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27,544 Article Results

An Efficient Cloud Scheduling Algorithm for the Conservation of Energy through Broadcasting

10.11591/ijece.v8i1.pp179-188
Kavita Arjun Sultanpure , Abhishek Gupta , L. S. S. Reddy
Method of broadcasting is the well known operation that is used for providing support to different computing protocols in cloud computing. Attaining energy efficiency is one of the prominent challenges, that is quite significant in the scheduling process that is used in cloud computing as, there are fixed limits that have to be met by the system. In this research paper, we are particularly focusing on the cloud server maintenance and scheduling process and to do so, we are using the interactive broadcasting energy efficient computing technique along with the cloud computing server. Additionally, the remote host machines used for cloud services are dissipating more power and with that they are consuming more and more energy. The effect of the power consumption is one of the main factors for determining the cost of the computing resources. With the idea of using the avoidance technology for assigning the data center resources that dynamically depend on the application demands and supports the cloud computing with the optimization of the servers in use.
Volume: 8
Issue: 1
Page: 179-188
Publish at: 2018-02-01

Multi-objective Optimization of PID Controller using Pareto-based Surrogate Modeling Algorithm for MIMO Evaporator System

10.11591/ijece.v8i1.pp556-565
Amrul Faruq , Mohd Fauzi Nor Shah , Shahrum Shah Abdullah
Most control engineering problems are characterized by several objectives, which have to be satisfied simultaneously. Two widely used methods for finding the optimal solution to such problems are aggregating to a single criterion, and using Pareto-optimal solutions. This paper proposed a Pareto-based Surrogate Modeling Algorithm (PSMA) approach using a combination of Surrogate Modeling (SM) optimization and Pareto-optimal solution to find a fixed-gain, discrete-time Proportional Integral Derivative (PID) controller for a Multi Input Multi Output (MIMO) Forced Circulation Evaporator (FCE) process plant. Experimental results show that a multi-objective, PSMA search was able to give a good approximation to the optimum controller parameters in this case. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) method was also used to optimize the controller parameters and as comparison with PSMA.
Volume: 8
Issue: 1
Page: 556-565
Publish at: 2018-02-01

Optimized Kernel Extreme Learning Machine for Myoelectric Pattern Recognition

10.11591/ijece.v8i1.pp483-496
Khairul Anam , Adel Al-Jumaily
Myoelectric pattern recognition (MPR) is used to detect user’s intention to achieve a smooth interaction between human and machine. The performance of MPR is influenced by the features extracted and the classifier employed. A kernel extreme learning machine especially radial basis function extreme learning machine (RBF-ELM) has emerged as one of the potential classifiers for MPR. However, RBF-ELM should be optimized to work efficiently. This paper proposed an optimization of RBF-ELM parameters using hybridization of particle swarm optimization (PSO) and a wavelet function. These proposed systems are employed to classify finger movements on the amputees and able-bodied subjects using electromyography signals. The experimental results show that the accuracy of the optimized RBF-ELM is 95.71% and 94.27% in the healthy subjects and the amputees, respectively. Meanwhile, the optimization using PSO only attained the average accuracy of 95.53 %, and 92.55 %, on the healthy subjects and the amputees, respectively. The experimental results also show that SW-RBF-ELM achieved the accuracy that is better than other well-known classifiers such as support vector machine (SVM), linear discriminant analysis (LDA) and k-nearest neighbor (kNN).
Volume: 8
Issue: 1
Page: 483-496
Publish at: 2018-02-01

Power Quality Compensation in Distribution System based on Instantaneous Power Theory and Recursive Fuzzy Proportional-Integral Controller

https://ijece.iaescore.com/index.php/IJECE/article/view/9496
Mehrdad Ahmadi Kamarposhti
In this paper, the power quality compensation problems such as current harmonics and system load's reactive power are considered. In this context, we use static distribution synchronous compensator to inject compensation current into the system, which its reference current signals have been derived from the instantaneous power theory. To improve the current control operation and fast tracking of reference signals, a PI recursive controller has been used which is able to reduce to zero tracking error compared to its conventional type. The performance of the controller is delayed for a period; to overcome this problem, the phase rules have been used to adjust the controller parameters to increase the control performance speed. Finally, in simulation we used Matlab / Simulink software, which has been proven to be better than conventional PI controller-based compensation for power quality.
Volume: 8
Issue: 1
Page: 538-543
Publish at: 2018-02-01

