• Title/Summary/Keyword: 정보처리지식

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A Control Method for designing Object Interactions in 3D Game (3차원 게임에서 객체들의 상호 작용을 디자인하기 위한 제어 기법)

  • 김기현;김상욱
    • Journal of KIISE:Computing Practices and Letters
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    • v.9 no.3
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    • pp.322-331
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    • 2003
  • As the complexity of a 3D game is increased by various factors of the game scenario, it has a problem for controlling the interrelation of the game objects. Therefore, a game system has a necessity of the coordination of the responses of the game objects. Also, it is necessary to control the behaviors of animations of the game objects in terms of the game scenario. To produce realistic game simulations, a system has to include a structure for designing the interactions among the game objects. This paper presents a method that designs the dynamic control mechanism for the interaction of the game objects in the game scenario. For the method, we suggest a game agent system as a framework that is based on intelligent agents who can make decisions using specific rules. Game agent systems are used in order to manage environment data, to simulate the game objects, to control interactions among game objects, and to support visual authoring interface that ran define a various interrelations of the game objects. These techniques can process the autonomy level of the game objects and the associated collision avoidance method, etc. Also, it is possible to make the coherent decision-making ability of the game objects about a change of the scene. In this paper, the rule-based behavior control was designed to guide the simulation of the game objects. The rules are pre-defined by the user using visual interface for designing their interaction. The Agent State Decision Network, which is composed of the visual elements, is able to pass the information and infers the current state of the game objects. All of such methods can monitor and check a variation of motion state between game objects in real time. Finally, we present a validation of the control method together with a simple case-study example. In this paper, we design and implement the supervised classification systems for high resolution satellite images. The systems support various interfaces and statistical data of training samples so that we can select the most effective training data. In addition, the efficient extension of new classification algorithms and satellite image formats are applied easily through the modularized systems. The classifiers are considered the characteristics of spectral bands from the selected training data. They provide various supervised classification algorithms which include Parallelepiped, Minimum distance, Mahalanobis distance, Maximum likelihood and Fuzzy theory. We used IKONOS images for the input and verified the systems for the classification of high resolution satellite images.

Usefulness of Data Mining in Criminal Investigation (데이터 마이닝의 범죄수사 적용 가능성)

  • Kim, Joon-Woo;Sohn, Joong-Kweon;Lee, Sang-Han
    • Journal of forensic and investigative science
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    • v.1 no.2
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    • pp.5-19
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    • 2006
  • Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

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Research about feature selection that use heuristic function (휴리스틱 함수를 이용한 feature selection에 관한 연구)

  • Hong, Seok-Mi;Jung, Kyung-Sook;Chung, Tae-Choong
    • The KIPS Transactions:PartB
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    • v.10B no.3
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    • pp.281-286
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    • 2003
  • A large number of features are collected for problem solving in real life, but to utilize ail the features collected would be difficult. It is not so easy to collect of correct data about all features. In case it takes advantage of all collected data to learn, complicated learning model is created and good performance result can't get. Also exist interrelationships or hierarchical relations among the features. We can reduce feature's number analyzing relation among the features using heuristic knowledge or statistical method. Heuristic technique refers to learning through repetitive trial and errors and experience. Experts can approach to relevant problem domain through opinion collection process by experience. These properties can be utilized to reduce the number of feature used in learning. Experts generate a new feature (highly abstract) using raw data. This paper describes machine learning model that reduce the number of features used in learning using heuristic function and use abstracted feature by neural network's input value. We have applied this model to the win/lose prediction in pro-baseball games. The result shows the model mixing two techniques not only reduces the complexity of the neural network model but also significantly improves the classification accuracy than when neural network and heuristic model are used separately.

