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29,922 Article Results

Evaluation of psoriasis skin disease classification using convolutional neural network

10.11591/ijai.v9.i2.pp349-355
Rosniza binti Roslan , Iman Najwa Mohd Razly , Nurbaity Sabri , Zaidah Ibrahim
Skin disease has lower impact on mortality compared to others but instead it has greater effect on quality of life because it involves symptoms such as pain, stinging and itchiness.  Psoriasis is one of the ordinary skin diseases which are relapsing, chronic and immune-mediated inflammatory disease.  It is estimated about 125 million people worldwide being infected with various types of skin infection.  Challenges arise when patients only predict the skin type disease they had without being accurately and precisely examined.  This is because as human being, they only observe and look at the diseases on the surface of the skin with their naked eye, where there are some limits, for example, human vision lacks of accuracy, reproducibility and quantification in the collection of image information.  As Plaque and Guttate are the most common Psoriasis skin disease happened among people, this paper presents an evaluation of Psoriasis skin disease classification using Convolutional Neural Network.  A total of 187 images which consist of 82 images for Plaque Psoriasis and 105 images for Guttate Psoriasis has been used which are retrieved from Psoriasis Image Library, International Psoriasis Council (IPC) and DermNet NZ.  Convolutional Neural Network (CNN) is applied in extracting features and analysing the classification of Psoriasis skin disease.  This paper showed the promising used of CNN with the accuracy rate of 82.9% and 72.4% for Plaque and Guttate Psoriasis skin disease, respectively.
Volume: 9
Issue: 2
Page: 349-355
Publish at: 2020-06-01

Transmission line fault identification and classification with integrated FACTS device using multiresolution analysis and naïve bayes classifier

10.11591/ijpeds.v11.i2.pp907-913
Elhadi Emhemed Aker , Mohammad Lutfi Othman , Ishak Aris , Noor Izzri Abdul Wahab , Hashim Hizam , Osaj Emmanuel
This paper is present a novel approach for solving the pending under-reach problem encountered by distance relay protection scheme in the 3rd zones protection coverage for a midpoint STATCOM compensated transmission lines. The propose transmission line model is develop in Matlab for analyzed feature extraction using Discrete Wavelet multiresolution analysis approach. Extracted feature from standard deviation and entropy energy contents of SLG transient faults current at location beyond the integrated STATCOM used for machine learning algorithm model building using WEKA software. The Naïve Bayes classifier model perform best with robustness prediction and detection of faults with quick convergence even with less training data. The outperformance of the proposed classifier has been 100 % for the relay algorithm modification for under-reach problem elimination in 3rd zones protection coverage.
Volume: 11
Issue: 2
Page: 907-913
Publish at: 2020-06-01

Convolutional recurrent neural network with template based representation for complex question answering

10.11591/ijece.v10i3.pp2710-2718
A. Chandra Obula Reddy , K. Madhavi
Complex Question answering system is developed to answer different types of questions accurately. Initially the question from the natural language is transformed to an internal representation which captures the semantics and intent of the question. In the proposed work, internal representation is provided with templates instead of using synonyms or keywords. Then for each internal representation, it is mapped to relevant query against the knowledge base. In present work, the Template representation based Convolutional Recurrent Neural Network (T-CRNN) is proposed for selecting answer in Complex Question Answering (CQA) framework. Recurrent neural network is used to obtain the exact correlation between answers and questions and the semantic matching among the collection of answers. Initially, the process of learning is accomplished through Convolutional Neural Network (CNN) which represents the questions and answers separately. Then the representation with fixed length is produced for each question with the help of fully connected neural network. In order to design the semantic matching between the answers, the representation of Question Answer (QA) pair is given into the Recurrent Neural Network (RNN). Finally, for the given question, the correctly correlated answers are identified with the softmax classifier.
Volume: 10
Issue: 3
Page: 2710-2718
Publish at: 2020-06-01

Deep learning in non coding variant (a brief overview)

10.11591/ijeecs.v18.i3.pp1432-1438
Lee Kuan Xin , Afnizanfaizal Abdullah
The 21st centuries were deemed to be the era of big data. Data driven research had become a necessity. This hold true not only in the business world, yet also in the field of biomedical world. From a few years of biological data extraction and derivation. With the advancement of Next Generation Sequencing, genomics data had grown to become an ambiguous giant which could not keep up with the pace of its advancement in it analysis counter parts. This results in a large amount of unanalysed genomic data. These genomic data consist not only plain information, researcher had discovered the potential of most gene called the non-coding variant and still failing in identifying their function. With the growth in volume of data, there is also a growth of hardware or technologies. With current technologies, we were able to implement a more complex and sophisticated algorithm in analysis these genomics data. The domain of deep learning had become a major interest of researcher as it was proven to have achieve a significant success in deriving insight from various field. This paper aims to review the current trend of non-coding variant analysis using deep learning approach.
Volume: 18
Issue: 3
Page: 1432-1438
Publish at: 2020-06-01

