Bulletin of Electrical Engineering and Informatics
Bulletin of Electrical Engineering and Informatics ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication, computer engineering, computer science, information technology and informatics from the global world. The journal publishes original papers in the field of electrical (power), electronics, instrumentation & control, telecommunication and computer engineering; computer science; information technology and informatics. Authors must strictly follow the guide for authors. Please read these instructions carefully and follow them strictly. In this way you will help ensure that the review and publication of your paper is as efficient and quick as possible. The editors reserve the right to reject manuscripts that are not in accordance with these instructions.
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539 Documents
<![CDATA[Parasitic consideration for differential capacitive sensor ]]>
<![CDATA[Nurul Arfah Che Mustapha]]>;
<![CDATA[A. H. M. Zahirul Alam]]>;
<![CDATA[Sheroz Khan]]>;
<![CDATA[Amelia Wong Azman]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v8i3.1526
<![CDATA[Parasitic integration for a single supply differential capacitive sensing technique is presented in this paper. In real capacitive sensor measurement, parasitic impedance exists in its measurement. This paper objective is to study the effect of capacitive and resistive parasitic to the capacitive sensor circuit. The differential capacitive sensor circuit derivation theory is elaborated first. Then, comparison is made using simulation. Test was carried out using frequency from 40 kHz up to 400 kHz. Result is presented and have shown good linearity of 0.99984 at 300 kHz, R-squared value. This capacitive sensor is expected to be used for energy harvesting application.]]>
<![CDATA[Velocity control of a two-wheeled inverted pendulum mobile robot: a fuzzy model-based approach ]]>
<![CDATA[Mustapha Muhammad]]>;
<![CDATA[Amir A. Bature]]>;
<![CDATA[Umar Zangina]]>;
<![CDATA[Salinda Buyamin]]>;
<![CDATA[Anita Ahmad]]>;
<![CDATA[Mohamad A. Shamsudin]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v8i3.1594
<![CDATA[This paper presents the design of a fuzzy tracking controller for balancing and velocity control of a Two-Wheeled Inverted Pendulum (TWIP) mobile robot based on its Takagi-Sugino (T-S) fuzzy model, fuzzy Lyapunov function and non-parallel distributed compensation (non-PDC) control law. The T-S fuzzy model of the TWIP mobile robot was developed from its nonlinear dynamical equations of motion. Stabilization conditions in a form of linear matrix inequalities (LMIs) were derived based on the T-S fuzzy model of the TWIP mobile robot, a fuzzy Lyapunov function and a non-PDC control law. Based on the derived stabilization conditions and the T-S fuzzy model of the TWIP mobile robot, a state feedback velocity tracking controller was then proposed for the TWIP mobile robot. The balancing and velocity tracking performance of the proposed controller was investigated via simulations. The simulation result shows the effectiveness of the proposed control scheme.]]>
<![CDATA[Direct space vector modulation for matrix converter fed dual star induction machine and neuro-fuzzy speed controller ]]>
<![CDATA[Meliani Bouziane]]>;
<![CDATA[Meroufel Abdelkader]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v8i3.1560
<![CDATA[This paper presents the modeling, design, and simulation of an adaptive neuro fuzzy inference strategy (ANFIS) for controlling the speed of the Double Star induction Machine (DSIM), the machine is fed by three phase direct matrix converter which makes directly AC-AC power conversion is modeled using Direct Space Vector Modulation technique(DSVM) for direct matrix converter. Double star Induction motor is characterized by highly non-linear, complex and time-varying dynamics and inaccessibility of some of the states and outputs for measurements. Hence it can be considered as a challenging engineering problem in the industrial sector. Various advanced control techniques has been devised by various researchers across the world. Some of them are based on the neuro-fuzzy techniques. The main advantage of designing the ANFIS coordination scheme is to control the speed of the DSIM to increase the dynamic performance, to provide good stabilization. To show the effectiveness of our scheme, the proposed method was simulated on an electrical system composed of a 4.5 kW six-phase induction machine and its power inverter. Digital simulation results demonstrate that the deigned ANFIS speed controller realize a good dynamic of the DSIM, a perfect speed tracking with no overshoot, give better performance and high robustness.]]>
