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Publisher: Universitas Ahmad Dahlan   (Total: 16 journals)   [Sort by number of followers]

Showing 1 - 16 of 16 Journals sorted alphabetically
Ahmad Dahlan J. of English Studies     Open Access   (Followers: 2)
Bahastra     Open Access  
Berkala Fisika Indonesia     Open Access  
Bulletin of Electrical Engineering and Informatics     Open Access   (Followers: 8)
HUMANITAS (Jurnal Psikologi Indonesia)     Open Access   (Followers: 4)
Intl. J. of Advances in Intelligent Informatics     Open Access   (Followers: 6)
J. of Education and Learning     Open Access   (Followers: 11)
Jurnal Hukum Novelty     Open Access  
Jurnal Ilmiah AdMathEdu     Open Access  
Jurnal Informatika     Open Access   (Followers: 1)
Kes Mas : Jurnal Fakultas Kesehatan Masyarakat     Open Access   (Followers: 2)
Media Farmasi     Open Access  
Pharmaciana     Open Access  
Psikopedagogia : Jurnal Bimbingan dan Konseling     Open Access   (Followers: 2)
Spektrum Industri : Jurnal Ilmiah Pengetahuan dan Penerapan Teknik Industri     Open Access  
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 8, SJR: 0.211, h-index: 8)
Journal Cover Bulletin of Electrical Engineering and Informatics
  [8 followers]  Follow
    
  This is an Open Access Journal Open Access journal
   ISSN (Print) 2089-3191 - ISSN (Online) 2302-9285
   Published by Universitas Ahmad Dahlan Homepage  [16 journals]
  • Maximum Loadability Enhancement with a Hybrid Optimization Method

    • Authors: E. E. Hassan, T. K. A. Rahman, Z. Zakaria, N. Bahaman, M. H. Jifri
      Abstract: Nowadays, a power system is operating in a stressed condition due to the increase in demand in addition to constraint in building new power plants. The economics and environmental constraints to build new power plants and transmission lines have led the system to operate very close to its stability limits. Hence, more researches are required to study the important requirements to maintain stable voltage condition and hence develop new techniques in order to address the voltage stability problem. As an action, most Reactive Power Planning (RPP) objective is to minimize the cost of new reactive resources while satisfying the voltage stability constraints and labeled as Secured Reactive Power Planning (SCRPP).  The new alternative optimization technique called Adaptive Tumbling Bacterial Foraging (ATBFO) was introduced to solve the RPP problems in the IEEE 57 bus system. The comparison common optimization Meta-Heuristic Evolutionary Programming and original Bacterial Foraging techniques were chosen to verify the performance using the proposed ATBFO method. As a result, the ATBFO method is confirmed as the best suitable solution in solving the identified RPP objective functions.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • Hybrid StandAlone Photovoltaic Systems Sizing Optimization Based On Load
           Profile

    • Authors: Zulkifli Othman, Shahril Irwan Sulaiman, Ismail Musirin, Ahmad Maliki Omar, Sulaiman Shaari
      Abstract: This paper presents a sizing optimization technique for Hybrid Stand-Alone Photovoltaic (HSAPV). In this research, three optimization techniques have been developed, namely Dolphin Echolocation Algorithm (DEA), Fast Evolutionary Programming (FEP), and Classical Evolutionary Programming (CEP). These techniques have been incorporated into the sizing process to maximize the technical performance of the SAPV system. The components of PV modules, charge controllers, inverters, and batteries are used to determine the optimum value. These components are used as the control parameters to maximize the expected performance ratio (PR) of the SAPV system. The Iterative Sizing Algorithm (ISA) is the benchmarking technique to conduct the optimization technique achieving maximum PR value and minimal computation time. Results obtained from the research show that DE overcomes FEP and CEP. In addition, the optimization techniques also demonstrated comparatively fast with respect to ISA as the benchmark technique."
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • 0.18µm-CMOS Rectifier with Boost-converter and Duty-cycle-control for
           Energy Harvesting

