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ijmcs  IJMCS

Volume-2 & Issue-4 Published (Acceptance Ratio=25%) http://www.ijmcs.info/current_issue

ijmcs  IJMCS

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-2(April 2016)
    Title: Temporal Reasoning and Temporal Maintenance Systems: A Survey
    Authors: Akash Rajak
    Abstract: The research in temporal databases is going to complete its third decade. From time to time various researches have been carried out in this direction leaving its impact on almost every area, such as record keeping applications, clinical application, scientific application, financial applications and project management. The researches in the field of temporal data mining can be divided into two areas. One is related to temporal maintenance while another deals with the task of temporal reasoning. The integration of these two tasks forms the architecture of temporal mediator, which now a days are used for the designing of management information systems. The paper is based on the survey of temporal maintenance and temporal reasoning systems developed so far.
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    Title: Fuzzy Stochastic Model for Socio-Economic Status of Socially downtrodden People in the Southern District of Tamilnadu
    Authors: Dr.P.Arumugam and P.Jose
    Abstract: The economic status plays a vital role, For every studies and analysis of a country growth, Socio economic status of individuals progress become one of an important fundamental element for every countries in this new age. Its perception is found to be very multifarious and difficult to measure. This paper is focusing about the economic status of socially drown trodden people in the Southern region villages of Tamil Nadu in India. As it is essential to obtain relevant information to take long term management decision for improve the basic needs of these people. We should be measured there economic status right away and precisely. This subject is treated using an appropriate technique namely fuzzy approach. The replica describes how fuzzy logic can be applied in measuring economic status of people using various indicators. The model intend to treated inputs from individual components like occupation, parental educational level, family income, wealth and place of residence, Expenditure. And they are combined using fuzzy rule bases to provide an overall measure of economic status. It may then be addressed to Government and decision makers as they move towards a rapid growth of rural life in the near future.
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    Title: A Review on Social Sentiment Analytics for Public Opinions on Twitter
    Authors: Monica Ingle and Emmanuel M
    Abstract:Sentiment analysis of micro-blogging sites like twitter has attracted much attention due to the rapid and extensive growth in Twitter’s popularity as a platform for people to express their opinions and attitudes towards a great variety of topics. It has provided an economical and influencing way to expose timely public sentiment, which is a critical issue for decision making in various domains or sectors. In this paper various techniques and approaches for performing sentiment analysis are surveyed. Some of the models reviewed here are specific to some domain, and some are not specific to any domain they can be also used to seek particular topic or aspects in one text cluster in comparison with another background text collection.
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    Title: Iris Recognition Using Fuzzy SVM Based On SIFT Feature Extraction Method
    Authors: Gourav Sachdeva and Dr. Bikrampal Kaur
    Abstract:Iris recognition is a standout amongst the most exact character verification system. From the time when it’s introduced, numerous systems have been proposed to improve the execution. Numerous strategies have been proposed to highlight extraction by numerous analysts. The Iris recognition is one of the alluring methodology for client's distinguishing proof, gives high state of safekeeping in addition to convenience as compared to other approaches of identification similar to customary ID in addition secret key that could be lost or else exchanged. Though, iris recognition systems are executed on wide-ranging purpose of sequential handling frameworks, for example generic CPUs. Iris recognition is the technique for biometric which is more steady and secure when contrasted with the other biometric attributes, for example, fingerprints, hand geometry, speech recognition, face acknowledgment, walking pattern, and so on in light of the fact that features of iris doesn’t transform in singular's lifetime. The iris recognition procedure only takes few seconds to confirm individuals ID. In this paper we proposed a novel technique by utilizing fuzzy SVM, SIFT and genetic algorithm. The result is evaluated using various parameters such as accuracy, FAR and FRR. The whole stimulation takes place in MATLAB environment.
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    Title: An Analysis of Women Evolution Using Ordinal Classification in Data Mining
    Authors: Dhanalakshmi.D and Dr.J.Komala Lakshmi
    Abstract:Women development and empowerment is one of the key factors for nation’s growth and success. Human development is the measure to evaluate nation’s achievements in health, knowledge and standard of living. India belongs to medium human development country. Human development means the development of both men and women. The evolution of women is essential to upgrade our country to very high or high human development country. This proposal evaluates women evolution in specific geographical area using ordinal scales. It helps to identify the relationship between women evolution and family’s enrichment in terms of health, economy and standard of living. The result would provide sufficient information to implement new mechanism and policies for women’s betterment and to improve human development of our nation. The improvement of both men and women improve the quality of life at home as well our nation.