Enhancement of voltage regulation using a 7-Level inverter based electric spring with reduced number of switches

10.11591/ijpeds.v11.i2.pp555-565
K. K. Deepika , J. Vijaya Kumar , G. Kesava Rao
Electric Springs has been testified recently to enhance voltage regulation in distribution systems using demand side management. In this paper, a 7-level Multilevel Inverter (MLI) with a resonant switched capacitor Converter based on sinusoidal PWM, is implemented to analyze the performance of an electric spring under voltage variations at PCC. By the proposed MLI based ES, voltage regulation of critical load voltage is studied for voltage sag and swell conditions. Remarkable features of the proposed topology are maintaining voltage balance in input capacitors and reduction of power components. Simulations have been done in MATLAB/Simulink on distribution system with DGs equipped with MLI based ES under line voltage anomalies. Tested results are analyzed with THD% in critical load voltage.
Volume: 11
Issue: 2
Page: 555-565
Publish at: 2020-06-01

A study of code change patterns for adaptive maintenance with AST analysis

10.11591/ijece.v10i3.pp2719-2733
Omar Meqdadi , Shadi Aljawarneh
Example-based transformational approaches to automate adaptive maintenance changes plays an important role in software research. One primary concern of those approaches is that a set of good qualified real examples of adaptive changes previously made in the history must be identified, or otherwise the adoption of such approaches will be put in question. Unfortunately, there is rarely enough detail to clearly direct transformation rule developers to overcome the barrier of finding qualified examples for adaptive changes. This work explores the histories of several open source systems to study the repetitiveness of adaptive changes in software evolution, and hence recognizing the source code change patterns that are strongly related with the adaptive maintenance. We collected the adaptive commits from the history of numerous open source systems, then we obtained the repetitiveness frequencies of source code changes based on the analysis of Abstract Syntax Tree (AST) edit actions within an adaptive commit. Using the prevalence of the most common adaptive changes, we suggested a set of change patterns that seem correlated with adaptive maintenance. It is observed that 76.93% of the undertaken adaptive changes were represented by 12 AST code differences. Moreover, only 9 change patterns covered 64.69% to 76.58% of the total adaptive change hunks in the examined projects. The most common individual patterns are related to initializing objects and method calls changes. A correlation analysis on examined projects shows that they have very similar frequencies of the patterns correlated with adaptive changes. The observed repeated adaptive changes could be useful examples for the construction of transformation approaches
Volume: 10
Issue: 3
Page: 2719-2733
Publish at: 2020-06-01

Enhancement of cascaded multi-level VSC STATCOM performance using ANN in the presence of faults

10.11591/ijpeds.v11.i2.pp895-906
Mohamad M Almelian , Izzeldin I Mohd , Abu Zaharin Ahmad , Mohamed A Omran , Mohamed Salem , Awang Jusoh , Tole Sutikno
A system can be disturbed in terms of stability when connected to a number of loads at the distribution ends or when subjected to faults. To reverse such systems to a stable state, FACTS devices such as static synchronous compensator (STATCOM) are used. In this paper, a cascaded multi-level voltage source converter (VSC) STATCOM was designed and implemented with a novel space vector pulse width modulation (SVPWM) scheme. Artificial neural network (ANN) controller was used instead of instead of Proportional-Integral (PI) controller in the proposed scheme to improve the response time (RT) and performance of STATCOM in terms of power factor (PF) and voltage amplitude during periods of voltage sag. During the implementation, two fault sources (single-line-to-ground (SLG) and line-to- line (LL) faults) were used to create voltage sag. STATCOM was subjected to performance evaluation in the presence of these disturbances via MATLAB simulation in IEEE 3-bus system. The outcome of the simulation studies showed the ANN controller to perform better than PI as it was able to rapidly recover voltage value (<1 cycle) with unity PF.
Volume: 11
Issue: 2
Page: 895-906
Publish at: 2020-06-01

Optimization of wind energy conversion systems – an artificial intelligent approach

