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Mitigation of overvoltage due to high penetration of solar photovoltaics using smart inverters volt/var control

10.11591/ijeecs.v19.i3.pp1259-1266
Dilini Almeida , Jagadeesh Pasupuleti , Janaka Ekanayake , Eshan Karunarathne
The modern photovoltaic (PV) inverters are embedded with smart control capabilities such as Volt/Var and Volt/Watt functions to mitigate overvoltage issues. The Volt/Var control has gained a significant attention in regulating grid voltage through reactive power compensation. However, the reactive power capability of a PV inverter is limited during peak irradiance and could be improved by curtailing the active power generation and by oversizing the PV inverter. This paper analyzes the performance of Volt/Var function of smart PV inverters in mitigating overvoltage issues due to high PV integration and thus increasing the hosting capacity of low voltage distribution networks (LVDNs). The study is conducted on a real Malaysian LVDN considering two different Volt/Var set points under different PV penetration levels. Results demonstrate that the oversized smart PV inverter could enhance the Volt/Var functionality by increasing its reactive power capability than a typical smart PV inverter. Further it reveals that adaptation of sensitive Volt/Var set points with shorter deadbands increase the PV hosting capacity of LVDNs.
Volume: 19
Issue: 3
Page: 1259-1266
Publish at: 2020-09-01

Nutritional status of under-five children in rural Bangladesh

10.11591/ijphs.v9i3.20425
Liton Chandra Sen , Md. Sabbir Ahmed , Abu Shoeb Md. Touhiduzzaman , Soumitra Mandal , AH Towfique Ahmed , Sanjit Kumar Das , Rama Saha
A cross-sectional study was carried out in Dumki Upazila of Patuakhali district in Bangladesh to assess the prevalence of stunting, wasting and underweight among the under-five children. Anthropometric measurements were taken from all children, aged 0-59 months in the studied area using wooden height board and digital weight machine. We used WHO Anthro software for analyzing the z scores of the children. A total of 4409 (2296 boys and 2113 girls) under five children were counted for anthropometric analysis.  Regarding the Height-for-age Z-score (HAZ), the study revealed that the prevalence of stunting was 27.10% (95% CI: 25.8-28.5) of the children while 7.80% (95% CI: 7-8.6) were severe stunting. By assessing the Weight-for-height Z-score (WHZ), the study showed that 11.20% (95% CI: 10.3-12.1) were wasting whereas 3% (95% CI 2.5-3.5) were severe wasting. According to Weight-for-age Z-score (WAZ), about 18.20% (95% CI: 17-19.3) were underweight and 4.1% (95% CI: 3.5-4.7) were underweight. The findings of the study show that prevalence of stunting is very high. Focusing on childhood stunting is a high priority, and there should be comprehensive efforts to increase the overall nutritional status of the under-five children in this area.
Volume: 9
Issue: 3
Page: 205-210
Publish at: 2020-09-01

Social comparison and life satisfaction in social media: The role of mattering and state self-esteem

10.11591/ijphs.v9i3.20509
Patrick P. T. Sim , Kususanto Ditto Prihadi
The overarching aim of this study is to explain how comparing self to others in social media might predict one’s sense of life satisfaction. In order to achieve that, we test the hypothesis that mattering and state self-esteem play a serial mediation that explains the link between social comparison in social media and life satisfaction. One hundred and forty-seven participants’ ages between 18 to 35 were recruited to participate in this research and were asked to fill up the Iowa-Netherlands Comparison Orientation Measure, General Mattering Scale, State Self-Esteem Scale and Riverside Life Satisfaction Scale questionnaires. Bias-free Bootstrap Method with 5000 sample has been conducted to analyze the relationship among the variables, and the results suggested that the overall model of the predictor significantly contributed to life satisfaction. Nevertheless, because social comparison did not predict the sense of mattering, serial mediation did not occur as per hypothesized. Our supplementary analyses indicated that state self-esteem fully mediated the contribution of mattering on life satisfaction. Implication, limitation and suggestions are discussed at the end of the paper.
Volume: 9
Issue: 3
Page: 245-254
Publish at: 2020-09-01

Design and implementation hamming neural network with VHDL

10.11591/ijeecs.v19.i3.pp1469-1479
Liqaa Saadi Mezher
Hamming Neural Network is type of artificial neural network consist of two types of layers (feed forward layers and recurrent layer). In this paper, two inputs of patterns in bianary number were used. In the first layer, two neurons and pure line function were used. In the second layer, three neurons and positive line function were used. Also applied Hamming Neural networks algorithm in three simulation methods (logical gate method, software program coding method and instant block diagram method). In this work in VHDL software program was used and FPGA hardware used.
Volume: 19
Issue: 3
Page: 1469-1479
Publish at: 2020-09-01

