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Optimal Voltage Stability Improvement under Contingencies using Flower Pollination Algorithm and Thyristor Controlled Series Capacitor

10.11591/ijeecs.v12.i2.pp497-504
Zulkiffli Abdul Hamid , Ismail Musirin , Muhammad Amirul Adli Nan , Zulkifli Othman
Recent power systems necessitate for maintaining a safe voltage stability as the number of problems such as contingencies and reactive power insufficiency are increasing. In this paper, installation and sizing of Flexible Alternating Current Transmission System (FACTS) devices have been introduced for solving the voltage stability problems under contingencies. The FACTS device to be used is Thyristor Controlled Series Capacitor (TCSC). Besides improving the voltage magnitude at all buses to a desired level, installation of TCSC at proper locations can minimize total transmission losses of the system. To conduct the sizing task, the newly developed Flower Pollination Algorithm (FPA) has been implemented as the engine for optimization. Through experimentation, the results proved that the proposed placement and sizing technique has successfully mitigated the voltage stability problems. In addition, the computation time for FPA’s convergence was tolerable with optimum results.
Volume: 12
Issue: 2
Page: 497-504
Publish at: 2018-11-01

A Modular and Extensible Framework for Human Resource System

10.11591/ijeecs.v12.i2.pp641-647
Muhammad Zabir Abdul Halim , Marshima Mohd Rosli
Human Resource is an essential part for an organization and integration of technology would just enhance the effectiveness. One of the scope that Human Resource must take note is performance and productivity. However, there is still no infallible or highly reliable way to measure productivity and performance of an organization and its employees for current industrial Human Resource systems. There is still possible improvement that can be made to the system in the current time. The purpose of this study is to propose a modular and extensible framework of Human Resource systems that used to measure the performance and productivity of an organization. This study compares the different criteria of existing Human Resource systems to ensure the proposed framework would surpassed the current real world industrial system. The results of the review provide insights for important criteria in HR system to increase the accuracy of the performance review. This study also constructs Entity Relationship Diagram (ERD) to demonstrate the logical structure of the proposed framework. The ERD will form the foundation of the proposed framework to improve the Human Resource system for evaluating the productivity and performance of an organization.
Volume: 12
Issue: 2
Page: 641-647
Publish at: 2018-11-01

Prediction of Solar Radiation Intensity using Extreme Learning Machine

10.11591/ijeecs.v12.i2.pp691-698
Hadi Suyono , Hari Santoso , Rini Nur Hasanah , Unggul Wibawa , Ismail Musirin
The generated energy capacity at a solar power plant depends on the availability of solar radiation. In some regions, solar radiation is not always available throughout the day, or even week, depending on the weather and climate in the area. To be able to produce energy optimally throughout the year, the availability of solar radiation needs to be predicted based on the weather and climate behavior data. Many methods have been so far used to predict the availability of solar radiation, either by mathematical approach, statistical probability, or even artificial intelligence-based methods. This paper describes a method of predicting the availability of solar radiation using the Extreme Learning Machine (ELM) method. It is based on the artificial intelligence methods and known to have a good prediction accuracy. To measure the performance of the ELM method, a conventional forecasting method using the Multiple Linear Regression (MLR) method has been used as a comparison. The implementation of both the ELM and MLR methods has been tested using the solar radiation data of the Basel City, Switzerland, which are available to public. Five years of data have been divided into training data and testing data for 6 case-studies considered. Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) have been used as the parameters to measure the prediction results based on the actual data analysis. The results show that the obtained average values of RMSE and MAE by using the ELM method respectively are 122.45 W/m2 and 84.04 W/m2, while using the MLR method they are 141.18 W/m2 and 104.87 W/m2 respectively. It means that the ELM method proved to perform better than the MLR method, giving 15.29% better value of RMSE parameter and 24.79% better value of MAE parameter.
Volume: 12
Issue: 2
Page: 691-698
Publish at: 2018-11-01

Components of Participatory Engagement within E-Learning Community

10.11591/ijeecs.v12.i2.pp556-561
Noor Hida Natrah Aziz , Haryani Haron , Afdallyna Fathiyah Harun
This paper explores the components of participatory engagement to improve learner’s engagement within the e-learning community. Data are gathered through observations to measuring the interactions of the learner’s. The measurement included the learners’ feedbacks through the interactions of learners and educators, learners and learners and learners and content. Follow-up interviews are conducted to get deeper insights into the interactions and overall learner’s engagement environment. Findings show that in order to promote learners’ engagement in e-learning components such as accessibility, mobility, active learning and collaboration must be present in an e-learning ecosystem.
Volume: 12
Issue: 2
Page: 556-561
Publish at: 2018-11-01

