Articles

Access the latest knowledge in applied science, electrical engineering, computer science and information technology, education, and health.

Advanced Search
Filter Icon

Filters article

Years

FAQ Arrow
Single Year
Range Year
0
0

Source Title

FAQ Arrow

Authors

FAQ Arrow

31,456 Article Results

A self-rectifying memristor model for simulation and ReRAM applications

10.11591/ijeecs.v19.i3.pp1204-1209
Sinan Sabah , Nasri Bin Sulaiman
In this paper, a self-rectifying memristor (SRM) model is proposed for memristive circuit simulations. This model is based on the behavior of voltage controlled, bipolar memristors that exhibit diode-like rectification behavior when reverse biased. Such unique feature can solve the sneak path problem in crossbar memristive memory structures without requiring additional cell selectors. The results show that the proposed model satisfies the basic memristor’s i-v characteristics and fits many different memristor devices adequately. The proposed model is implemented in Verilog-A so that it is conveniently incorporated into various memristor applications with different circuit simulators
Volume: 19
Issue: 3
Page: 1204-1209
Publish at: 2020-09-01

Increasing the efficiency of information transmission in communication channels

10.11591/ijeecs.v19.i3.pp1306-1315
Bohdan Zhurakovskyi , Juliy Boiko , Vladymir Druzhynin , Irina Zeniv , Oleksander Eromenko
This paper discusses compression methods focused on data transmission over communication channels. The characteristics of different algorithms for different types of incoming data are analyzed. The purpose of this study is to evaluate the speed of operation of each of the compression algorithms for different types of information and different compression parameters, on the basis of the obtained results to make recommendations for the application of compression methods in systems critical to the performance of the algorithm. Based on the results of the analysis, the methods of compression that can be used in communication channels are selected: LZW, LZH, Vitter and matrix. The practical research of the selected methods on different information flows (text, graphics, measurement data, combined data) was carried out, their comparative analysis was performed. Research has highlighted compression methods that give the most optimal results in each case. Comparative evaluation of algorithms for different parameters is made, the possibility of data compression implementation in systems running in real time is analyzed. Based on the results of the study, recommendations are made for the application of particular compression methods in specific conditions.
Volume: 19
Issue: 3
Page: 1306-1315
Publish at: 2020-09-01

Dynamic spectrum access using markov chain technique for regional area network

10.11591/ijeecs.v19.i3.pp1420-1427
Jayant P Pawar , Prashant V. Ingole
Cognitive Radio Network is the effective solution to the spectrum scarcity.  Dynamic spectrum access is a paradigm used to access the spectrum dynamically. A Markov Chain is a stochastic model describing a sequence of possible events in which probability of each event depends only on the state attained in the previous event. We model the dynamics of cognitive user with 2-D Markov chain. The resource distribution probability (RDP) verses addition/ elimination rate of the channels in the network is also plotted. The RDP verses utilization factor of the queue, which is the secondary user in the network, is also plotted. This plot helps to maintain the total arrival and departure rate based on the RDP. The base station of the network will use this relation to maintain the proper RDP for the devices. The dynamics of each cognitive user and its correlation with Markov Chain is an interesting approach. Here we considered the DSA at Base Station as a Markov chain and analyzed it. This analysis helps us to determine the behavior of the cognitive radio and also helps to find the fault in the cognitive devices. 
Volume: 19
Issue: 3
Page: 1420-1427
Publish at: 2020-09-01

To the theory of electromagnetic radiation by fast moving body

10.11591/ijeecs.v19.i3.pp1267-1274
Sergey Gladkov
The problem of finding out the connection between the flight speed of a metal object and the length of electromagnetic radiation that accompanies its movement has been solved. The calculations are based on the application of Lienar-Vihert's potential theory. Based on the assumption of the dipole mechanism of radiation, the intensity of electromagnetic radiation was calculated and its distribution by coordinates was found. 
Volume: 19
Issue: 3
Page: 1267-1274
Publish at: 2020-09-01

