013413   Abdalla A K A;Pathan A S K (Computer Science Dep, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia) : On protecting data storage in mobile cloud computing paradigm. IETE Tech Rev 2014, 31(1), 82-91.

To enhance the security of mobile cloud storage, a few proposals have been presented already, most of which focus on securing data through passwords and encryption-decryption of data through cryptographic tools and existing or rather new algorithms. However, these passwords and algorithms eventually get cracked by the expert hackers who mostly spend their entire time learning the algorithms and the way to get through the password-protected frameworks. It is for this reason that our article concentrates on a different way of securing data-storage for mobile cloud computing users. In this article, we present a secure framework that helps protect the mobile-user data through storage in different servers located at different geographical locations across the globe. In this way, it ensures strong data protection ability, because part of the data is stored in one server located at a location and another part of the data is stored in another server located at a far different location. We also analyse various facets of the issue and report on the state-of-the-art achievements.

5 illus, 25 ref

012466   Zhou J;Li Y;Tian X (College of Urban Construction, Hebei Univ of Engineering, Handan 056038) : Fuzzy evaluation and analysis of surface water. Nat Envir Pollut Technol 2013, 12(3), 497-502.

Comprehensive evaluation of the monitoring data of surface water in Handan City, based on the model of fuzzy comprehensive evaluation, was made in this paper. According to the monitoring data, selecting seven evaluation factors, namely, permanganate index, BOD, total nitrogen, total phosphorus, ammonia, fluoride and dissolved oxygen, weight matrix has been established for each factor, and the weight of each factor was obtained in the assessment of water quality. Then using the membership function in fuzzy mathematics, computed the data measured, and obtained the corresponding water level. The result of the evaluation shows that the water quality of Handan city is V level, severely polluted, and it becomes a security risk to the residents' drinking water. Besides, it can be used as the scientific basis for water quality control.

6 tables, 9 ref

012465   Yadav R S;Ahmed P;Soni A K;Pal S (Computer Science and Engineering Dep, SET, Sharda Univ, Greater Noida-201 306, Email: ramjeetsinghy@gmail.com) : Academic performance evaluation using soft computing techniques. Curr Sci 2014, 106(11), 1505-17.

This article presents a study of academic performance evaluation using soft computing techniques inspired by the successful application of K-means, fuzzy C-means (FCM), subtractive clustering (SC), hybrid subtractive clustering-fuzzy C-means (SC-FCM) and hybrid subtractive clustering-adaptive neuro fuzzy inference system (SC-ANFIS) methods for solving academic performance evaluation problems. Modelling of students' academic performance is a difficult optimization problem. We explore the applicability of K-means and FCM, SC, hybrid SC-FCM and SC-ANFIS clustering methods to the new student's allocation problem, which allocates new students into some classes that consist of similar students and the number of students in each class not exceeding its maximum capacity. The models were combined with fuzzy logic techniques to analyse the students' results. In this article, we have conducted clustering based computational experiments to analyse the effects of the different clustering algorithms like K-means, FCM, SC, hybrid SC-FCM and hybrid SC-ANFIS clustering methods for modelling students' academic performance evaluation. Based on the comparison of the results, it is found that the hybrid SC-ANFIS clustering is better than the other methods.

1 illus, 12 tables, 37 ref

012464   Shyamasundar R K (NO, School of Technology and Computer Science, Tata Institute of Fundament, Homi Bhabha Road, Mumbai-400 005, Email: shyam@tifr.res.in) : Computing legacy of Alan M. turing (1912-1954). Curr Sci 2014, 106(12), 1669-80.

Alan Turing is considered one among the 20th cen-tury's 100 greatest minds. The invention of stored-program universal computer by him, is arguably the most influential mathematical abstraction of the 20th century that changed the whole world for good. While this invention became one of the cornerstones of computer science, Turing was best known during his time as the genius who broke some of Germany's most secret codes during the war of 1939-45. His inventions and discoveries covered a wide spectrum of areas like logic and computability, cryptology, computer architecture, artificial intelligence, digital forecast, chemical morphogenesis, algorithm randomness. While he was a theoretician's theoretician, he had an immense practical outlook with a deep understanding of computing, including its impact on science and society. In this article, some of his pioneering contributions shall be highlighted in an accessible way.

9 illus, 11 ref

012463   Sheela K G;Deepa S N (NO, Anna Univ, Regional Centre, Coimbatore-641 047, Email: sheelabijins@gmail.com) : Selection of number of hidden neurons in neural networks in renewable energy systems. J scient ind Res 2014, 73(10), 686-8.

This paper presents a new approach to select number of hidden neurons in neural network in renewable energy systems. The random selection of number of hidden neurons might cause over fitting and under fitting problems in neural networks. The proper selection of neurons in hidden layer is important in the design of neural network model. To fix hidden neurons, 91 various criteria are examined based on estimated mean squared error. The convergence analysis is performed for the various proposed criteria. To verify the effectiveness of the proposed model, simulations were conducted on real time wind data. Results show that with minimum error the proposed approach can be used in renewable energy systems.

1 illus, 1 table, 13 ref

012462   Ounsrimuang P;Boonjing V (Software Engineering Laboratory, Computer Science Dep, Faculty of Science King Mongkut's Institute of Technology Ladkrabang B, Thailand, Email: s9062912@kmitl.ac.th) : Mutual information rough sets feature selection and classification for microarray data analysis. Far East J mathl Sci 2014, 85(2), 129-49.

Feature selection (FS) techniques aim to reduce the subset size of an original data set, which are retained in the most useful information by selecting the most informative feature instead of irrelevant or redundant features. The benefits of FS for classification analysis can reduce the input data, improved predictive accuracy, learned knowledge is that easily understood, and reduced execution time. Many approaches based on rough set theory up to now, have operated the dependency function for measuring the goodness of the feature. However, there is not tolerance to noisy or inconsistency data, especially on high dimensional data microarray data sets. Moreover, mostly relevant information could be invisible by using only information from a positive region but neglecting a boundary region, mostly relevant may be invisible. Therefore, this paper proposes the maximal positive region and minimal boundary region criterion, based on rough set and mutual information, which use the different values among the information contained in the positive region, and the information contained in the boundary region. The experimental results indicate that our proposed method can increase the classification accuracy.

1 illus, 10 tables, 40 ref

012461   Kumar A;Malik S C (Statistics Dep, M.D. Univ, Rohtak-124 001, Email: sc_malik@rediffmail.com) : Cost-benefit analysis of a computer system with priority to S/W replacement over H/W repair activities subject to maximum operation and repair times. J scient ind Res 2014, 73(10), 653-5.

