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25,002 Article Results

Prediction and Realization of DO in Sewage Treatment Based on Machine Vision and BP Neural Network

10.12928/telkomnika.v12i4.437
Liu; Hebei United University Liping , Sunjin; Hebei United University Sheng , Yin; Hebei Energy College of Vocation and Technology Jing-tao , Liang; Hebei United University Na
Dissolved Oxygen (DO) is one of the most important parameters describing biochemical process in wastewater treatment. It is usually measured with dissolved oxygen meters, and currently galvanic and polarographic electrodes are the predominant methods. Expensive, membrane surface inactivation, and especially need of cleaning and calibrating very frequently are common disadvantages of electrode-type measuring sensors. In our work, a novel method for Prediction and Realization dissolved oxygen based-on Machine Vision and BP Neural Network was researched. Pictures of the water-body surface in aeration basins are captured and transformed into HSI space data. These data plus the correspondent measured DO values are processed with a neural network. Using the well-trained neural network, a satisfied result for classifying dissolved oxygen according to the water-body pictures has been realized.
Volume: 12
Issue: 4
Page: 890-896
Publish at: 2014-12-01

Image Deblurring via an Adaptive Dictionary Learning Strategy

10.12928/telkomnika.v12i4.532
Lei; Beijing Forestry University Li , Ruiting; Beijing Technology and Business University Zhang , Jiangmin; Beijing Forestry University Kan , Wenbin; Beijing Forestry University Li
Recently, sparse representation has been applied to image deblurring. The dictionary is the fundamental part of it and the proper selection of dictionary is very important to achieve super performance. The global learned dictionary might achieve inferior performances since it could not mine the specific information such as the texture and edge which is contained in the blurred image. However, it is a computational burden to train a new dictionary for image deblurring which requires the whole image (or most parts) as input; training the dictionary on only a few patches would result in over-fitting. To address the problem, we instead propose an online adaption strategy to transfer the global learned dictionary to a specific image. In our deblurring algorithm, the sparse coefficients, latent image, blur kernel and the dictionary are updated alternatively. And in every step, the global learned dictionary is updated in an online form via sampling only a few training patches from the target noisy image. Since our adaptive dictionary exploits the specific information, our deblurring algorithm shows superior performance over other state-of-the-art algorithms. 
Volume: 12
Issue: 4
Page: 855-864
Publish at: 2014-12-01

Mitigation of SSR Oscillations in Series Compensated Line using LCAP Subsynchronous Damping Controller

https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3917
Sanjiv Kumar , Narendra Kumar
Subsynchronous Resonance (SSR) is a growing problem in power systems having series compensated transmission lines. Subsynchronous resonance with low frequency that surpasses aggregate fatigue threshold of the generator shaft frequently could significantly reduce the shaft service life, which is a new problem that emerges in recent years. Flexible AC transmission systems (FACTS) controllers are widely applied to alleviate subsynchronous resonance. A line current and active power (LCAP) supplementary subsynchronous damping controller (SSDC) is proposed to damp subsynchronous resonance caused by series capacitors. Both eigenvalue investigation and time-domain simulation results verify that the proposed control strategy can effectively damping power system oscillations of the power system with SVS and SSDC. Time domain simulations using the nonlinear system model are also carried out to demonstrate the effectiveness of the proposed damping controller. The recommended control approach has been accumulated with the IEEE first benchmark model for SSR study.  The analysis indicates that SVS using the proposed control strategy has better alleviation effect and output characteristics. All the simulations are validated by using MATLAB/Simulink environment. http://dx.doi.org/10.11591/telkomnika.v12i12.6726 
Volume: 12
Issue: 12
Page: 8042-8050
Publish at: 2014-12-01

