bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling of Balanced and Unbalanced Three-Phase Induction Motor under Balanced and Unbalanced Supply Based on Winding Function Method
Authors: Jannati Mohammad , Sutikno Tole , Nik Idris Nik Rumzi , Abdul Aziz Mohd Junaidi
Published: October 2019

An accurate model of balanced and unbalanced three-phase Induction Motor (IM) under balanced and unbalanced supply conditions based on Winding Function Method (WFM) is presented in this work. In this paper, the unbalanced condition in three-phase IM is limited to stator winding open-phase fault. The analysis of presented models is shown in details which allow predicting the performance of 3-phase IM under different conditions. Computer simulations were obtained using the MATLAB software for a three-phase squirrel cage IM. MATLAB simulation results show that the oscillation of the speed and electromagnetic torque has increased considerably due to the open-phase fault in stator windings.
Performance Enhancement of Multicore Architecture
Authors: Awadalla Medhat , Konsowa Hanan
Published: October 2019

Multicore processors integrate several cores on a single chip. The fixed architecture of multicore platforms often fails to accommodate the inherent diverse requirements of different applications. The permanent need to enhance the performance of multicore architecture motivates the development of a dynamic architecture. To address this issue, this paper presents new algorithms for thread selection in fetch stage. Moreover, this paper presents three new fetch stage policies, EACH_LOOP_FETCH, INC-FETCH, and WZ-FETCH, based on Ordinary Least Square (OLS) regression statistic method. These new fetch policies differ on thread selection time which is represented by instructions’ count and window size. Furthermore, the simulation multicore tool, , is adapted to cope with multicore processor dynamic design by adding a dynamic feature in the policy of thread selection in fetch stage. SPLASH2, parallel scientific workloads, has been used to validate the proposed adaptation for multi2sim. Intensive simulated experiments have been conducted and the obtained results show that remarkable performance enhancements have been achieved in terms of execution time and number of instructions per second produces less broadcast operations compared to the typical algorithm.
Metal Mountable Ladder Feed Line UHF-RFID Tag Antenna
Authors: Mohd Faudzi Najwa , Ali Mohd Tarmizi , Ismail Ismarani , Jumaat Hadi , Mohd Sukaimi Nur Hidayah
Published: October 2019

A microstrip dipole UHF-RFID tag antenna that can be mounted on metal object is presented in this paper. The antenna, which has a very simple structure without any shorting pin and shorting plate, is composed of ladder feed line, rectangular loop, capacitive tip-loading and T-match structure. The insertion of ground plane in the tag antenna design reduces the negative impact of metal object to the performance of the tag antenna. The tag is designed to operate in the Malaysia frequency range with the center frequency of 921 MHz. The performance of the tag is evaluated through simulation and measurement in terms of impedance matching, antenna reflection coefficient and tag reading range. The measured reading range obtained when the tag is in free air and on metal object is 2.3 m and 2.2 m respectively.
Security against Timing Analysis Attack
Authors: Rani Deevi Radha , Venkateswarlu S
Published: October 2019

Timing attack is the type of side-channel attack involves the time taken to complete critical operations. Securing crypto processor from timing attack is critical issue. This paper implements the Bernstein’s Timing Attack and timing attack based on hamming weight. The countermeasures of Bernstein’s Timing attack are implemented in our experimental test bed and their performance is compared.  This paper also proposes the key recovery method based on timing attack using hamming weight of the key.
Time Series Prediction Using Radial Basis Function Neural Network
Authors: Haviluddin Haviluddin , Tahyudin Imam
Published: October 2019

This paper presents an approach for predicting daily network traffic using artificial neural networks (ANN), namely radial basis function neural network (RBFNN) method. The data is gained from 21-24 June 2013 (192 samples series data) in ICT Unit of Mulawarman University, East Kalimantan, Indonesia. The results of measurement are using statistical analysis, e.g. sum of square error (SSE), mean of square error (MSE), mean of absolute percentage error (MAPE), and mean of absolute deviation (MAD). The results show that values are the same, with different goals that have been set are 0.001, 0.002, and 0.003, and spread 200. The smallest MSE value indicates a good method for accuracy. Therefore, the RBFNN model illustrates the proposed best model to predict daily network traffic.
Scientific Documents clustering based on Text Summarization
Authors: Amoli Pedram Vahdani , Sojoodi Sh. Omid
Published: October 2019

