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28,188 Article Results

A Modified Diagonal Mesh Shuffle Exchange Interconnection Network

10.11591/ijece.v7i2.pp1042-1050
Akash Punhani , Pardeep Kumar , Nitin Nitin
Interconnection network is an important part of the digital system. The interconnection mainly describes the topology of the network along with the routing algorithm and flow control mechanism. The topology of the network plays an important role on the performance of the system. Mesh interconnection network was the simplest topology, but has the limited bisection bandwidth on the other hand torus and diagonal mesh was having long links. The Modified diagonal mesh network tried to replace the torodial links but was having more average path length so in proposed topology we have tried to improve the average distance using shuffle exchange network over the boundary node. In this paper, we propose the architecture of Modified Diagonal Mesh Shuffle Exchange Interconnection Network. This Modified Diagonal Mesh Shuffle Exchange Interconnection network have been compared with four popular topologies that are simple 2D Mesh, 2D Torus, Diagonal Mesh and Modified Diagonal Mesh Interconnection Network on the four traffic patterns such as Bit Complement traffic, Neighbor traffic, Tornado traffic and Uniform traffic are used for comparisonand performance analysis. We have performed the analysis with a 5% and 10% of hotspot on the Uniform Traffic. The simulation results shows that the proposed topology is performed better on bit complement traffic and can also handle the other traffic up to certain level.
Volume: 7
Issue: 2
Page: 1042-1050
Publish at: 2017-04-01

The Application of Homer Optimization Software to Investigate the Prospects of Hybrid Renewable Energy System in Rural Communities of Sokoto in Nigeria

10.11591/ijece.v7i2.pp596-603
Abdullahi Abubakar Masud
This paper investigates the prospects and cost-effectiveness of implementation of standalone PV/wind system in sokoto state Nigeria. Daily electricity demand, yearly solar radiation and wind speed were applied to determine the optimum sizing of the renewable energy (RE) system. To design optimum RE with proper sizing of system components, meteorological data obtained from the National Aeronautics and Space Administration were applied as input for this study. In Nigeria, sokoto is a region with solar radiation of 6kWh/m2/day and wind speed of 5m/s at 10m above height. Using the Homer optimization software, the optimum integrated RE system is 35.21kW PV, 3 x 25kW wind turbines, 12 x 24V lead acid battery and 17.44kW converter. The system has a total capital cost of $249910.24, the replacement cost of $82914.85 and maintenance cost of $53802.80 for 25 years. Though the initial capital cost is high but the long term benefits are enormous, considering the high cost of implementing rural electrification scheme, coupled with ahike in electricity tariff. There is also a payback period of 5 years. The results imply a standalone PV/wind system is feasible in rural communities of sokoto with 100% pollution free energy system.
Volume: 7
Issue: 2
Page: 596-603
Publish at: 2017-04-01

Artificial Neural Network for Non-Intrusive Electrical Energy Monitoring System

10.11591/ijeecs.v6.i1.pp124-131
Khairell Khazin Kaman , Mahdi Faramarzi , Sallehuddin Ibrahim , Mohd Amri Md Yunus
 This paper discusses non-intrusive electrical energy monitoring (NIEM) system in an effort to minimize electrical energy wastages. To realize the system, an energy meter is used to measure the electrical consumption by electrical appliances. The obtained data were analyzed using a method called multilayer perceptron (MLP) technique of artificial neural network (ANN). The event detection was implemented to identify the type of loads and the power consumption of the load which were identified as fan and lamp. The switching ON and OFF output events of the loads were inputted to MLP in order to test the capability of MLP in classifying the type of loads. The data were divided to 70% for training, 15% for testing, and 15% for validation. The output of the MLP is either ‘1’ for fan or ‘0’ for lamp. In conclusion, MLP with five hidden neurons results obtained the lowest average training time with 2.699 seconds, a small number of epochs with 62 iterations, a min square error of 7.3872×10-5, and a high regression coefficient of 0.99050.
Volume: 6
Issue: 1
Page: 124-131
Publish at: 2017-04-01

Game-Theoretic Channel Allocation in Cognitive Radio Networks

10.11591/ijece.v7i2.pp986-991
Sangsoon Lim
Cognitive radio networks provide dynamic spectrum access techniques to support the increase in spectrum demand. In particular, the spectrum sharing among primary and secondary users can improve spectrum utilization in unused spectrum by primary users. In this paper, we propose a novel game theoretic channel allocation framework to maximize channel utilization in cognitive radio networks. We degisn the utility function based on the co-channel interference among primary and secondary users. In addition, we embed the property of the adjacent channel intererence to consider real wireless environment. The results show that the utility function converges quickly to Nash equilibrium and achieves channel gain by up to 25 dB compared to initial assignment.
Volume: 7
Issue: 2
Page: 986-991
Publish at: 2017-04-01