Emphasis of the present study is on the evaluation of reliability measures of a computer system with independent hardware (h/w) and software (s/w) failures. A single repair facility is provided immediately for conducting repair activities of h/w and s/w. Preventive maintenance of the system is done after a maximum operation time. Replacement of the h/w by new one is made in case server fails to complete its repair in a given maximum time. However, only replacement of the s/w is done by new one giving some replacement time. Priority is given to s/w replacement over h/w repair activities. The failure time distribution of the h/w and s/w follows negative exponential while the distributions of preventive maintenance, repair and replacement time are taken as arbitrary with different probability density functions. Illustration for a particular case is given to show the graphical behaviour of some important reliability measures.

1 illus, 3 ref

012460   Kavitha Rani B;Srinivas K;Govardhan A (NO, Jyothishmathi Institute of Technology & Science, Karimnagar, Andhra Pradesh, Email: kavi_gdk1978@yahoo.co.in) : Rainfall prediction with TLBO optimized ANN. J scient ind Res 2014, 73(10), 643-7.

Rainfall prediction is very crucial for India as its economy is based on mainly agriculture. The parameters that are required to predict the rainfall are very complex in nature and also contain lots of uncertainties. Although various approaches have been earlier suggested for prediction, the soft computing is found to be very effective in developing models which emulates human being and derives expertise like human being to adapt to the situations and learn from the experiences. In this study, rainfall prediction for Andhra Pradesh (AP) state is carried out with Artificial Neural Network (ANN). A new heuristic approach Teaching Learning Based optimization (TLBO) is used to train the weights of the ANN developed for rainfall prediction. A comparison is done with classical back Propagation learning approach and mTLBO (a variant of classical TLBO). The data of monthly rainfall (mm) in Coastal Andhra is collected from Indian Institute of Tropical Meteorology (IITM), Pune, India. The data set consists of 1692 monthly observations during years 1871 to 2011. The simulated results reveal the effectiveness of ANN-mTLBO over ANN-BP on investigated datasets. The findings of our work will be very useful in assessing the possible drought situations in AP from the rainfall predictions.

2 illus, 1 table, 9 ref

012459   Hariharan R (Computer Science Dep, Indian Institute of Science, Bangalore-560 012, Email: ramesh@standls.com) : Turing and animal coat patterns. Curr Sci 2014, 106(12), 1681-6.

Present article describes a beautiful contribution of Alan Turing to our understanding of how animal coat patterns form. The question that Turing posed was the following. A collection of identical cells (or processors for that matter), all running the exact same program, and all communicating with each other in the exact same way, should always be in the same state. Yet they produce nonhomogeneous periodic patterns, like those seen on animal coats. How does this happen? Turing gave an elegant explanation for this phenomenon, namely that differences between the cells due to small amounts of random noise can actually be amplified into structured periodic patterns. We attempt to, describe his core conceptual contribution below.

5 illus, 2 tables, 3 ref

011421   Parab A Y;Dhane O;Deshmukh A;Mahajani A (NO, , Computer Engineering Dep, SIT Lonavala, Email: aditi.parab1@gmail.com) : Approach to heterogeneous database migration. Int J latest Technol Engng Mgmt appl Sci 2014, 3(4A), 20-2.

Main issue in the database migration is the work of data organizing, analyzing, accuracy and integrity. In this paper we have tried to eliminate these problems, by making use of XML file as an intermediate. XML supplies a neutral platform for the information description. As the information is mostly stored in RDBs, we have decided to create a system to export the information from a DB into XML, and to import XML documents into any RDB management system. Till date systems were available to covert data from one DB into an XML file, in our paper we have given more emphasis on the conversion of the XML file into the required target DB. Our system has enabled us to transform data from one DB into another using XML as an intermediate representation. Main aim of our paper is to generate a system to automate the transference of data between databases. The proposed system performs conversion of DBs like Ms-Access, MS-SQL, Oracle, and MySQL.

6 ref

010387   Sundar C;Chitradevi M;Geetharamani G (CSE Dep, Christian College of Engineering and Technology, Anna University, Chennai, Email: sundarc007@yahoo.com) : Incapable of identifying suspicious records in CTG data using ANN based machine learning techniques. J scient ind Res 2014, 73(8), 510-16.

Cardiotocography (CTG) is a simultaneous recording of fetal heart rate (FHR) and uterine contractions (UC). It is one of the most common diagnostic techniques to evaluate maternal and fetal well-being during pregnancy and before delivery. By observing the Cardiotocography trace patterns doctors can understand the state of the fetus. We implement a model based CTG data classification system using a supervised artificial neural network (ANN) and support vector machine (SVM) which can classify the CTG data based on its training data. The performance neural network based classification model has been compared with the most commonly used unsupervised clustering methods Fuzzy C-mean and k-mean clustering and supervised clustering method SVM classification. According to the arrived results, the performance of the supervised machine learning based classification (ANN) approach provided significant performance than other compared unsupervised clustering methods and supervised SVM classification method. We used Precision, Recall, F-Measure and Rand Index as the metric to evaluate the performance. Even though the traditional clustering methods can identify the Normal CTG patterns, they were incapable of finding Suspicious and Pathologic patterns and the SVM based classifier provided good performance, it was absolutely incapable of identifying a single suspicious record. It was found that, the ANN based classifier was capable of identifying Normal, Suspicious and Pathologic condition, from the nature of CTG data with very good accuracy. The important finding in this paper is Even though SVM is a well proven technique for classification, it was incapable of identifying Suspicious Records in Cardiotocogram Data - but ANN did considerably good classification of Suspicious Records.

2 illus, 1 table, 26 ref

009378   Nair B G;Malthane G B;Solomon S S (Agri. Economics Dep, Dr. P.D. Krishi Vidyapeeth, Akola-444 104, Email: bhavitasanalkumar@gmail.com) : Measurement of technical efficiency of cotton growers - a data envelopment analysis approach. Green Fmg 2013, 4(1), 113-15.

Study on measurement of technical efficiency of cotton growers-a data envelopment analysis was undertaken to study the technical efficiency at farm level in respect of soybean crop by selecting farmers growing cotton in Amravati district. They were grouped in three groups. Group I for small farmers, Group II for medium farmers and Group III for large farmers. The primary data was collected by survey method and the analysis was done by using Data Envelopment Analysis computer programme. The analysis revealed that the mean technical efficiency under constant returns to scale for small farmers was found to be77.2 and other group was 83.7 percent, respectively.

