet to be addressed effectively. A comprehensive review of common machine learning techniques like artificial neural networks, support vector machines, and Gaussian mixture models along with hidden Markov models employed in ASR is provided. A thorough review on the recent developments in deep learning which has provided significant improvements in ASR performance, along with its relevance in the future of ASR, is also presented.

2 illus, 81 ref

014015   Liao B;Xu J;Lv J;Zhou S (School of Electronic and Electricity Engineering, North China Electric Power Univ, Beijing 102206, China) : Image retrieval method for binary images based on DBN and softmax classifier. IETE Tech Rev 2015, 32(4), 294-303.

Currently, the common methods for image retrieval are content-based, while the abilities of image feature representation of these methods are very limited. In this paper, a new image retrieval method for binary images based on Deep Belief Networks (DBN) and Softmax classifier is proposed, which classifies the image data-set into some categories with the DBN and Softmax classifier first, and then classifies the query image in the same way, and those images in the same category will be returned as the similar images of the query image. Unlike the existing image retrieval models, the new method aims to provide a more effective representation and extraction measure by simulating the architecture of human visual system, and it is not necessary to set the threshold manually for this method like most of the existing methods based on the hamming distance computation. Experimental results show that the proposed method can get better recall and precision than some existing methods, such as perceptual hash algorithm and shape-based algorithm.

11 illus, 28 ref

013006   Song J;Guo C;Zhang Y;Zhu Z;Yu G (Software College, Northeastern Univ, Shenyang-110 819, China) : Research on mapreduce based incremental iterative model and framework. IETE J Res 2015, 61(1), 32-9.

In the big data environment, MapReduce could be adopted to improve the efficiency of iterative algorithm on massive data through running the iterative algorithm on larger PC-cluster. However, it is inefficient if the entire data has to be re-iterated when new data is introduced. In this paper, the incremental iterative computing model (I2M) based on the incremental data and original iterative results is proposed. Then, the MapReduce and I2M based descendant query, PageRank, and K-means, are enumerated. Finally, incremental iterative computing framework (I2F) is implemented by extending HaLoop to support incremental iterative computing. A series of test cases are designed to evaluate I2F on functionality, performance, and cost of incremental iteration. The incremental iterative model proposed in this paper can adapt many iterative algorithms, and promotes the application and optimization of iterative algorithm in the big data environment.

5 illus, 2 tables, 19 ref

013005   Kumar V;Chhabra J K;Kumar D (CSE Dep, Manipal Univ, Jaipur, Rajasthan) : Automatic unsupervised feature selection using gravitational search algorithm. IETE J Res 2015, 61(1), 22-31.

Feature selection is an optimization problem that selects the features that have minimum redundancy and maximum relevance to improve the efficiency of algorithms. In this paper, we have proposed a novel automatic unsupervised feature selection method based on gravitational search algorithm, called AFSGSA (automatic feature selection using gravitational search algorithm). In contrast to most of existing unsupervised feature selection techniques, the proposed AFSGSA requires no prior knowledge of the data to be classified and number of features to be selected. AFSGSA determines the optimal number of features of the data-set on the run. Statistical property of data-set is used to develop a novel threshold setting concept to refine the features. A novel fitness function is also proposed to make the search more efficient. The performance of AFSGSA has been compared with recently developed well-known feature selection techniques. The experimental results reveal the efficiency and efficacy of the proposed feature selection technique over other existing techniques.

1 illus, 9 tables, 46 ref

013004   Jayanthiladevi A;Kadharnawaz G M (NO, Jain Univ, Bangalore, Email: greendaank@gmail.com) : Efficient utilization of spectrum in seamless mobility by using retransmission rerouting mechanism in mobile IP. J scient ind Res 2015, 74(9), 489-93.