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    Title: Privacy Preserving Using Public Auditing and Detection of Packet Drop Attacks in Wireless Ad Hoc Networks
    Authors: Mr. Gangadhar Immadi, Kavya Ravindren and Elizabeth Varghese
    Abstract:Network Security consists of various protocols that are adopted to prevent and monitor unauthorized access, misuse or modification of network accessible resources. Networks are subject to attacks from malevolent sources which cause loss of packets. In a multi-hop wireless Ad hoc network, the sources of these attacks can be due to link errors and malicious drops. When a series of packet loss in a network are observed, we identify if these losses are generated due to link error itself or by the combination of link errors and malicious drops. The intruder drops packets without the knowledge of the nodes present, which corrupts or reduces the network’s performance. The packet drop rate in this intruder case has similar value when compared to the link error rate. Due to this, an accurate detection cannot prove satisfactory. In this paper, we develop an improved accurate detection rate to find the correlation between the packets lost based on a public auditing framework which uses Homomorphic Linear Authenticator (HLA).
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    Title: A Survey on Cloud Computing Energy Efficient Scheduling Algorithms
    Authors: Pardeep Singh and Simarjeet Kaur
    Abstract:Cloud computing is emerging technology due to pay-as-you-go pricing model. It is spreading globally, due to its easy and simple service oriented model as it offers utility -oriented IT services. Some people are having perception that cloud computing is just another name of Internet. The numbers of users accessing the cloud are rising day by day. Clouds are based on data centers, which are powerful to handle large number of users, who can access anytime and anywhere. Data centers consumes huge amount of energy leads to increase cost and carbon emission. Large number of data centers is easy to built, but not good for environment. In cloud computing we are available with different virtualized resources in order to complete the user task, hence in cloud computing. In this paper we have analyzed various algorithms by considering various parameters in which energy efficiency is mainly focused, in order to resolve the issue of large energy consumption in data servers, scheduling place a vital role, either in assigning virtual machines on servers or assigning tasks to various virtual machines. There are some limitations in these algorithms which further need improvement. Meta-heuristic algorithms could be used for solving the issue of energy consumption based on scheduling. Cloudsim simulator a toolkit for simulation is also discussed in brief.
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    Title: Study of Planar Inverted-F Antenna (PIFA) for Fourth Generation Wireless Devices
    Authors: Rajpreet Kaur, Surekha and Naveen Kumar
    Abstract:The substantial increase of wireless communication has lead to great demand of compact antenna designs and wide connectivity. An antenna covering maximum frequency bands with low profile structure is highly demandable in today’s wireless field. The Planar Inverted F Antenna (PIFA) is a perfect example that provides compact size with higher connectivity. The purpose of the paper is to give overview of various designs of Planar Inverted F Antennas used in 4G wireless communication. The paper also provides a conceptual study on various benefits of Planar Inverted F Antenna for 4G communication.
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    Title: A Survey on Scheduling Algorithm in Cloud Computing Environment
    Authors: Pardeep Singh and Rupinder Kaur
    Abstract:Cloud computing is the emerging technology in current day scenario. Cloud environment provider provides applications to their customer by virtualized resources dynamically. Cloud environment is constructed on base of virtualization, distributed computing and grid computing. Cloud computing is especially good for the businesses that are not able to afford the same amount of resources as the other bigger organizations are affording. Cloud environment allows consumers, the businesses and the other user to use applications, infrastructure and other resources without any installation. Cloud environment service provider’s one goals is to utilize the resources efficiently and consume maximum profit. This leads to Job scheduling as a main and challenging problem in cloud environment. This paper put forward several algorithms with parameters which impact cloud computing in positive as well as negative way and energy consumption is the major parameter which we consider in this paper. Today energy efficiency is one of the main problems arising in cloud environment due to issues either in assigning VM on server or in assigning tasks to VM.
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    Title: Image Enhancement Using Fuzzy Weber’s law Notation
    Authors: Dillip Ranjan Nayak
    Abstract:Image enhancement techniques are concerned with improving the quality of the digital images. This paper proposes a new approach for structure based enhancement of images with poor contrast using fuzzy morphology and Weber’s law notion. A modified membership function has been used to fuzzify the image matrix. The quality of the obtained images in the fuzzy Weber’s method is observed to be greatly enhanced.
