• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Journal of Ethics
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• no.97
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• pp.279-306
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• 2014

This study presents the leadership model that is to build of ethical and cultural leadership. This model is to operat the functions of a systemof leadership that based on the universal principles of life, that is performed bybalance and harmonized judgment of the ideal ethical oughtfulness and cultural values, and practise ethically through relationship, process, and skill of leadership. And this model turn out to lead a real impact and then overcome conflict, problem solving, motivation. To check the validity of leadership, this study analysis the case study of leadership of King Sejong. His leadership is based at heaven that on the basis of the universal principles of life. The ideal ethical oughtfulness is to cares for people and the value of the cultural is to cherish the people's will. His leadership is to be balance and harmonized judgment of the ideal ethical oughtfulness and the cultural values by practice of virtues through relationship, process, and skill of leadership. Leadership relationship is a equal role relationship that are the children of the sky, thus to be coexistence and harmonyin close collaboration. Leadership process is a process of transvaluation to ensure the validity of the values by rational discussion and persuasion. Leadership skills led to active obedience through leading by example and love of learning. King Sejong' leadership is the leadership that ethical and cultural leadership become well-implemented.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.6
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• pp.67-84
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• 2023

In some areas of the Republic of Korea, the designation and management of conservation areas do not adequately reflect regional characteristics and often impose behavioral regulations without considering the local context. One prominent example is the Busan EDC area. As a result, conflicts may arise, including large-scale civil complaints, regarding the conservation and utilization of these areas. Therefore, for the efficient designation and management of protected areas, it is necessary to consider various ecosystem factors, changes in land use, and regional characteristics. In this study, we specifically focused on the Busan EDC area and applied machine learning techniques to analyze the habitat of regional species. Additionally, we employed Explainable Artificial Intelligence techniques to interpret the results of our analysis. To analyze the regional characteristics of the waterfront area in the Busan EDC district and the habitat of migratory birds, we used bird observations as dependent variables, distinguishing between presence and absence. The independent variables were constructed using land cover, elevation, slope, bridges, and river depth data. We utilized the XGBoost (eXtreme Gradient Boosting) model, known for its excellent performance in various fields, to predict the habitat probabilities of 11 bird species. Furthermore, we employed the SHapley Additive exPlanations technique, one of the representative methodologies of XAI, to analyze the relative importance and impact of the variables used in the model. The analysis results showed that in the EDC business district, as one moves closer to the river from the waterfront, the likelihood of bird habitat increases based on the overlapping habitat probabilities of the analyzed bird species. By synthesizing the major variables influencing the habitat of each species, key variables such as rivers, rice fields, fields, pastures, inland wetlands, tidal flats, orchards, cultivated lands, cliffs & rocks, elevation, lakes, and deciduous forests were identified as areas that can serve as habitats, shelters, resting places, and feeding grounds for birds. On the other hand, artificial structures such as bridges, railways, and other public facilities were found to have a negative impact on bird habitat. The development of a management plan for conservation areas based on the objective analysis presented in this study is expected to be extensively utilized in the future. It will provide diverse evidential materials for establishing effective conservation area management strategies.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.71-88
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• 2017