Export Control System based on Case Based Reasoning: Design and Evaluation (사례 기반 지능형 수출통제 시스템 : 설계와 평가)

  • Hong, Woneui;Kim, Uihyun;Cho, Sinhee;Kim, Sansung;Yi, Mun Yong;Shin, Donghoon
    • Journal of Intelligence and Information Systems
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    • v.20 no.3
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    • pp.109-131
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    • 2014
  • As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

Survey on Pest Management Practice and Scheme of Increasing Income in Sweet Persimmon Farms in Korea (단감원의 병해충 관리 실태와 소득 증대 방안에 대한 농가 의식조사)

  • Lee, Dong-Woon;Lee, Seong-Wook;Park, Chung-Gyoo;Choo, Ho-Yul;Shin, Chang-Hoon;Lee, Gyoo-Chul
    • The Korean Journal of Pesticide Science
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    • v.5 no.4
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    • pp.45-49
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    • 2001
  • As a series of studies to develop pest management system for sweet persimmon production matched with the quarantine criterion of sweet persimmon-imported county, a survey was conducted by questionnaire on pest management practice and scheme of increasing income in sweet persimmon farms in Korea. Above 80% of sweet persimmon farmers was over fifties in age. The greatest limiting factor for sweet persimmon production was thought to be disease by the farmers. Percentage of farmers who answered that the most important pest is anthracnose cause by Gloeosporium kaki, and stink bugs was 64.6% and 73.5%, respectively. In particular, the farmers did not consider Dichocrocis punctiferalis, a main targer insect for quarantine in USA, as serious problem. Obtaining information on pest management practice or decision-making on both selection of pesticide and time of pesticide application depended highly on their own experience with the highest proportion. Eight to nine times of pesticide applications a year was highest among farms with 56.6%. More than 80% of farmers recorded the diary of pesticide application. farmers considered increasing cost for pest management as the greatest problem with 35.4% in proportion, and 34.5% of farmers pointed out that increase in export is essential for increasing farm income with highest proportion.

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An Analysis of Cultural Contents in Elementary School English Textbooks for Grades 3 and 4 Based on the 2015 Revised Korean National Curriculum (초등학교 3,4학년 영어교과서 문화 내용 분석 : 2015 개정 교육과정을 중심으로)

  • Jang, Na-rae;Kim, Jeong-ryeol
    • The Journal of the Korea Contents Association
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    • v.18 no.8
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    • pp.1-8
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    • 2018
  • The aim of this study was to analyze the cultural contents represented in elementary school English textbooks for grades 3 and 4 based on the 2015 revised Korean national curriculum. An analysis of cultural contents was conducted on the basis of Morgan(2001)'s five category criteria. Among the five aspects of culture, 'practices' relevant to daily life were presented most frequently in the textbooks followed by 'products'. English textbooks showed a relatively low frequency in 'perspectives' and 'communities' areas of culture. 'Persons' did not appear at all in all eight textbooks. It revealed that there was a serious imbalance in the representation of textbook about cultural contents. In conclusion, there should be balanced cultural contents for the students to have a balanced cultural awareness and to accept cultural diversity and differences. In addition, textbooks should include more various cultural materials and activities for the students to develop four key competencies suggested on the 2015 revised Korean national curriculum.

Kinematic Analysis of a Mastication Model Employing the 6-DOF Parallel Mechanism (6자유도의 병렬기구를 사용한 저작 모델의 기구학적 분석)

