• 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.

• Journal of Educational Research in Mathematics
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• v.15 no.3
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• pp.251-272
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• 2005

Given that cognitive demands of mathematical tasks can be changed during instruction, this study attempts to provide a detailed description to explore how tasks are set up and implemented in the classroom and what are the classroom-based factors. As an exploratory and qualitative case study, 4 of six-grade classrooms where high-level tasks on ratio and proportion were used were videotaped and analyzed with regard to the patterns emerged during the task setup and implementation. With regard to 16 tasks, four kinds of Patterns emerged: (a) maintenance of high-level cognitive demands (7 tasks), (b) decline into the procedure without connection to the meaning (1 task), (c) decline into unsystematic exploration (2 tasks), and (d) decline into not-sufficient exploration (6 tasks), which means that the only partial meaning of a given task is addressed. The 4th pattern is particularly significant, mainly because previous studies have not identified. Contributing factors to this pattern include private-learning without reasonable explanation, well-performed model presented at the beginning of a lesson, and mathematical concepts which are not clear in the textbook. On the one hand, factors associated with the maintenance of high-level cognitive demands include Improvising a task based on students' for knowledge, scaffolding of students' thinking, encouraging students to justify and explain their reasoning, using group-activity appropriately, and rethinking the solution processes. On the other hand, factors associated with the decline of high-level cognitive demands include too much or too little time, inappropriateness of a task for given students, little interest in high-level thinking process, and emphasis on the correct answer in place of its meaning. These factors may urge teachers to be sensitive of what should be focused during their teaching practices to keep the high-level cognitive demands. To emphasize, cognitive demands are fixed neither by the task nor by the teacher. So, we need to study them in the process of teaching and learning.

• 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.

• Journal of Korea Port Economic Association
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• v.31 no.2
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• pp.41-53
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• 2015

In Paracomon Inc. v. Telus Communication, Realice's anchor became entangled with a working fiber-optic submarine cable during its voyage and are presentative of the shipowner(the captain) cut the cable. The owner of the cable brought a claim for the repair cost against the shipowner. The shipowner then advanced a third party claim against a liability insurance underwriter. The Supreme Court of Canada (SCC) held that the shipowner was entitled to limit its liability under the 1976 Convention on the Limitation of Liability for Maritime Claims. The SCC also ruled that even though the misdeed of the shipowner was insufficient to break its right to limitation of liability, its wrongdoing constituted willful misconduct under the 1993 Canada Marine Insurance Act, allowing the underwriter to deny coverage for the incident. Thecasewasthefirsttoaddresstheinterrelationship between the shipowner's right to limit liability under the international convention regime and the availability of liability insurance with respect to such limited liability. This study analyzes the reasoning behind the SCC's judgment and evaluates the appropriateness of this court's decision based on the current maritime industry as well as prevailing maritime law. It concludes that the SCC's decision to declare that the shipowner retained the right to limit its liability is appropriate under the Limitation Convention (1976). However, its declaration that the liability insurer was discharged from liability is not correct in due consideration of the common recognition in the maritime industry, the intended purpose of a third party's right against the liability insurer, and the adoption process of the conduct barring limitation. Based on the SCC's decision, this study finally reviews the issue of the shipowner's right to limit and the coverage of the liability insurer in the Sewol case (2014).

• The Journal of Society for e-Business Studies
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• v.16 no.2
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• pp.1-18
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• 2011

Context-aware computing aims to enable the on-line applications and services to be executed in a timely and automated manner. Many of such applications and services involve group-level interactions. For more smoothing communication within a community, specific group-level issues such as group dynamics must be considered. To do so, obtaining group-level contexts such as the role, conflict resolution and norms, are key ingredients to improve group performance. Since group context is not the same as a simple summation of individual context, as group is not just a simple set of individuals, awaring individual context is not sufficient for group-level communication support. However, context-aware computing research still has stressed more on individual context. This leads us to the motivation of searching for group context aware method. Hence, the of this paper is to propose a novel methodology which automatically recognizes group context. Especially, we focus on group conhesiveness in this paper just because group cohosiveness is one of the important variables to control the performance of group interaction. To verify the applicability of the proposed method, an empirical test has been conducted to compare the performance of the proposed methodology with that of conventional methods.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.1
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• pp.51-59
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• 1999

