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National Conference on (Advances in Modern Computing and Application Trends) Organised By Acharya Institute of Technology Bangalore, India

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    Volume-4 Issue-5(October 2016)
    Title: Distributed Data with Association Rule Mining
    Authors: A.Subhasheni and R.Rangaraj
    Abstract: Data mining is used to extract data from large amount of data, these data are stored in database. Data processing is large in many applications so processing time and storage area of data was increased, so this problem is solved by using distributed database. The clustering algorithm is used to reduce processing time and storage area by clustering approaches. In this paper proposed a Association Rule Mining (ARM), Mining Frequent Pattern and Cover Rule (CR) algorithm are used along with distributed database for reducing response time and communication cost.
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    Title: Advanced Detection Strategy Using 5G Technology for Potential Prevention of Brain Disorders
    Authors: Ahalya Mary J and R. Badri Narayanan
    Abstract: A wireless architecture exclusively for instantaneous sensing and transmitting important physiological signals over cellular networks has been introduced in this paper. Electrical activity in the form of nerve impulses from neurons is selected as the preliminary source of acquiring signals for this exercise. This method of analysis of electrical signals could potentially help in the diagnosis various degenerative disorders of the brain. The basis of the technology uses a Wireless Body Area Sensor Network to receive the physiological data from a user's body and effectively transmit those signals to a WBAN fixer. The details of diversified techniques that have been adopted for the transmission of the physiological data have been explained. We envisage having a keen channel in upcoming fifth generation mobile technology, as increased bandwidth for everyone is anticipated for services like data on demand. The originality and uniqueness of the approach being stated, lies in the fact that it would enable online, round-the-clock transmission cellular system for the subscribers at very low power consumption by collaborating with the underlying sensor networks.
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    Title: Different Approaches in Software Reliability
    Authors: Ashutosh Shukla, Aarti Pandey and Krishna Kumar Verma
    Abstract: Software reliability is the probability which is used to predicting the quality of software system. Different modeling approaches is used to improve software reliability like based on path, state,, architecture, prediction etc. Software reliability is different from hardware reliability because it is design process not manufacturing. We utilize the different modeling for capturing the behavior of software system in heterogeneous environment. For model validation they used real time constraint and obtained satisfactory output. This models implements in software development life cycle.
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    Title: An Overview on Major Task in Data Mining System
    Authors: B. Chitradevi and Thinaharan.N
    Abstract: Currently, the amount of data stored in databases is rising at a great speed. This provides increase to a need for new techniques and tools to aid humans in automatically and intelligently analyzing vast data sets to gather useful information. This growing require provides birth to a new research field called Knowledge Discovery in Databases (KDD) or Data Mining, which has attracted attention from researchers in many different fields including database design, statistics, pattern recognition, machine learning, and data visualization. This paper gives a definition of KDD and Data Mining, describing its tasks, methods, and applications. In this study is gaining the best technique for extracting useful information from large amounts of data. This paper gives impression on different tasks includes in Data mining. Data mining involves the tasks like anomaly detection, classification, regression, association rule learning, summarization and clustering.
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    Title: The Impact of Data-Aggregation Techniques In WSN
    Authors: Dr.NagendraNath Giri
    Abstract: Wireless sensor networks (WSNs) consist of sensor nodes. These networks have huge application in habitat monitoring, disaster management, security and military etc. Wireless sensor nodes are very small in size and have limited processing capability with very low battery power. This restriction of low battery power makes the sensor network prone to failure. The main goal of data aggregation algorithms is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced. In this paper we discuss about data aggregation and its impact in WSN.
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    Title: Cluster Based Radio Coverage for Node Clone Detection in Wireless Sensor Network
    Authors: Mr.R.KALIYAPPAN. and Dr.J.THIRUMARAN.
    Abstract: Energy efficiency and sensing coverage are essential metrics for enhancing the lifetime and the utilization of wireless sensor networks. Many protocols have been developed to address these issues, among which, clustering is considered a key technique in minimizing the consumed energy. An efficient power saving scheme and corresponding algorithm must be developed and designed in order to provide reasonable energy consumption and to improve the network lifetime for wireless sensor network systems. The cluster-based technique is one of the approaches to reduce energy consumption in wireless sensor networks. In this propose a clustering based clone detection algorithm (CCDA) to provide efficient energy consumption in such networks. improved LEACH (CCDA-LEACH) protocol to reduce the scale of the cluster by considering the residual energy of nodes and the optimal number of clusters. Furthermore, the proposed algorithm clone detection algorithm to detect the replicate node attacks by location information of nodes in the network so as to greatly reduce the occurrence of tampering with the information. Simulation results show that our proposed algorithm is simple yet efficient. An attacker can be detected with high probability while achieving approximately optimal throughput. The network’s ability against the attack from clone nodes is greatly improved.
