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31,456 Article Results

Accelerated Mobile Pages from JavaScript as Accelerator Tool for Web Service on E-Commerce in the E-Business

10.11591/ijece.v8i4.pp2399-2405
Agus Wibowo , Guruh Aryotejo , Mufadhol Mufadhol
E-commerce is a sub-part of E-business which includes all kinds of functions and business activities by using electronic data that has the main purpose to increase corporate profits. One of the strategies used is to automate the existing tasks in E-commerce by utilizing web service facilities, which will significantly save time. The use of smartphones as a primary means of information and communication forces web service application providers to improve their services and facilities, such as websites that can be opened quickly and lightly on smartphone devices. This paper will discuss the benefits of accelerated mobile pages as a coding accelerator tool in the javaScript programming language using XML, HTML and XHTML programming as well as involving the use of SOAP, WSDL and NuSOAP that will run on both HTTP and HTTPS protocols. Using accelerated mobile pages as a means of accelerator tool on E-commerce in E-business can directly improve web service performance. This is very prominent when the site is accessed through a smartphone that has limited resources, in the form of website access will feel fast, easy and light.
Volume: 8
Issue: 4
Page: 2399-2405
Publish at: 2018-08-01

Reliability worth Assessment of Active Distribution System Considering Protective Devices and Multiple Distributed Generation Units

10.11591/ijape.v7.i2.pp111-119
Subramanya Sarma S , V. Madhusudhan , V. Ganesh
Reliability worth assessment is a primary concern in planning and designing of electrical distribution systems those operate in an economic manner with minimal interruption of electric supply to customer loads. Renewable energy sources (RES) based Distributed Generation (DG) units can be forecasted to penetrate in distribution networks due to advancement in their technology. The assessment of reliability worth of DG enhanced distribution networks is a relatively new research area. This paper proposes a methodology that can be used to analyze the reliability of active distribution systems (DG enhanced distribution system) and can be applied in preliminary planning studies to compute the reliability indices and statistics. The reliability assessment in this work is carried out with analytical approach applied on a test system and simulated results validate that installation of distributed generators can improve the distribution system reliability considerably.
Volume: 7
Issue: 2
Page: 111-119
Publish at: 2018-08-01

Reliability Constrained Unit Commitment Considering the Effect of DG and DR Program

10.11591/ijece.v8i4.pp1985-1996
Masoud Aliakbari , Pouria Maghouli , Habib Allah Aalami
Due to increase in energy prices at peak periods and increase in fuel cost, involving Distributed Generation (DG) and consumption management by Demand Response (DR) will be unavoidable options for optimal system operations. Also, with high penetration of DGs and DR programs into power system operation, the reliability criterion is taken into account as one of the most important concerns of system operators in management of power system. In this paper, a Reliability Constrained Unit Commitment (RCUC) at presence of time-based DR program and DGs integrated with conventional units is proposed and executed to reach a reliable and economic operation. Designated cost function has been minimized considering reliability constraint in prevailing UC formulation. The UC scheduling is accomplished in short-term so that the reliability is maintained in acceptable level. Because of complex nature of RCUC problem and full AC load flow constraints, the hybrid algorithm included Simulated Annealing (SA) and Binary Particle Swarm Optimization (BPSO) has been proposed to optimize the problem. Numerical results demonstrate the effectiveness of the proposed method and considerable efficacy of the time-based DR program in reducing operational costs by implementing it on IEEE-RTS79.
Volume: 8
Issue: 4
Page: 1985-1996
Publish at: 2018-08-01

Solar Energy System Based Impedance-Source Inverter for Grid Connected System

10.11591/ijape.v7.i2.pp129-138
S Kamalakkannan , D. Kirubakaran
In this work, the fickleness of solar energy can be overcome by using Maximum Power Point Tracking algorithm (MPPT). Perturb and Observation (P&O) MPPT algorithm accomplish fast the maximum power point for rapid change of environmental conditions such as irradiance intensity and temperature. The MPPT algorithm applied to solar system keep the boost converter output constant. Output from boost converter is taken to three phase impedance-source inverter with RL load and grid system. Impedance-source inverter performs the transformation of variable DC output of the solar system in to near sinusoidal AC output. This near sinusoidal AC output consecutively is served to the RL load first and then to grid system. The simulation is carried out in matlab/simulink platform both for RL load and grid system and the simulation results are experimentally validated for RL load arrangement only.
Volume: 7
Issue: 2
Page: 129-138
Publish at: 2018-08-01