In this paper a novel method is proposed for scientific document clustering. The proposed method is a summarization-based hybrid algorithm which comprises a preprocessing phase. In the preprocessing phase unimportant words which are frequently used in the text are removed. This process reduces the amount of data for the clustering purpose. Furthermore frequent items cause overlapping between the clusters which leads to inefficiency of the cluster separation. After the preprocessing phase, Term Frequency/Inverse Document Frequency (TFIDF) is calculated for all words and stems over the document to score them in the document. Text summarization is performed then in the sentence level. Document clustering is finally done according to the scores of calculated TFIDF. The hybrid progress of the proposed scheme, from preprocessing phase to document clustering, gains a rapid and efficient clustering method which is evaluated by 400 English texts extracted from scientific databases of 11 different topics. The proposed method is compared with CSSA, SMTC and Max-Capture methods. The results demonstrate the proficiency of the proposed scheme in terms of computation time and efficiency using F-measure criterion.
Design of Slotted and Slotless AFPM Synchronous Generators and their Performance Comparison Analysis by using FEA Method
Authors: Soe Saint Saint , Oo Yan Aung
Published: October 2019

Axial-flux permanent magnet machines are popular and widely used for many applications due to their attractive features such as light weight, low noise, high torque, robust and higher efficiency due to lack of field excitation. The main essence of this paper is to perform slotted and slotless axial-flux permanent magnet synchronous generator design based on theoretical sizing equations and then finite element analysis is reinforcement in order to get a more reliable and accuracy machine design. A comparative study of machine design and performances over the same rating but different configurations i.e., slotted and slotless are also discussed. And then, finite-element method (FEM) software was made for the slotted stator and slotless stator (AFPMSG) in order to compare their magnetic flux density and efficiency. The AFPMSG topology considered in this paper is a three-phase double-rotor single-stator topology with 16 pole-pairs, 2kW rated power and 188 rpm rated speed.
Automatic Vehicle Tracking System Based on Fixed Thresholding and Histogram Based Edge Processing
Authors: Shobha Rani N. , O. P. Neethu , Ponnath Nila
Published: October 2019

Automatic detection, extraction and recognition of vehicle number plate region in traffic control systems is one of the prominent application in Computer vision. The drastic increase in number of vehicles in the current generation greatly increases the complexity in tracking the vehicles through the human visual system, manual procedure of controlling traffic and enforcement of various laws and rules is not sufficient for smooth control of traffic. This urges the need for development of technology that can automate this process. This paper mainly focuses on the development of an automatic number plate extraction and recognition algorithm by incorporating constructs like edge detection, horizontal and vertical edge processing using fixed threshold technique. The extracted number plate region is again processed using template matching algorithm for the recognition of the characters embossed on the number plate with respect to every individual piece of number plate. The algorithm developed has achieved an accuracy of around 100% and works for both front and rear images of the car.
Complementary Split Ring Resonator based Sensor for Crack Detection
Authors: Rajni Rajni , Kaur Amanpreet , Marwaha Anupma
Published: October 2019

In this paper, the performance of Complementary Split Ring Resonator
(CSRR) based sensor is explored by varying the geometrical parameters of a
sub millimeter crack. Behavior analysis of the CSRR based sensor is
performed by variation in the parameters of crack. Variation in resonant
frequency of sensor is observed in every case and is noteworthy for our
purpose. This signifies the sensor’s ability to detect crack of different
geometrical parameters on a metal surface.The effectiveness of the sensor is
being contemplated through this approach which is appreciable. An
illustrious performance of the crack detection sensor has been discovered in
this analysis. Simulated results show the feasibility of detecting very small
cracks upto 25 􀟤m width, in the metallic surfaces.
New Method to Optimize Initial Point Values of Spatial Fuzzy c-means Algorithm
Authors: Omidvar Tehrani Iman , Ibrahim Subariah , Haron Habib
Published: October 2019

Fuzzy based segmentation algorithms are known to be performing well on medical images. Spatial fuzzy C-means (SFCM) is broadly used for medical image segmentation but it suffers from optimum selection of seed point initialization which is done either manually or randomly. In this paper, an enhanced SFCM algorithm is proposed by optimizing the SFCM initial point values. In this method in order to increasing the algorithm speed first the approximate initial values are determined by calculating the histogram of the original image. Then by utilizing the GWO algorithm the optimum initial values could be achieved. Finally By using the achieved initial values, the proposed method shows the significant improvement in segmentation results. Also the proposed method performs faster than previous algorithm i.e. SFCM and has better convergence. Moreover, it has noticeably improved the clustering effect.
Model Predictive Control System Design for Boiler Turbine Process
Authors: Kumar Sunori Sandeep , Kumar Juneja Pradeep , Jain Anamika Bhatia
Published: October 2019

MPC is a computer based technique that requires the process model to anticipate the future outputs of that process. An optimal control action is taken by MPC based on this prediction. The MPC is so popular since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. In the present work the control of boiler turbine process with three manipulated variables namely fuel flow valve position, steam control valve position and feed water flow valve position and three controlled variables namely drum pressure, output power and drum water level deviation [8] has been attempted using MPC technique. Boiler turbine process is very complex and nonlinear multivariable process. A linearized model obtained using Taylor series expansion around operating point has been used.
XML and Semantics
Authors: Moradi Mohammad , Keyvanpour MohammadReza
Published: October 2019

