• Convergence Security Journal
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• v.14 no.5
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• pp.37-47
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• 2014

A Trojan malicious code is one of largest malicious codes and has been known as a virus that causes damage to a system as itself. However, it has been changed as a type that picks user information out stealthily through a backdoor method, and worms or viruses, which represent a characteristic of the Trojan malicious code, have recently been increased. Although several modeling methods for analyzing the diffusion characteristics of worms have proposed, it allows a macroscopic analysis only and shows limitations in estimating specific viruses and malicious codes. Thus, in this study an ESP model that can estimate future occurrences of Trojan malicious codes using the previous Trojan data is proposed. It is verified that the estimated value obtained using the proposed model is similar to the existing actual frequency in causes of the comparison between the obtained value and the result obtained by the Markov chain.

• Journal of Internet of Things and Convergence
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• v.7 no.2
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• pp.13-19
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• 2021

It is analyzed that the energy pattern is affected by the social matters of the disease trend where the energy consumption has been reduced following the depression of the national economy. The campaign of social distance for the people has been done by voluntary or legally due to the epidemic of the Coronavirus Disease 2019 (COVID-19). Some economic stimulus policies have been done in some countries including the United States, South Korea, and some others. It is shown the susceptible, infectious, and recovered (SIR) modeling applied by system dynamics (SD) where the logical modeling is constructed with S, I, and R. Especially, the I is connected with Society including Population, Race, and Maturity. In addition, Economy and Politics are connected to Income, GDP, Resources, President, Popularity, Ruling Government, and Leadership. The graph shows the big jump on 2020 April when is the starting month of the S value multiplication. This shows the effect of the COVID-19 and its related post-pandemic trend. The trends of OECD and non-OECD are very similar and the effect of the virus hazards causes significantly to the economic depressions.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.331-350
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• 2022

This study aims to understand topics of incivility related to COVID-19 from analyzing Twitter posts including COVID-19-related hate speech. To achieve the goal, a total of 63,802 tweets that were created between December 1st, 2019, and August 31st, 2021, covering three targets of hate speech including region and public facilities, groups of people, and religion were analyzed. Frequency analysis, dynamic topic modeling, and keyword co-occurrence network analysis were used to explore topics and keywords. 1) Results of frequency analysis revealed that hate against regions and public facilities showed a relatively increasing trend while hate against specific groups of people and religion showed a relatively decreasing trend. 2) Results of dynamic topic modeling analysis showed keywords of each of the three targets of hate speech. Keywords of the region and public facilities included "Daegu, Gyeongbuk local hate", "interregional hate", and "public facility hate"; groups of people included "China hate", "virus spreaders", and "outdoor activity sanctions"; and religion included "Shincheonji", "Christianity", "religious infection", "refusal of quarantine", and "places visited by confirmed cases". 3) Similarly, results of keyword co-occurrence network analysis revealed keywords of three targets: region and public facilities (Corona, Daegu, confirmed cases, Shincheonji, Gyeongbuk, region); specific groups of people (Coronavirus, Wuhan pneumonia, Wuhan, China, Chinese, People, Entry, Banned); and religion (Corona, Church, Daegu, confirmed cases, infection). This study attempted to grasp the public's anti-citizenship public opinion related to COVID-19 by identifying domestic COVID-19 hate targets and keywords using social media. In particular, it is meaningful to grasp public opinion on incivility topics and hate emotions expressed on social media using data mining techniques for hate-related to COVID-19, which has not been attempted in previous studies. In addition, the results of this study suggest practical implications in that they can be based on basic data for contributing to the establishment of systems and policies for cultural communication measures in preparation for the post-COVID-19 era.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.267-291
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• 2021

Due to the global pandemic caused by COVID-19 in 2020, there have been major changes in the education sites. Universities have fully introduced remote learning, which was considered as an auxiliary education, and non-face-to-face classes have become commonplace, and professors and students are making great efforts to adapt to the new educational environment. In order to improve the quality of non-face-to-face lectures amid these changes, it is necessary to study the factors affecting lecture satisfaction. Therefore, This paper presents a new methodology using big data to identify the factors affecting university lecture satisfaction changed before and after COVID-19. We use Topic Modeling method to analyze lecture reviews before and after COVID-19, and identify factors affecting lecture satisfaction. Through this, we suggest the direction for university education to move forward. In addition, we can identify the factors of satisfaction and dissatisfaction of lectures from multiangle by establishing a topic classification model with an F1-score of 0.84 based on KoBERT, a deep learning language model, and further contribute to continuous qualitative improvement of lecture satisfaction.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.157-160
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• 2000

This paper deals with the fuzzy modeling for the complex and uncertain system in which conventional and mathematical models may fail to give satisfactory results. mGA(messy Genetic Algorithm) has more effective and adaptive structure than sGA with respect to using changeable-length string and VEGA(Virus Evolution Genetic) Algorithm) can search the global and local optimal solution simultaneously with reverse transcription operator and transduction operator. Therefore in this paper, the optimal fuzzy model is obtained using Virus-messy Genetic Algorithm(Virus-mGA). In this method local information is exchanged in population so that population may sustain genetic divergence. To prove the surperioty of the proposed approach, we provide the numerical example.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.1130-1135
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• 2009

Avian Influenza is an infectious desease of birds. The infection can cause a wide spectrum of symptoms in birds, ranging from mild illness to a rapidly fatal diseases which might bring a tremendous economic loss to poultry farms[1]. It can also give fatal diseases to human. Therefore it is important to surveil wildbirds that are primary transportation of avian influenza. This report showed a relationship between avian influenza and a habitat of wildbirds using system dynamics, and concluded with suggestion for surveilance.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.522-524
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• 1999

