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29,939 Article Results

Single line to ground fault detection and location in medium voltage distribution system network based on neural network

10.11591/ijeecs.v23.i2.pp621-632
Ahmed K. Abbas , Sumaya Hamad , Nuha A. Hamad
The aim of this project was to detect and locate the single ground failure lines that occurs in medium voltage (MV) networks on the transmission lines (TL). Compared with anther faults, single line-to-ground (SLG) is the most frequent. The neural network (NN) algorithm was advanced in order to discover and locate SLG faults. The network is simulated through simulated numerous defects at various locations, as well as changing earth resistance from (or 100 Ω) to TL to gather all of the data. In the electromagnetic transients’ program (EMTP) program software, the existing fault have been measured. In addition, the waves were evaluated by utilize MATLAP's fastfourier-transform to calculate the waves of top three of them, On the MV network are fifty hundred faults are simulated all data in the neural network at MATLAB were trained and examined to improve the NN algorithm according to this data. Comparing all the simulated location faults that have been applied with those all locations detected in the NN algorithm, the overall error between them has been found to be very low and not to exceed 0.7. The Simulink circuit was created from this algorithm and checked in order to predict each failure could occur in the future in the MV network.
Volume: 23
Issue: 2
Page: 621-632
Publish at: 2021-08-01

A fully integrated violence detection system using CNN and LSTM

10.11591/ijece.v11i4.pp3374-3380
Sarthak Sharma , B. Sudharsan , Saamaja Naraharisetti , Vimarsh Trehan , Kayalvizhi Jayavel
Recently, the number of violence-related cases in places such as remote roads, pathways, shopping malls, elevators, sports stadiums, and liquor shops, has increased drastically which are unfortunately discovered only after it’s too late. The aim is to create a complete system that can perform real-time video analysis which will help recognize the presence of any violent activities and notify the same to the concerned authority, such as the police department of the corresponding area. Using the deep learning networks CNN and LSTM along with a well-defined system architecture, we have achieved an efficient solution that can be used for real-time analysis of video footage so that the concerned authority can monitor the situation through a mobile application that can notify about an occurrence of a violent event immediately.
Volume: 11
Issue: 4
Page: 3374-3380
Publish at: 2021-08-01

Data mining techniques for lung and breast cancer diagnosis: A review

10.11591/ijict.v10i2.pp93-103
Bakhan Tofiq Ahmed
Today, cancer counted as the riskier disease than the other diseases in the globe. There are many cancer forms like leukemia, skin cancer, and stomach cancer but lung and breast cancer are the most common forms that many people suffered from. Cancer is the disease that cell has grown rapidly and abnormally that is why treating it is somehow tough in some cases but it can be controlled if it is detected in the initial stage. Data-mining classification algorithms had a vital role in predicting and recognizing both benign and malignant cell. Several classifiers are available to classify the usual and unusual cells such as decision-tree, artificial-neural net, SVM, and KNN. This paper presents a systematic review about the most well-known data-mining classification algorithms for lung and breast cancer diagnose. A brief review about KDD and the data-mining concept has demonstrated. The Decision-Tree (D-Tree), ANN, Support-vector-machine, and naïve Bayes classifier that is widely utilized in the biomedical field has been reviewed along with the some algorithms such as C4.5, Cart, and Iterative -Dichotomiser 3 ‘ID3’. A comparison has been done among various reviewed papers in terms of accuracy that used various data-mining classification algorithms to propose the lung and breast cancer diagnosis system. The experimental results of the reviewed papers showed that the Multilayer Perceptron (MLP) and Logistic Regression (LR) gave a higher accuracy of 99.04% and 98.1%, respectively.
Volume: 10
Issue: 2
Page: 93-103
Publish at: 2021-08-01

Optimal path discovery for two moving sinks with a common junction in a wireless sensor network

10.11591/ijeecs.v23.i2.pp879-889
Satish Tunga , Sadashiva V. Chakrasali , N. Shylashree , Latha B. N. , Mamatha A. S.
A new algorithm is described for determining the optimal round-trip paths for two moving sinks in a wireless sensor network. The algorithm uses binary integer programming to select two non-overlapping shortest paths except having a common junction node to cover all the sensor nodes. The two paths are balanced as nearly equal as possible. That is the sensor nodes along each path are equal or differ by just one depending on whether the total number of sensor nodes excluding the junction node is even or odd. In this method, both the path lengths are made equal or very nearly equal while the total length is minimized. This integrated approach is a novel and unique solution to solve the dual moving sink path problem in a wireless sensor network.
Volume: 23
Issue: 2
Page: 879-889
Publish at: 2021-08-01

