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Accepted Papers

    PERFORMANCE ANALYSIS OF CONGESTION CONTROL TECHNIQUES ADTCP AND IMPROVED-ADTCP: FOR IMPROVING TCP PERFORMANCE OVER AD-HOC NETWORKS.
    Sreenivasa B.C1 and G.C. Bhanu Prakash2 ,
    1Associate Professor Department of Computer Science and Engineering Research Scholar, SAHE Uni-versity ,Tumkur
    2Professor Department of Computer Science and Engineering, SirMVisvesvarayaInstituteofTechnology-Bangalore,INDIA
    ABSTRACT
    Identifying the occurrence of congestion in a Mo-bile Ad-hoc Network (MANET) is a major task. The inbuilt congestion control techniques of existing Transmission Control Protocol (TCP) designed for wired networks do not handle the unique properties of shared wireless multi-hop link. There are several approaches proposed for detecting and overcoming the congestion in the mobile ad-hoc network. In this paper we present a Modified AD-hoc Transmission Control Protocol (IMPROVED-ADTCP) method where the receiver detects the probable current network status and transmits this information to the sender as feedback. The sender behavior is altered appropriately. The proposed technique is also compatible with standard TCP.
    KEYWORDS

    Congestion, TCP, Ad-hoc.

    UNSW-NB15 DATASET FEATURE SELECTION AND DATA VISUALIZATION
    V. Kanimozhi,School of Computing,Sathyabama Institute of Science & Technology, Chennai, India
    ABSTRACT
    Anomaly detection system in network, monitors and detects intrusions in the networking area, which forms the Network Intrusion Detection System (NIDS). The various network datasets are available in networking communications with relevant and irrelevant features, which drastically decreases the rate of intrusion detection and increases False Alarm Rate. The recently available network dataset is UNSW-NB15 dataset was created in 2015. The top significant features are proposed as feature selection for dimensionality reduction in order to obtain more accuracy in attack detection and to decrease False Alarm Rate. We apply a combination fusion of Random Forest Algorithm with Decision Tree Classifier using Anaconda3 (a free and open-source distribution of Python3) and package management system Miniconda (package manager) in which 45 features have been decreased to the strongest four features.
    KEYWORDS

    Data visualization; feature selection; intrusion detection; UNSW-NB15 Dataset

    FEATURE EXTRACTION AND AUTHENTICATION OF THE IRIS OF A HUMAN EYE
    Barsha Deka, Sharmistha Sarkar and Jyotismita Sarma Department of Electronics and Telecommunication, Royal School of Engineering and Technology, Assam
    ABSTRACT
    With the need for security systems going up, Iris recognition is emerging as one of the most important methods of biometrics-based identification systems. This paper discusses about iris recognition which is used to overcome some of the problem like to automate the recognition of the iris by reducing complexity and increasing algorithm speed. To derive a unique mapping, Iris recognition systems make use of the uniqueness of the iris patterns. Iris recognition system outperforms others because of its high accuracy. Three stages are followed while working with this iris system i.e. preprocessing, feature extraction and recognition stage. This paper presents an automated iris recognition system where overall computational match speed is reduced. The proposed method is tested with the CASIA database iris images, which consists of left and right eye set for the different human. The proposed method reduces the FAR to 15.6 percent and FRR to 14 percent.
    KEYWORDS

    Iris recognition, FAR, FRR.

    SEGMENTATION AND DETECT MOVING RGB OBJECT BASED ON KINECT
    Ahmed Mustafa Taha Alzbier, Han Cheng,Mohamed Tahir, Jiang Shan, Umer Syed Changchun University of Science and Technology, Changchun, China
    ABSTRACT
    As the present field of computer vision technology is growing up fast, the Image processing is most important in this field used to produce digital maps and satellite photos, which yields more accurate results. Kinect Capture the video frames using the video input function in MATLAB and Set the properties of the video object. Moving RGB object detection and segmentation is an important and fundamental topic in computer vision. Its applications can be found in a large number of engineering fields .However, object detection is defined as extracting the motion part of a video stream. Now in this paper to detection and segmentation RGB colour objects in real time we have to subtract the colour component of the gray scale image to extract the components in the frame image. And use a median filter to filter out noise. A median filter is more effective than convolution when the goal is to simultaneously reduce noise. However, the adaptive median filtering can handle impulse noise with probabilities even larger than these, and Convert the resulting gray scale image into a binary image. Remove all those pixels less than what you want, Label all the connected components in the image. And we do the image blob analysis get a set of properties for each labelled region. Generally, this paper is organized as follows. We describe our proposed algorithm for object colour detection and segmentation .The concept of the motion detection, background subtraction, segmentation. How to make the colour and segmentation followed by some experimental results and conclusions.
    KEYWORDS

    Computer Vision, Color Model, Median filter, Blob Analysis, Median filter, Kinect, Segmentation, Background Subtraction

    INTRINSIC AND EXTRINSIC VARYING EFFECTS ON PHOTOVOLTAIC SOLAR PANEL PARAMETERS FOR I-V AND P- V CURVES CHARACTERISTICS BY MATLAB/SIMULINK
    Burak Akin and Idriss Dagal Yildiz Technical University Istanbul, Turkey
    ABSTRACT
    The characteristics of PV solar panel for standalone system use will be studied based on manufacturer specifications in order to assure the adequate power required for the system normal operation. We examine in this paper different I-V and P-V curves based on the variation of environment and panel internal parameters effects. These studies are carrying further in order to give a success results to standalone maximum power point tracking to battery charge controller for the suburb or rural areas applications.
    KEYWORDS

    Photovoltaic solar panel, extrinsic-intrinsic effects, current-voltage, power-voltage curves behaviors and Matlab/Simulink

    IMPROVEMENT OF THE RECOGNITION OF RELATIONSHIPS IN SOCIAL NETWORKS USING COMPLEMENTARY GRAPH COLORING BASED ON CELLULAR AUTOMATA
    Mostafa Kashani, Saeid Gorgin1, SeyedVahab Shojaedini Department of Electrical Engineering and Information Technology, Iranian Research Organization for Science and Technology (IROST), Tehran, Iran
    ABSTRACT
    Each social network can be modeled as a graph G = [V, E] in which V is a vertex representing a person in this social network, and E is an edge representing the existence of a relationship between two individuals. The social infrastructure with size m is known as the Km group in the social network G with m individual. In other words, in aKm, each person knows other individuals and is in touch with them. The present study aims at developing a method for optimizing interpersonal communication in the social network using a simple cellular automaton algorithm. The experimental resultsobtained from both simulated social network and two real social networks were analyzed.The findings revealed that the proposed method has the potential to considerably reduce not onlythe number of colorsassignedbut also the running time of the program.
    KEYWORDS

    Social networks, Graph coloring, Cellular automata