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International Conference on Innovative Trends in Computer Science and Applications
ICITCSA 2017
📅 Date: 6th January 2017
🏫 Organized by: Pioneer College of Arts and Science, Coimbatore
📚 Department: Department of CSE
A Survey on Automated Classification Techniques in Data Mining for Brain Tumor Analysis
T. Vishnusaranya, A. Sathish
Bayesian Network Based Classification of Optical Coherence Tomography Images for Diagnosis of Glaucoma using Discrete Wavelet Transform Compression
Dr.V. Kathiresan, S. Nithya
Implementation of Rail Fence & Position Analyze Technique for More Secure Data
N. Sivakumar, V. Navamani, V. Yuvaraj
Online Optical Character Recognition (OCR) Tools – Performance Analysis
Dr. S. Vijayarani, Ms. A. Sakila
Object Oriented Approach for Analysis of Software Fault Prediction using K-Jensen Shannon Entropy Model based Clustering Algorithm
M. Praneesh, K. Mahalakshmi
A Review on Classification of Eye Movement using Electrooculography
Dr. S. Ramkumar, Mr. Barathkesavan, Mr. Hariharasubramanian
Android Application for Student – Faculty Interaction
Dr. K. Sumathi, V. Pitchai Kani, M. Rajapriya
Efficient File Search in Delay Tolerant Networks with Social Content and Contact Awareness
N. Sowmiya, S.Sampath
Mathematical Approach for Fourier-Finite Mellin Transform using Adjoint Operators for Secure Medical Image Steganography based on QR-Codes
Dr. D. Napoleon, M. Praneesh
Recent Routing Protocols in Mobile AdHoc Network (MANET)
Mr. C. Rangarajan, Mrs. S. Sridevikarumari, Ms. V. Sujitha
A New QPSO Based Network Intrusion Detection System using Feature Selection
V. Attchara, K. Sujitha, S. Sayina
A Comparative Study of Genetic Algorithm with the KNN Evolutionary Optimization Algorithm in Data Mining
Dr. M. Subha
The Private Key Capacity of a Cooperative Pairwise-Independent Network (PIN)
S.Gopalakrishnan, D.Suganya, S.Vennila
Quality Assurance for Business Needs using Software Testing Concepts
R. Jaya Kumar, A. Senthil Kumar
Heterogeneous Cloud Radio Access Networks Based on New Perspective for Enhancing Spectral and Energy Efficiencies
S. Roja, M. Indira
Information Technology Drives Innovation: A Path to Success in Business and in Higher Education
Dr. Indhu Gopal
An Effective Fuzzy Set Theory with Neural Networks for using Feature Selection and Classification
Dr. N. Balakumar, A. Vaishnavi
A Survey of Characteristics and Emerging Technologies in Big Data
Dr. S. Krishnaveni, R. Divya, V. Attchara
A Survey of Characteristics and Emerging Technologies in Big Data
R. Anusuya, B. Prabadevi, R. Divya
A Comparative Study on Healthcare System using Data Mining Prediction Techniques
R. Kalaivani, S. Subhasini
Logistic Regression: A Novel Approach to Implement in Business Intelligence
D. Kalaivani, Dr. T. Arunkumar
A Knowledge Based Post Mining Techniques in Large Databases through Interactive Post Processing of Association Rules using Ontologies
A. Vaishnavi, M. Hemalatha
Performance Tuning with Different Kernel Function Hyperplane Analysis for Optimal Recognition Rate
P. Rukmanidevi, V. Kalaivani
Effective Global Sensor Deployment for Coverage Problem in WSN using Ant Colony Optimization
T.B. Saranya Preetha, V. Sowmiya, K. Yamuna devi
Estimation of Claim Severity in Non-Life Insurance: A Non-Parametric Approach
K.M. Sakthivel, C.S. Rajitha
Horizontal Aggregation Function Using Multi Class Clustering (MCC) and Weighted (PCA)
Dr. K. Sathesh Kumar, P. Sabiya, S.Deepika
Secured Transcode Enabled Layer 7 Proxy Handoff in Mobile Networks
Anantha Prabha.P, Immaculate Jennifer J, Haripreethi G, Harshini P, Gokulraj S, Gowtham R
Mean Weighted Artificial Bee Colony (MWABC) based Feature Selection for Gene Co-Expression using Microarray Data
M. Sofia, Dr. N. Tajunisha
A State of Art Review on Current Researches in Moblie Adhoc Networks
G. Deepalakshmi, R. Saradha, G. Santhiya
A Review on Security Issues in Wireless Sensor Networks using Bio-inspired Computing
R. Kanagaraj, P.S. Shinu, K. Pavithra
A Review on Wireless Sensor Network Routing Algorithm using Bio-inspired Computing
D. Antony Arul Raj, V. Keerthana, R. Roshini
Abstract
A Survey on Automated Classification Techniques in Data Mining for Brain Tumor Analysis
T. Vishnusaranya, A. Sathish
Abstract:
Data mining is popularly research area known for knowledge discovery .In this paper we highlights the classification techniques in data mining for the detection of brain tumor. This survey results tends to automated techniques in classification applied in brain tumor analysis. In segmentation of MRI, identification is complicated process in medical field. A Comparative study is applied here to show the difference between various proposed techniques in the identification of brain tumor.
Keywords:
Brain tumor, MRI, TANNN, segmentation.
Abstract
Bayesian Network Based Classification of Optical Coherence Tomography Images for Diagnosis of Glaucoma using Discrete Wavelet Transform Compression
Dr.V. Kathiresan, S. Nithya
Abstract:
In worldwide, Glaucoma is a second major retinal disease which results permanent blindness. Loss of Retinal Nerve Fiber Layer (RNFL) is the result of glaucoma disease. RNFL thickness is evaluated from Optical Coherence Tomography (OCT) images is an important diagnostics indicator for glaucoma disease. At the same time in medical field they were maintaining large volume of medical image data with low quality of image contrast, speckle noise, exact compression of OCT is difficult. To solve above issues, Discrete Wavelet Transform (DWT) based OCT and image compression is proposed in this work. In this work speckle noise are removed by using radar improved frost filter, secondly the RNFL features are extracted by using Improved Linear Discriminant Analysis. Then the OCT image is segmented by using K-mean clustering algorithm. Hence the severity of Glaucoma is classified by using Bayesian network. Finally Discrete Wavelet Transform (DWT) is used to compress the image without any significant loss in the diagonsability of the real image. Experimental result shows that the proposed Bayesian network is efficient for detecting the severity of the Glaucoma.
Keywords:
Optical Coherence Tomography, RNFL, Radar improved frost filter, Discrete Wavelet Transform, K-mean clustering algorithm, Bayesian Network.
Abstract
Implementation of Rail Fence & Position Analyze Technique for More Secure Data
N. Sivakumar, V. Navamani, V. Yuvaraj
Abstract:
In this faster world peoples shares important information through network and wants strong security while sharing data. So to provide such a strongest security to our data the most popular method is used which is known as cryptography. Cryptography is the art and science of achieving security by encoding messages to make them non-readable. In this paper, we combine the rain fence technique and positions analyze technique to achieve more secure data than the normal transposition technique. To increase security we use such type of techniques.
Keywords:
cryptography, transposition technique, rail fence technique, position analyze technique, cipher text, plain text.
