• Information Systems Review
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• v.16 no.3
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• pp.161-177
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• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.157-167
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• 2009

Recently, the leakage of confidential information and personal information is taking place on the Internet more frequently than ever before. Most of such online security incidents are caused by attacks on vulnerabilities in web applications developed carelessly. It is impossible to detect an attack on a web application with existing firewalls and intrusion detection systems. Besides, the signature-based detection has a limited capability in detecting new threats. Therefore, many researches concerning the method to detect attacks on web applications are employing anomaly-based detection methods that use the web traffic analysis. Much research about anomaly-based detection through the normal web traffic analysis focus on three problems - the method to accurately analyze given web traffic, system performance needed for inspecting application payload of the packet required to detect attack on application layer and the maintenance and costs of lots of network security devices newly installed. The UTM(Unified Threat Management) system, a suggested solution for the problem, had a goal of resolving all of security problems at a time, but is not being widely used due to its low efficiency and high costs. Besides, the web filter that performs one of the functions of the UTM system, can not adequately detect a variety of recent sophisticated attacks on web applications. In order to resolve such problems, studies are being carried out on the web application firewall to introduce a new network security system. As such studies focus on speeding up packet processing by depending on high-priced hardware, the costs to deploy a web application firewall are rising. In addition, the current anomaly-based detection technologies that do not take into account the characteristics of the web application is causing lots of false positives and false negatives. In order to reduce false positives and false negatives, this study suggested a realtime anomaly detection method based on the analysis of the length of parameter value contained in the web client's request. In addition, it designed and suggested a WAF(Web Application Firewall) that can be applied to a low-priced system or legacy system to process application data without the help of an exclusive hardware. Furthermore, it suggested a method to resolve sluggish performance attributed to copying packets into application area for application data processing, Consequently, this study provide to deploy an effective web application firewall at a low cost at the moment when the deployment of an additional security system was considered burdened due to lots of network security systems currently used.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.717-722
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• 2001

This paper presents a methodology on the backward path tracking control of a trailer type robot which consists of two parts: a tractor and a trailer. It is difficult to control the motion of a trailer vehicle since its dynamics is non-holonomic. Therefore, in this paper, the modeling and parameter estimation of the system using a real-coded genetic algorithm(RCGA) is proposed and a backward path tracking control algorithm is then obtained based on the linearized model. Experimental results verify the effectiveness of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.3 s.345
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• pp.21-32
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• 2006

A new SRAM circuit with row-by-row activation and low-swing write schemes is proposed to reduce switching power of active cells as well as leakage one of sleep cells in this paper. By driving source line of sleep cells by $V_{SSH}$ which is higher than $V_{SS}$, the leakage current can be reduced to 1/100 due to the cooperation of the reverse body-bias. Drain Induced Barrier Lowering (DIBL), and negative $V_{GS}$ effects. Moreover, the bit line leakage which may introduce a fault during the read operation can be eliminated in this new SRAM. Swing voltage on highly capacitive bit lines is reduced to $V_{DD}-to-V_{SSH}$ from the conventional $V_{DD}-to-V_{SS}$ during the write operation, greatly saving the bit line switching power. Combining the row-by-row activation scheme with the low-swing write does not require the additional area penalty. By the SPICE simulation with the Berkeley Predictive Technology Modes, 93% of leakage power and 43% of switching one are estimated to be saved in future leakage-dominant 70-un process. A test chip has been fabricated using $0.35-{\mu}m$ CMOS process to verify the effectiveness and feasibility of the new SRAM, where the switching power is measured to be 30% less than the conventional SRAM when the I/O bit width is only 8. The stored data is confirmed to be retained without loss until the retention voltage is reduced to 1.1V which is mainly due to the metal shield. The switching power will be expected to be more significant with increasing the I/O bit width.