Without an iota of doubt, the aspect of seamless mobility has become an important characteristic for high-fidelity wireless communication. As handy and trendy cell phones / smart phones are primarily used for the communication purpose, the cell coverage zones are mandated to be of high quality and adaptively to make and receive calls with all clarity and confidence. Usually, the seamless mobility capability is being achieved through the automatic handover from one cell to another under certain situations. The aspect of automatic handover is the process of adaptively changing the connection linkage established and being currently used to another connection even when the user is still talking. This channel shift is initiated often when crossing a borderline of the cell or if there is a substantial downturn in the receiving signal quality in the current channel. Mobile IP too has to reinforce the redirect the data to new foreign agent after the access of the network changes according to a particular sequence to hold up the seamless mobility. In this case, there is an additional delay caused by the redirection and in some cases, retransmission of the original data. The ideal case is therefore that the service interruption has to be extremely minimal to ensure the quality of experience (QoE). Therefore minimizing the unwanted delay handover process is being insisted everywhere for keeping up the connectivity anytime and anywhere across communication networks.

1 illus, 6 ref

013003   Hussain S Z;Shetty S D (Computer Science Dep, BITS Pilani, Dubai Campus, Email: skcs10814@gmail.com) : Spatial data analysis on the cloud. Int J Geomatics Geosci 2015, 6(1), 20-3.

Spatial Data is usually big data and requires large amount of computing power, space and specialized features for its analysis. Thus, the scientists at ESRI came up with an open source project, GIS Tools for Hadoop on GitHub. The project aims at integrating the distributed computing power of Hadoop and the specialized geometry libraries provided by ARCGIS to perform Big Data Spatial Analysis. In this paper, we have further explored this ESRI Project on the Amazon EC2 cloud. Thus, we conclude that a trio of ArcGIS, Apache Hadoop and Cloud can miraculously improve the quality of spatial data analysis if given a chance.

4 ref

013002   Ghuli P;Shukla A;Kiran R;Jason S;Shettar R (CSE Dep, R.V.College of Engineering, Bangalore, Karnataka) : Multidimensional canopy clustering on iterative mapreduce framework using Elefig tool. IETE J Res 2015, 61(1), 14-21.

A number of applications today deal with the processing and analysis of Big Data. As the size of the data increases, it becomes important to process it to reveal many new and interesting patterns. One such task of processing huge data is to group records into logical clusters. Most of the clustering algorithms are iterative in nature. Hence, these clustering algorithms exceptionally outperform if modelled using iterative distributed framework like Twister. Here, a canopy clustering algorithm was modelled as a series of MapReduce jobs. Once the overlapping canopies are generated, k-means clustering is applied to form actual clusters. A comparative study was performed on the variants of MapReduce framework like Twister and Hadoop. Experimental results show that, even for a large number of data points, the implementation of canopy clustering on Twister was more than three times as fast as its implementation on Hadoop. The speedup of canopy clustering using Twister was considerable - more than 24 times faster as compared to the implementation of a k-means algorithm on Hadoop. In addition to this, a new tool called Elefig is designed to facilitate the master node to automatically find the location of slave nodes in a Hadoop cluster. Without Elefig tool, one has to manually fix the problem by updating the hosts file on each node of the cluster whenever cluster is booted up.

8 illus, 3 tables, 12 ref

013001   Dhavale S V;Deodhar R S;Pradhan D;Patnaik L M (Computer Science and Engineering Dep, Defence Institute of Advanced Technology, Girinagar, Pune-411 025) : State Transition based embedding in cepstrum domain for audio copyright protection. IETE J Res 2015, 61(1), 41-55.

In this paper, authors propose a new state transition based embedding (STBE) technique for audio watermarking with high fidelity. Furthermore, we propose a new correlation based encoding (CBE) scheme for binary logo image in order to enhance the payload capacity. The result of CBE is also compared with standard run-length encoding (RLE) compression and Huffman schemes. Most of the watermarking algorithms are based on modulating selected transform domain feature of an audio segment in order to embed given watermark bit. In the proposed STBE method instead of modulating feature of each and every segment to embed data, our aim is to retain the default value of this feature for most of the segments. Thus, a high quality of watermarked audio is maintained. Here, the difference between the mean values (M_diff) of insignificant complex cepstrum transform (CCT) coefficients of down-sampled subsets is selected as a robust feature for embedding. M_diff values of the frames are changed only when certain conditions are met. Hence, almost 50% of the times, segments are not changed and still STBE can convey watermark information at receiver side. STBE also exhibits a partial restoration feature by which the watermarked audio can be restored partially after extraction of the watermark at detector side. The psychoacoustic model analysis showed that the noise-masking ratio (NMR) of our system is less than -10dB. As amplitude scaling in time domain does not affect selected insignificant CCT coefficients, strong invariance towards amplitude scaling attacks is also proved theoretically. Experimental results reveal that the proposed watermarking scheme maintains high audio quality and are simultaneously robust to general attacks like MP3 compression, amplitude scaling, additive noise, re-quantization, etc.

