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31,456 Article Results

Prediction the data consumption for power demands by elman neural network

10.11591/ijece.v9i5.pp4003-4009
Lafta Ismael , Ammar Issa Ismael
The load forecasting consider as part important in power system operation.  The exact prediction for power demand is important for planning how much need extra power generation to cover extra load to keep without happen shutdown. Neural networks stay frequently designed for modeling dynamic processes. The Multi-Layer Perceptron (MLP) with Radial Basis Functions (RBF) network is static approximations used fewer frequently in the discrete-time domain. In this paper proposed predict method for daily peak load by Elman Neural Network (ENN) with using data power demand for 2 years collected from National Control Center (NCC) and comparing the result. The result show the proposal is evaluated and followed the power demand.
Volume: 9
Issue: 5
Page: 4003-4009
Publish at: 2019-10-01

An algorithm for IoT based vehicle verification system using RFID

10.11591/ijece.v9i5.pp3751-3758
Alen Joseph Samuel , Shoney Sebastian
The verification of vehicle documents is an important role of transport department which is rising day by day due to the mass registration of the vehicles. An automated vehicle verification system can improve the efficiency of this process.  In this paper, we propose an IOT based vehicle verification system using RFID technology. As a result, the vehicle checking which is done now manually can be replaced by automation. There is a loss of a significant amount of time when the normal vehicle checking is done manually. The proposed system will make this process automated. The present verification process is using inductive loops that are placed in a roadbed for detecting vehicles as they pass through the loop of the magnetic field. Similarly, the sensing devices spread along the road can detect passing vehicles through the Bluetooth mechanism. The fixed audio detection devices that can be used to identify the type of vehicles on the road. Other measurements are fixed cameras installed in specific points of roads for categorising the vehicles. But all these mechanisms cannot verify the documents and certificates of the vehicles. In our work, we have suggested an algorithm using RFID technology to automate the documentation verification process of the vehicles like Pollution, Insurance, Rc book etc with the help of RFID reader placed at road checking areas. This documents will be updated by the motor vehicle department at specific periods.
Volume: 9
Issue: 5
Page: 3751-3758
Publish at: 2019-10-01

Optimal power flow model for building integrated photovoltaic systems operating in the Andean range

10.11591/ijeecs.v16.i1.pp52-58
Andres Julian Aristizabal , Daniel Ospina , Mónica Castaneda , Sebastian Zapata , Edison Banguero
This paper presents a novel model to evaluate the power output of a building integrated photovoltaic system (BIPVS) operating in the Andean Range.  The Optimal Power Flow (OPF) model optimizes the power output of the BIPVS within an electrical system without violating operational limits.  The model is validated with the experimental performance of a 6 kW BIPVS installed in Bogota, Colombia. The meteorological data affect the power flow. The model is evaluated under sunny and rainy days to characterize the photovoltaic array performance. The results showed that the AC PV-energy generation was 5,904 kWh/year for 2017 and that there is a correlation factor of 99.87% between the experimental power flow and the proposed model.
Volume: 16
Issue: 1
Page: 52-58
Publish at: 2019-10-01

A simplified machine learning approach for recognizing human activity

10.11591/ijece.v9i5.pp3465-3473
Abdul Lateef Haroon P.S , U. Eranna
With the wide ranges of real-time event feed capturing devices, there has been significant progress in the area of digital image processing towards activity detection and recognition. Irrespective of the presence of various such devices, they are not adequate to meet dynamic monitoring demands of the visual surveillance system, and their features are highly limited towards complex human activity recognition system.  Review of existing system confirms that still there is a large scope of enhancement as they lack applicability to real-life events and also doesn't offer optimal system performance. Therefore, the proposed manuscript presents a model for activity recognition system where the accuracy of recognition operation and system performance are retained with good balance. The study presents a simplified feature extraction process from spatial and temporal traits of the event feeds that is further subjected to the machine learning mechanism for boosting recognition performance
Volume: 9
Issue: 5
Page: 3465-3473
Publish at: 2019-10-01

Recommender system for surplus stock clearance

10.11591/ijece.v9i5.pp3813-3821
Vipul Agarwal , Vijayalakshmi A
Accumulation of the stock had been a major concern for retail shop owners. Surplus stock could be minimized if the system could continuously monitor the accumulated stock and recommend the stock which requires clearance. Recommender Systems computes the data, shadowing the manual work and give efficient recommendations to overcome stock accumulation, creating space for new stock for sale to enhance the profit in business. An intelligent recommender system was built that could work with the data and help the shop owners to overcome the issue of surplus stock in a remarkable way. An item-item collaborative filtering technique with Pearson similarity metric was used to draw the similarity between the items and accordingly give recommendations. The results obtained on the dataset highlighted the top-N items using the Pearson similarity and the Cosine similarity. The items having the highest rank had the highest accumulation and required attention to be cleared. The comparison is drawn for the precision and recall obtained by the similarity metrics used. The evaluation of the existing work was done using precision and recall, where the precision obtained was remarkable, while the recall has the scope of increment but in turn, it would reduce the value of precision. Thus, there lies a scope of reducing the stock accumulation with the help of a recommender system and overcome losses to maximize profit
Volume: 9
Issue: 5
Page: 3813-3821
Publish at: 2019-10-01

