• Journal of the Korea Society for Simulation
• /
• v.19 no.4
• /
• pp.209-218
• /
• 2010

The aim of the study on the tactical object representation techniques in synthetic environment is on acquiring fundamental techniques for detection and tracking of tactical objects, and evaluating the strategic situation in the virtual ground. In order to acquire these techniques, there need the tactical objects' position tracking and evaluation, and an inter-sharing technique between tactical models. In this paper, we study the algorithms on the sensor data fusion and coordinate conversion, proportional navigation guidance(PNG), and pursuit-evasion technique for engineering and higher level models. Additionally, we simulate the position evaluation of tractical objects using the pursuit and evasion maneuvers between a submarine and a torpedo.

• Journal of Korean Port Research
• /
• v.12 no.1
• /
• pp.55-64
• /
• 1998

Directed graphic algorithm was applied to an empirical analysis of traffic occupant fatalities based on a model by Crandall. In this paper, Crandall's data on U.S. traffic fatalities for the period 1947-1981 are focused and extended to include 1982-1993. Based on the 1947-1981 annual data, the directed graph algorithms reveal that occupant traffic deaths are directly caused by income, vehicle miles, and safety devices. Vehicle mileage is caused by income and rural driving. The estimation is conducted using three stage least squares regression. Those results show a difference between the traditional regression methodology and causal graphical analysis. It is also found that forecasts from the directed graph based model outperform forecasts from the regression-based models, in terms of mean squared forecasts error. Furthermore, it is demonstrates that there exists some latent variables between all explanatory variables and occupant deaths.

• Journal of KIISE:Databases
• /
• v.36 no.5
• /
• pp.352-365
• /
• 2009

Recently, data access control policies have not been applied for authorized or unauthorized persons properly and information leakage incidents have occurred due to database security vulnerabilities. In the traditional database access control methods, administrators grant permissions for accessing database objects to users. However, these methods couldn't be applied for diverse access control policies to the database. In addition, another database security method which uses data encryption is difficult to utilize data indexing. Thus, this paper proposes an enhanced database access control system via a packet analysis method between client and database server in network to apply diverse security policies. The proposed security system can be applied the applications with access control policies related to specific factors such as date, time, SQL string, the number of result data and etc. And it also assures integrity via a public key certificate and MAC (Message Authentication Code) to prevent modification of user information and query sentences.

• Journal of KIISE
• /
• v.44 no.7
• /
• pp.703-709
• /
• 2017

Outsourcing databases is to offload storage and computationally intensive tasks to the third party server. Therefore, data owners can manage big data, and handle queries from clients, without building a costly infrastructure. However, because of the insecurity of network systems, the third-party server may be untrusted, thus the query results from the server may be tampered with. This problem has motivated significant research efforts on authenticating various queries such as range query, kNN query, function query, etc. Although aggregation queries play a key role in analyzing big data, authenticating aggregation queries has not been extensively studied, and the previous works are not efficient for data with high dimension or a large number of distinct values. In this paper, we propose the AMR-tree that is a data structure, applied to authenticate aggregation queries. We also propose an efficient proof construction method and a verification method with the AMR-tree. Furthermore, we validate the performance of the proposed algorithm by conducting various experiments through changing parameters such as the number of distinct values, the number of records, and the dimension of data.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.11a
• /
• pp.205-207
• /
• 2013

멀티 클라우드 서비스 제공자가 연동된 환경에서 각 데이터 센터에 위치하고 있는 물리 노드들의 위치에 따라서 클라우드 서비스 사용자와 연결된 네트워크 속도에 차이가 발생하고 이에 의해서 각 물리 노드에서 생성되는 가상 자원 인스턴스의 작업 처리 성능에도 영향을 미치게 된다. 특히 웹 어플리케이션과 같은 네트워크 성능에 의존도가 높은 응용의 경우 이에 대한 성능 영향의 정도가 매우 크게 증가한다. 본 논문에서는 이러한 문제를 해결하기 위하여 클라우드 서비스 사용자와 가상 자원 인스턴스간의 물리적인 거리 및 동적인 네트워크 상황을 고려한 적응적 가상 자원 할당 기법을 소개한다.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.3
• /
• pp.17-24
• /
• 2023