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    Title: An Adaptive Approach to Vehicle Number Plate Detection for Indian Style Based
    Authors: Rajath A N and Parashiva Murthy B M
    Abstract: Vehicle number plate recognition system is the hardcore of the intelligent traffic system. Detecting the region of a license plate is the key component of the vehicle number plate recognition (VNPR) system. A new method is adopted in this paper to analyze road images which often contain vehicles and extract NP from natural properties by finding vertical and horizontal edges from vehicle region. The proposed vehicle number plate detection (VNPD) method consists of 3 main stages: (1) a novel adaptive edge detection and logical OR masking used for detecting candidate region. (2) decomposing candidate region which contains predetermined NP alphanumeric character by using position histogram to verify and detect vehicle number plate (VNP) region. (3) Finally, the number plate slant correction to the horizontal line is adopted by the related operation of mathematical morphology and Randon transformation. In the proposed method, input vehicle images are commuted into grey images. Then the candidate regions are found by logical OR masking. We detect VLP region which contains predetermined LP and LP alphanumeric character by using position histogram. Experimental results show that the proposed method is very effective in coping with different conditions such as poor illumination, varied distances from the vehicle and varied weather.
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    Title: Enhanced Software Defect Prediction by using SVM-RBF Kernel
    Authors: Jasvir Kaur and Shelly Bhalla
    Abstract: Machine Learning approaches are good in solving problems that have less information. In most cases, the software domain problems characterize as a process of learning that depend on the various circumstances and changes accordingly. A predictive model is constructed by using machine learning approaches and classified them into defective and non-defective modules. Machine learning techniques help developers to retrieve useful information after the classification and enable them to analyse data from different perspectives. Machine learning techniques are proven to be useful in terms of software bug. In this paper prediction by SVM with RBF kernel and feature extraction by KPCA.
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    Title: Delay Aware Scheduler and Minimum Energy Routing Protocol in VANET
    Authors: V.Yokeshwaran and D. Raj Balaji
    Abstract: VANET (Vehicle Ad-hoc Networks) is emergent technologies that they justify, lately, the care of the industry and academics organisations. Vehicular Ad hoc Network (VANET) is an emerging field of technology, wireless communication networks into vehicles to attain intelligent transportation systems. The communication between nodes that they are beyond of the reach of transmission of the radio is made in multi hops through the intermediate nodes contribution. These systems are used to provide a numerous of services ranging from traffic safety application to expediency applications for drivers and passengers. Key challenges in designing protocols for vehicular access networks include quick flexibility to frequent changes in the network topology due to vehicular mobility and delay awareness in data delivery. The proposed scheduling algorithm can be used to reduce infrastructure energy costs in vehicular roadside networks. In this system consider the scheduling problem when there is multiple roadside units (RSUs). In this case it is often needed to load balance and energy consumption across the roadside units so that energy provisioning costs can be reduced. The first is a low complexity Delay Aware scheduler algorithm which makes greedy RSU selections based on a minimum energy time slot task. Another proposed algorithm called Greedy Flow Graph Algorithm (GFGA), it makes the same RSU selection it reallocates time slots each and every time a new vehicle is assigned to the same region RSU. The experiments results show that the proposed scheduling algorithms perform well when compared to the existing algorithm.
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    Title: An Intelligent Approach to Detect and Isolate Black Hole Attacks in WSN
    Authors: Avneet Kaur and Mandeep Kaur
    Abstract: The detector nodes are connected wirelessly to make a network known as because the wireless detector network (WSN). The nodes have confined battery power and also the battery of the nodes can't be replaced. These detector nodes are used for collection the detector knowledge and transmit them to the sink or base station. This knowledge transmission from a node to the opposite node utilizes additional energy if the information is broadcasted the from detector nodes on to the sink. The cluster methodology is employed to cut back the energy utilization of the detector nodes and also the nodes are sorted into the clusters and also the cluster-head in every cluster can gathers the information and transmits it to the sink. During this Paper, planned study analyzes part attack in WSN victimization reserve path primarily based node activity and link health pursuit for the detection and elimination the part nodes.