Evaluation of the Energy Performance of the Amougdoul Wind Farm, Morocco

10.11591/ijece.v7i2.pp692-705
Asma Ezzaidi , Mustapha Elyaqouti , Lahoussine Bouhouch , Ahmed Ihlal
This paper is concerned with the assessment of the the performance of the Amougdoul wind farm. We have determined the Weibull parameters; namely the scale parameter, c (m/s) and shape parameter, k. After that, we have estimated energy output by a wind turbine using two techniques: the useful power calculation method and the method based on the modeling of the power curve, which is respectively 134.5 kW and 194.19 KW corresponding to 27% and 39% of the available wind energy, which confirm that the conversion efficiency does not exceed 40%.
Volume: 7
Issue: 2
Page: 692-705
Publish at: 2017-04-01

Image Processing for Rapidly Eye Detection based on Robust Haar Sliding Window

10.11591/ijece.v7i2.pp823-830
Fitri Utaminingrum , Renaldi Primaswara Praetya , Yuita Arum Sari
Object Detection using Haar Cascade Clasifier widely applied in several devices and applications as a medium of interaction between human and computer such as a tool control that utilizes the detection of eye movements. Obviously speed and precision in the detection process such as eyes, has an effect if implemented on a device. If the eye could not detect accurately, controlling device systems could reach bad detection as well. The proposed method can be used as an approach to detect the eye region of eye based on haar classifier method by means of modifying the direction of sliding window. In which, it was initially placed in the middle position of image on facial area by assuming the location of eyes area in the central region of the image. While the window region of conventional haar cascade scan the whole of image start from the left top corner. From the experiment by using our proposed method, it can speed up the the computation time and improve accuracy significantly reach to 92,4%.
Volume: 7
Issue: 2
Page: 823-830
Publish at: 2017-04-01

An Improved Integrated Hash and Attributed based Encryption Model on High Dimensional Data in Cloud Environment

10.11591/ijece.v7i2.pp950-960
Satheesh K S V A Kavuri , Gangadhara Rao Kancherla , Basaveswararao Bobba
Cloud computing is a distributed architecture where user can store their private, public or any application software components on it. Many cloud based privacy protection solutions have been implemented, however most of them only focus on limited data resources and storage format. Data confidentiality and inefficient data access methods are the major issues which block the cloud users to store their high dimensional data. With more and more cloud based applications are being available and stored on various cloud servers, a novel multi-user based privacy protection mechanism need to design and develop to improve the privacy protection on high dimensional data. In this paper, a novel integrity algorithm with attribute based encryption model was implemented to ensure confidentiality for high dimensional data security on cloud storage. The main objective of this model is to store, transmit and retrieve the high dimensional cloud data with low computational time and high security. Experimental results show that the proposed model has high data scalability, less computational time and low memory usage compared to traditional cloud based privacy protection models.
Volume: 7
Issue: 2
Page: 950-960
Publish at: 2017-04-01

Fault Identification of In-Service Power Transformer using Depolarization Current Analysis

10.11591/.v7i2.pp559-567
M.A. Talib , N.A. Muhamad , Z.A. Malek , B.T. Phung
Preventive diagnostic testing of in-service power transformers require system outage and expert’s knowledge and experiences in interpreting the measurement results. The chemical oil analysis may cause significant variance to measurement results due to the different practices in oil sampling, storage, handling and transportation. Thus, a cost effective measuring technique by means of a simpler method that is able provide an accurate measurement results is highly required. The extended application of Polarization and Depolarization Current (PDC) measurement for characterization of different faults conditions on in-service power transformer has been presented in this paper. The oil sample from in-service power transformers with normal and 3 different faults type conditions were sampled and tested for Dissolved Gases Analysis (DGA) and PDC measurement. The DGA results was used to confirm type of faults inside the transformer while the PDC pattern of oil with normal, partial discharge, overheating and arcing were correlated to the oil sample conditions. The analysis result shows that depolarization current provides significant information to defferenciate fault types in power transformer. Thus this finding provides a new alternative in identifying incipient faults and such knowledge can be used to avoid catastrophic failures of power transformers.
Volume: 7
Issue: 2
Page: 559-567
Publish at: 2017-04-01