6 tables, 3 ref

008370   Thakkar A;Kosta Y P (NO, , CSPIT, Charusat Changa, Gujarat, Email: amitthakkar.it@ecchanga.ac.in) : Improving efficiency of relational classification technique based on relational database using contribution of tables. Int J Data Mining Emerging Technol 2014, 4(1), 1-9.

Classification is one of the most popular data mining tasks with a wide range of applications. Many algorithms have been proposed to build an accurate classifier. These algorithms work for a single Table as an input but in real-world applications most of the data relies on multiple Tables. As converting data from multiple relations into single flat relation usually causes many problems, development of classification across multiple database relations becomes important. There have been many approaches for classification, such as neural networks and support vector machines. However, they can only be applied to data in single flat relations. It is counterproductive to convert multi-relational data into single flat Tables because such conversion may lead to the generation of huge relation and loss of essential semantic information. In this work, we propose algorithm for multi-relational classification (MRC) which uses weighted voting technique to combine classifiers to get class label based on the contribution of Tables. This will classify the instance accurately and efficiently.

4 illus, 6 tables, 22 ref

008369   Saha G K;Kumar S (NO, Scientist, Project Engineer, C-DAC, Kolkata-700 091, Email: sahagk@gmail.com) : Intelligent healthcare agent system design issues. Int J appl Res Inf Technol Comput 2014, 5(1), 31-47.

In this paper, we will discuss about the different types of intelligent agents of healthcare which delved health information system for better treatment and suggestion. In today's world, computer science plays a vital role in day-to-day life. In almost every field, computers play a vital role according to their requirements. Even in healthcare, computer science (computer) plays an important role in analysing and diagnosing medical problems and diseases. Artificial intelligence (AI) has revolutionised medical science. Nowadays, AI is in high demand in medicinal science. This paper describes important issues related to the characteristics of the Intelligent Healthcare Agent System (IHCAS) and the methodologies used for its implementation. Intelligent agents are a new paradigm for developing software application. Currently, agents are the focus of intense interest on the parts of many sub fields of computer science and artificial intelligence. It defines how they are figured out for diagnosis of diseases, symptoms and suggestion. These case-studies lead us to IHCAS and help figure out the most optimal methodology and the best solution for diagnosis. This paper aims to survey important intelligent healthcare agent research works and presents a case-study based on the analysis and comparison of various methodologies used in intelligent healthcare agents. We find that every methodology has some good and some bad aspects. Different methodologies for intelligent healthcare agent are used for providing better healthcare diagnosis problems. Some methodologies are very good in one domain, whereas others are good in a different domain, but the aim of all methodologies is the same, i.e. to solve medical diagnosis problems, food habits, healthy lifestyle and healthcare awareness among the people.

2 illus, 34 ref

008368   Rai S;Saini P;Jain A K (Computer Science Dep, Banasthali Univ, Jaipur, Rajasthan, Email: swetarai90@gmail.com) : Factors affecting the dropout students using discriminant analysis and association rule. Int J Data Mining Emerging Technol 2014, 4(1), 25-33.

Currently, the educational institutions face a lot of issues, such as high dropout rate, predicting the quality of stu-dent interaction, student's performance evaluation and the placement of the students. To overcome these issues of educational institutions, data mining techniques are used. One of the biggest challenges that higher education faces is scaling down the rate of dropout students. The aim of this paper was to select the subset of relevant features from a large set of features using the statistical tool Statistical Package for the Social Sciences (SPSS), and to find frequent item sets and to extract the hidden information from the large data regarding the factors that are responsible for student dropout using the Waikato Environment for Knowledge Analysis (WEKA) tool. This paper proposes a novel concept of discriminant analysis used for analysing the affects of 33 variables on the student dropout in higher education. It also indicates which variables are important in explaining a dropout student and the Apriori algorithm in mining association rule from a dataset containing dropout student data concerning women. For this study, data of the first year undergraduate students were collected randomly from a survey based on personal interview at the university. The generated knowledge will be quite useful for understanding the problem in a better way and to have a proper planning or decision to scale cown the dropout rate.

3 illus, 10 tables, 13 ref

008367   Patwa S;Malviya A K (Science Dep, FASC, MUST, Lakshmangarh, Sikar-332 311, Email: anilkmalviya@yahoo.com) : A survey on factors affecting testing techniques in object oriented software. Int J appl Res Inf Technol Comput 2014, 5(1), 78-85.

The focus of this research paper is on the analysis of factors which affect software testing techniques in Object Oriented Software with the opinion of people who are engage in software development phases. The study uses a survey instrument to analyze the factors and identify factors that have significant impact on software testing techniques. The research focuses on the perspective of the primary participants, managers, programmers, testers and other people involved in software research or development teams. The original contribution of this research is to provide a general guide to the important aspects to consider in the whole software development process.

4 tables, 6 ref

008366   Nara R;Yenduri S (School of Computing, Southern Mississippi Univ, 730 East Beach Boulevard Long Beach, Mississippi 39560, USA, Email: sumanth.yenduri@usm.edu) : Simulation of an optimality algorithm for railway traffic networks. Int J appl Res Inf Technol Comput 2014, 5(1), 86-9.

Dynamic railway traffic management needs accurate time/location estimates on the fly in order to work efficiently. In this student project, we use the permutation based algorithm proposed by Ton J.J. van den Boom et al. to achieve efficient traffic control management. A switching max-plus linear system was proposed by them. Our goal was to build a simple piece of software that is based on their methodology. We finally present the results from our simulation.

8 illus, 5 ref

008365   Mellah M A;Amine A;Hamou R M;Senthil Kumar A V (Computer Science Dep, Tahar Moulay Univ of Saida, Saida, Algeria, Email: amine_abd1@yahoo.fr) : Link analysis for communities detection on facebook. Int J Data Mining Emerging Technol 2014, 4(1), 16-24.

Social networks have become a part in the daily life of millions of users, which offer wide range of interests and practices. The main characteristic of social networks is its ability to gather different individuals around a common point of view or collective beliefs. Among the current social networking sites, Facebook is the most popular, which has the highest number of users. However, in Facebook, the existence of communities (groups)is a critical question; thus, many researchers focus on potential communities by using techniques like data mining and web mining. In this work, we present four approaches based on link analysis techniques to detect prospective groups and their members.