    • Authors: Roskhatijah Radzuan, Mohd Khairul Mohd Salleh, Nuha A. Rhaffor, Shukri Korakkottil Kunhi Mohd
      Abstract: Existing works on battery-less of energy harvesting systems often assume as a high efficiency of rectifier circuit for power management system. In practice, rectifier circuit often varies with output power and circuit complexity. In this paper, based on a review of existing rectifier circuits for the energy harvesters in the literature, an integrated rectifier with boost converter for output power enhancement and complexity reduction of power management system is implemented through 0.18-micron CMOS process. Based on this topology and technology, low threshold-voltage of MOSFETs is used instead of diodes in order to reduce the power losses of the integrated rectifier circuit. Besides, a single switch with the duty-cycle control is introduced to reduce the complexities of the integrated boost converter. Measurement results show that the realistic performances of the rectifier circuit could be considerably improved based on the performances showed by the existing study.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • Load Management for Voltage Control Study Using Parallel
           Immunized-computational Intelligence Technique

    • Authors: Amirul Izzat Abu Bakar, Mohamad Khairuzzaman Mohamad Zamani, Ismail Musirin, Nor Azura Md Ghani
      Abstract: The increase of power demand is a crucial issue in the power system community in many parts of the world. Malaysia has also witnessed the familiar scenario due to the current development throughout the country has invited the urgency of increase in the power supply. Since Malaysia practices vertical system; where the electricity is supplied by only one utility, load management is an important issue so that the delivery of electricity is implemented without discrimination. Parallel Computational Intelligence will be developed which can alleviate and avoid all the unsolved issues, highlighting the weakness of current schemes. Parallel Computational Intelligence is developed to manage the optimal load in making sure the system maintains the stability condition, within the voltage limits. This paper presents evolutionary programming (EP) technique for optimizing the voltage profile. In this study, 3 algorithms which are Gaussian, Cauchy and Parallel EP were developed to solve optimal load management problem on IEEE 26-bus Reliability Test System (RTS). Results obtained from the study revealed that the application of Parallel EP has significantly reduced the time for the optimization process to complete.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • A Review of Low Power Wide Area Technology in Licensed and Unlicensed
           Spectrum for IoT Use Cases

    • Authors: Noor Laili Ismail, Murizah Kassim, Mahamod Ismail, Roslina Mohamad
      Abstract: There are many platforms in licensed and license free spectrum that support LPWA (low power wide area) technology in the current markets. However, lack of standardization of the different platforms can be a challenge for an interoperable IoT environment. Therefore understanding the features of each technology platform is essential to be able to differentiate how the technology can be matched to a specific IoT application profile. This paper provides an analysis of LPWA underlying technology in licensed and unlicensed spectrum by means of literature review and comparative assessment of Sigfox, LoRa, NB-IoT and LTE-M. We review their technical aspect and discussed the pros and cons in terms of their technical and other deployment features. General IoT application requirements is also presented and linked to the deployment factors to give an insight of how different applications profiles is associated to the right technology platform, thus provide a simple guideline on how to match a specific application profile with the best fit connectivity features.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • Comparison of Solar Radiation Intensity Forecasting Using ANFIS and
           Multiple Linear Regression Methods

    • Authors: Hadi Suyono, Rini Nur Hasanah, R. A. Setyawan, Panca Mudjirahardjo, Anthony Wijoyo, Ismail Musirin
      Abstract: Solar radiation forecasting is important in solar energy power plants (SEPPs) development. The electrical energy generated from the sunlight depends on the weather and climate conditions in the area where the SEPPs are installed. The condition of solar irradiation will indirectly affect the electrical grid system into which the SEPPs are injected, i.e. the amount and direction of the power flow, voltage, frequency, and also the dynamic state of the system. Therefore, the prediction of solar radiation condition is very crucial to identify its impact into the system. There are many methods in determining the prediction of solar radiation, either by mathematical approach or by heuristic approach such as artificial intelligent method. This paper analyzes the comparison of two methods, Adaptive Neuro Fuzzy Inference (ANFIS) method, which belongs into the heuristic methods, and Multiple Linear Regression (MLP) method, which uses a mathematical approach. The performance of both methods is measured using the root mean square error (RMSE) and the mean absolute error (MAE) values. The data of the Swiss Basel city from Meteoblue are used to test the performance of the two methods being compared. The data are divided into four cases, being classified as the training data and the data used as predictions. The solar radiation prediction using the ANFIS method indicates the results which are closer to the real measurement results, being compared to the the use MLP method. The average values of RMSE and MAE achieved are 123.27 W/m2 and 90.91 W/m2 using the ANFIS method, being compared to 138.70 W/m2 and 101.56 W/m2 respectively using the MLP method. The ANFIS method gives better prediction performance of 12.51% for RMSE and 11.71% for MAE with respect to the use of the MLP method.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • FPGA based design of microprocessor and its implementtion using vivado