10.11591/ijpeds.v11.i2.pp1040-1046
Ying Ying Koay , Jian Ding Tan , Siaw Paw Koh , Kok Hen Chong , Sieh Kiong Tiong , Janaka Ekanayake
The environmentally friendly wind energy conversion system has become one of the most studied branches of sustainable energy. Like many other power generator, maximum power point tracking is an easy yet effective way to boost the efficiency of the conversion system. In this research, a modified Electromagnetism-like Mechanism Algorithm (EM) is proposed for the maximum power point tracking (MPPT) scheme of a micro-wind energy conversion system (WECS). In contrast with the random search steps used in a conventional EM, modified EM is enhanced with a Split, Probe, and Compare (SPC-EM) feature which ensures solutions with higher accuracies quicker by not having to scrutinize the search in details at the beginning stages of the iterations. Experiments and simulations are carried to test the SPC-EM in tracking the maximum power point under different wind profiles. Results indicate that the performance of the modified EM showed significant improvement over the conventional EM in the benchmarking. It can thus be concluded that based on the simulations, the SPC-EM performs well as an MPPT scheme in a micro-WECS.
Volume: 11
Issue: 2
Page: 1040-1046
Publish at: 2020-06-01

Control of PMSG based variable speed wind energy conversion system connected to the grid with PI and ADRC approach

10.11591/ijpeds.v11.i2.pp953-968
Youssef Barradi , Khalida Zazi , Malika Zazi , Naoufel Khaldi
This paper presents the modeling and simulation of wind energy Conversion System using the Permanent Magnet Synchronous Generator (PMSG). The objectives are: to extract the maximum power of the wind speed by controlling the electromagnetic torque of the PMSG, to maintain constant the DC-link voltage despite the wind speed variations and to attain the unity power factor. In order to ensure a regulation with high performance and a good robustness against the internal and the external disturbances, a new control strategy called the Active Disturbance Rejection Control (ADRC) is used. Therefore, the Analysis and simulation of the ADRC and PI controllers are developed with MATLAB/Simulink software. The performance of these controllers is compared in term of references tracking, robustness and grid faults.
Volume: 11
Issue: 2
Page: 953-968
Publish at: 2020-06-01

Algorithm development and hardware implementation for medical image compression system: a review

10.11591/ijeecs.v18.i3.pp1331-1341
Noor Huda Ja’afar , Afandi Ahmad
In the high-tech world, medical imaging is very important to diagnose and analyze illness inside human body. The increasing number of patients annually has continuously growth the amount of medical imaging data generated and directly causes a demand for data storage. Generally, medical images are rich with data, where these data are important for diagnosing purpose. However, some of the data represents redundant information and sometimes can be discarded. Thus, the research area on medical image compression dealing with three-dimensional (3-D) modalities need to be given more attention and exploration. The algorithm development using wavelet transform with software implementation are the famous topics explored among researchers, whilst fewer works have been done in utilizing curvelet transform in medical image compression. Along with that, very limited hardware implementation of 3-D medical image compression is discovered. In term of performance evaluation, most of the previous works conducted objective test compared with subjective test. To fill in this gap, medical image compression system will be reviewed, with the aim to identify the recent method used in medical image compression system. This paper thoroughly scrutinizes the recent advances in medical image compression mainly in terms of compression method, algorithm development with software and hardware implementations and performance evaluation. In conclusion, the overall picture of the medical image compression landscape, where most of the researchers more focused on algorithm development or software implementations without having the combination of software and hardware implementations.
Volume: 18
Issue: 3
Page: 1331-1341
Publish at: 2020-06-01

Photovoltaic emulator of different solar array configurations under partial shading conditions using damping injection controller

10.11591/ijpeds.v11.i2.pp1019-1030
Mustapha Alaoui , Hattab Maker , Azeddine Mouhsen , Hicham Hihi
In the last decades, researchers and scientists have been trending towards photovoltaic (PV) solar energy research as one of the noteworthy renewable energies. As a matter of fact, the need for a laboratory system devoted to performing measurements and experimentation on PV systems is being increased. The PV array emulator is designed to accomplish this task by reproducing accurately the electrical behavior of real PV sources. The present paper proposes thus a new control and design of PV array emulators. It is based essentially on a hybrid Damping Injection controller. The proposed control strategy circumvents obviously the existing PV emulator's limitations in terms of accuracy, speed and partial shading emulation. Several results are given and discussed to show the efficiency of the proposed system to emulate PV modules and different PV array configurations under uniform solar irradiance and partial shading conditions.
Volume: 11
Issue: 2
Page: 1019-1030
Publish at: 2020-06-01

