Earticle

본 연구의 핵심은 공간상에 빈번하게 발생하는 범죄의 위험지점(Hotspot)을 찾고, 방범 CCTV 적정설치위치를 도출하는 것이 목적이다. 범죄의 특징 중 하나가 과거 발생지역중심 으로 군집하는 현상을 보이며 또한 이런 범죄들은 상호연관성이 강하다는 것이다. 범죄이력 을 통해 군집이 발생한 원인과 범죄에 영향을 미치는 변수를 찾을 수 있다. 방법은 전통적인 OLS모델 외에 공간적 자기상관성을 포함하는 공간시차모델, 공간오차모델을 적용하여 5대 범죄율과 절도율, 외국인 거주율에 영향을 미치는 변수를 선정하였다. 5대 범죄에 영향을 미 치는 변수는 생활보호대상자율과 풍속업소율에는 양(+)의 부호로, 가로등 밀집도에는 음(-)의 부호로 나타나. 생활보호대상자가 군집한 지역, 풍속업소 군집지역, 다문화가정이 많은 지역, 가로등 밀집도가 낮은 지역을 중첩하여 위험공간으로 선정하고, 이를 근거로 기존 CCTV영 역이 Hotspot의 46%를 담당하고 있다는 사실을 밝혀냈다. 현재 운영 중인 CCTV를 감안한 상 태에서 위험지점을 커버할 신규물량은 총 89대로 나타났다.

The main purpose of this study is to find the hotspots of crimes that occur frequently in the space and to derive the appropriate CCTV installation location. One of the characteristics of crime is clustered around past occurrence area, and these crimes are strongly correlated. It is also possible to find the cause of the clusters and the variables that affect the crime through the history of the crime. In addition to the traditional OLS model, spatial differential model including spatial autocorrelation and spatial error model were used to select the variables influencing the five major crime rate, the theft rate and the foreign resident rate. The variables affecting the Five major crimes were positive (+) sign for the welfare and the rate of the bar cluster rate, and negative (-) for the street density. The CCTV area occupies 46% of the hotspots based on the overlapping of the areas where the elderly people are crowded, the bar cluster, many multicultural families, and the areas with low density of street lamps. It turned out. Taking into account the current CCTV operation, the total number of new cases to cover the risk point was 89.

Purpose: Based on the health belief model and theory of planned behavior, this study investigated how age group (adolescence and emerging adulthood) moderated the relative effects of perceived susceptibility, perceived severity, and subjective norms on preventive behavior against coronavirus disease 2019 (COVID-19). Methods: This secondary data analysis utilized data from adolescents (n=272) and emerging adults (n=239). Hierarchical multiple regression analysis was performed to test the moderating effect of age group on the relationships among variables. Results: Higher perceived susceptibility (β=.21, p<.001), perceived severity (β=.14, p=.002), subjective norms (friends) (β=.26, p<.001), subjective norms (parents) (β=.44, p<.001), and subjective norms (schools) (β=.28, p<.001) enhanced COVID-19 preventive behaviors. Moderated regression analysis showed that subjective norms (friends and school) impacted preventive behavior in adolescents more than in emerging adults. Conclusion: Given the need to increase perceived susceptibility and severity among adolescents and emerging adults, these findings provide baseline data for designing effective COVID-19 prevention interventions that consider the developmental characteristics of different age groups. Interventions by health centers at universities can strengthen COVID-19 preventive behavior among emerging adults. As adolescents are influenced by friends, their peer roles must be strengthened to enhance adherence to COVID-19 preventive guidelines.

This study aims to develop a predictive model for student counseling support by identifying key individual factors encountered in university life, such as academic performance, financial conditions, psychological factors, and campus environment, as explanatory variables. Using logistic regression (logit model), the model was constructed to predict academic persistence and dropout, set as binary response variables, and validated for consistency through the support index. Additionally, the consistency of the dropout prediction model based on the logit model was cross-validated using a classification model with CART (Classification and Regression Tree) to determine which model or approach provided superior results. Modeling and comparing 2,000 simulated data points yielded similar results. All explanatory variables, except gender, were significant (p < .05), and, considering odds ratios, the number of leaves of absence (1.7818) and academic warnings (1.2921) had strong positive effects on dropout likelihood. Conversely, academic year, number of enrolled semesters, and GPA showed a negative effect on dropout probability. From a practical perspective for system implementation and operation, the logit model proved more efficient for constructing and applying the prediction model.