  • Khang, G.;Tsutsumi, Sadami
    • Journal of Biomedical Engineering Research
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    • v.20 no.4
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    • pp.479-484
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    • 1999
  • 본 연구에서는 사람의 턱 운동과 턱 사이에 작용하는 힘(혹은 압력)을 그대로 나타낼 수 있는 저작로봇을 개발하는 것을 궁극적인 목표로 한다. 이러한 저작로봇이 개발되면, 치과의사가 환자의 턱운동에 나타나는 병변을 진단하고 치료하는데 큰 도움이 될 것으로 사료된다. 또한 , 본 연구에 채택한 병렬기구(parallel mechanism)에대한 순기구학적( forward kinematics)분석은 일반적인 병렬기구의 실계에도 응용될 것으로 기대된다. 본 연구진이 1차적으로 설계한 모델은 베이스와 플랫폼(platform), 그리고 이 둘을 연결하는 3개의 다리로 구성되어 있다. 다리와 플랫폼은 3자유도의 관절로 다리와 베이스는 1자유도의 경첩 관절로 연결되어 있으며, 이 3개의 경첩 관절은 베이스 위의 수평면에서 직선을 따라 움직인다. 경첩 관절의 수평 변위와 세 다리의 길이가 주어졌을 때 플랫폼의 위치와 오리엔테이션을 구하는 순기구학의 해( 解)를 계산해내는 알고리즘을 개발하였다. 이 알고리즘의 특징은 매 순간 오차를 계산하여 이 오차가 줄어드는 방향으로 나아가도록 시간간격(time step)을 조절하는 것이다. 본 알고리즘은 현재 가장 보편적으로 사용되고 있는 뉴튼-렙슨 방법에 비하여 3가지 장점을 나타내고 있다. 우선 , 초기치(initial guess)에 관계없이 수렴한다는 것이다. 또한, 본 알고리즘은 뉴튼-렙슨 방법에 비하여 수렴속도가 훨씬 빠르며, 연산 시간이 매우 짧아져 실제적인 실시간 적용에 적합하다. 마지막으로, 뉴튼-렙슨 방법에서는 여러 개의 해 가운데 어느 곳으로 수렴할 지 예측 할수 없으나 본 알고리즘에서는 초기치에 가장 가까운 해로 수렴한다. 이러한 순기구학의 다중성(multiplicity)문제를 해결하기 위하여 두 개의 조건을 제시하였으며, 이를 적용한 시뮬레이션 결과에 의하면 항상 원하는 해(true solution)에 수렴할 수 있었다.발생량의 감소를 기대 할 수 있는 친환경기술로 유지관리비를 최소화할 수 있는 장점이 있었다. 않은 사람들 중 미래의 검진실행의지에 건강소식지가 영향을 미친 경우는 48.7%였다. 보건교육을 받은 후 유방암 자가검진 실천율은 사업군에서 53.9%로 받기 전의 27.3%보다 증가하였으나 대조군의 경우는 별 차이가 없었다. 연령별로는 60대가 가장 높았고 사업군에서 검진율의 증가분은 30대가 가장 컸다. 교육수준별로는 사업군은 고졸이, 대조군은 전문대졸이 가장 높았고 사업군에서 검진율의 증가분은 고졸에서 가장 컸다. 보건교육 후 유방암과 관련된 건강지식의 정도는 사업군이 3.7점으로 대조군보다 유의하게 높았으며, 유방암 자가검진법을 실천하는 사람들의 동기는 ‘일반 대중매체의 영향’이 가장 많았으며 건강소식지가 동기인 경우도 20.4%였다. 사업군에서 건강소식지가 유방암 자가검진법 실천에 영향을 미친 경우가 79.6%였으며 유방암 자가검진법에 관한 보건교육을 받고 실천하지 않은 사람들 중 미래의 실천의지에 건강소식지가 영향을 미친 경우는 43.6%였다. 이상의 소견에서 지역주민을 대상으로 인쇄매체를 통한 보건교육은 인쇄물만으로도 쉽게 실천 할 수 있는 유방암 자가검진법이 가장 효과적이었으며, 자궁암검진에 관해서도 검진을 받을 수 있도록 지역사회의 보건의료의 하부구조를 정비하여 제도적 장치를 마련하고 정보를 제공한다면 자궁암검진 실천율도 증가할 것이다.고 12.9% 의 발달율을 보여 유의적인 차이를 보이지 않았다. 이상의 결과로 보아 핵이식 수정란을 효율적으로 생산하기 위하여 수핵난자의 세포질에 ionomycin 과 DMAP 의 혼합처리로 탈핵난자의 활성화를 유도하는 것이 효율을 증진시킬 수 있었다고 본다. 또한 공핵수정란을 수정 후 90시간과 114시간 개별 배양하여 할구를 공핵체로 핵이식에 이용하였을 때도 그룹배양에 비하여 효율이 떨어지지 않음을 알 수 있었으며, 수정란의 할구