Sensorless Control of Brushless Doubly-Fed Generator Using Luenberger Observer Based Wind Energy Conversion Systems

10.11591/ijape.v7.i2.pp188-198
Hicham Serhoud , Djilani Benattous
This paper investigates the use of Luenberger observer for sensorless power control of brushless double fed induction machine (BDFM) in wind energy conversion systems, the control strategy for flexible power flow control is developed by applying flux oriented vector control (technique), In order to estimate the rotor speed, an adaptive algorithm based on Lyapunov stability theory will be design. Finally the analyzed and simulation results in MATLAB/ Simulink platform confirmed the good dynamic performance of this new sensorless control for BDFG based variable speed wind turbines.
Volume: 7
Issue: 2
Page: 188-198
Publish at: 2018-08-01

Coal-Fired Boiler Fault Prediction using Artificial Neural Networks

10.11591/ijece.v8i4.pp2486-2493
Nong Nurnie Mohd Nistah , King Hann Lim , Lenin Gopal , Firas Basim Ismail Alnaimi
Boiler fault is a critical issue in a coal-fired power plant due to its high temperature and high pressure characteristics. The complexity of boiler design increases the difficulty of fault investigation in a quick moment to avoid long duration shut-down. In this paper, a boiler fault prediction model is proposed using artificial neural network. The key influential parameters analysis is carried out to identify its correlation with the performance of the boiler. The prediction model is developed to achieve the least misclassification rate and mean squared error. Artificial neural network is trained using a set of boiler operational parameters. Subsequenlty, the trained model is used to validate its prediction accuracy against actual fault value from a collected real plant data. With reference to the study and test results, two set of initial weights have been tested to verify the repeatability of the correct prediction. The results show that the artificial neural network implemented is able to provide an average of above 92% prediction rate of accuracy.
Volume: 8
Issue: 4
Page: 2486-2493
Publish at: 2018-08-01

Neural Network Model Development with Soft Computing Techniques for Membrane Filtration Process

10.11591/ijece.v8i4.pp2614-2623
Zakariah Yusuf , Norhaliza Abdul Wahab , Shafishuhaza Sahlan
Membrane bioreactor employs an efficient filtration technology for solid and liquid separation in wastewater treatment process. Development of membrane filtration model is significant as this model can be used to predict filtration dynamic which is later utilized in control development. Most of the available models only suitable for monitoring purpose, which are too complex, required many variables and not suitable for control system design. This work focusing on the simple time seris model for membrane filtration process using neural network technique. In this paper, submerged membrane filtration model developed using recurrent neural network (RNN) train using genetic algorithm (GA), inertia weight particle swarm optimization (IW-PSO) and gravitational search algorithm (GSA). These optimization algorithms are compared in term of its accuracy and convergent speed in updating the weights and biases of the RNN for optimal filtration model. The evaluation of the models is measured using three performance evaluations, which are mean square error (MSE), mean absolute deviation (MAD) and coefficient of determination (R2). From the results obtained, all methods yield satisfactory result for the model, with the best results given by IW-PSO.
Volume: 8
Issue: 4
Page: 2614-2623
Publish at: 2018-08-01

CCTV Surveillance System, Attacks and Design Goals

10.11591/ijece.v8i4.pp2072-2082
Muthusenthil B. , Hyun Sung Kim
Closed Circuit Tele-Vision surveillance systems are frequently the subject of debate. Some parties seek to promote their benefits such as their use in criminal investigations and providing a feeling of safety to the public. They have also been on the receiving end of bad press when some consider intrusiveness has outweighed the benefits. The correct design and use of such systems is paramount to ensure a CCTV surveillance system meets the needs of the user, provides a tangible benefit and provides safety and security for the wider law-abiding public. In focusing on the normative aspects of CCTV, the paper raises questions concerning the efficiency of understanding contemporary forms of ‘social ordering practices’ primarily in terms of technical rationalities while neglecting other, more material and ideological processes involved in the construction of social order. In this paper, a 360-degree view presented on the assessment of the diverse CCTV video surveillance systems (VSS) of recent past and present in accordance with technology. Further, an attempt been made to compare different VSS with their operational strengths and their attacks. Finally, the paper concludes with a number of future research directions in the design and implementation of VSS.
Volume: 8
Issue: 4
Page: 2072-2082
Publish at: 2018-08-01

