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Bulletin of Electrical Engineering and Informatics

EEI
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Published by Universitas Ahmad Dahlan

ISSN : - EISSN : - DOI : -

Core Subject : Engineering,

Electrical & Electronics Engineering

Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 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. The journal publishes original papers in the field of electrical, computer and informatics engineering.

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Articles 2,901 Documents

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Recognition of sign language hand gestures using leap motion sensor based on threshold and ANN models Muhammad Ilhamdi Rusydi; Syafii Syafii; Rizka Hadelina; Elmiyasna Kimin; Agung W. Setiawan; Andrivo Rusydi
Bulletin of Electrical Engineering and Informatics Vol 9, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

Hand gesture recognition is a topic that is still investigated by many scientists for numerous useful aspects. This research investigated hand gestures for sign language number zero to nine. The hand gesture recognition was based on finger direction patterns. The finger directions were detected by a Leap Motion Controller. Finger direction pattern modeling was based on two methods: threshold and artificial neural network. Threshold model 1 contained 15 rules based on the range of finger directions on each axis. Threshold model 2 was developed from model 1 based on the behavior of finger movements when the subject performed hand gestures. The ANN model of the system was designed with four neurons at the output layer, 15 neurons at the input layer, seven neurons at the first hidden layer and 5 neurons at the second hidden layer. The artificial neural network used the logsig as the activation function. The result shows that the first threshold model has the lowest accuracy because the rule is too complicated and rigid. The threshold model 2 can improve the threshold model, but it still needs development to reach better accuracy. The ANN model gave the best result among the developed model with 98% accuracy. LMC produces useful biometric data for hand gesture recognition.

Low power wake-up receiver based on ultrasound communication for wireless sensor network Yan Chiew Wong; Szi Hui Tan; Ranjit Singh Sarban Singh; Haoyu Zhang; A. R. Syafeeza; N. A. Hamid
Bulletin of Electrical Engineering and Informatics Vol 9, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

Wireless sensor network (WSN) consists of base stations and sensors nodes to monitor physical and environmental conditions. Power consumption is a challenge in WSN due to activities of nodes. High power consumption is required for the main transceiver in WSN to receive communication requests all the time. Hence, a low power wake-up receiver is needed to minimize the power consumption of WSN. In this work, a low power wake-up receiver using ultrasound data communication is designed. Wake-up receiver is used to detect wake-up signal to activate a device in WSN. Functional block modelling of the wake-up receiver is developed in Silterra CMOS 130nm process technology. The performance of the wake-up receiver has been analyzed and achieving low power consumption which is 22.45μW. A prototype to demonstrate a wireless sensor node with wake-up receiver has been developed incorporating both ultrasonic and RF for internal and external communication respectively. We achieve 99.97% of power saving for 10s operation in the experimental setup for the WSN with and without wake-up receiver. Wake-up receiver used in WSN save power and prolong the lifetime of batteries and thus extending the operational lifetime of WSN.

An alternative approaches to predict flashover voltage on polluted outdoor insulators using artificial intelligence techniques Ali. A. Salem; Rahisham Abd Rahman; M. S. Kamarudin; N. A. Othman; N. A. M. Jamail; H. A. Hamid; M. T. Ishak
Bulletin of Electrical Engineering and Informatics Vol 9, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

This paper presents an alternative approach for predicting critical voltage of pollution flashover by using Artificial Intelligence (AI) technique. Data from experimental works combined with the theoretical results from well-known theoretical modelling are used to derive algorithm for Artificial Neural Network (ANN) and Adaptive Neuro-fuzzy Inference System (ANFIS) for determining critical voltage of flashover. Series of laboratory testing and measurement are carried for 1:1, 1:5 and 1:10 ratios of top to bottom surface salt deposit density on cup and pin insulators. Insulators variables such as height H, diameter D, form factor F, creepage distance L, equivalent salt deposit density (ESDD) and flashover voltage correction are identified and used to train the AI network. Comparative studies have evidently shown that the proposed (AI) technique gives the satisfactory results compared to the analytical model and test data with the Coefficient of determination R-Square value of more than 97%.

Novel design of a fractional wavelet and its application to image denoising Lanani Abderrahim; Meghriche Salama; Djouambi Abdelbaki
Bulletin of Electrical Engineering and Informatics Vol 9, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

This paper proposes a new wavelet family based on fractional calculus. The Haar wavelet is extended to fractional order by a generalization of the associated conventional low-pass filter using the fractional delay operator Z-D. The high-pass fractional filter is then designed by a simple modulation of the low-pass filter. In contrast, the scaling and wavelet functions are constructed using the cascade Daubechies algorithm. The regularity and orthogonality of the obtained wavelet basis are ensured by a good choice of the fractional filter coefficients. An application example is presented to illustrate the effectiveness of the proposed method. Thanks to the flexibility of the fractional filters, the proposed approach provides better performance in term of image denoising.