Based on the problem of 'Tatanic - Machine Learning from Disaster', a representative competition of Kaggle that presents challenges related to data science and solves them, we want to see how data preprocessing and model construction affect prediction accuracy and score. We compare and analyze the features by selecting seven top-ranked solutions with high scores, except when using redundant models or ensemble techniques. It was confirmed that most of the pretreatment has unique and differentiated characteristics, and although the pretreatment process was almost the same, there were differences in scores depending on the type of model. The comparative analysis study in this paper is expected to help participants in the kaggle competition and data science beginners by understanding the characteristics and analysis flow of the preprocessing methods of the top score participants.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.614-616
• /
• 2021

The world faces difficulties in terms of eye care, including treatment, quality of prevention, vision rehabilitation services, and scarcity of trained eye care experts. However, it is difficult to develop a method for classifying various ocular diseases because the existing dataset for retinal image disclosure does not consist of various diseases found in clinical practice. We propose a method for classifying ocular diseases using the Retinal Fundus Multi-disease Image Dataset (RFMiD), a dataset published in the ISBI-2021 challenge. Our goal is to develop a robust and generalizable model for screening retinal images into normal and abnormal categories. The performance of the proposed model shows a value of 0.9782 for the test dataset as an area under the curve (AUC) score.

• Proceedings of the Korea Contents Association Conference
• /
• 2008.05a
• /
• pp.823-826
• /
• 2008

This paper shows linkage management for external services. There are many services for specific entities such as DBLP and OntoWorld. OntoFrame, as a Semantic Web-based research information service portal, aims at one-stop service in ways that it connects external services with hyperlinks. For managing the linkage, linkage rules are manually edited by human administrators and automatically verified and tested by linkage management system. It consists of linkage rule management, linkage rule verification, linkage test, and dynamic link generation. Linkage rule management creates and edits linkage rules to connect external services on the Web. After finished rule editing and verification step, linkage management invokes linkage test with entity list. Only valid links are visible to enable users to click on our system, and thus it increases user's reliability on the system.

• Education of Primary School Mathematics
• /
• v.26 no.4
• /
• pp.333-348
• /
• 2023

Clear analysis and diagnosis of various characteristic factors of individual students is the most important in order to realize individual customized teaching and learning, which is considered the most essential function of math artificial intelligence-based digital textbooks. In this study, analysis factors and tools for individual customized learning diagnosis and construction models for data collection and analysis were derived from mathematical AI digital textbooks. To this end, according to the Ministry of Education's recent plan to apply AI digital textbooks, the demand for AI digital textbooks in mathematics, personalized learning and prior research on data for it, and factors for learner analysis in mathematics digital platforms were reviewed. As a result of the study, the researcher summarized the factors for learning analysis as factors for learning readiness, process and performance, achievement, weakness, and propensity analysis as factors for learning duration, problem solving time, concentration, math learning habits, and emotional analysis as factors for confidence, interest, anxiety, learning motivation, value perception, and attitude analysis as factors for learning analysis. In addition, the researcher proposed noon data on the problem, learning progress rate, screen recording data on student activities, event data, eye tracking device, and self-response questionnaires as data collection tools for these factors. Finally, a data collection model was proposed that time-series these factors before, during, and after learning.

• Journal of KIISE:Databases
• /
• v.28 no.2
• /
• pp.131-139
• /
• 2001

데이터 변환은 데이터 재사용, 데이터 교환 및 통합 등에 사용되는 중요한 기술이다. 본 논문에서는 객체지향 데이터베이스를 유효한 XML 문서들로 변환시키는 두 가지 알고리즘을 제시한다. 먼저 객체지향 데이터베이스의 스키마, 객체지향 데이터베이스, DTD 그리고 XML 문서를 정의한 뒤 두 가지 알고리즘, 즉 객체지향 데이터베이스의 스키마를 DTD로 변환시키는 알고리즘과 객체지향 데이터베이스를 XML 문서들로 변환시키는 알고리즘을 제시한다. 그리고 제시한 두 가지 알고리즘의 결과는 항상 잘 구성된 XML 문서들이고 유효한 XML 문서들임을 증명한다. 잘 구성된 XML 문서는 XML문서가 갖추어야 하는 필수 조건이므로 반드시 필요하다. 또한 유효성은 유효한 XML 문서들을 필요로 하는 XML 응용에 유효한 XML 문서를 제공할 수 있도록 한다.