<![CDATA[Integrated cmos rectifier for rf-powered wireless sensor network nodes ]]>
<![CDATA[Mohammed Abdul Raheem Esmail Alselwi]]>;
<![CDATA[Yan Chiew Wong]]>;
<![CDATA[Zul Atfyi Fauzan Mohammed Napiah]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v8i3.1579
<![CDATA[This article presents a review of the CMOS rectifier for radio frequency energy harvesting application. The on-chip rectifier converts the ambient low-power radio frequency signal coming to antenna to useable DC voltage that recharges energy to wireless sensor network (WSN) nodes and radiofrequency identification (RFID) tags, therefore the rectifier is the most important part of the radio frequency energy harvesting system. The impedance matching network maximizes power transfer from antenna to rectifier. The design and comparison between the simulation results of one- and multi-stage differential drive cross connected rectifier (DDCCR) at the operating frequencies of 2.44GHz, and 28GHz show the output voltage of the multi-stage rectifier doubles at each added stage and power conversion efficiency (PCE) of rectifier at 2.44GHz was higher than 28GHz. The (DDCCR) rectifier is the most efficient rectifier topology to date and is used widely for passive WSN nodes and RFID tags.]]>
<![CDATA[Moving object detection via TV-L1 optical flow in fall-down videos ]]>
<![CDATA[Nur Ayuni Mohamed]]>;
<![CDATA[Mohd Asyraf Zulkifley]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v8i3.1346
<![CDATA[There is a growing demand for surveillance systems that can detect fall-down events because of the increased number of surveillance cameras being installed in many public indoor and outdoor locations. Fall-down event detection has been vigorously and extensively researched for safety purposes, particularly to monitor elderly peoples, patients, and toddlers. This computer vision detector has become more affordable with the development of high-speed computer networks and low-cost video cameras. This paper proposes moving object detection method based on human motion analysis for human fall-down events. The method comprises of three parts, which are preprocessing part to reduce image noises, motion detection part by using TV-L1 optical flow algorithm, and performance measure part. The last part will analyze the results of the object detection part in term of the bounding boxes, which are compared with the given ground truth. The proposed method is tested on Fall Down Detection (FDD) dataset and compared with Gunnar-Farneback optical flow by measuring intersection over union (IoU) of the output with respect to the ground truth bounding box. The experimental results show that the proposed method achieves an average IoU of 0.92524.]]>
<![CDATA[Dermatological diagnosis by mobile application ]]>
<![CDATA[Shihab A. Hameed]]>;
<![CDATA[Alaa Haddad]]>;
<![CDATA[Mohamed Hadi habaebi]]>;
<![CDATA[Ali Nirabi]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v8i3.1502
<![CDATA[Health care mobile application delivers the right information at the right time and place to benefit patient’s clinicians and managers to make correct and accurate decisions in health care fields, safer care and less waste, errors, delays and duplicated errors.Lots of people have knowledge a skin illness at some point of their life, For the reason that skin is the body's major organ and it is quite exposed, significantly increasing its hazard of starting to be diseased or ruined.This paper aims to detect skin disease by mobile app using android platform providing valid trustworthy and useful dermatological information on over 4 skin diseases such as acne, psoriasis content for each skin condition, skin rush and Melanoma. It will include name, image, description, symptoms, treatment and prevention with support multi languages English and Bahasa and Mandarin. the application has the ability to take and send video as well as normal and magnified photos to your dermatologist as an email attachment with comments on safe secure network, this app also has a built in protected privacy features to access to your photo and video dermatologists. The mobile application help in diagnose and treat their patients without an office visit teledermatology is recognized by all major insurance companies doctor. ]]>
<![CDATA[Pre-trained based CNN model to identify finger vein ]]>
<![CDATA[Subha Fairuz]]>;
<![CDATA[Mohamed Hadi Habaebi]]>;
<![CDATA[Elsheikh Mohamed Ahmed Elsheikh]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v8i3.1505