An approach to Measure Transition Density of Binary Sequences for X-filling based Test Pattern Generator in Scan based Design

10.11591/ijece.v8i4.pp2063-2071
Sabir Hussain , V. Malleshwara Rao
Switching activity and Transition density computation is an essential stage for dynamic power estimation and testing time reduction. The study of switching activity, transition densities and weighted switching activities of pseudo random binary sequences generated by Linear Feedback shift registers and Feed Forward shift registers plays a crucial role in design approaches of Built-In Self Test, cryptosystems, secure scan designs and other applications. This paper proposed an approach to find transition densities, which plays an important role in choosing of test pattern generator We have analyze conventional and proposed designs using our approache, This work also describes the testing time of benchmark circuits. The outcome of this paper is presented in the form of algorithm, theorems with proofs and analyses table which strongly support the same. The proposed algorithm reduces switching activity and testing time up to 51.56% and 84.61% respectively.
Volume: 8
Issue: 4
Page: 2063-2071
Publish at: 2018-08-01

Information Retrieval from Emotions and Eye Blinks with help of Sensor Nodes

10.11591/ijece.v8i4.pp2433-2441
Puneet Singh Lamba , Deepali Virmani
In everyday life, there are situations where the only way to communicate are emotions. EMOTICONS are the epitome of the same. This aspect of communication can also be used in emergency situations (terrorist attacks, hijacks) where the only way to communicate is by performing some extraordinary actions or through some emotions. Incorporating technology to the above mentioned circumstances the paper proposes a novel framework of detecting an emergency situation by retrieving information from emotions and eye blinks using sensor nodes. The proposed framework can be deployed in places (hotels, banks, airports etc.) which are more suspected to attacks. The framework takes input from real time parameters: eye blinks, emotions, heart rate. Based on behavioral changes, biological changes and physical changes the proposed framework extracts meticulous information. The proposed framework is further validated through implementation of a facial emotion recognition system that successfully recognizes various human emotions. The facial emotion recognition system of the proposed framework is compared with existing SVM technique in terms of accuracy, training and testing error. Accuracy with the proposed system is increased to 78.40% in comparison with existing SVM that is 75.37% and the training error is decreased to 0.004103 whereas with the existing SVM method training error is 0.008935.
Volume: 8
Issue: 4
Page: 2433-2441
Publish at: 2018-08-01

Controlling a DC Motor through Lypaunov-like Functions and SAB Technique

10.11591/ijece.v8i4.pp2180-2198
Alejandro Rincón , Fabiola Angulo , Fredy Hoyos
In this paper, state adaptive backstepping and Lyapunov-like function methods are used to design a robust adaptive controller for a DC motor. The output to be controlled is the motor speed. It is assumed that the load torque and inertia moment exhibit unknown but bounded time-varying behavior, and that the measurement of the motor speed and motor current are corrupted by noise. The controller is implemented in a Rapid Control Prototyping system based on Digital Signal Processing for dSPACE platform and experimental results agree with theory.
Volume: 8
Issue: 4
Page: 2180-2198
Publish at: 2018-08-01

Angular Symmetric Axis Constellation Model for Off-line Odia Handwritten Characters Recognition