Machine learning-based technique for big data sentiments extraction

10.11591/ijai.v9.i3.pp473-479
Noraini Seman , Nurul Atiqah Razmi
A huge amount of data is generated every minute for social networking and content sharing via Social media sites that can be in a form of structured, unstructured or semi-structured data.  One of the largest used social media sites is Twitter, where each and every day millions of data generated in the form of unstructured tweets. Tweets or opinions of the people can be used to extract sentiments of the people. Sentiment analysis is beneficial for organizations to improve their products and make required changes on demand to increase their profit. In this paper, three machine learning algorithms Support Vector Machine (SVM), Decision Trees (DT), and Naive Bayes (NB) for classifying sentiments of twitters data. The purpose of this research is to compare the outcomes of these algorithms to identify best machine learning method which gives most accurate and efficient results for classifying twitter data. Our experimental result shows that same preprocessing methods on a different dataset affect similarly the classifiers performance. After analyzing the results it is observed that SVM provides 64.96%, 71.26% and 91.25% precision which is better than other two algorithms. Also, overall Recall and F-measure rate of SVM is greater than NB and DT for three datasets. However, it is important to further study current available preprocessing techniques that help us to improve results of various classifiers.
Volume: 9
Issue: 3
Page: 473-479
Publish at: 2020-09-01

Effect of heating temperature on quality of bio-briquette empty fruit bunch fiber

10.11591/ijaas.v9.i3.pp192-200
Nofriady Handra , Anwar Kasim , Gunawarman Gunawarman , Santosa Santosa
Empty Fruit Bunches (EFB) are one of the palm oil industry wastes, which are quite plentiful and currently unused optimally. Biomass is one of the renewable energy resources which has important roles in the world. The bio-briquettes are manufactured through densification of waste biomass by implementing certain processes. This research aimed to obtain variations in the mold temperature at 150 ºC, 200 ºC, and 250 ºC to the calorific value and toughness of the briquette material. The toughness was tested using ASTM D 440-86 R02 standard. Arduino program was used for setting the heating resistance time of the mold, which was 20 minutes and the thermal controller was used to adjust the temperature variation. The average mold pressure was 58 Psi. The highest heating value was obtained at a mold temperature of 250 ºC with a value of 5256 cal/g, and the lowest was resulted at a temperature of 150 ºC (4117 cal/g). Meanwhile, the briquette toughness test at 200 ºC mold temperature indicated good data results in which the average loss of fiber particles was only 4.17 %, this was because the adhesion between particles by lignin and cellulose in the fiber functions optimally at this temperature so that the resistance of briquettes went through minor damage.
Volume: 9
Issue: 3
Page: 192-200
Publish at: 2020-09-01

Web design structure with wordpress content management for sports centre booking system

10.11591/ijeecs.v19.i3.pp1643-1653
Nor Sajidah Ab Ghani , Murizah Kassim , Aziati Husna Awang
Sports center booking system need to be more systematic to increase its efficiency. The world wide web (WWW) had been a revolution and it has been utilized to be tools of automation in many applications, including managing booking and payment system in this area of services.  However, existing system needs an ID booking to book the facilities at the court centre and does not delegate any confirmation to users on their booking. This paper aims at integrating stripe payment method by using the WordPress platform where it is one of the content management system (CMS) by using XAMPP. MySQL has been used to store the database while PHP and HTML have been designed to generate QR code. This system was designed based on some function needed for the new member, staffs, and students. The procedure is that the new members will register and pay their members fees. Existing student and staff will just need to sign in using their ID number. This system has provided a booking system which presented the availability of time and date as well as the payment for the new members. Upon booking and payment, email and QR code are given to the user after the confirmation booking by an administrator.  The result shows the increase of efficiency after implementing the new features on the web system which shows 86.66% of increases in term of using the website to book the facilities at the sports centre from the existing system.
Volume: 19
Issue: 3
Page: 1643-1653
Publish at: 2020-09-01

Modelling of time-to collision for unmanned aerial vehicle using particles swarm optimization