Abstract
An Overview: Basic Concept of Network Simulation Tools
Mrs. C. Gayathri, Dr. R. Vadivel
Abstract:
This context represents with network simulation with tools. The network simulation tools are a modern technology. The simulator helps the user to develop the networks with real time. It is useful to test new networking protocols or changes in the existing protocols. The network simulator have different type of tools such as OPNET, QualNet, NS2, Ns3, OMNET++,NetSim, REAL, J-sim, GloMosim.In this article represent with type of network simulator, advantages and disadvantages , and basic architecture of network simulator tools. It is easy to understand for the users.
Keywords:
Opnet, Qualnet, Ns2, Ns3, Omnet++, Netsim, J-sim, Glomosim.
Abstract
Online Optical Character Recognition (OCR) Tools – Performance Analysis
Dr. S. Vijayarani, Ms. A. Sakila
Abstract:
Optical Character Recognition (OCR) is a technique, which is used to convert the document images into editable text format. Many different types of OCR tools are freely and commercially available today. The primary objective of this work is to compare the performance of the open source OCR tools for extracting the text information from the image (Table format). The main functions of these tools are to convert the images into text format. Eight different types OCR tools are considered for this analysis. From this analysis is observed that the performances of OCR Convert and My Free OCRtools are better than other OCR tools.
Keywords:
Optical Character Recognition, Online OCR, Free Online OCR, OCR Convert, My free OCR, Free OCR, i2OCR, To-text.net, Google Docs.
Abstract
Object Oriented Approach for Analysis of Software Fault Prediction using K-Jensen Shannon Entropy Model based Clustering Algorithm
M. Praneesh, K. Mahalakshmi
Abstract:
In software engineering, the most frequent problem highlighted by IT Practioners concerned the measurement of quality. In order to improve the quality of the software, fault prediction is the necessary task. This prediction reduces the time complexity between modules. In the recent years lot of software metrics are used for predicting whether the particular models of the software faulty are fault free. In this paper we have proposed K-Jensen Shannon Entropy Model based Clustering Algorithm for predicting the faults in software projects. In our experiment, we used CM1, PC1, KC1, KC2 and PC4 collected from NASA MDP. Finally, our proposed system is compared with Euclidean distance based K-Means Clustering Algorithm.
Keywords:
software fault prediction, clustering, Quality and Metrics.
Abstract
A Study on Ransomware Cryptowall
V. Archana, S. Vinothini
Abstract:
Ransomware is a malware for data kidnapping, an exploit in which the defender encrypts the target's data and loads expense for the decryption key. Ransomware blowouts through e-mail attachments, infected programs and compromised websites. A ransomware malware database may also be named ascryptovirus, cryptotrojan or cryptoworm.
Keywords:
Ransomware, Crypto Locker, Decryptor, Cryptowall.
Abstract
A Review on Classification of Eye Movement using Electrooculography
Dr. S. Ramkumar, Mr. Barathkesavan, Mr. Hariharasubramanian
Abstract:
In the recent trend most of the researchers are payed their attention towards to improving the human computer interaction through EOG. EOG technique using eye movements are playing important role in diagnostic, medical and industrial fields. EOG is based on eye blinks and movements. Eye blinks are typically classi?ed into three categories one is a spontaneous eye blink which occurs frequently, another is a re?exive eye blink which is evoked by an external stimulus, and the other is a voluntary eye blink which is caused by intentional eye closing. EOG is a biosignal technique for measuring the resting potential of the membrane. The ensuing signal is named the Electrooculogram. Eye movements are used to detect were the people look. The main purpose of the EOG is to assist disabled persons. This paper gives an outlook on various works done by the researchers in the field of eye blink, detection, Eye tracking and other eye movements and different classifiers which attempts to classify the eye movement using Electrooculography. Finally it gives a light on various issues related to Electrooculography and its classification techniques.
Keywords:
Electrooculography (EOG), eye tracking, eye blinks, Human Computer Interaction (HCI).
Abstract
Android Application for Student – Faculty Interaction
Dr. K. Sumathi, V. Pitchai Kani, M. Rajapriya
Abstract:
This work is aimed at developing an Android Application for student-faculty interaction, which is very important in any educational institution. This system will be useful for both students and faculty members for effective communication. Students and staff can access the system to share their knowledge. Faculty members can upload technical information like lecture notes, tutorial sheets and online course details through which students can improve their knowledge. Using this system student can be aware of Workshops, training programs and conference organized in the educational institution. Student can also use this system to search the current location of the faculty members, download lecture notes, and participate in the discussion forum. The main objective of the work is to provide an effective interaction system between students and faculty members.
Keywords:
MobileApp, student- faculty interaction.
Abstract
Mobile Application for Student Information System
Dr. K. Sumathi, M. Umarani, P. Abinaya
Abstract:
This work is aimed at developing an Android Application for student Information System which is very important in educational institution. This system will be useful for parents, students and faculty members for effective communication. Using this system parents will be able to access their wards details such as academic performance, attendance details, co curricular and extracurricular information. This system helps the students to view the details such as Workshops, training programs and conference organized in the educational institution, attendance and academic details. Student can also use this system to download lecture notes which will be posted by faculty members. The main objective of the work is to provide an effective interaction system among parents, academic institutions and faculty members. Faculty members can upload technical information like lecture notes, tutorial sheets and online course details through which students can improve their knowledge.
Keywords:
MobileApp, student information system, parent-academic institution interaction.
Abstract
Intelligent Tutoring System for Teaching Java
R. Sivarasan, Dr. G.P. Ramesh Kumar
Abstract:
An Intelligent Tutoring System is based on cognitive learning theory which is a learning theory interested in how information organizes in human�s memory. ITS are intelligent programs which know what, how and whom they will teach so computer play an important part in education and instruction aims are performed and suggested in this work. In this paper described of ITSs in educational application and demonstrate used modules in ITSs. In Intelligent Tutoring System, using Pre-quiz evaluation the knowledge level of the student is measured by asking objective type question to the student. And the system automatically allots and registers the details of the student according to their performance level. According to the level of the student allotted by the system, the study material is provided. In this system the student level is categorized into three sections, beginner level, average level and excellent level. In this system, tutor is registered by the administrator; this system has monitored all the apparition has based on student Id, who help in managing quiz creation for evaluation purpose and study material creation according to each level of student. And Student can also ask any queries or doubts to the tutor for any clarification. To clarify important terms in a concept, this system automates the key terms will search expand and definition by matching with the database, whenever the students move to the curser on the keyword. The server show immediately the keyword expands and also illustration. In advance this system provides solution student immediately because the tutor also available on another side, which helps the student to have searched with the study material with any keyword terms. The quiz evaluation each phase of section is made, which helps the student to know their l evel if they perform well they are upgraded. Reports are also managed by this system.
Keywords:
Intelligent Tutoring System, Student, Java, learning.
Abstract
Efficient File Search in Delay Tolerant Networks with Social Content and Contact Awareness
N. Sowmiya, S.Sampath
Abstract:
In this paper analysis a DTNs backup network for infrastructure intensive areas or a low-cost communication structure in severe environments. This paper focus on distributed peer-to-peer file search in a delay tolerant network (DTN) formed by mobile devices, the holders of which exhibit certain social network properties. However, due to sparse node distribution and continuous node mobility, DTNs are featured by frequent network partition and intermittent connections. DTN Packet forwarding is often realized in a store-carry-forward manner in DTN routing algorithms, which means that a message is carried by current holder until meeting another forwarder. Furthermore, due to the distributed network structure, it is almost impossible to maintain global file distribution information in DTNs. In this existing we design three components in Contact and Content model: community creation, neighbor table construction and update and content and contact based file search. Common-interest communities benefit file searching from two aspects: (1) it increases the probability that a node finds its interested files in its own community since common-interest nodes tend to meet more frequently and (2) it can enable a request to learn the destination community directly. The neighbor table provides organized information regarding how to find the requested file efficiently and the propose system implement a advanced techniques that can further enhance file searching efficiency, thought at additional costs.
