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29,758 Article Results

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

Optical Sensor Based on Dye Sensitized Solar Cell (DSSC)

10.11591/ijeecs.v12.i2.pp685-690
Rahmadwati Rahmadwati , Sapriesty Nainy Sari , Eka Maulana , Akhmad Sabarudin
An optical sensor is designed to convert a number of light energy in to electrical energy. The sensor hasbeen successfully measured using light illuminance to achieve electric parameters as the sensor output. In this research the optical sensor design was characterized according to the voltage and current output with the stimulus from mercury lamp. The sensor is customized from Dye-Sensitized Solar Cell with photo-electrode and photo-catalysator of Titanium Dioxide and extracted tobacco chlorophyll dye. Spin coating method was conducted to fabricate the thick layer deposition using selected material. Based on the absorbance measurement, it shows that tobacco dye has the characteristics of visible light absorption in the wavelength of 300-000 nm. The result of this research revealed that from 2 variation of optical sensor design square with active area of (2 cm x 2 cm) and (1 cm x 1 cm). Analitycal result shows that the sensor has wide linear characteristic in certain light illuminance both of output current and voltage.
Volume: 12
Issue: 2
Page: 685-690
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

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

On the Use of Edge Features and Exponential Decaying Number of Nodes in the Hidden Layers for Handwritten Signature Recognition

10.11591/ijeecs.v12.i2.pp722-728
Teddy Surya Gunawan , Mira Kartiwi
Handwritten signatures are playing an important role in finance, banking and education and more because it is considered the “seal of approval” and remains the most preferred means of authentication. In this paper, an offline handwritten signature authentication algorithm is proposed using the edge features and deep feedforward neural network (DFNN). The number of hidden layers in DFNN is configured to be at least one layer and more. In this paper, an exponential decaying number of nodes in the hidden layers was proposed to achieve better recognition rate with reasonable training time. Of the six edge algorithms evaluated, Roberts operator and Canny edge detectors were found to produce better recognition rate. Results showed that the proposed exponential decaying number of nodes in the hidden layers outperform other structure. However, more training data was required so that the proposed DFNN structure could have more efficient learning.
Volume: 12
Issue: 2
Page: 722-728
Publish at: 2018-11-01

Concealment of Files Blocked by Gmail with EOF-Based Image Steganography

10.11591/ijeecs.v12.i2.pp716-721
Ichsan Taufik , Undang Syaripudin , Faiz M. Kaffah , Jaka Giri Sobirin , Nanang Ismail , Teddy Surya Gunawan
Nowadays, due to security concern, not all the process of sending files via email runs smoothly. There are several types of file extensions that are blocked when sent via email. For examples, there are several file extensions blocked by Gmail. This paper discusses steganographic implementation using End of File (EOF) algorithm to insert special file into image cover file with JPG and PNG format so that files with these extensions can be sent via email. Before a special extension file is inserted into the cover file, a compression process should be conducted first to make the file size smaller. The proposed algorithm is implemented on Visual Basic.Net software. Based on the tests performed, the application can insert Gmail-blocked file system to the image cover file, without changing the physical bit of the image cover file or file system that inserted with 100% success rate. The stego-image file is also successfully sent via email without being blocked.
Volume: 12
Issue: 2
Page: 716-721
Publish at: 2018-11-01

Temperature Based Control of Ventilation System for Optimum Climate in Tomato Greenhouse

10.11591/ijeecs.v12.i2.pp655-661
NY Dahlan , Aminuddin Idham Halid , T. Juhana Hashim , SZ Sakimin
Tomato has been grown successfully in highlands of Malaysia. However, the production does not meet the demand in the large market due to problem related to climate change and lack of smart control mechanism for the tomato crop to grow healthily in the micro climate. Tomato requires optimum temperature to ensure a good quality fruit production especially under greenhouse system environment. This paper presents an optimum control mechanism for ventilation system in a greenhouse to minimize the energy consumption and meet the temperature requirement for lowland tomato. The control mechanism is tested on a tomato greenhouse system located in Universiti Putra Malaysia (UPM), Serdang. The ventilation system in the greenhouse comprises of six exhaust fans and two axial fans. Results show that the proposed control mechanism on the ventilation system is able to maintain the desired temperature for lowland tomato at lower energy consumption. With the automatic control of the ventilation system, an average of 65.8% of energy consumption was saved from the greenhouse as compared to baseline energy without the control system.
Volume: 12
Issue: 2
Page: 655-661
Publish at: 2018-11-01
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