• The Korean Journal of Nuclear Medicine
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• v.38 no.5
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• pp.338-343
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• 2004

Purpose: The purpose of this study was to develop a small animal PET using dual layer phoswich detector to minimize parallax error that degrades spatial resolution at the outer part of field-of-view (FOV). Materials and Methods: A simulation tool GATE (Geant4 Application for Tomographic Emission) was used to derive optimal parameters of small PET, and PET was developed employing the parameters. Lutetium Oxyorthosilicate (LSO) and Lutetium-Yttrium Aluminate-Perovskite(LuYAP) was used to construct dual layer phoswitch crystal. $8{\times}8$ arrays of LSO and LuYAP pixels, $2mm{\times}2mm{\times}8mm$ in size, were coupled to a 64-channel position sensitive photomultiplier tube. The system consisted of 16 detector modules arranged to one ring configuration (ring inner diameter 10 cm, FOV of 8 cm). The data from phoswich detector modules were fed into an ADC board in the data acquisition and preprocessing PC via sockets, decoder block, FPGA board, and bus board. These were linked to the master PC that stored the events data on hard disk. Results: In a preliminary test of the system, reconstructed images were obtained by using a pair of detectors and sensitivity and spatial resolution were measured. Spatial resolution was 2.3 mm FWHM and sensitivity was 10.9 $cps/{\mu}Ci$ at the center of FOV. Conclusion: The radioactivity distribution patterns were accurately represented in sinograms and images obtained by PET with a pair of detectors. These preliminary results indicate that it is promising to develop a high performance small animal PET.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.8
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• pp.759-769
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• 2013

Electronic equipment has been applied to virtually every area associated with commercial, industrial, and military applications. Specifically, electronics have been incorporated into avionics components installed in aircraft. This equipment is exposed to dynamic loads such as vibration, shock, and acceleration. Especially, avionics components installed in a helicopter are subjected to simultaneous sine and random base excitations. These are denoted as sine on random vibrations according to MIL-STD-810F, Method 514.5. In the past, isolators have been applied to avionics components to reduce vibration and shock. However, an isolator applied to an avionics component installed in a helicopter can amplify the vibration magnitude, and damage the chassis, circuit card assembly, and the isolator itself via resonance at low-frequency sinusoidal vibrations. The objective of this study is to investigate the dynamic characteristics of an avionics component installed in a helicopter and the structural dynamic modification of its tray plate without an isolator using both a finite element analysis and experiments. The structure is optimized by dynamic loads that are selected by comparing the vibration, shock, and acceleration loads using vibration and shock response spectra. A finite element model(FEM) was constructed using a simplified geometry and valid element types that reflect the dynamic characteristics. The FEM was verified by an experimental modal analysis. Design parameters were extracted and selected to modify the structural dynamics using topology optimization, and design of experiments(DOE). A prototype of a modified model was constructed and its feasibility was evaluated using an FEM and a performance test.

• Korean Chemical Engineering Research
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• v.46 no.5
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• pp.994-1001
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• 2008

Freundlich isothermal adsorption parameters, applicable to such biofilter-model as process-lumping model(Lim's model), for sterilized granular activated carbon(GAC), sterilized compost and sterilized equal volume mixture of GAC and compost were obtained and were compared each other, assuming that adsorbents are enclosed by water layer, in order to construct robust process-lumping biofilter model effective for wide-range of hydrophilic volatile organic compounds(VOC). In this investigation 0.04, 0.08, 0.12, 0.16, 0.2, 0.4, 0.8 and 1.0ml of ethanol were added to three kinds of adsorbent-media and were placed at $30^{\circ}{\cdots}$ under the wet condition of the media, which was the same as biofilter operating condition, until the adsorption reached the condition of equilibrium before each adsorbed amount of ethanol was obtained. Then adsorption capacity parameters(K) and adsorption exponents of Freundlich adsorption isotherm equation, which simulates the adsorbed amount of ethanol equilibrated with the ethanol concentration of the condensed water in the pore of the media, were constructed for sterilized granular activated carbon(GAC), sterilized compost and sterilized equal volume mixture of GAC and compost as (0.7566 and $5.070{\times}10^{-7}mg-ethanol/mgmedia/(mg-ethanol/m^3)^{0.7566}$), (0.8827 and $1.000{\times}10^{-8}mg-ethanol/mgmedia/(mg-ethanol/m^3)^{0.8827}$) and (0.5688 and $5.243{\times}10^{-6}mg-ethanol/mgmedia/(mg-ethanol/m^3)^{0.5688}$), respectively. These Freundlich isothermal adsorption parameters were applicable to the adsorption characteristics of biofilter media enclosed with bio-layer. The order of magnitude of the ratio of ethanol-air/water partition coefficient and toluene-air/water partition coefficient was almost consistent to that of ethanol-adsorbed amounts in this experiment with compost and in the investigation of Delhomenie et al. on toluene-adsorption to wet compost.