Evaluation of Energy Consumption using Receiver–Centric MAC Protocol in Wireless Sensor Networks

10.11591/ijece.v8i1.pp87-93
Ananda Kumar K S , Balakrishna R
At present day’s wireless sensor networks, obtain a lot consideration to researchers. Maximum number of sensor nodes are scattered that can communicate with all others. Reliable data communication and energy consumption are the mainly significant parameters that are required in wireless sensor networks. Many of MAC protocols have been planned to improve the efficiency more by enhancing the throughput and energy consumption. The majority of the presented medium access control protocols to only make available, reliable data delivery or energy efficiency does not offer together at the same time. In this research work the author proposes a novel approach based on Receiver Centric-MAC is implemented using NS2 simulator. Here, the author focuses on the following parametric measures like - energy consumption, reliability and bandwidth. RC-MAC provides high bandwidth without decreasing energy efficiency. The results show that 0.12% of less energy consumption, reliability improved by 20.86% and bandwidth increased by 27.32% of RC-MAC compared with MAC IEEE 802.11.
Volume: 8
Issue: 1
Page: 87-93
Publish at: 2018-02-01

Bit Error Rate (BER) QoS Attribute in Solving Wireless Pricing Scheme on Single Link Multi Service Network

10.11591/ijece.v8i1.pp236-245
Irmeilyana Irmeilyana , Fitri Maya Puspita , Indrawati Indrawati , Rahayu Tamy Agustin
Pricing schemes were set up on multi service network of wireless internet pricing scheme to proposed models applying Bit Error Rate QoS attribute due to requirements for ISP to maximize revenue and provide high quality of service to end users.The model was deigned by improving the original model together with added parameters and variables to the model of multi- service network by setting the base price (α) and premium quality (β) as variables and parameters. LINGO 11.0 were applied to help finding the solution. The results show that the improved models yield maximum revenue for ISP by applying the improved model by setting up a variable α and β as constant as well as by increasing the cost of all the changes in QoS. The QoS attriute BER is proven to achieve the ISP’s goal to maximize the revenue.
Volume: 8
Issue: 1
Page: 236-245
Publish at: 2018-02-01

Coordination of Adaptive Neuro Fuzzy Inference System (ANFIS) and Type-2 Fuzzy Logic System-Power System Stabilizer (T2FLS-PSS) to Improve a Large-scale Power System Stability

10.11591/ijece.v8i1.pp76-86
Agung Budi Muljono , I. M. Ginarsa , I. M. A. Nrartha , A. Dharma
Intelligent control included ANFIS and type-2 fuzzy (T2FLS) controllers grown-up rapidly and these controllers are applied successfully in power system control. Meanwhile, small signal stability problem appear in a large-scale power system (LSPS) due to load fluctuation. If this problem persists, and can not be solved, it will develop blackout on the LSPS. How to improve the LSPS stability due to load fluctuation is done in this research by coordinating of PSS based on ANFIS and T2FLS. The ANFIS parameters are obtained automatically by training process. Meanwhile, the T2FLS parameters are determined based on the knowledge that obtained from the ANFIS parameters. Input membership function (MF) of the ANFIS is 5 Gaussian MFs. On the other hand, input MF of the T2FLS is 3 Gaussian MFs. Results show that the T2FLS-PSS is able to maintain the stability by decreasing peak overshoot for rotor speed and angle. The T2FLS-PSS makes the settling time is shorter for rotor speed and angle on local mode oscillation as well as on inter-area oscillation than conventional/ ANFIS-PSS. Also, the T2FLS-PSS gives better performance than the other PSS when tested on single disturbance and multiple disturbances.
Volume: 8
Issue: 1
Page: 76-86
Publish at: 2018-02-01