    • Authors: Archana Rani, dr. naresh grover
      Abstract: This paper deals with the novel design and implementation of asynchronous microprocessor by using HDL on Vivado tool wherein it has the capability of handling even I-Type, R-Type and Jump instructions with multiplier instruction packet. Moreover, it uses separate memory for instructions and data read-write that can be changed at any time. The complete design has been synthesized and simulated using Vivado. The complete design is targeted on Xilinx Virtex-7 FPGA.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • A New Copy Move Forgery Detection Technique using Adaptive
           over-Segementation and Feature Point Matching

    • Authors: Anil Gupta
      Abstract: With the development of Image processing editing tools and software, an image can be easily manipulated . The image manipulation detection is vital  for the reason that an image can be used  as legal evidence, in the field of forensics investigations, and also in numerous various other fields. The image forgery detection based on pixels aims to validate the digital image authenticity with no aforementioned information of the main image. There are several means intended for tampering a digital image, for example, copy-move or splicing, resampling a digital image (stretch, rotate, resize), removal as well as the addition of an object from your image. Copy move image forgery detection is utilized to figure out the replicated regions as well as the pasted parts, however forgery detection may possibly vary dependant on whether or not there is virtually any post-processing on the replicated part before inserting the item completely to another party. Typically, forgers  utilize many operations like rotation, filtering, JPEG compression, resizing as well as the addition of noise to the main image before pasting, that make this thing challenging to recognize the copy move image forgery. Hence, forgery detector needs to be robust to any or all manipulations and also the latest editing software tools.. This research paper illustrates recent issues in the techniques of forgery detection    and proposes a advanced  copy–move forgery detection scheme using adaptive over-segmentation and feature point matching. The proposed scheme integrates both block-based and key point-based forgery detection methods
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • Detection of Prostate Cancer Using Radial/Axial Scanning of 2D
           Trans-rectal Ultrasound Images

    • Authors: Chijindu V. C., Udeze C. C., Ahaneku M. A., Anoliefo E.C.
      Abstract: The search for improvement in the result of segmentation of regions of interest in medical images has continued to be a source of challenge to researchers. Several research efforts have gone in to delineate regions of interest in the prostate gland from Trans-rectal ultrasound (TRUS) 2D-images. In this work, we develop a fast algorithm based on radial/axial scanning of the pixels of the prostate gland image with the goal of detecting hyper-echoic pixels that are bound within the boundaries of the gland TRUS 2D-images. The algorithm implements expert knowledge and utilizes the features extracted from the intensity of the TRUS images, primarily the relative intensity and gradient to delineate region of interest. It employs radial/axial scanning of the image from common seed point automatically selected to detect the region of the gland and subsequently hyper-echoic pixels which indicate suspected cancerous tissue cites. Evaluation of the algorithm performance was done by comparing detection result with that of expert radiologists. The detection algorithm gave an average accuracy of 88.55% and sensitivity of 71.65%.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • Signal-to-noise Ratio Study on Pipelined Fast Fourier Transform Processor

