• Annual Conference of KIPS
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• 2010.11a
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• pp.58-61
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• 2010

최근 인터넷이 보편화되면서 검색에 대한 관심도가 높아지고 있다. 특히 사용자는 정확한 키워드의 입력 없이도 자신이 원하는 검색을 하고 싶어 한다. 그러한 욕구를 충족시키기 위해서 네이트의 '시맨틱', MSN의 'Bing' 등이 새로 제작되어 지고 있으며 네이버, google 등 대형 포털 사이트들도 검색분야에 투자를 아끼지 않고 있다. 본 논문은 사용자중심의 검색을 구현하기 위해서 패턴을 분석하여 연관규칙을 사용하여 검색시간을 단축함을 물론 검색결과의 정확성을 높였다. 구현을 위해서 네이버 사이트의 블로그로 검색의 범위를 한정 하여 데이터를 분석, 관리 및 시각화 하는 사이트를 개발하였다. 또한 검색을 위한 크롤러, 루씬 등을 실질적으로 직접 개발 활용 하였다. 시제품의 시험결과 정답사이트 도출 정확도는 google에 비해 20%, 재현율은 7.2%의 향상성을 보였다.

• Journal of the Korea Computer Industry Society
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• v.5 no.5
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• pp.761-770
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• 2004

The multicarrier direct sequence code-division (MC-DS/CDMA) is a well-known multiple access and data transmission scheme that is applicable for various mobile and wireless communications. Particularly for modern, smart vehicles equipped with multiple sensors, MC-DS/CDMA is one of the possible means for giving the sensors to get connected one another for sending and receiving messages and control information. For intra-vehicalur communicaiton and networking applications, we have proposed a novel MC-DS/CDMA multiple access and data transmission scheme incorporating a new idea of inserting sub-symbol based cyclic prefixes for compromising inter-symbol interference. In the performance investigation of our MC-DS/CDMA, we have looked into system performances related to bandwidth utiltzation, coding gain, and multiple number of sensors. Since the channel delay is comparatively shorter inside of vehicle than any other general mobile channels, the proposed scheme can be a successful candidate for networking wireless sensors simultaneously operting in an intelligent vehicle.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.244-251
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• 2014

In this study, we give a detailed account of normal and abnormal state of GIS(Gas Insulated Switch-gear) using the preventive diagnostic technology. And it is based on the analysis and diagnosis for storing data of GIS by intelligent GIS monitoring system. The wave shape of GIS sound is similar to noise and is systematically generated by discharge and its corona sound. Therefore, in this paper, to classify normal and abnormal GIS sound. We could discriminate between normal and abnormal case using level crossing rate(LCR) and spectrogram energy rate.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.33-43
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• 2012

Semantic web is utilized to construct advanced information service by using semantic relationships between entities. Text mining can be applied to generate semantic relationships from unstructured data resources. In this study, ontology schema guideline, ontology instance generation, disambiguation of same name by text mining and advanced historical people finding service by reasoning have been proposed. Various relationships between historical event, organization, people, which are created by domain experts, are linked to literatures of National Institute of Korean History (NIKH). It improves the effectiveness of user access and proposes advanced people finding service based on relationships. In order to distinguish between people with the same name, we compares the structure and edge, nodes of personal social network. To provide additional information, external resources including thesaurus and web are linked to all of internal related resources as well.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.203-211
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• 2006

Today, Internet covers a world wide range and most appliances of our life are linked to network from enterprise server to household electric appliance. Therefore, the importances of administrable framework that can grasp network state by real-time is increasing day by day. Our objective in this paper is to describe a network weather report framework that monitors network traffic and performance state to report a network situation including traffic status in real-time. We also describe a mobile agent architecture that collects state information in each network segment. The framework could inform a network manager of the network situation. Through the framework. network manager accumulates network data and increases network operating efficiency.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.33-39
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• 2019