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    Title: Forecasting Web Pages Using User Access Logs
    Authors: E.Vidhya and R.Khanchana
    Abstract: Web resources are analyzed using web mining techniques. Web mining techniques are divided into three categories. Content mining, structure mining and usage mining are the main types of web mining. Content mining and structure mining methods are used to analyze web page contents. User access details are analyzed using usage mining methods. The association rule mining techniques are used to mine hidden knowledge from large data sets. Candidate sets combines the attribute name and value. Item sets are build with candidate sets. Support and confidence values are used in the association rule mining process.Web page forecasting process includes the preprocessing and prediction faces. Preprocessing challenges include large amount of data, choosing sliding window size, identify sessions, and extracting domain knowledge. Prediction challenges include long training/prediction time, low prediction accuracy, and memory limitation. Support vector machines (SVMs), artificial neural networks (ANNs), and Markov models are integrated. Markov model and all Kth Markov model are used in Web prediction process. Modified Markov model is used to alleviate the issue of scalability in the number of paths. Two-tier prediction framework creates an example classifier EC, based on the training examples and the generated classifiers. Markov model and association rule mining techniques are combined to perform the prediction process. The two tier architecture is extended with statistical log features. Boosting association rule mining algorithm is integrated with the prediction system. The prediction system is also improved with bagging technique. The preprocessing techniques are also adopted to select optimal data and sessions.
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    Title: Implementation of Different Recognition System: Iris, Fingerprint
    Authors: Shraddha S. Giradkar and Dr. N. K. Choudhari
    Abstract: With the rapid development of technologies, security and privacy are the major concern. In order to keep electronic data safe many corporations are using different technologies to monitor their employees. Biometric is one of the security system methods which are used by many industries. Biometric security system is used for recognition of employees or persons by using their biological characteristics such as iris, fingerprint, and face. In this process we present software and hardware based fake detection method which can be used in multibiometric system to detect different types of fraudulent access attempts. The proposed research includes three parts, that is first one is iris recognition; second one is fingerprint recognition and third one face recognition. This paper covers only first two parts i.e. iris recognition and fingerprint recognition of our research. To make sure the actual presence of real characteristic against fake self generated sample which is most important problem in biometric authentication, which can be resolved with the development of new efficient and effective protection measures. The present approach has a very low complexity, using different sample of image quality features extracted from one image which is used to compare the difference between real and fake samples. The experimental results which is obtained from the sample images of datasets of fingerprint and iris show that the present method is competitive as compared with other state of the art approach and this study of the image quality of real biometric samples provides valuable information which helps to differentiate between the real and fake traits.
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    Title: Preprocessing of Mammograms for Computer-Aided Diagnosis of Breast Cancer
    Authors: Pravin M. Palkar and Dr Pankaj Agrawal
    Abstract: The appearance of masses in in X-ray mammograms is one of the early signs of women breast cancer. Currently, mammography is the single most effective and reliable technique in the investigation of breast abnormalities detection such as masses. However, their detection is still a challenging problem due, to the diversity in shape, size, and ambiguous margins to the poor contrast between the cancerous areas and surrounding bright structures. This paper presents an effective image preprocessing algorithm for detection of masses in digitized mammograms. Preprocessing techniques are implemented using MATLAB.It is preliminary stage used in mammogram image enhancement. The algorithm removes and deletes unwanted signs present in the background of the mammogram, and to extract the breast area. Then an enhancement process is applied to improve appearance and increase the contrast of images and to eliminate noise. Once the breast region has been found, a segmentation phase is performed for detection of various types of masses in mammograms.
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    Title: An Innovative methodology to detect and prevent black hole attacks in wireless sensor networks
    Authors: Avneet Kaur and Mandeep Kaur
    Abstract: Due to the particular characteristics, Wireless sensor Networks (WSN) is severely unsafe and are receptive malicious attacks. One amongst the foremost malicious threats to WSN is within the sort of part attack that focuses on the routing protocols. This genre of attacks will have a awfully serious impact on ranked routing protocols. A range of security solutions is place forth to safeguard WSNs from part attacks. However, a majority of the solutions are cumbersome and vitality inefficient. During this paper an jury-rigged classified energy efficient black-hole detection & interference model is planned, to guard device Network from part attacks. Our planned approach is straightforward and relies on reserve path choice between device node and base station. The results show that our planned algorithmic program is effective in detection and preventing with efficiency the part attacks.