Since the early days of introducing eXtensible Markup Language (XML), owing to its expressive capabilities and flexibilities, it became the defacto standard for representing, storing, and interchanging data on the Web. Such features have made XML one of the building blocks of the Semantic Web. From another viewpoint, since XML documents could be considered from content, structural, and semantic aspects, leveraging their semantics is very useful and applicable in different domains. However, XML does not by itself introduce any built-in mechanisms for governing semantics. For this reason, many studies have been conducted on the representation of semantics within/from XML documents. This paper studies and discusses different aspects of the mentioned topic in the form of an overview with an emphasis on the state of semantics in XML and its presentation methods.
Unbalanced Variable Nonlinear Load Compensation Using Multiple Shunt Active Filters
Authors: Janyavula Deepthi , Saxena Satyendra Nath
Published: October 2019

The proposed scheme has considered a three-phase four-wire system, which experienced sag and swell in source voltage for a certain period while feeding an unbalanced and variable non-linear load. The load has unequal resistive and reactive elements in the three phases, forming the unbalanced component. A three-phase silicon controlled rectifier converter with adjustable firing angle connected to the load has formed the variable non-linear component. This has been considered, so as to simulate the unbalanced and variable non-linear  nature of loads in real-time power system. The trends in the total harmonic distortion variation were obtained for the proposed system under power factor correction and voltage regulation mode operation when the load-side converter firing angles of 30°, 60° and 90° were considered using MATLAB/SIMULINK software. Three pulse-width-modulation methods, namely, sinusoidal pulse-width-modulation, space vector modulation and hysteresis pulse-width-modulation have been used to generate pulses for the voltage source converter of the shunt active filter based on the reference currents generated using synchronous reference frame theory.  It has been demonstrated in the proposed paper that power factor correction, voltage regulation, better harmonic reduction and hence load compensation are obtained simultaneously by using two SAFs.
Loss Minimization of Power Distribution Network using Different Types of Distributed Generation Unit
Authors: Win Su Hlaing , Lai Swe Pyone
Published: October 2019

A Radial Distribution network is important in power system area because of its simple design and reduced cost. Reduction of system losses and improvement of voltage profile is one of the key aspects in power system operation. Distributed generators are beneficial in reducing losses effectively in distribution systems as compared to other methods of loss reduction. Sizing and location of DG sources places an important role in reducing losses in distribution network. Four types of DG are considered in this paper with one DG installed for minimize the total real and reactive power losses. The objective of this methodology is to calculate size and to identify the corresponding optimum location for DG placement for minimizing the total real and reactive power losses and to improve voltage profile   in primary distribution system. It can obtain maximum loss reduction for each of four types of optimally placed DGs. Optimal sizing of Distributed Generation can be calculated using exact loss formula and an efficient approach is used to determine the optimum location for Distributed Generation Placement.  To demonstrate the performance of the proposed approach 36-bus radial distribution system in Belin Substation in Myanmar was tested and validated with different sizes and the result was discussed.
Design Calculation of Parabolic Trough Solar Thermal System and Three-phaseTurbo Alternator
Authors: Htun Theingi , Thet Tun Myo
Published: October 2019

Solar energy can be converted into thermal energy with the help of solar
collectors. Electricity can be produced directly from solar energy using
photovoltaic devices or indirectly from steam generators using solar thermal collectors to heat a working fluid. This research is using the conversion of solar energy into electricity in a closed cycle driven by natural convection. It would mean that electricity is cheaper than from any other renewable technology and cheaper than from fossil fuels. This paper describes converting thermal energy collected by solar collector to electricity by using turbine. Anywhere in Myanmar will cheaply use electricity by using solar turbine generator. Remote areas will improve more and more when getting the efficient electricity. The design calculation and performance predication of 1 MVA turbo-alternator/generator are also mentioned. Design calculation of absorbed flux, useful heat gain and exit temperature is described. And then development of two-tank thermal storage system that uses molten salt as the heat transfer fluid is described.
Multilevel MPSoC Performance Evaluation: New ISSPT Model
Authors: Alali A. , Assayad I. , Sadik M.
Published: October 2019

To deploy the enormous hardware resources available in Multi Processor Systems-on-Chip (MPSoC) efficiently, rapidly and accurately, methods of Design Space Exploration (DSE) are needed to evaluate the different design alternatives. In this paper, we present a framework that makes fast simulation and performance evaluation of MPSoC possible early in the design flow, thus reducing the time-to-market. In this framework and within the Transaction Level Modeling (TLM) approach, we present a new definition of ISS level by introducing two complementary modeling sublevels ISST and ISSPT. This later, that we illustrate an arbiter modeling approach that allows a high performance MPSoC communication. A round-robin method is chosen because it is simple, minimizes the communication latency and has an accepted speed-up. Two applications are tested and used to validate our platform: Game of life and JPEG Encoder. The performance of the proposed approach has been analyzed in our platform MPSoC based on multi-MicroBlaze. Simulation results show with ISSPT sublevels gives a high simulation speedup factor of up to 32 with a negligible performance estimation error margin.
Networking Heterogeneous Microcontroller based Systems through Universal Serial Bus
Authors: Jammalamadaka Sastry Kodanda Rama , Kumar Reddy Valluru Sai , J Sasi Bhanu Smt
Published: October 2019