Analysis of variable speed chopper fed Brushless Direct Current motor

10.11591/ijeecs.v12.i12.pp8060-8068
Jeya Selvan Renius , Vinoth Kumar K , Raja Guru , Arnold Fredderics
This paper provides the detailed analysis of the DC-DC chopper fed Brushless DC motor drive used for low-power applications. The various methods used to improve the power quality at the ac mains with lesser number of components are discussed. The most effective method of power quality improvement is also simulated using MATLAB Simulink. Improved method of speed control by controlling the dc link voltage of Voltage Source Inverter is also discussed with reduced switching losses. The continuous and discontinuous modes of operation of the converters are also discussed based on the improvement in power quality. The performance of the most effective solution is simulated in MATLAB Simulink environment and the obtained results are presented.
Volume: 12
Issue: 12
Page: 8060-8068
Publish at: 2014-12-01

System Identification and LMI Based Robust PID Control of a Two-Link Flexible Manipulator

10.12928/telkomnika.v12i4.293
M.; Universitas Negeri Yogyakarta Khairudin , Z.; Universiti Teknologi Malaysia Mohamed , A.R.; Universiti Teknologi Malaysia Husain
This paper presents investigations into the development of a linear matrix inequalities (LMI) based robust PID control of a nonlinear Two-Link Flexible Manipulator (TLFM) incorporating payload. A set of linear models of a TLFM is obtained by using system identification method in which the linear model represents the operating ranges of the dynamic system. Thus, the LMI constraints permit to robustly guarantee a certain perturbation rejection level and a region of pole location.  To study the effectiveness of the controller, initially a PID control is developed for TLFM with varying payloads. The performances of the controllers are assessed in terms of the input tracking controller capability of the system as compared to the response with PID control. Moreover, the robustness of the LMI based robust PID control schemes is discussed. Finally, a comparative assessment of the control strategies is presented.
Volume: 12
Issue: 4
Page: 829-838
Publish at: 2014-12-01

A Reliable Web Services Selection Method for Concurrent Requests

10.12928/telkomnika.v12i4.786
Guiming; University of Water Resources and Electric Power Lu , Yan; University of Water Resources and Electric Power Hai , Yaoyao; University of Water Resources and Electric Power Sun
Current methods of service selection based on quality of service (QoS) usually focus on a single service request at a time, or let the users in a waiting queue wait for Web services when the same functional Web service has more than one requests, and then choose the Web service with the best QoS for the current request according to its own needs. However, there are multiple service requests for the same functional web service at a time in practice and we cannot choose the best service for users every time because of the service’s load. This paper aims at solving the Web Services selection for concurrent requests and developing a global optimal selection method for multiple similar service requesters to optimize the system resources. It proposes the improved social cognitive (ISCO) algorithm which uses genetic algorithm for observational learning and uses deviating degree to evaluate the solution. Furthermore, to enhance the efficiency of ISCO, the elite strategy is used in ISCO algorithm. We evaluate performance of the ISCO algorithm and the selection method through simulations. The simulation results demonstrate that the ISCO is valid for optimization problems with discrete data and more effective than ACO and GA.
Volume: 12
Issue: 4
Page: 1053-1063
Publish at: 2014-12-01

Accelerating Computation of DNA Multiple Sequence Alignment in Distributed Environment

https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3946
Ramdan Satra , Wisnu Ananta Kusuma , Heru Sukoco
Multiple sequence alignment (MSA) is a technique for finding similarity in many sequences. This technique is very important to support many Bioinformatics task such as identifying Single Nucleotide Polymorphism (SNP) and metagenome fragments binning. The simplest algorithm in MSA is Star Algorithm. The complexity of DNA multiple sequence alignment using dynamic programming technique is very high. This research aims to accelerate computation of Star Mutiple Sequence Alignment using Message Passing Interfaces (MPI). The performance of the proposed method was evaluated by calculating speedup. Experiment was conducted using 64 sequences of 800 bp Glycine-max-chromosome-9-BBI fragments yielded by randomly cut from reference sequence of Glycine-max-chromosome-9-BBI taken from NCBI (National Center for Biotechnology Information). The results showed that the proposed technique could obtain speedup three times using five computers when aligning 64 sequences of Glycine-max-chromosome-9-BBI fragments.  Moreover, the increasing of the number of computers would significantly increased speedup of the proposed. http://dx.doi.org/10.11591/telkomnika.v12i12.6572 
Volume: 12
Issue: 12
Page: 8278-8285
Publish at: 2014-12-01