Keywords:
DTN, store-carry forward, packet forwarding.
Abstract
Mathematical Approach for Fourier-Finite Mellin Transform using Adjoint Operators for Secure Medical Image Steganography based on QR-Codes
Dr. D. Napoleon, M. Praneesh
Abstract:
In the current scenario, medical records are most sensitive information and require an uncompromising security during both storage and transmission. In most of the hospitals these information are stored separately and referred to the consultant separately. Due to this separate storage and transmission there is a possibility of unauthorized access of data which already exists. In order to protect these data, we proposed a new steganography technique based on Fourier- Finite Mellin Transform using Adjoint Operators.
Keywords:
Transmission, Steganography, Fourier- Finite Mellin Transform, Adjoint Operators.
Abstract
Recent Routing Protocols in Mobile AdHoc Network (MANET)
Mr. C. Rangarajan, Mrs. S. Sridevikarumari, Ms. V. Sujitha
Abstract:
Mobile Ad Hoc Networks (MANETs) are kind of wireless network with self-administrating characteristics, where the nodes get associated in a spontaneous or ad hoc basis. MANET is not an infrastructure based network and there exist no centralized resources. Framing a route between source and destination is a challenging task in MANET. Several protocols have been proposed to overcome this problem. This paper surveys the recent protocols which are proposed to overcome the routing issue.
Keywords:
Routing, Protocol, MANET, Proactive, Reactive, Hybrid.
Abstract
A Detail Study on Big Data Analytics
Mrs. R. Anusuya, Ms. R Vinothini
Abstract:
Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate to deal with them. Challenges include analysis, capture, sharing, storage, transfer, visualization, querying, updating and information privacy. The term �big data� often refers simply to the use of predictive analytics, user behaviour analytics, or certain other advanced data analytics methods that extract value from data, user behaviour analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. The paper focus on the analytic methods used for big data. Big data analytics is the process of collecting, organizing and analysing large sets of data to discover patterns and others useful information. Big data analytics can help organizations to better understand the information contained within the data and will also help identifying the data that is most important to the business and future business decisions. This paper highlights the need to develop appropriate methods to unstructured text, audio, and video formats.
Keywords:
Big data, Big data analytics, Big data definitions, Unstructured data analytics, Predictive analytics.
Abstract
Li-Fi Technology in Wireless Communication
Mr. C. Rangarajan, Ms. D. Devi
Abstract:
Li-Fi is abbreviated as Light Fidelity refers to 5G Visible Light Communication systems using light-emitting diodes as a medium to high-speed communication in a parallel behavior as Wi-Fi. In the days where internet has become a major insist, people are in a search for Wi-Fi hotspots. Li-Fi or New Life of data communication is a improved a new Wi-Fi in wireless communication. This paper proposes a study on Li-Fi Technology. The Li-fi technology was made-up by Professor Harald Hass of University of Edinburgh. Li-Fi has more facility in terms of bandwidth invisible region therefore it does not poke its nose in other communications which uses radio occurrence range, without taking its frequency bands. Li-Fi has thousand times greater speed than Wi-Fi and provides security as the visible light is unable to enter through the walls, which offer a new era of wireless communication. The concept of Li-Fi is data communication on fast sparkling of light which is not detected by human eye but it is focused on photo detector which converts the on-off state into binary digital data. It has gained a huge status in two years of its innovation. Such technology has brought not only greener but safer and cheaper future of communication.
Keywords:
LED (Light Emitting Diode),Wi-Fi (Wireless Fidelity),Li-Fi (Light Fidelity),VLC (Visible Light Communication),RF (Radio Frequency).
Abstract
Study of Image Fusion on Satellite Images
Sudha.V, Priya .R
Abstract:
The image fusion is one of the emerging advanced technology in the field of research. It is mostly used for challenges of Face Recognition. Image fusion is the combination of two or more source images which vary in resolution or image capture technology into a single composite representation. The main objective of an image fusion algorithm is to integrate the redundant and complementary information obtained from the satellite images in order to form a new image which provides a better description of the scene for human or machine perception. In this paper, we used a method based on the curvelet transform which represents edges better than wavelets. Since edges play a important role in image understanding and also enhances spatial resolution to enhance the edges. Curvelet-based image fusion method provides wider information in the spatial and spectral domains simultaneously.
Keywords:
Principal Component Analysis , Eigen faces, empirical mean, peak signal to noise ratio (PSNR), Fusion, Multiresolution analysis, Wavelet transform, Curvelet transform
Abstract
A New QPSO Based Network Intrusion Detection System using Feature Selection
V. Attchara, K. Sujitha, S. Sayina
Abstract:
As the Internet services spread all over the world, many kinds and a large number of security threats are increasing. Therefore, intrusion detection systems, which can effectively detect intrusion accesses, have attracted attention. This paper proposes a novel approach for feature selection based on Genetic Quantum Particle Swarm Optimization (GQPSO) attribute reduction in network intrusion detection which aiming to problem of classification algorithm with low detection speed and low detection rate in high dimensional network data intrusion detection. In the approach, selection and variation of genetic algorithm with QPSO algorithm are combined to form GQPSO algorithm; normalized mutual information between attributes defined as GQPSO algorithm fitness function to guide it�s reduction of attributes to realize optimal selection of network data feature subset. KDD99 data-set are used to experiment. The experimental result shows that the approach is more effective than QPSO and PSO algorithms in discarding independent and redundancy attributes. As a result, intrusion detection rate and speed of classification algorithm are greatly heightened by using the method.
Keywords:
Genetic Quantum Particle Swarm Optimization(GOPSO); Normalized Mutual Information; Attribute reduction; Intrusion Detection; Feature Selection.
Abstract
Honeypot in Code Injection Attacks
V. Attchara, M. Nithya, R. Epsi
Abstract:
In this paper honey pot is used to detect the fraud when the online credit card purchasing. In computer terminology, a honeypot is a computer. Generally, a honeypot consists of data (for example we can use the network site) that appears to be a legitimate part of the site but is actually isolated and monitored. Also it seems to contain information or a resource of value to attackers, which are then blocked. It is similar to the police baiting of a criminal and then conducting undercover surveillance, and finally punishing the criminal, by this they could not escape from the police.[1] Nowadays there is lot of online credit card purchase are made, so we don�t know the person how is using the card online, we just capture the IP address for verification purpose. IP addresses will be unique. So there need a help from the cyber-crime to investigate the fraud. To avoid the entire above disadvantage we propose the system to detect the fraud in a best and easy way.The credit card fraud detection features uses user behavior and location scanning to check for unusual patterns, but using the honeypot we can protect it from the fraud. These patterns include user characteristics such as user spending patterns as well as usual user geographic locations to verify his identity. If any unusual pattern is detected, the system requires revivification. Lot of troubles will be reduced. The message will be send to the user when the fraud detecting time, after that by opening the user system we can define the message(some one hacking our web page) from the server. The system analyses user credit card data for various characteristics. These characteristics include user country, usual spending of the procedures. It is Based upon the before the data of that user the system recognizes unusual patterns in the payment procedure in this system by the securing format. So now the system may be require the user to login the area again or even block the user for more than 3 invalid attempts the message will be display.
