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ijmcs  IJMCS

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

  • For More Detail Click Here
  • http://www.acharya.ac.in/Techman_2014.pdf

    Volume-2 Issue-5 (October 2014)
    Title: A Novel Procedure of extracting Small Objects from diatom images
    Authors: Dr. V S Giridhar Akula and Dr Murugan S
    Abstract: This paper highlights two novel methods based on watershed transform, which includes small object detection and data classification. The proposed method uses efficient noise removal procedure to remove noise from images and then applies watershed transforms to extract small objects which highlight simplicity without loss of efficiency. Results indicate that the proposed method performs better in extracting contours of small objects with low contrast. Results are compared with the existing methods and shows that the proposed method is feasible.
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    Title: Demarcating Happy Affect Identification in Faces Using a Mathematical Model
    Authors: Dr. Nachamai M and Pranti Dutta
    Abstract: An exploratory analysis of mathematics behind face affect recognition is done. This paper discusses a clear approach of coherence between eigenvalues and eigenfaces, with an effective method for happy affect identification. The generation of eigenfaces for a given image based on the eigenvalue is inevitably, the mirror process of finding eigenvalues for a matrix. The identification of happy affect in the recognized face is attempted with a mathematical model Principal Component Analysis (PCA). The image set used is sampled for every eigenvalue in the image matrix. The code for deriving eigenfaces and affect identification is written in MATLAB. An extensive experiment was conducted on the Japanese Female Facial Expression (JAFFE) database with 213 images. The results demonstrate the efficacy behind the methodological application of PCA for happy affect recognition. The success rate of 91.8% on identifying happy faces proves the strength of the model deployed in this research work.
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    Title: Enhancement of Exploring Malicious Vehicle in Urban Network with Trust Authority
    Authors: Mr. Mohan Jaynarayan Pande and Prof.Anil Rao
    Abstract: In Urban network, where seclusion of van, largely the place of automobile is tremendously not crackled, anonymous substantiation of vehicles is unfeasible to argue or distinction. first, couple of official individuality messages signed by the correspondent RSU inside the same given period of time that with reference to each other for provisional purpose are recognizable in order that they can be used for breakthrough; Nextly Road-Side Unit signatures on messages are signer are unusual so that the RSU place identity data is hidden from the resulted official message. In this paper, we mentioned a straightforward Sybil attack occurs in the network using the trajectories of vehicle for identification of the node while at rest maintaining the node location retreat in the network. When a vehicle in the vehicular network co-related a Road-Side Unit (RSU), it with dynamism demands an permission identity message from the RSU as the substantiation identity of the vehicle in the present RSU region. A malicious node (attacker in network) who tries to forging multiple same bogus identities of the node accessible in the network can without difficulty launch an attack called Sybil attack, in advance a suspiciously large influence. More principally, we design a location-hidden identity approved message discovery method for two objectives: With the lack of technique, official messages from the vehicle used for long-term identification are refusing so that at the challenging road side unit its authorization is used as identity of vehicle. With this order on the identity format, vehicles keep its position privacy as the identification by taking all the series of progression of authorized message.
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    Title: An Approach for Identification of a Speech Template in Presence of Emotion in a Multimodal Approach
    Authors: Manas Kumar Choudhury and Dr.Y.Srinivas
    Abstract: The present article describes an approach for the verification of biometric traits in the presence of Emotion speech signal. This paper is based upon the utilization of Generalized Gamma Mixture Model (GGMM) together with clustering technique. In order to evaluate the performance of the model, the face is considered from the bench mark dataset of YALE and for speech, fingerprint template synthetic dataset are being considered. The efficiency is evaluated using metric like Acceptance Rate (AR), Equal Error Rate (EER), FAR (False Acceptance Rate), FRR (False Rejection Rate).
