• 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.

• Smart Media Journal
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• v.12 no.1
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• pp.9-16
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• 2023

Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.23-33
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• 2016

The current smart lighting is shaped to offer the lighting environment suitable for current context, after identifying user's action and location through a sensor. The sensor-based context awareness technology just considers a single user, and the studies to interpret many users' various context occurrences and conflicts lack. In existing studies, a fuzzy theory and algorithm including ReBa have been used as the methodology to solve context conflict. The fuzzy theory and algorithm including ReBa just avoid an opportunity of context conflict that may occur by providing services by each area, after the spaces where users are located are classified into many areas. Therefore, they actually cannot be regarded as customized service type that can offer personal preference-based context conflict. This paper proposes a priority-based LED lighting control system interpreting multiple context conflicts, which decides services, based on the granted priority according to context type, when service conflict is faced with, due to simultaneous occurrence of various contexts to many users. This study classifies the residential environment into such five areas as living room, 'bed room, study room, kitchen and bath room, and the contexts that may occur within each area are defined as 20 contexts such as exercising, doing makeup, reading, dining and entering, targeting several users. The proposed system defines various contexts of users using an ontology-based model and gives service of user oriented lighting environment through rule based on standard and context reasoning engine. To solve the issue of various context conflicts among users in the same space and at the same time point, the context in which user concentration is required is set in the highest priority. Also, visual comfort is offered as the best alternative priority in the case of the same priority. In this manner, they are utilized as the criteria for service selection upon conflict occurrence.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.37-52
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• 2011

Supply chain management is a strategic thinking which enhances the value of supply chain and adapts more promptly for the changing environment. For the seamless partnership and value creation in supply chains, information and knowledge sharing and proper partner selection criteria must be applied. Thus, the partner selection criteria are critical to maintain product quality and reliability. Each part of a product is supplied by an appropriate supply partner. The criteria for selecting partners are technological capability, quality, price, consistency, etc. In reality, the criteria for partner selection may change according to the characteristics of the components. When the part is a core component, quality factor is the top priority compared to the price. For a standardized component, lower price has a higher priority. Sometimes, unexpected case occurs such as emergency order in which the preference may shift on the top. Thus, SCM partner selection criteria must be determined dynamically according to the characteristics of part and its context. The purpose of this research is to develop an OWL model for the supply chain partnership depending on its context and characteristics of the parts. The uncertainty of variable is tackled through fuzzy logic. The parts with preference of numerical value and context are represented using OWL. Part preference is converted into fuzzy membership function using fuzzy logic. For the ontology reasoning, SWRL (Semantic Web Rule Language) is applied. For the implementation of proposed model, starter motor of an automobile is adopted. After the fuzzy ontology is constructed, the process of selecting preference-based supply partner for each part is presented.

• KDI Journal of Economic Policy
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• v.12 no.3
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• pp.71-94
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• 1990

This paper reviews the rationale of monetary and banking intervention by an outside authority, either the government or the central bank, and seeks to delineate clearly the optimal limits to the monetary and banking deregulation currently underway in Korea as well as on a global scale. Furthermore, this paper seeks to establish an objective and balanced view on the role of the central bank, especially in light of the current discussion on the restructuring of Korea's central bank, which has been severely contaminated by interest-group politics. The discussion begins with the recognition that the modern free banking school and the new monetary economics are becoming formidable challenges to the traditional role of the government or the central bank in the monetary and banking sector. The paper reviews six arguments that have traditionally been presented to support intervention: (1) the possibility of an over-issue of bank notes under free banking instead of central banking; (2) externalities in and the public good nature of the use of money; (3) economies of scale and natural monopoly in producing money; (4) the need for macro stabilization policy due to the instability of the real sector; (5) the external effects of bank failure due to the inherent instability of the existing banking system; and (6) protection for small banknote users and depositors. Based on an analysis of the above arguments, the paper speculates on the optimal role of the government or central bank in the monetary and banking system and the optimal degree of monetary and banking deregulation. By contrast to the arguments for free banking or laissez-faire monetary systems, which become fashionable in recent years, monopoly and intervention by the government or central bank in the outside money system can be both necessary and optimal. In this case, of course, an over-issue of fiat money may be possible due to political considerations, but this issue is beyond the scope of this paper. On the other hand, the issue of inside monies based on outside money could indeed be provided for optimally under market competition by private institutions. A competitive system in issuing inside monies would help realize, to the maxim urn extent possible, external economies generated by using a single outside money. According to this reasoning, free banking activities will prevail in the inside money system, while a government monopoly will prevail in the outside money system. This speculation, then, also implies that the monetary and banking deregulation currently underway should and most likely will be limited to the inside money system, which could be liberalized to the fullest degree. It is also implied that it will be impractical to deregulate the outside money system and to allow market competition to provide outside money, in accordance with the arguments of the free banking school and the new monetary economics. Furthermore, the role of the government or central bank in this new environment will not be significantly different from their current roles. As far as the supply of fiat money continues to be monopolized by the government, the control of the supply of base money and such related responsibilities as monetary policy (argument(4)) and the lender of the last resort (argument (5)) will naturally be assigned to the outside money supplier. However, a mechanism for controlling an over-issue of fiat money by a monopolistic supplier will definitely be called for (argument(1)). A monetary policy based on a certain policy rule could be one possibility. More importantly, the deregulation of the inside money system would further increase the systemic risk inherent in the current fractional banking system, while enhancing the efficiency of the system (argument (5)). In this context, the role of the lender of the last resort would again become an instrument of paramount importance in alleviating liquidity crises in the early stages, thereby disallowing the possibility of a widespread bank run. Similarly, prudential banking supervision would also help maintain the safety and soundness of the fully deregulated banking system. These functions would also help protect depositors from losses due to bank failures (argument (6)). Finally, these speculations suggest that government or central bank authorities have probably been too conservative on the issue of the deregulation of the financial system, beyond the caution necessary to preserve system safety. Rather, only the fullest deregulation of the inside money system seems to guarantee the maximum enjoyment of external economies in the single outside money system.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.69-85
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• 2016