A smart management system of electric vehicles charging plans on the highway charging stations

10.11591/ijeecs.v23.i2.pp752-759
Ibrahim El-Fedany , Driss Kiouach , Rachid Alaoui
Electric vehicles (EVs) are seen as one of the principal pillars of smart transportation to relieve the airborne pollution induced by fossil CO2 emissions. However, the battery limit, especially where the journey is with a long-distance road remains the most formidable obstacle to the large-scale use of EVs. To overcome the issue of prolonged waiting charging time due to the large number of EVs may have a charging plan at the same charging station (CS) along the highway, we propose a communication system to manage the EVs charging demands. The architecture system contains a smart scheduling algorithm to minimize trip time including waiting time, previous reservations and energyare needed to reach the destination. Moreover, an automatic mechanism for updating reservation is integrated to adjust the EVs charging plans. The results of the evaluation under the Moroccan highway scenario connecting Rabat and Agadir show the effectiveness of our proposal system. 
Volume: 23
Issue: 2
Page: 752-759
Publish at: 2021-08-01

Smart element aware gate controller for intelligent wheeled robot navigation

10.11591/ijece.v11i4.pp3022-3031
Nadia Adnan Shiltagh Al-Jamali , Mahmood Z. Abdullah
The directing of a wheeled robot in an unknown moving environment with physical barriers is a difficult proposition. In particular, having an optimal or near-optimal path that avoids obstacles is a major challenge. In this paper, a modified neuro-controller mechanism is proposed for controlling the movement of an indoor mobile robot. The proposed mechanism is based on the design of a modified Elman neural network (MENN) with an effective element aware gate (MEEG) as the neuro-controller. This controller is updated to overcome the rigid and dynamic barriers in the indoor area. The proposed controller is implemented with a mobile robot known as Khepera IV in a practical manner. The practical results demonstrate that the proposed mechanism is very efficient in terms of providing shortest distance to reach the goal with maximum velocity as compared with the MENN. Specifically, the MEEG is better than MENN in minimizing the error rate by 58.33%.
Volume: 11
Issue: 4
Page: 3022-3031
Publish at: 2021-08-01

Four-leg active power filter control with SUI-PI controller

10.11591/ijece.v11i4.pp2768-2778
Mohamed M. El-sotouhy , Ahmed A. Mansour , Mostafa I. Marei , Aziza M. Zaki , Ahmed A. EL-Sattar
Four-leg active power filter is considered one of the greatest vital active filters that are frequently used in industrial applications, especially those that need to be controlled in each individual phase. Also, to control the neutral current that created because of a lot of unbalanced and non-linear loads. In this paper, the used active filter was controlled by a proposed control method which can achieve simplicity and intelligence at the same time. The novelty of this paper is using the proposed controller with Four-leg active power filter. This controller relies on instantaneous reactive power theory, which used to create the required currents that are injected into the network via the used active filter to remove the problems created by unbalanced and non-linear loads. It is also maintained that the current source a pure sinusoidal wave. The system is implemented on MATLAB/Simulink. The simulation results proved the preference of the proposed controller than the conventional proportional-integration controller, where it reduced the percentage of total harmonic distortion for the current source.
Volume: 11
Issue: 4
Page: 2768-2778
Publish at: 2021-08-01

Improved LEACH protocol for increasing the lifetime of WSNs

10.11591/ijece.v11i4.pp3106-3113
Ikram Daanoune , Abdennaceur Baghdad , Abdelhakim Ballouk
Recently, wireless sensor network (WSN) is taking a high place in several applications: military, industry, and environment. The importance of WSNs in current applications makes the WSNs the most developed technology at the research level and especially in the field of communication and computing. However, WSN’s performance deals with a number of challenges. Energy consumption is the most considerable for many researchers because nodes use energy to collect, treat, and send data, but they have restricted energy. For this reason, numerous efficient energy routing protocols have been developed to save the consumption of power. Low energy adaptive clustering hierarchy (LEACH) is considered as the most attractive one in WSNs. In the present document, we evaluate the LEACH approach effectiveness in the cluster-head (CH) choosing and in data transmission, then we propose an enhanced protocol. The proposed algorithm aims to improve energy consumption and prolong the lifetime of WSN through selecting CHs depending on the remaining power, balancing the number of nodes in clusters, determining abandoned nodes in order to send their data to the sink. Then CHs choose the optimal path to achieve the sink. Simulation results exhibit that the enhanced method can decrease the consumption of energy and prolong the life-cycle of the network.
Volume: 11
Issue: 4
Page: 3106-3113
Publish at: 2021-08-01

