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28,296 Article Results

Software Reliability Using SPRT: Burr Type III Process Model

10.11591/ijece.v6i6.pp3060-3067
CH. Smitha , R. Satya Prasad , R. Kiran Kumar
Increased dependence on software systems elicited the assessment of their reliability, a crucial task in software development. Effective tools and mechanisms are required to facilitate the assessment of software reliability. Classical approaches like hypothesis testing are significantly time consuming as the conclusion can only be drawn after collecting huge amounts of data. Statistical method such as Sequential Analysis can be applied to arrive at a decision quickly. This paper implemented Sequential Probability Ratio Test (SPRT) for Burr Type III model based on time domain data. For this, parameters were estimated using Maximum Likelihood Estimation to apply SPRT on five real time software failure datasets borrowed from different software projects. The results exemplify that the adopted model has given a rejection decision for the used datasets.
Volume: 6
Issue: 6
Page: 3060-3067
Publish at: 2016-12-01

Performance Forecasting of Share Market using Machine Learning Techniques: A Review

10.11591/ijece.v6i6.pp3196-3204
Sachin Kamley , Shailesh Jaloree , R.S. Thakur
Forecasting share performance becomes more challenging issue due to the enormous amount of valuable trading data stored in the stock database. Currently, existing forecasting methods are insufficient to analyze the share performance accurately. There are two main reasons for that: First, the study of existing forecasting methods is still insufficient to identify the most suitable methods for share price prediction. Second, the lack of investigations made on the factors affecting the share performance. In this regard, this study presents a systematic review of the last fifteen years on various machine learning techniques in order to analyze share performance accurately. The only objective of this study is to provide an overview of the machine learning techniques that have been used to forecast share performance. This paper also highlights a how the prediction algorithms can be used to identify the most important variables in a share market dataset. Finally, we could have succeeded to analyze share performance effectively. It could bring benefits and impacts to researchers, society, brokers and financial analysts.
Volume: 6
Issue: 6
Page: 3196-3204
Publish at: 2016-12-01

Virtual Maintenance, Reality, and Systems: A Review

10.11591/ijece.v6i6.pp2698-2707
Kouroush Jenab , Saeid Moslehpour , Sam Khoury
Virtual Reality is a computer-generated, mock environment that can allow people to interact with it in a seemingly real way by using certain types of specialized equipment. It is mainly used for training or educational purposes and allows for “real-life” training in a safe and monitored environment. Virtual training can be used in many different fields such as medical, military, biomedical research, aviation, and many others. However, this paper reviews the most cited publications related to the application of virtual reality for training in the United States Military. As a result, researchers can find research venues based on the challenges, risk, and infrastructures.
Volume: 6
Issue: 6
Page: 2698-2707
Publish at: 2016-12-01

New Lossless Compression Method using Cyclic Reversible Low Contrast Mapping (CRLCM)

10.11591/ijece.v6i6.pp2836-2845
Hendra Mesra , Handayani Tjandrasa , Chastine Fatichah
In general, the compression method is developed to reduce the redundancy of data. This study uses a different approach to embed some bits of datum in image data into other datum using a Reversible Low Contrast Mapping (RLCM) transformation. Besides using the RLCM for embedding, this method also applies the properties of RLCM to compress the datum before it is embedded. In its algorithm, the proposed method engages Queue and Recursive Indexing. The algorithm encodes the data in a cyclic manner. In contrast to RLCM, the proposed method is a coding method as Huffman coding. This research uses publicly available image data to examine the proposed method. For all testing images, the proposed method has higher compression ratio than the Huffman coding.
Volume: 6
Issue: 6
Page: 2836-2845
Publish at: 2016-12-01

Energy Efficient Frame Structure for Gigabit Passive Optical Networks

10.11591/ijece.v6i6.pp2971-2978
Rizwan Aslam Butt , Sevia Mahdaliza Idrus , Raja Zahilah Radzi , Kashif Naseer Qureshi
Increasing power consumption in information and communication access networks is one of the major cause of greenhouse gas emissions. These emissions are harmful to life on earth. Passive Optical Networks (PONs) are energy efficient but the broadcast nature of downstream traffic may cause of huge unnecessary processing of frames by the optical network units and result in significant energy wastage. Bi-PON technique tried to solve this problem by changing the XGPON / GPON frame structure to an interleaved pattern but also required additional hardware changings at the optical network units.  In this study, we have tried to achieve the same objective by making a few changings in the GPON frame structure without modifying the existing hardware structure. The simulation results show that 25.25% processing energy of an ONU can be saved by incorporating these changes.
Volume: 6
Issue: 6
Page: 2971-2978
Publish at: 2016-12-01

Localization of Cooperative WSN using Distributed PSO with Optimum References

10.11591/ijece.v6i6.pp3094-3102
Ravichander Janapati , Ch. Balaswamy , K. Soundararajan
In indoor environment WSN nodes are deployed randomly and do not know the accurate position. Find the node position with the help of anchor nodes is known as localization. CRB algorithm selects the best anchor nodes which gives high accuracy. In this paper distributed PSO algorithm with optimum selection of reference nodes using CRB is proposed to find accurate node position. The proposed method performs better in comparison with other algorithms like PSO, RLS, LMS and GPS in terms of position accuracy, latency and complexity.
Volume: 6
Issue: 6
Page: 3094-3102
Publish at: 2016-12-01

