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2016 | Buch

Proceedings of First International Conference on Information and Communication Technology for Intelligent Systems: Volume 2

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Über dieses Buch

This volume contains 60 papers presented at ICTIS 2015: International Conference on Information and Communication Technology for Intelligent Systems. The conference was held during 28th and 29th November, 2015, Ahmedabad, India and organized communally by Venus International College of Technology, Association of Computer Machinery, Ahmedabad Chapter and Supported by Computer Society of India Division IV – Communication and Division V – Education and Research. This volume contains papers mainly focused on ICT and its application for Intelligent Computing, Cloud Storage, Data Mining, Image Processing and Software Analysis etc.

Inhaltsverzeichnis

Frontmatter

ICT Based Security and Privacy Applications

Frontmatter
POS Word Class Based Categorization of Gurmukhi Language Stemmed Stop Words

Literature in Indian language must be classified for its easy retrieval. In Punjabi literature classifier, five different categories: nature, romantic, religious, patriotic and philosophical, are manually populated with 250 poems. These poems are pre-processed through data cleaning, tokenization, bag of word, stop word identification and stemming phases. Due to unavailability of Punjabi stop words in public domain, manual collection of 256 stop words are done from poetry and articles. After stemming, 184 unique stemmed words are identified. Based on part of speech tagging, 184 stop words are categorized into 98 adverbs, 7 conjunctions, 43 verbs, 24 pronouns and 12 miscellaneous words. These unique 184 stemmed words are being released for other language processing algorithm in Punjabi. This paper concentrates on providing better and deeper understanding of Punjabi stop words in lieu of Punjabi grammar and part of speech based word class categorization.

Kaur Jasleen, R. Saini Jatinderkumar
Techniques and Challenges in Building Intelligent Systems: Anomaly Detection in Camera Surveillance

Security is tedious, complex and tough job in today’s digitized world. An attempt is made to study and propose an intelligent system for surveillance. Surveillance camera systems are used for monitoring and controlling the security. Anomaly detection techniques are proposed for designing the intelligent control system. In the paper challenges in detection and processing of anomaly in surveillance systems are discussed and analyzed. Major components related to an anomaly detection technique of camera control system are proposed in the paper. Surveillance data is generated through camera, and then this data is transmitted over the network to the storage. Processing is to be done on real time basis and if there is any anomaly detected, the system must produce an alert. This paper is an attempt to study soft computing approaches for anomaly detection.

Dinesh Kumar Saini, Dikshika Ahir, Amit Ganatra
Ensemble Recommendation for Employability Using Cattell’s Sixteen Personality Factor Model

In corporate world, recruiting the best candidate for an organization is a big challenge these days. Whilst it is agreed that basic skills, technical abilities and expertise in a particular domain of interest are central to employability, there are arguably a number of additional factors which guide employability. To fill the void between the employee and the recruiter, is the prime idea behind the current research work. The paper highlights the personality traits of potential employees identified through Cattell’s 16 Personality Factor Model and elaborates the areas which the present corporate world should focus upon. The paper will show direction to the corporate employers especially seeking long term relationship with the employees regarding selection of such workforce which can sustain in the challenging and vibrant global work environment. The new approach of using psychology with ensemble learning will also provide new insights into the research works related to emotional intelligence.

Ashima Sood, Rekha Bhatia
Search Logs Mining: Survey

Search engine process millions of query and collect data of user interaction every day. These huge amount of data contains valuable information through which web search engine can be optimized. Search engine mostly relies on explicit judgement received from domain experts. To survive the competition search engine must understand user’s information needs very well. Search logs provide implicit data about user’s interaction with search engine. Search logs are noisy, they contain data of both successful search and unsuccessful search. The challenge is to accurately interpret user’s feedback to search engine and learning the user access patterns, such that search engine will better be able to cater the user’s information needs. User feedback can be used to re-rank the search result, query suggestion and URL recommendation.

Vivek Bhojawala, Pinal Patel
An Effective Model for Face Detection Using R, G, B Color Segmentation with Genetic Algorithm

Face detection is a grave concern in digital image processing and automatic face recognition system. This research work proposed a complete mechanism for face detection using R, G, B color segmentation and search optimization scheme with Genetic Algorithm, also refer a discrete technique that is appropriate for combinatorial problems. In this paper we tried to build an R, G, B color range that will shelter a skin part from an image and handover a best fitted solution as fitness function for GA to perform further operation to detect images in complex background. In this paper our tryout are to enrich detection accuracy in lesser computational time. The evaluation shows that this algorithm is capable to detect the face from complex background conditions and for side faces too. This algorithm is tested on a wide number of test images. All the simulation has been done on MATLAB.

Devesh Kumar Srivastava, Tarun Budhraja
Analysing Performance Disruption of MANET Under Explicit Flooding Attack Frequency

The number of routing protocol is available in Mobile Ad hoc Networks (MANETs), but none of them is perfect as it is hard to achieve the security in it. The MANETs is in vulnerable of different attacks because the network is scalable and has very dynamic mobile nodes. The performance of protocols is severely affected in the presence of malicious nodes as these causes routing information to be erroneous and introduces excessive traffic load and inefficient routing. In this paper, we analyse the network performance extensively using Ad hoc On Demand Distance Vector (AODV) routing protocol in the presence of a flooding attack with specific frequency rate. The NS2 network simulator is used to analyse this flooding attack on AODV and its impact are shown using various performance metrics like Packet Delivery Ratio (PDR), throughput with variable flooding rates and malicious nodes etc.

Priyanka Wadhwani, Sourabh Singh Verma
An Efficient Agro-Meteorological Model for Evaluating and Forecasting Weather Conditions Using Support Vector Machine

Weather prediction is an essential area of analysis in everyday life. Climate forecasting is one of the highly relevant attributes affecting agricultural sectors and industries. Predicting climate conditions is necessary for diverse areas. Metrological department facing the greater challenge to predict the state of the environmental temperature to forecast the weather conditions based on the present, future time for expecting the rainfall. This paper majorly focuses on handling Weather data using big data statistical analysis and for effective forecasting. Support Vector Machine (SVM) predictive based modeling is used for classifying the weather dataset by using regression analysis and thereby forecasting for predicting weather conditions which is suitable for agriculture. Experiment the input dataset parameters of weather like mean temperature, mean dew point, max_sustained wind speed, mean sea level pressure, mean station pressure max_ temperature, min_ temperature, precipitation amount, max_wind gust, snow depth. The results are compared with single decision tree.