Language models were originally developed for speech recognition and language processing. Using a set of example sentences, a language model predicts the next word or character based on sequential input data. N-gram models have been widely used but this model cannot model the correlation between the input units efficiently since it is a probabilistic model which are based on the frequency of each unit in the training set. Recently, as the deep learning algorithm has been developed, a recurrent neural network (RNN) model and a long short-term memory (LSTM) model have been widely used for the neural language model (Ahn, 2016; Kim et al., 2016; Lee et al., 2016). These models can reflect dependency between the objects that are entered sequentially into the model (Gers and Schmidhuber, 2001; Mikolov et al., 2010; Sundermeyer et al., 2012). In order to learning the neural language model, texts need to be decomposed into words or morphemes. Since, however, a training set of sentences includes a huge number of words or morphemes in general, the size of dictionary is very large and so it increases model complexity. In addition, word-level or morpheme-level models are able to generate vocabularies only which are contained in the training set. Furthermore, with highly morphological languages such as Turkish, Hungarian, Russian, Finnish or Korean, morpheme analyzers have more chance to cause errors in decomposition process (Lankinen et al., 2016). Therefore, this paper proposes a phoneme-level language model for Korean language based on LSTM models. A phoneme such as a vowel or a consonant is the smallest unit that comprises Korean texts. We construct the language model using three or four LSTM layers. Each model was trained using Stochastic Gradient Algorithm and more advanced optimization algorithms such as Adagrad, RMSprop, Adadelta, Adam, Adamax, and Nadam. Simulation study was done with Old Testament texts using a deep learning package Keras based the Theano. After pre-processing the texts, the dataset included 74 of unique characters including vowels, consonants, and punctuation marks. Then we constructed an input vector with 20 consecutive characters and an output with a following 21st character. Finally, total 1,023,411 sets of input-output vectors were included in the dataset and we divided them into training, validation, testsets with proportion 70:15:15. All the simulation were conducted on a system equipped with an Intel Xeon CPU (16 cores) and a NVIDIA GeForce GTX 1080 GPU. We compared the loss function evaluated for the validation set, the perplexity evaluated for the test set, and the time to be taken for training each model. As a result, all the optimization algorithms but the stochastic gradient algorithm showed similar validation loss and perplexity, which are clearly superior to those of the stochastic gradient algorithm. The stochastic gradient algorithm took the longest time to be trained for both 3- and 4-LSTM models. On average, the 4-LSTM layer model took 69% longer training time than the 3-LSTM layer model. However, the validation loss and perplexity were not improved significantly or became even worse for specific conditions. On the other hand, when comparing the automatically generated sentences, the 4-LSTM layer model tended to generate the sentences which are closer to the natural language than the 3-LSTM model. Although there were slight differences in the completeness of the generated sentences between the models, the sentence generation performance was quite satisfactory in any simulation conditions: they generated only legitimate Korean letters and the use of postposition and the conjugation of verbs were almost perfect in the sense of grammar. The results of this study are expected to be widely used for the processing of Korean language in the field of language processing and speech recognition, which are the basis of artificial intelligence systems.

• Asia Marketing Journal
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• v.7 no.3
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• pp.53-76
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• 2005

With rapid technological and market change, new product development (NPD) complexity is a significant issue that organizations continually face in their development projects. There are numerous factors, which cause development projects to become increasingly costly & complex. A product is more likely to be successfully developed and marketed when the complexity inherent in NPD projects is clearly understood and carefully managed. Based upon the previous studies, this study examines the nature and importance of complexity in developing new products and then identifies several issues in managing complexity. Issues considered include: definition of complexity : consequences of complexity; and methods for managing complexity in NPD projects. To achieve high performance in managing complexity in development projects, these issues need to be addressed, for example: A. Complexity inherent in NPD projects is multi-faceted and multidimensional. What factors need to be considered in defining and/or measuring complexity in a development project? For example, is it sufficient if complexity is defined only from a technological perspective, or is it more desirable to consider the entire array of complexity sources which NPD teams with different functions (e.g., marketing, R&D, manufacturing, etc.) face in the development process? Moreover, is it sufficient if complexity is measured only once during a development project, or is it more effective and useful to trace complexity changes over the entire development life cycle? B. Complexity inherent in a project can have negative as well as positive influences on NPD performance. Thus, which complexity impacts are usually considered negative and which are positive? Project complexity also can affect the entire organization. Any complexity could be better assessed in broader and longer perspective. What are some ways in which the long-term impact of complexity on an organization can be assessed and managed? C. Based upon previous studies, several approaches for managing complexity are derived. What are the weaknesses & strengths of each approach? Is there a desirable hierarchy or order among these approaches when more than one approach is used? Are there differences in the outcomes according to industry and product types (incremental or radical)? Answers to these and other questions can help organizations effectively manage the complexity inherent in most development projects. Complexity is worthy of additional attention from researchers and practitioners alike. Large-scale empirical investigations, jointly conducted by researchers and practitioners, will help gain useful insights into understanding and managing complexity. Those organizations that can accurately identify, assess, and manage the complexity inherent in projects are likely to gain important competitive advantages.