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    Title: Smartphone as a Real-time and Participatory Data Collection Tool for Civil Engineers
    Authors: Arabinda Sharma and Dheeraj Gupta
    Abstract: Smartphones have advanced computing capability and connectivity equipped with the features of a touchscreen computer, including web browsing, Wi-Fi, 3rd-party apps, motion sensor digital camera, and GPS navigation unit. It has enables field data collection, uploading of gathered data to a server in real time and in participatory manner. The data collected through smart mobile devices served as a basis for updating of database that is being used for real time analysis and which in turn helps in decision making. This has become a pervasive phenomenon due to reduced back-office assignments, errors in processing of information collected in paper format, time and cost effectiveness. It has opens plethora of opportunities in geo- environmental, civil engineering and many other application areas. Keeping in view the above facts, the present paper first aims to highlight the potential civil engineering areas/projects wherein smart-phone can play important role in improving the accuracy and efficiency. Next the paper presents some civil engineering case studies with the use of smartphone. Although the of these case studies are prototypes and the results are preliminary only, it indicates the vast possibilities of using smart-phone as a valuable tool for real-time data collection and analysis for many engineering projects in participatory manner.
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    Title: Review paper on Minimization of power dissipation, area and off-set voltage in CMOS dynamic Comparator for high speed ADCs
    Authors: Murari Kumar and Manish Singhal
    Abstract: This paper presents the comparison between the different comparator. The comparison parameters are power dissipation, offset voltage, slew rate, delay and noise of the circuit. With the help of this paper we compare the different comparators very easily. The comparators are implemented in 90nm cadence virtuoso analogy environment technology.
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    Title: Cluster Formulation Using Hybrid Approach to Reduce the Outlier
    Authors: Nancy Lekhi and Manish Mahajan
    Abstract: The Outlier detection is main focus area of research in data mining where outlier is a mismatched data in dataset with respect to the other available data. In existing approaches the outlier detection done mostly on numeric dataset. The Proposed Method works on numeric data set as well as text and date/time dataset. The proposed method uses hybrid approach to formulate the clusters. The number of outlier can only reduce by improving the cluster formulation method. The proposed method uses two data mining techniques for cluster formulation i.e. weighted k-mean and neural network where weighted k-mean is the Partitioning clustering method that can apply on text and date/time data set as well as numeric data set. Weighted k-mean assign the weights to each element in dataset. The output of weighted k-mean becomes the input for neural network where the neural network is the classification technique of data mining. The neural network test the cluster formulated by weighted k-mean to ensure that the clusters formulated by weighted k-mean are group accordingly. There is lots of outlier detection methods present in data mining. The proposed method use Integrating Semantic Knowledge (SOF) for outlier detection. This method detects the semantic outlier where the semantic outlier is a data point that behaves differently with other elements within the same class. The main motive of this research work is to reduce the number of outliers by improving the cluster formulation methods so that outlier rate reduces and also decrease the mean square error and improve the accuracy.
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    Title: Connecting Heterogeneous Cloud Storages through Windows Communication Foundation
    Authors: Parvinder Kaur and Manish Mahajan
    Abstract: Many organizations provide computing resources or services to the client like hardware, software, storage etc. Storage is one of important service that is popular and commonly used today and it provides storage space online to store the data. Service providers give a storage space to consumers on the basis of renting criteria with a trust of high and powerful security. Consumer and organization uses these storages to secure own personal data. There are many reasons come across that causes to move data from one place to other. Some of them are: reconstruction of storage, backup, new technologies, security etc. So, data migration, data transfer between different cloud storages, often requires. Achieving mechanism of Data migration between cloud storages is very difficult as they work on various protocols with their different data format. As there is no standard format of cloud storage so all cloud storage's format of storing data is depend upon its corresponding cloud vendors. The main vision of this research work is to provide an intermediate service that provides a common way to move the data between homogeneous and heterogeneous cloud storages. This intermediate service is a two way strategy that built in a SOA technology called WCF, which helps the clients, organizations to move data between same and different cloud storages (Window Azure and Go Daddy mainly used in this research work).
