• Journal of Korean Medicine for Obesity Research
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• v.18 no.2
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• pp.144-151
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• 2018

Objectives: The purpose of this study is to evaluate the quality of case reports of the Journal of Korean Medicine for Obesity Research by the Case Report (CARE) guidelines. Methods: Case reports published in the Journal of Korean Medicine for Obesity Research from January 2013 to July 2018 were searched from Oriental Medicine Advanced Searching Integrated System (OASIS). We assessed the quality of reporting based on CARE guidelines. Results: A total of 8 case reports were finally included for the assessment. There was a deviation in the sub-item reporting rate by a maximum 75% and a minimum 57.14% in case reports. The 10 sub-items mentioned below, such as 'Timeline', 'Diagnostic challenges', 'Diagnostic reasoning including other diagnoses considered', 'Prognostic characteristics', 'Changes in intervention', 'Important follow-up diagnostic evaluations and other test results', 'Intervention adherence and tolerability', 'Adverse and unanticipated events', 'Patient perspective' and 'Informed consent' were reported below 30%. Conclusions: Efforts to diversify the subject of the case study and to apply appropriate reporting guidelines are needed to improve the quality of the case report contributed to the Journal of Korean Medicine for Obesity Research.

• Structural Engineering and Mechanics
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• v.43 no.3
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• pp.371-394
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• 2012

Accurate finite element (FE) models are needed in many applications of Civil Engineering such as health monitoring, damage detection, structural control, structural evaluation and assessment. Model accuracy depends on both the model structure (the form of the equations) and the model parameters (the coefficients of the equations), and can be generally improved through that process of experimental reconciliation known as model updating. However, modelling errors, including (i) errors in the model structure and (ii) errors in parameters excluded from adjustment, may bias the solution, leading to an updated model which replicates measurements but lacks physical meaning. In this paper, an application of ambient-vibration-based model updating to a large-scale benchmark prototype of a building structure is reported in which both types of error are met. The error in the model structure, originating from unmodelled secondary structural elements unexpectedly working as resonant appendages, is faced through a reduction of the experimental modal model. The error in the model parameters, due to the inevitable constraints imposed on parameters to avoid ill-conditioning and under-determinacy, is faced through a multi-model parameterization approach consisting in the generation and solution of a multitude of models, each characterized by a different set of updating parameters. Results show that modelling errors may significantly impair updating even in the case of seemingly simple systems and that multi-model reasoning, supported by physical insight, may effectively improve the accuracy and robustness of calibration.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.175-180
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• 2006

Total conceptual cost estimates and the assessment of the reliability of these estimates are critical in the early stages of a building construction project. The purpose of this study is to propose the method to clients or estimators for improving the reliability of conceptual cost estimates by evaluating the reliability of conceptual cost estimates. The data from 83 building construction projects were collected for this study. The results showed that the proposed method can propose alternatives to clients or estimators for improving the reliability of conceptual cost estimates with the process of evaluation, review and feedback. This process can assist clients in their evaluation of the reliability of the estimated cost and the probability of exceeding the target cost, and in their re-estimation after dealing with the elements that influence the conceptual cost estimate badly.

• The Journal of Korean Academy of Sensory Integration
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• v.6 no.1
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• pp.47-62
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• 2008

Introduction : Sensory Integration(SI) theory, science it is developed by an occupational therapist A. Jean Ayres, is the one of the most popular frames of reference used in occupational therapy(OT) intervention. It has been proved as a scientific theory especially in neuroscience discipline through abundant research and practice. Occupational therapists apply the SI therapy with strong clinical reasoning to improve adaptive behaviors of their clients and try to link the adaptive behaviors with occupational performance in the clients' everyday life. One of the manners regarding clinical reasoning is Top-down approach. In occupational therapy discipline, Top-down approach is well-reflected within two evaluation tools; Canadian Occupational Performance Measure(COPM) and Assessment of Motor and Process Skills(AMPS) and two models of practice; Canadian Model of Occupational Performance(CMOP) and Occupational therapy intervention process model(OTIPM). Objective : The purpose of this paper demonstrates how SI therapy can be employed within OTIPM and how the OT process (evaluation-intervention-outcome) can be structuralized based on the Top-down approach. This single-case study recognizes the impact of a SI therapy for a male adolescent on his occupational performance. Intervention Examined : "P" was 16 years old male adolescent with no diagnosis and junior of the high school when he was referred. P was always with mouth opened, showed difficulties in gathering things need to be prepared and managing and paying money for shopping, and his colleges dislike getting close to him because he can't was his body well. AMPS was administrated in initial evaluation and reevaluation of P's occupation performance, Bruininks-Oserestky Test of Motor Proficiency-2(BOT-2) was carried out to assess motor functions and perception skills related in sensory integration, and occupational therapist performed clinical observation in order to complement the evaluation quantitatively and quantitatively. Based on the evaluation, it is concluded that the SI therapy is primary means to improve P's occupational performance, and three therapeutic approaches were constructed; restorative, acquired and compensatory approach. P showed improved motor and process skills in occupational performance after undergone the occupational therapy. Conclusions : The sensory integration therapy was practical enough to build the bridge between the occupational performance(Top) and the underlying component problems (Bottom). The OTIPM was helpful to identify meaningful occupation for P and P's family within P's contexts, and the AMPS was valuable to analyze and clarify the cause of difficulties in the chosen occupational performance.