Networking heterogeneous embedded systems is a challenge. Every distributed embedded systems requires that the network is designed specifically considering the heterogeneity that exits among different Microcontroller based systems that are used in developing a distributed embedded system. Communication architecture, which considers the addressing of the individual systems, arbitration, synchronisation, error detection and control etc., needs to be designed considering a specific application. The issue of configuring the slaves has to be addressed. It is also important that the messages, flow of the messages across the individual ES systems must be designed. Every distributed embedded system is different and needs to be dealt with separately. This paper presents an approach that addresses various issues related to networking distributed embedded systems through use of universal serial bus communication protocol (USB). The approach has been applied to design a distributed embedded that monitors and controls temperatures within a Nuclear reactor system.
An Efficient Face Recognition Using SIFT Descriptor in RGB-D Images
Authors: Ouloul M. I. , Moutakki Z. , Afdel K. , Amghar A.
Published: October 2019

Automatic face recognition has known a very important evolution in the last decade, due to its huge usage in the security systems. The most of facial recognition approaches use 2D image, but the problem is that this type of image is very sensible to the illumination and lighting changes. Another approach uses the 3D camera and stereo cameras as well, but it’s rarely used because it requires a relatively long processing duration. A new approach rise in this field, which is based on RGB-D images produced by Kinect, this type of cameras cost less and it can be used in any environment and under any circumstances. In this work we propose a new algorithm that combines the RGB image with Depth map which is less sensible to illumination changes. We got a recognition rate of 96, 63% in rank 2.
A Smart Management Approach Investigation for Hybrid Autonomous Power System
Authors: Sihem Nasri , Sami Ben Slama , Adnane Cherif
Published: October 2019

A novel design of system management based on multi-agents approach applied to an autonomous hybrid power system is proposed and investigated. The system under study integrates few elements, some serve to provide power requirements, while the others used to store energy. Among these items, we can mention a Solar Power Source namely (SPS) which works as primary source to feed a DC electric load. The system integrates also a secondary power source namely Power Recovery Source (PRS) based on a fuel cell technology used to compensate the power deficit if required. More than two kinds of energy storage, the first called Hydrogen Generation Element (HGE) including a water electrolyzer to store the energy in hydrogen form, while the second uses an Ultracapacitor Element (UE) to store the energy in its electrical form. To reach the well functioning of the system in order to satisfy the load requirements whatever the facts, an intelligent energy management approach based on multi-agent modeling is implemented and verified. Hence, the reliability and the effectiveness of the applied management strategy, which allows the coordination between the different energy sources and protects the system against any fluctuation, are proved by the obtained results from Matlab/Simulink.
A Novel Method for Vector Control of Faulty Three-Phase IM Drives Based on FOC Method
Authors: Jannati Mohammad , Nik Idris Nik Rumzi , Abdul Aziz Mohd Junaidi , Sutikno Tole
Published: October 2019

This paper proposes a novel method for vector control of faulty three-phase Induction Motor (IM) drives based on Field-Oriented Control (FOC) method. The performance characteristics of the presented drive system are investigated at healthy and open-phase fault conditions. The simulation of the case study is carried out by using the Matlab/M-File software for a star-connected three-phase IM. The results show the better performance of the proposed drive system especially in reduction of motor speed and torque oscillations during open-phase fault operating.
A Neuro-fuzzy Approach for Predicting Load Peak Profile
Authors: Draidi Abdellah , Labed Djamel
Published: October 2019

Load forecasting has many applications for power systems, including energy purchasing and generation, load switching, contract evaluation, and infrastructure development.

Load forecasting is a complex mathematical process characterized by random data and a multitude of input variables.To solve load forecasting, two different approaches are used, the traditional and the intelligent one.Intelligent systems have proved their efficiency in load forecasting domain.