A distributed trust mechanism for malicious behaviors in VANETs

10.11591/ijeecs.v19.i3.pp1147-1155
Ali Kamil Ahmed , Mohanad Najm Abdulwahed , Behnam Farzaneh
Vehicular ad-hoc networks (VANETs) are one of the most important types of networks which are widely used in recent years. Along with all the benefits of quality of service (QoS) improvements, vulnerability analysis for this type of networks is an important issue. For instance, a gray-hole attack decreases network performance. We proposed a novel solution to help to secure these networks against this vulnerability. The proposed method can detect and prevent the gray-hole attack. Anywhere in the network, each node (vehicle) can distinguish between the gray-hole attack and the failed link. Some topology related information helps us to detect attacks more accurately. Also, the proposed method uses the most reliable path in terms of link failure when there is no malicious node. In this paper, we used the TOPSIS method for choosing the most trusted node for routing intelligently. We validated our proposal using a simulation model in the NS-2 simulator. Simulation results show that the proposed method can prevent Gray-hole attack efficiently with low overhead.
Volume: 19
Issue: 3
Page: 1147-1155
Publish at: 2020-09-01

Grid search of exponential smoothing method: a case study of Ho Chi Minh City load demand

10.11591/ijeecs.v19.i3.pp1121-1130
Ngoc Thanh Tran , Le Van Dai
The exponential smoothing method is one of the widely used methods for load forecasting. The taxonomy of exponential smoothing method shows that its trend and seasonal component affect the results of exponential smoothing method. This paper proposed a framework for grid search with the optimal model of exponential smoothing method based on math formulas. The training process will specify the optimal models which satisfy requirement of minimum of akaike information criterion, accuracy scores of the root mean square error, mean absolute percentage error, and mean absolute error. The testing process will evaluate the accuracy scores between the optimal models and all other ones. The results indicated that the optimal models have accuracy scores near the minimum values. The load demand data collected in Ho Chi Minh City were used to verify the accuracy and reliability of the grid search framework.
Volume: 19
Issue: 3
Page: 1121-1130
Publish at: 2020-09-01

Development process and testing of partial discharge detection device on medium voltage XLPE cable

10.11591/ijeecs.v19.i3.pp1297-1305
Mohamad Izmir Farhan Mohamad Radzi , N H Nik Ali , Azrul Mohd Ariffin , Muhamad Safwan Abd Rahman , Norhidayu Rameli , Mohamad Radzi Ahmad , Ali Syari’ati Mohd Salleh
High voltage assets play a vital role in providing uninterrupted power to the consumers and any slight problems experienced by the assets may cause losses in millions of dollars to businesses. Therefore it is of utmost importance to monitor the health of high voltage assets. This research presents the development process of a partial discharge (PD) device that is able to detect PD acoustic waves for monitoring high voltage assets purposes. Medium voltage cross-linked polyethylene (XLPE) cable was used which was introduced with spherical void defects at the joints of the cable that functioned to produce PD acoustic waves. Outcome of the development processes provides the finished design of the PD sensing device, known as partial discharge detection (PDD) device. The functionality of the PDD device was also assessed through controlled experimentations, and they proved to be successful. Pure PD waveform captured by the ultrasonic sensor was similar when compared to a HFCT sensor’s pure PD waveform. The PDD device is a small and affordable, and is opened to various improvements such as integrating artificial intelligence (AI) unto the device, and one day may replace most existing bulky and expensive PD sensing devices that are readily available in the market.
Volume: 19
Issue: 3
Page: 1297-1305
Publish at: 2020-09-01

On the review of image and video-based depression detection using machine learning

10.11591/ijeecs.v19.i3.pp1677-1684
Arselan Ashraf , Teddy Surya Gunawan , Bob Subhan Riza , Edy Victor Haryanto , Zuriati Janin
Machine learning has been introduced in the sphere of the medical field to enhance the accuracy, precision, and analysis of diagnostics while reducing laborious jobs. With the mounting evidence, machine learning has the capability to detect mental distress like depression. Since depression is the most prevalent mental disorder in our society at present, and almost the majority of the population suffers from this issue. Hence there is an extreme need for the depression detection models, which will provide a support system and early detection of depression. This review is based on the image and video-based depression detection model using machine learning techniques. This paper analyses the data acquisition techniques along with their databases. The indicators of depression are also reviewed in this paper. The evaluation of different researches, along with their performance parameters, is summarized. The paper concludes with remarks about the techniques used and the future scope of using the image and video-based depression prediction. 
Volume: 19
Issue: 3
Page: 1677-1684
Publish at: 2020-09-01