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    Title: Improved Edge Detection Using Fuzzy Gaussian Morphology
    Authors: Dillip Ranjan Nayak
    Abstract: Fuzzy Gaussian morphology is a new approach for detecting edges in noisy images. Initially image is fuzzified with Gaussian membership function and then used morphology for edge detection Experimental results show superiority of the proposed method, as compared to the traditional morphology based edge detection method. The proposed method shows clear and continuous edges.
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    Title:To Study the Scope of Data Hiding In Ultrasound Video
    Authors: Raghvir Singh Grewal and Gaurav Deep
    Abstract: Information security has become the area of concern as a result of widespread use of communication medium over the internet. Video files are generally a collection of images. So most of the presented techniques on images and audio can be applied to video files too. The great advantages of video are the large amount of data that can be hidden inside and the fact that it is a moving stream of image. Medical records are extremely sensitive patient information and require uncompromising security during both storage and transmission. So we can use steganography in medical videos for storing secret data. In this paper we have reviewed ultrasound technology and its scope in steganography for hiding data in it. We have also explained some steganographic techniques which can be used to embed data in video files.
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    Title: MRI Medical Image and Steganography
    Authors: Gurinder Singh and Gaurav Deep
    Abstract:In this paper we present the working and functions of Magnetic Resonance. MRIs are widely used in the medical field to show the inner parts of human body. MRI tells us about the defects in body. These medical records contain extremely sensitive information about the patient which should not be compromised. Image steganography is used to hide the sensitive patient information into the carrier medical image to ensure confidentiality. Using steganography we can reduce the overhead of paperwork to record the patient information because this technique embeds the information in image. We review various steganography techniques which were previously used in medical field.
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    Title: The Techniques of Wireless Sensor Network in Improve the Energy Saving Clustering with Low Energy Adaptive Cluster Hierarchy Protocol
    Authors: Avininder Singh and Lekh Raj
    Abstract:The conceptual framework in this techniques we have a propose of routing protocol algorithm for energy saving cluster in the area of wireless sensor networks is individual of the rising and fast mounting fields in the technical world. This has brought about rising low cost, low-power and multi-function antenna nodes. The major fact that antenna nodes run out of energy speedily has been an issue and many energy competent routing protocols have been proposed to explain this problem and protect the life of the network. This is the basis why routing techniques in wireless sensor network focus generally on the accomplishment of power saving.
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    Title:A Review On Secure the Data from Attackers in MapReduce Systems Using Honeypots
    Authors: Surabhi Soni and Gaurav Goel
    Abstract: Cloud computing is an important paradigm in terms of computing in the field of computer science. Nowadays, many research institutions and IT industries are stored their data on the cloud. On the other hand the controllers/owners are worried about their data that is stored on the cloud which is not secure. By using and handling the Honeypots for some months, is the way to access the security of the cloud. The collection of data from Honeypots indicates that cloud environment is insecure. Here, a software framework MapReduce System that is capable for data processing is described which is used in Hadoop and can analysis the large datasets. To secure data, encrypting the data before transfering to the cloud is not the right way to Map-Reduce calculations because some data analysis jobs are explained in Map-Reduce environment by usage some computer languages such as Java and homomorphic encoded techniques are not applicable for big data. In this paper, to secure the data from attackers who are trying to access the data in an unauthorized way in MapReduce Systems is a big challenge. To overcome this challenge, Honeypots are spread over the data which is only accessed by the attackers and/or unauthorized users but not by authorized MapReduce jobs. The analysis indicates that the detection of unauthorized data access with satisfactory performance could be found in MapReduce based cloud environments.
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    Medicine Neural Networks Control Mind of Memory in Image Processing (Men-Net-Mind)A
    Authors: Prof P.Senthil
    Abstract: Medical image processing is developing recently due to its wide applications. An efficient MRI image segmentation is needed at present. In this paper, MRI Brain segmentation is done by Semi supervised learning which does not require pathology modeling and, thus, allows high degree of automation. In abnormality detection, a vector is characterized as anomalous if it does not comply with the probability distribution obtained from normal data. The estimation of the probability density function, however, is usually not feasible due to large data dimensionality. In order to overcome this challenge, we treat every image as a network of locally coherent image partitions (overlapping blocks). We formulate and maximize a strictly concave likelihood function estimating abnormality for each partition and fuse the local estimates into a globally optimal estimate that satisfies the consistency constraints, based on a distributed estimation algorithm. After this features are extracted by Gray-Level Co-occurrence Matrices (GLCM) algorithm and those features are given to Particle Spam Optimization (PSO) and finally classification is done by using Library Support Vector Machine (LIBSVM).Thus results are evaluated and proved its efficiency using accuracy.