Successful relationship with loving partners is one of the most important factors in life. In psychology, there have been some previous researches studying the factors influencing romantic relationships. However, most of these researches were performed based on statistical analysis; thus they have limitations in analyzing complex non-linear relationships or rules based reasoning. This research analyzes commitment and persistence in heterosexual involvement according to styles of loving using a datamining technique as well as statistical methods. In this research, we consider six different styles of loving - 'eros', 'ludus', 'stroge', 'pragma', 'mania' and 'agape' which influence romantic relationships between lovers, besides the factors suggested by the previous researches. These six types of love are defined by Lee (1977) as follows: 'eros' is romantic, passionate love; 'ludus' is a game-playing or uncommitted love; 'storge' is a slow developing, friendship-based love; 'pragma' is a pragmatic, practical, mutually beneficial relationship; 'mania' is an obsessive or possessive love and, lastly, 'agape' is a gentle, caring, giving type of love, brotherly love, not concerned with the self. In order to do this research, data from 105 heterosexual couples were collected. Using the data, a linear regression method was first performed to find out the important factors associated with a commitment to partners. The result shows that 'satisfaction', 'eros' and 'agape' are significant factors associated with the commitment level for both male and female. Interestingly, in male cases, 'agape' has a greater effect on commitment than 'eros'. On the other hand, in female cases, 'eros' is a more significant factor than 'agape' to commitment. In addition to that, 'investment' of the male is also crucial factor for male commitment. Next, decision tree analysis was performed to find out the characteristics of high commitment couples and low commitment couples. In order to build decision tree models in this experiment, 'decision tree' operator in the datamining tool, Rapid Miner was used. The experimental result shows that males having a high satisfaction level in relationship show a high commitment level. However, even though a male may not have a high satisfaction level, if he has made a lot of financial or mental investment in relationship, and his partner shows him a certain amount of 'agape', then he also shows a high commitment level to the female. In the case of female, a women having a high 'eros' and 'satisfaction' level shows a high commitment level. Otherwise, even though a female may not have a high satisfaction level, if her partner shows a certain amount of 'mania' then the female also shows a high commitment level. Finally, this research built a prediction model to establish whether the relationship will persist or break up using a decision tree. The result shows that the most important factor influencing to the break up is a 'narcissistic tendency' of the male. In addition to that, 'satisfaction', 'investment' and 'mania' of both male and female also affect a break up. Interestingly, while the 'mania' level of a male works positively to maintain the relationship, that of a female has a negative influence. The contribution of this research is adopting a new technique of analysis using a datamining method for psychology. In addition, the results of this research can provide useful advice to couples for building a harmonious relationship with each other. This research has several limitations. First, the experimental data was sampled based on oversampling technique to balance the size of each classes. Thus, it has a limitation of evaluating performances of the predictive models objectively. Second, the result data, whether the relationship persists of not, was collected relatively in short periods - 6 months after the initial data collection. Lastly, most of the respondents of the survey is in their 20's. In order to get more general results, we would like to extend this research to general populations.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.139-157
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• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.

• Journal of Korean Home Economics Education Association
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• v.32 no.1
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• pp.107-125
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• 2020

The purpose of this study was to analyze the dietary life units of Korean and American high school home economics textbook according to Habermas's three systems of action and to find out how the three systems of action are reflected in the learning objectives and activity tasks of the textbook. To achieve this purpose, this study analyzed the learning objectives and activity tasks of the dietary life units in the textbooks of 'technology & home economics' and 'home economics science' in Korea, and 'succeeding in life and career' in America using a content analysis technique based on Habermas's three systems of action. In analyzing the content, each learning objective or activity was matched with one of the three systems of action by examining the context. In some cases, two or more systems of actions were integrated in one activity. This is a case where a series of learning tasks that involve different action system were grouped into one. The numbers of learning objectives and activities of the units of 'technology & home economics', 'home economics science' textbooks of Korean high schools and 'succeeding in life and career' dietary life of American high schools were 3, 26, and 248, respectively. In Korean textbooks, the percentage of communicative action was highest among the three systems, that is, 66.7% for 'technology & home economics' textbooks and 50% for 'home economics science' textbooks. In comparison technical action was the highest in American textbooks at 66.5%. Activities related to technical action included cooking, conducting research on health and food, or conducting experiments. The activities related to communicative action included role play related to health and table manners, or writing reports after conducting surveys or interviewing professionals. The activities related to emancipative action were to social participation activities such as service project in relation to health and food, or to find problems that occur in dietary life and think about be best solution through practical reasoning.