7 illus, 1 table, 19 ref

008364   Madhu G;Rajinikanth T V;Govardhan A (Information Technology Dep, VNRV JIET, Hyderabad-90) : Novel discretization method for continuous attributes: a machine learning approach. Int J Data Mining Emerging Technol 2014, 4(1), 34-43.

Discretization plays a vital role where continuous attributes are transformed into discrete values for preprocessing tasks in data mining algorithms and machine learning classifiers. Most of the real data often come in mixed notations, i.e., continuous and discrete, while many machine learning algorithms require it in the form of discrete data only. In the past few decades, numerous techniques have been proposed as discretization techniques for continuous data, which are unable to provide better accuracy, understandability of models and also classifier confusion in the form of continuous data. In this paper, we propose a new discretization technique called 'ZDisc' based on the standard deviation normalization statistical technique for continuous attributes to generate less number of cut points. The proposed method has been compared with other state-of-the-art discretization techniques on benchmark continuous datasets. The experiment shows that the proposed discretization method performs competitive discretization schemes in terms of classifier accuracy and to minimize the classifier confusion.

5 illus, 6 tables, 33 ref

008363   Kushwah V S (Computer Science & Engineering Dep, Maharishi Markandeshwar Univ, Mullana-Ambala, Haryana-133 207, Email: kushwah.virendra248@gmail.com) : A review of various cross-layer frameworks for ad hoc network. Int J appl Res Inf Technol Comput 2014, 5(1), 71-7.

In this paper, it has been discussed and focused over the various frameworks on ad hoc networks. Since, it is not easy to follow all the aspects and issues over ad hoc networks followed by cross layer designing approaches. This paper discussed various frameworks supported by real-time multimedia, multi objective performance, multi-path transmission for Voice over Internet Protocol (VoIP) communication, privacy enhancement in Radio Frequency Identification (RFID) systems, Mobile Man architecture for ad hoc wireless networks, congestion control, scalable video transmission, scheduling of video streaming over Universal Mobile Telecommunication Systems (UMTS) and security and quality of service (QoS) co-design based cross layer frameworks or architectures.

4 illus, 12 ref

008362   Karegowda A G (Master of Computer Applications Dep, Siddaganga Institute of Technology, Visvesvaraya Technological Univ, Tumkur, Karnataka, Email: ashagksit@gmail.com) : Enhanced categorization of wheat seeds by integrating ensemble methods with decision tree identified significant features. Int J Data Mining Emerging Technol 2014, 4(1), 10-15.

Data mining has great potential for exploring the hidden patterns in different domains. This paper presents the development of an ensemble model, using bagging and multiboost with five base classifiers: RBF, Naive Bayes, Bayesian, K-nearest classifier and SVM. The development of the model involved two stages: (i) identify the group-sensitive attributes in the large database pertaining to wheat seeds dataset using decision tree and (ii) make a fine-tuned classification using bagging and multi-boost ensemble with five different base classifiers using the sensitive attributes elicited in the first stage. The publicly available wheat seed dataset has been used for the development of the model. Computational experimentations have been conducted using ten-fold cross validations. This investigation conclusively proves the significance of cascading decision tree for feature selection with ensemble methods, namely, bagging and multiboost for the enhanced categorization of wheat dataset.

4 illus, 1 table, 15 ref

008361   Fathima H;Musthafa A S (Computer Science Dep, Bharathidasan College of Arts and Science, Ellispettai, Erode-16, Email: fathi.fathimahussain@gmail.com) : Optimization based routing algorithms. Int J appl Res Inf Technol Comput 2014, 5(1), 55-70.

A new agent-based routing algorithm using optimization techniques is discussed in this paper. The different optimization techniques are Ant, Bee, Ant Bee, Ant GA, Ant PSO, GA, PSO, Pillar, Simulated Annealing, Ant Pillar, Bee Pillar, GA PSO, GA Pillar, GA-SA,PSO Pillar, PSO SA, Bee PSO, Bee GA, Bee SA are the combinations used in the packet delivery between the networks. The routing is a process of carrying the data from source to destination in the network. The outputs of these algorithms are determined by the simulation time and throughput. The experiments are implemented with the NS2 software platform, which is based on the basics of C, C++, and TCL Scripting Language. The results of the algorithm showed that the GA-PSO is much better than the other algorithms in the packet delivery between the networks.

8 illus, 2 tables, 25 ref

008360   Dhakar K S;Singh S;Sathwane R A;Niranjan H K;Patel A (Extenion Education Dep, J N K V V Jabalpur, College of Agriculture, Rewa (MP)) : Utility perception of farmers in relation to Modern Mas Media under Information Communication Technology in Rewa District (MP). Envir Ecol 2013, 31(2c), 1022-5.

The present study was conducted in Rewa district of MP to assess the utility perception of ICT based program. The study was entirely on the farmers availing the facility of ICT through mobile advisory services. The study revealed that the aspect of ICT i.e. location specific had the highest utility perception index (86.96) followed by timeliness (utility perception index 82), understandability (utility perception index 80.4), applicability (utility perception index 77 .36) and simplicity (utility perception index 75.36). The study also revealed that out of 125 respondents 40.80% showed medium utility perception, 36.00% of respondents indicated high utility perception whereas 23.20% had low utility perception about mobile advisory services.

3 tables, 1 illus, 5 ref

008359   Contaldo N;Bertaccini A;Nicolaisen M (NO, Alma Mater Studiorum-Univ of Bologna, DipSA, Plant Pathology, Viale Fanin 42, Bologna, 40127 Italy, Email: assunta.bertaccini@unibo.it) : Q-bank phytoplasma database. Phytopath Mollicutes 2014, 4(1), 1-4.

Setting of the Q-Bank database free available on line for quarantine phytoplasma and also for general phytoplasma identification is described. The tool was developed in the frame of the EU-FP7 project Qbol and is linked with a new project Q-collect in order to made widely available the identification of relevant plant pests by nucleic acid sequence comparison of their barcodes.

4 illus, 7 ref

008358   Aher S B (Computer Science Engineering Dep, Walchand Institute of Technology, Solapur-413 006, Email: sunita_aher@yahoo.com) : EM&AA: an algorithm for predicting the course selection by student in e-learning using data mining techiques. J Instn Engrs : Ser B 2014, 95(1), 43-54.

Recommendation systems have been widely used in internet activities whose aim is to present the important and useful information to the user with little effort. Course Recommendation System is system which recommends to students the best combination of courses in engineering education system e.g. if student is interested in course like system programming then he would like to learn the course entitled compiler construction. The algorithm with combination of two data mining algorithm i.e. combination of Expectation Maximization Clustering and Apriori Association Rule Algorithm have been developed. The result of this developed algorithm is compared with Apriori Association Rule Algorithm which is an existing algorithm in open source data mining tool Weka.

