• The Journal of Information Systems
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• v.8 no.1
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• pp.27-44
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• 1999

Case-Based Reasoning(CBR) offers a new approach for developing knowledge based systems. CBR has several research issues which can be divided into two categories : (1) static issues and (2) dynamic issues. The static issues are related to case representation scheme and case data model, that is, focus on casebase which is a repository of cases. The dynamic issues, on the other hand, are related to case retrieval procedure and problem solving process, i.e. case adaptation phase. This research is forcused on retrieval procedure Traditional query processing accepts precisely specified queries and only provides exact answers, thus requiring users to fully understand the problem domain and the casebase schema, but returning limited or even null information if the exact answer is not available. To remedy such a restriction, extending the classical notion of query answering to approximate query answering(AQA) has been explored. AQA can be achieved by neighborhood query answering or associative query answering. In this paper, neighborhood query answering technique is used for AQA. To reinforce the CBR process, a new retrieval procedure(cooperative CBR) using neighborhood query answering is proposed. An neighborhood query answering relaxes a query scope to enlarge the search range, or relaxes an answer scope to include additional information. Computer Aided Process Planning(CAPP) is selected as cooperative CBR application domain for test. CAPP is an essential key for achieving CIM. It is the bridge between CAD and CAM and translates the design information into manufacturing instructions. As a result of the test, it is approved that the problem solving ability of cooperative CBR is improved by relaxation technique.

• Phonetics and Speech Sciences
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• v.7 no.3
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• pp.183-191
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• 2015

This study evaluated the effect of the therapeutic methods between vocal function exercise(VFE), which has been used for the patients with presbyphonia in the precedent studies and laryngeal calibration technique($SKLCT^{(R)}$), which is designed by the author. We identified 58 patients who was been diagnosed as presbylaryngis by laryngoscopic examinations. 21 patients were underwent voice therapy using $SKLCT^{(R)}$, 20 patients were taken VFE, and the control group of 17 patients were not taken any voice therapy. All subjects received the therapy, ranging from seven to nine sessions, and were evaluated the voice change on pretherapy and posttherapy. The grade of hoarseness, roughness, and breathiness voice were reduced on perceptual judgments after $SKLCT^{(R)}$, but only grade of hoarseness was reduced after the VFE. Jitter, Shimmer, NHR were reduced and MPT were increased after the $SKLCT^{(R)}$(p<.05), while Jitter and SFF were reduced after the VFE. Frequency and intensity range were increased significantly on the posttest performance after taking voice therapy by the $SKLCT^{(R)}$, on the other hand only intensity range was increased after VFE. Especially, we can find the significant change that glottic gap and supraglottic compressions was reduced in most of patients after the $SKLCT^{(R)}$, but there's no changes in the group of VFE and control group. In the study, we can suggest that the $SKLCT^{(R)}$ may be useful in improving the voice qualities and laryngeal function of presbyphonia.

• Journal of Information Processing Systems
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• v.10 no.2
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• pp.283-299
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• 2014

Skin detection is used in many applications, such as face recognition, hand tracking, and human-computer interaction. There are many skin color detection algorithms that are used to extract human skin color regions that are based on the thresholding technique since it is simple and fast for computation. The efficiency of each color space depends on its robustness to the change in lighting and the ability to distinguish skin color pixels in images that have a complex background. For more accurate skin detection, we are proposing a new threshold based on RGB and YUV color spaces. The proposed approach starts by converting the RGB color space to the YUV color model. Then it separates the Y channel, which represents the intensity of the color model from the U and V channels to eliminate the effects of luminance. After that the threshold values are selected based on the testing of the boundary of skin colors with the help of the color histogram. Finally, the threshold was applied to the input image to extract skin parts. The detected skin regions were quantitatively compared to the actual skin parts in the input images to measure the accuracy and to compare the results of our threshold to the results of other's thresholds to prove the efficiency of our approach. The results of the experiment show that the proposed threshold is more robust in terms of dealing with the complex background and light conditions than others.

• Journal of Ginseng Research
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• v.37 no.4
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• pp.491-495
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• 2013

Wood-cultivated ginseng, including roots in its dried form, is produced in forest land without using artificial facilities such as light barriers. To identify suitable sites for the propagation of wood-cultivated ginseng, factor combination technique (FCT) and linear combination technique (LCT) were used with geographic information system and the results were superimposed onto an actual wood-cultivated ginseng plantation. The LCT more extensively searched for suitable sites of cultivation than that by the FCT; further, the LCT probed wide areas considering the predominance of precipitous mountains in Korea. In addition, the LCT showed the much higher degree of overlap with the actual cultivation sites; therefore, the LCT more comprehensively reflects the cultivator's intention for site selection. On the other hand, the inclusion of additional factors for the selection of suitable cultivation sites and experts' opinions may enhance the effectiveness and accuracy of the LCT for site application.

• Structural Engineering and Mechanics
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• v.69 no.5
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• pp.499-509
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• 2019

While the wheel flat is an asymmetrical phenomenon in the railway, majority of researches have used two-dimensional models in the investigation of the effect of wheel flat on the wheel rail forces. This is due to the considerably low computational costs of two dimensional (2D) models although their reliability is questionable. This leaves us with the question of "what is the optimum modeling technique?". It is addressed in this research. For this purpose, two and three dimensional numerical models of railway vehicle/track interaction were developed. The three dimensional (3D) model was validated by comparisons of its results with those obtained from a comprehensive field tests carried out in this research and then, the results obtained from the 2D and 3D models were compared. The results obtained indicate that there are considerable differences between wheel/rail forces obtained from the 2D and 3D models in the conditions of medium to large wheel-flats. On the other hand, it was shown that the results of the 2D models are reliable for particular ranges of vehicle speed, railway track stiffness and wheel-fats lengths and depths. The results were used to draw a diagram, which presents the optimum modeling technique, compromising between the costs and accuracy of the obtained results.