Service Cooperation Incentive Mechanism in a Dual-channel Supply Chain under Service Differentiation

https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3949
Jun Chen , Ying Yang
An incentive mechanism about service effort provided by the manufacturer in a dual-channel supply chain is studied under asymmetric information. The principal-anent models are developed for asymmetric information and symmetric information, and then the optimal fixed payment and the optimal profit sharing ratio are obtained. In contrast to the case under symmetric information, the conclusion implies that the manufacturer’s profit decreases under asymmetric information, the retailer’s profit keep same even lower service level is provided. Thus, the system performance of the supply chain decreases. http://dx.doi.org/10.11591/telkomnika.v12i12.6193 
Volume: 12
Issue: 12
Page: 8303-8311
Publish at: 2014-12-01

Image Tamper Detection and Recovery by Intersecting Signatures

10.12928/telkomnika.v12i4.1009
Chun-Hung; National Sun Yat-sen University Chen , Yuan-Liang; Chaoyang University of Technology Tang , Wen-Shyong; Shu-Te University Hsieh , Min-Shiang; Asia University Hwang
In this paper, we propose an exact image authentication scheme that can, in the best case, detect image tampering with the accuracy of one pixel. This method is based on constructing blocks in the image in such a manner that they intersect with one another in different directions. Such a technique is very useful to identify whether an individual image pixel has been tampered with. Moreover, the tampered region can be well recovered with the embedded recover data.
Volume: 12
Issue: 4
Page: 1123-1131
Publish at: 2014-12-01

The B+-tree-based Method for Nearest Neighbor Queries in Traffic Simulation Systems

10.11591/ijeecs.v12.i12.pp8175-8192
Zhu Song , Zhiguang Qin , Weiwei Deng , Yuping Zhao
Extensive used traffic simulation systems are helpfulin planning and controlling the traffic system. In traffic sim-ulation systems, the state of each vehicle is affected by thatof nearby vehicles, called neighbors. Nearest neighbor (NN) queries, which are multi 1-dimensional and highly concurrent,largely determine the performance of traffic simulation systems. Majority of existing traffic simulation systems use Linked list-based methods to process NN queries. Although simple andeffective they are, existing methods are neither scalable nore fficient. In this paper, we propose a B+-tree-based method to improve the efficiency of NN queries by borrowing ideas from methods used in databases. In particular, we create a linked local B+-tree, called LLB+-tree, which is a variation of Original B+-tree, to maintain the index of neighbors of each vehicle. We also build a mathematical model to optimize the parameter setting of LLB+-tree according to multiple parameters for lanes and vehicles. Our theoretical analysis shows that the time complexityof the method is O(logN) under the assumption of randomly distribution of vehicles. Our simulation results show that LLB+-tree can outperform Linked list and Original B+-tree by 64.2%and 12.8%, respectively.
Volume: 12
Issue: 12
Page: 8175-8192
Publish at: 2014-12-01

Cooperative Avoidance Control-based Interval Fuzzy Kohonen Networks Algorithm in Simple Swarm Robots

10.12928/telkomnika.v12i4.495
Siti; University of Sriwijaya Nurmaini , Siti; Universiti Teknologi Malaysia Zaiton , Ricy; University of Sriwijaya Firnando
A novel technique to control swarm robot’s movement is presented and analyzed in this paper. It allows a group of robots to move as a unique entity performing the following function such as obstacle avoidance at group level. The control strategy enhances the mobile robot’s performance whereby their forthcoming decisions are impacted by its previous experiences during the navigation apart from the current range inputs. Interval Fuzzy-Kohonen Network (IFKN) algorithm is utilized in this strategy. By employing a small number of rules, the IFKN algorithms can be adapted to swarms reactive control. The control strategy provides much faster response compare to Fuzzy Kohonen Network (FKN) algorithm to expected events. The effectiveness of the proposed technique is also demonstrated in a series of practical test on our experimental by using five low cost robots with limited sensor abilities and low computational effort on each single robot in the swarm. The results show that swarm robots based on proposed technique have the ability to perform cooperative behavior, produces minimum collision and capable to navigate around square shapes obstacles.
Volume: 12
Issue: 4
Page: 795-810
Publish at: 2014-12-01