2 illus, 6 tables, 35 ref

007319   Vivekanadan K;Rajasri K (Computer Science & Engineering Dep, Pondicherry Engineering College, Puducherry-605 014, Email: kvivek27@yahoo.com) : Secure manet based on on-demand routing protocol and IDS. Int J Comp Applic 2014, 9(1), 115-29.

An ad-hoc network is a collection of mobile nodes forming a network in which the network topology changes dynamically. The nodes use the service of other nodes in the network to transmit packets to destinations that are out of their range. The Ad Hoc On-Demand Distance Vector (AODV) routing protocol is a reactive protocol, applied in Mobile Ad-hoc Networks (MANETs). AODV performs better than many other on-demand protocols under high mobility, large network scenarios. Since there are no centrally administered secure routers, attackers can easily exploit the network. Moreover, shared wireless medium, dynamic topology also adds on to the challenges in the security design of Mobile Ad Hoc Networks. In this paper, we present our approach of securing a MANET using a secure routing protocol and threshold-based intrusion detection system. SecAODV incorporates security features of non-repudiation and authentication. While the IDS help detect attacks on data traffic.

11 illus, 3 tables, 17 ref

007318   Vijaya G;Arumugam S (NO, KGiSL Institute of Information Technology, Coimbatore, Tamil Nadu) : Feasibility study on SPC in software process. Int J Comp Applic 2014, 9(1), 1-8.

The demand for increased efficiency and effectiveness of software processes places measurement demands on the software engineering community beyond those traditionally practiced. The consistency and capability of the processes can be determined by the use of Statistical and Process Control Methods. This paper reviews various research works performed about using Statistical Process Control (SPC) to measure and analyze software processes. The research concentrates as the usage of SPC to measure and analyze software processes.

31 ref

007317   Sreekanth P D;Geethanjali N;Sreedevi P D; Ahmed S;Balakrishna R (NO, National Research Centre for Cashew, Puttur, Karnataka, India) : Efficacy of support vector regression prediction model. Int J Comp Applic 2014, 9(1), 93-8.

In the last decade or so, machine learning techniques such as Artificial Neural Networks (ANN), fuzzy logic, Support Vector Machine (SVM), genetic programming, etc., have been widely used in the modeling and prediction of hydrologic variables. Developing a time series prediction models are an important and complex problem in machine learning and statistics, but all Support Vector Machine (SVM) models are benchmarked against traditional prediction techniques. In this study, a Support Vector Regression (SVR) model was developed for forecasting groundwater level at Maheshwaram watershed, Hyderabad, India well in advance. By using different kernels, different models were developed and compared in terms of prediction efficiency and accuracy. Based on Root Mean Square (RMSE) and Regression Coefficient (R^{2), SVR with linear kernel model provided the best results (RMSE = 2.39 and R2 = 0.98) over other selected kernels, Radial Basis Function (RBF) and Multi Layer Perceptron (MLP) for predicting groundwater level one month ahead for above location.}

3 illus, 2 tables, 16 ref

007316   Marzjarani M;Urbain J;Cieszlak J (NO, Saginaw Valley State Univ, 7400 Bay Road, Univ Center, MI 48710) : Distributed web service for statistical and artificial intelligence methods. Int J Comp Applic 2014, 9(1), 83-92.

The cooperative approach of distributed computing and the power-hungry fields of artificial intelligence and statistics can be joined to create a powerful and rapid system. By creating a way to make parallel processes of artificial intelligence and statistical methods, we can separate work among many cost-effective computers, rather than force users to wait long periods of time or use supercomputers. The methods created can then be used by anyone in the field (as well as databases and computer architecture, among many others) to speed their systems.

11 illus, 2 ref

007315   Mahadevan G;Kiruba R J (Mathematics Dep, Gandhigram Rural Univ, Gandhigram-624 302, Email: gmaha2003@yahoo.co.in) : A new algorithmic approach for edge detection using graph theoretical techniques. Int J Comp Applic 2014, 9(1), 99-108.

This paper introduces an algorithmic approach for edge detection and linking based on representing edge segments in the form of a graph. An algorithm is proposed for finding the minimum-cost path. A program has been developed for finding the minimum-cost path. The effectiveness of the algorithm is illustrated by means of an example.

2 illus, 7 ref

007314   Latha R;Rajagopalan S P (Computer Applications Dep, St. Peter's Engineering College Avadi, Chennai-600 054, Email: rslatha2002@yahoo.co.in) : Parallel simulation framework. Int J Comp Applic 2014, 9(1), 17-28.

A model is usually defined to consist of independent tasks which synchronize by communicating time-stamped events/messages. The parallel and distributed simulation has been proved to reduce the time required to complete the simulation of some scenarios, improve the code reusability, address the requests for fault-tolerance and support the spatially located architectures. The Grid enables large-scale resource sharing and makes it viable for running large-scale pads. The High Level Architecture (HLA) paradigm provides a software platform and interoperability interface for simulation components to utilize these hardware resources. In this paper, a framework for designing and executing parallel simulation using the RTI is introduced to assist load balancing and check pointing. Our framework incorporates automatic code generation. It also uses Data Distribution Management to route simulation events (interactions) to achieve efficient use of network bandwidth.

7 illus, 1 table, 6 ref

007313   Lakshmi A S;Singaraju J (Computer Science Dep, Sri Padmavathi Mahila Visva Vidyalayam, Tirupati, AP, 517502, Email: ayathusrilakshmi@gmail.com) : On predicting macropatterns in Indian industry performance using data mining techniques. Int J Comp Applic 2014, 9(1), 69-82.

The process of extracting previously unknown or potentially useful patterns from data, referred to as Data Mining, has become an integral part of a majority of businesses globally. However, application of the same on macro-economic indicators has been rare worldwide. The work presented here deals with application of standard machine learning and data mining techniques a new data set collected about Indian industry performance. We defined the prediction problems, built suitable experimental models, and found classifiers that succeed with accuracies of more than 90%. The work indicates that machine learning/ data mining techniques have a high degree of suitability to macroeconomic indicator prediction in countries like India, and paves way for further detailed work in this direction.