10.11591/ijai.v9.i3.pp488-496
Sulaiman bin Sabikan , Nawawi. S. W , NAA Aziz
A method for the development of Time-to-Collision (TTC) mathematical model for outdoor Unmanned Aerial Vehicle (UAV) using Particles Swarm Optimization (PSO), are presented. TTC is the time required for a UAV either to collide with any static obstacle or completely stop without applying any braking control system when the throttle is fully released. This model provides predictions of time before UAV will collide with the obstacle in the same path based on their parameter, for instance, current speed and payload. However, this paper focus on the methodology of the implementation of PSO to develop the TTC model for 5 different set of payloads. This work utilizes a quadcopter as our testbed system, that equipped with a Global Positioning System (GPS) receiver unit, a flight controller with data recording capability and ground control station for real-time monitoring. The recorded onboard flight mission data for 5 different set of payloads has been analyzed to develop a mathematical model of TTC through the PSO approach. The horizontal ground speed, throttle magnitudes and flight time stamp are extracted from the on-board quadcopter flight mission. PSO algorithm is used to find the optimal linear TTC model function, while the mean square error is used to evaluate the best fitness of the solution. The results of the TTC mathematical model for each payload are described.
Volume: 9
Issue: 3
Page: 488-496
Publish at: 2020-09-01

Region of interest-based image retrieval techniques: a review

10.11591/ijai.v9.i3.pp520-528
Mardhiyah Md Jan , Nasharuddin Zainal , Shahrizan Jamaludin
This paper presents a review of the region of interest-based (ROI) image retrieval techniques. In this study, the techniques, the performance evaluation parameters, and databases used in image retrieval process are being reviewed. A part of an image that is considered important or a selected certain area of the image is what defines a region of interest. Retrieval performance in large databases can be improved with the application of content-based image retrieval systems which deals with the extraction of global and region features of images. The capability of reflecting users' specific interests with greater accuracy has shown to be more effective when using region-based features compared to global features. Segmentation, feature extraction, indexing, and retrieval of an image are the tasks required in retrieving images that contain similar regions as specified in a query. The idea of the region of interest-based image retrieval concepts is presented in this paper and it is expected to accommodate researchers that are working in the region-based image retrieval system field. This paper reviews the work of image retrieval researchers in the span of twenty years. The main goal of this paper is to provide a comprehensive reference source for scholars involved in image retrieval based on ROI.
Volume: 9
Issue: 3
Page: 520-528
Publish at: 2020-09-01

Investigation of iris segmentation techniques using active contours for non-cooperative iris recognition

10.11591/ijeecs.v19.i3.pp1275-1286
Akinola Samuel Akinfende , Agbotiname Lucky Imoize , Olumide Simeon Ajose
Iris image segmentation process based on graphical user interface (GUI) to accurately localize the iris structure is presented in this paper. The major challenge confronting the precision of an iris recognition model is how to determine the accuracy of the iris segmentation and localization. There are varying parameters that introduce constraints during feature extraction and these greatly affect the matching performance during iris localization. To this end, the Integro-differential operator, which involves the detection of inner and outer regions of the iris, and the circular hough transform, which is capable of detecting the circular boundary from the edge mapping were investigated, and an active contour model was evolved. In the evolved model, an emerging curve mapped with the zeros of the data set function is experimentally exploited. To demonstrate the suitability of the model for precise iris recognition, its parameters were compared against other related models. Simulation results show that the model has higher flexibility of substitution of images, and the images could be analyzed more accurately with less false rejections (FR) and false acceptance (FA) in comparison with the integro-differential operator. This implies that images could be analyzed faster using the evolved model, and easily substituted especially in situations where the need to care for numerous eye patients occur.
Volume: 19
Issue: 3
Page: 1275-1286
Publish at: 2020-09-01

Rice false smut detection based on faster R-CNN

10.11591/ijeecs.v19.i3.pp1590-1595
Prabira Kumar Sethy , Nalini Kanta Barpanda , Amiya Kumar Rath , Santi Kumari Behera
Rice false smut is one of the most dangerous diseases in rice at the ripening phase caused by Ustilaginoidea Virens. It is one of the most important grain diseases in rice production worldwide. Its epidemics not only lead to yield loss but also reduce grain quality because of multiple mycotoxins generated by the causative pathogen. The pathogen infects developing spikelets and specifically converts individual grain into rice false smut ball. Rice false smut balls seem to be randomly formed in some grains on a panicle of a plant in the paddy field. In this study, we suggest a novel approach for the detection of rice false smut based on faster R-CNN. The process of faster R-CNN comprises regional proposal generation and object detection. The both tasks are done in same convolutional network. Because of such design it is faster for object detection. The faster R-CNN is able to detect the RFS using rectangular labelling from on-field images. The proposed approach is the initial steps to make a prototype for the automatic detection of RFS.
Volume: 19
Issue: 3
Page: 1590-1595
Publish at: 2020-09-01

Frequency response analysis technique for induction motor short circuit faults detection