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    Title: From 'Pre-Position' to 'Post-position'
    Authors: Priyanka Jain
    Abstract: Lately, due to gravity in computational undertakings, Prepositions have acknowledged an ample amount of debate. This paper discusses on experiments in analyzing the linguistic role definitions assigned to prepositional phrases. We have done a detailed study along with a research on semantic and syntactic equities of prepositions in the context of semantic interpretation of phrases.
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    Title: Performance Evaluation of Cyclic Prefix and Zero Padding Equalization for QPSK MIMO-OFDM System
    Authors: Preeti Sondhi and Reena
    Abstract: The paper gives an overview of an equalization technique for MIMO-OFDM system for the uplink in broadband wireless communication system. In this paper, an equalization technique is proposed for general MIMO-OFDM systems. MIMO-OFDM is a powerful modulation technique used for high data rate and is able to eliminate inter-symbol interference by using guard interval and inter-carrier interference by using an equalizer. This paper also compares the BER performance for cyclic prefix and zero padding for QPSK MIMO-OFDM systems with and without the use of equalization technique. The future challenges are also highlighted in this paper.
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    Title: Heterogeneous Face Recognition Technique used in Caricatured Faces
    Authors: Chaya P
    Abstract: Segmentation and recognition of the caricatured faces problems are addressed in this paper. A caricature is a facial sketch of a subject’s face that exaggerates identifiable facial features beyond realism, while still conveying his identity. Segmentation deals with extracting facial features of the subject like eyes, nose, chin etc., and adding a textual description for each attribute. This segmentation procedure helps in defining the facial attributes and which is helpful for caricatures face recognition. In our experiment we have considered lined based caricatures
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    Title: An Efficient Tree based Micro Cluster using DBSTREAM
    Authors: Kayalvizhi T and K. Renuka
    Abstract: Clustering streaming data requires algorithms that are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited. Clustering has to be performed in a single pass over the incoming data and within the possibly varying inter-arrival times of the stream. Likewise, memory is limited, making it impossible to store all data. For clustering, we are faced with the challenge of maintaining a current result that can be presented to the user at any given time. The proposed system works a without parameter based algorithm that automatically adapts to the speed of the data stream. It makes best use of the time available under the current constraints to provide a clustering of the objects seen up to that point. The proposed approach incorporates the age of the objects to reflect the greater importance of more recent data. For efficient and effective handling, here introduce the Tree based DBSTREAM micro cluster (TDBS), a compact and self-adaptive index structure for maintaining stream summaries. Additionally, we present solutions to handle very fast streams through aggregation mechanisms and propose novel descent strategies that improve the clustering result on slower streams as long as time permits. Our experiments show that our approach is capable of handling a multitude of different stream characteristics for accurate and scalable anytime stream clustering.
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    Title: Ontology Based Information Extraction - A Survey
    Authors: Dr.S.Vijayarani and Mrs.K.Geethanjali
    Abstract: Information Extraction is used for finding structured information from unstructured or semi structured machine readable web documents. The main function of information extraction is to retrieve relevant information from the web document. Nowadays, Ontology Based Information Extraction system becomes an emerging subfield in the field of information extraction. Ontology is a proper and explicit specification of conceptualization. Ontology plays an important role in the process of information extraction. Ontology supports to build a semantic web and plays a vital role in the knowledge representation. In this paper we have conducted a detailed study about information extraction, ontology and its approaches, architecture of ontology and ontology based information extraction. This study will help the researchers those who wish to do their research in the area of ontology based information extraction.
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    Title: Combination of Cloud Computing and DevOps
    Authors: Mandeep Kumar
    Abstract: Cloud computing is a powerful technology that provides Software as a Service (SaaS), Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). So it provides storage, data center, software, hardware, infrastructure and application which all are on demand, anytime and anywhere with low-cost. Platform as a Services (PaaS) enable developers to automate the application build and development process within a secure, enterprise grade application infrastructure all in the cloud. Development and Operations (DevOps) is a productive way to develop software in high quality code and delivered more quickly. The combination of Cloud computing and DevOps services simplify provisioning and managing infrastructure, deploying application code, automating software release processes, fast application development and monitoring your application and infrastructure performance. Adopting both, organizations are not only virtually build application in any programming language with any programming tools but also deploy and run application quickly and reliably on any infrastructure.
