• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.165-172
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• 2009

According to the American Cancer Society, breast cancer is the second largest cause of cancer deaths and most frequently diagnosed cancer in women. The currently most popular method for early detection of breast cancer is the digital mammography. A mass or calcification lesion has been known as the most important clue for the diagnosis. In this paper, we propose a diagnosis approach based on fuzzy cluster knowledge base. We combine different two sources of feature data in duel OFUN-NET and produce the diagnosis result with possibility degree. We also present the experimental results on the dataset of mass and calcification lesions extracted from the public real world mammogram database DDSM. These results show higher classification accuracy than conventional methods and the feasibility as a decision supporting tool for diagnosis of digital mammogram.

• Korean Journal of Optics and Photonics
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• v.29 no.4
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• pp.149-158
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• 2018

A generalized structural design equation can be used to simplify and systematize a telecentric lens system composed of multiple lenses, as a creative design method of the authors. Through this structural equation, we have investigated the feasibility and design methodology of a telecentric lens equipped with a conventional smartphone camera for machine vision. As a result, we could verify and present a useful, generalized structural equation termed the $f{\theta}$ formula, being able to divide and combine the whole telecentric lens system into two modularized lens groups.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.11
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• pp.30-41
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• 2010

In this study we propose a new texture feature extraction method based on an estimation of the brightness and structural uniformity of CT images representing the important characteristics for emphysema recognition. The Center-Symmetric Local Binary Pattern (CS-LBP) is first used to combine gray level in order to describe the brightness uniformity characteristics of the CT image. Then the gradient orientation difference is proposed to generate another CS-LBP code combining with gray level to represent the structural uniformity characteristics of the CT image. The usage of the gray level, CS-LBP and gradient orientation differences enables the proposed method to extract rich and distinctive information from the CT images in multiple directions. Experimental results showed that the performance of the proposed method is more stable with respect to sensitivity and specificity when compared with the SGLDM, GLRLM and GLDM. The proposed method outperformed these three conventional methods (SGLDM, GLRLM, and GLDM) 7.85[%], 22.87[%], and 16.67[%] respectively, according to the diagnosis of average accuracy, demonstrated by the Receiver Operating Characteristic (ROC) curves.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.12
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• pp.1145-1151
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• 2012

In this paper, we propose an unambiguous binary offset carrier (BOC) correlation function with narrow main-peak width for BOC code tracking. Specifically, we first separate a subcarrier pulse into two rectangular pulses, obtain the associated partial correlations, and re-combine the partial correlations to yield the unambiguous correlation function with narrow main-peak width. From numerical results, it is demonstrated that the proposed correlation function provides a significant performance improvement over the conventional correlation functions.

• Journal of Satellite, Information and Communications
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• v.6 no.2
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• pp.78-83
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• 2011

In this paper, we propose a computationally efficient early stopping method to reduce the average number of iterations. The conventional early stopping methods have too much computational complexity to compute the stopping criterion. Thus, only the hard decision based early stopping method is suitable to realize the hardware of LDPC decoder. However, this method also can increase the computational complexity of LDPC decoder. The proposed method can effectively reduce the computational complexity of stopping criterion as we do not compute hard decision, and we combine the stopping criterion with horizontal shuffling scheduling decoding scheme. The simulation results show that a new early stopping method achieves acceptable bit error rate performance also reduces the average number of iterations.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.2
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• pp.144-148
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• 2005

The industrial development of large scale deep bed filters has been a very important step in the process of drinking water production and more recently in the tertiary treatment of wastewater. The target of deep bed filtration is the retention is the retention of small particles generally smaller than 30 microns at relatively small concentration, generally less than 30 mg/l from natural water (surface water or aquifers) or secondary treated wastewater. The relation between the retention efficiency and the characteristics of the particles has been extensively studied experimentally and through different models of retention. During the last years the development of new technologies (fiber filter, membrane modules) lead to more intensive processes compared to conventional sand filtration. Fiber filters can combine intensification with a decrease in specific energy needed however they cannot be operated under gravity like sand filters. Membrane filters (UF or MF) are much more intensive and efficient than sand filters. The specific energy needed is not so high (about $0.1Kwh/M^3$) but is higher than sand or fiber filter. A Life Cycle Analysis (LCA) has to be made for a complete comparison between these technologies taking in account that the efficiency of particle retention obtained by membrane filters is unique.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.565-569
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• 2004