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    Title: K-Medoids clustering, Redundancy Reduction Ant Colony Algorithm in Solving Multiple Traveling Salesman Problems
    Authors: S. Ravichandran and Dr. M. Umamaheswari
    Abstract: Multiple travelling salesman problem (MTSP) is a typical computationally complex combinatorial optimization problem, which is an extension of the famous travelling salesman problem (TSP). Multiple traveling salesman problem uses the shortest total route as an optimization criteria, has huge application in both theoretical research and industry. In this paper Multiple Travelling Salesman problem uses a methodology of clustering the given cities depending upon the number of sales man and each cluster is allotted to a salesman. “k-medoids clustering” algorithm which is more robust or noise and outliers have been used for easy clustering of the cities. After Clustering an optimized route is generated for each salesman in his allotted cluster. In this way the MTSP has been converted to TSP which is simple in computation compared to TSP. Now every cluster was again solved as a TSP by applying Ant colony Algorithm Optimization (ACO) by redundancy reduction Known as Redundancy Reduction Ant colony Optimization (RRACO) algorithm which eliminates the redundancy and reduce the computation time. Thus it will be an efficient method to determine the optimal distance value and time optimization.
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    Title: Analysis of Berger Code Based Fault Tolerant Techniques for Embedded System
    Authors: N.Ramkumar and Boopathy.S
    Abstract: With continued scaling of silicon process technology, producing reliable electronic components in extremely denser technologies pose a challenge. Further, the systems fabricated in deep sub-micron technology are prone to intermittent or transient faults, causing unidirectional errors, upon exposure to ionizing radiations during system operation. The ability to operate in the intended manner even in the presence of faults is an important objective of all electronic systems. In order to achieve fault-tolerance, each module of the system must be fault-tolerant by possessing run-time (or online) fault detection capabilities. Totally Self-checking (TSC) circuits permit online detection of hardware faults. The objective of this project is to analyze the area (resource utilization), speed and power consumption for n bit Look-Up Table (LUT) implementation with and without fault detection capability using Berger technique on Xilinx FPGA. The Berger code is the least redundant systematic code available for detecting all single and multi-bit unidirectional errors. This project is proposed to find the fault in 4, 8, 16, 32 bits LUT. The fault will be detected by Berger checker architecture.
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    Title: A Complete Analysis on Modified Clonal Classifier with MACA for Addressing Various Problems in Bioinformatics
    Authors: P.Kiran Sree and SSSN Usha Devi N
    Abstract: The modified clonal algorithm with MACA has gained importance in addressing various logical problems in bioinformatics. This classifier is applied to predict the protein coding regions, splice site junctions, secondary protein structure, promoter prediction and many more. A common frame work of AIS-MACA is used to address all these problems. All the addressed problems could register an improvement in the prediction accuracy, specificity and sensitivity. This is because the classifier is trained to use very less features to predict the class of the problems. This paper gives a complete analysis of AIS-MACA for addressing major problems in bioinformatics.
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    Title: Enhanced Authetication Scheme Using Image Fuzion and Multishared Cryptography
    Authors: Anil Boyal, Amit Limba and Aniket Suman
    Abstract: As the technology is growing rapidly the area of nanotechnology has become an important research during the last ten-years stage, needing payment to scientific moves-forward in the discovery and development of fiction story materials with nothing like it electrics and mechanical qualities. CNT is such a material. Properties such as electrics and thermal conductivity have been of CNT possibly right for use in a wide range of fields such as medical substance, engineering, making, military and energy place for storing and distribution. This has led to CNT being researched meticulously; as such, this paper presents a general overview on the main qualities, making methods current state of the art and a discussion on future possible & unused quality applications of this material. Everywhere on earth business interest in carbon nanotubes (CNTs) is given picture of in a producing capacity that presently goes over limits several thousand tons per year. currently, the greater size CNT powders are made into company in different business products ranging from rechargeable electric units, automotive parts, and sporting goods to boat outer cover (of grain) and water apparatus for making liquid clean. Moves-forward in CNT putting-together, purification, and chemical adjustment are giving power united as complete thing of CNTs in thin-film electronics and large-area coatings. Although not yet making ready forcing mechanical power or electrics or thermal conductivities for many requests, CNT rough wools and bed liners already have making statement of undertaking operation for applications including higher degree capacitors, actuators, and lightweight electromagnetic shields.
