• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1248-1251
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• 2002

Logistics optimization problems related with vehicle routing such as warehouse locating, track scheduling, customer order delivery, wastage pickup etc. are very interesting and important issues to date. Many Vehicle Routing and Scheduling Systems (VRSS) have been developed/proposed to optimize the logistics problems. But majority of them are dedicated to a particular problem and are unable to handle the real world spatial data directly. The system developed for one problem may not be suitable for others due to inter-problem constraint variations. The constraints may include geographical, environmental and road traffic nature of the working region along with other constraints related with the problem. So the developer always needs to modify the original routing algorithm in order to fulfill the purpose. In our study, we propose a general-purpose platform by combining GIS road map and Database Management System (DBMS), so that VRSS can interact with real world spatial data directly to solve different kinds of vehicle routing problems. Using the features of our developed system, the developer can frequently modify the existing algorithm or create a new one to serve the purpose.

• Journal of Power Electronics
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• v.11 no.4
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• pp.542-550
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• 2011

This paper describes the design and hardware implementation of a Single Input Fuzzy Logic Controller (SIFLC) to regulate the output voltage of a boost power converter. The proposed controller is derived from the signed distance method, which reduces a multi-input conventional Fuzzy Logic Controller (CFLC) to a single input FLC. This allows the rule table to be approximated to a one-dimensional piecewise linear control surface. A MATLAB simulation demonstrated that the performance of a boost converter is identical when subjected to the SIFLC or a CFLC. However, the SIFLC requires nearly an order of magnitude less time to execute its algorithm. Therefore the former can replace the latter with no significant degradation in performance. To validate the feasibility of the SIFLC, a 50W boost converter prototype is built. The SIFLC algorithm is implemented using an Altera FPGA. It was found that the SIFLC with asymmetrical membership functions exhibits an excellent response to load and input reference changes.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.443-450
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• 2012

As power grids are integrated into one big umbrella (i.e., Smart Grid), communication network plays a key role in reliable and stable operation of power grids. For successful operation of smart grid, interoperability and security issues must be resolved. Security means providing network system integrity, authentication, and confidentiality service. For a cyber-attack to a power grid system, which may jeopardize the national security, vulnerability of communication infrastructure has a serious impact on the power grid network. While security aspects of power grid network have been studied much, security mechanisms are rarely adopted in power gird communication network. For security issues, strict timing requirements are defined in IEC 61850 for mission critical messages (i.e., GOOSE). In this paper, we apply security algorithms (i.e., MD-5, SHA-1, and RSA) and measure their processing time and transmission delay of secured mission critical messages. The results show the algorithms satisfying the timing requirements defined in IEC 61850 and we observer the algorithm that is optimal for secure communication of mission critical messages. Numerical analysis shows that SHA-1 is preferable for secure GOOSE message sending.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2080-2085
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• 2018

There have been numerous studies that extract the R-peak from electrocardiogram (ECG) signals. All of these studies can extract R-peak from ECG. However, these methods are complicated and difficult to implement in a real-time portable ECG device. After filtration choosing a threshold value for R-peak detection is a big challenge. Fixed threshold scheme is sometimes unable to detect low R-peak value and adaptive threshold sometime detect wrong R-peak for more adaptation. In this paper, a simple and robustness algorithm is proposed to detect R-peak with less complexity. This method also solves the problem of threshold value selection. Using the adaptive filter, the baseline drift can be removed from ECG signal. After filtration, an appropriate threshold value is automatically chosen by using the minimum and maximum value of an ECG signals. Then the neighborhood searching scheme is applied under threshold value to detect R-peak from ECG signals. Proposed method improves the detection and accuracy rate of R-peak detection. After R-peak detection, we calculate heart rate to know the heart condition.

• Journal of Power Electronics
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• v.15 no.1
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• pp.202-215
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• 2015

This paper investigates the stability and performance of model predictive controlled active-front-end (AFE) rectifiers for energy storage systems, which has been increasingly applied in power distribution sectors and in renewable energy sources to ensure an uninterruptable power supply. The model predictive control (MPC) algorithm utilizes the discrete behavior of power converters to determine appropriate switching states by defining a cost function. The stability of the MPC algorithm is analyzed with the discrete z-domain response and the nonlinear simulation model. The results confirms that the control method of the active-front-end (AFE) rectifier is stable, and that is operates with an infinite gain margin and a very fast dynamic response. Moreover, the performance of the MPC controlled AFE rectifier is verified with a 3.0 kW experimental system. This shows that the MPC controlled AFE rectifier operates with a unity power factor, an acceptable THD (4.0 %) level for the input current and a very low DC voltage ripple. Finally, an efficiency comparison is performed between the MPC and the VOC-based PWM controllers for AFE rectifiers. This comparison demonstrates the effectiveness of the MPC controller.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.121-129
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• 2013