• Asian Journal of Business Environment
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• v.11 no.2
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• pp.27-38
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• 2021

Purpose: The study mainly investigates bankruptcy risk and income smoothing tendency of Non-Banking Financial Institutions (NBFIs) in Bangladesh. External parties of NBFIs take investment decisions based on financial reports. Stable and predictable income is one of their preference. On the other hand, poor income is one of the signs of NBFIs having bankruptcy risk. Hence the study tries to find whether the NBFIs having bankruptcy are involved in income smoothing or not. Research design, data and methodology: Data were collected from the annual report of twenty-two listed NBFIs in Bangladesh. Data from 2013 to 2017 were used. Altman's Z score and Eckel's model are used to detecting bankruptcy risk and income smoothing respectively. Results: Result implies that most of the NBFIs which have bankruptcy risk are not involved in income smoothing. Therefore, NBFIs which has bankruptcy risk are involved less with income smoothing. Conclusions: The present study revealed that most of the listed NBFIs in Bangladesh are facing bankruptcy risk. They didn't use any fraudulent technique to show smooth income. The findings will help the investor to take an investment decision on NBFIs in Bangladesh. It will convey signals to the stock market in Bangladesh.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.389-396
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• 2022

Smartphones are growing more susceptible as technology develops because they contain sensitive data that offers a severe security risk if it falls into the wrong hands. The Android OS includes permissions as a crucial component for safeguarding user privacy and confidentiality. On the other hand, mobile malware continues to struggle with permission misuse. Although permission-based detection is frequently utilized, the significant false alarm rates brought on by the permission-based issue are thought to make it inadequate. The present detection method has a high incidence of false alarms, which reduces its ability to identify permission-based attacks. By using permission features with intent, this research attempted to improve permission-based detection. However, it creates an excessive number of features and increases the likelihood of false alarms. In order to generate the optimal number of features created and boost the quality of features chosen, this research developed an intersection feature approach. Performance was assessed using metrics including accuracy, TPR, TNR, and FPR. The most important characteristics were chosen using the Correlation Feature Selection, and the malicious program was categorized using SVM and naive Bayes. The Intersection Feature Technique, according to the findings, reduces characteristics from 486 to 17, has a 97 percent accuracy rate, and produces 0.1 percent false alarms.

• Computers and Concrete
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• v.30 no.1
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• pp.43-74
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• 2022

Machine learning technique is recently opening new opportunities to identify the complex shear transfer mechanisms of reinforced concrete (RC) beam members. This study employed 1224 shear test specimens to train decision tree-based machine learning (ML) programs, by which strong correlations between shear capacity of RC beams and key input parameters were affirmed. In addition, shear contributions of concrete and shear reinforcement (the so-called V_c and V_s) were identified by establishing three independent ML models trained under different strategies with various combinations of datasets. Detailed parametric studies were then conducted by utilizing the well-trained ML models. It appeared that the presence of shear reinforcement can make the predicted shear contribution from concrete in RC beams larger than the pure shear contribution of concrete due to the intervention effect between shear reinforcement and concrete. On the other hand, the size effect also brought a significant impact on the shear contribution of concrete (V_c), whereas, the addition of shear reinforcements can effectively mitigate the size effect. It was also found that concrete tends to be the primary source of shear resistance when shear span-depth ratio a/d<1.0 while shear reinforcements become the primary source of shear resistance when a/d>2.0.

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.13-18
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• 2013

Panorama picturing is an elongated photographing technique that connects images with rotating and moving multiple images horizontally that are partly overlapped. However, for hand-operated photographs, it is difficult to adjust overlapped parts because of tilted angles. There has been a study comparing adjacent pictures using labeling technique but it was time-consuming and had angle dissonant cases in nature. In this paper, we propose a less time-consuming paranoiac scene reconstruction method. Our method is also based on labeling-and-comparing technique but uses only 1/3 of it. Then, if there exists angle dissonance, it tries to find characteristic points by SURF algorithm and adjusts them with homography. The efficacy of this method is experimentally verified by experiments using various images

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.3-11
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• 2016

Sixty four percent of Korean territory consists of forest which is fragile for forest fire. However, it is difficult to detect the disaster-induced damages due to topographic complexity in mountainous areas and harsh weather conditions. For this reason, satellite imaging systems have been widely utilized to detect the damage caused by forest fire. In particular, ground vegetation condition can be estimated from multi-spectral satellite images and change detection technique has been used to detect forest fire damages. However, since Korea has clear four seasons, simple change detection technique has limitation. In this regard, this study applied the NDVI(normalized difference vegetation index) annual cycle modeling technique on time-series of Landsat images from 1991 to 2007 to analyze influence of forest fire of Yangyang-gun, Gangwon-do in 2005 on vegetation condition. The encouraging result was obtained when comparing the areas where forest fire occurs with non-damaged areas. The mean value of NDVI was decreased by 0.07 before and after the forest fire. On the other hand, annual variability of NDVI had been increasing and peak value of NDVI was stationary after the forest fire. It is interpreted that understory vegetation was seriously damaged from the forest fire occurred in 2005.