Baghavathi Priya Sankaralingam, Usha Sarangapani, Ravichandran Thangavelu
Simulation of a Model for Refactoring Approach for Parallelism Using Parallel Computing Tool Box

Refactoring is the process of retaining the behavior of a program by making changes to the structure of a program. Initially refactoring is used only for sequential programs, but due to highly configurated architectural availability, it also aids parallel programmers in implementing their parallel applications. Refactoring provides many advantages to parallel programmers, in identifying independent modules, in refining process of programs, it also helps in separating concerns between application and system programmers, and it reduces the time for deployment. All mentioned advantages benefit the programmer in writing parallel programs. The approach for refactoring using multi core system is already developed. Hence all these advantages made us to thought of a system to develop refactoring approach for parallelism which uses heterogeneous parallel architectures which uses combination of both Graphic Processing Unit (GPU) and Central Processing Unit (CPU). A Tool in MATLAB, Parallel Computing Toolbox can be used to execute programs on multiple processing elements simultaneously with local workers available in the toolbox, which takes benefit of GPUs. This tool box uses complete processing speed of multi core system to execute applications on local workers without changing the code. Our suggested model can be simulated by using Parallel Computing Toolbox.

Shanthi Makka, B. B. Sagar
Dynamic Congestion Analysis for Better Traffic Management Using Social Media

Social media has emerged as an imperative tool for addressing many real-life problems in an innovative way in recent years. Traffic management is a demanding problem for any populous city in the world. In the current paper, we explore how the dynamic data from social media can be employed for continuous traffic monitoring of cities in a better way. To accomplish this, congestion analysis and clustering of congested areas are performed. With the term congestion, we denote co-gatherings in an area for two different occasions within a defined time interval. While doing so, we introduce a novel measure for quantifying the congestion of different areas in a city. Subsequently, association rule mining is applied to find out the association between congested roads. To our surprise, we observe a major impact of various gatherings on the disorder of traffic control in many cities. With additional analyses, we gain some new insights about the overall status of traffic quality in India from the temporal analysis of data.

Sujoy Chatterjee, Sankar Kumar Mridha, Sourav Bhattacharyya, Swapan Shakhari, Malay Bhattacharyya
An Intelligent Optimization Approach to Quarter Car Suspension System Through RSM Modeled Equation

This paper present on minimum value of rider comfortness vibration values to obtain maximum rider comfortness during riding. The simulation model was being achieved with the help of MATLAB/Simulink for further process to Genetic Algorithm through Response surface methodology modeled equation. As the response surface methodology is a long established technique in optimization for experimental process. Recently a new intelligent approach to the quarter car suspension system has been tried with response surface methodology and genetic algorithm which is new in the computational field. For the Response surface methodology, an experimental design was chosen in order to order to obtain the proper modelling equation. Later this modeled equation was served as evaluation function or objective function for further process into genetic algorithm. In Genetic algorithm case, the optimality search was carried without the knowledge of modelling equations between inputs and outputs. This situation is to choose the best values of three control variables. The techniques are performed and results indicated that technique is capable of locating good conditions to evaluate optimal setting, to reduce comfortness vibrations for maximum comfortness.

M. B. S. Sreekar Reddy, S. S. Rao, P. Vigneshwar, K. Akhil, D. RajaSekhar
MEAL Based Routing in WSN

Wireless sensor network is growing area. Characteristics of WSN (Wireless Sensor Network) is such that nodes are running on limited battery power. As each device are now trying to connect to WAN, this field has caught many eyes of researchers. We are modifying LEACH in such a way that it include advantages of both the energy leach (E-LEACH) and multi-hop leach (MH-LEACH) in proposed protocol. We have deployed our proposed MEAL (Multi-hop Energy Aware Leach) in our college campus, and we have monitored our campus environment by CO2 level and temperature of each department. Our protocol giving best output with respect to energy usage compare to LEACH. EL-LEACH and ML-LEACH. We have used TINY-OS and TINY-VIZ environment for configuring our motes.

Tejas Patalia, Naren Tada, Chirag Patel
Intelligently Modified WFQ Algorithm for IEEE 802.16 Resource Allocations

IEEE 802.16 standard more commonly known as WiMAX is an upcoming standard popularized by WiMAX Forum. Quality of service in WiMAX is provided with help of five scheduling services with different properties. WiMAX standard does not define provisioning for providing bandwidth allocation to different scheduling services. Most algorithms focus on traffic classes having rigid time constraints and classes without real time requirements are neglected This paper proposes modified Weighted Fair Queuing Algorithm using concepts of fuzzy logic for grant of bandwidth to all types of traffic. It enables fair distribution of network resources to low priority traffic classes and helps to improve their performance. Simulations have been done for performance justification and results are encouraging.

Akashdeep
A Comparative Study of Secure Hash Algorithms

Important responsibility of every organization is to provide an adequate security and confidentiality to its electronic data system. Data should be protected during transmission or while in storage it is necessary to maintain the integrity and confidentiality of the information represented by the original data. Message digests are the condensed representation of a message after processing that message through some mathematical algorithm which is iterative in nature and one way. Integrity of message is ensured by these algorithms: any change to the message, with a very high probability, results in a different message digest. This paper explains the implementation of all available secure hash algorithms (SHA) and their performance evaluation. Performance evaluation has been done in terms of security. Randomness of all the hash algorithms have been evaluated with K-S, Chi Square and Autocorrelation tests. It is observed that all available SHAs are very useful in their area of applications because they produce totally random output even if their input is highly correlated. Hence it is found that a very high level of security attained using hash algorithms. It has been observed that SHA-512 provides a very high level of security because it has 512 bits inside which are randomly distributed but it is a bit lengthy and time taking.

Smriti Gupta, Sandeep Kumar Yadav, Alok Pratap Singh, Krishna C. Maurya
Enhancing Data Security Using AES Encryption Algorithm in Cloud Computing

Cloud Computing offers computation as per utility of the customer and hence it is known as utility computing. This model is attractive mainly for business oriented people because it reduces total cost of operation, maintainance cost, increases return of investment. But the only thing that is impeding popularity of cloud computing is security issues. This paper discuss about AES encryption algorithm (RIJNDAEL) that secure data stored on cloud. This method is more efficient than DES which is symmetry based algorithm and offers 56 bits key size whereas RIJNDAEL algorithm is asymmetry and offers 128 bits key and 128 bits blocks. RIJNDAEL is block cipher algorithm and is secure against cryptanalytic attacks. It is versatile, which means it can be implemented on different working environment efficiently, its key agility is good which means setup time of key is less and this algorithm is easy to be understood and using it. Rijndael requires less memory and hence make it is well suited for environments which have less space such as 8 bit micro-processor, also it shows marvellous performance in terms of software and hardware implementation.

