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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

67 68 69 70 71

Performance analysis of the convolutional recurrent neural network on acoustic event detection Suk-Hwan Jung; Yong-Joo Chung
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

In this study, we attempted to find the optimal hyper-parameters of the convolutional recurrent neural network (CRNN) by investigating its performance on acoustic event detection. Important hyper-parameters such as the input segment length, learning rate, and criterion for the convergence test, were determined experimentally. Additionally, the effects of batch normalization and dropout on the performance were measured experimentally to obtain their optimal combination. Further, we studied the effects of varying the batch data on every iteration during the training. From the experimental results using the TUT sound events synthetic 2016 database, we obtained optimal performance with a learning rate of 1/10000. We found that a longer input segment length aided performance improvement, and batch normalization was far more effective than dropout. Finally, performance improvement was clearly observed by varying the starting points of the batch data for each iteration during the training.

Measurement of material volumes in a cylindrical silo using acoustic wave and resonance frequency analysis Chukiet Sodsri
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

This work presents an approach for measuring material volumes in a closed cylindrical silo by using acoustic waves and resonance frequency analysis of silo’s acoustic systems. With an assumption that the acoustical systems were linear and time-invariant, frequency responses of the systems were identified via measurement. A sine sweep was generated, amplified and fed to a loudspeaker inside the silo. Acoustic waves were picked up by a microphone and processed to yield the silo's frequency response. Resonance frequencies and wave mode numbers of standing waves in the frequency range below 900 Hz were analyzed and used for calculation of air-cavity lengths. With known silo's dimension, the material volume estimations were achieved. Sets of experiments for estimating volumes of sand, cement, water, rice grain, and stone flakes in a closed silo, were done. It was found that the approach could successfully estimate the volumes of sand, cement, and water with a satisfactory accuracy. Percent errors of the estimations were less than 3% from the actual volumes. However, the approach could not estimate the volume of rice grain and stone flakes, since their sound refractions were neither resulted in standing waves nor acoustical modes in the silo.

Generation of infectious disease alerts through the use of geolocation Antonio Sarasa Cabezuelo
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

In recent years, there have been several cases of global epidemics such as influenza B or Ebola. In these cases, several factors are key to limit the effects of the epidemic and avoid contagion. Between of them is the speed of knowing which persons are infected, which persons has been in contact with any infected person or know what the focus of the epidemic. In general, obtaining this information requires a process of research among the first affected that can be slow and complicated. This article describes a tool that aims to generate alerts when there are data about an epidemic, and notify all persons who could be exposed to contagion and prevent new infections occurs.

Implementation of electronic stethoscope for online remote monitoring with mobile application Sugondo Hadiyoso; Dieny Rofiatul Mardiyah; Dadan Nur Ramadan; Asril Ibrahim
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

The stethoscope is a piece of medical standard equipment that isused by a physician for an initial examination of the patient. Generally, the stethoscopeis used for auscultating sounds which are generated by the workings of organ systems such as cardiac, lung or digestive. In the present condition with the growing number of the patient population, it has an impact on the burden of hospitals and medical practitioners. So that treatment is not optimal, especially patients who need continuous monitoring. Thus it needs a system that can work dynamically, flexibly and remotely based. This paper focuses on the implementation of the electronic stethoscope which is integrated with a mobile phone as the modality of online data transmission through the internet network. The prototype of an electronic stethoscope uses condenser mic, pre-amplifier, wide bandpass filter (20 Hz-1 KHz) and audio amplifier. The maximum gain is 28.63 dB in the 20 Hz-690 Hz frequency range. The signal output can be connected to the android mobile through the jacked phone to be stored in MP3 format and then sent to the cloud server for further monitoring and analysis. The application called “Steder” supports realtime communication between patient and physician for medical check-up, consultation, and discussion activities.

Verification analysis for the reliable analytical multi-taper detector in next generation network Hebat Allah O. Selim; Ahmed Shaaban Dessouki; Heba Y. M. Soliman
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Multi-taper method (MTM) acts as an effective detector of spectrum sensing in Cognitive radio networks. In this paper, an analytical study was proposed in which reliable, simple, and computationally efficient mathematical terms for the mean and variance of the probability density function (PDF) were derived using the MTM technique. The closed-form expressions for the probability of detection and false alarm for the MTM detector were obtained accordingly. The proposed analytical study was evaluated by intensive simulations using MATLAB. Different simulation techniques were proposed to verify the derived analysis. The existence of White Gaussian Noise was assumed. Important aspects of spectrum detection in cognitive radio networks were included such as, receiver operating characteristics, detection rate versus signal to noise ratio (SNR), and the minimum desired sample points for a specific performance. A comparison was completed with the energy detection technique and all of the results suggested that the proposed paradigm is both credible and powerful under all the parameters considered in the simulation.

