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31,291 Article Results

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

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

Link Adaptation Algorithm for IEEE 802.11 Wireless Local Area Netwoks in Fading Channel

10.11591/ijeecs.v12.i2.pp677-684
Wan Norsyafizan W Muhamad , Suzi Seroja Sarnin , Azlina Idris , Aliya Syahira
This paper proposes an enhance version of the dual parameter based cost function algorithm for time-varying environments. For ideal channel condition, the proposed cost function algorithm adaptively change the transmission data rate according to traffic load condition. However, similar approach is not well-suited for time-varying environment. For time-varying condition, transmission of packet at lower transmission data rate is much preferred in order to achieve reliable transmission. In addition to that, packet transmission at lower data rate contributes to low energy consumption due to lower transmit power used to transmit packet. This paper presents a combination of cost function algorithm with adaptive rate/power. Adaptation of transmission data rate and transmit power for time varying condition are carried out based on received power values. An OPNET based simulation model was developed to analyses the performance of the propose algorithm. Simulation results show the proposed algorithm can significantly improve the energy efficiency of a WLAN while maintaining the network QoS in fading channel environments.
Volume: 12
Issue: 2
Page: 677-684
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

Insulation Properties of PMMA:TiO2 Nanodielectric Film for High Voltage Applications

10.11591/ijeecs.v12.i2.pp527-534
Melvin Welan Mathew , Lyly Nyl Ismail , Norsabrina Sihab , Ahmad Asri Abd Samad , Nur Ashida Salim
This research investigates the insulation properties of poly methyl methacrylate with titanium dioxide (PMMA:TiO2) nanodielectric film to be used as insulation layer in high voltage (HV) applications. AC and DC breakdown test has been conducted to investigate the insulation properties of PMMA:TiO2 nanodielectric to be used as solid insulation in HV. In this research, the PMMA:TiO2 nanodielectric film were prepared by varying the annealing temperature (60°C up to 180°C) and spin coating techniques wwere used to form the PMMA:TiO2 nanocomposite film. The insulation properties of the nanocomposite film were characterized using high voltage test (DC and AC breakdown strength) to identify which nanocompoiste film has the good insulation properties. In addition, different types of electrodes are also used to to measure the insulation properties of nanocompoiste film. The structural properties of PMMA:TiO2 nanocomposite films were characterized using atomic force microscopy (AFM). Results from HV test shows that the annealing temperature affected the insulation properties PMMA:TiO2 nanocomposite film. By increasing the annealing temperature, the insulation properties decreased. Film anneal at 120 oC has the good insulation compare to other temperature. 120 oC are the optimize temperature to prepared the PMMA:TiO2 nanocomposite films. Result from different types of electrodes show that sharp tip has high DC breakdown strength compare to spherical electrodes.
Volume: 12
Issue: 2
Page: 527-534
Publish at: 2018-11-01

Analytical Review on Graphical Formats Used in Image Steganographic Compression

10.11591/ijeecs.v12.i2.pp441-446
Roshidi Din , Osman Ghazali , Alaa Jabbar Qasim
This paper reviews the method of classification of the types of images used in data concealment based on the perspective of the researcher’s efforts in the past decade. Therefore, all papers were analyzed and classified according to time periods. The main objective of the study is to infer the best types of images that researchers have discussed and used, several reasons will be shown in this study, which started from 2006 to 2017, through this paper the pros and the cons in the use of favourite types in the concealment of data through previous studies.
Volume: 12
Issue: 2
Page: 441-446
Publish at: 2018-11-01

Neural Network Prediction for Efficient Waste Management in Malaysia

10.11591/ijeecs.v12.i2.pp738-747
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 population growth factor. This study uses Malaysian population as sample size and the data for weight is acquired via authorized Malaysia statistics’ websites. 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 ten and five nodes were used respectively. The result portrayed that there will be an increase of 29.03 percent of SWG in year 2031 compared to 2012. The limitation to this study is that the data was not based on real time as it was restricted by the government.
Volume: 12
Issue: 2
Page: 738-747
Publish at: 2018-11-01
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