10.11591/ijict.v7i2.pp96-104
Pyari Mohan Jena , Soumya Ranjan Nayak
Optical character recognition is one of the emerging research topics in the field of image processing, and it has extensive area of application in pattern recognition. Odia handwritten script is the most research concern area because it has eldest and most likable language in the state of odisha, India. Odia character is a usually handwritten, which was generally occupied by scanner into machine readable form. In this regard several recognition technique have been evolved for variance kind of languages but writing pattern of odia character is just like as curve appearance; Hence it is more difficult for recognition. In this article we have presented the novel approach for Odia character recognition based on the different angle based symmetric axis feature extraction technique which gives high accuracy of recognition pattern. This empirical model generates a unique angle based boundary points on every skeletonised character images. These points are interconnected with each other in order to extract row and column symmetry axis. We extracted feature matrix having mean distance of row, mean angle of row, mean distance of column and mean angle of column from centre of the image to midpoint of the symmetric axis respectively. The system uses a 10 fold validation to the random forest (RF) classifier and SVM for feature matrix. We have considered the standard database on 200 images having each of 47 Odia character and 10 Odia numeric for simulation. As we have noted outcome of simulation of SVM and RF yields 96.3% and 98.2% accuracy rate on NIT Rourkela Odia character database and 88.9% and 93.6% from ISI Kolkata Odia numerical database.
Volume: 7
Issue: 2
Page: 96-104
Publish at: 2018-08-01

Smart Wheelchair: A Literature Review

10.11591/ijict.v7i2.pp63-66
Kedar Sukerkar , Darshitkumar Suratwala , Anil Saravade , Jairaj Patil , Rovina D’britto
In today’s world there are many disabled persons who find it difficult to perform movements or perform daily activities. This types of persons are mainly dependent on others for their assistance. But they can become self-independent and perform some daily activities on their own with the help of assistive devices. The most widely used assistive devices are Wheelchairs. Wheelchairs is basically a chair fitted with wheels, which can help people move around who cannot walk because of illness, disability or injury. But there are many disabled people with weak limbs and joints who cannot move the wheelchair. Thus, Smart Wheelchair can benefit a lot to them and everyone in society. Smart Wheelchairs are electric powered wheelchairs with many extra components such as a computer and sensors which help the user or guardian accompanying wheelchair to handle it easily and efficiently. The recent development in the field of Artificial Intelligence, Sensor technologies and Robotics help the growth of wheelchairs with new features. This paper is to review the current state of art of Smart Wheelchairs and discuss the future research in this field.
Volume: 7
Issue: 2
Page: 63-66
Publish at: 2018-08-01

Protecting Data by Improving Quality of Stego Image based on Enhanced Reduced difference Expansion

10.11591/ijece.v8i4.pp2468-2476
Maurice Ntahobari , Tohari Ahmad
In this era of internet development, security of information sharing is the main problem faced by human being. Data hiding technique is one of the solutions. However, hiding credential information within a multimedia file such as image reduces its visual quality. Therefore, unauthorized users may suspect the existance of secret data within that image. In the past years, various data hiding algorithms have been developed by researchers to overcome the problem of high distortion of image after data embedding process. Achieving a high quality stego image, however, is still a challenging problem. In this paper, we proposed a new data hiding algorithm based on different expansion. It aims to enhance the quality of stego image for a given payload size. The new algorithm is evaluated on various medical images. Thereafter, the experimental results show that the visual quality is improved; and increasing the embedding capacity leads to more noises. Therefore, a better choice of base point and a reduced difference expansion affect the quality of stego image.
Volume: 8
Issue: 4
Page: 2468-2476
Publish at: 2018-08-01

A Novel Study on Bipolar High Voltage Direct Current Transmission Lines Protection Schemes

10.11591/ijece.v8i4.pp1977-1984
Shobha Agarwal , C. K. Panigrahi , Aishwarya Sahoo , Sanitha Mishra
In long dc transmission lines identification of fault is important for transferring a large amount of power. In bipolar Line commutated converter transmission lines are subjected to harsh weather condition so accurate and rapid clearance of fault is essential. A comparative study of the bipolar system with both converters healthy and one converter tripped is studied. Most of the research paper has focussed on transmission line faults in bipolar mode but none of them had focussed when HVDC system works in monopolar mode after the fault. In the proposed scheme the voltage signals are extracted from both poles of the rectifier ends and are processed to identify the faults in transmission lines.The Artificial neural network is utilised in detecting the fault in both bipolar and monopolar system. Since it can identify the relationship between input and output data to detect the fault pattern it can be utilised under all conditions. Moreover, benefits of the proposed method are its accuracy, no requirement of the communication system as it acquires data from one end and has a reach setting of 99%.
Volume: 8
Issue: 4
Page: 1977-1984
Publish at: 2018-08-01
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