Keywords:
IP address, geographic locations, computer terminology, honeypot.
Abstract
A Comparative Study on Data Mining Algorithm for Gene Cancer Analysis
M. Sofia, S. Diviya
Abstract:
DNA microarray data now permit scientists to screen thousand of genes simultaneously and determine whether those genes are active or silent in normal and cancerous tissues. With the advancement of microarray technology, new analytical methods must be developed to find out whether microarray data have discriminative signatures of gene expression over normal or cancerous tissues. Fuzzy C-Means is a method of clustering which allows one piece of data to belong to two or many clusters. This method is frequently used in pattern recognition. It is based on minimizing functions. Fuzzy Partitioning is carried out through an interactive optimization of the objective function, with the update of membership the cluster centers. Fuzzy c-means is one of them and it is used widely in such applications as a clustering algorithm. In this study, we applied a different clustering algorithm, an artificial immune system (AIS), for data reduction process. We realized the performance evaluation experiments on standard Chain link and Iris datasets, while the main application was conducted by using Wisconsin Breast Cancer dataset and Pima Indians dataset which were taken from the UCI Machine learning repository.
Keywords:
K-mean, Fuzzy C-Means, Microarray, Gene selection, Classification.
Abstract
Cloud Computing Security in IAAS
Dr. N. Balakumar, K. Zuvairiya, R. Kausalya
Abstract:
Cloud computing is current buzzword in the market. It is paradigm in which the resources can be leveraged on peruse basis thus reducing the cost and complexity of service providers. Cloud computing promises to cut operational and capital costs and most importantly let IT departments focus on strategic projects instead of keeping datacenters running. It is much more than simple Internet. It is a construct that allows user to access applications that actually reside at location other than user�s own computer or other Internet connected devices. There are numerous benefits of this construct. For instance other company hosts user application. This implies that they handle cost of servers, they manage software updates and depending on the contract user pays less i.e. for the service only. Confidentiality, Integrity, Availability, Authenticity, and Privacy are essential concerns for both Cloud providers and consumers as well. Infrastructure as a Service (IaaS) serves as the foundation layer for the other delivery models, and a lack of security in this layer will certainly affect the other delivery models.
Keywords:
Cloud Computing, IAAS, PAAS, SAAS.
Abstract
Mobile Phone Cloning
Dr. S. Kirshnaveni, M. Kanagapriya, K. Zuvairiya
Abstract:
Mobile communication has been readily available for several years, and is major business today. It provides a valuable service to its users who are willing to pay a considerable premium over a fixed line phone, to be able to walk and talk freely. Because of its usefulness and the money involved in the business, it is subject to fraud. Unfortunately, the advance of security standards has not kept pace with the dissemination of mobile communication. Some of the features of mobile communication make it an alluring target for criminals. It is a relatively new invention, so not all people are quite familiar with its possibilities, in good or in bad. Its newness also means intense competition among mobile phone service providers as they are attracting customers. The major threat to mobile phone is from cloning.
Keywords:
GSM, CDMA, ESN, MIN, PIN, IMEI, CTIA.
Abstract
Cloud OS and Security Protocols
Mr. S. Gopalakrishnan, Ms. V. Sujitha
Abstract:
In the current trends of computing, cloud computing plays a vital role and it is emerging at the level of maximum. The reason behind this is people started moving their data to cloud with the expectation of hundred percentage availability on their demand, i.e., anytime anywhere computing. Though the cloud services are provided by the third party, security becomes a very big question mark. The main objective of this paper is to provide an overview of cloud computing and its security, which help the young researchers to get clear idea.
Keywords:
Computing, Cloud, Grid, Public, Private, Hybrid, IaaS, PaaS, SaaS, Security.
Abstract
Security and Privacy in Big Data
T. Shanmuga Vadivu, D. Saranya, S. Karthika
Abstract:
Although the use of Social Networking web sites and applications is increasingly on the rise, many users are not properly informed of the risks associated with using these sites and application. Understanding these risks and challenges should be addressed to avoid potential loss of private and personal information. Current authentication systems suffer from many weaknesses. Many available graphical passwords have a password space that is less than or equal to the textual password space. . In this paper, we present and evaluate our contribution, i.e., the 3-D password. The 3-D password is a multifactor authentication scheme. This paper examines the issues of security, privacy, and trust in social networking sites from users' viewpoint.
Keywords:
3D password, Security, authentication, privacy, and trust in social networking sites.
Abstract
A Comparative Study of Genetic Algorithm with the KNN Evolutionary Optimization Algorithm in Data Mining
Dr. M. Subha
Abstract:
Evolutionary optimization algorithms have been proved to be good solutions for many practical applications. They were mainly inspired by natural evolutions. However, they are still faced to some problems such as trapping in local minimums. This paper proposes the comparative study of inspired algorithms like Stem Cells Algorithm (SCA), Ant Colony Optimization (ACO) algorithm with the K-nearest neighbor algorithm (KNN) to reduce the local minima by using benchmark functions in data mining.
Keywords:
Evolutionary inspired optimization algorithm, local minima, benchmark functions.
Abstract
Secure Image using Steganography
G. Saranya, N. Pravaeena
Abstract:
Information security is one of the most exigent problems in today�s technological world. In order to secure the transmission of secret data over the public network (INTERNET) various schemes have been presented to the last decennium. Stenography combined with cryptography, can be one of the best choices for solving this problem. This paper advance a new steganographic method based on the gray-level modification for true color images using image reciprocity, secret key and cryptography.
Keywords:
Steganography, grapters, Network, Encrypt, Decrypt.
Abstract
The Private Key Capacity of a Cooperative Pairwise-Independent Network (PIN)
S.Gopalakrishnan, D.Suganya, S.Vennila
Abstract:
This paper studies the private key generation of a cooperative pairwise-independent network (PIN) with M + 2 terminals (Alice, Bob and M relays), M = 2. In this PIN, the correlated sources observed by every pair of terminals are independent of those sources observed by any other pair of terminal. In the PIN, the pairwise source observed by every pair of terminals is independent of those sources observed by any other pairs. Secrecy is required from an eavesdropper that has access to the public inter-terminal communication. All the terminals can communicate with each other over a public channel which is also observed by Eve noiselessly. the PK needs to be protected not only from Eve but also from the two relays. The objective is to generate a private key between Alice and Bob under the help of the M relays; such a private key needs to be protected not only from Eve but also from individual relays simultaneously. The private key capacity of this PIN model is established, whose lower bound is obtained by proposing a novel random binning (RB) based key generation algorithm, and the upper bound is obtained based on the construction of M enhanced source models. PK generation algorithms are extended to a cooperative wireless network, where the correlated source observations are obtained from estimating wireless channels during a training phase. The two bounds are shown to be exactly the same. Then, we consider a cooperative wireless network and use the estimates of fading channels to generate private keys. It has been shown that the proposed RB-based algorithm can achieve a multiplexing gain M - 1, an improvement in comparison with the existing XOR- based algorithm whose achievable multiplexing gain is ?M?/2.
Keywords:
PIN model, Private key capacity, Multiplexing gain, co-operative PIN model, index security.
Abstract
Quality Assurance for Business Needs using Software Testing Concepts
R. Jaya Kumar, A. Senthil Kumar
Abstract:
Software testing is a process of verifying and validating that a software application or program 1. Meets the business and technical requirements that guided its design and development, and 2. Works as expected. Software testing also identifies important defects, flaws, or errors in the application code that must be fixed. During test planning we decide what an important defect is by reviewing the requirements and design documents. An important defect is one that from the customer�s perspective affects the usability or functionality of the application. Assuring quality is not a responsibility of the testing team. The testing team cannot improve quality; they can only measure it, although it can be argued that doing things like designing tests before coding begins will improve quality because the coders can then use that information while thinking about their designs and during coding and debugging.