Snehal Rajput, J S Dhobi, Lata J Gadhavi
Investigating the Performance of Energy Efficient Routing Protocol for MANET Under Pareto Traffic

Mobile Ad Hoc Network (MANET) is a multi-hop, infrastructureless wireless network with limited bandwidth and battery power. The investigation of energy efficient protocols under Pareto traffic is being carried out in this paper. The routing protocols taken for analysis are ECG_AODV [1, 2], ECNC_AODV [3], EBG_AODV [4, 5] and Energy plus Node Cache plus Gossip (E+NC+G) and compare it with AODV. The behavior of all these algorithms under CBR traffic is already studied in [6]. Here we have focused on Stochastic (Pareto) traffic source. Based on the simulation results, we observed that there is reduction in energy and overhead up to 10–30 % with 2–12 % deprivation in the delivery ratio for all protocol as compared to AODV.

Dhiraj Nitnaware
Implementing and Evaluating Collaborative Filtering (CF) Using Clustering

A tremendous increase has taken place in the amount of online content. As a result, by using traditional approaches, service-relevant data becomes too big to be effectively processed. In order to solve this problem, an approach called clustering based collaborative filtering (CF) is proposed in this paper. Its objective is to recommend services collaboratively in the same clusters. It is a very successful approach in such settings where interaction can be done between data analysis and querying. However the large systems which have large data and users, the collaboration are many times delayed due to unrealistic runtimes. The proposed approach works in two stages. First, the services which are available are divided into small clusters for processing and then collaborative filtering algorithm is used in second stage on one of the clusters. It is estimated to decrease the online execution time of collaborative filtering algorithm because the number of the services in a cluster is much less than the entire services available on the web.

Sachin S. Agrawal, Ganjendra R. Bamnote
Double Fully Homomorphic Encryption for Tamper Detection in Incremental Documents

The famous scheme of Van Dijk, Gentry, Halevi and Vaikuntanathan (DGHV) style of Fully Homomorphic Encryption (FHE) is simple to implement. This paper proposes how this scheme can be modified and used for double encryption to secure files stored at third party like Cloud service provider (CSP). The files belong to an incremental text model which is followed by majority of confidential documents. Encryption is similar to a homomorphic hash function. A protocol is also proposed to detect if files have been tampered, and the tampering can be located up to single file level or up to a word of file level.

Vishnu Kumar, Bala Buksh, Iti Sharma

Intelligent Systems for Health and IT Applications

Frontmatter
Enhancement of GSM Stream Cipher Security Using Variable Taps Mechanism and Nonlinear Combination Functions on Linear Feedback Shift Registers

With the advance wireless communication, data security became a significant concern. The GSM standard hardware level encryption technique uses A5/1 algorithm circuit which embedded in the Mobile Equipment. A5/1 algorithm uses Linear Feedback Shift Register (LFSR) to produce a key streams for encode the information sent between the mobile station and the base station. It is a secure cipher among all the versions of ciphers using in GSM. However, latest research studies demonstrate that A5/1 can be subjected to several attacks owing to feeble clocking mechanism which results in a low rate of linear complexity. To overcome from these issues, we introduce a feedback tap mechanism enhanced by variable taps and four nonlinear combination functions. Analysis shows that the proposed method has a high algebraic degree of correlation immunity against basic correlation attack, mathematical attack, linear estimate attack and Berlekamp-Massey attack.

Darshana Upadhyay, Priyanka Sharma, Srinivas Sampalli
Implementation of Taguchi Method in the Optimization of Roller Burnishing Process Parameter for Surface Roughness

Need of industrial growth for developing country gives rapid acceleration in the field of technical research. Industries are very much aware of producing mechanical component with good surface quality without allowing a margin of error. Among the different challenges of industry, surface quality is the key factor now a day’s which can be improved by a novel after machining process known as burnishing process. This paper is mainly concerned with the effect of different process parameter on the surface roughness of aluminum alloy and the optimization of response measure. To achieve the goal of proposed work first pilot experiment is intended to ascertain the range of different parameters required for the experimental design methodology. Analysis of variance and signal to noise ratio are applied as statistical analysis to find out the significant control factor and optimize the level. The result shows the optimum set of process parameter having a value of 850 RPM spindle speed, 8 mm interference, 0.024 mm/rev feed and 4 no. of tool pass predict 0.010 µm surface roughness value which is having a greater agreement with the experimental value.

Kiran A. Patel, Pragnesh K. Brahmbhatt
Relationship Strength Based Access Control in Online Social Networks

Online social networking site is a platform, where a person can communicate with others by creating his own profile. Lots of contents (e.g., photos, videos, etc.) are being generated every minute, because of its popularity. Generally, users do not want to share their all information with everyone as some of them are very sensitive, this raises privacy and confidentiality issues. So, Online Social Network (OSN) requires an effective and reliable access control mechanism to protect the users’ contents. This paper presents a novel Relationship Strength Based Access Control (RSBAC) mechanism which allow users to provide the access to their contents based on intimacy degree or closeness with respect to their friends. A reliable intimacy degree is calculated by considering the social activities and profile similarities between the friends. The content owner can make the access control policy by assigning different range of intimacy degrees. Users whose intimacy degrees are in the acceptable range, can access the contents.

Abhinav Kumar, Nemi Chandra Rathore
Enhancement for Power Transfer Loadability in Long Transmission Line by Reactive Power Compensation

This paper presents the reactive power management for 765 kV Extra High Voltage (EHV) transmission system. Reactive power compensation is used to control the power system voltage stability and increase the power transfer capability of the transmission line. The proposed 765 kV transmission line between Sipat—Seoni in India is simulated on PSCAD Library. The shunt compensation has been stimulated in the transmission line to maintain the system voltage. The effect of voltage, active power and reactive power has been studied at different transmission length and verifying the optimization transmission length for high power transfer. In order to increase the power transfer capability of the transmission system the series compensation is used. The work presented here also compares the shunt and series compensation using PSCAD simulation for better voltage control and its performance for power transfer capability.

Manisha Jaswani, Satyadharma Bharti
A Contextual Approach for Modeling Activity Recognition

In this paper, we propose a contextual approach for modeling human activity recognition. Activity recognition is performed using motion estimation based on context. Here contextual information is derived from motion, which is predicted from previous frames. This greatly enhances the process of activity recognition, by setting up a particular scenario which helps in constructing the activity. Context is acquired with the help of external inputs which surround an activity and help towards accurate reasoning about that activity. Context Modeling for any object can be done in terms of its relationship to other objects, called as contextual associations that lead towards accurate estimate of object position and presence. Here our focus is on vision based activity recognition. This process involves efficient feature extraction and subsequent classification for image representations. Classification accuracy is enhanced through Support Vector Machine (SVM) classifier, used along with Principle Component Analysis.