Purpose: This study was done to examine actor and partner effect of dementia knowledge, self-efficacy and depression on dementia preventive behavior in elderly couples. Methods: Participants were 115 couples aged 60 years or over who met eligibility criteria. All measures were self-administered. Data were analyzed using SPSS 18.0 and AMOS 18.0 program. Results: Dementia knowledge in elderly couples showed actor and partner effect on dementia preventive behavior. Self-efficacy in the wife did not have direct effects on dementia preventive behavior, but showed indirect effects through dementia knowledge. Self-efficacy in the husband showed direct effects on dementia preventive behavior and indirect effects through dementia knowledge. Wife's depression had direct actor effect on dementia preventive behavior and indirect effect through self-efficacy and dementia knowledge. Husband's depression did not have direct actor effect on dementia preventive behavior, but indirect effect through self-efficacy and dementia knowledge. Effect size of wives' dementia knowledge, self-efficacy and depression on dementia preventive behavior was larger than that of husbands'. Dementia preventive behavior, dementia knowledge and depression had a mutual effect. Conclusion: Results indicate that to promote dementia preventive activity in elderly couples, programs should be conducted for both of the couple, but focused differently for wife and husband.

With the advance information system technologies used in the world transition to Internet Protocol version 6 has begun and will continue. However IPV6 standards are immature and are some cases still in progress. Within infrastructure control system the advantage of moving to an IPV6 networking protocol is associated with addressing the potentially large increase in the number sensors collecting data from the infrastructure system. However, although there are advantages a pressing issue of security lie beneath. The immaturity of IPV6 presents a lot of security threats which are presented in this paper and post recommendations as countermeasures.

In the way of personal health assessment is a subjective health evaluation and objective evaluation of this study affect health behavior practices to target a sample of a national scale in order to mitigate the limitations with the existing research on each of the subjective health evaluation, objective health assessment the correlation between health behavior practices impact relationships, behavioral health practice in subjective health evaluation among health assessment and health practices and determine the impact of actions related to objective health assessment to confirm. This research was to find the association preventive health practice behavior using big data to health assessment. Of the preventive health behavior practices we studied, adequate sleep and regular exercise positively influenced self-rated health (SRH), whereas attempts to quit or restrict drinking negatively influenced it. And, of the preventive health behavior practices, the habit of eating breakfast and regular health check-up positively influenced a disease prevalence rate, i.e., an objective assessment of health. The findings suggest that people who make more efforts to quit or restrict drinking are more likely to assess their own health as poor. The finding that a disease prevalence rate increased with such preventive health behavior practices as eating breakfast and getting regular health check-up can be interpreted as showing that those behaviors were required by the physician instruction and the use of medication. The study shows that preventive health behavior practices can have a positive or negative relationship with SRH and also with objective health assessment.

Purpose: Based on the health belief model and theory of planned behavior, this study investigated how age group (adolescence and emerging adulthood) moderated the relative effects of perceived susceptibility, perceived severity, and subjective norms on preventive behavior against coronavirus disease 2019 (COVID-19). Methods: This secondary data analysis utilized data from adolescents (n=272) and emerging adults (n=239). Hierarchical multiple regression analysis was performed to test the moderating effect of age group on the relationships among variables. Results: Higher perceived susceptibility (β=.21, p<.001), perceived severity (β=.14, p=.002), subjective norms (friends) (β=.26, p<.001), subjective norms (parents) (β=.44, p<.001), and subjective norms (schools) (β=.28, p<.001) enhanced COVID-19 preventive behaviors. Moderated regression analysis showed that subjective norms (friends and school) impacted preventive behavior in adolescents more than in emerging adults. Conclusion: Given the need to increase perceived susceptibility and severity among adolescents and emerging adults, these findings provide baseline data for designing effective COVID-19 prevention interventions that consider the developmental characteristics of different age groups. Interventions by health centers at universities can strengthen COVID-19 preventive behavior among emerging adults. As adolescents are influenced by friends, their peer roles must be strengthened to enhance adherence to COVID-19 preventive guidelines.