Information Structure Framework for ISMS Planning and Certification: Malaysian Data

10.11591/ijeecs.v12.i2.pp634-640
Palaniappan Shamala , Muruga Chinniah , Cik Feresa Mohd Foozy , Chuah Chai Wen , Aida Mustapha , Rabiah Ahmad
Information security are becoming an important aspect of organizations. Organisations also are progressively conscious of its important in their business strategy. The awareness make organisations are currently applying for information security management system (ISMS) to effectively manage their information assets. Therefore, this research aims to provide an Information Structure Framework for ISMS planning and certification. Then Likert structured questionnaire was distributed and the findings have been analyzed using Rasch Measurement Model (RMM). The results from this study, managed to develop Information Structure Framework for ISMS. The proposed framework consists of information structure focuses on providing the information outline which is structured in a way, in which the components are put together to form a meaningful structure which can be navigated at any time. The framework contributes to the field of ISMS and certification area. The framework provides an awareness on knowing beforehand what to do and to what extent they are already conquering the information needed for getting clear direction and to develop ISMS.
Volume: 12
Issue: 2
Page: 634-640
Publish at: 2018-11-01

Application-based Smart Parking System using CAN Bus

10.11591/ijeecs.v12.i2.pp759-764
Rahul Muppanagouda Patil , N R Vinay , Pratiba D
We have witnessed a rapid growth in the Internet of Things and its contribution to the growth of Smart cities in recent years. Consistent efforts have been undertaken by the Government of India to elevate the growth of this industry. The increase in population and vehicular densities have led to congested roads, inadequate parking facilities and poor infrastructure has called for a technology-driven solution known com-monly as a Smart Parking System (SPS). The solution proposed in this paper is a client-based parking slot reservation system that is implemented using micro-controllers interfaced with sensors for parking vacancy detection. They are also connected to cloud services in order to produce a complete IoT solution, with each micro-controller acting as a node in a network. Additionally, the CAN protocol is deployed for communication between nodes of this network in case of failure of the nodes in the wireless network. This is a solution de-veloped that caters to users mainly residing in Smart Cities and addresses the issue of network node failure.
Volume: 12
Issue: 2
Page: 759-764
Publish at: 2018-11-01

Design of Smart Waste Bin and Prediction Algorithm for Waste Management in Household Area

10.11591/ijeecs.v12.i2.pp748-758
Siti Hajar Yusoff , Ummi Nur Kamilah Abdullah Din , Hasmah Mansor , Nur Shahida Midi , Syasya Azra Zaini
Maintaining current municipal solid waste management (MSWM) for the next ten years would not be efficient anymore as it has brought many environmental issues such as air pollution. This project has proposed Artificial Neural Network (ANN) based prediction algorithm that can forecast Solid Waste Generation (SWG) based on household size factor. Kulliyyah of Engineering (KOE) in International Islamic University Malaysia (IIUM) has been chosen as the sample size for household size factor. A smart waste bin has been developed that can measure the weight, detect the emptiness level of the waste bin, stores information and have direct communication between waste bin and collector crews. This study uses the information obtained from the smart waste bin for the waste weight while the sample size of KOE has been obtained through KOE’s department. All data will be normalized in the pre-processing stage before proceeding to the prediction using Visual Gene Developer. This project evaluated the performance using R2 value. Two hidden layers with five and ten nodes were used respectively. The result portrayed that the average rate of increment of waste weight is 2.05 percent from week one until week twenty. The limitation to this study is that the amount of smart waste bin should be replicated more so that all data for waste weight is directly collected from the smart waste bin.
Volume: 12
Issue: 2
Page: 748-758
Publish at: 2018-11-01

Ideal Huffman Code for Lossless Image Compression for Ubiquitous Access

10.11591/ijeecs.v12.i2.pp765-774
T Kavitha , K. Jayasankar
Compression technique is adopted to solve various big data problems such as storage and transmission. The growth of cloud computing and smart phone industries has led to generation of huge volume of digital data. Digital data can be in various forms as audio, video, images and documents. These digital data are generally compressed and stored in cloud storage environment. Efficient storing and retrieval mechanism of digital data by adopting good compression technique will result in reducing cost. The compression technique is composed of lossy and lossless compression technique. Here we consider Lossless image compression technique, minimizing the number of bits for encoding will aid in improving the coding efficiency and high compression. Fixed length coding cannot assure in minimizing bit length. In order to minimize the bits variable Length codes with prefix-free codes nature are preferred. However the existing compression model presented induce high computing overhead, to address this issue, this work presents an ideal and efficient modified Huffman technique that improves compression factor up to 33.44% for Bi-level images and 32.578% for Half-tone Images. The average computation time both encoding and decoding shows an improvement of 20.73% for Bi-level images and 28.71% for Half-tone images. The proposed work has achieved overall 2% increase in coding efficiency, reduced memory usage of 0.435% for Bi-level images and 0.19% for Half-tone Images. The overall result achieved shows that the proposed model can be adopted to support ubiquitous access to digital data.
Volume: 12
Issue: 2
Page: 765-774
Publish at: 2018-11-01