Megha Sharma, Bela Joglekar, Parag Kulkarni
A Fuzzy Trust Enhanced Collaborative Filtering for Effective Context-Aware Recommender Systems

The Recommender systems (RSs) are well-established techniques for providing personalized recommendations to users by successfully handling information overload due to unprecedented growth of the web. Context-aware RSs (CARSs) have proved to be reliable for providing more relevant and accurate predictions by incorporating contextual situations of the user. Although, collaborative filtering (CF) is the widely used and most successful technique for CARSs but it suffers from sparsity problem. In this paper, we attempt toward introducing fuzzy trust into CARSs to address the problem of sparsity while maintaining the quality of recommendations. Our contribution is twofold. Firstly, we exploit fuzzy trust among users through fuzzy computational model of trust and incorporate it into context-aware CF (CACF) technique for better recommendations. Secondly, we use fuzzy trust propagation for alleviating sparsity problem to further improve recommendations quality. The experimental results on two real world datasets clearly demonstrate the effectiveness of our proposed schemes.

Sonal Linda, Kamal K. Bharadwaj
An Optimal LEACH-Based Routing Protocol to Balance the Power Consumption and Extending the Lifetime of the WSNs

Wireless sensor networks (WSNs) are made of tiny sensor nodes (SNs) and a base station (BS). As these tiny sensor nodes run on non- rechargeable batteries due to their wide distribution the lifetime of the network is of great importance. LEACH routing protocol that is the earliest hierarchical routing protocol suffers from some drawbacks such as not considering the remaining energy of SNs and the clusters’ size to prolong the network life time to a higher level. In this paper we propose an efficient LEACH-based routing protocol in an effort to prolong the lifetime of WSNs. The proposed protocol consider residual energy of sensor nodes, their distance from base station and the size of each cluster to prolong the network life to a higher level. The result of our simulation indicates that our improved protocol works significantly better than existing LEACH its improved versions K-LEACH and T-LEACH in case of balancing the energy consumption of the network.

Yahya Kord Tamandani, Mohammad Ubaidullah Bokhari, Qahtan Makki
Social Spider Algorithm Employed Multi-level Thresholding Segmentation Approach

Multi-level based thresholding is one of the most imperative techniques to realize image segmentation. In order to determine the threshold values automatically, approaches based on histogram are commonly employed. We have deployed histogram based bi-modal and multi-modal thresholding for gray image using social spider algorithm (SSA). We have employed Kapur’s and Otsu’s functions and in order to maximize its value, we have employed social spider algorithm (SSA). We have used the standard pre-tested images. Results have shown that the social spider algorithm has out-performed the results obtained by Particle Swarm Optimization (PSO) as far as optimal threshold values and computational time are concerned.

Prateek Agarwal, Rahul Singh, Sandeep Kumar, Mahua Bhattacharya
Simulation Based Comparison Between MOWL, AODV and DSDV Using NS2

Mobile Ad-hoc network is collection of mobile nodes which can move anywhere within the network and because of the mobility of node which have limited resources, routing faces challenges as maximize the delivery ratio and minimize the delay with less consumption of nodes resources. MANET does not have any central coordinator. AODV is the most popular MANET routing protocols as it works very well in the dynamic nature of MANET. AODV is based on BFS and high scalability. DSDV is proactive routing which is very efficient for the small scale network. It uses a routing table maintained by every node of the network which contain the information about the network and remaining nodes of the network. MOWL is the new enhancement of basic OWL which is based on HS. MOWL tries to achieve scalability of basic OWL by using multiple BFS. In this research we going to analysis and compare the simulation results of MOWL with well known MANET routing protocols.

Balram Swami, Ravindar Singh
PeTelCoDS—Personalized Television Content Delivery System: A Leap into the Set-Top Box Revolution

At home, on the television, the sheer number of Channels and the vast number of Programs on each Channel has itself made the task of identifying the “appropriate” program to watch difficult for the common user. There is a need of a system to generate suggestions/recommendation to the common user about which Programs to watch and when. In this paper, we propose a method and system which assists the user to choose which Programs on which Channels to watch without any inputs from the Viewer about his “Likes” or “Dislikes”. It learns from the Viewer Implicitly over time and learns all the patterns that the Viewer exhibits over the course of Television watching.

Mangesh Bedekar, Saniya Zahoor, Varad Vishwarupe
Wave Front Method Based Path Planning Algorithm for Mobile Robots

Path planning problem revolves around finding a path from start node to goal node without any collisions. This paper presents an improved version of Focused Wave Front Algorithm for mobile robot path planning in static 2D environment. Existing wave expansion algorithms either provide speed or optimality. We try to counter this problem by preventing the full expansion of the wave and expanding specific nodes such that optimality is retained. Our proposed algorithm ‘Optimally Focused Wave Front algorithm’ provides a very attractive package of speed and optimality. It allocates weight and cost to each node but it defines cost in a different fashion and employs diagonal distance instead of Euclidean distance. Finally, we compared our proposed algorithm with existing Wave Front Algorithms. We found that our proposed approach gave optimal results when compared with Focused Wave Front Algorithm and faster results when compared with Modified Wave Front Algorithm.

Bhavya Ghai, Anupam Shukla
Multimodal Database: Biometric Authentication for Unconstrained Samples

Biometrics provides a reliable authentication of a human in a wide variety of applications such as security systems, surveillance and human-computer interaction. Biometric system was started with utilization of a single biometric feature referring as a unimodal biometric system, which is unable to fulfill the security needs extensively in a highly sensitive environment and hence multibiometrics has emerged gaining more importance in the research area. Though there is a shortage of publicly available multimodal databases acquired in real unconstrained environment, a multimodal biometric system can succeed with the assistance of suitable multiple sensors providing higher accuracy rate than that of unimodal biometrics, of course subject to cost, time and subject’s acceptance This paper presents a new multimodal dataset which is developed using simple acquisition setup and devices to capture features belonging to the same person in uncontrolled scenarios. The dataset is composed of color images collected from 100 subjects (50 male and 50 female) under the age group 18–22. Totally 6 samples per trait were collected at different time internals between 2011 and 2014 with various occlusions. The dataset is also tested and analyzed by our developed biometric recognition system.

S Poornima
Study and Comparison of Non-traditional Cloud Storage Services for High Load Text Data

With the fastest growing nature of application migrating to cloud, the problem of choosing the best suitable cloud service for storage is always a challenge. The cloud storage services are majorly paid service and some of them are designed to deal best with specific kinds of data like read only or update only. Some of the services are designed to match small amount of data blocks and some of the services are designed to best match the larger blocks of data. Many of the application uses file storage, rather than RDBMS storage structure on cloud services. The storage hardware, replication and distribution policies are decided and controlled by cloud storage service providers. The storage options are converted and associated with manageable access portals. This access portal demonstrates the user interface view of the storage visualization and usability. In this paper we compare multiple cloud storage services on high textual data loads and implement an algorithm to choose the best cloud storage service based on cost and storage efficiency.

