• Title/Summary/Keyword: modeling system

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A Study on Exploring Factors Influencing Military Security Level (Based on the Theory of Planned Behavior, Deterrence and Protection Motivation) (군(軍) 보안수준에 미치는 영향요인 탐색에 관한 연구 (계획 행동이론, 억제이론, 보호 동기 이론을 중심으로))

  • Jong-Hyoun Kim;Sang-Jun Ahn
    • Convergence Security Journal
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    • v.22 no.4
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    • pp.3-9
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    • 2022
  • Recently, as the environment of the 4th industrial revolution has arrived, the opening, sharing and convergence of data are actively being achieved in any organization. However, the opening and sharing of data inevitably leads to security vulnerability and there is ambivalence that is a threat that can affect the existence of an organization operated in the 4th industrial revolution environment. Especially security issues in the organization of the military can be a threat to the state, not the military itself, so it is always necessary to maintain a high level of security discipline. In this paper, 14 variables were selected through structural equation model applying theory of planned behavior, deterrence and protection motivation to find out the security level development measures by extracting factors that can affect security level. As a result, the theory of planned behavior that the security knowledge embodied through the usual security regulation education and evaluation affects the behavior was adopted, and the theory of deterrence and protection motivation showed the significance of the rejection level. In addition, it was confirmed that the variables that have the greatest impact on the military security level through the measured values of the three-year security audit were commanders and mental security. In conclusion, in order to improve the security level, it is suggested that security education, definite reward and punishment, and security system upgrading should be firmly established and mental security posture should be secured.

Development of Truck Axle Load Distribution Model using WIM Data (WIM 자료를 활용한 화물차 축하중 분포 모형 개발)

  • Lee, Dong Seok;Oh, Ju Sam
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.5D
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    • pp.821-829
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    • 2006
  • Traffic load comprise primary input to pavement design causing pavement damage. therefore it should be proceeded suitable traffic load distribution modeling for pavement design and analysis. Traffic load have been represented by equivalent single axle loads (ESALs) which convert mixed traffic stream into one value for design purposes. But there are some limit to apply ESALs to other roads because it is empirical value developed as part of the original AASHO(American Association of State Highway Officials) road test. There have been many efforts to solve these problems. Several leading country have implemented M-E(Mechanistic-Empirical) design procedures based on mechanical concept. As a result, they established traffic load quantification method using load distribution model known as Axle Load Spectra. This paper details Axle Load Spectra and presents axle load distribution model based on normal mixture distribution function using truck load data collected by WIM system installed in national highway. Axle load spectra and axle load distribution model presented in this paper could be useful for basic data when making traffic load quantification plan for pavement design, overweight vehicle permit plan and pavement maintenance cost plan.

A Meshless Method Using the Local Partition of Unity for Modeling of Cohesive Cracks (점성균열 모델을 위한 국부단위분할이 적용된 무요소법)

  • Zi, Goangseup;Jung, Jin-kyu;Kim, Byeong Min
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.5A
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    • pp.861-872
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    • 2006
  • The element free Galerkin method is extended by the local partition of unity method to model the cohesive cracks in two dimensional continuum. The shape function of a particle whose domain of influence is completely cut by a crack is enriched by the step enrichment function. If the domain of influence contains a crack tip inside, it is enriched by a branch enrichment function which does not have the LEFM stress singularity. The discrete equations are obtained directly from the standard Galerkin method since the enrichment is only for the displacement field, which satisfies the local partition of unity. Because only particles whose domains of influence are influenced by a crack are enriched, the system matrix is still sparse so that the increase of the computational cost is minimized. The condition for crack growth in dynamic problems is obtained from the material instability; when the acoustic tensor loses the positive definiteness, a cohesive crack is inserted to the point so as to change the continuum to a discontiuum. The crack speed is naturally obtained from the criterion. It is found that this method is more accurate and converges faster than the classical meshless methods which are based on the visibility concept. In this paper, several well-known static and dynamic problems were solved to verify the method.

Stochastic Self-similarity Analysis and Visualization of Earthquakes on the Korean Peninsula (한반도에서 발생한 지진의 통계적 자기 유사성 분석 및 시각화)

  • JaeMin Hwang;Jiyoung Lim;Hae-Duck J. Jeong
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.11
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    • pp.493-504
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    • 2023
  • The Republic of Korea is located far from the boundary of the earthquake plate, and the intra-plate earthquake occurring in these areas is generally small in size and less frequent than the interplate earthquake. Nevertheless, as a result of investigating and analyzing earthquakes that occurred on the Korean Peninsula between the past two years and 1904 and earthquakes that occurred after observing recent earthquakes on the Korean Peninsula, it was found that of a magnitude of 9. In this paper, the Korean Peninsula Historical Earthquake Record (2 years to 1904) published by the National Meteorological Research Institute is used to analyze the relationship between earthquakes on the Korean Peninsula and statistical self-similarity. In addition, the problem solved through this paper was the first to investigate the relationship between earthquake data occurring on the Korean Peninsula and statistical self-similarity. As a result of measuring the degree of self-similarity of earthquakes on the Korean Peninsula using three quantitative estimation methods, the self-similarity parameter H value (0.5 < H < 1) was found to be above 0.8 on average, indicating a high degree of self-similarity. And through graph visualization, it can be easily figured out in which region earthquakes occur most often, and it is expected that it can be used in the development of a prediction system that can predict damage in the event of an earthquake in the future and minimize damage to property and people, as well as in earthquake data analysis and modeling research. Based on the findings of this study, the self-similar process is expected to help understand the patterns and statistical characteristics of seismic activities, group and classify similar seismic events, and be used for prediction of seismic activities, seismic risk assessments, and seismic engineering.

