• Journal of Pharmacopuncture
• /
• v.25 no.3
• /
• pp.149-185
• /
• 2022

Objectives: The Barak Valley is well known for its rich diversity of medicinal plants. Ethnomedicinal practices are prominent among Barak Valley's major and minor ethnic groups. This systemic review focuses on traditionally used medicinal plants found in the Barak Valley as reported in different ethnobotanical surveys. Methods: We searched various databases, including PubMed, Web of Science, and Google Scholar, to find ethnomedicinal surveys conducted in the Barak Valley. The search was performed using different terms, including ethnomedicinal survey, folk medicine, indigenous knowledge, and Barak Valley. Potential articles were identified following the exclusion and inclusion criteria. Results: A total of eight ethnobotanical surveys were included in this study. We identified a total of 216 plant species belonging to 167 genera and 87 families, which are widely used by the ethnic communities who live in the rural areas of Barak Valley for the treatment of various diseases and ailments. Conclusion: Folk medicine is the result of decades of accumulated knowledge and practices by people who live in rural communities based on their needs and provides an important source of information to assist the search for new pharmaceuticals. Therefore, available information on traditional medicinal plants needs to be explored scientifically to find effective and alternative treatments for different diseases.

• Journal of the Korean Society for Precision Engineering
• /
• v.19 no.11
• /
• pp.83-88
• /
• 2002

In order to predict the moldability of a injection molded part, a simulation of filling is needed. Short shot is one of the most frequent troubles encountered during injection molding process. The adjustment of process conditions is the most economic way to troubleshoot the problematic short shot in cost and time since the mold doesn't need to be modified at all. But it is difficult to adjust the process conditions appropriately in no times since it requires an empirical knowledge of injection molding. In this paper, the intelligent CAE system synergistically combines fuzzy-neural network (FNN) for heuristic knowledge with CAE programs for analytical knowledge. To evaluate the intelligent algorithms, a cellular phone flip has been chosen as a finite element model and filling analyses have been performed with a commercial CAE software. As the results, the intelligent CAE system drastically reduces the troubleshooting time of short shot in comparison with the experts' conventional methodology which is similar to the golden section search algorithm.

• Journal of Fisheries and Marine Sciences Education
• /
• v.27 no.1
• /
• pp.108-114
• /
• 2015

The purpose of this study is to find the relationships among communication competency, social network centrality(trust centrality and knowledge sharing centrality), discussion performance, and online boarding activity in the team based learning situation. For investigating this topic, 44 students are participated in the classes of educational technology. In order to find out the relationships among communication competency, social network centrality, discussion performance, and online boarding activity, compared t-test and path analysis are used. Followings are the results of the research: (a) Communication competency is improved significantly after team based learning. (b) Trust centrality effects significantly on the knowledge sharing centrality. (c) Knowledge sharing effects significantly on discussion performance. (d) Trust centrality effects on the online boarding activity in the team based learning.

• Korean Journal of Computational Design and Engineering
• /
• v.5 no.3
• /
• pp.232-241
• /
• 2000

Even though we have greater chances to accomplish successful collaborative design by utilizing recent proliferation of networks, current practices do not fully take advantage of the information infrastructure. There are so much data over the networks, but not enough knowledge about the data is available to users. The main objectives of the product data interface system proposed in this paper are to capture more knowledge on managing product data and to provide users effective search capability. We define the metadata model for product data defined in STEP AP 203 and manage the metadata from product data in a repository system. Because we utilize the standard formats such as STEP for product data and RDF for metadata, the proposed approach can be applied to various fields of industries independently on commercial products.

• Proceedings of the Korean Information Science Society Conference
• /
• 2012.06b
• /
• pp.405-407
• /
• 2012

학술 문서 내에서 테이블은 실험 결과, 정의, 요약하는 정보들을 함축하여 사용자에게 제공하는 역할을 한다. 즉 이러한 테이블을 학술 문서 내에서 탐색, 추출하여 검색에 이용하는 것은 학술 문서의 이해를 돕는 것과 더불어 학술 문서를 사용자가 직접 작성할 때에도 비슷한 형태의 테이블을 참조하여 형식에 맞는 테이블을 작성하는 데에 도움을 준다. 따라서 본 연구는 이러한 다양한 목적의 테이블 검색을 지원하기 위하여 문서로부터 자동으로 적합한 키워드를 추출하고 이를 통하여 문서와 유사한 테이블, 문서 내 테이블과 유사한 형식의 테이블을 검색하는 데 적합한 새로운 지능형 테이블 검색 시스템을 제안하며 이를 통해 기존에 존재하는 테이블 검색 시스템 알고리즘들과 성능 비교를 통해 향후 테이블 기반 검색 시스템 발전 가능성을 제시한다.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2016.05a
• /
• pp.235-236
• /
• 2016