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    Title:Digital Forensics method to analyze various data hiding spaces in NTFS file system
    Authors:Tejpal Sharma and Harleen Kaur Sahota
    Abstract: NTFS is a file system which restores and manages the important data. It is a common file system in Windows Operating System. A suspect hides the data in these files so that they are not accessible to anyone. In this paper a technique is proposed which will be helpful to analyze the storage media having NTFS file system. In this we will check the hard disk for the hidden data in the boot sector and copy of boot sector and also to analyze the slack space on the disk for hidden data. And, this will also check here for the possibility of the hidden data in the boot sector file of the partition and analysis of deleted files. It will help in cyber crime cases to collect the evidence and solve the cases.
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    Title: Fingerprint Recognition with Identical Twins using PFCM Algorithm
    Authors: B. Lakshmi Priya and Dr. M. Pushpa Rani
    Abstract: In biometric system, the fingerprint Recognition with identical twins is a challenging task due to the closest genetics based relationship and therefore the maximum similarity between fingerprints is expected to be found among identical twins. In this Paper, we proposed a method for fingerprint image segmentation based on possibilistic fuzzy c-means (PFCM) algorithm. In fingerprint recognition system, fingerprint segmentation is an important step. PFCM is a hybridization of possibilistic c-means clustering (PCM) and fuzzy c-means clustering (FCM) algorithm. PFCM overcomes the noise sensitivity defect in FCM and coincident cluster problem in PCM. PFCM was used to generate an initial contour curve for level set method. PFCM algorithm is used to compute the fuzzy membership values of each pixel. Based on the above fuzzy membership values edge indicator function is redefined. By using the edge indicator function fingerprint segmentation was performed to extract the required regions for advance processing. Experimental results of proposed method showed significant improvement in the evolution of the automatic fingerprint verification system can successfully distinguish identical twins though with a slightly lower accuracy than non-twins.
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    Title: A Review on Automatic License Plate Recognition Methods
    Authors:Sandeep Singh and Dr.Bikrampal Kaur
    Abstract:The automatic license plate recognition (ALRP) systems are the systems designed for the license plate recognition in order to recognize the number of the vehicle by localizing and optically recognizing the character printed over the license plate. There are several approaches, which have been already proposed for the ALPR systems with the higher accuracy. Most of the ALPR systems have been found working on the basis of the spatial constraint based methods, where the license plate location is determined by the centrally weighted or specific region analysis based methods which facilitates the higher accuracy but in the case of strategically placed cameras. There are several other cases, such as road surveillance cameras, where it is entirely not possible to implement the camera in such strategically situated manner to result with higher accuracy. In this paper, we have discussed the solution for the road surveillance cameras, where the higher variety of the vehicular movement can be found and tracked. It becomes very critical for the proposed model to localize the vehicular regions and the number plate regions from the detected vehicular regions. The proposed model is expected to solve the problem of higher accuracy and precision while detecting the vehicular objects in the real-time systems.
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    Title: Novel stratification of uterus region for prior stage treatment based on severity level
    Authors: Dr. K.Kavitha
    Abstract: Cervical cancer, one of the most common cancers affecting women worldwide and the most common in developing countries can be cured in almost all patients, if detected and treated in time. In this research work, we predict the uterus condition and provide early stage treatment to that patient based on extracted features and classification method. This method of feature extraction and classification will provide better treatment at early stage of uterus cancer. More number of irrelevant features in this prediction may cause misclassified result. To prevent this misclassification, a novel feature selection method is used to predict the best attribute selection from the overall feature data. This methodology will reduce the prediction error rate and improve its performance rate.
