• The KIPS Transactions:PartC
• /
• v.11C no.4
• /
• pp.429-438
• /
• 2004

This Paper Presents the control structure for incoming traffic from arbitrary node to Provide admission control in policy-based W network management structure using fuzzy logic control approach. The proposed control structure uses scheme for deciding network resource allocation depending on requirements predefined-policies and network states. The proposed scheme enhances policy adapting methods of existing binary methods, and can use resource of network more effectively to provide adaptive admission control, according to the unpredictable network states for predefined QoS policies. Simulation results show that the proposed controller improves the ratio of packet rejection up to 26%, because it Performs the soft adaption based on the network states instead of accept/reject action in conventional CAC(Connection Admission Controller).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.553-557
• /
• 2009

USS(Ubiquitous Smart Space) give services, that fit in with customer's goal, by cognizing various situations that happens in a space and cooperating autonomously objects or services in a space. In USS, U-Safety is a system that cognizes more exact situations with multiple sensors in USS, deals with this and take proper actions. When men reason on situations objectively, it is most ideal that image data among collected data with used various sensors in U-Safety. A senter collects a lot of image data from image input devices equipped in various points and work a multiple situation cognition and inference that are based on this. So, senters spend many resources for processing massive data. This paper proposes hierarchical image processing method that does the first situation cognization in image input devices, blocks only points that situation cognization possibility is high among a total image, and transfers to senters. It improves the efficiency of smooth situation cognization by reducing resources that a senter spends on image processing. So, it reduces proportion of image data in U-Safety.

• Journal of Korean Home Economics Education Association
• /
• v.14 no.3
• /
• pp.1-9
• /
• 2002

The objectives of this study were to measure the effect of Practical Reasoning Instruction in Home Economics : specifically. its effect on developing of critical thinking as well as to evaluate the degree of the critical thinking process. with reference to its sub-factors and the level. The research subjects were consisted of the experimental group of 119 freshman class female students from the “A” High School and the comparative group of 110 freshman class female student from the “C” High School in the city of Chung-Ju. This research was conducted under the pre-post test control group design. administering the Pre-Post testing to both the experimental and the comparative groups. The experimental group was subjected to Practical Reasoning Instruction in Home Economics : whereas the comparative group was taught under the lecture-Instruction in Home Economics The research findings are as follows: 1. Those who studied Home Economics under the Practical reasoning method scored higher on the critical thinking Process than the comparative group students who were taught Home Economics in the lecture-style approach. 2. The experimental group of students. who studied Home Economics under the Practical reasoning method. scored higher than the comparative group in their ability to perceive assumption and to render Judgment among the five sub-factors of their critical thinking processes.

• Journal of the Korean Society for information Management
• /
• v.34 no.1
• /
• pp.177-195
• /
• 2017

This study attempts to infer research fronts using factor graph model based on heterogeneous features. The model suggested by this study infers research fronts having documents with the potential to be cited multiple times in the future. To this end, the documents are represented by bibliographic, network, and content features. Bibliographic features contain bibliographic information such as the number of authors, the number of institutions to which the authors belong, proceedings, the number of keywords the authors provide, funds, the number of references, the number of pages, and the journal impact factor. Network features include degree centrality, betweenness, and closeness among the document network. Content features include keywords from the title and abstract using keyphrase extraction techniques. The model learns these features of a publication and infers whether the document would be an RF using sum-product algorithm and junction tree algorithm on a factor graph. We experimentally demonstrate that when predicting RFs, the FG predicted more densely connected documents than those predicted by RFs constructed using a traditional bibliometric approach. Our results also indicate that FG-predicted documents exhibit stronger degrees of centrality and betweenness among RFs.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.4
• /
• pp.193-202
• /
• 2017

Development of Intelligent Systems involves effective integration of large-scaled knowledge processing and understanding, human-machine interaction, and intelligent services. Especially, in our project for development of a self-growing knowledge-based system with inference methodologies utilizing the big data technology, we are building a platform called WiseKB as the central knowledge base for storing massive amount of knowledge and enabling question-answering by inferences. WiseKB thus requires an effective methodology to analyze diverse requirements convoluted with the integration of various components of knowledge representation, resource management, knowledge storing, complex hybrid inference, and knowledge learning, In this paper, we propose an integrated requirement analysis method that blends the traditional sequential method and the iterative-incremental method to achieve an efficient requirement analysis for large-scale systems.

• The KIPS Transactions:PartD
• /
• v.16D no.6
• /
• pp.889-898
• /
• 2009

Currently, the amount of containers is growing up continuously. However, they still depend on humans checking or validating. In this situation, humans must participate in the systems. Situation-awareness technologies allow human participation to be minimized. The situation-awareness technologies provide data or service appropriate to the object's current state, and the state is recognized automatically by the system. They can automatically execute working processes without human intervention. We suggest a middleware system based on situation-awareness technologies using an ontology for the safety transportation of containers. The middleware is aware of the current state and sends the data required by an application. It can help build new applications by enhancing agility, and it can also support automated service processing by invoking the service required like fire-fighting, fixing container, and so on. Improving transportation of containers process automation with situation-awareness technologies reduces manpower requirements for checking and validating containers, and so saves logistics costs of container transportation.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.2
• /
• pp.169-180
• /
• 2009