This paper proposes a linear-time algorithm that has been designed to obtain an accurate solution for Dominating Set (DS) problem, which is known to be NP-complete due to the deficiency of polynomial-time algorithms that successfully derive an accurate solution to it. The proposed algorithm does so by repeatedly assigning vertex v with maximum degree ${\Delta}(G)$among vertices adjacent to the vertex v with minimum degree ${\delta}(G)$ to Minimum Independent DS (MIDS) as its element and removing all the incident edges until no edges remain in the graph. This algorithm finally transforms MIDS into Minimum DS (MDS) and again into Minimum Connected DS (MCDS) so as to obtain the accurate solution to all DS-related problems. When applied to ten different graphs, it has successfully obtained accurate solutions with linear time complexity O(n). It has therefore proven that Dominating Set problem is rather a P-problem.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.595-598
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• 2013

Background: Lung cancer is the leading cause of cancer death worldwide Therefore, identification of genetic as well as environmental factors is very important in developing novel methods of lung cancer prevention. However, this is a multi-layered problem. Therefore a lung cancer risk prediction system is here proposed which is easy, cost effective and time saving. Materials and Methods: Initially 400 cancer and non-cancer patients' data were collected from different diagnostic centres, pre-processed and clustered using a K-means clustering algorithm for identifying relevant and non-relevant data. Next significant frequent patterns are discovered using AprioriTid and a decision tree algorithm. Results: Finally using the significant pattern prediction tools for a lung cancer prediction system were developed. This lung cancer risk prediction system should prove helpful in detection of a person's predisposition for lung cancer. Conclusions: Most of people of Bangladesh do not even know they have lung cancer and the majority of cases are diagnosed at late stages when cure is impossible. Therefore early prediction of lung cancer should play a pivotal role in the diagnosis process and for an effective preventive strategy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4754-4773
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• 2018

In sensor medium access control (SMAC) protocol, sensor nodes can only access the channel in the scheduling and listening period. However, this fixed working method may generate data latency and high conflict. To solve those problems, scheduling duty in the original SMAC protocol is divided into multiple small scheduling duties (micro duty MD). By applying different micro-dispersed contention channel, sensor nodes can reduce the collision probability of the data and thereby save energy. Based on the given micro-duty, this paper presents an adaptive duty cycle (DC) and back-off algorithm, aiming at detecting the fixed duty cycle in SMAC protocol. According to the given buffer queue length, sensor nodes dynamically change the duty cycle. In the context of low duty cycle and low flow, fair binary exponential back-off (F-BEB) algorithm is applied to reduce data latency. In the context of high duty cycle and high flow, capture avoidance binary exponential back-off (CA-BEB) algorithm is used to further reduce the conflict probability for saving energy consumption. Based on the above two contexts, we propose an improved SMAC protocol, micro duty adaptive SMAC protocol (MDA-SMAC). Comparing the performance between MDA-SMAC protocol and SMAC protocol on the NS-2 simulation platform, the results show that, MDA-SMAC protocol performs better in terms of energy consumption, latency and effective throughput than SMAC protocol, especially in the condition of more crowded network traffic and more sensor nodes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.63-68
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• 2014

This paper related with the I-CMA (Improved-CMA) algorithm that is possible to compensates of phase in CMA adatpve equalizer which is used for the elemination of intersymbol interference in the multipath fading and band limit characteristics of channel. The new cost function is proposed for the eliminate the amplitude and phase simulataneous by modifying the cost fuction for get the error signal in present CMA algorithm. It has a merit to the algorithm simplicities and eliminats the PLL device for phase compensation after equalization. For proving this, the recovered signal constellation that is the output of equalizer output signal and the residual isi and Maximum Distortion charateristic learning curve that are presents the convergence performance in the equalizer and the overall frequency transfer function of channel and equalizer were used. As a result of computer simulation, the I-CMA has more good compensation capability of amplitude and phas in the recovered constellation. But the convergence time is slow due to the simultaneously phase compensation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.4 s.304
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• pp.45-50
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• 2005

In digital hearing aid system, one of the main problems is acoustic feedback which is known as howling because of miniaturization md high-gain amplification. In this paper, we proposed a feedback cancellation algorithm for hearing aid using time delay and time-varying decorrelation filter. The proposed algorithm has a kind of adaptive filter structure, which is combined with time delay and time-varying decorrelation filter to improve feedback cancellation. An all pass filter was implemented as the time-varying decorrelation filter using low frequency modulator. From the result of computer simulation, it is verified that the proposed algorithm has good ability to cancel feedback.