Size Reduction and Gain Enhancement of a Microstrip Antenna using Partially Defected Ground Structure and Circular/Cross Slots

10.11591/.v7i2.pp894-898
Nada N. Tawfeeq
Microwave engineers have been known to designedly created defects in the shape of carved out patterns on the ground plane of microstrip circuits and transmission lines for a long time, although their implementations to the antennas are comparatively new. The term Defected Ground Structure (DGS), precisely means a single or finite number of defects. At the beginning, DGS was employed underneath printed feed lines to suppress higher harmonics. Then DGS was directly integrated with antennas to improve the radiation characteristics, gain and to suppress mutual coupling between adjacent elements. Since then, the DGS techniques have been explored extensively and have led to many possible applications in the communication industry. The objective of this paper is to design and investigate microstrip patch antenna that operates at 2.4 GHz for Wireless Local Area Network WLAN IEEE 802.11b/g/n, ,Zigbee, Wireless HART, Bluetooth and several proprietary technologies that operate in the 2.4 GHz band. The design of the proposed antenna involves using partially Defected Ground Structure and circular/cross slots and compare it to the traditional microstrip patch antenna.  The results show improvement in both the gain of 3.45 dB and the S11 response of -22.3 dB along with reduction in the overall dimensions of the antenna. As a conclusion, the performance of the antenna has been improved through the incorporation with the DGS and slots structures regarding the S11 response and the gain. The proposed antenna become more compact. Finally, the radiation pattern of proposed antenna has remained directional in spite of adding slots on the ground plane.
Volume: 7
Issue: 2
Page: 894-898
Publish at: 2017-04-01

Optimizing Tri-Core Permanent-Magnet-Linear-Generator Direct-Drive Wave-Energy-Conversion System Design for Sea Wave Characteristics in South Coast Yogyakarta

10.11591/.v7i2.pp610-618
Fransisco Danang Wijaya , Sarjiya Sarjiya , Muhammad Rifa'i Putra Sugita
According to statistical data, the south coast Yogyakarta has significant ocean wave height which can be used to generate electricity by using wave-energy-converter system. One of the simplest way to convert wave energy to electricity is using direct-drive wave-energy-conversion (WEC) system with permanent-magnet-linear-generator (PMLG). This method is simple because it doesn’t need to convert linear motion to rotational motion. However, PMLG has large electric power losses, has great weight in both of the stator and rotor, and expensive to make. In this paper, a tri-core PMLG was designed. The electric power losses in the winding, translator weight, and manufacturing cost were ideally minimized using multiobjective optimization combined with simulated annealing (SA) algorithm. Then, the design was verified using finite element analysis. The optimized design of this PMLG was simulated using sinusoidal ocean waves which usually occur in the south coast of Yogyakarta to analyze the performance of this linear generator. Simulation result has been shown that this generator can generate 911 watt peak output power at the rated condition and at the optimum load with 81.14% efficiency. This confirms that the optimized design of PMLG is suitable for direct-drive WEC with low power losses and manufacturing cost.
Volume: 7
Issue: 2
Page: 610-618
Publish at: 2017-04-01

Parallel Genetic Algorithms for University Scheduling Problem

10.11591/ijece.v7i2.pp1096-1102
Artan Berisha , Eliot Bytyçi , Ardeshir Tershnjaku
University scheduling timetabling problem, falls into NP hard problems. Re-searchers have tried with many techniques to find the most suitable and fastest way for solving the problem. With the emergence of multi-core systems, the parallel implementation was considered for finding the solution. Our approaches attempt to combine several techniques in two algorithms: coarse grained algorithm and multi thread tournament algorithm. The results obtained from two algorithms are compared, using an algorithm evaluation function. Considering execution time, the coarse grained algorithm performed twice better than the multi thread algorithm.
Volume: 7
Issue: 2
Page: 1096-1102
Publish at: 2017-04-01