Image Retrieval with Relevance Feedback using SVM Active Learning

10.11591/ijece.v6i6.pp3238-3246
Giang Truong Ngo , Tao Quoc Ngo , Dung Duc Nguyen
In content-based image retrieval, relevant feedback is studied extensively to narrow the gap between low-level image feature and high-level semantic concept. In general, relevance feedback aims to improve the retrieval performance by learning with user's judgements on the retrieval results. Despite widespread interest, but feedback related technologies are often faced with a few limitations. One of the most obvious limitations is often requiring the user to repeat a number of steps before obtaining the improved search results. This makes the process inefficient and tedious search for the online applications. In this paper, a effective feedback related scheme for content-based image retrieval is proposed. First, a decision boundary is learned via Support Vector Machine to filter the images in the database. Then, a ranking function for selecting the most informative samples will be calculated by defining a novel criterion that considers both the scores of Support Vector Machine function and similaritymetric between the "ideal query" and the images in the database. The experimental results on standard datasets have showed the effectiveness of the proposed method.
Volume: 6
Issue: 6
Page: 3238-3246
Publish at: 2016-12-01

Time Independent Signature Verification using Normalized Weighted Coefficients

10.11591/ijece.v6i6.pp2658-2664
Manas Singhal , Manish Trikha , Maitreyee Dutta
Signature verification is one of the most widely accepted verification methods in use. The application of handwritten signatures includes the banker’s checks, the credit and debit cards issued by banks and various legal documents. The time factor plays an important role in the framing of signature of an individual person. Signatures can be classified as: offline signature verification and online signature verification. In this paper a time independent signature verification using normalized weighted coefficients is presented. If the signature defining parameters are updated regularly according to the weighted coefficients, then the performance of the system can be increased to a significant level. Results show that by taking normalized weighted coefficients the performance parameters, FAR and FRR, can be improved significantly.
Volume: 6
Issue: 6
Page: 2658-2664
Publish at: 2016-12-01

The Contour Extraction of Cup in Fundus Images for Glaucoma Detection

10.11591/ijece.v6i6.pp2797-2804
Anindita Septiarini , Hamdani Hamdani , Dyna Marisa Khairina
Glaucoma is the second leading cause of blindness in the world; therefore the detection of glaucoma is required. The detection of glaucoma is used to distinguish whether a patient's eye is normal or glaucoma. An expert observed the structure of the retina using fundus image to detect glaucoma. In this research, we propose feature extraction method based on cup area contour using fundus images to detect glaucoma. Our proposed method has been evaluated on 44 fundus images consisting of 23 normal and 21 glaucoma. The data is divided into two parts: firstly, used to the learning phase and secondly, used to the testing phase. In order to identify the fundus images including the class of normal or glaucoma, we applied Support Vector Machines (SVM) method. The performance of our method achieves the accuracy of 94.44%.
Volume: 6
Issue: 6
Page: 2797-2804
Publish at: 2016-12-01

Adaptive Online Module Prototype for Learning Unified Modelling Language (UML)

10.11591/ijece.v6i6.pp2931-2938
Arief Hidayat , Victor Gayuh Utomo
Every student has their own learning style. Some students may prefer to read the learning material while some other students may prefer to discuss with their colleagues to help them understanding the information more effectively. One of the learning materials is Unified Modeling Language or UML. UML is an industry standard language to specify, visualize, construct, and document the artifacts of software systems. Today, many UML online learning sites are designed to give added information to students other than face-to-face interaction in the classroom. However, most of UML materials provided by the online learning resources are limited to text-based material which is suitable only for students with verbal learning styles. This research aims to identify and analyze the needs before developing a prototype of an adaptive online module. The research is also driven by the need to develop a prototype of adaptive online module that is based on the student's learning style categories in order to help students understand UML better. The result of this research is a prototype of adaptive online module which will identify students' learning styles and lead the students to learning environment that suits their learning style.
Volume: 6
Issue: 6
Page: 2931-2938
Publish at: 2016-12-01

Performance Evaluation of A Multi-Sensor System Using Fixed Point DSP For Water Leak Detection

10.11591/ijeecs.v4.i3.pp555-560
Loutfi Benyettou
DSPs (Digital Processors Signal) are processors specifically designed for digital signals processing. The fixed-point DSPs are processors operating in integer arithmetic whose characteristics are often limited but not less powerful with respect to floating-point DSPs. In this article, it is a question of checking the performances provided by the fixed-point DSP, the TMS320C541. This one is used in a detection and remote locating system ensuring a control of water leaks on the pipes. The acoustic correlation technique used as means of detection of these leaks represents the key element of the suggested system. In fact the DSP which deals the acquisition and processing of the signals emanating from the leaks. The had aim consists in initially to confirm the choice of such a processor for such an application. A simulation study to evaluate its performances as regards of computational accuracy and computing speed is carried out. A floating-point DSP of last generation, more accurate and faster, taken as reference element, is used for this purpose.
Volume: 4
Issue: 3
Page: 555-560
Publish at: 2016-12-01