The conventional paper retrieval is the keyword-based search and as a huge amount of data be published, this search becomes more difficult in retrieving information that user want to find. In order to search for information to the user's intent, we need to introduce semantic Web that represents semantics of Web document resources on the Internet environment as ontology and enables the computer to understand this ontology. Therefore, we describe a paper retrieval system through OWL(Ontology Web Language) ontology-based reason in this paper. We build the paper ontology based on OWL which is new popular ontology language for semantic Web and represent the correlation among diverse paper properties as the DL(description logic) query, and then this system infers the correct results from the paper ontology by using the DL query and makes it possible to retrieve information intelligently. Finally, we compared our experimental result with the conventional retrieval.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.3
• /
• pp.65-75
• /
• 2008

Grid Computing has enabled enormous amount of computational jobs by connecting distributed computing resources. This technology has developed and widely used in various fields. Previous researches usually focused on how to efficiently manage and use the grid resources. However, there was not enough tries to understand and manage information of application softwares in a well-defined structure. Therefore users in application domain need to how about grid deeply to identify and describe the resource requirements matching for each jobs. We introduce a semantic grid management system based on application ontology to overcome this problem. We design and implement the ontology to store various information of the applications. With the ontology, this system can infer the resource requirements from input parameters and input data of the application software and automatically assign appropriate resources by matching the requirement. Also it can transform the information to other forms which grid middlewares can handle. We apply the system to construct an analysis environment of bioinformatics and compare it with other grid systems to explain usefulness of the system.

• Journal of the Korea Society for Simulation
• /
• v.18 no.2
• /
• pp.29-38
• /
• 2009

In the computing environment with heterogeneous resources, a job scheduling model is necessary for effective resource utilization and high-speed data processing. And, the job scheduling model has to cope with a dynamic change in the condition of resources. There have been lots of researches on resource estimation methods and heuristic algorithms about how to distribute and allocate jobs to heterogeneous resources. But, existing researches have a weakness for system compatibility and scalability because they do not support the standard language. Also, they are impossible to process jobs effectively and deal with a variety of computing situations in which the condition of resources is dynamically changed in real-time. In order to solve the problems of existing researches, this paper proposes a semantic computing-based dynamic job scheduling model that defines various knowledge-based rules for job scheduling methods adaptable to changes in resource condition and allocate a job to the best suited resource through inference. This paper also constructs a resource ontology to manage information about heterogeneous resources without difficulty as using the OWL, the standard ontology language established by W3C. Experimental results shows that the proposed scheduling model outperforms existing scheduling models, in terms of throughput, job loss, and turn around time.

• Proceedings of the Plant Resources Society of Korea Conference
• /
• 2018.04a
• /
• pp.42-42
• /
• 2018

메밀은 마디풀과(polygonaceae)의 메밀속에 속하는 일년생 초본으로 야생종을 포함하여 20여 종이 확인되고 있다. 현재 재배되고 있는 메밀 재배종은 보통메밀(Fagopyrum esculentum Moench)과 쓴메밀(Fagopyrum tataricum Gaertn., 타타리메밀) 등 두 종이 주류를 이루고 있으며 우리나라에서는 보통메밀이 주로 재배되어 왔다. 본 연구는 농업유전자원센터에서 보유중인 보통메밀 341점과 쓴메밀 38점을 봄, 여름에 파종하여 특성조사를 수행하고 재배시기별 생육특성을 비교하기 위해 수행되었다. 봄, 여름 파종은 각각 2017년 4월 14일과 8월 17일에 전주 소재 농업유전자원센터 포장에 하였으며 줄기색, 엽색, 엽형, 개화기, 성숙기, 꽃색, 종피색, 종자모양, 주경절수, 총분지수, 백립중 등 11개 농업형질을 조사하였다. 봄 파종시 개화기는 대부분 5월 25일 전후였으며 성숙기는 6월 말부터 7월 중순까지 분포하였고 여름 파종시는 9월 15일 전후 개화하여 10월 말에 성숙하였다. 줄기색은 홍색의 비율이 높았고 엽색은 연녹색과 녹색이 대부분이었으며 엽형은 화살촉형이 90% 이상이었다. 꽃색은 흰색이 대부분이었지만 연녹색 자원도 40점 조사되었으며 종피색은 연갈색이 70%를 차지하였다. 종자 생산과 관련된 주경절수와 총분지수는 봄 파종과 여름 파종에서 많은 차이를 나타냈으며 봄 재배시 영양생장이 왕성하여 가을 재배보다 많은 주경절수와 총분지수가 조사되었다. 그러나 백립중에서는 여름 파종이 봄 파종보다 무거운 경향을 나타내어 주경절수, 총분지수와 백립중 간 부의 상관관계를 추론할 수 있었다. 일반메밀 유전자원을 국내 수집지별로 나누어 조사한 결과 주경절수와 총분지수는 봄, 여름 파종 모두에서 전남 수집자원이 가장 많았으며, 강원, 경남, 경북, 전북, 충북 수집자원과 유의성있는 차이를 나타내었다. 강원, 충북 수집자원은 제일 낮은 주경절수와 총분지수를 보였으나 백립중은 가장 높게 조사되었다.