Process Improvement of LSA for Semantic Relatedness Computing

10.12928/telkomnika.v12i4.811
Wujian; Zhejiang University City College Yang , Lianyue; Zhejiang University City College Lin
Tang poetry semantic correlation computing is critical in many applications, such as searching, clustering, automatic generation of poetry and so on. Aiming to increase computing efficiency and accuracy of semantic relatedness, we improved the process of latent semantic analysis (LSA). In this paper, we adopted “representation of words semantic” instead of “words-by-poems” to represent the words semantic, which based on the finding that words having similar distribution in poetry categories are almost always semantically related. Meanwhile, we designed experiment which obtained segmentation words from more than 40000 poems, and computed relatedness by cosine value which calculated from decomposed co-occurrence matrix with Singular Value Decomposition (SVD) method. The experimental result shows that this method is good to analyze semantic and emotional relatedness of words in Tang poetry. We can find associated words and the relevance of poetry categories by matrix manipulation of the decomposing matrices as well.
Volume: 12
Issue: 4
Page: 1045-1052
Publish at: 2014-12-01

Feature Selection Method Based on Improved Document Frequency

10.12928/telkomnika.v12i4.536
Wei; Hebei North University Zheng , Guohe; South China Normal University Feng
Feature selection is an important part of the process of text classification, there is a direct impact on the quality of feature selection because of the evaluation function. Document frequency (DF) is one of several commonly methods used feature selection, its shortcomings is the lack of theoretical basis on function construction, it will tend to select high-frequency words in selecting. To solve the problem, we put forward a improved algorithm named DFM combined with class distribution of characteristics and realize the algorithm with programming, DFM were compared with some feature selection method commonly used with experimental using support vector machine, as text classification .The results show that, when feature selection, the DFM methods performance is stable at work and is better than other methods in classification results.
Volume: 12
Issue: 4
Page: 905-910
Publish at: 2014-12-01

HVDC Application for Different Solar PV Technology Combinations in India

https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3912
Suprava Chakraborty , Pradip Kumar Sadhu , Nitai Pal
Conventionally Grid Connected Solar PV plants initially generate DC power and then converted to AC via inverters and connected into AC grid for transmission power. Depending on the size of the plant, required environmental condition and land availability large PV plants are generally located far away from the load centre. Hence reduction of transmission loss and incised transmission capacity expansion is a greater challenge for modern newly establish solar power plant. Transmitting high voltage DC power directly from Solar PV panel to High voltage DC grid is become an accretive option for modern PV power plant. In this paper DC-DC bypass diode converter model is adopted to generate high voltage DC voltage in PV power plant. Result shows that power in the range of HVDC level can be generated when the voltage of different PV technology blocks are used as input. P-SIM software is used for simulating the circuit here.http://dx.doi.org/10.11591/telkomnika.v12i12.6822 
Volume: 12
Issue: 12
Page: 8008-8014
Publish at: 2014-12-01

High Recognition Ratio Image Processing Algorithm of Micro Electrical Components in Optical Microscope

10.12928/telkomnika.v12i4.304
Wu; Xi'an Jiaotong University Jie , Zuren; Xi'an Jiaotong University Feng , Lei; Xi'an Railway Vocational & Technical Institute Wang
In order to process small components of original image under the microscope, firstly, this paper adopts median filtering algorithm to enhance targets; and the targets are sharpened by using lateral inhibition algorithm, the edge of targets is outlined. In order to get reliable target region, adaptive threshold segmentation algorithm is used to extract need target region, and characteristics of target is used to distinguish multiple targets. Based on the chip resistor, one tiny component, in the captured image, we judge if the chip resistor is qualified by calculating the pixels area values. The experimental results show that, the image processing algorithm and qualified detection algorithm is reasonable, which provides the theoretical basis and implementation method of effective target extraction and further qualified test.
Volume: 12
Issue: 4
Page: 911-920
Publish at: 2014-12-01
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