Scheduling Workflow Applications with Makespan and Reliability Constraints

10.11591/ijeecs.v12.i2.pp482-488
Maslina Abdul Aziz , Jemal H. Abawajy , Morshed Chowdhury
In the last few years, workflows are becoming richer and more complex. Workflow scheduling management system to be robust, flexible with multicriteria scheduling algorithms. It needs to satisfy the Quality of Service (QoS) parameters. However, QoS parameters and workflow system objectives are often contradictory. In our analysis, we derived an efficient strategy to minimize the overall processing time for scheduling workflows modelled by using Directed Acyclic Graph (DAG). We studied the problem of workflow scheduling that lead to optimizing makespan and reliability. The proposed algorithm handles unsuccessful job execution or resource failure by dynamically scheduling workflows to available resources. Based on the experiments results, our proposed Failure-Aware Workflow Scheduling (FAWS) Algorithm can significantly optimize the makespan and minimize the reliability by rescheduling the failed task to the unused resources. The effectiveness of the FAWS algorithm was validated based on a simulation-driven analysis based on the workflow application.
Volume: 12
Issue: 2
Page: 482-488
Publish at: 2018-11-01

Analysis of Wireless Power Transfer on the inductive coupling resonant

10.11591/ijeecs.v12.i2.pp592-599
Cik Ku Haroswati Che Ku Yahaya , Syed Farid Syed Adnan , Murizah Kassim , Ruhani Ab Rahman , Mohamad Fazrul bin Rusdi
Wireless power transfer through inductive coupling is proposed in this paper. Based on the concept of Tesla, the circuit was designed using two parallel inductors that are mutually coupled. The designed was split into two which are transmitter part and receiver part. The circuit was simulated using proteus simulation software. The results had shown that the changes in a number of turn of the inductor coils and distance of the two resonators affecting the efficiency of the power transfer. The wireless power transfer can be described as the transmission of electrical energy from the power source to the electrical load without any current-carrying wire connecting them. Wireless power transfer is deemed to be very useful in some circumstances where connecting wires are inconvenient. Wireless power transfer problems are different from wireless telecommunications such as radio. Commonly, wireless power transfers are conducted using an inductive coupling and followed by magnetic induction characteristics. In this project, we use magnetic induction using copper wire with a different diameter. By using these different diameters of wires, we are going to see the power transfer performance of each wire. It is possible to achieve wireless power transfer up to 30 centimeters between the transmitter and the receiver with a higher number of coil's turn. As concern as it may seem, the wireless power transfer field would be in high demand for electric power to be supplied in the future.
Volume: 12
Issue: 2
Page: 592-599
Publish at: 2018-11-01

Object Recognition Inspiring HVS

10.11591/ijeecs.v12.i2.pp783-793
Mohammadesmaeil Akbarpour , Nasser Mehrshad , Seyyed-Mohammad Razavi
Human recognize objects in complex natural images very fast within a fraction of a second. Many computational object recognition models inspired from this powerful ability of human. The Human Visual System (HVS) recognizes object in several processing layers which we know them as hierarchically model. Due to amazing complexity of HVS and the connections in visual pathway, computational modeling of HVS directly from its physiology is not possible. So it considered as a some blocks and each block modeled separately. One models inspiring of HVS is HMAX which its main problem is selecting patches in random way. As HMAX is a hierarchical model, HMAX can enhanced with enhancing each layer separately. In this paper instead of random patch extraction, Desirable Patches for HMAX (DPHMAX) will extracted.  HVS for extracting patch first selected patches with more information. For simulating this block patches with more variance will be selected. Then HVS will chose patches with more similarity in a class. For simulating this block one algorithm is used. For evaluating proposed method, Caltech 5 and Caltech101 datasets are used. Results show that the proposed method (DPMAX) provides a significant performance over HMAX and other models with the same framework.
Volume: 12
Issue: 2
Page: 783-793
Publish at: 2018-11-01

Brain Developmental Disorders’ Modelling based on Preschoolers Neuro-Physiological Profiling