Bangla handwritten character recognition using MobileNet V1 architecture Tapotosh Ghosh; Md. Min-Ha-Zul Abedin; Shayer Mahmud Chowdhury; Zarin Tasnim; Tajbia Karim; S. M. Salim Reza; Sabrina Saika; Mohammad Abu Yousuf
Bulletin of Electrical Engineering and Informatics Vol 9, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v9i6.2234

Handwritten character recognition is a very tough task in case of complex shaped alphabet set like Bangla script. As optical character recognition (OCR) has a huge application in mobile devices, model needs to be suitable for mobile applications. Many researches have been performed in this arena but none of them achieved satisfactory accuracy or could not detect more than 200 characters. MobileNet is a state of art (convolutional neural network) CNN architecture which is designed for mobile devices as it requires less computing power. In this paper, we used MobileNet for handwritten character recognition. It has achieved 96.46% accuracy in recognizing 231 classes (171 compound, 50 basic and 10 numerals), 96.17% accuracy in 171 compound character classes, 98.37% accuracy in 50 basic character classes and 99.56% accuracy in 10 numeral character classes.

Physical security layer with friendly jammer in half-duplex relaying networks over rayleigh fading channel: Intercept probability analysis Phu Tran Tin; Duy Hung Ha; Minh Tran; Tran Thanh Trang
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

In this research, thephysical security layer with a friendly jammerin half-duplex (HD) relaying networksover the Rayleigh fading channel is proposed and investigated. Firstly, we proposed the system model and the time switching,power splitting protocolsfor the system model. Then we conductedthe mathematical analysisfor deriving the exact analysis and asymptotic analysisintegral forms for intercept probability (IP). Finally, the analytical formulationis verified by the Monte Carlo simulation with all main system parameters. From the results, we can show that the simulation and analytical values are the same values.

English poems categorization using text mining and rough set theory Saif Ali Alsaidi; Ahmed T. Sadeq; Hasanen S. Abdullah
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

In recent years, Text Mining wasan important topic because of the growth of digital text data from many sources such as government document, Email, Social Media, Website, etc. The English poemsare one of the text data to categorization English Poems will use Text categorization, Text categorization is a method in which classify documents into one or more categories that were predefined the category based on the text content in a document .In this paper we will solve the problem of how to categorize the English poem into one of the English Poems categorizations by using text mining technique and Machine learning algorithm, Our data set consist of seven categorizations for poems the data set is divided into two-part training (learning)and testing data. In the proposed model we apply the text preprocessing for the documents file to reduce the number of feature and reduce dimensionality the preprocessing process converts the text poem to features and remove the irrelevant feature by using text mining process (tokenize,remove stop word and stemming), to reduce the feature vector of the remaining feature we usetwo methods for feature selection and use Rough set theory as machine learning algorithm to perform the categorization, and we get 88% success classification of the proposed model.

The enhancement of logging system accuracy for infrastructure as a service cloud Surapong Wiriya; Winai Wongthai; Thanathorn Phoka
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

We introduce the novel technical results of the enhanced logging system for customer virtual machines (VMs) in an infrastructure as a service (IaaS) cloud. The main contribution is that the enhanced system can work with a better system's accuracy and speed, with the simplicity of the design and implementation. We measure the accuracy of the unenhanced logging system, then find a quick solution to enhance the system based on the results of the measurement. To measure and enhance the unenhanced system, we increase the main memory and CPU cores of the VMs then collect the accuracy results from each increment configuration. We analyze the results and propose to use the taskset tool to enhance the accuracy of the system. Found three main findings include: firstly, the accuracy of the enhanced system is about 20% on maximum better than the unenhanced one; the enhanced system accuracy becomes 100%; lastly, the enhanced system can detect a file with the smaller file size as almost 12% smaller. The findings can be a basis to design the logging systems in an IaaS cloud, to decrease hardware and energy investment. To the best of our knowledge, the contribution and findings are not in the literature.

Stabilized controller of a two wheels robot Ahmad Fahmi; Marizan Sulaiman; Indrazno Siradjuddin; I Made Wirawan; Abdul Syukor Mohamad Jaya; Mahfud Jiono; Zakiyah Amalia
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v9i4.1965

The Segway Human Transport (HT) robot, it is dynamical self-balancing robot type. The stability control is an important thing for the Segway robot. It is an indisputable fact that Segway robot is a natural instability framework robot. The case study of the Segway robot focuses on running balance control systems. The roll, pitch, and yaw balance of this robot are obtained by estimating the Kalman Filter with a combination of the pole placement and the Linear Quadratic Regulator (LQR) control method. In our system configuration, the mathematical model of the robot will be proved by Matlab Simulink by modelling of the stabilizing control system of all state variable input. Furthermore, the implementation of this system modelled to the real-time test of the Segway robot. The expected result is by substitute the known parameters from Gyro, Accelero and both rotary encoder to initial stabilize control function, the system will respond to the zero input curve. The coordinate units of displacement response and inclination response pictures are the same. As our expected, the response of the system can reach the zero point position.

Page 69 of 291 | Total Record : 2901

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