Adaptive neuro-fuzzy inference systems (ANFIS) are a combination of two intelligent techniques where we can get neural networks and fuzzy logics advantages simultaneously.
 In this paper, we will forecast night load peak of Algerian power system using multivariate input adaptive neuro-fuzzy inference system (ANFIS) introducing the effect of the temperature and type of the day as input variables.
The Transient Stability Study of a Synchronous Generator Based on the Rotor Angle Stability
Authors: Fetissi Selwa , Labed Djamel , Labed Imen
Published: October 2019

Transient stability is an important aspect in the operation of electrical power system. In case of fault occurs in the system, the determining of fault clearing time of circuit breaker is considered one of the main factors to ensure power transfer of the system. This paper is aim to study the transient stability of single machine infinite bus system (SMIB), based on the rotor angle stability. The study is performed to determine the influence of the critical clearing time of the circuit breakers on the rotor angle stability of the generator in the case of three phase fault. For obtaining and determining numerically the nature of the rotor angle of machine, we applied the Step-by-step method for different values of fault clearing time. The results of simulation indicate that determine of critical clearing time is a major evaluation in stability studies. The system model is created in MATLAB/ SIMULINK software.
Modeling of Split Ring Resonators loaded microstrip line with different orientations
Authors: Rajni Rajni , Singh Gurwinder , Marwaha Anupma
Published: October 2019

This paper presents the different circuit approaches of the electric and magnetic interaction of Single Split Ring Resonator (SRR) loaded microstrip line. We loaded the microstrip line with planar square split ring resonator in different configurations and orientations. The modeling behavior of metamaterials-based microstrip lines loaded with single and two-mirrored split ring resonators is analyzed numerically in two orientations (with gap of SRR parallel and perpendicular to the line). The full wave simulations are performed for the single and two-mirrored split ring resonators loaded microstrip inside a waveguide with ‘High Frequency Structure Simulator’ software. The equivalent circuit parameters are obtained for the single split ring resonator loaded with microstrip line with the gap parallel and near to the line from transmission line theory  that make use of just the resonance frequency and minimum of the reflection coefficient. The simulation of different orientations of split ring resonator gives better reflection coefficient and wider frequency.
Performance Comparison of Routing Protocols in Bipartite Wireless Sensor Network
Authors: Gosain Devashish , Snigdh Itu
Published: October 2019

This paper evaluates and ranks the suitability of routing algorithms for bipartite wireless sensor network topology. The network considered in this paper, consists of an irregular combination of fixed and mobile nodes, which leads to construction of a bipartite graph among them. A wireless sensor network is usually constrained by the energy limitations and processing capabilities. We therefore, consider the important metrics for analysis namely, carried load, energy consumption and the average delay incurred. We present the possibilities of employing the routing algorithms subject to the quality of service required by the wireless sensor networks applications
Password Authentication for multicast host using zero knowledge Proof
Authors: Ranganathan Seetha , Saravanan R.
Published: October 2019

The password which is a more secure and valuable data should be highly protected from eavesdropper. This paper presents how password required for authentication of members of group communication is securely delivered by the source or initiator of the group. The password delivery uses zero knowledge proof and sent to the group member in an encrypted format using cipher block mode encryption. The password delivered is a One Time Password which can be used for certain amount of time in order to ensure a highly secure communication environment among the group.
An Optimistic Approach for Clustering Multi-version XML Documents Using Compressed Delta
Authors: Sonawane Vijay R , Rao D. Rajeswara
Published: October 2019

Today with Standardization of XML as an information exchange over web, huge amount of information is formatted in the XML document. XML documents are huge in size. The amount of information that has to be transmitted, processed, stored, and queried is often larger than that of other data formats. Also in real world applications XML documents are dynamic in nature. The versatile applicability of XML documents in different fields of information maintenance and management is increasing the demand to store different versions of XML documents with time. However, storage of all versions of an XML document may introduce the redundancy. Self describing nature of XML creates the problem of verbosity,
in result documents are in huge size. This paper proposes optimistic approach to Re-cluster multi-version XML documents which change in time by reassessing distance between them by using knowledge from initial clustering solution and changes stored in compressed delta. Evolving size of XML document is reduced by applying homomorphic compression before clustering them which retains its original structure. Compressed delta stores the changes responsible for document versions, without decompressing them. Test results shows that our approach performs much better than using full pair-wise document comparison.
Dynamic Time Slice Calculation for Round Robin Process Scheduling Using NOC
Authors: Siva Nageswara Rao G , Srinivasu N. , Srinivasu S.V.N. , Koteswara Rao G. Rama
Published: October 2019

Process scheduling means allocating a certain amount of CPU time to each of the user processes.  One of the popular scheduling algorithms is the “Round Robin” algorithm, which allows each and every process to utilize the CPU for short time duration.  Processes which finish executing during the time slice are removed from the ready queue.  Processes which do not complete execution during the specified time slice are removed from the front of the queue, and placed at the rear end of the queue. This paper presents an improvisation to the traditional round robin scheduling algorithm, by proposing a new method. The new method represents the time slice as a function of the burst time of the waiting process in the ready queue. Fixing the time slice for a process is a crucial factor, because it subsequently influences many performance parameters like turnaround time, waiting time, response time and the frequency of context switches.  Though the time slot is fixed for each process, this paper explores the fine-tuning of the time slice for processes which do not complete in the stipulated time allotted to them.
Tree Based Energy Balancing Routing Protocol by Self Organizing in Wireless Sensor Networks
Authors: Umar Syed , D Prasada Rao P.V.R. , Gutta Sridevi
Published: October 2019