13 illus, 6 tables, 21 ref

013000   Chen C L;Chen C C;Li D K;Chen P Y (Computer Science and Information Engineering Dep, Chaoyang Univ of Technology, Taichung, Taiwan) : Verifiable and secret buyer- seller watermarking protocol. IETE Tech Rev 2015, 32(2), 104-13.

A trusted third party (TTP) is introduced to the buyer-seller protocol to guarantee the transaction fairness in protocol. However, the TTP practically increases the cost in the buyer-seller protocol. To address this issue, we propose a novel buyer-seller watermarking protocol to eliminate the need for a TTP. By dividing the buyer's secret key into two primary mechanisms: the buyer's watermark, embedded in digital content, and the transaction number produced by the seller; the seller can verify buyer's watermark without decryption. After inserting a digital watermark from the seller, the buyer cannot remove the watermark from the digital content without a watermark extraction algorithm. The seller cannot fabricate piracy to frame an innocent buyer. When piracy is found, it can be traced clearly because of the privacy homomorphism property. In other words, the proposed protocol can trace piracy and protect the customer's rights without a TTP. Therefore, the conspiracy problem can be solved. The proposed protocol also can protect the anonymity of the buyer and bind the buyer's watermark to digital content. Moreover, the buyer is no longer required to participate in the dispute resolution in our scheme.

4 illus, 1 table, 20 ref

012999   Bakariya B;Thakur G S (Computer Applications Dep, Maulana Azad National Institute of Technology, Bhopal) : Efficient algorithm for extracting high utility itemsets from weblog data. IETE Tech Rev 2015, 32(2), 151-60.

High utility itemset refers to those set of items which has high utility such as profit in a database. High utility of itemset plays a crucial role in real life. In recent years, various algorithms have been proposed for finding high utility itemset but unfortunately they are not completely relevant at the time and space point of view. In the data mining field, high utility itemset can be found in different categories of data like time series, categorical, etc. Log data is useful for finding behaviour of the user in different aspects. In this paper, we have proposed an algorithm named HUIM (High Utility Itemsets Mining) and construct HUI-FP (High Utility Itemsets-Frequent Pattern) Tree for efficiently mining high utility itemsets from log database. The behaviour of the user can be predicted through the high utility of every visited page. We have also proposed pattern generation technique based on cosine similarities among itemsets. These techniques generate strong patterns, and customized users profile according to that pattern. The proposed algorithm is better than the previous state of the art algorithm for high utility itemset generation.

8 illus, 5 tables, 32 ref

011976   Vishnu Sankar M;Ravindran B (Computer Science and Engineering Dep, Indian Institute of Technology, Madras, Chennai-600 036, Email: vishnusankar1512@gmail.com) : Parallelization of game theoretic centrality algorithms. Sadhana 2015, 40(6), 1821-43.

Communication has become a lot easier with the advent of easy and cheap means of reaching people across the globe. This has allowed the development of large networked communities and, with the technology available to track them, has opened up the study of social networks at unprecedented scales. This has necessitated the scaling up of various network analysis algorithms that have been proposed earlier in the literature. While some algorithms can be readily adapted to large networks, in many cases the adaptation is not trivial. In this work, we explore the scaling up of a class of node centrality algorithms based on cooperative game theory. These were proposed earlier as an efficient alternatives to traditional measure of information diffusion centrality. We present here distributed versions of these algorithms in a Map-Reduce framework, currently the most popular distributed computing paradigm. We empirically demonstrate the scaling behavior of our algorithm on very large synthetic networks thereby establishing the utility of these methods in settings such as online social networks.

