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27,860 Article Results

A New Approach of Iris Detection and Recognition

10.11591/ijece.v7i5.pp2530-2536
Rubel Biswas , Jia Uddin , Md. Junayed Hasan
This paper proposes an IRIS recognition and detection model for measuring the e-security. This proposed model consists of the following blocks: segmentation and normalization, feature encoding and feature extraction, and classification. In first phase, histogram equalization and canny edge detection is used for object detection. And then, Hough Transformation is utilized for detecting the center of the pupil of an IRIS. In second phase, Daugmen’s Rubber Sheet model and Log Gabor filter is used for normalization and encoding and as a feature extraction method GNS (Global Neighborhood Structure) map is used, finally extracted feature of GNS is feed to the SVM (Support Vector Machine) for training and testing. For our tested dataset, experimental results demonstrate 92% accuracy in real portion and 86% accuracy in imaginary portion for both eyes. In addition, our proposed model outperforms than other two conventional methods exhibiting higher accuracy.
Volume: 7
Issue: 5
Page: 2530-2536
Publish at: 2017-10-01

Behavioral Tracking in E-Learning by Using Learning Styles Approach

10.11591/ijeecs.v8.i1.pp17-26
Amira Fatiha Baharudin , Noor Azida Sahabudin , Adzhar Kamaludin
Currently, e-learning is becoming an option as it can save the cost of education, time, and more flexible in its implementation. The main problem that arises is how to create e-learning content that is interesting and really fit the needs of the users. One way that can be done to optimize the content of e-learning is to analyze the user behavior. This study aims to analyze user (student) behavior in KALAM UMP, based on logs report (activity history), which is often called as behavioral tracking. First, the learning style of the students is determined based on Honey and Mumford Learning Styles Model by using Learning Styles Questionnaire. The analysis is done using SPSS 16.0 for Windows. The results shows that student with Reflector and Theorist learning styles access e-learning materials the most. From Spearman Correlation analysis, the relationship between learning styles and students’ behavior in e-learning is found to be very weak (rs=.276, p=.000), but statistically significant (p<0.05). In other words, students’ learning styles and behavior in e-learning have significant impacts on the improvement or degradation of students’ performance. Therefore, from the results of this study, an adaptive KALAM e-learning system which can suits the learning styles of UMP students is proposed. In adaptive e-learning system, students can access learning materials that match the students' learning needs and preferences.
Volume: 8
Issue: 1
Page: 17-26
Publish at: 2017-10-01

Insights to Problems, Research Trend and Progress in Techniques of Sentiment Analysis

10.11591/ijece.v7i5.pp2818-2822
Kumar P. K. , Nandagopalan S.
The research-based implementations towards Sentiment analyses are about a decade old and have introduced many significant algorithms, techniques, and framework towards enhancing its performance. The applicability of sentiment analysis towards business and the political survey is quite immense. However, we strongly feel that existing progress in research towards Sentiment Analysis is not at par with the demand of massively increasing dynamic data over the pervasive environment. The degree of problems associated with opinion mining over such forms of data has been less addressed, and still, it leaves the certain major scope of research. This paper will brief about existing research trends, some important research implementation in recent times, and exploring some major open issues about sentiment analysis. We believe that this manuscript will give a progress report with the snapshot of effectiveness borne by the research techniques towards sentiment analysis to further assist the upcoming researcher to identify and pave their research work in a perfect direction towards considering research gap.
Volume: 7
Issue: 5
Page: 2818-2822
Publish at: 2017-10-01

Chaos Embedded Symbiotic Organisms Search Technique for Optimal FACTS Device Allocation for Voltage Profile and Security Improvement