Prediction of Water Storage Rate for Agricultural Reservoirs Using Univariate and Multivariate LSTM Models (단변량 및 다변량 LSTM을 이용한 농업용 저수지의 저수율 예측)

  • Sunguk Joh;Yangwon Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1125-1134
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    • 2023
  • Out of the total 17,000 reservoirs in Korea, 13,600 small agricultural reservoirs do not have hydrological measurement facilities, making it difficult to predict water storage volume and appropriate operation. This paper examined univariate and multivariate long short-term memory (LSTM) modeling to predict the storage rate of agricultural reservoirs using remote sensing and artificial intelligence. The univariate LSTM model used only water storage rate as an explanatory variable, and the multivariate LSTM model added n-day accumulative precipitation and date of year (DOY) as explanatory variables. They were trained using eight years data (2013 to 2020) for Idong Reservoir, and the predictions of the daily water storage in 2021 were validated for accuracy assessment. The univariate showed the root-mean square error (RMSE) of 1.04%, 2.52%, and 4.18% for the one, three, and five-day predictions. The multivariate model showed the RMSE 0.98%, 1.95%, and 2.76% for the one, three, and five-day predictions. In addition to the time-series storage rate, DOY and daily and 5-day cumulative precipitation variables were more significant than others for the daily model, which means that the temporal range of the impacts of precipitation on the everyday water storage rate was approximately five days.

The Prediction of the Helpfulness of Online Review Based on Review Content Using an Explainable Graph Neural Network (설명가능한 그래프 신경망을 활용한 리뷰 콘텐츠 기반의 유용성 예측모형)

  • Eunmi Kim;Yao Ziyan;Taeho Hong
    • Journal of Intelligence and Information Systems
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    • v.29 no.4
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    • pp.309-323
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    • 2023
  • As the role of online reviews has become increasingly crucial, numerous studies have been conducted to utilize helpful reviews. Helpful reviews, perceived by customers, have been verified in various research studies to be influenced by factors such as ratings, review length, review content, and so on. The determination of a review's helpfulness is generally based on the number of 'helpful' votes from consumers, with more 'helpful' votes considered to have a more significant impact on consumers' purchasing decisions. However, recently written reviews that have not been exposed to many customers may have relatively few 'helpful' votes and may lack 'helpful' votes altogether due to a lack of participation. Therefore, rather than relying on the number of 'helpful' votes to assess the helpfulness of reviews, we aim to classify them based on review content. In addition, the text of the review emerges as the most influential factor in review helpfulness. This study employs text mining techniques, including topic modeling and sentiment analysis, to analyze the diverse impacts of content and emotions embedded in the review text. In this study, we propose a review helpfulness prediction model based on review content, utilizing movie reviews from IMDb, a global movie information site. We construct a review helpfulness prediction model by using an explainable Graph Neural Network (GNN), while addressing the interpretability limitations of the machine learning model. The explainable graph neural network is expected to provide more reliable information about helpful or non-helpful reviews as it can identify connections between reviews.

A Study on the Information Protection Intention of Digital Healthcare Service Providers (디지털 헬스케어 서비스 제공자의 정보보호의도에 관한 연구)

  • Yang, Chang-Gyu
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.4
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    • pp.163-172
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    • 2022
  • This study investigates the IPI (Information Protection Intention) of DHS (Digital Healthcare Service) providers by introducing PMT (Protection Motivation Theory). This study examines the effects of protection motivation, such as threat appraisal and coping appraisal, on IPI, such as ICI(Induction Control Intention) and SDI(Self Defense Intention). The research model, based on the PMT, adopted severity, vulnerability, reaction efficacy and self-efficacy as independent variables. The research model was validated through quantitative research, a survey of 222 DHS providers in South Korea, using structural equation modeling. The results show that (1) a clear awareness of the consequences of security threats increases the understanding of DHS providers on the severity of closure of healthcare information, and thus may decreases abuse of DHS by providers; (2) user confidence and satisfaction on the security system may make them be confident that they can handle the closure of healthcare information by themselves; and (3) although DHS providers are realizing the consequences of closure of healthcare information, they think that they are unlikely to encounter such situations. As a result of this study, venture companies that provide DHS need to provide contents that can continuously increase providers' security level in order to increase providers' information protection intention. It suggests that IPI is important through trust of healthcare service providers.