4 illus, 12 tables, 19 ref

011975   Veningston K;Shanmugalakshmi R;Nirmala V (Computer Science and Engineering Dep, Government College of Technology, Coimbatore, Email: veningstonk@gct.ac.in) : Semantic association ranking schemes for information retrieval applications using term association graph representation. Sadhana 2015, 40(6), 1793-1819.

Most of the Information Retrieval (IR) techniques are based on representing the documents using the traditional vector space and probabilistic language model i.e., bag-of- words model. In this paper, associations among words in the documents are assessed and it is expressed in Term Association Graph model to represent the document content and the relationship among the keywords. Earlier attempt on exploiting term association graph was done for non-personalized document re-ranking task. This paper experiments improved non-personalized and personalized re-ranking strategy which exploits term association graph data structure to assess the importance of a document for the user query and thus documents are re-ranked according to the association and similarity exists among the documents. This paper proposes various approaches under two models namely, Term Rank based Approach (TRA) and Path Traversal based Approaches (PTA1, PTA2, and PTA3). These approaches employ term association graph and has been evaluated using manually prepared real dataset and benchmark OHSUMED dataset. The results obtained are reasonably promising.

16 illus, 12 tables, 47 ref

011974   Singh P;Verma A;Chaudhari N S (Electronics and Instrumentation Engineering Dep, Institute of Engineering and Technology DAVV, Khandwa Road, Indore-452 017, Email: prat_ibh_a@yahoo.com ) : Feature selection based classifier combination approach for handwritten Devanagari numeral recognition. Sadhana 2015, 40(6), 1701-14.

In this paper a method for the recognition of handwritten Hindi numerals is presented. The paper is reporting the effectiveness of the proposed approach, which is utilizing the feature selection based on the Information theory measures. The Multilayer Perceptron (MLP) based classifier combination is used along with feature selection using two criterion functions: (i) Maximum relevance minimum redundancy and (ii) Conditional mutual information maximization. Conditional mutual information based feature selection when driving the ensemble of classifier produces improved recognition results for most of the benchmarking datasets. The improvement is also observed with maximum relevance minimum redundancy based feature selection when used in combination with ensemble of classifiers. The main contribu-tion of the proposed method is that, the method gives quite efficient results utilizing only 10% patterns of the available dataset.

5 illus, 7 tables, 19 ref

011973   Sait S Y;Bhandari A;Khare S;James C;Murthy H A (Computer Science and Engineering Dep, Indian Institute of Technology Madras, Chennai-600 036, Email: cyriac83@gmail.com) : Multi-level anomaly detection: relevance of big data analytics in networks. Sadhana 2015, 40(6), 1737-67.

Internet has become a vital source of information; internal and external attacks threaten the integrity of the LAN connected to the Internet. In this work, several techniques have been described for detection of such threats. We have focussed on anomaly-based intrusion detection in the campus environment at the network edge. A campus LAN consisting of more than 9000 users with a 90 Mbps internet access link is a large network. Therefore, efficient techniques are required to handle such big data and to model user behaviour. Proxy server logs of a campus LAN and edge router traces have been used for anomalies like abusive Internet access, systematic downloading (internal threats) and DDoS attacks (external threat); our techniques involve machine learning and time series analysis applied at different layers in TCP/IP stack. Accuracy of our techniques has been demonstrated through extensive experimentation on huge and varied datasets. All the techniques are applicable at the edge and can be integrated into a Network Intrusion Detection System.

22 illus, 10 tables, 54 ref

011972   Praveena Priyadarsini R;Valarmathi M L; Sivakumari S (Computer Science and Engineering Dep, Faculty of Engineering, Avinashilingam Institute for Homescience and H, Coimbatore-641 108, Email: praveena.priya04@gmail.com) : Attribute association based privacy preservation for multi trust level environment. Sadhana 2015, 40(6), 1769-92.