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    Title: Image Compression Techniques – An Overview
    Authors: Dr. S.Vijayarani and Ms. Nivetha
    Abstract: Compression is one of the image processing technique, it reduces the size of the digital image and allows more images to be stored in memory, easy file transfer, decrease costs for storage hardware and network bandwidth. It is minimizing the size in bytes of an image without degrading the quality of the image to an unacceptable level. It also reduces the time required for images to be sent over the Internet or downloaded from Web pages. Different types of compression techniques are available which compress the image for easy transmission over the internet. Compression can be either lossy or lossless. This paper provides the basic concept of image compression techniques, lossy and lossless compression techniques, different types of compression techniques and methods.
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    Title: Agent Based File Security
    Authors: Avinash Konduri and Pajjuri Srividhya
    Abstract: Agent Based File Security is a network based application which is used for file security over a network. In today’s context, data, files, images get copied from place to place on the internet and are claimed by the copiers for ownership. In such an environment prevention of copying, deletion of data etc. is a tough job and requires a great deal of attention. Hence, in Agent Based File Security the main objective is to create a secure environment for the files to be stored in and to create an agent which has to monitor the changes that takes place on the file. Whenever a file is created, an agent has to be attached to that file so that the agent monitors each and every modification that is done on that file. The main objective of the agent is to monitor the temporary file which contains all the changes that is done on the actual file. Whenever a file from one system is copied into another system on a network, the file along with the attached agent is copied to the system. The changes on the file such as Edit, Rename, Copy, Cut, and Delete will be read by the agent from the temporary file in the client system and informs these changes to the server which can be saved for future use. Thus a file can be monitored for the changes within a network and any misuse of these files can be detected
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    Title: Performance Analysed in V To V Communication
    Authors: D.Rajbalaji and R.Umamaheswari
    Abstract: Vehicular Ad-hoc Network (VANET) is a type of mobile Peer To Peer wireless network. That allows providing communication among nearby vehicles and between two vehicles and nearby fixed, roadside equipment. The lack of centralized infrastructure high node mobility and increasing, number of vehicles in VANETS result in several problems. Discussed in this paper such as interrupting connections, difficult routing, security of communications and scalability. Vehicular Ad-Hoc networks are mobile networks adapted to vehicles. It is possible to say they are a special case of Mobile Ad -hoc Network (MANET). Some authors have mentioned that, vehicular networks are also known as Inter-Vehicle Communications (IVC), Vehicle –to -Infrastructure (V2I), Vehicle-to-Vehicle (V2V), Car-to-Car (C2C) or simply VANET. For security purpose Vehicular Public Key Infrastructure (VPKI) has been used. VANET becomes very important security in considering the criticality of secured application. By using elliptic curve cryptography PKI algorithm provide’s trustworthiness of vehicular communications and privacy of vehicles, and enables vehicles to react to vehicular reports containing cryptographic data. New Technique HMAC provides secure and efficient communication in VANET environment. The Elliptic Curve Cryptography (ECC) malicious messages are identified based VtoV. It also detects the accident and other problems in the path of the vehicles. Elliptic Curve Cryptography (ECC) algorithm is used for stronger security during communication. The experiments results show that the proposed security algorithms perform well when compared to the existing algorithm.
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    Title: Performance Analysis of Clustering Algorithms on Heart Dataset
    Authors: K. Merlin Jeba and Dr.V.Srividhya
    Abstract: Clustering is a technique for uncovering similarity groups in data, called clusters. These approaches are used to understand the behavior or pattern of the large multidimensional data. The mission of this research work is to cluster the numerical datasets. Healthcare datasets (Heart) is used. To cluster the given dataset three different clustering algorithms K-Means, PAM and CLARA are used. After clustering, check the validation of cluster using Silhouette width measure. Through the experimental results, CLARA Clustering gets better performance when compared with other two Clustering Algorithms.
