• Korean Journal of Cognitive Science
• /
• v.21 no.1
• /
• pp.47-75
• /
• 2010

Two experiments were conducted to explore whether the Or structure works as a default causal model in inferring the causal structure from the contingency data. The contingencies of three unfamiliar variables were used in Experiment 1. Participants inferred the Or structure quite well from the OR data, but incorrectly inferred the Or structure from the And data for about a little less than half of the time, and almost always inferred the Or structure from the chain data. The results suggested that the Or interpretation can be the default causal model. The prevalence of the Or interpretation from the contingency data was reported even when the three variables were familiar ones in Experiment 2. Multinomial modeling performed on the results of the two experiments strongly suggested that the Or interpretation work as a default causal model.

• Journal of the Korean Home Economics Association
• /
• v.44 no.11
• /
• pp.35-42
• /
• 2006

A criticism model for dress was developed to offer a methodological insight into research on aesthetics of dress. Concepts from Edmund B. Feldman's art criticism model, James D. Carney's style-relative model of art criticism, and Sung Bok Kim's fashion criticism model were borrowed and integrated to create a criticism model for dress, comprising identification of styles, descriptive features, aesthetic value features, external interpretation, socio-cultural interpretation, and evaluation. Both inductive and deductive approaches for the identification of styles can be made in the process of dress criticism. In the former case, descriptive features and aesthetic features are sequentially identified to locate the styles of dress. In the latter case, styles are identified first, and descriptive features and aesthetic features are identified accordingly. Logical criticisms can be made based on the critics' background knowledge of the history of dress and art.

• Journal of Ocean Engineering and Technology
• /
• v.2 no.2
• /
• pp.51-60
• /
• 1988

A data transform is performed by using a point-electrode focusing method in order to obtain accurate and objective interpretation of the borehole normal resistivity data. Two new synthetic curves can be generated through the data transform. The one is an approximate apparent resistivity curve, which would be used to predict the true resistivity of the formation. The other one is a bed boundary coefficient curve, which would be used to distinguish bed boundaries. The accuracy of the normal data interpretation can be improved and this method takes much less computational time than a linear inversion technique. Moreover, this method does not require an initial guess model and limitation of number of unknown parameters. Since this algorithm can be run on a personal computer, an immediate interpretation would be possible at the field work site. If an additional set of electrodes(a=125cm)is attached to a normal resistivity tool which is being used (a=25cm, 50cm, 100cm), the apparent resistivity for the point-electrode focusing device can be calculated, and it would maximize the use of short and long normal resistivity data and promote the accuracy of the interpretation.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.2
• /
• pp.198-205
• /
• 2011

GPS, ARPA, AIS, NAVTEX, VHF as modern aids-to-navigation equipments improve the safe navigation and help to reach a reduction in marine accidents by providing images, numeric values, texts, audio-based information for mates, However, we also noticed that it's complicate and difficult for a mate to acquire and analyze such information from these devices while he should devote himself to bridge watchkeeping especially in the urgent situation. Language is another way to get information and free the eyes and hands, so, to solve the problem above, we are trying to propose a new aids-to-navigation system, which can understand and merge multimedia marine safety information, analyze the situation and provide the necessary information in language. In this paper, we try to suggest a meaning interpretation model for supporting linguistic navigation safety information.

• Asian Journal of Business Environment
• /
• v.4 no.4
• /
• pp.5-11
• /
• 2014

Purpose - The paper aims to study strategic enterprise resource initiative formation processes. It analyzes the process of managing the strategic resource initiative and discusses its implementation mechanism. A research model for enterprises' strategic development is proposed, which suggests a geometric interpretation for estimating a company's long-term development. Research design, data, and methodology - The analysis employs theoretical studies of modern researchers. The main models used to determine the optimal alternative business strategy are graphic interpretation and mathematical modeling. Results - The hypotheses testing demonstrates the definition of a company's strategic resource initiative and explains the-mechanism or design of its formation. The study presents a geometric prism-refraction model of practice using a strategic resource initiative. Conclusions - An enterprise's strategy could return to its initial state in case of its unexpected deviation as a result of passing through the nodal points. The proposed model allows us to evaluate business performance, its surrounding environment, and the resource management strategy, to determine the necessary scope of strategy changes necessary to bring it back to the original state.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1996.11a
• /
• pp.851-856
• /
• 1996