A Study on the Effect of the Linkage among Internal Stakeholders in Small Businesses on Industrial Accident: Focusing on the Safety Commiment of the Business Owner, Safety Leadership of the Supervisor and the Participation of Workers (소규모 사업장에서 내부 이해관계자들 간의 연계가 산업재해에 미치는 영향: 사업주의 안전의지, 관리감독자의 안전리더십, 근로자 참여를 중심으로)

  • Jin-Woo Choi;Ik-Mo Lee;Hong-Kwan Kim;Duk-Han Kim;Young-Woo Chon
    • Journal of the Korea Safety Management & Science
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    • v.25 no.4
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    • pp.45-56
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    • 2023
  • This study attempted to provide implications by analyzing the impact of business Owner's safety commitment on industrial accidents and examining the mediating role of management supervisors' safety leadership and worker participation. Analysis was conducted on 2,067 manufacturing sites with 20 to 50 employees in the 10th Occupational Safety and Health Survey data. SPSS waw used to secure the reliability of the measurement variable. Hypothesis vertification was carried out after securing the suitability and validity of the structural model using AMOS. The direct impact of three latent variables on industrial accidents was confirmed: the business owner's safety commitment, the management supervisor's safety leadership, and the worker participation. The employer's safety will and the management supervisor's safety leadership do not directly affect industial accidents, but it has been verified that worker participation has a diret impact on industrial accident reduction. In addition, it has been confirmed that the safety leadership and worker participation of the management. Supervior have a complete mediating effect on the reduction of industrial accidents by mediating with the safety leadership of the management supervior and the participation of the workers. This study analyzed the impact on industrial accidents by dividing the stakeholders constituting the workplace into three classes: business owners, superviors, and workers, but the results suggest that employers and all workers inside the workplace may be organically linked to achieving the goal of reducing industrial accidents. Therefore, in order to establish an autonomous safety management system for safety and health at workerplaces, efforts are needed to reduce industrial accidents in their respective location by forming an organic community among internal stakeholders.

Modeling of Scattered Signal from Ship Wake and Experimental Verification (항적 산란신호의 모델링과 실험적 검증)

  • Ji, Yoon-Hee;Lee, Jae-Hoon;Kim, Jea-Soo;Kim, Jung-Hae;Kim, Woo-Shik;Choi, Sang-Moon
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.1
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    • pp.10-18
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    • 2009
  • A moving surface vessel generates a ship wake which contains a cloud of micro-bubbles with radii ranging between $8{\sim}200{\mu}m$. Such micro-bubbles can be detected by active sonar system for more than ten minutes depending on the size and speed of the surface vessel. In this paper, a reverberation model for the ship wake is presented. The developed model consists of the acoustic scattering model due to the distribution of the micro-bubbles and the kinematic model for the moving active sonar. The acoustic scattering model is based on the volume integration, where the volume scattering strengths are obtained from the spatial distribution of micro-bubbles. Since the directivity and look-direction of active sonar are important factors for moving active sonar, the kinematic model utilizes the Euler transformation to obtain the relative motion between the global and local coordinates. In order to verify the developed model, a series of sea experiment was executed in September 2007 to obtain the spatial-temporal distribution of a bubble cloud, and analyzed to be compared with the simulation results.

The Impact of the Government's R&D Support and the Introduction of Stock Options by Venture Companies on the Innovation Achievement of Venture Companies (정부의 R&D 지원과 벤처기업의 스톡옵션제도 활용이 벤처기업의 혁신성과에 미치는 영향)

  • Kim, Ho-hyun;Park, Hyung-jun
    • Journal of Venture Innovation
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    • v.7 no.1
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    • pp.17-39
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    • 2024
  • The purpose of this study was to analyze the effect of the government's R&D support and the use of stock options by venture companies on the innovation of venture companies, that is, innovation capabilities and innovation performance. An empirical analysis was conducted using the partial least squares structural equation modeling (PLS-SEM) method using the data from the detailed survey of venture companies conducted on domestic venture confirmation companies. As a result of the analysis, it was found that the benefit of government R&D support had a positive (+) effect on strengthening the innovation capabilities of venture companies, and R&D support also had a positive (+) effect on the innovation performance of venture companies. Next, it was found that the use of stock options by venture companies had a positive (+) effect on the reinforcement of the innovation capabilities of companies and a positive (+) effect on the innovation performance of venture companies. In addition, it was found that the innovation capabilities of venture companies significantly mediate between the government's R&D support and the use of stock options by venture companies and the innovation performance of companies. These analysis results show that the government's R&D support and the use of stock option systems can play a meaningful role in the innovation of venture companies, and also show that the innovation capabilities of venture companies have an important meaning in the process of innovation. Therefore, it is necessary to continue the stance of R&D support for ventures and at the same time to introduce multi-faceted policy measures to support corporate capacity building, and legal and institutional maintenance and policy support to revitalize the stock option system need to be continuously provided.