Enormous amount of e-data is collected world-wide by organizations for the purpose of their research and decision making. The availability of this heterogeneous, sensitive information in e-databases poses a threat to the privacy of the individual or organization on which the data is collected. Privacy Preserving Data Mining [PPDM] is a field of research which concentrates on preserving data privacy during the process of data mining. This paper proposes a two level partition and perturbation frame work to release multiple copies of privacy preserved datasets in Multi Trust Level [MTL] scenario that can prevent linking and diversity attack. The framework proposes two methods namely, Entropy based Attribute Privacy Preservation [EAPP] and Information Gain based Attribute Privacy Preservation [IGAPP] for privacy preservation in MTL environment. The two methods perform vertical and horizontal partitioning of data for privacy preservation. Simple K-Means clustering algorithm with cluster size 2 using both Euclidean and Manhattan distance functions are used for horizontal partitioning. The vertical partitioning of attributes within the cluster is performed based on their entropy value that indicates its one way association with its class in EAPP method and Information Gain [IG] value of the attributes that indicates the two way associations with class in IGAPP method. The attributes in the clusters are subjected to privacy preservation technique based on their entropy and IG values in EAPP and IGAPP methods, respectively. The effect of distance in clustering the data points on privacy preservation and the ability of the privacy preserved datasets generated using the proposed methods to prevent privacy attacks are studied using variance, rank distortion and utility metrics. Real life medical and bench mark adult data sets have been used here for experimentation. The, results show that the generated datasets exhibit good variance and rank distortion values and hence can prevent diversity and linking attacks in MTL environment. Also, the privacy preserved datasets have comparable utility on selected classification and clustering algorithms with original and L-Diversified datasets.

16 illus, 3 tables, 45 ref

011971   Pinder J;Johnson E J (Social Work Unit, Behavioural Sciences Deputy Dean Dep, Undergraduate Affairs, Faculty of Social Sciences The Univ of the West, St. Augustine Campus, Trinidad) : Investigation into social workers' perceptions of online counselling in social work practice in Trinidad. Int J Family Home Sci 2016, 12(1), 77-96.

This article explored the perception of social workers in regard to online counselling in practice. The study was carried out in Trinidad, West Indies whereby, social workers from every field were chosen as research participants. The findings reflected that all the participants held positive views about online counselling but preferred the traditional method. There were benefits and challenges that were unearthed such as, the ability to develop a new skill, it helped reduce emotional stress and some of the challenges were; the possibility of the technology breaking down, not being able to observe body language and the loss of human interaction

2 tables

011970   Perosov D A;Lomazov V A;Dobrunova S I M I; Lomazova V I (NO, Belgorod State Agricultural Univ Named After V.Gorin, Russia 308 503, Belgorod region, Pos. Mayskiy, ul.Vavilova 1) : Large discrete systems evolutionary synthesis procedure. Biosci Biotechnol Res Asia 2015, 12(2), 1767-75.

Article discusses the problems of structural synthesis of large discrete systems with predefined behavior, which assumes transition of a given input signal into required reference output signal. A combined method for building the procedure of synthesis based on evolutionary methods and mathematical analysis of Petri nets has been proposed. An evolutionary procedure of structural synthesis of large discrete systems with static inter-component links has been developed. Computational experiments performed with the use of the built model give evidence to the efficiency of the proposed synthesis procedure.

3 illus, 23 ref

011969   Nussipbekov A K;Amirgaliyev Y N;Hahn M (NO, Al-Farabi Kazakh National Univ, AL-Farabi Ave, 050 038, Almaty, Kazakhstan) : Improvement of human key posture recognition. Biosci Biotechnol Res Asia 2015, 12(2), 1139-44.

Human pose recognition is an important problem in such fields like scene recognition, robotics, multimedia systems an etc. It plays an essential role in full body gesture recognition. The obtained poses can be then used to detect gestures. In gesture recognition it is essential to capture all poses. Because missing some key pose may significantly decrease the gesture recognition accuracy. Most pose recognition approaches use silhouettes extracted from regular cameras that may not bring a favorable pose accuracy or different kind of special costumes that uncomfortable to wear. In this paper we propose to classify poses based on their skeleton appearance. For this we use depth camera called Microsoft Kinect. The main difference of our method is that we add some additional objects that take place in the scene into skeleton provided by Kinect camera. In another words we use an advanced type of skeleton unlike camera can provide. The skeleton can be modified upon the specific pose recognition task by modifying it which in turn increase the pose recognition accuracy. In our work we adopt it for golf postures recognition problem by tracking golf club head. The background of an image is subtracted by using depth image histogram, then we calculate object coordinates using HSV(Hue Saturation Value) color information and image moment. Finally we perform classification using Support Vector Machines. The obtained results demonstrate the efficiency of the proposed method.