10.11591/ijeecs.v8.i1.pp146-153
Mohamad Khairuzzaman Mohamad Zamani , Ismail Musirin , Saiful Izwan Suliman , Tarek Bouktir
Due to the ever-increasing energy demand, power system operators have attempted to cope with these demands while keeping the power system remain operable. Economic constraints have forced the power system operator to abandon their effort in expanding the power system. The increased load demand can cause the power system to suffer from voltage instability and voltage collapse, especially during contingency condition. Hence, a strategy is required to maintain the steady state operation of a power system. Various research has been conducted to tackle this problem. Therefore, this paper presents the implementation of Chaos Embedded Symbiotic Organisms Search technique to solve optimal FACTS device allocation problem in power transmission system. Various practical constraints are also considered in the optimisation process to emulate the real-life constraints in power system. The optimisation process is conducted on a 26-bus IEEE RTS has validated that the results obtained has not violated the power system stability. The results provided by the proposed optimisation technique has successfully improved the voltage profile and voltage security in the system. Comparative studies are also conducted involving Particle Swarm Optimization and Evolutionary Programming technique resulting good results agreement and superiority of the proposed technique. Results obtained from this study would be beneficial to the power system operators regarding optimisation in power system operation for the implementation in real power transmission network.
Volume: 8
Issue: 1
Page: 146-153
Publish at: 2017-10-01

A Novel Integrated Framework to Ensure Better Data Quality in Big Data Analytics over Cloud Environment

10.11591/ijece.v7i5.pp2798-2805
C.S. Sindhu , Nagaratna P. Hegde
With advent of Big Data Analytics, the healthcare system is increasingly adopting the analytical services that is ultimately found to generate massive load of highly unstructured data. We reviewed the existing system to find that there are lesser number of solutions towards addressing the problems of data variety, data uncertainty, and data speed. It is important that an error-free data should arrive in analytics. Existing system offers single-hand solution towards single platform. Therefore, we introduced an integrated framework that has the capability to address all these three problems in one execution time. Considering the synthetic big data of healthcare, we carried out the investigation to find that our proposed system using deep learning architecture offers better optimization of computational resources. The study outcome is found to offer comparatively better response time and higher accuracy rate as compared to existing optimization technqiues that is found and practiced widely in literature.
Volume: 7
Issue: 5
Page: 2798-2805
Publish at: 2017-10-01

Performance Enhancement in SU and MU MIMO-OFDM Technique for Wireless Communication: A Review

10.11591/ijece.v7i5.pp2459-2467
S.N. Raut , R.M. Jalnekar
The consistent demand for higher data rates and need to send giant volumes of data while not compromising the quality of communication has led the development of a new generations of wireless systems. But range and data rate limitations are there in wireless devices. In an attempt to beat these limitations, Multi Input Multi Output (MIMO) systems will be used which also increase diversity and improve the bit error rate (BER) performance of wireless systems. They additionally increase the channel capacity, increase the transmitted data rate through spatial multiplexing, and/or reduce interference from other users. MIMO systems therefore create a promising communication system because of their high transmission rates without additional bandwidth or transmit power and robustness against multipath fading. This paper provides the overview of Multiuser MIMO system. A detailed review on how to increase performance of system and reduce the bit error rate (BER) in different fading environment e.g. Rayleigh fading, Rician fading, Nakagami fading, composite fading.
Volume: 7
Issue: 5
Page: 2459-2467
Publish at: 2017-10-01

Optimized High-Utility Itemsets Mining for Effective Association Mining Paper

10.11591/ijece.v7i5.pp2911-2918
K Rajendra Prasad
Association rule mining is intently used for determining the frequent itemsets of transactional database; however, it is needed to consider the utility of itemsets in market behavioral applications. Apriori or FP-growth methods generate the association rules without utility factor of items. High-utility itemset mining (HUIM) is a well-known method that effectively determines the itemsets based on high-utility value and the resulting itemsets are known as high-utility itemsets. Fastest high-utility mining method (FHM) is an enhanced version of HUIM. FHM reduces the number of join operations during itemsets generation, so it is faster than HUIM. For large datasets, both methods are very expenisve. Proposed method addressed this issue by building pruning based utility co-occurrence structure (PEUCS) for elimatination of low-profit itemsets, thus, obviously it process only optimal number of high-utility itemsets, so it is called as optimal FHM (OFHM). Experimental results show that OFHM takes less computational runtime, therefore it is more efficient when compared to other existing methods for benchmarked large datasets.
Volume: 7
Issue: 5
Page: 2911-2918
Publish at: 2017-10-01

Power System State Estimation Bad Data Detection and Identification: A Review on Issues and Alternative Formulations