Today the wireless sensor networks (WSN) play a crucial role in wireless technology in various domains like military, medicine, communications etc. The energy conservation is the crucial factor in the WSN. The WSN is a system which has more number of nodes in which various sensors are fabricated on the nodes to monitor various factors of the given task. These nodes will form a network by connecting the one to other for the effective communication between the nodes, and sends the whole information to the base station (BS). As the nodes which we use for the WSN are of low cost and are battery operated. The main drawback is replacement of the battery in the WSN. The main goal is to conserve the energy consumption in WSN and also to balance the load on WSN. For this many protocols are designed like LEACH, PEGASIS, PEDAP, etc. in those balancing the load and time delayed. some drawbacks are there. So we proposed a protocol so called “Tree Based Energy Balancing routing Protocol by Self Organizing” (TEBRSO), in which instead of routing tables a routing tree will be used for routing from nodes to base station (BS), which chooses one root/control node for the broadcasting messages to the selected sensor nodes. By this protocol we can save the energy consumption in WSN and can extend the life time of it. The performance of this protocol is better when we compare with other energy saving protocols.
Sociopsychotechnological Predictors of Individual’s Social Loafing in Virtual Team
Authors: Abraham Juneman , Trimutiasari Melina
Published: October 2019

The rapid development of technology and the demands of the workers to be productive have made efficiency and effectiveness of virtual team collaboration is becoming increasingly urgent lately. Therefore, it is important to identify the variables undermining the efficiency and effectiveness. This study aimed to investigate the role of perceived usefulness, perceived ease of use, and perceived playfulness of online collaboration tool (as elements of technology acceptance) and xenophobia in predicting social loafing (at the individual level)─a social psychological phenomenon that shows the declining performance of the individual when working in the group. The contribution of this research is its attempt to combine social psychological and technological factors in explaining human performance in the context of the group when interacting with technology. The research design was correlational predictive, with multiple linear regression data analysis technique. Participants of this study were 80 students and employees (43 males, 37 females; mean of age = 25.58 years of old, standard deviation of age = 4.92 years) who work using online collaboration tool in a virtual team. The results showed that the perceived playfulness, perceived ease of use, and xenophobia were able to predict an individual’s social loafing, but the perceived usefulness is not able to predict it. Implications of the results of research in order to prevent social loafing are stated in the Discussion section.
Anti-Phishing Techniques in Cryptography
Authors: Nanda Akshey , Gupta Himanshu
Published: October 2019

Phishing is a process in which Phishers try to leak out the credentials of users by hosting a fake web page on user's browser. To save users from phishing attacks, many researchers have dug deep and presented their insights. Nowadays, in the era of 21st century,  banks are using the OTP and visual cryptography for the authentication of both sides i.e. user and the bank. In this paper, we are proposing a methodology in which a user will need to give his finger prints as an authentication.
Novel Approach for Control Data Theft Attack in Cloud Computing
Authors: Sastry K. Narasimha , Rao B. Thirumala , Gunasekhar T
Published: October 2019

Information security is a major problem faced by cloud computing around the world. Because of their adverse effects on organizational information systems, viruses, hackers, and attackers insiders can jeopardize organizations capabilities to pursue their undertaken effectively. Although technology based solutions help to mitigate some of the many problems of information security, even the preeminent technology can’t work successfully unless effective human computer communication occurs.IT experts, users and administrators all play crucial role to determine the behavior that occurs as people interact with information technology will support the maintenance of effective security or threaten it. In the present paper we try to apply behavioral science concepts and techniques to understanding problems of information security in organizations.
A Polynomial Digital Pre-Distortion Technique Based on Iterative Architecture
Authors: Lee Kwang-Pyo , Hong Soon-Il , Jeong Eui-Rim
Published: October 2019

A digital predistortion (DPD) technique based on an iterative adaptation structure is proposed for linearizing power amplifiers (PAs). To obtain proper DPD parameters, a feedback path that converts the PA’s output to a baseband signal is required, and memory is also needed to store the baseband feedback signals. DPD parameters are usually found by an adaptive algorithm by using the transmitted signals and the corresponding feedback signals. However, for the adaptive algorithm to converge to a reliable solution, long feedback samples are required, which increases hardware complexity and cost. Considering that the convergence time of the adaptive algorithm highly depends on the initial condition, we propose a DPD technique that requires relatively shorter feedback samples. Specifically, the proposed DPD iteratively utilizes the short feedback samples in memory while keeping and using the DPD parameters found at the former iteration as the initial condition at the next iteration. Computer simulation shows that the proposed technique performs better than the conventional technique, as the former requires much shorter feedback memory than the latter.
Projected Range Dependent Tunneling Current of Asymmetric Double Gate MOSFET
Authors: Jung Hak Kee
Published: October 2019