Keywords:
Software, Quality.
Abstract
Heterogeneous Cloud Radio Access Networks Based on New Perspective for Enhancing Spectral and Energy Efficiencies
S. Roja, M. Indira
Abstract:
To mitigate the severe inter-tier interference and enhance limited cooperative gains resulting from the constrained and non-ideal transmissions between adjacent base stations in heterogeneous networks (HetNets), heterogeneous cloud radio access networks (H-CRANs) are proposed as cost-efficient potential solutions through incorporating the cloud computing into HetNets. In this article, state-of-the-art research achievements and challenges on H-CRANs are surveyed. In particular, we discuss issues of system architectures, spectral and energy efficiency performances, and promising key techniques. A great emphasis is given towards promising key techniques in H-CRANs to improve both spectral and energy efficiencies, including cloud computing based coordinated multi-point transmission and reception, large-scale cooperative multiple antenna, cloud computing based cooperative radio resource management, and cloud computing based self-organizing network in the cloud converging scenarios. The major challenges and open issues in terms of theoretical performance with stochastic geometry, fronthaul constrained resource allocation, and standard development that may block the promotion of H-CRANs are discussed as well.
Keywords:
Heterogeneous cloud radio access networks (H-RANs), heterogeneous networks (HetNets), cloud computing, mobile convergence.
Abstract
An Overview of Data Warehousing and OLAP Technology
B. Prabadevi, P. Aswini
Abstract:
Data warehousing and on-line analytical processing (OLAP) are decision support, which has increasingly become a focus of the database industry. Many marketable products and services are now available, and all of the principal database management system vendor now have offerings in these areas. Decision support places some rather different requirements on database technology compare to traditional on-line transaction processing applications. This paper provides an overview of data warehousing and OLAP technologies, with an emphasis on their new requirements. It can be back end tools for extracting, cleaning and loading data into a data warehouse; multidimensional data models typical of OLAP; front end client tools for querying and data analysis; server extensions for proficient query processing; and tools for metadata management and for managing the warehouse.
Keywords:
OLAP, Data warehousing, database management system, vendor.
Abstract
Getting IoT Ready: From Connected Things to Living in the Data
Jacob Thomas
Abstract:
The Internet of Things (IoT) is rapidly evolving. There is a need to understand challenges in obtaining horizontal and vertical application balance and the key fundamentals required to attain the expected 50 billion connected devices in 2020. The number of Internet-connected devices surpassed the number of human beings on the planet in 2011 and by 2020. Internet-connected devices are expected to number between 26 billion and 50 billion. For every Internet-connected PC or handset there will be 5-10 other types of devices sold with native Internet connectivity. These will include all manner of consumer electronics, machine tools, industrial equipment, cars, appliances, and a number of devices likely not yet invented. The concept of the IoT will disrupt consumer and industrial product markets generating hundreds of billions of dollars in annual revenues, serve as a meaningful growth driver for semiconductor, networking equipment, and service provider end markets globally, and will create new application and product end markets that could generate billions of dollars annually. This paper explores the history of the IoT, some early applications that are already disrupting existing markets, and some interesting applications that have the potential to go mainstream in the next several years. This paper also explain the value chain of companies that creates the IoT in various end markets and attempt to quantify its impact on specific semiconductor, software, device, and service provider end markets.
Keywords:
Internet of Things (IoT), RFIDs, Sensors, Machine-to-Machine (M2M) communications.
Abstract
Information Technology Drives Innovation: A Path to Success in Business and in Higher Education
Dr. Indhu Gopal
Abstract:
Information technology drives innovation and innovation is the path to business success. Innovation in business has the same impact that steam had on the industrial revolution. This article looks at two case studies: the changing face of medical care practice which has become more of a business to provide modern, convenient and efficient cardiac services through the implementation of an electronic clinical information system (ECIS), that integrates all aspects of the business, including financial and clinical applications, and uses electronic medical records (EMR) to collect and store patient data. The results include significant operational cost savings, raised revenue, expanded research abilities, and improved physician and patient satisfaction. Secondly, it looks at the business of higher education with students as its �customers�. Money is exchanged, debt is incurred, and a valuable asset in the form of a degree, certificate, or badge is obtained. Technology has shaped learning at a private university in a Southern state in the Unites States. In 2010 it became the first Think Pad university, and in 2014 the first IPad university. Learning Management System-CANVAS, an intuitive learning platform that provides both faculty and students to shape a different learning experience, with diverse features and tools in a single online environment was implemented. The academic technology responded to the way students now want and expect to learn, student-driven learning, interactivity & collaboration between faculty & students & assessment tools leading to customer satisfaction and student retention. Information technology fosters innovation in business and in higher education.
Keywords:
Business, ECIS, EMR, Higher Education, IT, LMS.
Abstract
An Effective Fuzzy Set Theory with Neural Networks for using Feature Selection and Classification
Dr. N. Balakumar, A. Vaishnavi
Abstract:
In fuzzy set theory, Fuzzy set theory defines set membership as a possibility distribution. The fuzzy set theory can be used in a wide range of domains in which information is incomplete or imprecise, such as bioinformatics. The uncertainty may arise due to partial information about the problem, or due to information which is not fully reliable, or due to inherent imprecision in the language with which the problem is obtained, or due to receipt of information from more than one source about the problem which is conflicting. Fuzzy set theory is an excellent mathematical tool to handle the uncertainty and vagueness inherent to human perception, speech, thinking and decision making. In this paper used to how to find the error and make the analysis will be made up with the help of neural networks
Keywords:
Fuzzy Rules, Fuzzy Classifier, nueral networks, artifial nueral networks.
Abstract
A Survey of Characteristics and Emerging Technologies in Big Data
Dr. S. Krishnaveni, R. Divya, V. Attchara
Abstract:
Big data make values for business and research, but create significant quarrel in terms of networking, storage, management, analytics and ethics of data. The 3Vs have been extended to other corresponding characteristics of big data: Volume: big data doesn�t sample; it just views and follows what happens. Velocity: big data is frequently available in real-time. Variety: big data depicts from multimedia like Audio, Video, Text and Animation; plus it entries missing pieces through data mixture. Engineers, computer scientists, statisticians and social scientists are needed to tackle, discover and understand big data for Multidisciplinary collaborations. This survey presents an overview of big data initiatives, technologies and Characteristics of Big Data.
Keywords:
Three V�s of Big Data, Emerging Technologies.
Abstract
A Survey of Characteristics and Emerging Technologies in Big Data
R. Anusuya, B. Prabadevi, R. Divya
Abstract:
Big Data is a turn of phrase used to mean a massive volume of both ordered and unordered data that is so huge it is complicated to process using traditional database and software techniques. This gives grow to the time of Bigdata. The term Big Data comes with the new dispute to input, process and output the data. The paper centre of attention on restraints of traditional approach to manage the data and works that are useful in treatment big data. One of the approaches used in processing big data is HADOOP framework the paper presents the major components of the framework and working process within the framework.
Keywords:
Big Data, Hadoop Framework. Components of Hadoop, Working of Hadoop.
Abstract
Big Data: Why? What? How?