Ant Colony Optimization for Optimal Low-Pass State Variable Filter Sizing

10.11591/ijece.v8i1.pp227-235
Kritele Loubna , Benhala Bachir , Zorkani Izeddine
In analog filter design, discrete components values such as resistors (R) and capacitors (C) are selected from the series following constant values chosen. Exhaustive search on all possible combinations for an optimized design is not feasible. In this paper, we present an application of the Ant Colony Optimization technique (ACO) in order to selected optimal values of resistors and capacitors from different manufactured series to satisfy the filter design criteria. Three variants of the Ant Colony Optimization are applied, namely, the AS (Ant System), the MMAS (Min-Max AS) and the ACS (Ant Colony System), for the optimal sizing of the Low-Pass State Variable Filter. SPICE simulations are used to validate the obtained results/performances which are compared with already published works.
Volume: 8
Issue: 1
Page: 227-235
Publish at: 2018-02-01

Mathematical Modelling and Computer Simulation Assist in Designing Non-traditional Types of Precipitators and Separators

10.11591/ijece.v8i1.pp441-449
Milan Bernat , Jaroslav Džmura , Renáta Bernátová , Ľubomr Žáčok , Jan Pavlovkin
The article deals with the application of the method for mathematical modeling and simulation at solving some issues in the area of electrostatic technology. It focuses on the processes in electrostatic separation and precipitation. Computer simulation is highly required for equipment design and for their diagnostics in critical operating states using theoretical calculations and experimental data evaluation. The presented computer models may be applied both by project and design engineers using the most advanced computer-aided design of electrostatic technologies.
Volume: 8
Issue: 1
Page: 441-449
Publish at: 2018-02-01

Image Resolution Enhancement Using Transform

10.11591/ijeecs.v9.i2.pp354-356
Syed Nazeeburrehman , Mohameed Ali Hussain
In this project, interruption based image resolution enhancement technique using Discrete Wavelet Transform (DWT) with high-frequency sub bands obtained is proposed. Input images are decomposed by using DWT in this proposed enhancement technique. Inverse DWT is used to generate a new resolution enhanced image from the interpolation of high-frequency sub band images and the input low-resolution image. Intermediate stage has been proposed for estimating the high frequency sub bands to achieve a sharper image. It has been tested on benchmark images from public database. Peak Signal-To-Noise Ratio (PSNR) and visual results show the dominance of the proposed technique over the predictable and state-of-art image resolution enhancement techniques.
Volume: 9
Issue: 2
Page: 354-356
Publish at: 2018-02-01

Energy Efficient for Web of Things Based on Reconfigurable Smart Quality Management Scheme

10.11591/ijeecs.v9.i2.pp279-281
Prasanna Moorthi N , V Mathivananr
Since the powerful and productive arrangement of water quality observing (WQM) are basic usage for the issue of contaminated water all inclusive, with expanding in the advancement of Wireless Sensor Network (WSN) innovation in the Internet of Things (IoT) condition, ongoing water quality checking is remotely checked by methods for continuous information obtaining, transmission and handling. This paper exhibits a reconfigurable brilliant sensor interface gadget for water quality checking framework in an IoT situation. The brilliant WQM framework comprises of Field Programmable Gate Array (FPGA) outline board, sensors, Zigbee based remote correspondence module and (PC). The FPGA board is the center part of the proposed framework and it is customized in fast incorporated circuit equipment depiction dialect (VHDL) and C programming dialect utilizing Quartus II programming and Qsys instrument. The proposed WQM framework gathers the five parameters of water information, for example, water pH, water level, turbidity, carbon dioxide (CO2) on the surface of water and water temperature in parallel and progressively premise with fast from numerous distinctive sensor hubs.
Volume: 9
Issue: 2
Page: 279-281
Publish at: 2018-02-01

An Influence of Measurement Scale of Predictor Variable on Logistic Regression Modeling and Learning Vector Quntization Modeling for Object Classification