Design and analysis of controllers for high voltage gain DC-DC converter for PV panel

10.11591/ijpeds.v11.i2.pp594-604
S. Nagaraj , R. Ranihemamalini , L. Rajaji
Bidirectional high gain DC-DC buck boost converter is a virtual interface among PV source and inverter fed motor drive. In this article, a PV panel integrating a non-isolated bidirectional DC/DC converter that has high voltage gain voltage and a 3 phase three level DC/AC inverter is projected. It highlights the comparison between proportional integral controller (PIC), fractional order proportional integral derivative Controller (FOPIDC) and fuzzy logic controller (FLC) based Bidirectional DC/DC Power Converter System (BDDPCS). The design, model and simulation using SIMULINK of open loop BDDPCS and closed loop PIC, FOPIDC and FLC based BDDPCS are done and the results are discussed. The findings indicate higher performance for FLC based control of BDDPCS. The proposed BDDPCS has merits such as bidirectional power transferability, lesser hardware count with enhanced dynamic response. The hardware of BDDPCS is tested and the experiment result is compared in association with simulation results.
Volume: 11
Issue: 2
Page: 594-604
Publish at: 2020-06-01

Passerine swarm optimization algorithm for solving optimal reactive power dispatch problem

10.11591/ijaas.v9.i2.pp101-109
Lenin Kanagasabai
This paper presents Passerine Swarm Optimization Algorithm (PSOA) for solving optimal reactive power dispatch problem. This algorithm is based on behaviour of social communications of Passerine bird. Basically, Passerine bird has three common behaviours: search behaviour, adherence behaviour and expedition behaviour. Through the shared communications Passerine bird will search for the food and also run away from hunters. By using the Passerine bird communications and behaviour, five basic rules have been created in the PSOA approach to solve the optimal reactive power dispatch problem. Key aspect is to reduce the real power loss and also to keep the variables within the limits. Proposed Passerine Swarm Optimization Algorithm (PSOA) has been tested in standard IEEE 30 bus test system and simulations results reveal about the better performance of the proposed algorithm in reducing the real power loss and enhancing the static voltage stability margin
Volume: 9
Issue: 2
Page: 101-109
Publish at: 2020-06-01

Ca[Mg3SiN4]Ce3+ phosphor: effect of particle concentration on lighting properties of the 7000K IPW-LEDs

10.11591/ijpeds.v11.i2.pp566-570
Q. S. Vu , Tang Tin Dao , Minh Tran
Nowadays, the white-light-emitting diodes (LEDs) have a vast application on the real-life based on its superior advantages such as energy efficiency, long lifetime, compactness, and environment-friendly and designable features in comparison with incandescent and fluorescent lamps. In this paper, we co-doping the Ca[Mg3SiN4]Ce3+ Phosphor on the phosphor compound of the 7000K In-cup Packaging White LEDs (IPW-LEDs) for improving the lighting properties. By varying the concentration of Ca[Mg3SiN4]Ce3+ Phosphor from 0% to 1.8%, the effect of the Ca[Mg3SiN4]Ce3+ Phosphor on the D-CCT, CRI, CQS, and LO of the 7000K IPW-LEDs are investigated. Using the Light Tool and software, the research results show that the concentration of the IPW-LEDs has a massive influence on the lighting properties of the 7000K IPW-LEDs. All the results are convinced by Light Tool simulation.
Volume: 11
Issue: 2
Page: 566-570
Publish at: 2020-06-01

Performance enhancement of solar powered floating photovoltaic system using arduino approach

10.11591/ijpeds.v11.i2.pp651-657
Nur Amirah Abdul Jamil , Siti Amely Jumaat , Suriana Salimin , Mohd Noor Abdullah , Ahmad Fateh Mohamad Nor
This paper presents Performance Enhancement of Solar Powered Floating Photovoltaic System using Arduino Approach. In the project, an Arduino nano as a main controller of the system. The objective of this project to monitor performance of the voltage, current and power output respectively. Furthermore, the prototype of the research is testing in two conditions: on water surface and on a land area. Based on the results, the power of the photovoltaic on the water surface is increased compared on the land area. The conclusion for this project is it can generate electricity using floating photovoltaic and the same time to monitor output of the system.
Volume: 11
Issue: 2
Page: 651-657
Publish at: 2020-06-01
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