• The Journal of Korean Academy of Sensory Integration
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• v.9 no.2
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• pp.1-13
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• 2011

Objective : Purpose of this study is to discuss benefits and implications of the clinical reasoning process and re-evaluation in the OTIPM by introducing a single case that occupational therapy intervention is provided based on the OTIPM. Methods : The case subject is a boy aged 5 years and 10 month who had diagnosed as attachment disorder and anxiety disorder from a pediatric psychiatrist before. The boy is referred to sensory integration therapy clinic and underwent occupational therapy intervention service twice a week for four month. Therapeutic activities for the intervention were consisted of sensory integration activities for restorative model, care-giver education for educational model, and performance skill training for acquisitional model. Measurements used in the initial evaluation are JSI-R, DDST-2, Social Maturity Test, KPPS-R, and observation-based performance task analysis. For the performance task analysis, performance skill items were constructed based on the Occupational Therapy Process Framework (OTPF), and those were assessed by the evaluation system of Assessment of Motor and Process Skill (AMPS) and Evaluation of Social Participation (ESI). Results : The detail process of implementing of the OTIPM in this study is reported by following four phases; 1) establish client-centered performance context; 2) establish baseline and interpret cause (initial evaluation); 3) intervention planning and implementing; and 4) recognize intervention outcome (reevaluation). Conclusion : In this case, occupational therapist could provide the client an occupation-based intervention within comprehensive performance context based on the OTIPM. Therapist could clearly identify the cause of problematic performance skills and behaviors and so provide effective intervention to improve client's occupational performance. Additionally, it was found that client's satisfaction of the intervention can be raised when the concept of 'who is the client' is expanded based on the OTIPM. From this study, it is proposed that OTIPM may be a model educible 'comprehensive' enhancement of 'specific' occupational engagement, as it considers both improvement of occupational performance and satisfaction.

• Journal of Korean Medicine Rehabilitation
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• v.29 no.3
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• pp.75-85
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• 2019

Objectives This study was perfomed to assess the adherance to CARE (CAse REport) guideline of case reports in the Journal of Korean Medicine Rehabilitation Methods We searched the case reports published in the Journal of Korean Medicine Rehabilitation from January 2016 to April 2019 in the database of oriental medicine advanced searching integrated system (OASIS). Then we evaluated the quality of the searched case reports based on the CARE guideline. Results Totally 31 papers were selected after the screening the case reports by the inclusion and exclusion criteria. The report rate of the sub-items of the CARE guideline was 78.26% at the maximum, 60.87% at the maximum, and 70.97% on the average. The following items were reported only in less than 50% of them; 'Timeline', 'Diagnostic challenges', 'Diagnostic reasoning including other diagnoses considered' 'Prognostic characteristics', 'Follow-up and Outcomes', 'Patient Perspective', 'Informed Consent' Conclusions This study is expected to contribute to the overall improvement of the level of case reports in the Journal of Korean Medicine Rehabilitation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.2
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• pp.21-30
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• 2000

If there exists a model that calculates the proper candidate position whenever the game of Go is in progress, it can be used for setting up the prototype of the candidate generation algorithm without using case-based reasoning. In this paper, we analyze Go through combinatorial game theory and on the basis of probability matrix (PM) showing the difference of the territory of the black and the white. We design and implement a candidate generation system(CGS) to find the candidates at a situation in Go. CGS designed in this paper can compute Influence power, safety, probability value(PV), and PM and then generate candidate positions for a present scene, once a stone is played at a scene. The basic strategy generates five candidates for the Present scene, and then chooses one with the highest PV. CGS generates the candidate which emphasizes more defence tactics than attack ones. In the opening game of computer Go, we can know that CGS which has no pattern is somewhat superior to NEMESIS which has the Joseki pattern.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.28-34
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• 2021

In the case of object detection using deep learning, both accuracy and real-time are required. However, it is difficult to use a deep learning model that processes a large amount of data in a limited resource environment. To solve this problem, this paper proposes an object detection model for small embedded devices. Unlike the general detection model, the model size was minimized by using a structure in which the pre-trained feature extractor was removed. The structure of the model was designed by repeatedly stacking lightweight convolution blocks. In addition, the number of region proposals is greatly reduced to reduce detection overhead. The proposed model was trained and evaluated using the public dataset PASCAL VOC. For quantitative evaluation of the model, detection performance was measured with average precision used in the detection field. And the detection speed was measured in a Raspberry Pi similar to an actual embedded device. Through the experiment, we achieved improved accuracy and faster reasoning speed compared to the existing detection method.

• Journal of the Korean earth science society
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• v.41 no.2
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• pp.194-207
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• 2020

The purpose of this study is to identify the types and characteristics of elementary school pre-service teachers revealed in the process of resolving the change of lunar phases, which emphasizes the context of actual observation, and to provide suggestions for areas to be considered in the elementary school teacher training program. To this end, we analyzed the 30 pre-service teachers' explaining the observable lunar phases, and the main research results are as follows. First, the phase change of the moon was often explained by introducing the timetable for each phase of the moon rather than based on observation of the phenomenon and scientific reasoning. Second, an alternative concept of the type that the moon is invisible when the sun rises or that the moon can always be observed has been identified. Third, there was a case of explaining that the time and orientation for observing the moon can be observed regardless of the position of the sun or when observing the sun. Also, the date of observing the moon was assumed to be approached by assuming the lunar calendar. Based on the above results, pedagogical implications were discussed.