1 illus, 2 tables, 16 ref

007312   Khan S S;Ali M S;Bamnote G R;Gupta S R (MCA Dep, Vidya Bharati Mahavidyalaya, Amravati, Email: sajidkhan362@yahoo.com ) : Real-time databases in embedded systems: future trends. Int J Comp Applic 2014, 9(1), 29-36.

Real-time systems are now used in many applications domains, including network infrastructure, telecommunications, banking and financial markets. As real-time systems continue to evolve, their applications become more complex, and often require timely access to, and processing of, huge amounts of data. In real-time system based applications, it is often assumed that a fast enough data processing engines created specifically for the system and tightly integrated with its code, will meet real-time requirements. However, often the application's input data must be correlated, merged, or compared across all data objects and across time, for filtering or analysis. In addition, the data must be shared by concurrent tasks that have different functions, time requirements and degrees of importance. These issues are better addressed by a proven database management system (DBMS). As a result, real-time systems increasingly feature a commercial, off-the shelf DEMS as a part of the architecture, to simplify design, streamline development and improve performance. Ultimate goal of the paper is to present the scope and space for the Real-Time Databases for Embedded System with its present scenario and future trends.

16 ref

007311   Katare R K;Chaudhari N S (Computer Science Dep, A.P.S. Univ, Rewa Madhya Pradesh-486 003, Email: katare_rakesh@yahoo.com) : Study of parallel algorithms for sparse linear systems and different interconnection networks. Int J Comp Applic 2014, 9(1), 109-14.

Parallel algorithms for Symmetric Gaussian elimination is presented. We showed actual testing operations that will be performed during Symmetric Gaussian elimination, which caused symbolic factorization to occur for sparse linear systems. The array pattern of processing elements (PE) in row major order for the specialized sparse matrix is formulated. We use symbolic factorization that produces a data structure, which is used to exploit the sparsity of the triangular factors. It has been studies that the access function or routing function to map data on hypercube and Perfect Difference Network (PDN) contains topological properties. This function is convergent in the finite interval. The hypercube is modeled as a discrete space with discrete time because the processors are in Hamming distances where as PDN's allow O(d^{2) nodes when nodes are of degree d, or equivalently, have a node degree that grows as the square root of the network size. The symmetry and rich connectivity of PDN's lead to balanced communication traffic and good fault tolerance.}

19 ref

007310   Goyal K K;Bhardwaj K;Agarwal P (Computer Application Dep, Faculty of Management & Computer Application, R.B.S. College, Khandari, Agra, Uttar Pradesh, Email: kkgoyal@gmail.com) : Protocol for user authentication from the remote autonomous object using TTP. Int J Comp Applic 2014, 9(1), 37-40.

In 2003, Novikov and Kiselev proposed a scheme for authentication of the user from the remote autonomous object. In 2005 Yang et al, [10] pointed out that Novikov and Kiselev scheme is insecure against the man-in-middle attack. Recently Minho and Cetin [12] proposed an improved version of the Novikov-Kiselev scheme to overcome such vulnerability. In this paper, we propose, a new protocol for user authentication from the remote autonomous object using trusted third party (TTP).

12 ref

006304   Yuvaraj M (Library & Information Science Dep, Banaras Hindu Univ, Varanasi, Uttar Pradesh, Email: mayank.yuvaraj@yahoo.com) : Examining librarians' behavioural intention to use cloud computing applications in Indian Central Universities. Ann Libr Inf Stud 2013, 60(4), 260-8.

The paper analyses the Technology Acceptance Model (TAM) in order to examine the librarians' behavioural intentions to use cloud computing applications. A questionnaire was developed using three TAM instruments: attitude, perceived ease of use and perceived usefulness to measure the librarian`s behavioural intentions of cloud computing applications use. Four hundred and seven library professionals completed the survey that measured their responses on perceived ease of use, perceived usefulness, attitude and the behavioural intentions on the use of cloud computing applications. Results show that librarians' perceived ease of use had significant impact on the attitude towards use. Further, perceived ease of use severely influenced the perceived usefulness of the cloud computing applications. The findings validate the implications of cloud computing applications in a library setting.

1 illus, 6 tables, 39 ref

006303   Ukachi N B;Onuoha UD (NO, Lagos Univ, Akoka, Yaba, Lagos, Nigeria, Email: ukachingozi2001@yahoo.com) : Continuing professional development and innovative information service delivery in NIgerian librries: inhibitors and the way out. Ann Libr Inf Stud 2013, 60(4), 269-75.

This study examined the various forms of continuing professional development (CPD) that Nigerian academic librarians have participated in during the last five years with a view to ascertain the various ways in which skills acquired from such programmes had enabled innovative and creative information service delivery. The survey method of investigation was adopted for the study. The findings revealed that the librarians participated in very few forms of CPD programmes and the few skills acquired during participation in the CPD programmes are minimally utilized in providing creative and innovative services in the library. The major inhibitors to being innovative and creative with the acquired skills were identified to be: epileptic Internet access due to low bandwidth, lack of computing facilities to put the skills into practice in the library, irregular power supply and, not working in the section where the skill can be put into use. The study therefore recommends that librarians should begin to explore other CPD programmes such as participation in webinars as well as making use of online training sites and YouTube tutorials. It also recommends that more skills in the areas of digitization, real-time referencing, teleconferencing, and networking management should be acquired by the librarians if they want to remain relevant while the university and library management should provide adequate number of computers and also upgrade the Internet bandwidth in the libraries to allow for its effective utilization in services creation and provision by the librarians.

4 tables, 12 ref

006302   Prithviraj K R;Sampath Kumar B T (Assistant in Library & Information Science, Directorate of Distance Education, Kuvempu Univ, Jnana Sahyadri, Shivamogga, Karnataka, Email: prithviraj.kr@gmail.com) : URLs as references in indian LIS conference papers: an analysis. Ann Libr Inf Stud 2013, 60(4), 284-95.

The paper compares the characteristics of URLs cited in Indian LIS conference proceedings papers.A total of 15,745 references appended to 1,700 articles published in three Indian LIS conference proceedings published during 2001-2010 were selected. From these references we extracted a total of 5698 URLs and were further classified according to their top level domains, file formats and path depths for further analysis. The results showed that the percentage of articles with at least one URL increased from 39.10% in 2001 to 91.67% in 2010. There was a constant and continuous increase in the number of articles with URLs over the years during 2001-2010. Of the 1,700 articles published in conference proceedings, there were 1,011 (59.47%) articles with URLs. Study also reveals the fact that, of the 5,698 URLs, more than 50% were shared by .org and .com domains which accounted for 1,799 (31.57%) and 1,474 (25.87%) URLs respectively. The highest percentage of cited URLs belonged to HTML (68.50%) followed by .pdf files (8.86%). The path depth levels 0 (no path), 2 and 3 collectively accounted for 67.67% of the extracted URLs. URLs with path depth 1 and 4 put together accounted for 25.31% of all the 5,698 URLs.