10.11591/ijeecs.v12.i2.pp542-547
Abdul Wahab , Norhaslinda Kamaruddin
Frequently misunderstood by their teachers as being low performers, children with learning disabilities (LDs) such as dyslexia, ADHD, and Asperger’s Syndrome develop low self-confidence and poor self-esteem that may lead to the risk of developing psychological and emotional problems. On contrary, research has shown that a substantial number of these children are capable of learning, and hence, are high-functioning. Therefore, there is a need to provide for the early detection of LDs and instruction that focuses on their needs based on their profiles. Profiling is normally done through observations on the psychological manifestations of LDs by parents and teachers as third-party observers. The first party experience, which is reflected through brain manifestations, is often overlooked. Hence the aim of this paper is to present an alternative solution to profile young children with LDs using electroencephalogram (EEG) that capture brain signals to measure brain functionalities and correlate them with the different LDs. Studies on neurophysiological signals and their relationship to LDs are used to develop Computational Neuro-Physiological (CN-P) model to be an alternative in quantifying the children brain activation function related to learning experience. It is envisaged that such model can profile children with learning disabilities to provide effective intervention in timely manner which can help teachers to provide differentiated instruction for children with LDs. This is in line with the thrust of the Education National Key Result Area (NKRA), the Malaysia Education Blueprint 2013-2025, and the Special Education Regulations 2013.
Volume: 12
Issue: 2
Page: 542-547
Publish at: 2018-11-01

Evaluation of CNN, Alexnet and GoogleNet for Fruit Recognition

10.11591/ijeecs.v12.i2.pp468-475
Nur Azida Muhammad , Amelina Ab Nasir , Zaidah Ibrahim , Nurbaity Sabri
Fruit recognition is useful for automatic fruit harvesting. Fruit recognition application can reduce or minimize human intervention during fruit harvesting operation. However, in computer vision, fruit recognition is very challenging because of similar shapes, colors and textures among various fruits. Illuminations changes due to weather condition also leads to a challenging task for fruit recognition. Thus, this paper tends to investigate the performance of basic Convolutional Neural Network (CNN), Alexnet and Googlenet in recognizing nine different types of fruits from a publicly available dataset.  The experimental results indicate that all these techniques produce excellent recognition accuracy, but basic CNN achieves the fastest recognition result compared with Alexnet and Googlenet.
Volume: 12
Issue: 2
Page: 468-475
Publish at: 2018-11-01

Monitoring of PV Performance Using LabVIEW

10.11591/ijeecs.v12.i2.pp461-467
Siti Amely Jumaat , Ammar Syahmi Bin Mohd Anuar , Mohd Noor Abdullah , Nur Hanis Radzi , Rohaiza Hamdan , Suriana Salimin , Muhammad Nafis bin Ismail
This project aims to design a simulator for PV monitoring using LabVIEW. This project will be divided into two parts ; software where LabVIEW and Arduino IDE been contracted and hardware parts. First part involves the software development. In this project, LabVIEW program is used as the main program to monitor the output of solar panel; voltage, current, power and temperature in real time. Next, the Arduino IDE program is used to interact the sensors with the Arduino board. The Arduino Uno microcontroller board is used as data acquisition medium to collect data from the solar panel. Second, the hardware part which is PV panel setup and measurement circuit that consist of sensors and Arduino board so that the sensors data will transfer and display to the PC connected. In this simulator, the sensors are connected to the Analog I/O of Arduino Uno microcontroller which read the analogue input of sensors. The Arduino then is connected to the PC program LabVIEW to display the I-V graph and P-V graph. To make the data more significant, the data will be collected at the location 1.8635° N, 103.1089 ° E which is in Parit Raja, Batu Pahat, Johor. The data was collected with 3 different day and time; 12PM, 1PM and 2PM on 28/11/2017, 29/11/2017 and 30/11/2017.
Volume: 12
Issue: 2
Page: 461-467
Publish at: 2018-11-01

J-slot EBG structure for SAR Reduction of Dual Band J-slot Textile Antenna

10.11591/ijeecs.v12.i2.pp794-802
Ramesh Manikonda , Rajyalakshmi Valluri , Mallikarjuna Rao Prudhivi
In this article, the dual band is achieved with J-slot on rectangular Textile antenna on Jeans fabric as substrate. It resonates at the 2.4 GHz and 5.4 GHz of Wireless Body Area Network (WBAN) bands. The novel J-slot Electromagnetic Band Gap (EBG) array consists of 2x2 elements. It is used as superstrate of J-slot textile antenna for Specific Absorption Rate (SAR) reduction and gain enhancement. The Reflection coefficient and VSWR of dual band textile antenna are simulated and measured with and without human body.
Volume: 12
Issue: 2
Page: 794-802
Publish at: 2018-11-01
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