K. Soniya
Abstract:
Due to recent technological development, the amount of data generated by internet, social networking sites, sensor networks, healthcare applications, and many others are drastically increasing day by day. All the enormous measures of data produced from various sources in multiple formats with very high speed are referred as big data. In today�s digital world, where lots of information is stored, the analysis of the databases can provide the opportunities that lead to better decisions in healthcare, business and others. This paper intends to define Big Data, its Applications and Techniques used for the analytics.
Keywords:
Stock-ticker data, Internet of Things, Point-Of-Sale, Anonymization, Correlations and High-Frequency Trading.
Abstract
A Comparative Study on Healthcare System using Data Mining Prediction Techniques
R. Kalaivani, S. Subhasini
Abstract:
Its fast growing fields is health care system. The medical industries have large amount of set collections about diagnosis, patient information and medications. To derive these data is into useful pattern and to predicting forthcoming trends data mining approaches are used in health care industries. The health care industries start with new treatments and giving medicine every day. The healthcare organization should give the important recognition and the patients to procuring good excellence of service. This paper examines various data mining techniques which are used in medicine area for good decision making.
Keywords:
Data mining, Prediction Techniques, Decision Making.
Abstract
Survey on Thyroid Diagnosis using Data Mining Techniques
S. Sathya Priya, Dr. D. Anitha
Abstract:
Recently, thyroid diseases are more and more spread worldwide. India, for example, one of eight women suffers from hypothyroidism, hyperthyroidism or thyroid cancer. Factors that affect the thyroid function are: stress, infection, trauma, toxins, low-calorie diet, certain medication etc. It is very important to prevent such diseases rather than cure them, because the majority of treatments consist in long term medication or in chirurgical intervention. The current study refers to thyroid disease classification in two of the most common thyroid dysfunctions (hyperthyroidism and hypothyroidism) among the population. The authors analyzed and compared four classification models: Naive Bayes, Decision Tree, Multilayer Perceptron and Radial Basis Function Network. The results indicate a significant accuracy for all the classification models mentioned above, the best classification rate being that of the Decision Tree model.
Keywords:
Data Mining, Classification Model, Thyroid Diseases, Neural Network, Decision Tree, Na�ve Bayes, Chi Square.
Abstract
Logistic Regression: A Novel Approach to Implement in Business Intelligence
D. Kalaivani, Dr. T. Arunkumar
Abstract:
Business Intelligence is defined as a set of mathematical model and analysis methodologies that exploit the available data to generate information and knowledge useful for complex decision-making processes.[1] Business Intelligence encompasses all aspects of gathering, cleansing, mining, storing and analyzing data as well as disseminating the insights to the right decision makers. Data warehousing and analytic modeling are as much a part of a BI strategy as are visualization tools and digital dashboards [1].Decision tree learning is the most popular and powerful approach in knowledge discovery as well as in data mining. This is used for exploring large and complex bodies of data in order to discover useful patterns. Decision tree learning uses a decision tree as a predictive model which maps observations about an item to conclusions about the item's target value. Classification algorithm processes a training set containing a set of attributes. There is a growing popularity of Internet as a medium of information search, communication link and online buying worldwide including India[2].This paper highlights the research opportunities in Business Intelligence [BI]. It also analyses the statistical method Logistic Regression.
Keywords:
Business Intelligence, Data Mining, Buyer Behaviour Prediction, Decision Making, Knowledge Management.
Abstract
Blue Eye Technology
N.Santhiya, E.Maheswari
Abstract:
Human error is still one of the most frequent causes of catastrophes and ecological disasters. The main reason is that the monitoring systems concern only the state of the processes whereas human contribution to the overall performance of the system is left unsupervised. Since the control instruments are automated to a large extent, a human � operator becomes a passive observer of the supervised system, which results in weariness and vigilance drop. Thus, he may not notice important changes of indications causing financial or ecological consequences and a threat to human life. It therefore is crucial to assure that the operator�s conscious brain is involved in an active system supervising over the whole work time period. Blue Eyes the system developed intended to be the complex solution for monitoring and recording the operator�s conscious brain involvement as well as his physiological condition. This required designing a Personal Area Network linking all the operators and the supervising system. As the operator using his sight and hearing senses the state of the controlled system, the supervising system will look after his physiological condition. The main objective of Blue eyes technology is to develop a computational machine having sensory and perceptual ability like those of humans. The Blue Eyes technology system is a combination of a set of hardware and software systems. The hardware consists of a central system unit (CSU) and data acquisition unit (DAU).
Keywords:
Analyzing Emotional state, Facial expression, Imparted Informational state, Perceptual abilities, Productive Sensory, Computational Machines
Abstract
Simulators and Emulators used for Wireless Sensor Network
Dr. V. Vasanthi
Abstract:
Wireless Sensor Networks (WSNs) have been gaining growing interest in the past years; WSN tasks of a each sensor network work include not only monitoring and measuring certain phenomena, but also delivering gathered data. Sensor network require applying different techniques used in wired and wireless network. Simulation tools for wireless sensor networks are increasingly being used to study sensor webs and to test new applications and protocols in this evolving research field. It is useful to researcher to verify new ideas and analyze with proposed algorithms in virtual environment and help to avoid expensive hardware usage and time consumption also. This paper provides a comprehensive survey and comparisons of various popular sensor network simulators with a view to help researchers to choose the best simulator available for a particular application environment.
Keywords:
Wireless sensor networks, Simulator, Emulator, Comparison, Survey Performance evaluation
Abstract
Mobile Banking and its Security
Dr. S. Krishnaveni, N. Sathyadevi
Abstract:
The most of the people are using in Mobile Banking option. It is the easy way to transacting the amount. We can easily download this application on our Smartphone and we should access in this mobile banking option. If we want access the mobile banking, the security was very important think. So there are variety of securities are available like NFC security, QR security and etc. As millions of dollars have been exhausted on building mobile banking systems, reports show that potential users may not be using the systems, despite their availability, as they are not aware its benefits, uses and how they should depend and trusted it. This manuscript investigate the differences between using Smartphone as a platform for authentication, using near field communication (NFC) and other applications in banking processes as well as security of each [16]. Mobile banking is attractive because it is a convenient approach to perform remote banking, but there are security shortfalls in the present mobile banking implementations [17].
Keywords:
Mobile Banking, Smartphone, NFC, Remote Banking, Security, Protocol
Abstract
A Knowledge Based Post Mining Techniques in Large Databases through Interactive Post Processing of Association Rules using Ontologies
A. Vaishnavi, M. Hemalatha
Abstract:
In Data Mining, Association rules are created by analyzing data for frequent if/then patterns and using the criteria support and confidence to identify the most important relationships. the usefulness of association rules is vigorous limited by the huge amount of delivered rules. To overcome this drawback, several methods were proposed in the literature such as itemset concise representations, redundancy reduction, and postprocessing. Although, being generally based on statistical report, most of these methods do not guarantee that the extracted rules are interesting for the user. Thus, it is critical to help the decision-maker with an efficient postprocessing step in order to reduce the number of rules. This paper proposes a new interactive approach to prune and filter discovered rules. First, it propose to use ontologies in order to improve the integration of user knowledge in the postprocessing task. Second, it proposes the Rule internal representation of formalism extending the specification language proposed by Liu et al. for user expectations. Third it proposes to use the same in large databases for an effective and efficient result with out loss of an interesting item set. This paper system will reduce the number of rules with out loss an interesting item set while dealing with Large Databases.