L. Srinivasa Rao, I. Raviprakash Reddy
Attenuation of Broadband Problems Using Data Mining Techniques

The aim of this paper, is to provide appropriate solution of customer complaints on time and up to the mark has been considered a “defensive marketing” strategy or a “zero- defections” strategy, which reduces client disappointment. Overseeing client disappointment goes with web client grumbling administration. It is the discriminating issue for online client administration arrangements and e-CRM. The problems addressed in this paper are, (1) Scrutinize the sources and causes of online complaints; (2) Evaluating efficient ways of handling customer complaints in different categories and (3) Use of data mining techniques to provide solution for broadband issues. The paper proposed that e-businesses should provide excellent online customer services and response time of customers’ requests/complaints must be much reduced in order to retain customers.

Archana Singh, Soham Benerjee, Sumit Shukla, Shubham Singhal
Chameleon Salting: The New Concept of Authentication Management

Entity authentication by means of keying in Username and Password has been adopted as the de-facto standard in many Internet based and enterprise based applications the world over. The service providers have always been bogged down by Information Security breaches and Cyber Attacks in the recent past, and the industry has time and again stood against odds and has been able to imbibe the best of security practices to beat back security breaches especially in the domain concerning Entity Authentication. Authentication process needs to be made robust and hardened; Salting of password is practiced by the application service provider to ensure security to the end-customer. Technology today offers protection and also provides the tools to the unscrupulous elements by means of cracking Username and Password. No amount of technology and processes is said to be adequate to keep away the perpetrator in this domain. Chameleon Salting is an innovative initiative to enhance security to the end user, where the end user is provided a secure environment for entity authentication even without the user having to implement or change the way the application is being used. Its implementation will lower impact of a loss, thereby providing better protection to the customers.

Binoj Koshy, Nilay Mistry, Khyati Jain
Identification of the Choice of Drugs in Epilepsy by the Method of Classification and Regression Tree

Data Mining helps its users deduce important information from huge databases. In medical stream, practitioners make use of huge patient data. Any effective medical treatmentis achieved after complete survey of ample amount of patient data. But practitioners usually faced with the obstacle of deducing pertinent information and finding certain trend or pattern that may further help them in the analysis or treatment of any disease. Data Mining is such a tool which sifts through that voluminous data and presents the data of essential nature. In this paper, we have designed a five-step data mining model that will help medical practitioners on determining the appropriate drug to be used in ministration for epilepsy. Most of the epileptic seizures are managed through drug remedy, particularly anti-convulsant drugs. The choice is most often related to other aspects particular to every patient. The trick to building a successful predictive model is to include parts of data in your database that describes what has happened in the past. There are a wide range of older as well as recent anticonvulsants present in market. Our paper will take into consideration both the older and the recent anticonvulsants and other factors to justify the use of a drug suitable for treatment in epilepsy. To determine the drug choice for treatment in different epilepsy, we have selected the classification method. Decision trees are a sort of data mining technology that has been around for almost 20 years now. They are now increasingly being used for prediction.

Vivek Kshirsagar, Anil Karwankar, Meghana Nagori, Kailas Elekar

Intelligent Managerial Applications for ICT

Frontmatter
Encryption of Motion Vector Based Compressed Video Data

Enormous size of video data for natural scene and objects is a burden, threat for practical applications and thus there is a strong requirement of compression and encryption of video data. The proposed encryption technique considers motion vector components of the compressed video data and conceals them for their protection. Since the motion vectors exhibit redundancies, further reduction of these redundancies are removed through run-length coding prior to the application of encryption operation. For this, the motion vectors are represented in terms of ordered pair (val, run) corresponding to the motion components along the row and column dimensions, where ‘val’ represents value of the motion vector while ‘run’ represents the length of repetition of ‘val’. However, an adjustment for having maximal run is made by merging the smaller run value. Eventually we encrypted the ‘val’ components using knapsack algorithm before sending them to the receiver. The method has been formulated, implemented and executed on real video data. The proposed method has also been evaluated on the basis of some performance measures namely PSNR, MSE, SSIM and the results are found to be satisfactory.

Manoj K Mishra, Susanta Mukhopadhyay, G. P. Biswas
A Hybrid Technique for Hiding Sensitive Association Rules and Maintaining Database Quality

In this digital world, data mining is a decisive for innovation and better services for user, but it raises the issues about individual privacy. Privacy can be achieved by hiding sensitive or private information in database before publishing it for innovation. This paper presents a hybrid technique for hiding sensitive association rules, which combines two heuristic based techniques viz. Decrease Support and Decrease Confidence of sensitive rule for selection and modification of items from the transactions. The proposed hybrid technique combines advantages of both algorithms to maintain the quality of the database and preserve the privacy of database. From the experimental results it is observed that proposed algorithm is competent to maintain privacy and database quality.

Nikunj H. Domadiya, Udai Pratap Rao
A Review on Load Balancing of Virtual Machine Resources in Cloud Computing

An effective load balance (LB) management achieves high performance computing (HPC) and green computing. Users can run their jobs on virtual machines (VMs). Virtual machine (VM) has own resources (CPU and memory). VM migrates from host to another host during fail of VM, hot spot and high resource demand. Effective LB management is based on scheduling policy and management Strategies. In this paper it is discussed the available scheduling mechanisms, goals and strategies of load balancing techniques. The aim of this work to elaborate the key analysis of research works on LB.

Pradeep Kumar Tiwari, Sandeep Joshi
Design of Square Shaped Polarization Sensitive Metamaterial Absorber

In this paper, the polarization sensitive metamaterial absorber is proposed. The metamaterial absorber structure consist of a plus shaped structure surrounded by square loop has been proposed. The proposed metamaterial absorber unit cell provides approximately unity (99.99 %) absorption at 16.25 GHz. The design of an ultrathin polarization sensitive absorber based on Ku-band applications. Absorber design has been simulated for different incident and polarization angles to tune the single band and dual band response for different frequency slots of Ku-band. To obtain best response, FR-4 substrate material having substrate height of 1 mm is used. This metamaterial absorber is used in stealth technology for battlefield, solar cell and airborne radar.