10.11591/ijpeds.v11.i3.pp1653-1659
A. A. Alawady , M. F. M. Yousof , N. Azis , M. A. Talib
The paper presents the description for diagnostic methods of induction motor's stator windings fault. The presented methods use Frequency Response Analysis (FRA) technique for detection of Winding Faults in Induction Motor . This method is previously reliable method for faults diagnosis and detection in many parts of transformers including transformer windings. In this paper, this method was used for motor windings faults detection. This paper presents the FRA response interpretation on internal short circuit (SC) fault at stator winding on three cases studies of different three-phase induction motors (TPIM), were analysed according to two status: healthy induction motor at normal winding status and same motor with windings shorted of main windings. A conclusion of this paper provides the interpretation of and validation the FRA response due to internal SC fault case by using NCEPRI algorithm, which is considered as one of certified statistical indicators. The proposed method in this paper had a useful result for detect and diagnosis of stator windings faults of TPIM. The applications of developed method can be used to detece the other machines types faults.
Volume: 11
Issue: 3
Page: 1653-1659
Publish at: 2020-09-01

Full versus decoupled constant matrices to speed up power system state estimation

10.11591/ijpeds.v11.i3.pp1287-1297
Meriem Majdoub , Bouchra Cheddadi , Omar Sabri , Abdelaziz Belfqih , Jamal Boukherouaa
This paper presents a performance evaluation of two solutions to reduce computational burden of the traditional Weighted Least Squares Algorithm for power system state estimation: Simplified methods SWLS1 / SWLS2 based on full constant matrices and Fast decoupled FDWLS based on decoupled constant matrices. First, the algorithms were tested on IEEE 14 and 118 bus transmission systems. Second, the solutions were tested on a rural distribution feeder to evaluate the response of the algorithms to high R/X ratio. Results show that for transmission systems, FDWLS is the fastest method but more sensitive to erroneous measurements. Simplifications considered in FDWLS, are not valid in distribution systems with high R/X ratio this results in slowing down the algorithm convergence speed considerably compared to SWLS2 which performs well. SWLS2 algorithm presents a promising solution to reduce computation time for application in future smart grid.
Volume: 11
Issue: 3
Page: 1287-1297
Publish at: 2020-09-01

An approach of controlling the inverter-based generator for use in an islanded microgrid

10.11591/ijpeds.v11.i3.pp1610-1616
Suchart Janjornmanit , Sakorn Panta , Vishnu Thonglek
The controls of power generation by the inverter-based generator are proposed in this work. The proposed control adjusts the active power output by varying the phase angle instead of the conventional frequency variation. The benefit of operating the network by a fixed frequency is that it eradicates the problems associated with the frequency deviation. The PID controls with recommended gain adjustment are proposed to control the power generation. The power generation schemes are adapted from the classical power generation by the synchronous generator, where the modes of operation are Swing, PV and PQ mode. The proposed three modes of operation are adequate to operate fully in a small-scale power system such as in an islanded microgrid. A case study of operating the proposed controls in a microgrid by simulation is used to demonstrate the feasibility of implementation of the controls.
Volume: 11
Issue: 3
Page: 1610-1616
Publish at: 2020-09-01

Frequent pattern growth algorithm for maximizing display items

10.12928/telkomnika.v19i2.16192
Asyahri Hadi; STMIK Triguna Dharma Nasyuha , Jalius; Universitas Negeri Padang Jama , Rijal; Universitas Negeri Padang Abdullah , Yohanni; STMIK Triguna Dharma Syahra , Zulfi; STMIK Royal Kisaran Azhar , Juniar; STMIK Triguna Dharma Hutagalung , Buyung Solihin; Universitas Dharmawangsa Hasugian
Products are goods that are available and provided in stores for sale. Products provided in stores must be arranged properly to order to attract the attention of consumers to buy. Products arranged in a store will depend on the type of store. The product arrangement at a retail store will be different from the product arrangement at a clothing store. Store display will reflect a picture that is in the store so consumers know the types of products sold by product arrangement. An attractive arrangement will stimulate the desire of consumers to buy. In data mining there are several types of methods by use including prediction, association, classification and estimation. In the prediction method there are several techniques including the frequent pattern growth (FP-growth) method. FP-growth algorithm is the development of the apriori algorithm. So, the shortcomings of the apriori algorithm are corrected by the FP-growth algorithm. FP-growth is one alternative algorithm that can be used to determine the set of data that most often appears (frequent itemset) in a data set. Results of research on the application of the FP-growth algorithm to maximizing the display of goods. It is hoped that this research can be used to adjust the product layout according to the level of frequency the product is sought by the customer so that the customer has no difficulty finding the product they want.
Volume: 19
Issue: 2
Page: 390-396
Publish at: 2020-08-29
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