Levenberg–Marquart logistic deep neural learning based energy efficient and load balanced routing in MANET

10.11591/ijeecs.v23.i2.pp1002-1010
A. Sangeetha , T. Rajendran
As the advent of new technologies grows, the deployment of mobile ad hoc networks (MANET) becomes increasingly popular in many application areas. In addition, all the nodes in MANET are battery operated and the node mobility affects the path stability and creates excessive traffic leads to higher utilization of energy, data loss which degrades the performance of routing. So, in this paper we propose Levenberg–Marquardt logistic deep neural learning based energy efficient and load balanced routing (LLDNL-EELBR) which is a machine learning method to deeply analyze the mobile nodes to calculate residual load and energy and it also uses logistic activation function to select the mobile node having higher residual energy and residual load to route the data packet. Experimental evaluations of three methods (LLDNL-EELBR, multipath battery and mobility-aware routing scheme (MBMA-OLSR) and opportunistic routing with gradient forwarding for MANETs (ORGMA)) were done and the result reveals that LLDNL-EELBR method is able to increase the through put and minimizes the delay and energy consumption in MANET when compared to works under consideration. 
Volume: 23
Issue: 2
Page: 1002-1010
Publish at: 2021-08-01

One input voltage and three output voltage universal biquad filters with orthogonal tune of frequency and bandwidth

10.11591/ijece.v11i4.pp2962-2973
May Phu Pwint Wai , Amornchai Chaichana , Winai Jaikla , Surapong Siripongdee , Peerawut Suwanjan
This research paper contributes the one input three output voltage mode universal biquad filters with linear and electronic control of the natural frequency (w0), using two commercially available ICs, LT1228s as active device with two grounded capacitors, five resistors. The presented universal biquad filters can simultaneously provide three voltage-mode filtering functions, low-pass (LP), high-pass (HP) and band-pass (BP) without changing the circuit architecture. Furthermore, the first presented biquad filter provides low impedance at HP, BP voltage output nodes and LP, BP output voltage nodes are low impedance for the second proposed filter which is easy cascade ability with other voltage mode circuits without the employment of buffer circuits. The quality factor (Q) of both proposed filters is orthogonally adjusted from the passband voltage gain and w0. The proposed filters are simulated and experimented with commercially accessible ICs, LT1228. The simulated and experimental results demonstrate the filtering performances.
Volume: 11
Issue: 4
Page: 2962-2973
Publish at: 2021-08-01

Efficient reconfigurable architecture for moving object detection with motion compensation

10.11591/ijeecs.v23.i2.pp802-810
Sridevi N. , M. Meenakshi
The detection and tracking of object in large data surveillance requires a proper motion estimation and compensation techniques which are generally used to detect accurate movement from video stream. In this paper, a novel hardware level architecture involving motion detection, estimation, and compensation is proposed for real-time implementation. The motion vectors are obtained using 16×16 sub-blocks with a novel parallel D flip flop architecture in this work to arrive at an optimised architecture. The sum of absolute difference (SAD) is then calculated by optimized absolute difference and adder blocks designed using kogge-stone adder which helps in improving the speed of the architecture. The controller block is designed by finite state machine model used for synchronization of all the operations. Further, the comparator and compensation blocks are optimized by using basic logical elements and the Kogge-stone adder. Finally, the proposed architecture is implemented on Zynq Z7-10 field-programmable gate array (FPGA) and simulated using System Generator tool for real time traffic signal. The hardware and software parameters are compared with the existing techniques which shows that the proposed architecture is efficient than existing methods of design.
Volume: 23
Issue: 2
Page: 802-810
Publish at: 2021-08-01