A data base design framework for predictive a preventive-maintenance system is presented in this paper in order to effectively control machines and reduce accident rates in the workplace. The data base is designed to meet general management requirements to evaluate different maintenance strategies. There are seven data files: the equipment list maintenace pesonnel, maintenance history, maintenance specification, spare part, maintenance equipment, and maintenance schedules. Each data base file has several record based upon data acquisition.

KEPCO is planning to operate 765kV Sin-Tao-Back and Sin-Ga-Pyong substations from 2004. A preventive diagnostic system to obtain the reliability of transformer and GIS is being adopted in 765kV substations. KEPRI has developed a preventive diagnostic system for 765kV substation since 1997. The preventive diagnostic system developed in that project was installed to the 345kV Eui-Ryung substation in June, 2000, and it is under circumstance durability test and operation capacity tests. In this paper, we analyze data of the preventive diagnostic system in 345kV Eui-Ryung substation.

선박, 항해기술 발달과 더불어 안전에 대한 교육 및 법제 강화에도 불구하고 해양사고는 지속적으로 발생하여 큰 피해를 주고 있다. 사고가 발생하면 생명, 재산 그리고 환경적 재해가 수반하게 되므로 예방활동이 강조되고 그를 위한 정책적, 교육적, 법제적 노력에도 예방성과는 미흡한 실정이다. 본 논문에서는 예방활동의 동기와 성과를 촉진하고 체계적인 안전관리를 위한 시각적이고 정량적인 지수를 개발하여 선순환적인 예방문화를 구축하고자 선박사고 예방지수(PISA)와 예방수준(PLSA)을 개념화하고 정량화하였다. 선박사고 예방지수를 설계하기 위하여 지난 5년(2009~2013)간 국내에서 발생한 사고통계 자료를 4개 영역, 즉 교육, 기술, 단속, 정보영역으로 구조화하고 예방요소와 인자를 추출함으로써 지수를 정의하였다. 정의된 지수 산정에 필요한 평가모듈을 설계하였으며, 설계된 모듈을 이용하여 화물선, 여객선, 유조선, 예선, 어선을 대상으로 지수를 측정하였다. 측정된 선박사고 예방지수 결과를 통계적, 사례적으로 위험성(Risk)과의 상관관계를 분석하여 유용성을 확인하였다. 제안된 선박사고 예방지수를 인증제도 등에 활용함으로써 선박별 맞춤형 성과기반 예방활동은 물론 예방중심의 안전문화 촉진과 선박사고 저감효과가 기대된다.

Despite the facts that navigation technology and educational programs were developed, and that maritime law has been enforced strictly, the number of maritime accidents has not dropped significantly. Accident prevention is emphasized because of the extreme life, property, and environmental losses that accompany maritime accidents. Even though there are a variety of preventive activities, their performance is not satisfactory. In order to promote preventive activities and to organize safety management, a Preventive Index of Ship Accident(PISA) and a Preventive Level of Ship Accident(PLSA) which are abstracted from the statistical data of ship accidents (2009~2013) are proposed. The survey module by which these variables can be calculated is composed of preventive domains such as education, engineering, enforcement and information, and is applied for the preventive indexes measurement of cargo, passenger, tanker, tugboat and fishery ships. We compared and analyzed measured result with statistical accident rates and cases to confirm the index utilities. It was found that there is some correlation between the index value and the ship accident rate. It is expected that this index will become useful to evaluate a preventive status for the prevention of ship accidents and for the maritime safety culture.