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    Title: Hard and Fuzzy partition in cluster analysis using Fuzzy C-means (FCM) clustering algorithm: A brief study
    Authors: R.Revathi and Dr. Antony Selvadoss Thanamani
    Abstract: In data mining, the conventional clustering algorithms have difficulties in handling the challenges posed by the collection of natural data which is often vague and uncertain. There are two types of clustering methods such as Hard and Fuzzy clustering. Fuzzy clustering methods have the potential to manage such situations efficiently. Fuzzy logic becomes more and more important in modern science. Clustering based on fuzzy logic, named Fuzzy Clustering. The basic notions of data, clusters and cluster prototypes are established and a broad overview of different clustering approaches is specified. There are many methods of Fuzzy Clustering nowadays. In our work we review the Fuzzy c - means clustering methods.
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    Title: A Succinct Study on Greedy Search Algorithm
    Authors: G.Banupriya and D.Thilagavathi
    Abstract: An algorithm is designed to achieve optimum solution for given problem. In greedy algorithm approach, decisions are made from the given solution domain. As being greedy, the closest solution that seems to provide optimum solution is chosen. Greedy algorithms tries to find localized optimum solution which may eventually land in globally optimized solutions. But generally greedy algorithms do not provide globally optimized solutions. A weighted matroids is a matroids together with a function from its elements to the nonnegative real numbers. The weight of a subset of elements is defined to be the sum of the weights of the elements in the subset. In this work we focus on the types, sources, components, advantages and disadvantages and its properties.
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    Title: Understandability of UML Class Diagrams using Object-Oriented Metrics
    Authors: Deepak Kumar Ravi and Rakesh Kumar Roshan
    Abstract: This Paper describe an improved hierarchal model for the assessment of high level designing of quality attributes of object oriented design using some advanced methods for quantitative evaluation of design attributes of object oriented software systems.Object-Oriented programs have changed the scenario of software industry in terms of software development and its supporting technology. The object-oriented features like inheritance and encapsulation have made it easy and suitably confined to the design. This Paper focuses on Metrics generation from UML Class diagrams. They can be used to model the dynamic aspects of a group of objects & control flow of an operation. Standard class diagram is taken from a project based on object oriented paradigms to calculate the metrics, which was developed using UML.
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    Title: Medical Image Retrieval Algorithms And Techniques Based On CBIR : A Review
    Authors: Mr. Suhas.S and Dr. C.R.Venugopal
    Abstract: Digital images are being produced and used in large quantities and volumes in the medical field for diagnostics and therapy. Due to the large sizes of the images as well as the image databases, CBMIR (Content based Medical Image Retrieval) arose. It has, therefore, led to an increased demand for efficient medical image data retrieval and management. In current medical image databases, images are mainly indexed and retrieved by alphanumerical keywords, classified by human experts. However, purely text-based retrieval methods are unable to sufficiently describe the rich visual properties or features inside the images content, and therefore pose significant limitations on medical image data retrieval. The ability to search by medical image content is becoming increasingly important, especially with the current trend toward evidence-based practice of medicine. This need is mainly due to the large amount of visual data produced and the unused information that these data contain, which could be used for diagnostics, teaching and research. The systems described in the literature and published propositions for image retrieval in medicine are critically reviewed and sorted by medical departments, image categories and technologies used. This article gives an overview of available technologies in the field of content based access to medical images.
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    Title: A Study of Decision Tree Algorithm for Data Mining
    Authors: A.Muruganandham and R.Sekar
    Abstract: Data mining is the useful tool to discover the knowledge from large data. Different methods & algorithms are available in data mining. Classification is most common method used for finding the mine rule from the large database. Decision tree method generally used for the classification, because it is the simple hierarchical structure for the user understanding & decision making. And also discussed about algorithms like ID3, C4.5, CART. HAC Algorithms from clustering and ID3 and C4.5 and CART algorithms from decision tree and it can produce the better results than the traditional algorithms. The comparative study of these algorithms to obtain which one is high accuracy, frequency, measure, procedure, Pruning, error rate and time complexities from the decision tree algorithm.
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    Title: A review of attitude and perception of IoT security and privacy in critical societal areas
    Authors: Miss. Gayakawad Ghrushmarani Liladhar
    Abstract: The gradual revolution has influenced public sectors called ‘transport, home-automation, industrial, energy and health issues’ .It has been going through novel devices of networking for progressing the services. Here I stress on the security requirements which are useful to all societies .They impress the public sector energy water and health management methods. I have prepared this paper collecting material from research paper and books available. It analyses the attitudes and perceptions of the IOT system .This paper brings the current challenges in this region and highlights the need for coming together to frame united opinion about the risks of IOT security.
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