    • Authors: S. L. M. Hassan, N. Sulaiman, S. S. Shariffudin, T. N. T. Yaakub
      Abstract: Fast Fourier transform (FFT) processor is a prevailing tool in converting signal in time domain to frequency domain.  This paper provides signal-to-noise ratio (SNR) study on 16-point pipelined FFT processor implemented on field-programable gate array (FPGA). This processor can be used in vast digital signal applications such as wireless sensor network, digital video broadcasting and many more. These applications require accuracy in their data communication part, that is why SNR is an important analysis. SNR is a measure of signal strength relative to noise. The measurement is usually in decibles (dB). Previously, SNR studies have been carried out in software simulation, for example in Matlab. However, in this paper, pipelined FFT and SNR modules are developed in hardware form. SNR module is designed in Modelsim using Verilog code before implemented on FPGA board. The SNR module is connected directly to the output of the pipelined FFT module. Three different pipelined FFT with different architectures were studied. The result shows that SNR for radix-8 and R4SDC FFT architecture design are above 40dB, which represent a very excellent signal. SNR module on the FPGA and the SNR results of different pipelined FFT architecture can be consider as the novelty of this paper.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • Harmonic Contribution Analysis of Electric Arc Furnace by Using
           Spectrogram

    • Authors: M. H. Jopri, A. R. Abdullah, M. Manap, T. Sutikno, MR. Ab Ghani
      Abstract: In this paper, spectrogram, a fast and accurate technique is introduced for the analysis of the contribution. Based on a rule-based classifier and the threshold settings that referred to the IEEE Standard 1159 2009, the analysis of the harmonic and interharmonic contribution of EAF are carried out successfully. Moreover, the impact of contribution is measured using total harmonic distortion (THD) and total non-harmonic distortion (TnHD). In addition, spectrogram also gives 100 percent correct detection and able to analyze the contribution impact. It is proven that the proposed method is accurate, fast and cost efficient for analyzing the impact of harmonic and interharmonic of EAF.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • An Identification of Multiple Harmonic Sources in a Distribution System by
           Using Spectrogram

    • Authors: M. H. Jopri, A. R. Abdullah, M. Manap, T. Sutikno, MR Ab Ghani
      Abstract: The identification of multiple harmonic sources (MHS) is vital to identify the root causes and the mitigation technique for a harmonic disturbance. This paper introduces an identification technique of MHS in a power distribution system by using a time-frequency distribution (TFD) analysis known as a spectrogram. The spectrogram has advantages in term of its accuracy, a less complex algorithm, and use of low memory size compared to previous methods such as probabilistic and harmonic power flow direction. The identification of MHS is based on the significant relationship of spectral impedances, which are the fundamental impedance (Z1) and harmonic impedance (Zh) that estimate the time-frequency representation (TFR). To verify the performance of the proposed method, an IEEE test feeder with several different harmonic producing loads is simulated. It is shown that the suggested method is excellent with 100% correct identification of MHS. The method is accurate, fast and cost-efficient in the identification of MHS in power distribution arrangement.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • PAPR Reduction Using Huffman and Arithmetic Coding Techniques in F-OFDM
           System

    • Authors: Azlina Idris, Nur Atiqah Md Deros, Idris Taib, Murizah Kassim, Mohd Danial Rozaini, Darmawaty Mohd Ali
      Abstract: Filtered orthogonal frequency division multiplexing (F-OFDM) was introduced to overcome the high side lobes in the OFDM system. Filtering is implemented in the system to reduce the out-of-band emission (OOBE) for the spectrum utilization and to meet the diversified expectation of the upcoming 5G networks. The main drawback in the system is the high peak to average ratio (PAPR). This paper investigates the method used in reducing the PAPR in the F-OFDM system. The proposed method using the block coding technique to overcome the problem of high PAPR are the Arithmetic coding and Huffman coding. This research evaluates the performance of F-OFDM system based on the PAPR values. From the simulation results, the PAPR reduction of the Arithmetic coding is 8.9% lower, while the Huffman Coding is 6.7% lower in the F-OFDM system. The results prove that the Arithmetic Coding will out-perform the Huffman coding in the F-OFDM system.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • WiFi-Friendly Building to Enable WiFi Signal Indoor