In this paper, we introduce the design method using CAE(Computer Aided Engineering) which is profitable in the compatability and standardization of the developed product, and the reduction of construction time and price to develop and design a machine equipment. Particularly, we select the standard model to design or develop from the large machinery to the super precision one, extract the peculiar characters of the model by the close analysis of the physical and technical part, the experiment for the characteristics of objective dimensions by analogical mathematical analysis for previous results, and can induce the design model demanded by user investigating optimal data in the design previous We present the analogical algorithms and process method of design factors and restriction factors in the systematization design with computer. Then we analyze step functions for each systematization equipment and induce the process of technical data with actuator model.

• Journal of Environmental Science International
• /
• v.12 no.9
• /
• pp.949-955
• /
• 2003

The subject basin of the research was the basin of Yeongcheon Dam located in the upper reaches of the Kumho River. The parameters of the model were derived from the results of abstracting topological properties out of rainfall-runoff observation data about heavy rains and Digital Elevation Modeling(DEM) materials. This research aimed at suggesting the applicability of the CELLMOD Model, a distribution-type model, in interpreting runoff based on the topological properties of a river basin, by carrying out runoff interpretation far heavy rains using the model. To examine the applicability of the model, the calculated peaking characteristics in the hydrograph was analyzed in comparison with observed values and interpretation results by the Clark Model. According to the result of analysis using the CELLMOD Model proposed in the present research for interpreting the rainfall-runoff process, the model reduced the physical uncertainty in the rainfall-runoff process, and consequently, generated improved results in forecasting river runoff. Therefore it was concluded that the algorithm is appropriate for interpreting rainfall-runoff in river basins. However, to enhance accuracy in interpreting rainfall-runoff it is necessary to supplement heavy rain patterns in subject basins and to subdivide a basin into minor basins for analysis. In addition, it is necessary to apply the model to basins that have sufficient observation data, and to identify the correlation between model parameters and the basin characteristics(channel characteristics).

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.3
• /
• pp.411-425
• /
• 2023

Today, AI (Artificial Intelligence) technology is widely used in various fields, performing classification and regression tasks according to the purpose of use, and research is also actively progressing. Especially in the field of security, unexpected threats need to be detected, and unsupervised learning-based anomaly detection techniques that can detect threats without adding known threat information to the model training process are promising methods. However, most of the preceding studies that provide interpretability for AI judgments are designed for supervised learning, so it is difficult to apply them to unsupervised learning models with fundamentally different learning methods. In addition, previously researched vision-centered AI mechanism interpretation studies are not suitable for application to the security field that is not expressed in images. Therefore, In this paper, we use a technique that provides interpretability for detected anomalies by searching for and comparing optimization references, which are the source of intrusion attacks. In this paper, based on reference, we propose additional logic to search for data closest to real data. Based on real data, it aims to provide a more intuitive interpretation of anomalies and to promote effective use of an anomaly detection model in the security field.

• International journal of advanced smart convergence
• /
• v.12 no.1
• /
• pp.53-58
• /
• 2023

With the fast development of artificial intelligence day by day, users are demanding explanations about the results of algorithms and want to know what parameters influence the results. In this paper, we propose a model for bankruptcy prediction with interpretability using the SHAP framework. SHAP (SHAPley Additive exPlanations) is framework that gives a visualized result that can be used for explanation and interpretation of machine learning models. As a result, we can describe which features are important for the result of our deep learning model. SHAP framework Force plot result gives us top features which are mainly reflecting overall model score. Even though Fully Connected Neural Networks are a "black box" model, Shapley values help us to alleviate the "black box" problem. FCNNs perform well with complex dataset with more than 60 financial ratios. Combined with SHAP framework, we create an effective model with understandable interpretation. Bankruptcy is a rare event, then we avoid imbalanced dataset problem with the help of SMOTE. SMOTE is one of the oversampling technique that resulting synthetic samples are generated for the minority class. It uses K-nearest neighbors algorithm for line connecting method in order to producing examples. We expect our model results assist financial analysts who are interested in forecasting bankruptcy prediction of companies in detail.

• Proceedings of the Korean Society for Language and Information Conference
• /
• 1996.02a
• /
• pp.347-356
• /
• 1996