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    Title: Performance Analysis of FBMC Prototype Filter under the Effect of Variable Parameters for Physical Layer Cognitive Radio
    Authors: Er.A.S Kang and Dr.Renu Vig2
    Abstract: In the present day world of wireless communication scenario, some spectrum bands are highly utilized while many remain moderately utilized or rarely occupied. The cognitive radio is a new paradigm to overcome the persisting problem of spectrum underutilization. Seeing the ever increasing demand of wireless applications, the radio spectrum is a valuable resource and in cognitive radio systems, trustworthy spectrum sensing techniques are required to avoid any harmful interference to the primary users. As cognitive radio has the capability to utilise the unused spectrum holes or white spaces so, there is a tremendous need to scan the large range of spectrum either for interference management or for primary receiver detection. Dynamic Spectrum Access techniques need to be implemented for the sake of better radio resource management and computational complexity analysis of multirate filter bank cognitive radio, where BER and Eb/No are the performance metrics or governing parameters to affect the system performance using polyphase filter bank. The present paper deals with the study of effect of variation of number of subchannels M at fix overlapping factor K of polyphase component of FBMC cognitive radio in terms of prototype filter length at Lp=KM+1.
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    Title: Role Based Access Control with Integrated Authentication to Prevent DDOS Attacks
    Authors: Ravneet Kaur and Manish Mahajan
    Abstract: Cloud computing is a model for enabling convenient, on-demand network to a shared pool of configurable computing resources that can be instantly provisioned and released with minimum management effort or service provider interaction. Access control has vital significance in cloud computing, where data files are stored in the cloud server. In current schemes, the cloud server typically needs to consult the backend authorization server, when processing access control request from data users. This will put a heavy burden on the authorization server, and therefore introduce Denial-of-Service attack on it. The results show that our scheme is quite improved, because it separates the authorization process from the access control process. By doing so, the burden on the authorization server is reduced, and the Denial-of-Service attacks on it during access control process are avoided. Also we have added the ontology concept with the RBAC to enhance the access control power.
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    Title: An efficient RSA based security for web Data with Attack Alert System
    Authors: Ankita Shrivastava and Anil Rao
    Abstract: There are several work is going on in the direction of securing client and server communication. The work is also going on to finding the possible threats in the direction of attack detection. The main attacks are content modification, visualization. Accessing information from such a webpage where proper permission is needed and if we access the data in an unauthorized way is also called Cross-Site scripting attacks. The flexibility of HTML techniques also flexible for the attackers which provide easy traceability. So in this paper we proposed RSA based communication system for web client and server communication. In our approach we have proposed RSA based security so that the data will be prevented from unauthorized access. In the case if the data is attacked then our hidden tag will alert the server for unauthorized access. Our framework suggested automated and manual processes both which help us to reducing the time of the data preprocessing. Our results show the effectiveness of our approach.
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    Title: Enhanced Bidirectional String Matching Algorithm
    Authors: Mohammad Aqiel and Ashu Gupta
    Abstract: In this paper we present Bidirectional exact string matching algorithm in detail. Bidirectional (BD) exact string matching (EPM) introduced a new idea to compare string with Selected Text Window (STW) of text string by using two pointers (right and left) simultaneously in searching phase. In preprocessing phase Bidirectional EPM algorithm improved the shift decision by comparing rightmost and mismatched character of Partial Text Window (PTW) to the left of string at same shift length. The time complexity of preprocessing phase of BD exact string matching is O(m) and searching phase takes O(mn/2). The proposed Bidirectional EPM algorithm is more efficient than the number of existing algorithms in many cases.
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    Title: Analysis and Modeling of an effective Anomaly Detection Techniques for Detecting Data Exfiltration of Network
    Authors:Arup Sarmah, Arabindu Dey and Chandan Jyoti Kumar
    Abstract: Data Exfiltration is the unauthorized data transfer from a computer. The primary focus of any data Exfiltration detection technique is the ability to make a distinction between legitimate and malicious information communication. Anomaly detection refers to the problem of finding patterns in data that do not conform to expected behaviour. In this paper, we have presented a novel behaviour based model for detecting data-Exfiltration attacks [1]. Uniqueness in our approach is in combining the KDE based technique with correlation coefficient method. In this approach we have used both system and network parameters and have shown the need for carrying out correlation based on these parameters to detect data Exfiltration. Data collection mechanisms for each host are developed and our approach is validated by carrying out analysis of results. We presented the analysis of results that bring out the efficacy of our model.
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