10.11591/ijece.v8i1.pp333-343
Waego Hadi Nugroho , Samingun Handoyo , Yusnita Julyarni Akri
Much real world decision making is based on binary categories of information that agree or disagree, accept or reject, succeed or fail and so on. Information of this category is the output of a classification method that is the domain of statistical field studies (eg Logistic Regression method) and machine learning (eg Learning Vector Quantization (LVQ)). The input argument of a classification method has a very crucial role to the resulting output condition. This paper investigated the influence of various types of input data measurement (interval, ratio, and nominal) to the performance of logistic regression method and LVQ in classifying an object. Logistic regression modeling is done in several stages until a model that meets the suitability model test is obtained. Modeling on LVQ was tested on several codebook sizes and selected the most optimal LVQ model. The best model of each method compared to its performance on object classification based on Hit Ratio indicator. In logistic regression model obtained 2 models that meet the model suitability test is a model with predictive variables scaled interval and nominal, while in LVQ modeling obtained 3 pieces of the most optimal model with a different codebook. In the data with interval-scale predictor variable, the performance of both methods is the same. The performance of both models is just as bad when the data have the predictor variables of the nominal scale. In the data with predictor variable has ratio scale, the LVQ method able to produce moderate enough performance, while on logistic regression modeling is not obtained the model that meet model suitability test. Thus if the input dataset has interval or ratio-scale predictor variables than it is preferable to use the LVQ method for modeling the object classification.
Volume: 8
Issue: 1
Page: 333-343
Publish at: 2018-02-01

Extremely Vibrant Routing Scheme for Mobile Adhoc Network

10.11591/ijeecs.v9.i2.pp306-310
Syes Abdul Syed S , T Senthil Kumaran
This paper aims to improve the performance of the traditional routing protocol for MANET such as DSR and AODV in terms of delay and overhead. The proposed routing scheme is called as Extremely Vibrant Routing (EVR) which adopts with the highly dynamic environment of MANET. The link residual life is estimated to reduce the link failure before forwarding data through a node. The velocity of the moving mode is considered while choosing the next forwarder node. This enables the EVR to decrease the delay in the network. The proposed routing scheme reduces routing overhead and reduces the delay. This scheme reduces the link failure too. The performance is evaluated by using the simulation results obtained by using NS2 simulator.
Volume: 9
Issue: 2
Page: 306-310
Publish at: 2018-02-01

Efficiency of Flat File Database Approach in Data Storage and Data Extraction for Big Data

10.11591/ijeecs.v9.i2.pp460-473
Mohd Kamir Yusof , Mustafa Man
Big data is the latest industry buzzword to describe large volume of structured and unstructured data that can be difficult to process and analyze. Most of organization looking for the best approach to manage and analyze the large volume of data especially in making a decision. XML and JSON are chosen by many organization because of powerful approach during retrieval and storage processes. However, these approaches, the execution time for retrieving large volume of data are still considerably inefficient due to several factors. In this contribution, three databases approaches namely Extensible Markup Language (XML), Java Object Notation (JSON) and Flat File database approach were investigated to evaluate their suitability for handling thousands records of publication data. The results showed flat file is the best choice for query retrieving speed and CPU usage. These are essential to cope with the characteristics of publication’s data. Whilst, XML, JSON and Flat File database approach technologies are relatively new to date in comparison to the relational database. Indeed, Text File Format technology demonstrates greater potential to become a key database technology for handling huge data due to increase of data annually.
Volume: 9
Issue: 2
Page: 460-473
Publish at: 2018-02-01

A Self-Tuned Simulated Annealing Algorithm Using Hidden Markov Model

10.11591/ijece.v8i1.pp291-298
Mohamed Lalaoui , Abdellatif El Afia , Raddouane Chiheb
Simulated Annealing algorithm (SA) is a well-known probabilistic heuristic. It mimics the annealing process in metallurgy to approximate the global minimum of an optimization problem. The SA has many parameters which need to be tuned manually when applied to a specific problem. The tuning may be difficult and time-consuming. This paper aims to overcome this difficulty by using a self-tuning approach based on a machine learning algorithm called Hidden Markov Model (HMM). The main idea is allowing the SA to adapt his own cooling law at each iteration, according to the search history. An experiment was performed on many benchmark functions to show the efficiency of this approach compared to the classical one.
Volume: 8
Issue: 1
Page: 291-298
Publish at: 2018-02-01
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