Vandana Jain, Sanjeev Yadav, Bhavana Peswani, Manish Jain, H. S. Mewara, M. M. Sharma
RSM and MLR Model for Equivalent Stress Prediction of Eicher 11.10 Chassis Frame: A Comparative Study

The main objective of the study is to compare the prediction accuracy of Response Surface Methodology (RSM) and Multiple Linear Regressions (MLR) model for the Equivalent stress of the chassis frame. The chassis frame is made of two sidebars connected with a series of crossbar. The web thickness, upper flange thickness and lower flange thickness of sidebar becomes the design variables for the optimization. Since the number of parameters and levels are more, so the probable models are too many. The variants of the frame are achieved by topology modification using the orthogonal array. Then Finite Element Analysis (FEA) is performed on those models. RSM model and MLR model are prepared using the results of FEA to predict equivalent stress on the chassis frame. The results indicate that predictions of RSM model are more accurate than predictions of MLR model.

Tushar M. Patel, Nilesh M. Bhatt
Gender Classification by Facial Feature Extraction Using Topographic Independent Component Analysis

Recognition of gender from face image has attracted a huge attention now a days. Many identification systems are being developed to identify a person, as most of the technique for gender classification stand on facial features. In this paper, we presented a gender classification framework consist of a series of phases for determining the gender as the final output. Initially we start by detecting the face from an image using Viola Jones and then extract the facial feature using the Topographic Independent Component Analysis. The features extracted here are used to train the SVM classifier for the classification step. Our experimental result gives the best accuracy in determining the images as of male or female and gives average performance of 96 % correct gender identification on images.

Shivi Garg, Munesh C. Trivedi
Provision of XML Security in E-Commerce Applications with XML Digital Signatures Using Virtual Smart Card

The paper aims at enhancing XML security by generating an XML digital signature capable of providing the major security features such as authentication, integrity, non-repudiation and confidentiality [14]. It also extends the concept of Information hiding which overcomes the hidden problem of traditional XML digital signature generation called “MID-WAY READING”. The security of the document is ensured by a process called ‘information hiding’. The document to be sent is digitally signed as well as encrypted and thereby ensuring excellent security level during the business transactions in an e-commerce environment and in addition to that, the private key used for signing the document is stored in a virtual smart card that provides enhanced security.

Joannah Ravi, Balamurugan Balusamy
Fuzzy Weighted Metrics Routing in DSR in MANETs

Communication path from source node to destination node in MANET is affected due to arbitrary movement, connection break down, power supply, bottleneck traffic, security etc. Hence, while designing the routing protocols these aspects are taken into account. Therefore, in this paper, we improve the existing DSR routing protocol by applying fuzzy inference system that offers a natural way of accepting multiple input constraints which are uncertain and imprecise in nature. The fuzzy weighted logic input metrics are hop count, stability factor and output metric fuzzy cost is dynamically calculated using MATLAB Fuzzy logic toolbox. Simulations are carried out using NS2.35 simulator and results show better performance of modified DSR protocol than DSR in terms of Packet delivery ratio and delay.

Vivek Sharma, Bashir Alam, M. N. Doja
Semantic Model for Web-Based Big Data Using Ontology and Fuzzy Rule Mining

A huge amount of data is being generated everyday through different transactions in industries, medicals, social networking, communication systems etc. This data is mainly of unstructured format in nature. Transformation of the large heterogeneous datasets into useful information is very much required for society. This huge unstructured information should be easily presented and made available in a significant and effective way to obtain semantic knowledge so that machine can interpret them. In this paper, we have introduced a novel approach for semantic analysis with web based big data using rule based ontology mapping. To handle social data with natural language terms, we have proposed the fuzzy rule based resource representation. After that, a refined semantic relation reasoning mining is applied to obtain overall knowledge representation. Finally semantic equivalent of these unstructured data is stored in structured database using Web Ontology Language (OWL) based ontology system.

Sufal Das, Hemanta Kumar Kalita
Face Verification Across Ages Using Discriminative Methods and See 5.0 Classifier

Identifying a person through face biometric and analysis of Facial image has been drawing interest of researchers in the field of Machine learning and Pattern recognition. Face Recognition Across Ages (FRA) is a challenging task due to aging effects like changes in facial shape and texture. In this paper, an attempt is made to describe a schematic using two different discriminative approaches for feature extraction and a see5.0 classifier for classification purposes. One of the feature finding approaches is based on Gradient Orientation Pyramids (GOP) that includes finding of gradient orientations in Gaussian pyramids, the later one is based on Local Binary Patterns (LBP) calculated at each stage of Gaussian pyramid decomposition. These we have used FG-NET database and accuracies of both the approaches are compared.

K. Kishore Kumar, P. Trinatha Rao
Autonomous Robot Navigation Using Fuzzy Logic

The paper starts with explaining in brief about fuzzy logic and then goes on to explain a Fuzzy Logic Controller (FLC). It is the basic unit or a block of any application of fuzzy logic. We mainly focus on how to design a Fuzzy Logic Controller (FLC), its main functions and all the parameters or different factors involved. We then move on to our main objective i.e. implementing fuzzy logic in robots for making it autonomous in terms of navigation. After understanding basics of FLC, we focus on steering and obstacle avoidance of robot by assuming certain conditions regarding the environment, in other words putting restrictions on the behaviors that the robot can display. Some of these restrictions are then lifted and improvements are made to our previous model. We then focus on controlling the speed of the robot as well, considering the environment complexity. So the main objective of this paper is to get clear understanding on how to make a robot navigate autonomously using fuzzy logic controller. The paper then concentrates on why fuzzy logic will be a good approach to do so giving some examples.

Sagar Nandu, Nikhil Nagori, Alpa Reshamwala
Improved Non-Linear Polynomial Filters for Contrast Enhancement of Breast Tumors

Non-Linear Polynomial Filters (NPF) consists of a framework of weighted coefficients of low-pass and high pass filters. This paper explores the applicability of NPF for the contrast enhancement of breast tumors in mammograms. NPF algorithm in the present work has been improved to provide controlled background suppression during the mammogram enhancement. This is because, in the process to control overshoots and visualization of tumor margins; the uncontrolled background suppression may lead to loss of finer details in the vicinity of the lesion region. Simulation results have shown that the response of the proposed NPF has been reasonably good on mammograms containing tumors embedded in different types of background tissues.

Vikrant Bhateja, Mukul Misra, Shabana Urooj, Aimé Lay-Ekuakille
Sparse Representation Based Face Recognition Under Varying Illumination Conditions

In this paper we have developed novel technique to recognize faces across Illumination. Illumination is a condition where an image of same individual looks different due to varying lighting conditions. Recognizing faces across Illumination is proposed using Sparse Representation technique and tested using Extended Yale B database which consist of images across varying lighting conditions. Here we have considered images of 16 individuals at different lighting conditions. From our analysis we have found that proposed system to recognize faces across various lighting conditions using Sparse Representation Technique gives the best recognition rate of 95 % on Extended Yale B database.