Influence of low power consumption on IEEE 802.15.4 in wireless networks performance A. Z. Yonis
Bulletin of Electrical Engineering and Informatics Vol 9, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

IEEE 802.15.4 standard defines both media access control (MAC) and physical (PHY) layer protocols for low power consumption, low peak data rate, and low cost applications. Nowadays the most important feature of IEEE 802.15.4 is maximizing battery life. This paper is focusing how to achieve low average power consumption through assuming that the amount of data transmitted is short and that it is transmitted infrequently so as to keep a low duty cycle. The outcomes demonstrate that the phase shift estimation of Offset quadrature phase-shift keying (OQPSK) modulation has no impact on bit error rate (BER) if it is identical in the transmitter as same as in the receiver.

Dynamic economic emission dispatch using ant lion optimization Hardiansyah Hardiansyah
Bulletin of Electrical Engineering and Informatics Vol 9, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

This paper aims to propose a new meta-heuristic search algorithm, called Ant Lion Optimization (ALO). The ALO is a newly developed population-based search algorithm inspired hunting mechanism of ant lions. The proposed algorithm is presented to solve the dynamic economic emission dispatch (DEED) problem with considering the generator constraints such as ramp rate limits, valve-point effetcs, prohibited operating zones and transmission loss. The 5-unit generation system for a 24 h time interval has been taken to validate the efficiency of the proposed algorithm. Simulation results clearly show that the proposed method outperforms in terms of solution quality when compared with the other optimization algorithms reported in the literature.

Frontal lobe and long-term memory retrieval analysis during pre-learning stress using EEG signals Omar Mahmoud AlShorman; Ahmad M. Alshorman
Bulletin of Electrical Engineering and Informatics Vol 9, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

This paper uses the EEG analysis to investigate the relationship between pre-learning stress, frontal lope and long-term memory in the brain. The stress on learning stage is a challenge, especially in academic life. Stress also on learning stage affects the retrieval or recall from the memory. Nowadays; there are many recent works have discovered the relationship between stress, learning and memory performance based on different techniques. Some of these techniques are biological methods. Moreover, these methods have discovered the effect of stress based on hormones levels such as cortisol, or based on physiological effects such as blood pressure. However, these techniques have given conflicting discoveries because of the instability of hormones and an extensive number of related elements. The main aim of this research is to discover the relationship between Pre-learning stress, frontal lope, and long-term memory retrieval using EEG signals. The experimental results indicate that there is a relationship between theta rhythm in the frontal lobe and long-term memory retrieval during Pre-learning stress.

Comparison of human detection using background subtraction and frame difference Mohd Saifulnizam Zaharin; Norazlin Ibrahim; Tengku Mohd Azahar Tuan Dir
Bulletin of Electrical Engineering and Informatics Vol 9, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

Image processing is mostly used for exploring image behaviour. There are several steps in image processing. Image acquisition, pre-processing, feature extraction, and classification are the processes used for the detection of human movement based on high-level feature extraction (HLFE), in which HLFE was used for feature extraction in this paper. This study proposed the use of background subtraction and frame difference. This research was conducted to analyse the difference of background subtraction and frame difference methods based on movement of human. Movement of human detected by using feature extraction were centroid image technique used. Furthermore, support vector machine (SVM) was used for classification.

Interoperability framework for integrated e-health services M. Miftakul Amin; Adi Sutrisman; Deris Stiawan; Ermatita Ermatita; Mohammed Y. Alzahrani; Rahmat Budiarto
Bulletin of Electrical Engineering and Informatics Vol 9, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

As one of the country with largest population in the world, Indonesia is facing major challenge to serve people in various sectors, one of them is health sector. Utilization of Information and Communication Technology (ICT) has a strategic role in improving efficiency and expanding services access. The main challenge related to data interoperability is the ability to integrate and synchronize data sourced from health information (e-health) systems with different (heterogeneous) platforms. This research aims to build a framework to materialize data interoperability and information exchange among e-health systems. The interoperability is materialized by utilizing service oriented architecture (SOA) paradigm and is implemented using Web Service technology. Service oriented analysis and design (SOAD) is used as method in the system development at the analysis phase and designing phase to generate service portfolio which consisting of three levels: conceptual view, logical view, and physical view. This research intruduces Interoperability Matrix (IM) to describe the modules and entities that involved in the framework design. The framework resulted from this research can be used as reference in e-health systems development in variety of health care applications.

CPU implementation using only logisim simulator to achieve computer architecture learning outcome Mochammad Hannats Hanafi Ichsan; Wijaya Kurniawan
Bulletin of Electrical Engineering and Informatics Vol 9, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

This paper proposes the design, implementation, and evaluation of an 8-bit CPU architecture in computer organization and architecture (COA) course for Undergraduate Computer Engineering using only Logisim simulator. The main advantage of using one simulator is the elimination of inefficiency so that students can concentrate more on the course’s content without spending their time just to learn how to use each different type of simulators. To achieve that, a simple CPU architecture is pre-designed and be implemented in Logisim simulator. According to previous researches, Mic-1 CPU architecture is chosen because it is the simplest one and can be easily built using many simple logic gates already existed in the Logisim. To evaluate the desired outcome, students are separated into two different groups. Each group used different type of learning media and material and then their examination scores and satisfaction are compared to each other. Every student belongs to the group that only used Logisim simulator obtained higher score and more than 50% are satisfied with the new learning process and material. Thus, it envisaged that this method will made the delivering learning process in COA course be more efficient than what has happened so far.

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