• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.4
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• pp.539-547
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• 2011

In this paper, a method of generating path planning map is developed using digitalized geographic information such as FDB(Feature DataBase). FDB is widely used by the Army and needs to be applied to all weapon systems of newly developed. For the autonomous navigation of a robot, it is necessary to generate a path planning map by which a global path can be optimized. First, data included in FDB is analyzed in order to identify meaningful layers and attributes of which information can be used to generate the path planning map. Then for each of meaningful layers identified, a set of values of attributes in the layer is converted into the traverse cost using a matching table in which any combination of attribute values are matched into the corresponding traverse cost. For a certain region that is gridded, i.e., represented by a grid map, the traverse cost is extracted in a automatic manner for each gird of the region to generate the path planning map. Since multiple layers may be included in a single grid, an algorithm is developed to fusion several traverse costs. The proposed method is tested using a experimental program. Test results show that it can be a viable tool for generating the path planning map in real-time. The method can be used to generate other kinds of path planning maps using the digitalized geographic information as well.

• Journal of Technology Innovation
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• v.24 no.3
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• pp.139-159
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• 2016

The purpose of this study is to find out the factors which promoting career development of scientist and engineer laborforce. We made up three logit analysis models to figure out the factors affecting the career of scientist and engineer laborforce. Dependent variables were composed of job attributes in 2011, current job attribute, changing of working conditions, efforts of job seeking, university education, and personal characters. Three analysis model were composed of demand side model which including job attributes factors, supply side model which focus on employment or university education characters and total model including the demand and the supply factors. The results showed a stable career to the development of scientist and engineer laborforce's job attributes on the demand side than the supply side, such as a college education even more important. After all, the initial stable jobs and good matching policy were the most important policies to be seated in the science and engineering professions.

• Asia pacific journal of information systems
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• v.19 no.3
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• pp.51-67
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• 2009

Developing an agile recommender system for nomadic users has been regarded as a promising application in mobile and ubiquitous settings. To increase the quality of personalized recommendation in terms of accuracy and elapsed time, estimating future context of the user in a correct way is highly crucial. Traditionally, time series analysis and Makovian process have been adopted for such forecasting. However, these methods are not adequate in predicting context data, only because most of context data are represented as nominal scale. To resolve these limitations, the alignment-prediction algorithm has been suggested for context prediction, especially for future context from the low-level context. Recently, an ontological approach has been proposed for guided context prediction without context history. However, due to variety of context information, acquiring sufficient context prediction knowledge a priori is not easy in most of service domains. Hence, the purpose of this paper is to propose a novel context prediction methodology, which does not require a priori knowledge, and to increase accuracy and decrease elapsed time for service response. To do so, we have newly developed pattern-based context prediction approach. First of ail, a set of individual rules is derived from each context attribute using context history. Then a pattern consisted of results from reasoning individual rules, is developed for pattern learning. If at least one context property matches, say R, then regard the pattern as right. If the pattern is new, add right pattern, set the value of mismatched properties = 0, freq = 1 and w(R, 1). Otherwise, increase the frequency of the matched right pattern by 1 and then set w(R,freq). After finishing training, if the frequency is greater than a threshold value, then save the right pattern in knowledge base. On the other hand, if at least one context property matches, say W, then regard the pattern as wrong. If the pattern is new, modify the result into wrong answer, add right pattern, and set frequency to 1 and w(W, 1). Or, increase the matched wrong pattern's frequency by 1 and then set w(W, freq). After finishing training, if the frequency value is greater than a threshold level, then save the wrong pattern on the knowledge basis. Then, context prediction is performed with combinatorial rules as follows: first, identify current context. Second, find matched patterns from right patterns. If there is no pattern matched, then find a matching pattern from wrong patterns. If a matching pattern is not found, then choose one context property whose predictability is higher than that of any other properties. To show the feasibility of the methodology proposed in this paper, we collected actual context history from the travelers who had visited the largest amusement park in Korea. As a result, 400 context records were collected in 2009. Then we randomly selected 70% of the records as training data. The rest were selected as testing data. To examine the performance of the methodology, prediction accuracy and elapsed time were chosen as measures. We compared the performance with case-based reasoning and voting methods. Through a simulation test, we conclude that our methodology is clearly better than CBR and voting methods in terms of accuracy and elapsed time. This shows that the methodology is relatively valid and scalable. As a second round of the experiment, we compared a full model to a partial model. A full model indicates that right and wrong patterns are used for reasoning the future context. On the other hand, a partial model means that the reasoning is performed only with right patterns, which is generally adopted in the legacy alignment-prediction method. It turned out that a full model is better than a partial model in terms of the accuracy while partial model is better when considering elapsed time. As a last experiment, we took into our consideration potential privacy problems that might arise among the users. To mediate such concern, we excluded such context properties as date of tour and user profiles such as gender and age. The outcome shows that preserving privacy is endurable. Contributions of this paper are as follows: First, academically, we have improved sequential matching methods to predict accuracy and service time by considering individual rules of each context property and learning from wrong patterns. Second, the proposed method is found to be quite effective for privacy preserving applications, which are frequently required by B2C context-aware services; the privacy preserving system applying the proposed method successfully can also decrease elapsed time. Hence, the method is very practical in establishing privacy preserving context-aware services. Our future research issues taking into account some limitations in this paper can be summarized as follows. First, user acceptance or usability will be tested with actual users in order to prove the value of the prototype system. Second, we will apply the proposed method to more general application domains as this paper focused on tourism in amusement park.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.21-29
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• 2009