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The Effect on Firm's Performance of Employee Stock Option (종업원의 주식보상시스템이 기업성과에 미치는 영향)

  • Park, Jong-Hyuk
    • Management & Information Systems Review
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    • v.28 no.1
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    • pp.71-97
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    • 2009
  • In this study, I compare the ability of alternative accounting method for employee stock option to reflect firm value using the Ohlson's(1995) valuation model for 200 firms. The each methods, I compare are employee stock option expense recognition based on the K-GAAP disclosures, and asset recognition at the grant date based on the SFAS No. 123 Exposure Draft: Accounting for stock-based compensation. The model include: (1) a model that uses reported earnings, equity book value, and compensation expense based on the K-GAAP disclosures; (2) a model that uses pro-forma earnings, equity book value and adds a measure of the unrecognized asset arising form granting of employee stock options. Finding form estimating equations that the K-GAAP method for calculating compensation has no explanatory power, and the SFAS No.123 Draft Exposure method for arising asset and fair value compensation better captures than market's perception of the economic impact of stock options on firm values. However, the correlation of employee stock option compensation expense is positive. These results suggest that incentive benefits derived from employee stock option plans outweigh the cost associated with plan. In addition, I couldn't find evidence that company in KOSDAQ that have high growth potential benefit more from employee stock option plan compared to lager, more mature firm in SEC.

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A Convergence Study on the Core Competencies of students: G university (G 대학 대학생 핵심역량 설정에 관한 융합연구)

  • Kim, Chang-Gyu;Jang, Kee-Duck;Chun, Yeol-Eo
    • Journal of the Korea Convergence Society
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    • v.9 no.7
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    • pp.77-86
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    • 2018
  • This research is based on core competency in order to provide diverse educational opportunities and to train compatible human resources according to industrial change. The research set up the core competency of university students according to document research and the importance of core competency of students, professors, faculty and parents. As a result, a total of 14 competencies were deducted by importance and validation from enrolled students, graduated students and professors. A total of 5 core competencies and 14 detailed competencies were deducted. Creativity, problem solving ability, self-directed overall problem solving abilities, expertise ability, data processing ability, technology application according to industry, consideration and serving character, community service, communicational ability, self-management, inter personal relationship, foreign language ability, global, leadership and competence were the 14 elements of this research. Based on the result of this study, it is necessary to improve the competence of university students by applying them to the curriculum development and operation and to find out the extent of the students competence enhancement through the development of future capacity measuring tools.

An Instructional Design for PBL-based English Classes in Elementary Schools (초등학교에서 PBL 기반 영어 수업을 위한 학습 모형 설계)

  • Park, In-Hwa
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.3
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    • pp.564-568
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    • 2020
  • Problem-based learning (PBL) is applied to various subjects for the sake of learners' creative thinking, problem-solving skills, presentation skills, confidence, self-directed learning, cooperation, and for the communication skills required in a rapidly changing society. Among them, the English language-an official language-is invested in 2.3 times more than other subjects, according to the English education company Yoon's Teacher. Therefore, PBL is an important learning method. However, the reality is that teacher-centered instruction, acquiring knowledge of the best answers only, and traditional evaluations are the main subjects. In order to supplement these weak points, this study designed a learning model for English subjects based on Barrows & Myers (2002) and the analyze, design, develop, implement, and evaluate (ADDIE) model. As a result of a PBL English class based on the ADDIE model, the learners were able to improve their presentation skills by 86%, their interest in learning by 86%, their understanding of learning by 86%, and cooperation by 100%. As such, studies on designing the learning model should be carried out continuously to achieve the purpose of 21st century English education, which is to improve learners' communication skills and information processing skills.