Development of marine observation system using LPWA communication system for marine IoT service

10.11591/ijeecs.v19.i3.pp1556-1563
Se-Hoon Kim , Min-Ho Jeon , Yeon-Ju Jo , Chang-Heon Oh
Because oceans account for 70.8% of the Earth's surface, various internet of things (IoT) applications for the marine industry are being researched and developed. The success of an IoT technology in the maritime industry depends on the location tracking technology used and how far it can communicate. In this study, we implemented a marine observation system using low power wide area (LPWA) communication technology to provide maritime IoT services. The proposed marine observation system consists of a marine IoT module and an ocean observation monitoring system. The information collected is GPS information and communication signal reception strength. As a result of an actual field test, we were able to obtain the distance to the gateway by measuring the position through the marine IoT module, and we found that the intensity of communication was proportional to the change in sea level.
Volume: 19
Issue: 3
Page: 1556-1563
Publish at: 2020-09-01

Main keyword comparison based on document analysis system

10.11591/ijeecs.v19.i3.pp1533-1539
Jongwon Lee , Jaeseung Lee , Hoekyung Jung
Existing document analysis systems list words in the document using a morpheme analyzer. Such a structural feature is difficult to help users to understand the document. To understand a document, you need to analyze the keyword in the document and extract the paragraphs including the keyword. The proposed system retrieves keywords from documents written in XML format, extracts them, and displays them to the user. In addition, it extracts the paragraphs including the keyword entered by the user and maintains paragraph sequence and delete for duplicate paragraphs. Then, the frequency and weight of the keyword are calculated, and the number of paragraphs is reduced by removing the paragraphs including the keyword having a weight less than other keywords weighed. This method may reduce the time and effort required for the user to understand the document as compared to the existing document analysis systems.
Volume: 19
Issue: 3
Page: 1533-1539
Publish at: 2020-09-01

A novel academic performance estimation model using two stage feature selection

10.11591/ijeecs.v19.i3.pp1610-1619
Pamela Chaudhury , Hrudaya Kumar Tripathy
Educational data mining has gained tremendous interest from researchers across the globe. Using data mining techniques in the field of education several significant findings have been made. Accurate academic performance estimation has been a challenging task due to the variety of students’ attributes involved. In this study we have developed a novel framework to estimate the academic performance of students. Our proposed model outperformed existing models of students’ academic performance determination and gives a new direction to academic performance estimation. The proposed model can help not only to reduce the number of academic failures but also help to comprehend the factors contributing to a students’ academic performance (poor, average or outstanding). Some of the techniques used were conversion of categorical attributes into dummy variables, instance segregation, classification using an optimised and improved differential evolutionary algorithm.
Volume: 19
Issue: 3
Page: 1610-1619
Publish at: 2020-09-01

Development of solar panel cleaning robot using Arduino

10.11591/ijeecs.v19.i3.pp1245-1250
Faridah Hanim Binti Mohd Noh , Muhamad Faizal Yaakub , Ili Najaa Aimi Mohd Nordin , Norain Sahari , Nor Aira Zambri , Sim Sy Yi , Muhammad Syukri Mohd Saibon
Solar power is mainly harnessed from photovoltaic (PV) panels which are arranged in multiple arrays in a solar farm or solar system. Though, power generation from PV solar system is characterised by uncertain efficiency, many countries with high insolation prefer solar as an alternative way of generating clean energy. However, the efficiency of energy generated from PV panels is affected by the accumulation of dust and debris, even on one panel in an array. This condition leads to the need for regular cleaning of the surface of PV panels. Current labour-based cleaning methods for photovoltaic arrays are costly in time, water and energy usage as well as lacking in automation capabilities. To overcome this problem, a fully automatic solar panel cleaning system with/without water is proposed. Hence, in this paper, the design of a robot for automated cleaning of the surface of PV panel is presented. The design utilizes an Arduino controller system to control the robot movement during the cleaning process. In addition, it is equipped with two rough sponge and a water pump system that can be used to clean dust or debris found on PV panel surfaces. The efficiency of the PV panels before and after the cleaning process is also observed. The result shows that the developed solar panel cleaning robot is able to clean the panel effectively and increase back the output current as well as the maximum power of the panel by 50%, after the dust on the PV panel is cleaned.
Volume: 19
Issue: 3
Page: 1245-1250
Publish at: 2020-09-01