Optimum Permanent Magnets Configuration in Flat-Quasi Linear Permanent Magnet Generators

10.11591/ijece.v6i6.pp2589-2602
Fransisco Danang Wijaya , Budi Azhari , Harnoko Stephanus
Flat-quasi type of linear permanent magnet generators (LPMGs) have been considered to be applied for several applications, such for wave energy conversion and free piston combustion engine. One of the important issues concerning LPMG is the permanent magnets configuration, due to its effects to the generator’s excitation performance. In this paper, a 1 kW flat-quasi LPMG would be designed and built. During the process, optimum permanent magnets configuration was required and researched. The optimum configuration considered the output power and resulted cogging force. Invetigation was then conducted by modifying several variables, including poles’ arrangement, pole length, number of pole, and pole skewing angle. The modification constraints were total permanent magnets’ volume and generator dimension. The results showed that permanent magnet configuration with halbach arrangement, pole length equals 55% of the slot pitch length, and 61.19o skewing angle produced the optimum output values.
Volume: 6
Issue: 6
Page: 2589-2602
Publish at: 2016-12-01

Improved Denoising Method for Ultrasonic Echo with Mother Wavelet Optimization and Best-Basis Selection

10.11591/ijece.v6i6.pp2742-2754
Mohammad Hossein Doost Mohammadi
Weak features of ultrasonicnondestructive test signals are usually immersed in noisy signals. So, in this paper, we proposed an improved scheme for noise reduction and feature extraction based on discrete wavelet transform. The basis of the mother wavelet was selected to be matched to a given signal. Three different constraints were presented to minimize the error between the denoised and the given signal. It should be mentioned that such an optimum wavelet can represent the signal more compactly with a few large coefficients which can be considered as the signal features. Standard signals and simulated ultrasonic echo were used to evaluate the performance of the presented algorithms. Signal to error ratio was used to compare the designed wavelet performance with that of standard wavelets. Simulation results revealed that the proposed method outperformed the other presented methods and even standard wavelets. The results also has shown that the signal-based noise reduction algorithms make the feature extraction more reliable. Finally, the performance of the proposed algorithm was compared with other methods from different literatures.
Volume: 6
Issue: 6
Page: 2742-2754
Publish at: 2016-12-01

Design and Implementation of Wheelchair Controller Based Electroencephalogram Signal using Microcontroller

10.11591/ijece.v6i6.pp2878-2886
M. I. Arzak , U. Sunarya , S. Hadiyoso
Wheelchair is a medical device that can help patients, especially for persons with physical disabilities. In this research has designed a wheelchair that can be controlled using brain wave. Mind wave device is used as a sensor to capture brain waves. Fuzzy method is used to process data from mind wave. In the design was used a modified wheelchair (original wheelchair modified with addition dc motor that can be control using microcontroller ). After processing data from mindwave using fuzzy method, then microcontroller ordered dc motor to rotate.The dc motor connected to gear of wheelchair using chain. So when the dc motor rotated the wheelchair rotated as well.  Controlling of DC motor used PID control method. Input encoder was used as feedback for PID control at each wheel.From the experimental results concentration level data of the human brain waves can be used to adjust the rate of speed of the wheelchair. The level accuracy of respons Fuzzy method ton system obtained by devide total true respons data with total tested data and the result is 85.71 %.  Wheelchairs can run at a maximum speed of 31.5 cm/s when the battery voltage is more than 24.05V. Moreover, the maximum load of wheelchair is 110 kg.
Volume: 6
Issue: 6
Page: 2878-2886
Publish at: 2016-12-01

Structural Equation Modeling to Analyze Person-Organization Fit and Organizational Effectiveness

10.11591/ijece.v6i6.pp3006-3017
Hadi Teimouri , Kouroush Jenab , Somaye Rafei , Maryam Yonespoor
Efficient management and leadership can be achieved via precise planning for selection, recruitment, and optimization of the labor force. One of the major goals in labor force selection and recruitment is the fit between people and an organization. This phenomenon is known as person-individual fit. In this research, the authors collected data via a survey aimed at exploring the relationship between person-individual fit and organizational effectiveness at the University of Isfahan. The research hypotheses were tested through variables such as environmental congruence, KSA (knowledge/skills/abilities) congruence, goals congruence, values congruence, and personality congruence, as dimensions of person-individual fit. The aim of this study is developing and practical and from the procedure implemented is introducing-analyzing. The sample studied in this study is the mangers and employers of the university in Isfahan. A stratified random sampling method was used based the Morgan table and a sample size of 120 was chosen from among 150 persons. The results revealed that there is a significant relationship between dimensions of person-individual fit and organizational effectiveness.
Volume: 6
Issue: 6
Page: 3006-3017
Publish at: 2016-12-01
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