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    Title: A Review on image reconstruction techniques using the regression models with fitness testing
    Authors: Ishu Garg and Dr. Bikrampal Kaur
    Abstract: The image reconstruction is gaining the popularity over the years. The image reconstruction methods have found their establishments in many real-time applications starting from space imaging to medical imaging. The image reconstruction reduces the transmission effort for the visual data over the Internet. Also the image reconstruction methods are used to recover the lost imagery data over the IT storage resources. The storage recovery takes the leap when it requires to recover the more critical data with higher accuracy and precision. The higher accuracy in the image reconstruction requires the fitness testing along with over the regression based reconstruction model. The regression includes the various rounds of reconstruction by testing the various types of fitness of the solution. The fittest solution or the saturated points are returned as the final solution, which can be further improved by the pixel recovery approaches. In this paper, the various and several techniques for the image reconstruction has been reviewed and evaluated for the resulting accuracy. The shortcomings and pitfalls of the existing models have been noticed in this paper. The proposed solutions based upon the matrix optimization and fitness evaluation would be proposed to mitigate the pitfalls of existing models to overcome the performance issues. The proposed solution is expected to resolve the performance issues related to the existing model which would be measured by the error rate, reconstruction accuracy and elapsed time.
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    Title:A Review over the Optimal Vulnerability Detection Methods
    Authors: Mohit Kumar and Sachin Majithia
    Abstract: Web applications are the most widespread and extensive platform for the delivery of services over the Internet. Web applications have become victim for the stealing of source code and for breeching of the integrity of the data. As a result of which the web developer requires hold up or assistance for identification and detection of susceptible code due to the restricted availability of resources and time. The major difficulty that is usually faced by the web developer is choosing and detection of an appropriate vulnerability detection tool. The available tools are restricted in the terms of detection approach. This paper reviewed the different types of vulnerabilities categorized by OWASP report and also the comparison is done on the basis of reviewed carried out.
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    Title: A Review on the Image Forgery Detection Methods
    Authors: Pahulpreet Kaur and Dr. Bikrampal Kau
    Abstract: The Image Forgery detection systems are mostly based upon the two level analysis to find the copy paste forgery. Various feature descriptors have been used after the image segmentation in the patches in the first stage. The existing model has used to EM clustering in the second level to revaluate the copy move forgery again. The most effective scheme for image forgery detection has combined the EM-segmentation with SIFT matching points to achieve the higher accuracy in terms of forgery detection. The popular models have utilized the clustering techniques along with the probabilistic or non- probabilistic classifiers over the given image data. Also the difference of Guassian, laplace of Guassian, EM, K-Means etc has been utilized in the image forgery detection models. The existing scheme has been found complex in the time domain as they take longer time to evaluate and detect the forgery points along with negation of less accurate due to use of inefficient image segmentation techniques. The random extraction for the adaptive clustering of the image data produces the less efficient results on the same image, which makes the system inefficient in terms of accuracy. The strong feature descriptors with multi- level forgery verification can play the vital role in determining the forgery regions with higher accuracy with low elapsed time.
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    Title: Multi-level authentication for Internet of Things for Secure healthcare network establishment
    Authors: Abhishek Sinha and Mrs.Chander Prabha
    Abstract: Cloud based healthcare monitoring sensor networks (C-HMSN) consist of a number of wireless nodes connected to each other using wireless connections. Because these nodes are wireless connected with each other and base stations, they are highly prone to the hacking attacks. HMSNs are used to sense various environmental or other parameters which can be used to predict natural hazards, climatic changes or other types of data analysis. During the periods when the HMSN nodes are in working condition, they need secure cryptographic keys for secure propagation of the sensitive information. Efficient key management and distribution scheme play an important role for the data security in HMSNs. Existing cryptographic key management and distribution technique usually consume higher amount of energy and put larger computational overheads on Wireless Sensor Nodes. The cryptographic keys are used on different communication levels of HMSN communications i.e. neighbour nodes, cluster heads and base stations. An effective corporate key management and distribution policy is required to maintain the security of the wireless sensor networks. This research project presents a improved key management architecture, called SECURE KEY EXCHANGE for the HMSNs, to enable comprehensive, trustworthy, user-verifiable, and cost-effective key management. SECURE KEY EXCHANGE protects the entire life cycle of cryptographic keys. In particular, SECURE KEY EXCHANGE allows only authorized applications and/or users to use the keys. Using simple devices, administrators can remotely issue authenticated commands to SECURE KEY EXCHANGE and verify system output. In this paper, we will make the “Keep it Simple and Secure” corporate key management technique adaptable for the HMSNs by making it energy efficient. In addition, it also has to be improved to work with HMSN nodes, which means it must use less computational power of the HMSN. The wireless sensor node should not use more computational power and battery of wireless sensor node, which will also increase the life of wireless sensor network
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    Title: Analysis of CT Liver Images for Tumor Diagnosis Based on PNN Classifier and Clustering Model
    Authors: Divya.v
    Abstract:This project presents the classification of liver images to detect the stages using unsupervised classifier and abnormal detection through spatial Fuzzy clustering algorithm. Here probabilistic neural network with radial basis function will be used for Stage classification. The detection of the liver tumor is a challenging problem, due to the structure of the tumor cells. This project presents a segmentation method of Spatial Fuzzy C-Mean clustering algorithm, for segmenting computed tomographic images to detect the liver tumor in its early stages. The neural network will be used to classify the stages of liver tumor into benign, malignant or normal. The manual analysis of the sputum samples is time consuming, inaccurate and requires intensive trained person to avoid diagnostic errors. The segmentation results will be used as a base for a Computer Aided Diagnosis (CAD) system for early detection of liver tumor which will improves the chances of survival for the patient. Here non subsampled wavelet transform is used to decompose the image. The simulated result shows that the Fuzzy based segmentation results are more accurate and reliable than thresholding and clustering methods in all cases. Probabilistic Neural Network with image and data processing techniques was employed to implement an automated Liver Tumor classification. Decision making was performed in two stages: feature extraction using the four level wavelet decomposition followed by Haralick features and the classification using probabilistic neural network (PNN). The Probabilistic Neural Network gives fast and accurate classification than other neural networks and it is a promising tool for classification of the tumors.