5 illus, 10 tables, 32 ref

006301   Jayanthi J;Rathi S (Computer Science and Engineering Dep, Sona College of Technology, Salem-636 005, Tamilnadu, Email: jayamithu2002@gmail.com) : Personalized search framework for industrial safety and health information retrieval. J scient ind Res 2014, 73(6), 407-14.

Emergence of the WWW brought about new searching and querying difficulties. It is evident that the Internet and its most popular service WWW have changed our everyday lives. Normally the search engines use the keyword based querying methods to retrieve the web documents as a result. But the fact is most of the results retrieved are not relevant to the users, because of the contextual ambiguities. A programmer may search for the query "SAFETY", referring to the state of being safe in various context. While it is searched by a home maker, it refers to the home safety. If it is searched by an expert who is training the people in safety and health management, his need may be of different nature. In order to produce the result based on the context, Personalization Methods are introduced. In the proposed system, personalization is done in two phases, (i) Building User profiles (ii) Reranking the SERPs (Search engine Result Pages). The browsing behavior of the user is represented in the form of user profile which consists of static initial information and dynamic search history of the user. Ranking algorithm takes the both static and dynamic factors weight as input for personalized reranking operation. The degree of personalization is also measured using the Jaccard Co-efficient and Hamming Distance. A Safety and Health Management System (SHMS) is a systematic approach that manages safety and health activities. It is covering occupational safety and health programs, policies, and objectives into organizational policies and Procedures. The dataset from the SHMS domain is used for the experiment and the profiles of different types are created. It shows the percentage of improvement in the relevancy of search results under various conditions in terms of precision and recall.

1 illus, 2 tables, 18 ref

006300   Chopra S C;Mahajan R (Pharmacology and Medical Superintendent Dep, Adesh Institute of Medical Sciences and Research, Bathinda-151 101, Email: sccpharma@gmail.com) : Free of cost excel workbook for calculating internal assessment. J Res med Educ Ethics 2013, 3(1), 6-12.

Proper calculation of internal assessment (IA) in any field of education is a cumbersome, time consuming and labour-intensive process. To reduce labour and time consumption as also to increase the uniformity, the authors present a free-of-cost MS Excel-2010 workbook for IA calculation of Bachelor of Medicine and Bachelor of Surgery (MBBS) students, which can be adopted for other medical and non-medical courses with suitable minor alterations. This easy-to-use, selfexplanatory and free-of-cost excel workbook can be downloaded from http://www.bmsa.co.in/internal_assessment_excel_tool. Authors expect feedback from the readers and users and the same can be sent to sccpharma@gmail.com.

004197   Yalman Y;Erturk I (Computer Engineering Dep, Turgut Ozal Univ, Ankara, Turkey, Email: yyalman@turgutozal.edu.tr) : Secret data embedding scheme modifying the frequency of occurrence of image brightness values. Sadhana 2014, 39(4), 939-56.

The main purpose of this presented work is to develop a data embedding method based on a new digital image histogram modification approach. The proposed scheme fundamentally is concerned about the frequency of occurrence of the image brightness values of the cover image for the data embedding procedures. The proposed scheme effectively realizes both perceptual invisibility and statistical invisibility so that obtained covered images are highly robust against common perceptual and statistical steganalysis techniques. The scheme provides reasonably higher payload values than its counterparts, as well as providing comparatively improved PSNR results.

12 illus, 8 tables, 35 ref

003171   Shobha G;Sharma S C;Doreswamy (NO, R.V. College of Engineering, Bangalore) : Mining association rules for a large data sets. J Analysis Computn 2013, 9(2), 95-106.

Data mining is defined as the process of discovering significant and potentially useful patterns in large volumes of data. Discovering associations between items in a large database is one such data mining activity. In finding associations, support is used as an indicator as to whether an association is interesting. The objective of the research work is focused on investigating a technique for extracting associations, finding frequent patterns, correlations, or causal structures from the data source, which is derived from the current population survey conducted by the United States. The survey is conducted based on demographic and economical aspects. The association module that we have developed uses frequent pattern (FP) - growth method which needs only two databases scans when mining all frequent item sets. The first scan counts the number of occurrences of each item. The second scan constructs the initial FP-tree, which contains all frequency information of the original data sets. FP-tree is mined for finding the associations. Our experimental results show that the investigated system achieves an acceptable level of performance.

2 illus, 15 ref

003170   Shankaraiah N;NarayanaSwamy B K;Sangappa; Balaganoormath L B (Agricultural Extension Dep, UAS, GKVK, Bangalore-560 065, Email: shankar_mnks@yahoo.com) : Profile of farmers using MMS network for dissemination of technologies in Bangalore rural district. Int J Trop Agric 2013, 31(1-2), 73-7.

Mobile phones are tools that can help farmers to climb out of poverty. The mobile phone technology is being used creatively in poor countries to help spur development and reduce poverty, particularly in remote rural areas. A research study was undertaken to know the Profile of Farmers using MMS for Dissemination of Technologies. The study was conducted at Doddaballapur taluk of Bangalore Rural District of Karnataka during 2010-11. The respondents were 40 farmers selected using simple random technique. Findings reported that forty per cent of farmers had favourable attitude towards MMS network. Education, Farm size, Material possession, Economic motivation, Innovative proneness, Achievement motivation, Cosmopoliteness, Mass media participation and Extension participation had positive and significant relationship with attitude of farmers at one per cent level of significance. Whereas, cropping intensity, Irrigation intensity, Decision making ability and Social participation had positive and significant relationship with attitude of farmers at five per cent level of significance. As far as age was concerned, it was found that negative and significant relationship with attitude of farmers at five per cent level of significance. Other variables such as farming experience, occupation, family size and annual income were found to have non significant relationship with attitude of the farmers and eighteen variables fitted together in the regression model explained 84.00 per cent of the variation in the attitude of farmers about MMS network.

3 tables, 8 ref

003169   Jha R;Saini A K;Jha D;Jha A;Jha S (NO, Guru Gobind Singh Indraprastha Univ, New Delhi, Email: rashmijha1909@gmail.com) : ERP and lean six sigma: a pioneer journey from most critical problems to most critical success factors. Invertis J Sci Technol 2014, 7(3), 138-46.

