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Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO
A. Rajagopal,
S. Somasundaram,
B. Sowmya
Issue:
Volume 6, Issue 1, March 2018
Pages:
1-9
Received:
18 November 2017
Accepted:
30 November 2017
Published:
26 January 2018
Abstract: Wireless Sensor Network involves in the communication task which demands the devices to form a connected network for collecting and disseminating information through radio transmission. The main objective of the Wireless Sensor Network is to extend the network lifetime in the operational environment, to charge or to exchange the sensor node batteries is probably an impossible/unfeasible activity. The clustered network aims to select CHs that minimize transmission costs and energy. To maximize the network lifetime, optimal CH selection is important. Selections of CH are Non deterministic Polynomial (NP) hard. Recently natural swarm inspired algorithms like Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) have found their way into this domain and proved their effectiveness. In this work the BFO is adapted for cluster head selection so that multiple objectives like reduced packet delivery ratio, improved cluster formation, improved network life time and reduced end to end delay are achieved. Also a novel Hybrid algorithm using Bacterial foraging Optimization (BFO) - Bee swarm Optimization (BSO) is attempted to analysis the number of clustered formed, end to end delay, packet drop ratio and lifetime.
Abstract: Wireless Sensor Network involves in the communication task which demands the devices to form a connected network for collecting and disseminating information through radio transmission. The main objective of the Wireless Sensor Network is to extend the network lifetime in the operational environment, to charge or to exchange the sensor node batteri...
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Mobile Computing Framework for Student Engagement System in Ethiopian Higher Educational Institution
Issue:
Volume 6, Issue 1, March 2018
Pages:
10-19
Received:
2 January 2018
Accepted:
12 January 2018
Published:
1 February 2018
Abstract: Students require a great deal of information from colleges such as admission notices, timetables, events details, assessments etc. Currently, this information is provided to students through college website. The information present on website is generic, pertaining to large group of students and other stakeholders. Currently in Ethiopia, Higher Educational Institution (HEI) information is distributed to students in two ways, one using traditional paper means and other is using its University website. However, the major challenge in obtaining information from website is that it provides collective information pertaining to large groups of students instead of focusing to individual student needs. In view of this problems and issues concerning the accessibility on on-time information of student in different higher educational institution of the country. In this study, the researcher propose a mobile educational framework student engagement information system coin as mSEIS, integrating the existing web-enabled system of the University and include other features pertaining to student services. The proposed framework and its implementation will empower student by providing them with relevant personalized information anywhere anytime. The study proposed extensible 3-tier architecture from its formulated mobile framework which consists of the following functionality: Grades Inquiry, Class time table, m-Learning, m-Library, Notice Board and Helpline. Among the 40 Ethiopian, HEI 6 institution was selected using purposive sampling technique because the goal of the study was to acquire the best-positioned and the most able thinkers on the problem. Using the Software Quality ISO 9126 standard based modified Likert survey questionnaire, the respondents strongly agreed that the acceptability factor of the system’s functionality, reliability, efficiency, usability, maintainability and portability are significant. The proposed system passed all criteria except the portability, in which it is recommended that it should be available in iOS and Windows Phone mobile operation system as future work.
Abstract: Students require a great deal of information from colleges such as admission notices, timetables, events details, assessments etc. Currently, this information is provided to students through college website. The information present on website is generic, pertaining to large group of students and other stakeholders. Currently in Ethiopia, Higher Edu...
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ANFIS-Based Visual Pose Estimation of Uncertain Robotic Arm Using Two Uncalibrated Cameras
Aung Myat San,
Wut Yi Win,
Saint Saint Pyone
Issue:
Volume 6, Issue 1, March 2018
Pages:
20-30
Received:
2 January 2018
Accepted:
17 January 2018
Published:
6 February 2018
Abstract: This paper describes a new approach for the visual pose estimation of an uncertain robotic manipulator using ANFIS (Artificial Neuro-Fuzzy Inference System) and two uncalibrated cameras. The main emphasis of this work is on the ability to estimate the positioning accuracy and repeatability of a low-cost robotic arm with unknown parameters under uncalibrated vision system. The vision system is composed of two cameras; installed on the top and on the lateral side of the robot, respectively. These two cameras need no calibration; thus, they can be installed in any position and orientation with just the condition that the end-effector of the robot must remain always visible. A red-colored feature point is fixed on the end of the third robotic arm link. In this study, captured image data via two fixed-cameras vision system are used as the sensor feedback for the position tracking of an uncertain robotic arm. LabVolt R5150 manipulator in our laboratory is used as case study. The visual estimation system is trained using ANFIS with subtractive clustering method in MATLAB. In MATLAB, the robot, feature point and cameras are simulated as physical behaviors. To get the required data for ANFIS, the manipulator was maneuvered within its workspace using forward kinematics and the feature point image coordinates were acquired with the two cameras. Simulation experiments show that the location of the robotic arm can be trained in ANFIS using two uncalibrated cameras; and problems for computational complexity and calibration requirement of multi-view geometry can be eliminated. Observing Mean Square Error (MSE), Root Mean Square Error (RMSE), Error Mean and Standard Deviation Errors, the performance of the proposed approach is efficient for using as visual feedback in uncertain robotic manipulator. Further, the proposed approach using ANFIS and uncalibrated vision system has better in flexibility, user-friendly manner and computational concepts over conventional techniques.
Abstract: This paper describes a new approach for the visual pose estimation of an uncertain robotic manipulator using ANFIS (Artificial Neuro-Fuzzy Inference System) and two uncalibrated cameras. The main emphasis of this work is on the ability to estimate the positioning accuracy and repeatability of a low-cost robotic arm with unknown parameters under unc...
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Analysis of Cognitive Radio Capacity in Fading Channels
Mohan Premkumar,
Muthappa Perumal Chitra
Issue:
Volume 6, Issue 1, March 2018
Pages:
31-36
Received:
31 December 2017
Accepted:
30 January 2018
Published:
12 February 2018
Abstract: This research paper is intended to derive, simulate and analyze the capacity of cognitive radio (CR) system in fading channels. Capacity being an information theoretic perspective for a wireless system plays a role in the amount of information bits which can be transmitted. As wireless channel is subjected to multipath effects in a CR system caused by fading, capacity analysis needs to be done. Simulation carried out in terms of capacity, mean square error for channel estimation and bit error rate (BER) for the proposed system model of cognitive radio can give valuable information about performance of CR system in terms of data bits handling capacity. The amount of capacity in flat fading channels and frequency selective fading channels are simulated. The obtained results in terms of capacity can be used as reference for further analysis to be explored relating to design of cognitive radio systems for developing applications for 5G systems.
Abstract: This research paper is intended to derive, simulate and analyze the capacity of cognitive radio (CR) system in fading channels. Capacity being an information theoretic perspective for a wireless system plays a role in the amount of information bits which can be transmitted. As wireless channel is subjected to multipath effects in a CR system caused...
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