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    Title: Big Data Practices based Semantic Ranking for Online Entity Listings
    Authors: Manpreet Kaur and Pravneet Kaur
    Abstract: This project presents the classification of liver images to detect the stages using unsupervised classifier and abnormal detection through spatial Fuzzy clustering algorithm. Here probabilistic neural network with radial basis function will be used for Stage classification. The detection of the liver tumor is a challenging problem, due to the structure of the tumor cells. This project presents a segmentation method of Spatial Fuzzy C-Mean clustering algorithm, for segmenting computed tomographic images to detect the liver tumor in its early stages. The neural network will be used to classify the stages of liver tumor into benign, malignant or normal. The manual analysis of the sputum samples is time consuming, inaccurate and requires intensive trained person to avoid diagnostic errors. The segmentation results will be used as a base for a Computer Aided Diagnosis (CAD) system for early detection of liver tumor which will improves the chances of survival for the patient. Here non subsampled wavelet transform is used to decompose the image. The simulated result shows that the Fuzzy based segmentation results are more accurate and reliable than thresholding and clustering methods in all cases. Probabilistic Neural Network with image and data processing techniques was employed to implement an automated Liver Tumor classification. Decision making was performed in two stages: feature extraction using the four level wavelet decomposition followed by Haralick features and the classification using probabilistic neural network (PNN). The Probabilistic Neural Network gives fast and accurate classification than other neural networks and it is a promising tool for classification of the tumors.
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    Title: Multi-Utility GPS Android Application
    Authors: Smriti Priyadarshani, Pooja Rani and Anushree Kanungo
    Abstract: In recent years the mobile has become a valuable part of the human beings. It is necessary for human beings to have a powerful device which will deliver all the facilities. Android provide such functionality which enables the developers to design such applications which will make a simple mobile to smart one. The proposed system provides various facilities to the users. It allows the user to set alarm based on location, which bangs when the location is reached. It also gives the reminder about the pre-visited location. It sends an SOS message in an emergency situation. It allows user to share his location. The application allows the user to request the current location of the person from his/her contact list. Moreover, an automated message is sent to the default recipients if SOS message is configured. The application notifies us about the current location of the person from the contact list. The user can also share his/her location to the persons present in the contact list. The proposed android application titled Multi-utility GPS Android Application uses location based services from Google API for the various purposes like setting location based alarm, reminding the pre-visited location, sending SOS messages along with the location. These features are helpful for those who are new to a location, for those who travel on a regular basis. These features are beneficial in relation with the women security concerns.
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    Title: Extraction of Feature and Detection of Abnormalities in Brain Tumor
    Authors: P.V.Rohini and J.Regan
    Abstract: Feature extraction is process visual content from the image. The feature extraction is the process to represent raw image in its reduced form to facilitate decision making such as classifications. This method has tried to set the problem of classification MRI brain images by creating a strong and more accurate classifier which can do. Like the expert of medical practitioners. The purpose of the paper is to present a classification and feature extraction. This method includes the intensity, Texture, Shape based Features and classifies the tumour. The research is performed on 140 tumour contained brain MRI images from the internet brain segmentation repository. Using the morphological operator feature selection method the proposed method is more efficient in analysis of high classification and accuracy to detect the tumour area in the brain image.