Web-based problem-based collaborative learning for converted muslim in learning Islamic knowledge

10.11591/ijeecs.v16.i1.pp516-523
Nurul Fatihah Sahidan , Nazrul Azha Mohamed Shaari , Hayati Abd Rahman
Web-based collaborative learning is well accepted learning methods since it provides flexibilities not only in term of learners’ interaction but also its timeliness learning materials. Even though there are many websites offer learning materials for Muslims generally but for new converted Muslims getting authentic materials and proper guidance are complicated. Hence, a web-based problem-based collaborative learning is proposed. This method integrates an elected virtual instructor to facilitate and support the new converted Muslims’ cognitive and emotional activities, develop their confidence of resolving and dealing with problems they are facing. This paper relates and analyzes the problem-based collaborative learning in terms of the functionality and user acceptance. Based on a survey conducted, it shows that 85% of the respondents found the system very useful and easy to use while 80%found that the system met their requirements. This system hypothetically able to help, and ease new converted Muslims in exploring Islamic authentic knowledge by using problem-based technique in web-based collaborative learning.
Volume: 16
Issue: 1
Page: 516-523
Publish at: 2019-10-01

Optimizing requirement analysis by the use of meta-heuristic in search based software engineering

10.11591/ijece.v9i5.pp4336-4343
Rajesh Kumar , Rakesh Kumar
Requirements analysis is the first phase of software development process and it is one of the main concerns of software engineers. The selection of requirements is a complex problem caused by the heterogeneity of the users and their varied interests and demands. In this paper, it is justified that their is a strong need of optimization in requirement analysis. The paper argues that requirement selection can be viewed as an application area of Search-Based Software Engineering(SBSE). The aim is to justify the claim that requirement engineering can be re-formulated as search problem to which meta-heuristic technique can be applied.
Volume: 9
Issue: 5
Page: 4336-4343
Publish at: 2019-10-01

Swarm algorithms in dynamic optimization problem of reactive power compensation units control

10.11591/ijece.v9i5.pp3967-3974
V.Z Manusov , P.V. Matrenin , N. Khasanzoda
Optimization of a power supply system is one of the main directions in power engineering research. The reactive power compensation reduces active power losses in transmission lines. In general, researches devoted to allocation and control of the compensation units consider this issue as a static optimization problem. However, it is dynamic and stochastic optimization problem that requires a real-time solution. To solve the dynamic optimization NP-hard problem, it is advisable to use Swarm Intelligence. This research deals with the problem of the compensation units power control as a dynamic optimization problem, considering the possible stochastic failures of the compensation units. The Particle Swarm Optimization and the Bees Algorithm were applied to solve it to compare the effectiveness of these algorithms in the dynamic optimization of a power supply system.
Volume: 9
Issue: 5
Page: 3967-3974
Publish at: 2019-10-01

Substitution-based linguistic steganography based on antonyms

10.11591/ijeecs.v16.i1.pp530-538
Fawwaz Zamir Mansor , Azizan Ismail , Roshidi Din , Aida Mustapha , Noor Azah Samsudin
The study of steganography focuses on strengthening the security in protecting content message by hiding the true intention behind the texts. However, existing linguistic steganography approach especially in synonym-based substitution is prone to attack. In this paper, a new substitution-based approach for linguistic steganography is proposed using antonyms. The antonym-based stego-text generation algorithm is implemented in a tool called the Antonym Substitution-based (ASb). Evaluation of ASb was carried out via verification and validation. The results showed highly favorable performance of this approach.
Volume: 16
Issue: 1
Page: 530-538
Publish at: 2019-10-01

The best quintic Chebyshev approximation of circular arcs of order ten

10.11591/ijece.v9i5.pp3779-3785
Abedallah M. Rababah
Mathematically, circles are represented by trigonometric parametric equations and implicit equations. Both forms are not proper for computer applications and CAD systems. In this paper, a quintic polynomial approximation for a circular arc is presented. This approximation is set so that the error function is  of degree $10$ rather than $6$; the Chebyshev error function equioscillates $11$ times rather than $7$; the approximation order is $10$ rather than $6$. The method approximates more than the full circle with Chebyshev   uniform error  of  $1/2^{9}$. The examples show the competence and simplicity of the proposed approximation, and that it can not be improved.
Volume: 9
Issue: 5
Page: 3779-3785
Publish at: 2019-10-01