The importance of construction management has been increasing due to the fact that complex construction projects blend several different industries depending on the traits of the construction. This research was conducted to search for a method to enhance efficiency in cost management of construction project and meet the need for reusability of accumulated construction information. The process of detailed estimation and methodology for using standard unit price information has been developed to strengthen the interoperability in cost information by utilizing a standard classification system. The concept of ontology is proposed as a method of connecting construction information based on a standard breakdown structure to increasing the connectivity of the cost information in the construction project. Therefore, construction information knowledge framework is developed in order to improve the efficiency of the detailed estimation work process.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.39 no.1
• /
• pp.16-21
• /
• 1990

A Knowledge based expert system is a computer program that emulates the reasoning process of a human expert in a specific problem domain. Expert system has the potential to solve a wide range of problems which require knowledge about the problem rather than a purely analytical approach. This papaer presents the application of knowledge based expert system to power system fault diagnosis. The contents of expert system develpped in this paper is judgement of fault section from a given alarm sets and production of all possible hypothesis for the single fault. Both relay failures and circuit breaker failures are considered simultaneously. Although many types of relay are used in actual system, experts recognize ones as several typical signals corresponding to the fault types. Therefore relays are classified into several types. The expert system is written in an artificial intelligence language "PROLOG" . Best-first search method is used for problem solving. Both forward chaining and backward chaining schemes are used in reasoning process. The application to a part of actual power system proves the availability of the developed expert system.

• Journal of Information Technology Applications and Management
• /
• v.26 no.1
• /
• pp.65-75
• /
• 2019

As the use of semantic web based on XML increases in the field of data management, a lot of studies to extract useful information from the data stored in ontology have been tried based on association rule mining. Ontology data is advantageous in that data can be freely expressed because it has a flexible and scalable structure unlike a conventional database having a predefined structure. On the contrary, it is difficult to find frequent patterns in a uniformized analysis method. The goal of this study is to provide a basis for extracting useful knowledge from ontology by searching for frequently occurring subgraph patterns by applying transaction-based graph mining techniques to ontology schema graph data and instance graph data constituting ontology. In order to overcome the structural limitations of the existing ontology mining, the frequent pattern search methodology in this study uses the methodology used in graph mining to apply the frequent pattern in the graph data structure to the ontology by applying iterative node chunking method. Our suggested methodology will play an important role in knowledge extraction.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.6
• /
• pp.1996-2011
• /
• 2021

To understand a trend is to explore the intricate process of how something or a particular situation is constantly changing or developing in a certain direction. This exploration is about observing and describing an unknown field of knowledge, not testing theories or models with a preconceived hypothesis. The purpose is to gain knowledge we did not expect and to recognize the associations among the elements that were suspected or not. This generally requires examining a massive amount of data to find information that could be transformed into meaningful knowledge. That is, looking through the lens of big-data analytics with an inductive reasoning approach will help expand our understanding of the complex nature of a trend. The current study explored the trend of well-being in South Korea using big-data analytic techniques to discover hidden search patterns, associative rules, and keyword signals. Thereafter, a theory was developed based on inductive reasoning - namely the hook, upward push, and downward pull to elucidate a holistic picture of how big-data implications alongside social phenomena may have influenced the well-being trend.

• Nutrition Research and Practice
• /
• v.10 no.2
• /
• pp.229-236
• /
• 2016

BACKGROUND/OBJECTIVES: The purpose of this study was to find out the level of knowledge on sugar-related nutrition among mothers with preschool children. SUBJECTS/METHODS: The study conducted a survey on 350 mothers whose children attended daycare. The dietary lives of the children and the nutritional knowledge of the mothers on sugar were checked. In order to analyze results, SPSS 18.0 was used. ANOVA and t-test were also performed to analyze recognition and educational needs. RESULTS: When the degree of nutritional knowledge was measured and analyzed, the results showed about 11 average points out of 15. The higher a group's nutritional knowledge, the better the dietary habits and activities were and the activities were more ccommon. The group with a low level of nutritional knowledge consumed more foods with high sugar content, but this difference was not statistically significant. Also the children from the group of mothers that provided nutritional education to their children were more likely to engage in better dietary habits and activities. CONCLUSIONS: 66.5% respondents did not know about policies to reduce sugar consumption, but most indicated that education on reducing sugar consumption is needed. Therefore, a government-driven search for efficient methods to campaign and publicize sugar reduction is needed in order to continuously provide appropriate education.