Steven Lawrence Fernandes, G. Josemin Bala

Content Based and Applications

Frontmatter
Interference Minimization Protocol in Heterogeneous Wireless Sensor Networks for Military Applications

Wireless sensor Network (WSN) is an emerging technology has significant applications in several important fields like military, agriculture, healthcare, environmental, artificial intelligence and research. All these applications demands high quality data transmission from resource constraint WSNs. But interference is one of the severe problem in WSN which can degrade the quality data transmission. Various interference minimization techniques have been proposed but not results the expected degree of quality enhancement in WSNs. This research paper investigates various types of heterogeneous wireless sensor networks (HTWSN) deployment techniques, interference and its effects, existing interference minimization techniques with limitations. We propose interference minimization (IM) protocol for heterogeneous wireless sensor networks. IM protocol can efficiently minimize the interference and enhance the quality data transmission in WSN.

Kakelli Anil Kumar, Addepalli V. N. Krishna, K. Shahu Chatrapati
An Empirical Study of a Cryptographic Scheme for Secure Communication in Mobile Ad Hoc Networks

The design and implementation of a cryptographic scheme in a mobile ad hoc network (MANET) is highly complicated than the traditional networks. This is due to several reasons, like—unavailable central infrastructure services, periodic movable nodes, wireless link unsteadiness, and possible network separations. In this paper, we present a cryptographic key management scheme for secure communications in ad hoc networks. The scheme transmits the data in the presence of security attacks. The scheme provides the scalability of nodes and storage space wherein the nodes makes use of more than one key pair to encrypt and decrypt the messages. The scheme has been executed in Java programming language and empirically valued its efficiency via performance and security assessments. The simulation outcome has shown that the proposed scheme opposes against selfish nodes and takes less key storage space than traditional schemes. The scheme also satisfies the secure communication requirements.

Kuncha Sahadevaiah, Nagendla Ramakrishnaiah, P. V. G. D. Prasad Reddy
Evolving an Algorithm to Generate Sparse Inverted Index Using Hadoop and Pig

Now a day’s users mostly prefer the keyword search method to access the data for the explosion of information. Inverted indexing efficiently plays a very important role for search operation over a large set of data. There are two problems exist in current keyword based searching technique. First, the large set of data is mostly unstructured and does not suite in the existing database systems. Second, the storage in inverted indexing is usually very large and compression techniques used so far is also not so efficient because they increase the processing time. To overcome these problems, Hadoop, which is a distributed framework for large dataset is needed where the required resources could be shared and accessed very easily. In our proposed work, we will join the list of consecutive document id in the inverted index into the intervals to save memory space. For this, we have developed the UDF (User Defined Function) for stemming and stop words for the sparse inverted index in pig latin. It can be observed in the results that our proposed method is efficient than existing techniques.

Sonam Sharma, Shailendra Singh
Leakage Power Reduction Technique by Using FinFET Technology in ULSI Circuit Design

Deep Sub Micron (DSM) technology demands for lower supply voltage, reduced threshold voltage and high transistor density which leads to exponentially increase in leakage power when circuit is in standby mode. Here review of FinFET transistor along with existing low power techniques in DSM circuits like sleep, LECTOR etc. are done. Then Lector with FinFET technology circuit is proposed. This work evaluates the impact of FinFET technology, which has huge potential to replace bulk CMOS in DSM range. Performance of proposed technique is investigated in terms of dynamic power, delay, Power Delay Product (PDP) and leakage power dissipation. The proposed techniques has leakage controlling sleep transistor inserted over pull up and pull down network which significantly reducing the leakage power by using HSPICE simulator in 32 nm FinFET technology at 25 and 110 °C with CL = 1 pF at 100 MHz frequency.

Ajay Kumar Dadoria, Kavita Khare, T. K. Gupta, R. P. Singh
Handwriting Recognition of Brahmi Script (an Artefact): Base of PALI Language

Handwriting recognition and OCR are two major fields of recognition and classification, one is area and other is dawn. Archaeology is that field of study where recognition and classification is needed at most to recognize ancient artefacts written in languages like Pali having various scripts such as Khmer, Sinhala, Devanagari and more. Handwritten character recognition with MOCR (Modified OCR) is shown for Pali language in this paper portraying modified OCR to recognize Brahmi script and showing comparisons in terms of accuracy with two other scripts that are Akkhara-Muni and Ariyaka. Brahmi giving an overall success rate of 85.66, 85.73 and 88.83 % respectively. MOCR has new steps in various phases which results in better accuracy than OCR.

Neha Gautam, R. S. Sharma, Garima Hazrati
Theoretical and Empirical Analysis of Usage of MapReduce and Apache Tez in Big Data

Big data means large amount of data requires new technologies for its faster processing. It is ineffective to process the large amount of data with traditional devices. Big data provides an extra advantage in business and better service delivery. Big data brings a new change in decision making process of various business organizations. Big data has many challenges related to the 5Vs-Volume, Velocity, Variety, Veracity and Value. Hadoop is a Big Data tool used to process larger amounts of Data. It has many subcomponents work together to achieve the goal of faster processing. Apache Hive and Apache Pig are tools used to access data in different ways in Hadoop Ecosystem. Apache Hive depends upon SQL like queries while Apache Pig uses scripts. These two tools uses MapReduce or Apache Tez framework to access data. In this paper we analyze how these two frameworks uses Hadoop Distributed File System (HDFS) by comparing them in both theoretical and empirical way.

Rupinder Singh, Puneet Jai Kaur
Strip Tree Based Offline Tamil Handwritten Character Recognition

In this paper, hierarchically represented Strip tree based feature extraction has been employed for offline Tamil handwritten recognition. Tamil handwritten character recognition is a challenging factor which gain more attention in the field of pattern recognition. Since Tamil language is rich in complex structures such as curves and loops, this work proposed a novel Strip tree to represent the curvy structure. So that more number of challenges could be addressed. A Strip tree representation resembles a hierarchical structure is used here to represent a single curve taken from pre-extracted features. This structure is represented in a tree form (hierarchical) to describe the features. Main novelty behind this paper is that all the curvy portions of character are addressed by the strip tree representation, where the height (level) of the tree gets increased when the curvy structure is complex. Later, vectors derived from the tree structure (Strip tree) are analyzed through a decision tree to predict the Tamil character. The final analysis shows that Strip tree yields high success rate in recognition. Since it able to address more number of shape variations.