Exploring the Design Space of HEVC Inverse Transforms with Dataflow Programming

10.11591/ijeecs.v6.i1.pp104-109
Khoo Zhi Yion , Ab Al-Hadi Ab Rahman
This paper presents the design space exploration of the hardware-based inverse fixed-point integer transform for High Efficiency Video Coding (HEVC). The designs are specified at high-level using CAL dataflow language and automatically synthesized to HDL for FPGA implementation. Several parallel design alternatives are proposed with trade-off between performance and resource. The HEVC transform consists of several independent components from 4x4 to 32x32 discrete cosine transform and 4x4 discrete sine transform. This work explores the strategies to efficiently compute the transforms by applying data parallelism on the different components. Results show that an intermediate version of parallelism, whereby the 4x4 and 8x8 are merged together, and the 16x16 and 32x32 merged together gives the best trade-off between performance and resource. The results presented in this work also give an insight on how the HEVC transform can be designed efficiently in parallel for hardware implementation.
Volume: 6
Issue: 1
Page: 104-109
Publish at: 2017-04-01

Mammography Image Segmentation: Chan-Vese Active Contour and Localised Active Contour Approach

10.11591/ijeecs.v5.i3.pp577-583
Mahfuzah Mustafa , Hana Najwa Omar Rashid , Nor Rul Hasma Abdullah , Rosdiyana Samad , Dwi Pebrianti
Breast cancer is one of the most common diseases diagnosed among female cancer patients. Early detection of breast cancer is needed to reduce the risk of fatality of this disease as no cure has been found yet for this illness. This research is conducted to improve the Gradient Vector Flow (GVF) Snake Active Contour segmentation technique in mammography segmentation. Segmentation of the mammogram image is done to segment lesions existence using Chan-Vese Active Contour and Localized Active Contour. Besides that, the effectiveness of these both methods are then compared and chosen to be the best method. Digital Database of Screening Mammograms (DDSM) is used for the purpose of screening. First, the images undergo pre-processing process using the Gaussian Low Pass Filter to remove unwanted noise. After that, contrast enhancement applied to the images. Segmentation of mammograms is then conducted by using Chan-Vese Active Contour and Localized Active Contour method. The result shows that Chan-Vese technique outperforms Localized Active Contour with 90% accuracy.
Volume: 5
Issue: 3
Page: 577-583
Publish at: 2017-03-01

Human Presence Recognition in a Closed Space by using Cost-effective CO2 Sensor and the Information Gain Processing Method

10.11591/ijeecs.v5.i3.pp549-555
Kimio Oguchi , Ryoya Ozawa
The recent rapid progress in ICT technologies such as smart/intelligent sensor devices, broadband/ubiquitous networks, and Internet of everything (IoT) has advanced the penetration of sensor networks and their applications. The requirements of human daily life, security, energy efficiency, safety, comfort, and ecological, can be achieved with the help of these networks and applications. Traditionally, if we want some information on, for example, environment status, a variety of dedicated sensors is needed. This will increase the number of sensors installed and thus system cost, sensor data traffic loads, and installation difficulty. Therefore, we need to find redundancies in the captured information or interpret the semantics captured by non-dedicated sensors to reduce sensor network overheads. This paper clarifies the feasibility of recognizing human presence in a space by processing information captured by other than dedicated sensors. It proposes a method and implements it as a cost-effective prototype sensor network for a university library. This method processes CO2 concentration, originally designed to check environment status. In the experiment, training data is captured with none, one, or two subjects. The information gain (IG) method is applied to the resulting data, to set thresholds and thus judge the number of people. Human presence (none, one or two people) is accurately recognized from the CO2 concentration data. The experiments clarify that a CO2 sensor in set in a small room to check environment status can recognize the number of humans in the room with more than 70 % accuracy. This eliminates the need for an extra sensor, which reduces sensor network cost.
Volume: 5
Issue: 3
Page: 549-555
Publish at: 2017-03-01

New Sensorless Sliding Mode Control of a Five-phase Permanent Magnet Synchronous Motor Drive Based on Sliding Mode Observer

10.11591/ijpeds.v8.i1.pp184-203
Anissa Hosseyni , Ramzi Trabelsi , Sanjeeve Kumar , Med Faouzi Mimouni , Atif Iqbal
This paper proposes a sensorless sliding mode control (SMC) for a five phase permanent magnet synchronous motor (PMSM) based on a sliding mode observer (SMO). The stability of the proposed strategy is proved in the sense of the Lyapunov theory. The sliding mode controller is designed with an integral switching surface and the sliding mode observer is developed for the estimation of rotor position and rotor speed. The proposed sensorless control strategy exhibits good dynamic response to disturbances. Simulation results are provided to prove the effectiveness of the proposed strategy.
Volume: 8
Issue: 1
Page: 184-203
Publish at: 2017-03-01
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