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    Title: Improvising Health Care in Social Media Using Intellectual Network
    Authors: I. Sahaya Jasmine Jenifer and Dr. K .Kavitha
    Abstract:Extracting knowledge from social media gives us several usage in various fields. In the field of biomedical and healthcare, extorting information from social forum is providing number of benefits such as knowledge about the latest technology, updates of current situation in medical field etc. In the implemented system, every organization maintains their own social forum, in which user/patient can post their views about the medicine and view other patient’s posts. These are collected and sentiment analysis is performed on them. The result of the analysis focuses on positive and negative opinion about the medicine, as well as the side effects of treatment. A novel network-based approach is used for modeling user/patients’ forum interactions and employed a network partitioning technique based on optimizing a quality measure. This allowed us to establish consumer opinion and identify influential user/patients within the recovered modules in the order obtained from both word-frequency data and network-based properties
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    Title: A Review on Adaptive Intrusion Detection Systems Based On Data Mining Approach
    Authors: Jaspreet Singh and Sachin Majithia
    Abstract:With the increasing network day by day, there is a threat to security of data. Security with the growth of data and networks, there is decrease in security feature and has become the greatest challenge of today’s scenario. The cryptographic mechanisms & algorithms were not enough to maintain the data security or secure the data network. Therefore a phenomenon named IDS came into existence. The malicious network traffic cannot be detected by a firewall. So that intrusion detection systems are used to detect such network traffic and different attacks. Mostly the IDS are created by combination of different machine learning techniques. There are fewer studies which focus on how to extract more representative features and different attacks detection.
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    Title:A Review on the Hybrid Approach for Data Visualization in Big Data
    Authors: Astha Gupta and Sachin Majithia
    Abstract: The big data concept begins from the massive amounts of the data after the evaluation of the data warehousing. The big data practices are generally directed to resolve the issues related to the very large data volumes of raw or unstructured data. The data structuring and visualization are the most required techniques over the bigger amount of data available in the various domains. There are several data structuring and visualization techniques which can be interpret, organize, inspect and scan the available data. Specifically, the data visualization techniques are associated with the understanding of the available data to plan the structuring of data as well as the analysis of the given databases. In this paper, the new visualization techniques based upon the concept of Nano-Cubes has been presented, which de-integrate the data into the smaller chunks to understand it in the much better and analytical manner. The accuracy of the proposed model would be measured in the form of accuracy, precision and elapsed time.
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    Title: Binary Image Reconstruction Using the Adaptive Hybrid Mechanism with Swarm Optimization
    Authors: Nirlap kaur and Sumanpreet kaur
    Abstract: The image reconstruction is the procedure to reproduce the image from the image contents provided in the form of projections or damaged image matrix. The image matrix damages are produced due to many internal or external factors which cause the image degradation. The image compression is also one the primary reasons behind the image reconstruction. The image reconstruction from the projection data is incorporated using the iterative reconstruction mechanisms. The data matrix processing and matrix regeneration is the iterative process to regenerate the matrix by estimating the data values from the provided projections. The projection data in obtained in the multi-dimensional format which includes the N-D projection data obtained from the various types of images. The proposed model is aimed at solving the problem of the binary matrix reconstruction by estimating the pixel values from the projection data. The swarm optimization techniques would be incorporated to effectively regenerate the image matrix. The proposed model design has been aimed at improving the performance of the existing models by eliminating the shortcomings of the existing schemes.
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    Title:Anti-Collusion Data Sharing Schema For Dynamic Groups in Cloud Computing Environment
    Authors: M. Usha and Dr. K. Kavitha
    Abstract: Cloud Computing now a day is increasing over the last few years due to its attractive features like scalability, flexibility, low cost and easy start up for the beginners. It provides effective security of the data and information in the cloud storage. The data Distribution in many users accessing for dynamic groups preserves data and its identity and privacy from an untrusted cloud and grants access to frequent change of membership. The group manager can revoke any number of users from the dynamic group. But there is possible for collusion when the revoked user can try to access the cloud data without the knowledge of the group manager. In order to stop collusion, this paper proposes a set of schema to make it possible. Primarily, a safe key distribution in a secure communication channel and the users can get the private key from the group manager. Along with it, the group user can categorize their fine-grained access control as creator, reader and writer in the system. Also, the revoked user of the group cannot get data and information from the untrusted cloud. Finally, this paper uses an effective polynomial function for performing revocation of the group users.