10.11591/ijeecs.v8.i1.pp122-128
Nurul Fauzana Imran Gulcharan , Nursyarizal Mohd Nor , Taib Ibrahim , Hanita Daud
State Estimation (SE) is the main function of power system where Energy Management System (EMS) is obliged to estimate the available states. Power system is a quasi-static system and hence changes slowly with time. Dynamic State Estimation (DSE) technique represents the time deviation nature of the system, which allows the forecasting of state vector in advance. Various techniques for DSE are available in the literature. This paper presents a review on different methodologies and developments in DSE, based on comprehensive survey of the available literature. From the survey it can be concluded that there are still areas in the developing DSE that can still be improved in terms of system computational time, redundancy and robustness of the system.
Volume: 8
Issue: 1
Page: 122-128
Publish at: 2017-10-01

Types of Circuit Breaker and its Application in Substation Protection

10.11591/ijeecs.v8.i1.pp213-220
Hui Hwang Goh , Sy yi Sim , Nur Iskandar bin Hamzah , Sulaiman bin Mazlan , Chin Wan Ling , Qing Shi Chua , Kai Chen Goh
Power system consists of the generation, transmission, distribution, and substation. All the power system component requires suitable protection devices as the protection system to protect the system during fault occur. In this paper, the circuit breaker has been selected as one of the protection devices in several applications. The types of circuit breaker that has been reviewed in this paper are oil circuit breaker (OCB), air circuit breaker (ACB), sulphur hexafluoride (SF6) circuit breaker, vacuum circuit breaker, and DC breaker which are hybrid DC breaker and solid-state DC breaker. Normally, the systems or the circuits disrupted or damaged by the fault. To implement the protection system in the system or circuit, the type of faults and cause of faults should be known to overcome the fault. To provide the suitable voltage for the consumer, the substation is needed to control the voltage transmitted at high voltage from the generating station. Protection system is also required in a substation.
Volume: 8
Issue: 1
Page: 213-220
Publish at: 2017-10-01

An Adaptive Scheme to Achieve Fine Grained Video Scaling

10.11591/ijeecs.v8.i1.pp43-58
S Safinaz , A. V. Ravi Kumar
A robust Adaptive Reconstruction Error Minimization Convolution Neural Network ( ARemCNN) architecture introduced to provide high reconstruction quality from low resolution using parallel configuration. Our proposed model can easily train the bulky datasets such as YUV21 and Videoset4.Our experimental results shows that our model outperforms many existing techniques in terms of PSNR, SSIM and reconstruction quality. The experimental results shows that our average PSNR result is 39.81 considering upscale-2, 35.56 for upscale-3 and 33.77 for upscale-4 for Videoset4 dataset which is very high in contrast to other existing techniques. Similarly, the experimental results shows that our average PSNR result is 38.71 considering upscale-2, 34.58 for upscale-3 and 33.047 for upscale-4 for YUV21 dataset.
Volume: 8
Issue: 1
Page: 43-58
Publish at: 2017-10-01

Extension Mode in Sliding Window Technique to Minimize Border Distortion Effect

10.11591/ijeecs.v8.i1.pp237-244
Saidatul Habsah Asman , Ahmad Farid Abidin , Nofri Yenita Dahlan
This paper deals with border distortion effect at starting and ending of finite signal by proposing sliding window technique and basic extension mode implementation. Single phase of transient and voltage sag is chosen to be analyzed in wavelet. The signal which being used for the analysis is simulated in Matlab 2017a. Disturbance signal decomposes into four level and Daubechies 4 (db4) has been chosen for computation. The proposed technique has been compared with conventional method which is finite length power disturbance analysis. Simulation result revealed that the proposed smooth-padding mode can be successfully minimized the border distortion effect compared to the zero-padding and symmetrization approach. 
Volume: 8
Issue: 1
Page: 237-244
Publish at: 2017-10-01

An Edge Exposure using Caliber Fuzzy C-means With Canny Algorithm

10.11591/ijeecs.v8.i1.pp59-68
Gowri Jeyaraman , Janakiraman Subbiah
Edge exposure or edge detection is an important and classical study of the medical field and computer vision.  Caliber Fuzzy C-means (CFCM) clustering Algorithm for edge detection depends on the selection of initial cluster center value. This endeavor to put in order a collection of pixels into a cluster, such that a pixel within the cluster must be more comparable to every other pixel. Using CFCM techniques first cluster the BSDS image, next the clustered image is given as an input to the basic canny edge detection algorithm. The application of new parameters with fewer operations for CFCM is fruitful. According to the calculation, a result acquired by using CFCM clustering function divides the image into four clusters in common. The proposed method is evidently robust into the modification of fuzzy c-means and canny algorithm. The convergence of this algorithm is very speedy compare to the entire edge detection algorithms. The consequences of this proposed algorithm make enhanced edge detection and better result than any other traditional image edge detection techniques.
Volume: 8
Issue: 1
Page: 59-68
Publish at: 2017-10-01

