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29,167 Article Results

Multiset Controlled Grammars: A Simple Method in Regulated Rewriting Theory

10.11591/ijeecs.v8.i1.pp36-42
Salbiah Ashaari , Sherzod Turaev , M. Izzuddin M. Tamrin , Abdurahim Okhunov , Tamara Zhukabayeva
This study focus on defining a new variant of regulated grammars called multiset controlled grammars as well as investigating their computational power. We apply a constructive theoretical approach; the intent of which is to provide new theories based on computational methods where the results are appeared in the form of examples, lemmas and theorems. In the study, we have found that multiset is powerful and yet a simple method in regulated rewriting theory. We have proved that multiset controlled grammars are at least as powerful as additive valence grammars, and they are at most powerful as matrix grammars.
Volume: 8
Issue: 1
Page: 36-42
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

Internet of Things: Surveys for Measuring Human Activities from Everywhere

10.11591/ijece.v7i5.pp2474-2482
Amine Rghioui , Abdelmajid Oumnad
The internet of things (IoT), also called internet of all, is a new paradigm that combines several technologies such as computers, the internet, sensors network, radio frequency identification (RFID), communication technology and embedded systems to form a system that links the real worlds with digital worlds. With an increase in the deployment of smart objects, the internet of things should have a significant impact on human life in the near future. To understand the development of the IoT, this paper reviews the current research of the IoT, key technologies, the main applications of the IoT in various fields, and identifies research challenges. A main contribution of this review article is that it summarizes the current state of the IoT technology in several areas, and also the applications of IoT that cause side effects on our environment for monitoring and evaluation of the impact of human activity on the environment around us, and also provided an overview of some of the main challenges and application of IoT. This article presents not only the problems and challenges of IoT, but also solutions that help overcome some of the problems and challenges.
Volume: 7
Issue: 5
Page: 2474-2482
Publish at: 2017-10-01

Raman Pumping as an Energy Efficient Solution for NyWDM Flexible-grid Elastic Optical Networks

10.11591/ijece.v7i5.pp2627-2634
Arsalan Ahmad , Andrea Bianco , Vittorio Curri , Guido Marchetto , Sarosh Tahir
This paper investigates transparent wavelength routed optical networks using three different fiber types NZDSF, SMF and PSCF - and validates the effectiveness of Hybrid Raman/EDFA Fiber Amplification (HFA) with different pumping levels, up to the moderate 60% pumping regime. Nodes operate on the basis of flexible-grid elastic NyWDM transponders able to adapt the modulation format to the quality-of-transmission of the available lightpath, exploiting up to five 12.5 GHz spectral slots. Results consider a 37- node Pan-European network for variable Raman pumping level, span length and average traffic per node. We show that HFA in moderate pumping regime reduces the power consumption and enhances spectral efficiency for all three fiber types with particular evidence in NZDSF. In essence to that, introduction of HFA is also beneficial to avoid blocking for higher traffic loads.
Volume: 7
Issue: 5
Page: 2627-2634
Publish at: 2017-10-01

Hybrid Method HVS-MRMR for Variable Selection in Multilayer Artificial Neural Network Classifier

10.11591/ijece.v7i5.pp2773-2781
Ben-Hdech Adil , Ghanou Youssef , El Qadi Abderrahim
The variable selection is an important technique the reducing dimensionality of data frequently used in data preprocessing for performing data mining. This paper presents a new variable selection algorithm uses the heuristic variable selection (HVS) and Minimum Redundancy Maximum Relevance (MRMR). We enhance the HVS method for variab le selection by incorporating (MRMR) filter. Our algorithm is based on wrapper approach using multi-layer perceptron. We called this algorithm a HVS-MRMR Wrapper for variables selection. The relevance of a set of variables is measured by a convex combination of the relevance given by HVS criterion and the MRMR criterion. This approach selects new relevant variables; we evaluate the performance of HVS-MRMR on eight benchmark classification problems. The experimental results show that HVS-MRMR selected a less number of variables with high classification accuracy compared to MRMR and HVS and without variables selection on most datasets. HVS-MRMR can be applied to various classification problems that require high classification accuracy.
Volume: 7
Issue: 5
Page: 2773-2781
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

Multi Objective Directed Bee Colony Optimization for Economic Load Dispatch With Enhanced Power Demand and Valve Point Loading