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    Title:CRS Model Design for Personal Health Records Protection with BIG DATA Analysis
    Authors: Gagana H.S and Dr. K.Thippeswamy
    Abstract: Big Data is the hottest trend in the IT technology, the capacity of the data has increased the terabytes to Zeta-byte, In healthcare field huge amount of data are produced in every days. This data is maintaining and protecting are complex problems. Even each general hospital is getting a large amounts of information stored and managed. In this case, there are very few studies on the methods to utilize the clinical information and medical research details efficiently and effectively. For the efficient analysis and utilization of medical BIG DATA stored in eRecord i.e. EMR (Electronic medical record) data. In this regard, in this paper, medical information, medication information, medical test results and allergy information were implemented up to Entry level using Clinical Document Architecture (CDA), the international medical standards, Health level 7 (HL7) and CRS (Care Record Summary) integrating these information was created reliable and Securable Electronic medical Record are Implemented. This paper mainly refers to patients medical eRecords are sharable between hospitals.
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    Title: Review on Co-operative Techniques for Energy Efficient Routing
    Authors: Reena and Dr. Shashi B. Rana
    Abstract: WSN is an emerging technology which consists of a large number of sensor nodes. Sensor nodes are having the capability of sensing, computing and communicating the data through the network to the base station. Routing is important for sending the data from sensor nodes to the Base Station (BS). So for any sensing application to be accomplished the data must be transmitted to the base station. In this paper, we present various types of routing issues of the WSN. In the other section of this paper, we have highlighted the various Co-operative techniques which are based on hierarchal routing. Further, we have extensively surveyed the most recent work done related to Co-operative MIMO and MISO techniques. The overall purpose of all these schemes is to enhance the network lifetime of WSN. It is evident from the various experimental studies that both these techniques (MISO & MIMO) not only enhance the network lifetime but also brings load balancing in the network. In the last section of this paper, we have highlighted the various drawbacks of these techniques in hierarchical routing protocols, and by considering all these drawbacks we can extend this research scheme for large area sensing applications.
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    Title: Performance Analysis of VIJANA Cryptography With Stream Ciphers
    Authors:M. Janaki
    Abstract: Internet allows rapid sharing of the data across the globe. The important security issue is data security when it deals with the sensitive data. Hence strong security mechanism is needed to protect sensitive information. Cryptography is proved to be a strong mechanism to secure the confidential data. It is the art of disguising sensitive data in order to share it through the network. Several encipher and decipher algorithms are available today, everything is having its own strength and weakness. This article sets out to analyse the performance of a noval enchipherment technique known as VIJANA cryptography. This algorithm is compared with the stream ciphers that include RC4, IDEA and Spritz. Encipher time, Decipher time and Execution time are the metrics taken for comparison. The comparative results are tabulated and visualized as graphs.
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    Title: Robust Image Segmentation for Removal of Distortion with Reconstruction
    Authors:Mr. ANAND M
    Abstract: A new algorithm is proposed for removing distortion from digital images. The challenge is to fill in the hole that is left behind in a visually plausible way and reconstruction techniques for filling in small image gaps. This paper presents a novel and efficient algorithm that combines the advantages. We propose a best-first algorithm in which the confidence in the synthesized pixel values is propagated in a manner similar to the propagation of information in reconstruction. The actual color values are computed. Reconstruction, the technique of modifying an image in an undetectable form, is as ancient as art itself. The goals and applications of reconstruction are numerous, from the restoration of damaged paintings and photographs to the removal/replacement of selected objects. In this paper, we introduce a novel algorithm for digital reconstruction of still images that attempts to replicate the basic techniques used by professional restorators. After the user selects the regions to be restored, the algorithm automatically fills-in these regions with information surrounding them. The fill-in is done in such a way that isophote lines arriving at the regions’ boundaries are completed inside. In contrast with previous approaches, the technique here introduced does not require the user to specify where the novel information comes from. This is automatically done (and in a fast way), thereby allowing to simultaneously fill-in numerous regions containing completely different structures and surrounding backgrounds. In addition, no limitations are imposed on the topology of the region to be inpainted. Applications of this technique include the restoration of old photographs and damaged film; removal of superimposed text like dates, subtitles, or publicity; and the removal of entire objects from the image like microphones or wires in special effects.
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