Conventional methods for reducing vibration in engineering designs (i.e. by stiffening or detuning) may be undesirable or inadequate in conditions where size or weight must be minimized or where complex vibration spectra exist. Alloys which combine high damping capacity with good mechanical properties can provide attractive technical and economic solutions to problems involving seismic, shock and vibration isolation. To meet these trends, we have developed a new high damping Fe-17%Mn alloys. Also, the alloy has advantages of good mechanical properties and more economical than any other known damping alloys(1/4 times as cost of non-ferrous damping alloy). Thus, the high damping Fe-17%6Mn alloy can be widely applied to household appliances, automobiles, industrial facilities and power plant components with its excellent damping capacity(SDC, 30%) and mechanical property(T.S 700MPa). It is the purpose of this paper to introduce the characterization of the high damping Fe-17%Mn alloy and the results of retrofit several such applications.

• Journal of Biomedical Engineering Research
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• v.21 no.5
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• pp.527-535
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• 2000

For a reliable patient set-up verification, better portal films are needed to track relevant features. Simulator films are compared with portal films as a reference image in radiotherapy planning. This shows some possibilities of the use of image information of simulator images for enhancement and restorations of portal images which are very poor in quality compared with the simulator images. This paper present an approach that combine an associative memory, a kind of artificial neural networks with fuzzy image enhancement technique using genetic algorithm which determines the fuzzy region of membership function by the use of maximum entropy principles. A higher portal image quality than conventional technique is achieved.

• Journal of Electrochemical Science and Technology
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• v.9 no.4
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• pp.251-259
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• 2018

In general, the charge storage characteristics and overall performance of electrochemical energy devices (such as lithiumion batteries and supercapacitors) significantly depends on the structural and geometrical factors of the electrodes' active materials. The most widely used active materials of electrochemical energy storage devices are based on carbons of various forms. Each carbon type has drawbacks and advantages when used as the electrode material. Studies have been recently carried out to combine different types of carbons, in particular nanostructured carbons, in order to overcome the structure-originated limitations and thus enhance the overall electrochemical performances. In this feature article, we report the recent progress on the development of this novel class of materials (multidimensional nanocarbons), and their applications for supercapacitors. Multidimensional nanocarbons include graphenes/carbon nanotubes (CNTs), CNTs/carbon films, CNTs/fullerenes, and ternary carbon nanostructures. Various applications using these multidimensional nanocarbons have been proposed and demonstrated in the literature. Owing to the recent extensive studies on electrochemical energy storage devices and considering that carbons are their most fundamental electrode materials, the number of reports on nanocarbons employed as electrodes of the electrochemical energy storage devices is rapidly increasing. Recently, numerous multidimensional nanocarbons have been designed, prepared, and utilized as electrodes of electrochemical capacitors or supercapacitors, which are considered next-generation energy devices owing to their unique merits compared to the conventional structures. In this review, we summarize the basic motivations, preparation methods, and resultant supercapacitor performances of each class of multidimensional nanocarbons published in the literature, focusing on recent reports.

• Ocean Systems Engineering
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• v.9 no.3
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• pp.261-285
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• 2019

Nowadays in offshore industry there are emerging hazards with vague property such as act of terrorism, act of war, unforeseen natural disasters such as tsunami, etc. Therefore industry professionals such as offshore energy insurers, safety engineers and risk managers in order to determine the failure rates and frequencies for the potential hazards where there is no data available, they need to use an appropriate method to overcome this difficulty. Furthermore in conventional risk based analysis models such as when using a fault tree analysis, hazards with vague properties are normally waived and ignored. In other word in previous situations only a traditional probability based fault tree analysis could be implemented. To overcome this shortcoming fuzzy set theory is applied to fault tree analysis to combine the known and unknown data in which the pre-combined result will be determined under a fuzzy environment. This has been fulfilled by integration of a generic bow-tie based risk analysis model into the risk assessment phase of the Risk Management (RM) cycles as a backbone of the phase. For this reason Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) are used to analyse one of the significant risk factors associated in offshore terminals. This process will eventually help the insurers and risk managers in marine and offshore industries to investigate the potential hazards more in detail if there is vagueness. For this purpose a case study of offshore terminal while coinciding with the nature of the Caspian Sea was decided to be examined.