10.11591/ijece.v7i5.pp2382-2391
S.K. Gachhayat , Saroj Kumar Dash , Priyambada Ray
Earlier economic emission dispatch methods for optimizing emission level comprising carbon monoxide, nitrous oxide and sulpher dioxide in thermal generation, made use of soft computing techniques like fuzzy,neural network,evolutionary programming,differential evolution and particle swarm optimization etc..The above methods incurred comparatively more transmission loss.So looking into the nonlinear load behavior of unbalanced systems following differential load pattern prevalent in tropical countries like India,Pakistan and Bangladesh etc.,the erratic variation of enhanced power demand is of immense importance which is included in this paper vide multi objective directed bee colony optimization with enhanced power demand to optimize transmission losses to a desired level.In the current dissertation making use of multi objective directed bee colony optimization with enhanced power demand technique the emission level versus cost of generation has been displayed vide figure-3 & figure-4 and this result has been compared with other dispatch methods using valve point loading(VPL) and multi objective directed bee colony optimization with & without transmission loss.
Volume: 7
Issue: 5
Page: 2382-2391
Publish at: 2017-10-01

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

Identity-Based Blind Signature Scheme with Message Recovery

10.11591/ijece.v7i5.pp2674-2682
Salome James , T. Gowri , G.V. Ramesh Babu , P. Vasudeva Reddy
Blind signature allows a user to obtain a signature on a message without revealing anything about the message to the signer. Blind signatures play an important role in many real world applications such as e-voting, e-cash system where anonymity is of great concern. Due to the rapid growth in popularity of both wireless communications and mobile devices, the design of secure schemes with low-bandwidth capability is an important research issue. In this paper, we present a new blind signature scheme with message recovery in the ID-based setting using bilinear pairings over elliptic curves. The proposed scheme is unforgeable with the assumption that the Computational Diffie-Hellman problem is hard. We compare our scheme with the related schemes in terms of computational and communicational point of view.
Volume: 7
Issue: 5
Page: 2674-2682
Publish at: 2017-10-01

Optimisation of Biochemical Systems Production using Hybrid of Newton Method, Differential Evolution Algorithm and Cooperative Coevolution Algorithm

10.11591/ijeecs.v8.i1.pp27-35
Mohd Arfian Ismail , Vitaliy Mezhuyev , Kohbalan Moorthy , Shahreen Kasim , Ashraf Osman Ibrahim
This paper present a hybrid method of Newton method, Differential Evolution Algorithm (DE) and Cooperative Coevolution Algorithm (CCA). The proposed method is used to solve the optimisation problem in optimise the production of biochemical systems. The problems are maximising the biochemical systems production and simultaneously minimising the total amount of chemical reaction concentration involves. Besides that, the size of biochemical systems also contributed to the problem in optimising the biochemical systems production. In the proposed method, the Newton method is used in dealing biochemical system, DE for optimisation process while CCA is used to increase the performance of DE. In order to evaluate the performance of the proposed method, the proposed method is tested on two benchmark biochemical systems. Then, the result that obtained by the proposed method is compare with other works and the finding shows that the proposed method performs well compare to the other works.
Volume: 8
Issue: 1
Page: 27-35
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

Economic Dispatch Using Quantum Evolutionary Algorithm in Electrical Power System Involving Distributed Generators

10.11591/ijece.v7i5.pp2365-2373
Ni Ketut Aryani , Adi Soeprijanto , I Made Yulistya Negara , Mat Syai’in
Unpredictable increase in power demands will overload the supply subsystems and insufficiently powered systems will suffer from instabilities, in which voltages drop below acceptable levels. Additional power sources are needed to satisfy the demand. Small capacity distributed generators (DGs) serve for this purpose well. One advantage of DGs is that they can be installed close to loads, so as to minimise loses. Optimum placements and sizing of DGs are critical to increase system voltages and to reduce loses. This will finally increase the overall system efficiency. This work exploits Quantum Evolutionary Algorithm (QEA) for the placements and sizing. This optimisation targets the cheapest generation cost. Quantum Evolutionary Algorithm is an Evolutionary Algorithm running on quantum computing, which works based on qubits and states superposition of quantum mechanics. Evolutionary algorithm with qubit representation has a better characteristic of diversity than classical approaches, since it can represent superposition of states.
Volume: 7
Issue: 5
Page: 2365-2373
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

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
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