<![CDATA[In current biometric security systems using images for security authentication, finger vein-based systems are getting special attention in particular attributable to the facts such as insurance of data confidentiality and higher accuracy. Previous studies were mostly based on finger-print, palm vein etc. however, due to being more secure than fingerprint system and due to the fact that each person's finger vein is different from others finger vein are impossible to use to do forgery as veins reside under the skin. The system that we worked on functions by recognizing vein patterns from images of fingers which are captured using near Infrared(NIR) technology. Due to the lack of an available database, we created and used our own dataset which was pre-trained using transfer learning of AlexNet model and verification is done by applying correct as well as incorrect test images. The result of deep convolutional neural network (CNN) based several experimental results are shown with training accuracy, training loss, Receiver Operating Characteristic (ROC) Curve and Area Under the Curve (AUC).]]>
<![CDATA[Video streaming over Ad hoc on-demand distance vector routing protocol ]]>
<![CDATA[Othman O. Khalifa]]>;
<![CDATA[Diaa Eldin Mustafa Ahmed]]>;
<![CDATA[Aisha Hassan Abdalla Hashim]]>;
<![CDATA[Mudathir Yagoub]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v8i3.1510
<![CDATA[Video streaming is content sent in compressed form over the netwoks and viwed the users progressively. The transmission of video with the end goal that it can be prepared as consistent and nonstop stream. The point is that to give client support to client at anyplace and at whatever time. Mobile Ad hoc Networks (MANETs) are considered an attractive nertwork for information transmission in many applications where the customer programme can begin showing the information before the whole record has been transmitted. Ad hoc On-demand Distance Vector (AODV) protocol is considered as one of the most important routing protocols in MANET. However, routing protocols assume a crucial part in transmission of information over the network. This paper investigates the performance of AODV Routing Protocol under video traffic over PHY IEEE 802.11g. The protocol model was developed in OPNET. Different outcomes from simulation based models are analyzed and appropriate reasons are also discussed. A different scenarios of video streaming were used. The metric in terms of throughput, end to end delay, packet delivery ratio and routing overhead were measured. A comparision with GRP and GRP are also reported.]]>
<![CDATA[Distinctive features for normal and crackles respiratory sounds using cepstral coefficients ]]>
<![CDATA[N. H. Mohd Johari]]>;
<![CDATA[Noreha Abdul Malik]]>;
<![CDATA[K. A. Sidek]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v8i3.1517
<![CDATA[Classification of respiratory sounds between normal and abnormal is very crucial for screening and diagnosis purposes. Lung associated diseases can be detected through this technique. With the advancement of computerized auscultation technology, the adventitious sounds such as crackles can be detected and therefore diagnostic test can be performed earlier. In this paper, Linear Predictive Cepstral Coefficient (LPCC) and Mel-frequency Cepstral Coefficient (MFCC) are used to extract features from normal and crackles respiratory sounds. By using statistical computation such as mean and standard deviation (SD) of cepstral based coefficients it can differentiate between crackles and normal sounds. The statistical computations of the cepstral coefficient of LPCC and MFCC show that the mean LPCC except for the third coefficient and first three statistical coefficient values of MFCC’s SD provide distinctive feature between normal and crackles respiratory sounds. Hence, LPCCs and MFCCs can be used as feature extraction method of respiratory sounds to classify between normal and crackles as screening and diagnostic tool.]]>
<![CDATA[Efficient 3D stereo vision stabilization for multi-camera viewpoints ]]>
<![CDATA[Sharif Shah Newaj Bhuiyan]]>;
<![CDATA[Othman O. Khalifa]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v8i3.1518
<![CDATA[In this paper, an algorithm is developed in 3D Stereo vision to improve image stabilization process for multi-camera viewpoints. Finding accurate unique matching key-points using Harris Laplace corner detection method for different photometric changes and geometric transformation in images. Then improved the connectivity of correct matching pairs by minimizing the global error using spanning tree algorithm. Tree algorithm helps to stabilize randomly positioned camera viewpoints in linear order. The unique matching key-points will be calculated only once with our method. Then calculated planar transformation will be applied for real time video rendering. The proposed algorithm can process more than 200 camera viewpoints within two seconds.]]>