ANFIS controller for vector control of three phase induction motor

10.11591/ijeecs.v19.i3.pp1177-1185
Girisha Joshi , Pinto Pius A J
For variable speed drive applications such as electric vehicles, 3 phase induction motor is used and is controlled by fuzzy logic controllers. For the steady functioning of the vehicle drive, it is essential to generate required torque and speed during starting, coasting, free running, braking and reverse operating regions. The drive performance under these transient conditions are studied and presented. In the present paper, vector control technique is implemented using three fuzzy logic controllers. Separate Fuzzy logic controllers are used to control the direct axis current, quadrature axis current and speed of the motor. In this paper performance of the indirect vector controller containing artificial neural network based fuzzy logic (ANFIS) based control system is studied and compared with regular fuzzy logic system, which is developed without using artificial neural network. Data required to model the artificial neural network based fuzzy inference system is obtained from the PI controlled induction motor system. Results obtained in MATLAB-SIMULINK simulation shows that the ANFIS controller is superior compared to controller which is implemented only using fuzzy logic, under all dynamic conditions.
Volume: 19
Issue: 3
Page: 1177-1185
Publish at: 2020-09-01

Automatic control system based on iot data identification

10.11591/ijeecs.v19.i3.pp1525-1532
Hankil Kim , Jaehyun Park , Hoekyung Jung
Recently, as the internet of things (IoT) technology has developed, researches are rigorously conducted to construct smart environments such as smart home, smart grid, and industrial IoT. However, currently existing systems consists of a series of events, and even if an existing task is running, unnecessary work still occurs as both works happen simultaneously. In this paper, we propose an automatic work control system to solve this problem. The proposed system transmits the data measured by the sensor to the server and identifies non-real-time tasks such as real-time work which is related to the dangerous situations, ventilation and temperature control. In addition, priority among the tasks is set in a way that existing tasks are stopped when high priority tasks occur. Accordingly, this can reduce the unnecessary waste of power, and the user is able to receive a proactive service.
Volume: 19
Issue: 3
Page: 1525-1532
Publish at: 2020-09-01

A comparison of the carbon footprint of pavement infrastructure and associated materials in Indiana and Oklahoma

10.11591/ijaas.v9.i3.pp227-239
Rachel D. Mosier , Sanjeev Adhikari , Saurav K. Mohanty
Although often overlooked, infrastructure has a significant role in modern society. It is necessary means of transportation for goods and services needed to support commerce. It is this need and the need for continued economic development that causes the continuous infrastructure construction and its’ associated greenhouse gas emissions. Infrastructure construction requires energy to process raw materials, transport, mix and final construction. Greenhouse gas emissions from pavement sections have previously been identified for pavement preservation techniques. This research further evaluates greenhouse gas emissions for typical pavement sections from Indiana and Oklahoma to determine the carbon footprint based on linear foot of pavement. The comparison of CO2e of two typical roadway sections finds the difference in carbon footprint since variation in their minimum roadway. The carbon footprint of typical utility pipe with HDPE produces minimum CO2e and steel produces maximum CO2e. Soil base remediation options produce minimum CO2e and stabilized aggregate base produces maximum CO2e. Carbon offsets are determined by choosing vegetative options, soil remediation methods and appropriate pavement. This study is limited to a few pavement sections with a small variety of typical anticipated carbon offsets that would be seen in roadway construction. The index presented allows users to simply quantify benefits of the carbon offsets.
Volume: 9
Issue: 3
Page: 227-239
Publish at: 2020-09-01
1 2 3
...
2097 2098
Show 1191 of 2098

Discover Our Library

Embark on a journey through our expansive collection of articles and let curiosity lead your path to innovation.

Explore Now
Library 3D Ilustration