As cyber attack methods are becoming more intelligent, incidents such as security breaches and international crimes are increasing. In order to predict and respond to these cyber attacks, the characteristics, methods, and types of attack techniques should be identified. To this end, many security companies are publishing security intelligence reports to quickly identify various attack patterns and prevent further damage. However, the reports that each company distributes are not structured, yet, the number of published intelligence reports are ever-increasing. In this paper, we propose a method to extract structured data from unstructured security intelligence reports. We also propose an automatic intelligence report analysis system that divides a large volume of reports into sub-groups based on their topics, making the report analysis process more effective and efficient.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.1-14
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• 2023

Soybeans are one of the world's top five staple crops and a major source of plant-based protein. Due to their susceptibility to climate change, which can significantly impact grain production, the National Agricultural Science Institute is conducting research on crop phenotypes through growth analysis of various soybean varieties. While the process of capturing growth progression photos of soybeans is automated, the verification, recording, and analysis of growth stages are currently done manually. In this paper, we designed and trained a YOLOv5s model to detect soybean leaf objects from image data of soybean plants and a Convolution Neural Network (CNN) model to judgement the unfolding status of the detected soybean leaves. We combined these two models and implemented an algorithm that distinguishes layers based on the coordinates of detected soybean leaves. As a result, we developed a program that takes time-series data of soybeans as input and performs growth analysis. The program can accurately determine the growth stages of soybeans up to the second or third compound leaves.

• Journal of Life Science
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• v.33 no.8
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• pp.663-679
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• 2023

This review analyzes research trends related to new drug development using artificial intelligence from 2010 to 2022. This analysis organized the abstracts of 2,421 studies into a corpus, and words with high frequency and high connection centrality were extracted through preprocessing. The analysis revealed a similar word frequency trend between 2010 and 2019 to that between 2020 and 2022. In terms of the research method, many studies using machine learning were conducted from 2010 to 2020, and since 2021, research using deep learning has been increasing. Through these studies, we investigated the trends in research on artificial intelligence utilization by field and the strengths, problems, and challenges of related research. We found that since 2021, the application of artificial intelligence has been expanding, such as research using artificial intelligence for drug rearrangement, using computers to develop anticancer drugs, and applying artificial intelligence to clinical trials. This article briefly presents the prospects of new drug development research using artificial intelligence. If the reliability and safety of bio and medical data are ensured, and the development of the above artificial intelligence technology continues, it is judged that the direction of new drug development using artificial intelligence will proceed to personalized medicine and precision medicine, so we encourage efforts in that field.

• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.1-7
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• 2013

A personalized recommendation system is a recommendation system that recommends goods to users' taste by using an automated information filtering technology. A collaborative filtering method in this technology is a method that discriminates certain types, which represent similar patterns. Thus, it is possible to estimate the pain strength based on the data of the patients who have the past similar types and extract related conditions according to the similarity in classified patients. A representative method using the Pearson correlation coefficient for extracting the similarity weight may represent inexact results as the sample data is small according to the amount of data. Also, it has a disadvantage that it is not possible to fast draw results due to the increase in calculations as a square scale as the sample data is large. In this paper, the excellency of the intelligence pain nursing intervention u-health system implemented by comparing the scale and similarity group of the sample data for extracting significant data is verified through the evaluation of MAE and Raking scoring. Based on the results of this verification, it is possible to present basic data and guidelines of the pain of patients recognized by nurses and that leads to improve the welfare of patients.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.51-57
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• 2021

Quite a few elementary school teachers began to utilize AI technology in order to provide students with customized, intelligent information services in recent years. However, learning principles of AI may be as important as utilizing AI in everyday life because understanding principles of AI can empower them to buildup adaptability to changes in highly technological world. In the paper, 'Linear Regression Algorithm' is selected for teaching AI-based prediction system to solve real world problems suitable for elementary students. A simulation program written in Scratch was developed so that students can find a solution of linear regression model using the program. The paper shows that students have learned analyzing data as well as comparing the accuracy of the prediction model. Also, they have shown the ability to solve real world problems by finding suitable prediction models.