• Journal of The Korean Association For Science Education
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• v.16 no.4
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• pp.376-388
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• 1996

The first and the second "Discussion Contest of Scientific Investigation" was evaluated in this study. This contest was a part of 'Korean Youth Science Festival' held in 1993 and 1994. The evaluation was based on the data collected from the middle school students of final teams, their teachers, a large number of middle school students and college students who were audience of the final competition. Questionnaires, interviews, reports of final teams, and video tape of final competition were used to collect data. The study focussed on three research questions. The first was about the preparation and the research process of students of final teams. The second was about the format and the proceeding of the Contest. The third was whether participating the Contest was useful experience for the students and the teachers of the final teams. The first area, the preparation and the research process of students, were investigated in three aspects. One was the level of cooperation, participation, support and the role of teachers. The second was the information search and experiment, and the third was the report writing. The students of the final teams from both years, had positive opinion about the cooperation, students' active involvement, and support from family and school. Students considered their teachers to be a guide or a counsellor, showing their level of active participation. On the other hand, the interview of 1993 participants showed that there were times that teachers took strong leading role. Therefore one can conclude that students took active roles most of the time while the room for improvement still exists. To search the information they need during the period of the preparation, student visited various places such as libraries, bookstores, universities, and research institutes. Their search was not limited to reading the books, although the books were primary source of information. Students also learned how to organize the information they found and considered leaning of organizing skill useful and fun. Variety of experiments was an important part of preparation and students had positive opinion about it. Understanding related theory was considered most difficult and important, while designing and building proper equipments was considered difficult but not important. This reflects the students' school experience where the equipments were all set in advance and students were asked to confirm the theories presented in the previous class hours. About the reports recording the research process, students recognize the importance and the necessity of the report but had difficulty in writing it. Their reports showed tendency to list everything they did without clear connection to the problem to be solved. Most of the reports did not record the references and some of them confused report writing with story telling. Therefore most of them need training in writing the reports. It is also desirable to describe the process of student learning when theory or mathematics that are beyond the level of middle school curriculum were used because it is part of their investigation. The second area of evaluation was about the format and the proceeding of the Contest, the problems given to students, and the process of student discussion. The format of the Contests, which consisted of four parts, presentation, refutation, debate and review, received good evaluation from students because it made students think more and gave more difficult time but was meaningful and helped to remember longer time according to students. On the other hand, students said the time given to each part of the contest was too short. The problems given to students were short and open ended to stimulate students' imagination and to offer various possible routes to the solution. This type of problem was very unfamiliar and gave a lot of difficulty to students. Student had positive opinion about the research process they experienced but did not recognize the fact that such a process was possible because of the oneness of the task. The level of the problems was rated as too difficult by teachers and college students but as appropriate by the middle school students in audience and participating students. This suggests that it is possible for student to convert the problems to be challengeable and intellectually satisfactory appropriate for their level of understanding even when the problems were difficult for middle school students. During the process of student discussion, a few problems were observed. Some problems were related to the technics of the discussion, such as inappropriate behavior for the role he/she was taking, mismatching answers to the questions. Some problems were related to thinking. For example, students thinking was off balanced toward deductive reasoning, and reasoning based on experimental data was weak. The last area of evaluation was the effect of the Contest. It was measured through the change of the attitude toward science and science classes, and willingness to attend the next Contest. According to the result of the questionnaire, no meaningful change in attitude was observed. However, through the interview several students were observed to have significant positive change in attitude while no student with negative change was observed. Most of the students participated in Contest said they would participate again or recommend their friend to participate. Most of the teachers agreed that the Contest should continue and they would recommend their colleagues or students to participate. As described above, the "Discussion Contest of Scientific Investigation", which was developed and tried as a new science contest, had positive response from participating students and teachers, and the audience. Two among the list of results especially demonstrated that the goal of the Contest, "active and cooperative science learning experience", was reached. One is the fact that students recognized the experience of cooperation, discussion, information search, variety of experiments to be fun and valuable. The other is the fact that the students recognized the format of the contest consisting of presentation, refutation, discussion and review, required more thinking and was challenging, but was more meaningful. Despite a few problems such as, unfamiliarity with the technics of discussion, weakness in inductive and/or experiment based reasoning, and difficulty in report writing, The Contest demonstrated the possibility of new science learning environment and science contest by offering the chance to challenge open tasks by utilizing student science knowledge and ability to inquire and to discuss rationally and critically with other students.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• Journal of the Korean Chemical Society
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• v.43 no.5
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• pp.578-588
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• 1999