An intelligent service robot is a robot that monitors its surroundings, and then provides a service to meet a user's goal. It is normally impossible for a robot to anticipate all the needs of its user and various situations in the surroundings ahead, and to prepare for all the necessary functions to cope with them. Therefore, it is required to support the self-growing capability by which robots can extend their functionality based on users' needs and external conditions. In this paper, as an enabler of the self-growing capability, we propose a method that allows a robot to select a component-composition pattern represented in an architectural form (called a sub-architecture), and to extend its functionality by obtaining a set of software components that are prescribed in the pattern. Sub-architecture is selected and instantiated not only based on the functionality required but also based on quality requirements of a user and the surrounding environment. To provide this method, we constructed a quality-attributes-in-use ontology and developed a brokering mechanism that matches quality requirements of users and surroundings against quality attributes of sub-architectures. The ontology provides the common vocabularies to represent quality requirements and attributes, and enables the semantically-based reasoning in matching and instantiating appropriate sub-architectures in supporting services to users. This ontology-based approach contributes to provide a great flexibility in extending robot functionality based on available software components, and to narrow the gap between users' Quality requirements and the Quality of the actual services provided by a robot.

• Archives of design research
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• v.14 no.3
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• pp.37-48
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• 2001

This paper is a study on how women consumers purchase are affected by models who appear in advertisements for cosmetics, focusing especially on studies concerning the impact that models have on advertisement strategies of the cosmetic industry in korea. In surveys conducted, consumers responded that cosmetic advertisement models should examplify a expertness and trustworthiness attitude more than just display their own physical attractiveness. The consumers who bought cosmetic products based on its endorsement from particular models responded that they had a positive reaction to the models physical attractiveness and likability while experiencing a negative reaction to the model's expertness and trustworthiness attitude. Women consumers are interested in cosmetic advertisement models, but do not necessarily trust them. Hence, the use of a Particular model does not directly affect the consumers Purchasing decision. Famous stars often appear in cosmetic advertisements in korea, and targeted consumers have a very positive response to their physical attractiveness, familiarity and perceived likability. However, the consumers have a completely negative response to the models in regards to their expertness, trustworthiness, and their sense of similarity with the model. The models, then, should be used in these advertisements to try and uphold the fellowing qualities. expertness in regards to having some knowledge of, experience with, and expertness in using the cosmetic produces, trustworthiness when expressing their own opinion of the product, matching image of products and targeted consumers.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.104-112
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• 2021

In this study, emotional analysis was conducted based on the basic attribute data of music and the emotional model in psychology, and the result was applied to the visualization rules in the formative arts. In the existing studies using musical parameter, there were many cases with more practical purposes to classify, search, and recommend music for people. In this study, the focus was on enabling sound data to be used as a material for creating artworks and used for aesthetic expression. In order to study the music visualization as an art form, a method that can include human emotions should be designed, which is the characteristics of the arts itself. Therefore, a well-structured basic classification of musical attributes and a classification system on emotions were provided. Also, through the shape, color, and animation of the visual elements, the visualization of the musical elements was performed by reflecting the subdivided input parameters based on emotions. This study can be used as basic data for artists who explore a field of music visualization, and the analysis method and work results for matching emotion-based music components and visualizations will be the basis for automated visualization by artificial intelligence in the future.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

• The Journal of Dong Guk Oriental Medicine
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• v.8 no.2
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• pp.1-24
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• 2000

The comparison of climate's character of Yunqi(運氣) with the data of meterological observation were made in the research of climate. 1. The comparison of the average velocity of wind, temperature, rainfall, humidity of Seoul, by late 1954 to 1983, with Yunqi(運氣) was made. Fire-Chi(火氣) and moisture-qi(濕氣) were matched with the attribute of Taiyun(大運). Cold-qi(寒氣) was had some relationship. Dry-qi(燥 氣) and Wind-qi(風氣) were not matched. About the relationship of Spirit-of-official-sky(司天之氣) with climate, when the Moisture-soil(濕土) was added, they were matched and when the King-fire(君火) was added, they have some relationship. But Wind-tree(風木), Dry-metal(燥金), Buble-fire(相火), Cold-water(寒水) was added they were not matched. 2. According to the observation data of rainfall by late 180 years of Seoul; about Taiyun(大運), when the Water-Yun(水運) was greatly exceeded and Fire-Yun(火運) was shorted, in the case of Official-sky(司天), when Wind-Tree(風木) was added, the frequency was highly. So when the Soil-Yun(土運) was greatly exceeded and when Official-sky(司天)was added to the Moisture-soil(濕土), the rainfall was not matched. 3. The relationship of the frequency of the abnormal climate occurrences between Yunqi-promotion-weak(運氣盛衰)and Yunqi-Harmony(運氣同化) and Yunqi-soft-attacking(運氣順逆) in the weather of Korean Peninsula was compared by 1564 to 1863. They were not matched except the case of Yunqi-Harmony(運氣同化). 4. There were some cases which were not matched exactly between the climate predicted by the theory and real climate in 1984, the year of Kap-ga(甲子年). But many correspondence between the observation by the office of meteorology and the prediction by the analysis from Yun-qi-sang-hab(運氣相合) theory. 5. Because meterological phenomena of real world and analysis from the hypothesis of Yunqi(運氣) have no relationship with each other, some of Doctor denied Yunqi(運氣) in the way of matching mechanically. But the thought of Doctor who denied Fortune-spirit(運氣) made promotion for the theory of divination by bringing deeper insight. And it was not only the negative side. 6. In the point of geographical difference, the climate of China, the origination Yunqi theory, is different from the Korea's. Thus some observation errors should be considered. From the basis of this thesis, I hope that the deeper advance would be made into the Korean Yunqi theory.