This study is to analyze the changes of tunneling current according to projected range, a variable of Gaussian function of channel doping function of Asymmetric Double Gate; ADG MOSFET. In MOSFET with channel length below 10 nm, tunneling current occupies a large percentage among off-currents. The increase of tunneling current has a large effect on the characteristics of subthreshold such as threshold voltage movement and the decline of subthreshold swing value, so the accurate analysis of this is being required. To analyze this, potential distribution of series form was obtained using Gaussian distribution function, and using this hermeneutic potential distribution, thermionic emission current and tunneling current making up off-current were obtained. At this point, the effect that the changes of projected range, a variable of Gaussian distribution function, have on the ratio of tunneling current among off-currents was analyzed. As a result, the smaller projected range was, the lower the ratio of tunneling current was. When projected range increased, tunneling current increased largely. Also, it was observed that the value of projected range which the ratio of tunneling current increased changed according to maximum channel doping value, channel length, and channel width.
Identification of Nonlinear Systems Structured by Wiener-Hammerstein Model
Authors: Brouri A , Slassi S
Published: October 2019

Wiener-Hammerstein systems consist of a series connection including a nonlinear static element sandwiched with two linear subsystems. The problem of identifying Wiener-Hammerstein models is addressed in the presence of hard nonlinearity and two linear subsystems of structure entirely unknown (asymptotically stable). Furthermore, the static nonlinearity is not required to be invertible. Given the system nonparametric nature, the identification problem is presently dealt with by developing a two-stage frequency identification method, involving simple inputs.
New Stability Conditions for Nonlinear Systems Described by Multiple Model Approach
Authors: Sassi Ameur , Abdelkrim Afef
Published: October 2019

This paper studies the global asymptotic stability and the tracking control problem of an uncertain non stationary continuous system described by the multiple model approach. It is based on the construction of a basis of models containing four extreme models and possibility of addition of an average model. Once the basis of models is generated, an operation of fusion of these different models is made to the level of the elementary control law and the partial output using the geometric method. New sufficient conditions for the stability are derived via Lyapunov technique. The matrices of feedback gains and tracking gains are determined while solving systems of LMI constraints (Linear Matrix Inequalities). The case of an unstable continuous nonlinear model of electrical circuit operating in pseudo-periodic system is considered to illustrate the proposed approach.
QoS Design Consideration for Enterprise and Provider’s Network at Ingress and Egress Router for VoIP protocols
Authors: Kolhar Manjur , M Abualhaj Mosleh , Rizwan Faiza
Published: October 2019

Compliance with the Service Level Agreement (SLA) metric is a major challenge in a Multiprotocol Label Switching Virtual Private Network (MPLS VPN) because mandatory models must be maintained on both sides of the MPLS VPN in order to achieve end-to-end service levels. The end-to-end service of an MPLS VPN can be degraded owing to various issues such as distributed denial of service (DDoS), and Random Early Detection (RED) that prevents congestion and differentiates between legitimate and illegitimate user traffic. In this study, we propose a centralized solution that uses a SLA Violation Detector (SLAVD) and intrusion detection to prevent SLA violation.
Key Software Metrics and its Impact on each other for Software Development Projects
Authors: Bhardwaj Mridul , Rana Ajay
Published: October 2019

Every software development project is unique and different from repeatable manufacturing process. Each software project share different challenges related to technology, people and timelines. If every project is unique, how project manager can estimate project in a consistent way by applying his past experience. One of the major challenges faced by the project manager is to identify the key software metrics to control and monitor the project execution. Each software development project may be unique but share some common metric that can be used to control and monitor the project execution. These metrics are software size, effort, project duration and productivity. These metrics tells project manager about what to deliver (size), how it was delivered in past (productivity) and how long will it take to deliver with current team capability (time and effort). In this paper, we explain the relationship among these key metrics and how they statistically impact each other. These relationships have been derived based on the data published in book “Practical Software Estimation” by International Software Benchmarking Group. This paper also explains how these metrics can be used in predicting the total number of defects. Study suggests that out of the four key software metrics software size significantly impact the other three metrics (project effort, duration and productivity). Productivity does not significantly depend on the software size but it represents the nonlinear relationship with software size and maximum team size, hence, it is recommended not to have a very big team size as it might impact the overall productivity. Total project duration only depends on the software size and it does not depend on the maximum team size. It implies that we cannot reduce project duration by increasing the team size. This fact is contrary to the perception that we can reduce the project duration by increasing the project team size. We can conclude that software size is the important metrics and a significant effort must be put during project initiation phases to estimate the project size. As software size will help in estimating the project duration and project efforts so error in estimating the software size will have significant impact on the accuracy of project duration and effort. All these key metrics must be re-calibrated during the project development life cycle.