5 illus, 2 tables, 16 ref

011968   Geetharamani R;Balasubramanian L (Information Science and Technology Dep, Anna Univ, Chennai-600 025, Email: rgeetha@yahoo.com) : Automatic segmentation of blood vessels from retinal fundus images through image processing and data mining techniques. Sadhana 2015, 40(6), 1715-36.

Machine Learning techniques have been useful in almost every field of concern. Data Mining, a branch of Machine Learning is one of the most extensively used techniques. The ever-increasing demands in the field of medicine are being addressed by computational approaches in which Big Data analysis, image processing and data mining are on top priority. These techniques have been exploited in the domain of ophthalmology for better retinal fundus image analysis. Blood vessels, one of the most significant retinal anatomical structures are analysed for diagnosis of many diseases like retinopathy, occlusion and many other vision threatening diseases. Vessel segmentation can also be a pre-processing step for segmentation of other retinal structures like optic disc, fovea, microneurysms, etc. In this paper, blood vessel segmentation is attempted through image processing and data mining techniques. The retinal blood vessels were segmented through color space conversion and color channel extraction, image pre-processing, Gabor filtering, image postprocessing, feature construction through application of principal component analysis, k-means clustering and first level classification using Naive-Bayes classification algorithm and second level classification using C4.5 enhanced with bagging techniques. Association of every pixel against the feature vector necessitates Big Data analysis. The proposed methodology was evaluated on a publicly available database, STARE. The results reported 95.05% accuracy on entire dataset; however the accuracy was 95.20% on normal images and 94.89% on pathological images. A comparison of these results with the existing methodologies is also reported. This methodology can help ophthalmologists in better and faster analysis and hence early treatment to the patients.

15 illus, 3 tables, 40 ref

011967   Das J C;De D (Computer Science and Engineering Dep, West Bengal Univ of Technology, BF-142, Salt Lake, Sector-I, Kolkata-700 064) : Reversible binary to grey and grey to binary code converter using QCA. IETE J Res 2015, 61(3), 223-9.

Quantum dot-cellular automata (QCA) is an emerging nanotechnological archetype and has widespread applications in designing nanoscale reversible circuit for nanocomputing. The low power consumption, faster operating speed, and low circuit area of QCA pledge the energy efficient design of logic circuit having high device complexity. This paper demonstrates the design of reversible binary to grey and grey to binary code converter based on Feynman gate using QCA for the first time. Both the proposed reversible code converter circuits have quantum cost as 2. The conversion of binary to grey code is achieved with only one garbage value and the grey to binary code conversion is achieved without any garbage value. The proposed Feynman gate circuit required only 38,880 nm^{2 areas and three clocking zones. The reversible binary to grey circuit required only 92,664 nm2 areas and three clocking zones whereas the reversible grey to binary circuit required only 139,968 nm2 areas and four clocking zones. The proposed design can be used to realise the nanoarchitecture in computer communication having low power consumption. The evaluation of simulation outcomes of proposed circuit with theoretical knowledge established the functional efficiency of the circuits. The circuits are designed and simulated by QCA Designer-2.0.3.}

9 illus, 5 tables, 20 ref

009893   Rajesha N;Viswanath H L (ECE,RRIT Dep, , Bangalore-90) : Efficient data scheduling policy in operating system for wireless sensor platforms to build fast query. Int J appl Sci Engng Res 2015, 4(2), 214-26.

It is going to be prescribed a dynamic multithreaded Operating System for wireless sensor network platforms. This operating system provides a cooperative threading model, for Underwater Sensor Network applications. Virtual memory is supported with the cooperation of the compiler, so that the sensor network platforms can execute code larger than the physical code memory they have. To enable firmware update for deployed sensor nodes, presented operating system supports remote reprogramming. The proposed techniques do not increase hardware cost, and are designed to require few changes to existing applications. It has been developed a compression algorithm well suited to this application. The commonly used library and the main logical structure are separated each sensor device has a copy of the dynamic loading library in the MMC card, and therefore only the main function and user-defined subroutines can be updated through RF. A dynamic, efficient file system named Flash File System is also included in OS. The code size and data size of OS including Flash File system are 8kB and 646 bytes, respectively.

