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International Journal of Electrical and Computer Engineering

IJECE
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Published by Institute of Advanced Engineering and Science

ISSN : 20888708 EISSN : 27222578 DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering

International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.

Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)

Articles 115 Documents

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Search results for , issue "Vol 10, No 3: June 2020" : 115 Documents clear

Predictive geospatial analytics using principal component regression Kyilai Lai Khine; ThiThi Soe Nyunt
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Nowadays, exponential growth in geospatial or spatial data all over the globe, geospatial data analytics is absolutely deserved to pay attention in manipulating voluminous amount of geodata in various forms increasing with high velocity. In addition, dimensionality reduction has been playing a key role in high-dimensional big data sets including spatial data sets which are continuously growing not only in observations but also in features or dimensions. In this paper, predictive analytics on geospatial big data using Principal Component Regression (PCR), traditional Multiple Linear Regression (MLR) model improved with Principal Component Analysis (PCA), is implemented on distributed, parallel big data processing platform. The main objective of the system is to improve the predictive power of MLR model combined with PCA which reduces insignificant and irrelevant variables or dimensions of that model. Moreover, it is contributed to present how data mining and machine learning approaches can be efficiently utilized in predictive geospatial data analytics. For experimentation, OpenStreetMap (OSM) data is applied to develop a one-way road prediction for city Yangon, Myanmar. Experimental results show that hybrid approach of PCA and MLR can be efficiently utilized not only in road prediction using OSM data but also in improvement of traditional MLR model.

Fiber optics based schemes modeling and simulation of QoS for Wi-Fi scenarios using OPNET modeler Suhad Hasan Rhaif; Adnan Hussein Ali; Rana K. Abdulnabi; Ali Abdulwahhab Abdulrazzaq
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Wireless Fidelity (Wi-Fi) network is created on the IEEE 802.11 standard. Connections for local devices in homes and business arenas are provided by Wi-Fi units. With the growing demand as well as penetration of wireless services, the wireless networks users now assume Quality of Service (QoS) besides performances comparable to what is accessible from secure networks. In this paper, OPNET Modeler is used as module and for the simulation of a fiber optic-based Wi-Fi network within a fixed local area network. The aim of this paper is to evaluate their Quality of service (QoS) performances in terms of Wi-Fi voice-packet delay and End-to-End for both Wi-Fi base fiber and Wi-Fi base line. Many scenarios, with same Physical and MAC parameters, have many subnet networks are implementing with fiber optics baseline in addition to Wi-Fi baseline, were created in the network OPNET simulation tool for obtaining the results. The results of simulation reveal that base line demonstrated more delay than base fiber.

Objective functions modification of GA optimized PID controller for brushed DC motor A.A.M. Zahir; Syed Sahal Nazli Alhady; A.A.A Wahab; M.F. Ahmad
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

PID Optimization by Genetic Algorithm or any intelligent optimization method is widely being used recently. The main issue is to select a suitable objective function based on error criteria. Original error criteria that is widely being used such as ITAE, ISE, ITSE and IAE is insufficient in enhancing some of the performance parameter. Parameter such as settling time, rise time, percentage of overshoot, and steady state error is included in the objective function. Weightage is added into these parameters based on users’ performance requirement. Based on the results, modified error criteria show improvement in all performance parameter after being modified. All of the error criteria produce 0% overshoot, 29.51%-39.44% shorter rise time, 21.11%-42.98% better settling time, 10% to 53.76% reduction in steady state error. The performance of modified objective function in minimizing the error signal is reduced. It can be concluded that modification of objective function by adding performance parameter into consideration could improve the performance of rise time, settling time, overshoot percentage, and steady state error