와이브로(Wibro) 또는 WiFI 망에서 동일한 멀티캐스트 그룹에 속한 이동 단말기들은 동일한 MBS(멀티캐스트/브로드캐스트 방송 서비스) 콘텐츠를 수신한다. 동일한 MBS 존 내의 기지국(RAS: Radio Access Station) 들이 MBS 콘텐츠 소스로부터 수신된 MBS 콘텐츠에 대한 전송 시간을 동기화할 수 있도록 기지국들은 전송 동기화 정보와 신뢰성 있는 데이터 패킷 수신을 동기 시간을 결정하기 이전에 보장받을 수 있어야 한다. 만약에 동일한 MBS 존에 속하는 다수의 기지국 중에 전송 동기화 정보를 수신하지 못하거나 패킷 데이터 일부 또는 전부를 수신하지 못한다면, 동기 전송 시간을 결정하기 전에 이미 손실된 정보와 패킷 데이터를 이동 단말기로 전송하게 됨으로써 이동 단말기가 MBS 콘텐츠를 수신하면서 동일 MBS 존 내의 다른 기지국으로 핸드오버하게 되면 MBS 콘텐츠에 대한 끊김없는 수신을 보장할 수 없을 뿐만 아니라 매크로 다이버시티(macro diversity) 이득을 얻기 위한 동일한 MBS 존에서 이동 단말기들에게 전송되는 MBS 콘텐츠들의 동기를 보장 할 수 없다. 따라서, 본 논문에서는 동기 전송 시간을 결정하기 앞서서 다수의 RAS가 전송 동기화 정보와 신뢰성 있는 패킷 데이터 콘텐츠 수신을 보장받을 수 있는 장치를 보완한 멀티캐스트/브로드캐스트 서비스 데이터 전송 동기화 방법을 제안한다.

가스절연개폐장치(Gas Insulated Switchgear:GIS)는 SF6가스를 절연 매체로 하는 대용량 전력 차단기기이다. GIS는 단순한 구조로 고장이 적고 신뢰성이 높은 편이지만 내부를 볼 수 없어 고장 확인이 어렵고 고장이 발생하면 파급 효과가 크고 복구가 어렵다. 따라서 GIS 내부의 이상 징후를 초기에 찾아낼 수 있도록 GIS 예방진단시스템이 도입되었다. GIS 예방진단시스템은 센서에서 수집, 분석한 정보로 이상 징후를 판단하기 때문에 데이터의 신뢰성과 적시성이 중요하다. 하지만 기존 시스템은 중앙 집중 데이터 수집 방식으로 효율이 낮고 신뢰성과 적시성의 보장이 어렵다. 이러한 신뢰성과 적시성을 보장하기 위하여 GIS 예방진단시스템은 실시간성을 보장하는 미들웨어를 탑재해야 한다. 따라서 본 논문에서는 GIS 예방진단시스템의 신뢰성 향상을 위하여 실시간 분산 컴퓨팅의 적시성 보장을 위해 제안된 TMO를 적용한 미들웨어를 사용한다. 그리고 TMO를 적용한 데이터 수집 및 감시, 제어 방법을 적용한 새로운 GIS 예방진단 시스템을 제안한다. 논문에서 제안하는 시스템은 TMO의 실시간 기능을 활용하여 데이터의 분산 처리가 가능한 통신제어장치를 개발하여 사용한다. 통신제어장치는 TMO를 통해 실시간 데이터 수집 및 처리 과정의 적시성을 보장하고 데이터의 신뢰성을 높여 시스템의 성능 향상에 기여한다. 또한, 기존의 서버의 데이터 수집 및 처리 과정을 통신제어장치가 부담하여 서버의 부하를 줄이고 향후 분산 환경을 지원할 수 있도록 설계하였다. 따라서 제안하는 시스템은 통신제어장치의 적시성 보장을 통해 GIS 예방진단시스템의 신뢰성과 성능을 향상시키고 GIS의 안정적인 운영을 보장할 수 있다.

GIS is used to isolate large power electrical equipment using SF6 gas. While GIS has simple structure, it has few break down, relatively high reliability. But it is hard to check up faults for reason of pressure. Faults of GIS should have a ripple effect on community and be hard to recovery. Consequently, GIS imports a preventive diagnostic system to find internal faults in advance. It is most important that reliability on the GIS preventive diagnostic system, because it estimates abnormality of system by analysis result of collected data. But, exist system which used central data management is low efficiency, and hard to guarantee timeliness and accuracy of data. To guarantee timeliness and accuracy, the GIS preventive diagnostic system needs accordingly to use a real-time middleware. So, in this paper, to improve reliability of the GIS preventive diagnostic system, we use a middleware based on TMO for guaranteeing timeliness of real-time distributed computing. And we propose an improved GIS preventive diagnostic system applying data acquisition, monitoring and control methods based on the TMO model. The presented system uses the Communication Control Unit(CCU) for distributed data handling which is supported by TMO. CCU can improve performance of the GIS preventive diagnostic system by guaranteeing timeliness of data handling process and increasing reliability of data through the TMO middleware. And, it has designed to take full charge of overload on a data acquisition task had been processed in an exist server. So, it could reduce overload of the server and apply distribution environment from now. Therefore, the proposed system can improve performance and reliability of the GIS preventive diagnostic system and contribute to stable operation of GIS.