4 illus, 3 tables, 17 ref

009892   Hemamalini S;Vijayaraja V;Yuvaraj S (Computer Science and Engineering Dep, Panmalar Institute of Technology, Chennai, Tamil Nadu) : Compression of combined fingerprints for secured authentication. Int J appl Sci Engng Res 2015, 4(2), 201-8.

Author propose a new idea based on authentication and compression. The two fingerprints have been registered during the enrollment process and a combined fingerprint template is generated based on minutiae positions from one finger and the orientation from the other finger. This template is compressed using sparse representation and stored in the database for future retrieval. With the help of an existing fingerprint reconstruction approach, we are able to convert the combined minutiae template into a real-look alike combined fingerprint. Using the method of sparse representation, we are able to obtain the coefficients which contain the actual information of the user. Hence the information cannot be easily stolen. The effects on actual ?ngerprint matching or recognition are not investigated.

3 illus, 1 table, 21 ref

009891   Divya P;Blessey P M (Computer Science and Esngineering Dep, S.A. Engineering College, Chennai) : Smartphone applications using bytewalla protocol in delay tolerant network. Int J appl Sci Engng Res 2015, 4(2), 259-64.

In Android platform, the Delay Tolerant Network (DTN) service and protocol stack and these presents an implementation of it that technique is called Bytewalla. This technique allows the use of Android phones for the physical carriage of data or information between the network nodes in which where there are no other communication between network nodes are available, for certain security issues the existing links need to be avoided or in some case the internet is blocked by a government authority like it happened in some countries eg.Arab country during the spring of 2011. This technique deals with an implementation of two applications that runs on top of Bytewalla, are addressed together with some usage scenarios and those two applications are store and forward messaging application (SFMA) and a Sentinel Surveillance health-care application (SSA). We concluded that the combination of DTN links in the wide-ranging IP-network architecture on mobile phone platform is feasible and it will make this easier to integrate DTN applications into communication-delayed areas. To best of our knowledge the implementation of the bundle protocol on the Android platform is the first in DTN application.

5 illus, 10 ref

008878   Kumar A N;Geetha B G (Computer Science and Engineering Dep, Christian College of Engineering and Technology, Oddanchatram, Dindigul, Tamilnadu-624 619, Email: greedaank@gmail.com) : Optimization of test case design in rational quality manager- A software testing tool. J scient ind Res 2015, 74(7), 387-9.

Software systems are playing important role in society and becoming more challenging to build. New methods, techniques and tools are available to support development and maintenance. Because software has such an important role in our lives both economically and socially. So there is a pressure for software professionals to focus on quality issues. Software testing is used to ensure the quality of the product. Even though, the Test Life Cycle consists of several steps, test case design plays a vital role. There are two types of testing namely manual testing and automated testing. The process of testing with the help of human is known as manual testing. The process of testing software by another testing tool is known as automated testing. There are lot of automated tools are available to test the software. In this research, the CD project is taken as example and explained briefly about how to work with the test cases in Rational Quality Manager which is the product of IBM.

3 illus, 12 ref

008877   Bhadra A (Sociology Dep, Hyderbad Univ, Gachibowli, Telangana-500 046) : Social networking site users: a sociological study of interaction pattern of the college goers in Kolkata metropolis. Indian J soc Res 2016, 57(2), 177-98.

In recent years rapid increase of use of Social Networking sites has brought impact on the pattern of social relations in our society. Social relations tend to alter the features of social groupings. Social networking has been replacing traditional patterns of interpersonal relations to become more intense among the youths as communication with unknown strangers and friends is in the rise. Unity among the non-kins cuts across the boundaries of kin, caste, ethnic and religious groups. A new type of primary groups seems to be emerging in the society as a 'Network Community'. Multiple identities of an individual is often based on e-personality, not on face-to-face social relations. This self- exposure to strangers often creates social problems now-a-days.

32 ref