    • Authors: Suherman S
      Abstract: The 802.11 networks (wireless fidelity (WiFi) networks) have been the main wireless internet access infrastructure within houses and buildings. Besides access point placement, building architectures contribute to the WiFi signal spreading. Even dough WiFi installation in buildings becomes prevalent; the building architectures still do not take WiFi-friendliness into considerations. In fact, the more friendly the building to WiFi signal, the more efficient the 802.11 based wireless infrastructure. This paper introduces the term of WiFi-friedly building by considering signal propagations, the obstacle impact, as well as proposing ornament-attaced reflector and hole-in-the-wall structure to improve WiFi signal distribution. Experiment results show that obstacle materials made of concrete reducing WiFi signal the most, following by metal and wood. Reflecting materials are able to improve the received signal level, for instance, theimplemented ornament-attached reflector is able to improve the received signal up 6.56 dBm. Further, the hole-in-the-wall structure is successfully increasing WiFi signal up to 2.3 dBm.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • Results of Fitted Neural Network Models on Malaysian Aggregate Dataset

    • Authors: Nor Azura Md Ghani, Saadi Bin Ahmad Kamaruddin, Ismail Musirin, Hishamuddin Hashim
      Abstract: This result-based paper presents the best results of both fitted BPNN-NAR and BPNN-NARMA on MCCI Aggregate dataset with respect to different error measures.  This section discusses on the results in terms of the performance of the fitted forecasting models by each set of input lags and error lags used, the performance of the fitted forecasting models by the different hidden nodes used, the performance of the fitted forecasting models when combining both inputs and hidden nodes, the consistency of error measures used for the fitted forecasting models, as well as the overall best fitted forecasting models for Malaysian aggregate cost indices dataset.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • Performance Comparison of Artificial Intelligence Techniques for
           Non-intrusive Electrical Load Monitoring

    • Authors: Khairuddin Khalid, Azah Mohamed, Ramizi Mohamed, Hussain Shareef
      Abstract: The increased awareness in reducing energy consumption and encouraging response from the use of smart meters have triggered the idea of non-intrusive load monitoring (NILM). The purpose of NILM is to obtain useful information about the usage of  electrical appliances usually measured at the  main entrance of electricity to obtain aggregate power signal by using a smart meter.  The load operating states  based on the on/off loads can be detected by analysing the aggregate power signals.  This paper presents a comparative study for evaluating the performance of artificial intelligence techniques in classifying the type and operating states of three load types that are usually available in commercial buildings, such as fluorescent light, air-conditioner and personal computer. In this NILM study, experiments were carried out to collect information of the load usage pattern by using a commercial smart meter.  From the power parameters captured by the smart meter, effective signal analysis  has been done using the time time (TT)-transform to achieve accurate load disaggregation. Load feature selection is also considered by using three power parameters which are real power, reactive power and the TT-transform parameters.  These three parameters are used as inputs for training the artificial intelligence techniques in classifying the type and operating states of the loads. The load classification results showed that the proposed extreme learning machine (ELM) technique  has successfully achieved high accuracy and fast learning compared with artificial neural network and support vector machine. Based on validation results, ELM achieved the highest load classification with 100% accuracy for data sampled at 1 minute time interval.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
  • Development of Intelligent Multi-agent systems for Collaborative
           e-learning support

    • Authors: Matazi Issam, Messoussi Rochdi, Bellmallem Salah-Eddine, Oumaira Ilham, Bennane Abdellah, Touahni Raja
      Abstract: The aim of this paper is the introduction of intelligence in e-learning collaborative system. In such system, the tutor plays an important role to facilitate collaboration between users and boost less active among them to get more involved for good pedagogical action. However, the problem lies in the large number of platform users, and the tutor tasks become difficult if not impossible. Therefore, we used fuzzy logic technics in order to solve this problem by automating tutor tasks and creating an artificial agent. This agent is elaborate in basing on the learners activities, especially the assessment of their collaborative behaviors. After the implementation of intelligent collaborative system by using Moodle platform, we have tested it. The reader will discover our approach and relevant results.
      PubDate: 2018-06-01
      Issue No: Vol. 7 (2018)
       
 
 
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