To successfully take on an ERP system, SMEs need to be dynamic with changing time and emerging trends to have an edge over competitors. Despite all, there might be some common problems that may be always considered as foremost which influence SMEs success rate to achieve objectives. The central aim of this paper is to make an exploratory factor analysis (EFA) through SPSS 18.0 to analyze and prioritize the most critical problems (MCPs) during ERP implementation. In effect, SMEs can take care of these problems on war footing basis to realize its sustainable success stories with most critical success factors (MCSFs), by implementing Lean Six Sigma implementation to ERP.

9 tables, 21 ref

003168   Agrawal S K;Sahu O P (Electronics and Comunication Engineering Dep, National Institute of technology, Kurukshetra, Haryana, Email: skagarwal5@rediffmail.com) : A computationally efficient technique to design two-channel quadrature mirror filter banks. Invertis J Sci Technol 2014, 7(3), 147-57.

An efficient technique for designing two-channel finite impulse response quadrature mirror filter (QMF) bank is proposed. Low-pass analysis prototype filter of the filter bank is represented in polyphase form to reduce the computational complexity. An optimization problem is formulated as linear combination of square error of the overall transfer function of the QMF bank at the quadrature frequency and pass-band error, and stop-band residual energy of the low-pass analysis filter. An iterative solution which involves the computation of eigenvector corresponding to minimum eigenvalue of a matrix with a dimensionality equal to one half of filter coefficients is suggested. Simulation results show that the proposed method reduces the computational time and number of iterations with almost same peak reconstruction error (PRE) performance in comparison to other existing techniques. Design examples are included, illustrating the effectiveness and superiority of the proposed approach.

10 illus, 2 tables, 28 ref

002137   Singh J;Singh S (NO, Rayat Bahra Institute of Engineering and Nano Technology, Hoshiarpur-146 001, Email: jaipuneetsingh@gmail.com) : Review of the web metrics model. Int J appl Res Inf Technol Comput 2013, 4(1), 55-63.

The Internet is a network connecting millions of servers and billions of people around the world. Life without the Internet is nothing. However, very little research has been conducted on the size of the Internet. This paper has been written to review the most popular web metrics and most importantly to examine how it can play a role in improving information on the web and also the quality of that information. Here, we present a basic comparison between web analytics and web metrics. We have gone deep into the subject of web metrics, discussing its different paradigms.

7 illus, 13 ref

002136   Satapathy S C;Naik A (IEEE, Computer Science and Enginering Dep, Anil Neerukonda Institute of Technology and Sciences (ANITS), Vishakhapatnam-531 162) : Cooperative teaching-learning based optimisation for global function optimisation. Int J appl Res Inf Technol Comput 2013, 4(1), 1-17.

The teaching-learning based optimisation (TLBO) is recently being used as a new reliable, accurate and robust optimisation technique for global optimisation over continuous spaces. This paper presents a variation on the traditional TLBO algorithm, called the Cooperative Teaching-Learning Based Optimizar, or CoTLBO, employing cooperative behaviour to significantly improve the performance of the original algorithm. This is achieved using multiple swarms to optimise different components of the solution vector cooperatively. Application of the new TLBO algorithm on several benchmark optimisation problems shows a marked improvement in performance over the traditional TLBO algorithm.

7 illus, 2 tables, 27 ref

002135   Saha G K;Sandeep Kumar (NO, Centre for Development of Advanced Computing, Sector-V, Saltlake, Kolkata-700 091, Email: sahagk@gmail.com) : Clinical decision support system design issues. Int J appl Res Inf Technol Comput 2013, 4(1), 42-54.

In healthcare, computer science plays an important role in analysing and diagnosing medical problems and diseases. Artificial intelligence (AI) has revolutionised medical science. Nowadays, AI is in high demand in medicinal science. This paper describes important design issues related to the characteristics of the clinical decision support system (CDSS) and the methodologies used for its implementation. It defines how they are figured out for diagnosis of diseases and symptoms. These case-studies lead us to CDSS and help figure out the most optimal methodology and the best solution for diagnosing a medical problem. This paper aims to survey important CDSS research works and presents a case-study based on the analysis and comparison of various methodologies used in CDSSs. We find that every methodology has some good and some had aspects. Different methodologies for CDSSs use various parameters for solving medical diagnosis problems. Some methodologies are very good in one domain, whereas others are good in a different domain, but the aim of all methodologies is the same, i.e., to solve medical diagnosis problems.

35 ref

002134   Purkait S (Vinod Gupta School of Management, Indian Institute of Technology, Kharagpur-721 302, Email: swapan@nettech.in) : Assessing anti-phishing awareness among undergraduate students in India. Int J appl Res Inf Technol Comput 2013, 4(1), 2641.

Fraudulent activities on the Internet, especially phishing, have grown to an unprecedented level. Phishing can result in identity theft, financial losses and can also clog cm email server. Although a number of technologies related to counter -measures ranging from SSL/TLS (Secure Sockets Layer/Transport Layer Security) to web browser-based warnings have been explored, user awareness remains fundamental against any anti-phishing activity. With the growing unemployment in India, a very large amount of undergraduate students are at a risk of becoming an innocent prey of phishers offering lucrative jobs. This study was conducted to empirically investigate the incidence of undergraduate students becoming victims of phishing attacks in India. We simulated a scenario where students were required to visit a fake website and give details of personal login information. Students irrespective of their computer know/edge visited the phishing website ignoring the information given on the security bar in the web browser.

4 illus, 5 tables, 32 ref

002133   Pal S K;Sarma S S (Computer Applications Dep, NSHM College of Management and Technology, Kolkata-700 053, Email: sarbojay@gmail.com) : Degree-constrained MST algorithm. Int J appl Res Inf Technol Comput 2013, 4(1), 18-25.

This paper shows generation of minimal spanning trees based on two constraints, namely degree constraint and node weightage, of a simple symmetric and connected graph G. A new algorithm is proposal here to find out the minimal spanning tree of graph G based on the average degree sequence factor of the nodes of the graph. The time complexity of the problem is less than O(N log|E|) compared with the existing algorithms' time complexity, O{|E| log|E|}+C of the Kniskal algorithm, which is optimum. The goal is to design an algorithm that is simple, elegant, efficient, easy to understand and applicable in the field of special areas like constraint-based network design, mobile computing with specific criteria and other special applications in the field of engineering and science.

1 table, 12 ref