Optimum Enhance Time of Use (ETOU) for Demand Side Electricity Pricing in Regulated Market: An Implementation Using Evolutionary Algorithm

10.11591/ijeecs.v8.i1.pp253-261
M. F. Sulaima , N. Y. Dahlan , Z.M. Yasin , N.A.M. Asari , Z.H. Bohari
The energy growth in Malaysia is rapidly increasing as the country moves forward with the advancement of industrial revolution. Peak hours require more energy generation, thus cost is also more expensive than during off-peak. Due to this reason, Demand Side Management (DSM) through Demand Response (DR) technique is introduced to modify the demand profile by implementing different strategies of measures. The objective of this study is to optimize the energy profile for commercial sector, as well as analyse the significance of electricity cost reduction by using the optimization technique. A Meta-heuristic technique called as Evolutionary Algorithm (EA) has been implemented in this study to optimize the load profile of a commercial installation. Significant testing shows that the proposed optimization technique has the ability to reform the Maximum Demand from peak zone to off-peak zone to reduce electricity cost. The test results have been validated through 4 cases, which are conventional method for C1 ETOU, C2 ETOU, and C1 ETOU with Optimization technique, and C2 ETOU with optimization technique tariff, respectively. The impact of the EP has been analysed, while the performance of six-time segmentation of C1 and C2 ETOU tariff indicate that the electricity cost for the medium voltage of installation has been reduced. It is hoped that the results from this study can benefit consumers by giving them the flexibility to rearrange their own energy consumption profile, so that the demand side will enjoy significant reduction of electricity cost in the future. 
Volume: 8
Issue: 1
Page: 253-261
Publish at: 2017-10-01

Transmission Line Fault Detection: A Review

10.11591/ijeecs.v8.i1.pp199-205
Hui Hwang Goh , Sy yi Sim , Asad Shaykh , Md. Humayun Kabir , Chin Wan Ling , Qing Shi Chua , Kai Chen Goh
Transmission line is the most important part of the power system.  Transmission lines a principal amount of power. The requirement of power and its allegiance has grown up exponentially over the modern era, and the major role of a transmission line is to transmit electric power from the source area to the distribution network. The exploded between limited production, and a tremendous claim has grown the focus on minimizing power losses. Losses like transmission loss and also conjecture factors as like as physical losses to various technical losses, Another thing is the primary factor it has a reactive power and voltage deviation are momentous in the long-range transmission power line. In essentially, fault analysis is a very focusing issue in power system engineering to clear fault in short time and re-establish power system as quickly as possible on very minimum interruption. However,  the fault detection that interrupts the transmission line is itself challenging task to investigate fault as well as improving the reliability of the system. The transmission line is susceptible given all parameters that connect the whole power system. This paper presents a review of transmission line fault detection.
Volume: 8
Issue: 1
Page: 199-205
Publish at: 2017-10-01

On-line Assessment of Voltage Stability using Synchrophasor Technology

10.11591/ijeecs.v8.i1.pp1-8
Satyendra Pratap Singh , S.P. Singh
Series of blackouts encountered in recent years in power system have been occurred because either of voltage or angle instability or both together was not detected within time and progressive voltage or angle instability further degraded the system condition, because of increase in loading. This paper presents the real-time assessment methodology of voltage stability using Phasor Measurement Unit (PMU) with observability of load buses only in power network. PMUs are placed at strategically obtained location such that minimum number of PMU’s can make all load buses observable. Data obtained by PMU’s are used for voltage stability assessment with the help of successive change in the angle of bus voltage with respect to incremental load, which is used as on-line voltage stability predictor (VSP). The real-time voltage phasors obtained by PMU’s are used as real time voltage stability indicator. The case study has been carried out on IEEE-14 bus system and IEEE-30 bus systems to demonstrate the results.
Volume: 8
Issue: 1
Page: 1-8
Publish at: 2017-10-01
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