In this paper we propose the technique for tracking players and a ball and for obtaining players' ground traces using image mosaic in general soccer sequences. Here, general soccer sequences mean the case that there is no extreme zoom-in or zoom-out of TV camera. Obtaining player's ground traces requires that the following three main problems be solved. There main problems: (1) ground field extraction (2) player and ball tracking and team indentification (3) player positioning. The region of ground field is extracted on the basis of color information. Players are tracked by template matching and Kalman filtering. Occlusion reasoning between overlapped players in done by color histogram back-projection. To find the location of a player, a ground model is constructed and transformation between the input images and the field model is computed using four or more feature points. But, when feature points extracted are insufficient, image-based mosaic technique is applied. By this image-to-model transformation, the traces of players on the ground model can be determined. We tested our method on real TV soccer sequence and the experimental results are given.

• 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.

• The Journal of Internal Korean Medicine
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• v.31 no.4
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• pp.792-812
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• 2010

In the 18th century, Xu Lingtai (徐靈胎) and Yoshimasu Todo (吉益東洞) were famous doctors advocating ancient medicine, though they lived in different countries, China and Japan. We compared their major books, analyzed their academic thoughts and then took conclusions as below. 1. The first, for instance "Classified Prescriptions of Treatise on Cold Damage Diseases, 傷寒論類方" and "Classified Assemblage of Prescriptions, 類聚方". Based on essential thought that a prescription and a syndrome should correspond, these books arranged and classified the Zhang Zhongjing (張仲景)'s texts."Classified Prescriptions of Treatise on Cold Damage Diseases", based on the thought that principles, methods, formulas and medicinals (理法方藥) were integrated in prescriptions, tried to find out the implicit treatment rules in prescriptions and syndromes through analyzing "Treatise on Cold Damage Diseases, 傷寒論". On the other hand, because Classified Assemblage of Prescriptions focused on the syndromes of ancient prescriptions (古方), it classified and collected the related texts of Treatise on Cold Damage Diseases and "Synopsis of Prescriptions of the Golden Chamber, 금궤요략", and then suggested only simple instructions on how to prescribe medicine. So in this book, the trend of experience was clear. 2. The second, there is "100 Kinds Records from Shennong's Classic of Materia Medica, 神農本草經百種錄" and "Description work of herbal pharmacology comprised of excerpts from Shanhanlun and medical experiences, 藥徵". Though both of these books are professional oriental pharmacology publications that advocate reactionism, there were remarkable differences in writing style between them. "Description work of herbal pharmacology comprised of excerpts from Shanhanlun and medical experiences" was based on "Treat on Cold Damage Diseases" and "Synopsis of Prescriptions of the Golden Chamber", just explained the effects of medications and discussed 'matter of course (所當然)', but not discussed 'the reason why (所以然)'. In explaining style of syndromes, it confirmed through research, and emphasized the inductive method. On the other hand, "100 Kinds Records from Shennong's Classic of Materia Medica based on "Shennong's Classic of Materia Medica, 神農本草經", explained the nature of medications and discussed 'the reason why (所以然)'. In explaining style of syndromes, it annotated and explained, and emphasized the process of reasoning. 3. The third, there is "Discuss the Headwaters of Medicine, 醫學源流論" and Severance of Medical evils, 醫斷". Aiming the then medical theories fallen in confused state, these books brought order out of chaos, clarified the categories of medical research, and emphasized the scientific method that could put theories into practice and verify them. The difference is that "Severance of Medical Evils" researched only macroscopic viewable clinical phenomena, and even denied the existence of names of diseases and etiological causes. Thus, it emphasized the accumulation of experiences, laid emphasis on "watching and realizing (目認)", and "understand and taking in (解悟)". Discuss the Headwaters of Medicine extremely emphasized the research of 'something not occuring (未然)', that is to say, induced notions of a disease from observing clinical phenomena, furthermore based on these, predicted the 'something not occuring (未然)' and emphasized researching 'the reason why (所以然)'. As regards how they deal with the traditional theories and post-Zhang Zhongjing's medicines, "Severance of Medical evils" took completely denying attitudes. In case of "Discuss the Headwaters of Medicine", it could be used reasonably through specific situation and detailed analysis. Collectively speaking, there were some differences between medical theories of Xu Lingtai and Yoshimasu Todo. Actually, these differences were whether he tried to research the essence of disease, whether he tried to consider it rationally, and how he treated various opinions occurring in the theories of traditional medicine and clinical experience.

• 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.