This paper addresses the systematic approach to the fuzzy modeling of the class of complex and uncertain nonlinear systems. While the conventional genetic algorithm (GA) only searches the global solution, Virus-Evolutionary Genetic Algorithm(VEGA) can search the global and local optimal solution simultaneously. In the proposed method the parameter and the structure of the fuzzy model are automatically identified at the same time by using VEGA. To show the effectiveness and the feasibility of the proposed method, a numerical example is provided. The performance of the proposed method is compared with that of conventional GA.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.11a
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• pp.171-179
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• 2005

Computer virus modeling and simulation research has been conducted with focus on the network vulnerability analysis. However, computer virus generally shows the biological virus characters such as proliferation, reproduction and evolution. Therefore it is necessary to research the computer virus modeling and simulation using Artificial Life. The approach of computer modeling and simulation using the Artificial Life technology Provides the efficient analysis method for the effects on the network by computer virus and the behavioral mechanism of the computer virus. Hence this paper proposes the methodology of computer virus modeling and simulation using Artificial Life, which may be contribute the research on the computer virus vaccine.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.478-481
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• 2002

본 논문에서는 생명체의 면역계에서 중요한 역할을 하는 세포독성 T세포의 생성과정의 하나인 긍정선택(positive selection)과 부정 선택(negative selection)을 모델링하여 침입에 의한 데이터 변경과 바이러스에 의한 데이터 감염 등을 탐지할 때 가장 중요한 요소인 변경 검사 알고리즘을 개발하였다. 제안한 알고리즘은 면역세포의 생성시 MHC 인식부를 형성해 주는 긍정 선택을 자기 인식 알고리즘으로 구현하여 컴퓨터에서 자기로 인식해야하는 파일이나 기능에 대해 MHC 인식부를 형성하고, 또한 항원 인식부를 형성하는 부정 선택을 이용해 변형 검지기(anomaly detector)를 구성한다. 따라서 제안한 알고리즘은 실제 면역세포와 마찬가지로 자신과 침입자 모두에 대한 인식기를 가지고 변경을 탐지하게 된다. 시뮬레이션을 통하여 자기파일의 일부가 변경되었을 때와 블록이 변경되었을 때에 대하여 두 가지 방법을 이용한 변경 검사 알고리즘의 특성과 유효성을 밝힌다.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2006.04a
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• pp.76-81
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• 2006

창녕군 증산리 지역은 신규 취수원 확보 일환으로 강변여과 방식 취수 가능성이 한국수자원공사에 의해서 평가되고 있는 지역이다. 강변여과 방식 취수의 타당성 평가를 위해 현장 지질조사, 시추조사, 전기 비저항 탐사 및 고해상도 탄성파 탐사를 수행하였다. 또한 대상 연구지역에서의 개략적 취수 가능량 산정을 위해 모델링 평가가 수행되었으며, 개별 정호에 대한 양수량 산정을 위해 시험 정호를 설치하였다. 현장 시추 조사와 시료에 대한 입도 분석 결과, 연구 지역의 충적층 두께는 35m 전후이며, 주 대수층 구간은 지표하 $25{\sim}35m$인 것으로 추정되었다. 또한 주 대수층 구간의 수리전도도는 $10^{-2}cm/sec$ 이상으로 주로 모래섞인 자갈층으로 구성되어있는 것으로 평가되었다. 또한 전기비저항 조사 결과는 부분적으로 매우 낮은 비저항 분포 지층을 보여주고 있으며, 이는 주로 실트 및 점토로 된 지층이 부분적으로 퇴적되어 있음을 지시하며, 고해상도 탄성파 탐사 결과는 전반적으로 지하수위는 지표하부 5m 전후에 분포하고, 충적층의 하부 경계는 35 내지 45m인 것으로 해석되었다. 지하수 모델링을 통해, 취수 목표량인 180,000톤/일은 주대수층까지의 지하수위 강하 없이 확보 가능할 것으로 평가되었다. 또한 개별 정호의 산출 특성을 평가하기 위해 시험 정호를 설치하여, 실제 2,700톤/일 예비 양수 시험을 수행하였다. 예비 양수 시험 결과, 양수정에서의 수위 강하는 개략 10m, 양수정관측정에서는 약 0.3m의 수위강하만이 관찰되었으며, 양수 영향권이 수 십 m를 넘지 않을 것으로 판단되었다.서의 S97과 JBR의 세포감염 억제율은 3.85%와 3.63%로 나타났다. $textsc{k}$-casein, CU는 로타바이러스 S97과 JBR에 대해 농도 2000UM에서 97%이상의 억제효과를 나타냈으며, sialic acid는 억제효과가 거의 없었다. K-casein, GMP는 송아지뿐만 아니라 유아의 로타바이러스에 의한 설사를 억제할 수 있을 것으로 기대된다.을 향상하기 위해서는 이러한 부위에 대한 미생물 오염을 낮출 수 있는 세심한 현장 품질관리가 필요하다.en and adolescents, analysed by country, age group and gender. The paper discusses the places young consumers can turn to in trying to fulfil their growing consumer needs. It also examines how much money is at their disposal. It then concludes by considering the influence of "financial socialization" on how young people deal with money.nsumption visions based on the various perspectives, consumers are influenced in the apparel buying decision-making. Many subjects reported experiencing positive affect when imagining positive outcomes of produc