Optimization of RF signal detection and alert system for restricted area

10.11591/ijeecs.v16.i1.pp325-332
Ili Najaa Aimi Mohd Nordin , Najla Aiman Nazari , Muhammad Rusydi Muhammad Razif , Nurulaqilla Khamis , Noraishikin Zulkarnain , Farkhana Muchtar , Nor Aira Zambri
This paper presents study on optimizing RF signal detection and alert system for restricted area. Nowadays, mobile phone utilization is very common among youngsters. Despite of being very useful for educational purpose, it turns into a noteworthy issue while being smuggled into restricted area, such as examination hall and used as a cheating tool. To overcome this problem, an advancement on the detection and alert system of active mobile phone was proposed by implementing RF signal detection system optimization using multi-band dipole antenna and alert system utilizing LED and camera. The system demonstrated higher sensitivity to 3G signal followed by GSM and Wi-Fi with the decrease in voltage value across the LED when distinguishing 3G, GSM and Wi-Fi signal with the estimation of 2.316 V, 1.162 V and 1.054 V respectively. The alert system was improved by activating LED and camera instead of buzzer in displaying the region of the active mobile phone. The camera was able to effectively capture the conceivable cheating area when active mobile phone is present. The images of the potential cheating region can be recovered from the computer. This framework can assist the invigilators with being cautioned to the potential regions of cheating using mobile phone.
Volume: 16
Issue: 1
Page: 325-332
Publish at: 2019-10-01

A review of object-oriented approach for test case prioritization

10.11591/ijeecs.v16.i1.pp429-434
Umar Farooq , Hannani Aman , Aida Mustapha , Zainuri Saringat
The most essential phase in regression testing is Test Case Prioritization (TCP), with its primary objective to increase the fault detection rate at different stages during testing. Prior to achieving the objective, existing evidence of techniques in TCP must be synthesized and analyzed. At present, fault detection for TCP based on object-oriented features only consider statement, module, and class level. The important features of object-oriented (OO) programming like inheritance and polymorphism have not been fully explored for fault detection in TCP. Such OO concepts are important for test case selection and in turn for ranking the test cases (prioritization). This paper reviews various test case prioritization techniques specific to OO systems. This review is hoped to highlight the importance and usage of TCP in relation to object-oriented software development lifecycle.
Volume: 16
Issue: 1
Page: 429-434
Publish at: 2019-10-01

A fuzzy system for detection and classification of textile defects to ensure the quality of fabric production

10.11591/ijece.v9i5.pp4277-4286
Iman Subhi Mohammed , Israa Mohammed Alhamdani
The aim of this research focuses on construct a computerized system for textile defects detection. The system merges between image processing methods, statistical methods in addition to the Intelligent techniques via Neural Network and Fuzzy Logic. Gabor filters were used to identify edges and to highlight defective areas in fabric images, then to train the neural network on statistical and geometry features derived from fabric images to form the special neural network distinguish and classify defects into the fourteen categories, which are the most common defects in the textile factory.  The proposed work includes two phases. The first phase is to detect the defects in fabrics. The second phase is the classification phase of the defect. At the defect detection stage, a Discrete Cosine Transfer (DCT) converts the images to the frequency domain.  Image features then drawn and introduce them to the Elman Neural Network to detect the existence of defects. In the classification stage, the images are converted to the frequency domain by the Gabor filter and then the image features are extracted and inserted into the back propagation network to classify the fabric defects in those images. Fuzzy logic is then applied to neural network outputs and interference values are used in fuzzy logic to increase final discrimination. We evaluate a distinction rate of 91.4286% .After applying the fuzzy logic to neural network output; the discrimination rate was raised to 97.1428%. 
Volume: 9
Issue: 5
Page: 4277-4286
Publish at: 2019-10-01

Global system for mobile communication based domestic electrical load control using arduino uno

10.11591/ijeecs.v16.i1.pp342-348
L. Velusamy , S. Salimin , S. N. M. Rozi , M. N. Abdullah , N. H. Radzi , S. A. Jumaat , A. F. M. Noor , R. Hamdan
This paper presents a wireless operation to switch on and off the load such as light, fan and power socket by sending messages via smartphone. The proposed project is focused on usage of the global system for mobile communication (GSM) protocol, which enables the user to control loads away from targeted area using the frequency bandwidths. The concept of serial communication and Uno microcontroller-commands are being applied towards development of the GSM based domestic electrical load control using Arduino UNO system. Besides that, the existing electrical switches that control the load manually is not being removed and this gives a safer control over the switches with low voltage usage technique. This system is designed to control electrical devices throughout the house with easy installation process, ease of use and cost effective design and implementation. Additionally, the system has several possibility to help satisfy the needs of the elderly and the handicapped at houses. Prototype of GSM based domestic electrical load control using Arduino UNO was implemented and successfully tested with maximum of five loads such as light, fan and power sockets.
Volume: 16
Issue: 1
Page: 342-348
Publish at: 2019-10-01

Comparing machine learning and ensemble learning in the field of football

10.11591/ijece.v9i5.pp4321-4325
Shuaib Khan , Kirubanand V. B
Football has been one of the most popular and loved sports since its birth on November 6th, 1869. The main reason for this is because it is highly unpredictable in nature. Predicting football matches results seems like the perfect problem for machine learning models. But there are various caveats such as picking the right features from an enormous number of available features.  There have been many models which have been applied to various football-related datasets. This paper aims to compare Support Vector Machines a machine learning model and XGBoost an Ensemble learning model and how Ensemble Learning can greatly improve the accuracy of the predictions.
Volume: 9
Issue: 5
Page: 4321-4325
Publish at: 2019-10-01
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