Keywords:
Association rules, classification, interactive data exploration and discovery , Post processing Clustering
Abstract
Performance Tuning with Different Kernel Function Hyperplane Analysis for Optimal Recognition Rate
P. Rukmanidevi, V. Kalaivani
Abstract:
Kernel principal component analysis is presented for kernel feature selection and High dimensional feature extraction to show kernel adaptations for nonlinear features selection of medical image data sets (MIDS). The proposed kernel principal component analysis extracts the salient features from a sample of unclassified patterns by use of a kernel. The kernel principal component analysis iteratively constructs a linear subspace of a high-dimensional feature space by exploiting a variance condition for the nonlinearly transformed samples. The resulting kernel subspace can be first chosen and then be processed for composite kernel subspace through the efficient combination representations used for further reconstruction and classification based on support vector machine.
Keywords:
Support Vector Machine, Principal component analysis, data-dependent kernel, nonlinear subspace.
Abstract
Effective Global Sensor Deployment for Coverage Problem in WSN using Ant Colony Optimization
T.B. Saranya Preetha, V. Sowmiya, K. Yamuna devi
Abstract:
This paper aims to identify optimal deployment locations of the given sensor nodes with a pre-specified sensing range, and to schedule them such that the network lifetime is maximum with the required coverage level. Since the upper bound of the network lifetime for a given network can be computed mathematically, this knowledge is used to compute locations of deployment such that the network lifetime is maximum. In this thesis ultimate goal is to realize an automated monitoring network so that detection applications of various emergency events can be practically implemented. Further, the nodes are scheduled to achieve this upper bound. This project uses artificial bee colony algorithm and particle swarm optimization for sensor deployment problem followed by a heuristic for scheduling. In addition, ANT colony optimization technique is used to provide maximum network lifetime utilization. The comparative study shows that artificial ACO performs better than bee colony algorithm for sensor deployment problem. The proposed heuristic was able to achieve the theoretical upper bound in all the experimented cases.
Keywords:
ANT colony optimization technique, artificial ACO, sensing range, sensor.
Abstract
Estimation of Claim Severity in Non-Life Insurance: A Non-Parametric Approach
K.M. Sakthivel, C.S. Rajitha
Abstract:
In non-life insurance setting of the right premium for the customer at the beginning of the insurance contract is absolutely necessary for an insurance practice. For that the accurate and authentic estimate of the number of claim occurrences and claims size is extremely important. Different methods are available in the literature for predicting the claim size of a policy for forthcoming years such as Generalized linear models (GLMs), Poisson regression models, Credibility models, Bayesian Models etc. But due to some changes in exposure, classification of rating factors, migration in risk classes, the above mentioned classical methods will not provide a suitable model for prediction of future claim size. Hence a dynamic empirical model will address this problem. Recent studies shown that Artificial Neural Networks (ANN) is powerful tools for prediction by observing variation present in the data and predict future observations based on the characteristics of trained data sets. In this paper, we have shown that ANN will produce relatively better result compare to GLM.
Keywords:
Claim Severity, Generalized Linear Model, Artificial Neural Network
Abstract
Horizontal Aggregation Function Using Multi Class Clustering (MCC) and Weighted (PCA)
Dr. K. Sathesh Kumar, P. Sabiya, S.Deepika
Abstract:
Data transformation and aggregation is the significant portion in data mining for data analysis and data set preparations. In a relational database environment, building such data set requires joining tables and aggregating columns from different dynamic tables. Several aggregation functions based on the SQL operations have been initiated for multi table aggregation by applying vertical joints. Such previous SQL aggregations are limited since they return a single number static data group. These aggregations worked well in the form of static datasets, but a major effort is still required to build data sets suitable for data mining purposes, where a tabular format is generally required and which need frequent updates. This suggested work proposes a very simple and effective summarization based dynamic join operations over high dimensional dataset. These extents the SQL aggregate functions to produce aggregations in horizontal form, returning a set of numbers instead of single aggregation. The research work also proposes a Multi Class Clustering (MCC) and Weighted PCA method to handle a high dimensional dynamic dataset with summarization technique. In the proposed technique, there are two common data preparation tasks are enlightened which includes transposition/aggregation and transforming categorical attributes into summarized labels. This executes the basic methods to evaluate horizontal aggregations which are named as CASE, SPJ and PIVOT respectively.
Keywords:
aggregation, Weighted PCA method, MCC (Multi class clustering)
Abstract
Secured Transcode Enabled Layer 7 Proxy Handoff in Mobile Networks
Anantha Prabha.P, Immaculate Jennifer J, Haripreethi G, Harshini P, Gokulraj S, Gowtham R
Abstract:
In today�s mobile era, multimedia applications need to communicate in real-time and are sensitive to the Quality of Service (QoS) they receive from the mobile network environment. For these applications to perform adequately and be widely used, QoS must be quantified and managed. Proxies can improve the quality of service of clients when the server proxy client networking architecture is applied to mobile networking environment. Since the mobile clients keep moving in the mobile networking environment, they should be able to switch to a new proxy dynamically in order to get the quality in multimedia streaming. In this paper, Application-layer Proxy Handoff (APH) is proposed to have applications be executed smoothly when mobile clients move in the server-proxy-client architecture. First, APH employs application-layer anycast to select one of the candidate proxies as the next proxy. Second, APH utilizes IPv6 multicast to switch the session from the original proxy to the next proxy smoothly. In order to meet the requirements of clients with multiple resolutions, transcoding enabled proxies are employed in this system. The transcoding enabled proxies perform transcoding as well as caching for efficient rich media delivery to mobile network users and also it optimizes the bandwidth requirement.
Keywords:
Proxy handoff, Transcoding, Application Layer any cast, Quos.
Abstract
Survey of Pros and Cons of Mobile Apps
S. Srividhya, A. Cynthia, J. Brindha
Abstract:
In this paper, The mobile application field has been receiving astronomical attention from the past few years due to the growing number of mobile app downloads and withal due to the revenues being engendered .With the surge in the number of apps, the number of lamentable apps/failing apps has withal been growing. Interesting mobile app statistics are included in this paper which might avail the developers understand the concerns and merits of mobile apps. In this paper, we have developed a mobile application with the aid of traditional software development life cycle phases (Requirements, Develop, Test, Maintenance) and we have used UML, M-UML, and mobile application development Technologies.
Keywords:
UML, M-UML, mobile application, Requirements, Develop, Test, Maintenance.
Abstract
Well-Ordered Workflow Preparation for Beneficial Multi Cloud Surroundings
N. Chithra, R. Saranya
Abstract:
Cloud computing is an require service in which common resources, information, software and other devices are provided according to the customer�s requirements. The data in cloud storage is hosted by the third parties. The cloud can contact all information over the internet without having any full knowledge of the infrastructure. The cloud provides safety, elasticity, low cost and it�s open to all users. Job scheduling is one of the major activities performed in all the computing environments. Scheduling is the process of deciding to commit resources between varieties of feasible task. It is a major challenge in similar and distributed systems. Task preparation techniques in distributed systems are usually based on trusting the precision of the information about the status of resources. The existing system scheduling algorithms in cloud reduces cost and conclusion time and also used for scheduling of scientific workflows. The proposed scheduling algorithm in is cloud based on deadline which allows the workflow management system to reduce the execution cost while delivering the results within deadline.
Keywords:
Task preparation techniques, distributed systems, Job scheduling.