M. Antony Robert Raj, S. Abirami
ICT Enabled Homes for Senior Citizens

The senior citizens are the group which often faces difficulties in the later phases of lifespan. The statistics states that about 95 million people in India are above the age of 60. By the year 2025 there would be almost 80 million more old age mass. The changing family values, economic compulsions of their children, abuse and neglect have caused the elders to come through the net of family concern. So there has been a hike in the old age home in India. This research primarily focused the senior citizens using modern technologies which can help them actively participate in the modern world without any problem. The primary objective of the paper is to know the issues of usage of ICT enabled appliances for senior citizens and widely distributing the computer literacy in this group. The paper focuses on the ICT equipped home for old ages which can bring new excitement of living in senior citizens.

Archana Singh, Jaya Bajpai, Sweta
Different Visualization Issues with Big Data

We are midst of digital inclusion era, where different technologies around us, providing a wide platform of engagement with meaningful data visualizations. That engagement demands rational sense from end-users’ to handle data in more sensitive manner. Large datasets for research need effective tools for data capture, curate them for designing appropriate algorithms and multidimensional analysis for effective visualizations. Effective use of ICT will help us a lot to curve with societal problems in multidimensional way. While exploring different activities around an event, selecting trusted sources using different visualization cum analysis tools are a handy option for journalists, government and common people. The complexity and volume of the data produced by an event remains largely untapped. Exploratory Data Analysis (EDA) with proper visualization techniques helped us a lot to demonstrate our ability to build an environment for heterogeneous large volume datasets. Different disciplines and data generation rates of different lab experiments, online as well as offline make the issue of creating effective visualization tools a formidable problem. Our main aim is to analyze and summarize large datasets in a concise manner with or without help of any statistical tools and produce the results using different visualization techniques In this paper we will discuss about different data intensive visualization tools, trends of different emerging technologies, how big data processing heavily relying on those effective tools and how it helps in efficient decision making for the society.

Koushik Mondal
Comparison and Analysis of Obstacle Avoiding Path Planning of Mobile Robot by Using Ant Colony Optimization and Teaching Learning Based Optimization Techniques

Now a day, one of the prime concerns of mobile robot is path planning, in the area of industrial robotics. A path planning optimization method was proposed to calculate shortest collision free path from source to destination by avoiding static as well as dynamic obstacles. Therefore, it is necessary to select appropriate optimization technique for optimization of paths. Such problems can be solved by metaheuristic methods. This research paper demonstrates the comparison and analysis of two Soft Computing Techniques i.e. Ant Colony Optimization (ACO) and Teaching Learning Based Optimization (TLBO) by simulating respective algorithms for finding shortest path of a Mobile Robot by Obstacle avoidance & Path re-planning and Path Tracking. Both of these techniques seem to be a promising technique with relatively competitive performances. The ACO has been more widely used in that and it gives good solution with smaller numbers of predetermined parameters in comparison with other algorithms.

A. Q. Ansari, Ibraheem, Sapna Katiyar
An Era of Big Data on Cloud Computing Services as Utility: 360° of Review, Challenges and Unsolved Exploration Problems

Cloud computing is an innovation technology for supply of computing as a utility towards digital world. It is provide platform and services for the massive-scale data storage and data sharing. Big Data on cloud environment analyze, storage, manage, visualization, security are some challenging techniques that requires more timing and large computation infrastructure processing. This paper mainly brush up for an era of 360° vision of massive data on cloud services computing. The meaning, taxonomy and literature reviews for some papers of cloud along with some big data model are introduced. The association and role of deluge computing and cloudy data, big data open sources tools are also discussed. Last but not least, research challenges and unsolved exploration problems are shortened.

Rahul Vora, Kunjal Garala, Priyanka Raval
Performance Evaluation of Energy Detection Based Cooperative Spectrum Sensing in Cognitive Radio Network

Cognitive Radio is a promising solution to spectrum underutilization problem, highlighting the concept of Dynamic Spectrum Access with two primary functions of efficient radio spectrum usage and providing reliable communication whenever and wherever needed. In a Cognitive Radio Network, secondary users are allowed to use the vacant licensed spectrum. Hence secondary users need to sense the spectrum to check availability of vacant spectrum and vacate as soon as primary user arrives back. Thus, spectrum sensing plays a significant role in Cognitive Radio Networks. Cooperative spectrum sensing is of great importance as it combats shadowing multipath fading and receiver uncertainty problems. There are two important parameters in spectrum sensing: probability of detection and probability of false-alarm. Higher detection probability signifies better primary user protection. In this paper, performance has been evaluated and depicted for Energy detection based cooperative spectrum sensing through MATLAB simulations.

Reena Rathee Jaglan, Rashid Mustafa, Sandeep Sarowa, Sunil Agrawal
Design of Robotic Hand-Glove for Assisting Mobility Impaired

This project explains the design of a robotic glove system specific to the applications of mobility impaired. It is mounted on a moving base which will help the user in accessing objects that are not within arm’s reach. A robotic arm will replicate the movements of wrist, elbow and shoulder joint of a person in response to movements produced by a wireless glove to perform the picking, gripping and moving actions. For gripping action a clamp based mechanism is used. Flex sensors produce the signals proportional to the amount and direction of movement of the user’s hand to actuate the clamp through high torque dc servo motors. For arm movement a potentiometer is used. The control circuit using arduino regulates the amount and direction of arm movement through feedback from the actuator.

Ramalatha Marimuthu, Sathyavathi Ramkumar, Harshini Infanta, Alagu Meenal, Preethi
An Approach for Mining Similar Temporal Association Patterns in Single Database Scan

Mining similar temporal association patterns from a time stamped temporal database is an important research problem in temporal data mining. The main objective and idea of this research is in finding similar temporal patterns from a given time stamped temporal database of transactions by scanning the input database only once. This objective to find temporally similar patterns through single scan of database coins out an important challenge to devise a single database scan procedure which shall use only support values of items computed in the first database scan, so as to discover all other temporal patterns. In the current research, we come out with a novel procedure to discover similar temporal patterns with respect to a reference sequence of support values for a given threshold limit. In this paper, we propose a novel approach to find similar temporal patterns followed by a case study. The approach is efficient in terms of space and time as it eliminates repeated scan of database by computing temporal frequent patterns or temporally similar patterns in only a single database scan.

Vangipuram Radhakrishna, P. V. Kumar, V. Janaki
Metadaten
Titel
Proceedings of First International Conference on Information and Communication Technology for Intelligent Systems: Volume 2
herausgegeben von
Suresh Chandra Satapathy
Swagatam Das
Copyright-Jahr
2016
Electronic ISBN
978-3-319-30927-9
Print ISBN
978-3-319-30926-2
DOI
https://doi.org/10.1007/978-3-319-30927-9