 
The Selection of Useful Visual Words for Class-Imbalanced Data in Image Classification
Authors: Chimlek Sutasinee , Pramokchon Part , Piamsa-nga Punpiti
Published: October 2019

The bag of visual words (BOVW) has recently been used for image classification in large datasets. A major problem of image classification using BOVW is high dimensionality, with most features usually being irrelevant and different BOVW for multi-view images in each class. Therefore, the selection of significant visual words for multi-view images in each class is an essential method to reduce the size of BOVW while retaining the high performance of image classification. Many feature scores for ranking produce low classification performance for class imbalanced distributions and multi-views in each class. We propose a feature score based on the statistical t-test technique, which is a statistical evaluation of the difference between two sample means, to assess the discriminating power of each individual feature. The multi-class image classification performance of the proposed feature score is compared with four modern feature scores, such as Document Frequency (DF), Mutual information (MI), Pointwise Mutual information (PMI) and Chi-square statistics (CHI). The results show that the average F1-measure performance on the Paris dataset and the SUN397 dataset using the proposed feature score are 92% and 94%, respectively, while all other feature scores do not exceed 80%.
Prediction Data Processing Scheme using an Artificial Neural Network and Data Clustering for Big Data
Authors: Jung Se-Hoon , Kim Jong-Chan , Sim Chun-Bo
Published: October 2019

Various types of derivative information have been increasing exponentially, based on mobile devices and social networking sites (SNSs), and the information technologies utilizing them have also been developing rapidly. Technologies to classify and analyze such information are as important as data generation. This study concentrates on data clustering through principal component analysis and K-means algorithms to analyze and classify user data efficiently. We propose a technique of changing the cluster choice before cluster processing in the existing K-means practice into a variable cluster choice through principal component analysis, and expanding the scope of data clustering. The technique also applies an artificial neural network learning model for user recommendation and prediction from the clustered data. The proposed processing model for predicted data generated results that improved the existing artificial neural network–based data clustering and learning model by approximately 9.25%.
3LRM-3 Layer Risk Mitigation Modelling of ICT Software Development Projects
Authors: Firdose Salma , Rao L. Manjunath
Published: October 2019

With the adoption of new technology and quality standards, the software development firms are still encountering the critical issues of risk modelling. With the changing dynamics of customer needs, potential competition has being mushrooming in the global IT markets to relay a new standard of software engineering which has higher capability of sustaining risk.  However, till date, it is still theoretical to large extent from research viewpoint. Hence, this paper presents a mathematical model called as 3LRM that is designed with the simple approach keeping in mind the real-time issues of risk factors in software engineering for ICT software development project. The study has also identified requirement volatility as one of the prominent source of risk and hence, the framework intends to identify a risk as well as mitigating the risk to a large extent. The paper is illustrated with some of the simple statistical approaches of random probability.
Sentimental Analysis of Twitter Data using Classifier Algorithms
Authors: Shah Sharvil , Kumar Kannan , Sarvananguru Ra. K.
Published: October 2019

Microblogging has become a daily routine for most of the people in this world. With the help of Microblogging people get opinions about several things going on, not only around the nation but also worldwide. Twitter is one such online social networking website where people can post their views regarding something. It is a huge platform having over 316 Million users registered from all over the world. It enables users to send and read short messages with over 140 characters for compatibility with SMS messaging. A good sentimental analysis of data of this huge platform can lead to achieve many new applications like – Movie reviews, Product reviews, Spam detection, Knowing consumer needs, etc. In this paper, we have devised a new algorithm with which the above needs can be achieved. Our algorithm uses three specific techniques for sentimental analysis and can be called a hybrid algorithm – (1) Hash Tag Classification for topic modeling; (2) Naïve Bayes Classifier Algorithm for polarity classification; (3) Emoticon Analysis for Neutral polar data. These techniques individually have some limitations for sentimental analysis.
Modelling of E-Governance Framework for Mining Knowledge from Massive Grievance Redressal Data
Authors: G Sangeetha , Rao L. Manjunatha
Published: October 2019

With the massive proliferation of online applications for the citizens with abundant resources, there is a tremendous hike in usage of e-governance platforms. Right from entrepreneur, players, politicians, students, or anyone who are highly depending on web-based grievance redressal networking sites, which generates loads of massive grievance data that are not only challenging but also highly impossible to understand. The prime reason behind this is grievance data is massive in size and they are highly unstructured. Because of this fact, the proposed system attempts to understand the possibility of performing knowledge discovery process from grievance Data using conventional data mining algorithms. Designed in Java considering massive number of online e-governance framework from civilian’s grievance discussion forums, the proposed system evaluates the effectiveness of performing datamining for Big data.