신환 환자는 병원 애원 경험에 따른 분류로 한번도 해당 병원을 방문한 적이 없어 진찰권번호를 처음으로 부여받는 환자를 말하는데, 특히 병원의 경쟁력 즉, 환자 유입력의 중요한 지표로서 사용되고 있다. 이에 의료기관에서는 병원에 내원하는 환자들이 계절별, 요일별, 일자별, 시간대별에 따라 불규칙적이며 일시적으로 폭주하는 불균형 때문에 장시간 대기하여야 하는 문제를 해소하기 위하여 진료예약제도를 도입하여 운영하고 있다. 그러나 이와 같은 예약제도는 예약문화에 대한 인식부족과 행정관리상의 문제로 아직 제대로 정착되지 못하고 있다. 이러한 문제로 예약부도 환자 문제가 발생하여 병원에서는 환자수의 감소로 인한 병원의 경제적 손실뿐만 아니라 진료를 받지 못한 다른 환자들에게 피해를 주는 사회적 손실의 문제가 발생하고 있다. 이러한 관점에서 본 연구에서는 병원이 보다 과학적인 접근방법을 통해 업무효율과 고객 확보 전략을 할 수 있도록 예약된 신환 환자관리를 위한 일반적 특성에 대한 통계분석과 예약환자 부도방지 모형을 제안하고자 한다.

The New Patient is called patients who have never visit the hospital before and receive the treatment numbers first, who is also classified by visiting experience. Especially The New Patient is used for an important index of the hospital competitiveness, that is, patients influx. Therefore, medical facilities are introducing and using the treatment reservation system to solve the problem of long waiting time due to irregular and temporary excessive unbalance of patients visit by season, week, day, and time. However, this reservation system is not correctly established due to the lack of understanding reservation culture and the problem of administration. Hospitals are experiencing the economical loss from the decreasing number of patients as well as the social loss from damages on patients who can not be treated. From this point of view, this study is to suggest the statistical analysis on general characteristics for reserved new patient management and the model of dishonor prevention of reserved patients in order to have the strategy of securing patients and the administration efficiency through more scientific approach method.

기후변화와 식품공급망의 복잡성 증대로 식품 위해요소의 발생 경로와 패턴이 다변화됨에 따라, 과학적 예측과 선제적 개입이 가능한 예방형 식품안전 관리체계의 필요성이 대두되고 있다. 본 연구는 기후·환경 요인이 식품 위해요소에 미치는 영향을 분석함으로써, 기후 민감성이 높은 위해 요소를 식별하고 예측 가능성과 주요 환경인자를 도출하였다. 아울러 국내외 데이터 기반 위해예측 시스템의 운영 사례를 비교·분석함으로써, 식품위해예측센터의 실질적 운영과 역할을 위한 발전방향을 제시하였다. 본 연구를 통해 향후 식품위해예측센터가 식품안전 정책의 과학화와 지능화를 이끄는 전략적 플랫폼으로 기능하고, 예방 중심의 관리 체계로의 전환을 유도할 수 있도록 실효적 토대와 정책적 방향성을 제공하고자 한다.

As the climate crisis intensifies, and the global food supply chain becomes increasingly complex, food safety management must shift from reactive responses to science-driven predictive systems capable of anticipating risks and enabling timely interventions. This study critically analyzed the impact of climatic and environmental variables on the emergence and dissemination of foodborne hazards, with a primary focus on biological hazards (bacteria, viruses, and parasites) and natural toxins (mycotoxins and marine biotoxins). Through a comparative assessment of domestic and international data-driven risk prediction systems, we propose strategic directions for the implementation and advancement of the Food Risk Prediction Center. Key policy recommendations include data-driven, risk-based sampling and inspection protocols, and optimized hygiene surveillance based on predicted risk scores, environmentally targeted interventions, climate-scenario-based response frameworks, and international data-sharing networks. This review aims to provide a foundation for strategic transformation toward a scientific, intelligent food safety policy infrastructure and to position the Food Risk Prediction Center as a core platform for proactive national food safety governance.