Abstract
5G Mobile and Wireless Networks
R. Suganya, G. Sowmiya, B. Maheswari
Abstract:
In this paper explains about next generation 5G networks. 5G (5th generation mobile networks or 5th generation wireless systems) denotes the proposed next major phase of mobile telecommunications standards beyond the current 4G/IMT (International Mobile Telecommunication)-Advanced standards. 5G planning includes Internet connection speeds faster than current 4G, and other improvements. As the customer becomes more and more aware of the mobile phone technology, he or she will look for a decent package all together, including all the advanced features a cellular phone can have. In the proposed design the user terminal has possibility to change the Radio Access Technology -RAT based on certain criteria. For the purpose of transparent change of the RATs by the mobile terminal, we introduce so-called Policy-Router as node in the core network, which establishes IP tunnels to the mobile terminal via different available RATs to the terminal.
Keywords:
5G, Radio Access Technology (RAT), VOIP (voice over Internet Protocol), D2D communication
Abstract
Cloud Computing Security Issues
K. Vasanthi, U. Vanitha
Abstract:
Cloud computing is current buzzword in the market. It is pattern in which the property can use basis thus reducing the cost and complexity of service providers. Cloud computing to cut operational and capital costs and more importantly let IT departments focus on planned projects instead of keeping datacenters running. It is much more than simple internet. It is a build that allows user to access applications that actually exist in at location other than user�s own computer or other Internet-connected devices. This Paper Presentation Study Of Iaas Components Confidentiality, Integrity, Availability, Authenticity, and Privacy are necessary concerns for both Cloud providers and clients as well. Infrastructure as a Service (IaaS) serves as the groundwork layer for the other delivery models, and a lack of security in this layer will certainly affect the other delivery models.
Keywords:
Computing, Cloud Computing Security, Infrastructure as a Service(IaaS)
Abstract
Automatic 2D-to-3D Image Conversion-A Study
M. Sofia, R. Sabarinathan, Shivashankar
Abstract:
With increasing demands of 3D contents, conversion of many existing two-dimensional contents to three-dimensional contents has gained wide interest in 3D image processing. It is important to estimate the relative depth map in a single view image for the 2D-To-3D conversion technique The three-dimensional (3D) displays required the depth information which is unavailable in the conventional 2D content. Recent advances in 3D have increased the importance of stereoscopic content creation and processing. Therefore, converting existing 2D contents into 3D contents is very important for growing 3D market. The most difficult task in 2D-to-3D conversion is estimating depth map from a single-view image.
Keywords:
2D-to-3D conversion, two-dimensional contents, single-view image.
Abstract
Mean Weighted Artificial Bee Colony (MWABC) based Feature Selection for Gene Co-Expression using Microarray Data
M. Sofia, Dr. N. Tajunisha
Abstract:
In microarray data analyses, three important issues are how to determine incomplete data, how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. To deal with redundant information and improve classification, propose a Mean Weight Artificial Bee Colony (MWABC) gene selection which combines ABC and mean weight function. First select a small subset of genes based on fuzzy and mean value of the attribute by considering the preference-ordered domains of the gene expression data. Propose an MWABC analysis to select discriminative genes and to use these genes to classify tissue samples of microarray data. Experiments show that the proposed MWABC is able to reach high classification accuracies with a small number of selected genes and its performance is robust to noise.
Keywords:
: Gene selection, microarray, classification, supervised-learning, Mean Weight Artificial Bee Colony (MWABC)
Abstract
An Efficient Accumulative Constraint Based Leader Ant Clustering
S. Sridevikarumari
Abstract:
The thesis entitled �An Efficient Accumulative Constraint Based Leader Ant Clustering� is based on the Ant colony optimization clustering algorithm. Ant-based clustering can be divided into two groups. The first group of methods directly mimics the clustering behavior observed in real ant colonies. The second group is less directly inspired by nature. Clustering task can be considered as the most important unsupervised learning problems, which deals with finding a structure in a collection of unlabeled data. To this end, it conducts a process of organizing objects into groups. These algorithms have recently been shown to produce good results in a wide variety of real-world applications. In recent years, research on and with the ant-based clustering algorithms has reached a very promising state. Clustering with constraints is a developing area of machine learning, improve the efficiency of analysis and express the intractability results. It is an interactive process where a user can run the constraints number of times to refine previous clustering results. In this research, An efficient and fast constraint based Leader Ant Clustering provide three new variants algorithm (MCALA, MEALA and CEALA) are proposed that implements the following constraints: the must-link, cannot-link constraints, e �constraints and accumulative constraints. The main aim of this research is to improve the accuracy of the clustering techniques. The real data sets from the Machine Learning repository namely Glass, Iris, Wine, Thyroid and Soybean are used in this experiment. These accumulative constraints algorithms have been compared to other constraint based clustering algorithms such as K-Means clustering with constraints and the original Leader Ant clustering algorithm. The average accuracy of the proposed MCALA, MEALA and CEALA are found to be higher than the COP-K-Means, MCLA, MELA and CELA.
Keywords:
clustering, constraint, artificial ants
Abstract
A State of Art Review on Current Researches in Moblie Adhoc Networks
G. Deepalakshmi, R. Saradha, G. Santhiya
Abstract:
Adhoc Mobile Networks is one of the area in wireless communication networks. Since it is a wireless network has many issues to be addressed in Clustering, Routing, and Security parts. Even though there are many issues, routing is have more concern. This paper gives a state of arts review of current routing algorithms. This paper suggest an approach to overcome deadlocks ,loops and provide improved performance of routing protocols for the adhoc network. Routing algorithms are used to overcome these problems.
Keywords:
Adhoc, Routing, Clustering, Throughput
Abstract
A Review on Security Issues in Wireless Sensor Networks using Bio-inspired Computing
R. Kanagaraj, P.S. Shinu, K. Pavithra
Abstract:
Wireless Sensor Networks (WSNs) is one of the most upcoming research area in computer science. Many issues such as clustering, routing and security problems were addressed by the latest interdisciplinary science. Now a day the Bio-Inspired Computing algorithms become more popular to solve the various issues of computer science field. Bio- Inspired Computing algorithms are the excellent behavior of the various species which is used for their life saving methods. This paper will have the review on Bio- inspired computing Algorithms which is specifically used in solving security problems in WSNs.
Keywords:
WSNs, bio-inspired computing, security issues, ant colony optimization, bee colony algorithm
Abstract
A Review on Wireless Sensor Network Routing Algorithm using Bio-inspired Computing
D. Antony Arul Raj, V. Keerthana, R. Roshini
Abstract:
Wireless sensor network is dynamic and distributed node which controls the transmission range, processing as similar as limited energy source. The information that enables them to select routes between any two nodes on a computer network is referred as routing protocol. Wireless sensor networks (WSN), is also called wireless sensor and actuator networks (WSAN), some of the modern networks are bi-directional, and sensor activity are used to control them. The WSN is built of "nodes" � each and every node is connected with the sensors they have connected radio receiver with external and internal antennas.
Keywords:
Component, formatting, style, styling, insert
Abstract
Study on Machine Learning Techniques using SVM
M. Selvanayaki, T.S. Anushya Devi
Abstract:
Machine Learning is the study of computer algorithms that improve automatically through experience. Applications range from data mining programs that discover general rules in large data sets, to information filtering systems that automatically learn user�s interests. An important task of machine learning is classification, also referred as pattern recognition; where one attempts to build algorithms capable of automatically constructing methods for distinguish between different exemplars. This paper deals about different machine learning techniques for the prediction process.
Keywords:
Machine Learning, Supervised Learning, Unsupervised Learning, Classification, Prediction, Support Vector Machine.