Enhanced direct sequence spread spectrum (eDSSS) Method to Mitigate SINR mismatch in LTE-Wi-Fi integrated networks Azita Laily Yusof; Ainnur Eiza Azhar; Norsuzila Ya'acob
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Demand of data usage and increase of subscribers in Long Term Evolution (LTE) has urged Third Group Partnership Project (3GPP) to find a solution of traffic data growth. In Release 12, the 3GPP introduced Wi-Fi as an alternative to ease the heavy traffic at the LTE base station in dense areas. In contrary with the traffic offloading, Wi-Fi users suffer the worst network degradation because of co-channel interference at frequency 2.4GHz due to collided with LTE band 40. Interference management in LTE-Wi-Fi integrated network is crucial as it affect user’s experiences and services. In this paper, we enhanced a method which is Direct Sequence Spread Spectrum (DSSS) to improve user’s performance in LTE-Wi-Fi network. The DSSS has advantages such as more robust and ability to expand to higher data rates. We introduce a new coefficient called as chip rate coefficient (α) to investigate Signal-to-Interference-Noise Ratio (SINR) expression for User Equipments (UEs) in LTE-Wi-Fi networks. The simulation results discovered that proposed α with value of 0.2 gave the optimum improvement of SINR for LTE and Wi-Fi users. By modifying the SINR expression of the standard DSSS, SINR values at MUE and WUE show better improvement with 4.69% and 17.94%, respectively.

A robust diagnosis method for speed sensor fault based on stator currents in the RFOC induction motor drive Cuong Dinh Tran; Pavel Brandstetter; Minh Chau Huu Nguyen; Sang Dang Ho; Bach Hoang Dinh; Phuong Nhat Pham
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

A valid diagnosis method for the speed sensor failure (SSF) is an essential requirement to ensure the reliability of Fault-Tolerant Control (FTC) models in induction motor drive (IMD) systems. Most recent researches have focused on directly comparing the measured and estimated rotor speed signal to detect the speed sensor fault. However, using that such estimated value in both the fault diagnosis and the controller reconfiguration phases leads to the insufficient performance of FTC modes. In this paper, a novel diagnosis-technique based on the stator current model combined with a confusion prevention condition is proposed to detect the failure states of the speed sensor in the IMD systems. It helps the FTC mode to separate between the diagnosis and reconfiguration phases against a speed sensor fault. This proposed SSF diagnosis method can also effectively apply for IMs’ applications at the low-speed range where the speed sensor signal often suffers from noise. MATLAB/Simulink software has been used to implement the simulations in various speed ranges. The achieved results have demonstrated the capability and effectiveness of the proposed SSF method against speed sensor faults.

Network efficiency enhancement by reactive channel state based allocation scheme Umesh G. B.; M. N. Shanmukha Swamy
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Now a day the large MIMO has considered as the efficient approach to improve the spectral and energy efficiency at WMN. However, the PC is a big issue that caused by reusing similar pilot sequence at cells, which also restrict the performance of massive MIMO network. Here, we give the alternative answer, where each of UEs required allotting a channel sequences before passing the payload data, so as to avoid the channel collision of inter-cell. Our proposed protocol will ready to determine the channel collisions in distributed and scalable process, however giving unique properties of the large MIMO channels. Here we have proposed a RCSA (Reactive channel state based allocation) scheme, which will very productively work with the RAP blockers at large network of MIMO. The position of time-frequency of RAP blocks is modified in the middle of the adjacent cells, because of this design decision the RAP defend from the hardest types of interference at inter-cell. Further, to validate the performance of our proposed scheme it will be compared with other existing technique.