Indoor positioning utilizing bluetooth low energy RSSI on LoRa system

10.11591/ijeecs.v23.i2.pp927-937
Kavetha Suseenthiran , Abd Shukur Ja'afar , Ku Wei Heng , Mohamad Zoinol Abidin Abd Aziz , Azmi Awang Md Isa , Siti Huzaimah Husin , Nik Mohd Zarifie Hashim
Indoor positioning systems has become popular in this era where it is a network of devices used to locate people or object especially in indoor environment instead of satellite-based positioning. The satellite-based positioning global positioning system (GPS) signal is affected and loss incurred by the wall of the building causes the GPS lack of precision which leads to large positioning error. As a solution to the indoor area coverage problem, an indoor positioning based on bluetooth low energy (BLE) and long range (LoRa) system utilising the receive signal strength indicator (RSSI) is proposed, designed and tested. In this project, the prototype of indoor positioning system is built using node MCU ESP 32, LoRa nodes and BLE beacons. The node MCU ESP 32 will collect RSSI data from each BLE beacons that deployed at decided position around the area. Then, linear regression algorithm will be used in distance estimation. Next, particle filteris implemented to overcome the multipath fading effect and the trilateration technique is applied to estimate the user’s location. The estimated location is compared to the actual position to analyze the root mean square error (RMSE) and cumulative distribution function (CDF). Based on the experiment result, implementing the particle filter reduces the error of location accuracy. The particle filter achieves accuracy with 90% of the time the location error is lower than 2.6 meters.
Volume: 23
Issue: 2
Page: 927-937
Publish at: 2021-08-01

Implementation of SHE-PWM technique for single-phase inverter based on Arduino

10.11591/ijece.v11i4.pp2907-2915
Laith A. Mohammed , Taha A. Husain , Ahmed M. T. Ibraheem
This paper presents design and practical implementation of single-phase inverter based on selective harmonic elimination-pulse width modulation (SHE-PWM) technique. Microcontroller mega type Arduino used as a controller for producing the gate pulses. The optimized switching angles determination results in wide range of output voltage. Depending on number of switching angles, the lower order harmonics (LOHs) can be eliminated to improve the output voltage waveform. A comparison study using MATLAB/Simulink for sinusoidal-PWM and SHE-PWM techniques, which shows for the same LOH in the output voltage waveform, the SHE-PWM has less number of pulses per half cycle than sinusoidal-PWM strategy. The reduction in number of pulses results less switching losses. The simulation done using ten switching angles to drive R-L load. A prototype of SHE-PWM inverter with R-L load is used to validate the simulation results.
Volume: 11
Issue: 4
Page: 2907-2915
Publish at: 2021-08-01

A review on supervised learning methodologies for detection of exudates in diabetic retinopathy

10.11591/ijeecs.v23.i2.pp837-846
Ujwala W. Wasekar , R. K. Bathla
Diabetic retinopathy has become one of the major reasons for blindness in the world. Early and precise diagnosis of the disease may save one’s eyesight from irreversible damage. Manual detection of lesions is time consuming and may not be as accurate as desirable. Many automated systems have been developed recently to help ophthalmologists in their endeavors. Exudates are one of the early signs of manifestation of diabetic retinopathy. In this paper, the methodologies detecting exudates in retinal fundus images were reviewed. These methods were categorized into deep learning, machine learning and methods primarily focusing on image processing techniques. The comprehensive view of the performances of the methods was given. Several datasets were described briefly. Most of the researchers preferred combination of multiple publically available databases. Also, the potential areas of research were discussed. It was found that sensitivity which identifies the abnormal images correctly, is the most widely used performance measure. The study will be helpful to the researchers wanting to explore more in this field.
Volume: 23
Issue: 2
Page: 837-846
Publish at: 2021-08-01

Design and implementation of bi-directional converter with internet of things control based reading

10.11591/ijeecs.v23.i2.pp938-952
Wisam Dawood Abdullah , Raad Z. Homod , Abdulbasit H. Ahmed
In this paper, a new technique to monitor and control bidirectional DC-DC converter was designed and implemented precisely. A prototype of a complete system is verified with efficient communication capabilities. This system is realized by integrating the internet of things (IoT) operating system and the bidirectional DC-DC converter. The IoT communication facilities further develop and extend the platform for this system. The DC-DC converter with the soft switching technique will then convert the battery voltage to a high voltage of 380V inverter bus in emergencies via boost converter mode. High-frequency toroidal transformer has been used for power level shifting and isolation between the primary and secondary sides of the transformer. The closed-loop control scheme is implemented in software by using a high-performance 32-bit STM32 micro controller. IoT technique is used to find current, voltage and perform the communication smoothly through Wi-Fi sensors to complete the design of the system. The results of the proposed system prove the effectiveness of the proposed system with high-performance specifications.
Volume: 23
Issue: 2
Page: 938-952
Publish at: 2021-08-01
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