The purpose of this study is to develope the more effective chemistry teaching strategy through analyzing the demanded cognitive levels of contents in high school chemistry I textbooks and the cognitive levels of students who learn these textbooks. For this purpose, the levets of cognitive development stages of 821 second grade students of high schools in Seoul City were anaIyzed using the GALT short version test. The demanded cognitive levels of understanding the contents of chemistry I textbooks in high school were analyzed using the curriculum analysis taxonomy developed by CSMS (Concept in Secondaly Mathematics and Science) program of the Great Britain. The resuIts showed that the proportion of students in the concrete operational stage, the transition stage, and the formal operational stage was l0.7%, 43.0% and 46.3%, respectively. The demanded levels of textbook contents were mostly the early formal operational stages. The concepts demanded the level of the late formal operational stage were 'atomic and molecular weight', 'stoichiometry of chemical reaction', and 'periodic properties of elements'. The results will be helpful for teachers in knowing what concepts are difficult for students to understand and in planning strategies for teaching those concepts. To demonstrate the application of the results obtained in this study, an example of developing teaching strategy which includes the adjustment of cognitive level of contents was shown.

• Journal of National Security and Military Science
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• s.4
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• pp.289-350
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• 2006

The world has been rapidly restructured in an agenda of national security from center of military strength to that of economic strength since the post cold-war era China military leadership-division carried out RMA through learning of a lesson from Gulf war in 1990 -1991 and Iraq war in 2003, thus the leadership-division made an attempt to convert the military system to a technical intensive system. The principle based on RMA of China military is (National defense strategy) drafted by the central military committee 1985 and (Four modernization general principles) 1978. China has introduced Russian high-technological arms and equipment in order to build up the military arms greatly thanks to an economical development, and they take pragmatism line as chinese socialism with their strategy to make secure a position as military powers such as they successfully launched a manned spacecraft and are building an air-craft carrie and soon. USA has a theory of dichotomy whether a country is a cooperator for USA, or not. and also enemy or friend since 9.11terror, thus USA is different from their direction of police. This is because USA stands a position as the superpower of the supremacy hegemony of the world. We must be carefully aware that USA considers as important area for Middle east, West south Asia, Central Asia and Northwest Asia to meet the demands of 2lcentury. Accordingly, the focus of USA's military strategy will be probably concentrated at the above mentioned four areas. On the other hand, USA enjoys such a superpower position due to collapse of USSR which was the past main enemy since the post cold war era. We could give an conclusive example as fact that USA has recurred to unilateralism But USA carry on the military operations to the terror groups at global around by converting thje military strike strategy to pre-emptive strike strategy since9.11 terror, 2001. USA seeks for transformation to the mobile military forces with light-quantity oriented in order to carry on such the military operations and makes progress GPR, And the USA forces in Korea makes progress a military renovation as part of such a military strategy. On the other hand, USA promotes the measures of choose for the countries standing at the crossroads of strategy and carries forward a main scheme of provision for four priority aims that the leaders of a hostile country and mis-country shall be prohibited from use and obtainment of weapons of mass destruction. Accordingly, this treatise found out a significant meaning to have an effect on the national security in the korean peninsula.