Estimation of TRMM rainfall for landslide occurrences based on rainfall threshold analysis Noraisyah Tajudin; Norsuzila Ya’acob; Darmawaty Mohd Ali; Nor Aizam Adnan
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Landslide can be triggered by intense or prolonged rainfall. Precipitation data obtained from ground-based observation is very accurate and commonly used to do analysis and landslide prediction. However, this approach is costly with its own limitation due to lack of density of ground station, especially in mountain area. As an alternative, satellite derived rainfall techniques have become more favorable to overcome these limitations. Moreover, the satellite derived rainfall estimation needs to be validated on its accuracy and its capability to predict landslide which presumably triggered by rainfall. This paper presents the investigation of using the TRMM-3B42V7 data in comparison to the available rain-gauge data in Ulu Kelang, Selangor. The monthly average rainfall, cumulative rainfall and rainfall threshold analysis from 1998 to 2011 is compared using quantitative statistical criteria (Pearson correlation, bias, root mean square error, mean different and mean). The results from analysis showed that there is a significant and strong positive correlation between the TRMM 3B42V7 and rain gauge data. The threshold derivative from the satellite products is lower than the rain gauge measurement. The findings indicated that the proposed method can be applied using TRMM satellite estimates products to derive rainfall threshold for the possible landslide occurrence.

Advanced location-based IPv6 address for the node of wireless sensor network Mohammed Nazar Hussein; Raed Abdulla; Thomas O’ Daniel; Maythem Abbas
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Fields such as military, transportation applications, human services, smart cities and many others utilized Wireless Sensor Network (WSN) in their operations. Despite its beneficial use, occurrence of obstacles is inevitable. From the sensed data, the randomly nodes distribution will produce multiple benefits from self-configuration and regular positioning reporting. Lately, localization and tracking issues have received a remarkable attention in WSNs, as accomplishing high localization accuracy when low energy is used, is much needed. In this paper, a new method and standards-compliant scheme according to the incorporation of GPS location data into the IPv6 address of WSN nodes is suggested. The suggestion is likewise others which depends on ground-truth anchor nodes, with a difference of using the network address to deliver the information. The findings from the results revealed that perfect GPS coordinates can be conducted in the IPv6 address as well as with the transmission radius of the node, and the information is significantly adequate to predict a node’s location. The location scheme performance is assessed in OMNet++ simulation according to the positioning error and the power metrics used. Moreover, some improvement practices to increase the precision of the node location are suggested.

A hybrid artificial neural network - genetic algorithm for load shedding Le Trong Nghia; Quyen Huy Anh; Phung Trieu Tan; N Thai An
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

This paper proposes the method of applying Artificial Neural Network (ANN) with Back Propagation (BP) algorithm in combination or hybrid with Genetic Algorithm (GA) to propose load shedding strategies in the power system. The Genetic Algorithm is used to support the training of Back Propagation Neural Networks (BPNN) to improve regression ability, minimize errors and reduce the training time. Besides, the Relief algorithm is used to reduce the number of input variables of the neural network. The minimum load shedding with consideration of the primary and secondary control is calculated to restore the frequency of the electrical system. The distribution of power load shedding at each load bus of the system based on the phase electrical distance between the outage generator and the load buses. The simulation results have been verified through using MATLAB and PowerWorld software systems. The results show that the Hybrid Gen-Bayesian algorithm (GA-Trainbr) has a remarkable superiority in accuracy as well as training time. The effectiveness of the proposed method is tested on the IEEE 37 bus 9 generators standard system diagram showing the effectiveness of the proposed method.

Accurate leakage current models for MOSFET nanoscale devices Abdoul Rjoub; Mamoun Mistarihi; Nedal Al Taradeh
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

This paper underlines a closed forms of MOSFET transistor’sleakage current mechanisms inthe sub 100nmparadigm.The incorporation of draininduced barrier lowering (DIBL), Gate Induced Drain Lowering (GIDL) and body effect (m) on the sub-threshold leakage (Isub) wasinvestigated in detail. The Band-To-Band Tunneling (IBTBT) due to the source and Drain PN reverse junction were also modeled witha close and accurate model using a rectangularapproximation method (RJA). The three types of gate leakage (IG) were also modeled and analyzed for parasitic (IGO), inversion channel (IGC), and gate substrate (IGB).In addition, the leakage resources due to the aggressive reduction in the oxide thickness (

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Tole Sutikno

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

Phone -

Journal Mail Official ijece@iaesjournal.com

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

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Abstract

Abstract

Abstract

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Abstract

Abstract

Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA