• Title/Summary/Keyword: threat scores

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Detecting Fake News about COVID-19 Infodemic Using Deep Learning and Content Analysis

  • Olga Chernyaeva;Taeho Hong;YongHee Kim;YoungKi Park;Gang Ren;Jisoo Ock
    • Asia pacific journal of information systems
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    • 제32권4호
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    • pp.945-963
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    • 2022
  • With the widespread use of social media, online social platforms like Twitter have become a place of rapid dissemination of information-both accurate and inaccurate. After the COVID-19 outbreak, the overabundance of fake information and rumours on online social platforms about the COVID-19 pandemic has spread over society as quickly as the virus itself. As a result, fake news poses a significant threat to effective virus response by negatively affecting people's willingness to follow the proper public health guidelines and protocols, which makes it important to identify fake information from online platforms for the public interest. In this research, we introduce an approach to detect fake news using deep learning techniques, which outperform traditional machine learning techniques with a 93.1% accuracy. We then investigate the content differences between real and fake news by applying topic modeling and linguistic analysis. Our results show that topics on Politics and Government services are most common in fake news. In addition, we found that fake news has lower analytic and authenticity scores than real news. With the findings, we discuss important academic and practical implications of the study.

학령기 입원아동의 병원관련 공포에 관한 탐색연구 (Identification and Measurement of Hospital-Related Fears in Hospitalized School-Aged Children)

  • 문영임
    • 대한간호학회지
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    • 제25권1호
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    • pp.61-79
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    • 1995
  • When children are admitted to hospital, they have to adapt to new and unfamiliar stimuli. Children may respond with fear to stimuli such as pain or unfamiliar experiences. One goal of nursing is to help hospitalized children to adapt effectively to their hospital experience. Accordingly, nurses need to assess childrens' fears of their hospital experience to contribute to the planning of care to alleviate these fears. The problem addressed by this study was to identify and measure hospital-related fears(hereafter called HRF) in hospitalized school-aged children. The study was conceptualized with Roy's model. A descriptive qualitative approach was used first, followed by a quantitative approach. This study was conducted from November 30, 1989 to January 12, 1991. The sample consisted of 395 hospitalized school-aged children selected through an allocated sampling technique in nine general hospitals. The HRF questionnaire (three point likert scale ) was developed by a delphi technique. The data were analyzed by an SAS program. Factor analysis was used for the examination of component factors. Differences in the HRF related to demographic variables were examined by t-test, analysis of variance and the Scheffe test. The crude scores of the HRF scale were transformed into T- scores to calculate the standard scores. The results included the following : 1. Forty-four items were derived from 188 statements identifying the childrens' hospital-re-lated fears. These items clustered into 14 factors, fear of injections, operations, bodily harm others' pain, medical rounds, physical examinations, medical staff, disease process, blood and X-rays, drugs and cockroaches, tests, harsh discipline from parents or staff, being absent from school, and separation from family. The 14 factors was classified into four categories,'pain','the unfamiliar','the un-known' and 'separation'. 2. The reliability of the HRF instruments was .92(Cronbach's alpha). In the factor analysis, Cronbach's alpha coefficients for the 14 factors ranged from .84 to .86 and Cronbach's alpha coefficients for the four categories ranged from .70 to .84. Pearson correlation coefficient scores for relationships among the 14 factors ranged from ,11 to .50, and among the four categories, from ,44 to ,63, indicating their relative independence. 3. The total group HRF score ranged from 45 to 130 in a possible range of H to 132, with a mean of 74.51. The fears identified by the children were, in order, injections, harsh discipline by parents or staff, bodily harm, operations, medical staff, disease process, and medical rounds ; the least feared was others' pain. The fear item with the highest mean score was surgery and the lowest was examination by a doctor. HRF scores were higher for girls than for boys, and for grade 1 students than for grade 6 students. HRF scores were lower for children whose fathers were over 40 than for those whose fathers were in the 30 to 39 age group, and whose mothers were over 35 than for those whose mothers were in the 20 to 34 age group. HRF scores were lower when the mother rather than any other person stayed with the child. The expressed fear of pain, the unfamiliar, the un-known and of separation directs nurses' concern to the threat felt by hospitalized children to their concept of self. This study contributes to the assessment of fears of hospitalized children and of stimuli impinging on those fears. Accordingly, nursing practice will be directed to the alleviation of pain, pre-admission orientation to the hospital setting and routines, initiation of information about procedures and experiences and arrangments for mothers to stay with their children. Recommendations were made for further research in different settings and for development and testing of the instrument.

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Quantitative Flood Forecasting Using Remotely-Sensed Data and Neural Networks

  • Kim, Gwangseob
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2002년도 학술발표회 논문집(I)
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    • pp.43-50
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    • 2002
  • Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4% and up to 6% were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

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Beliefs, Attitudes, and Behavior of Turkish Women about Breast Cancer and Breast Self-Examination According to a Turkish Version of the Champion Health Belief Model Scale

  • Erbil, Nulufer;Bolukbas, Nurgul
    • Asian Pacific Journal of Cancer Prevention
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    • 제13권11호
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    • pp.5823-5828
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    • 2012
  • Background: Breast cancer (BC) is one of the most common cancer affecting women worldwide. Although a great deal of progress has been made in the health sciences, early diagnosis, and increasing community awareness, breast cancer remains a life-threatening illness. In order to reduce this threat, breast cancer screening needs to be implemented in all communities where possible. Objective: The purpose of this study was to examine health beliefs, attitudes and behaviors about breast cancer and breast self-examination of Turkish women. Methods: Data were collected from a sample of 656 women, using an adapted Turkish version of Champion's Health Belief Model Scale (CHBMS), between January and May 2011, in Ordu province of Turkey. Results: The results showed that 67.7% of women had knowledge about and 55.8% performed BSE, however 60.6% of those who indicated they practiced BSE reported they did so at irregular intervals. CHBMS subscales scores of women according to women's age, education level, occupation, family income and education level of the women's mothers, family history of breast cancer, friend and an acquaintance with breast cancer, knowledge about breast cancer, BSE and mammography were significantly different. Conclusion: Knowledge of women about the risks and benefits of early detection of breast cancer positively affect their health beliefs, attitudes, and behaviors. Health care professionals can develop effective breast health programs and can help women to gain good health behavior and to maintain health.

2018년도에 분리된 닭 전염성기관지염 바이러스에 대한 병원성 시험 (Determining Pathogenicity of Infectious Bronchitis Virus Isolated in Korea 2018)

  • 박담희;윤하나;주효선;김규직;고성혜;이다예;송창선
    • 한국가금학회지
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    • 제46권4호
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    • pp.263-269
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    • 2019
  • IBV는 전세계적으로 양계산업에 문제시되고 있는 호흡기성 질병으로 육계 및 산란계의 생산성에 큰 영향을 미치고 있다. 본 연구는 2018년도에 분리된 3개의 IBV의 병원성을 확인하였다. 동물실험을 통해서 염증정도, 섬모소실도 그리고 폐사율의 결과를 바탕으로 2018년도 분리주인 QX-like IBV형은 병아리에게서 충분한 병원성을 지닌 것을 확인하였다.

An Intelligent Game Theoretic Model With Machine Learning For Online Cybersecurity Risk Management

  • Alharbi, Talal
    • International Journal of Computer Science & Network Security
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    • 제22권6호
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    • pp.390-399
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    • 2022
  • Cyber security and resilience are phrases that describe safeguards of ICTs (information and communication technologies) from cyber-attacks or mitigations of cyber event impacts. The sole purpose of Risk models are detections, analyses, and handling by considering all relevant perceptions of risks. The current research effort has resulted in the development of a new paradigm for safeguarding services offered online which can be utilized by both service providers and users. customers. However, rather of relying on detailed studies, this approach emphasizes task selection and execution that leads to successful risk treatment outcomes. Modelling intelligent CSGs (Cyber Security Games) using MLTs (machine learning techniques) was the focus of this research. By limiting mission risk, CSGs maximize ability of systems to operate unhindered in cyber environments. The suggested framework's main components are the Threat and Risk models. These models are tailored to meet the special characteristics of online services as well as the cyberspace environment. A risk management procedure is included in the framework. Risk scores are computed by combining probabilities of successful attacks with findings of impact models that predict cyber catastrophe consequences. To assess successful attacks, models emulating defense against threats can be used in topologies. CSGs consider widespread interconnectivity of cyber systems which forces defending all multi-step attack paths. In contrast, attackers just need one of the paths to succeed. CSGs are game-theoretic methods for identifying defense measures and reducing risks for systems and probe for maximum cyber risks using game formulations (MiniMax). To detect the impacts, the attacker player creates an attack tree for each state of the game using a modified Extreme Gradient Boosting Decision Tree (that sees numerous compromises ahead). Based on the findings, the proposed model has a high level of security for the web sources used in the experiment.

Studies on QTLs for Bakanae Disease Resistance with Populations Derived from Crosses between Korean japonica Rice Varieties

  • Dong-Kyung Yoon;Chaewon Lee;Kyeong-Seong Cheon;Yunji Shin;Hyoja Oh;Jeongho Baek;Song-Lim Kim;Young-Soon Cha;Kyung-Hwan Kim;Hyeonso Ji
    • 한국작물학회:학술대회논문집
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    • 한국작물학회 2022년도 추계학술대회
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    • pp.201-201
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    • 2022
  • Rice bakanae disease is a serious global threat in major rice-cultivating regions worldwide causing high yield loss. It is caused by the fungal pathogen Fusarium fujikuroi. Varying degree of resistance or susceptibility to bakanae disease had been reported among Korean japonica rice varieties. We developed a modified in vitro bakanae disease bioassay method and tested 31 Korean japonica rice varieties. Nampyeong and Samgwang varieties showed highest resistance while 14 varieties including Junam and Hopum were highly susceptible with 100% mortality rate. We carried out mapping QTLs for bakanae disease resistance with four F2:F3 populations derived from the crosses between Korean japonica rice varieties. The Kompetitive Allele-Specific PCR (KASP) markers developed in our laboratory based on the SNPs detected in Korean japonica rice varieties were used in genotyping F2 plants in the populations. We found four major QTLs on chromosome 1, 4, 6, and 9 with LOD scores of 21.4, 6.9, 6.0, and 60.3, respectively. In addition, we are doing map-based cloning of the QTLs on chromosome 1 and 9 which were found with Junam/Nampyeong F2:F3 population and Junam/Samgwang F2:F3 population, respectively. These QTLs will be very useful in developing bakanae disease resistant high quality rice varieties.

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조기경험이 노인 정신건강에 미치는 영향 (Effect of the Early Traumatic Experience on the Mental Health of the Elderly)

  • 이광헌;이중훈;이종범;박병탁;정성덕
    • Journal of Yeungnam Medical Science
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    • 제7권2호
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    • pp.67-77
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    • 1990
  • 1988년 대구시내 거주하는 노인 278명을 대상으로 하여 불안우울통합척도(CADS)와 조기경험척도(PTES)로 평가한 성적은 다음과 같다. l. CADS로 평가한 성적이 49점이하는 대조군, 50점 이상은 실험군으로 나누었으며 이들 양군의 성적은 대조군 $40.15{\pm}6.19$, 실험군이 $57.75{\pm}6.37$로 실험군이 유의하게 높았다 (p<0.001). 2. 실험군과 대조군이 각각 평가한 불안우울 항목은 성욕감퇴(Decreased libido) 피로감(Fatigue) 정신적 혼란(Mental disintegration) 정신운동지연(Psychomotor retardation) 및 이상감각과 전신통증(Paresthesis and Body-ache & pain)등이 있다. 3. 실험군은 대조군보다 다음과 같은 조기경험 항목이 유의하게 높은 의미를 보였다. 식생활 곤란(Dietary life difficulty), 가족중 과음주자(Alcoholism among family members), 부모간의 불화(Disunion between husband and wife), 부자간의 불화(Trouble between mother and children), 모친상실(Early maternal loss), 부모의 무관심(Patent's indifference), 원치 않는 출생(Unwanted birth)등이었다(p<0.001). 그리고, 거부적 부모태도 항목중 주워 온 자식이란 부모의 위협(Threat of parent's rejection), 차라리 죽어버리라는 위협(Threat of my parent desiring my early death), 부모의 과잉간섭, 심한징벌(Severe punishment by parent), 잡일 시키기(Parent's demand of doing domestic chores) 및 기타 정신 사회적요인 항목중 도깨비나 귀신의 위협(Fear of devil or ghost)등이었다. 4. 실험군과 대조군을 비교했을 때 실험군에서 조기경험성적이 유의하게 높은 사회 정신의학적 요인은 다음과 같다. 성별, 연령별, 결혼 상태별 및 성장지별성적은 실험군에서 모두 높았다(p<0.001). 노인자신이 무직, 중류 및 하류계층일 경우와 부모가 농업 및 상업일 경우 그리고 무종교나 불교일 경우에 조기경험성적이 높았다(p<0.001). 형제자매가 많거나 자녀가 많을 경우 노인자신이 자녀와 동거할 때 조기경험성적이 높았다(p<0.001).

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2012년 겨울철 특별관측자료를 이용한 강수현상 시 대기 연직구조와 민감도 실험 (Vertical Atmospheric Structure and Sensitivity Experiments of Precipitation Events Using Winter Intensive Observation Data in 2012)

  • 이상민;심재관;황윤정;김연희;하종철;이용희;정관영
    • 대기
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    • 제23권2호
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    • pp.187-204
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    • 2013
  • This study analyzed the synoptic distribution and vertical structure about four cases of precipitation occurrences using NCEP/NCAR reanalysis data and upper level data of winter intensive observation to be performed by National Institute of Meteorological Research at Bukgangneung, Incheon, Boseong during 63days from 4 JAN to 6 MAR in 2012, and Observing System Experiment (OSE) using 3DVAR-WRF system was conducted to examine the precipitation predictability of upper level data at western and southern coastal regions. The synoptic characteristics of selected precipitation occurrences were investigated as causes for 1) rainfall events with effect of moisture convergence owing to low pressure passing through south sea on 19 JAN, 2) snowfall events due to moisture inflowing from yellow sea with propagation of Siberian high pressure after low pressure passage over middle northern region on 31 JAN, 3) rainfall event with effect of weak pressure trough in west low and east high pressure system on 25 FEB, 4) rainfall event due to moisture inflow according to low pressures over Bohai bay and south eastern sea on 5 MAR. However, it is identified that vertical structure of atmosphere had different characteristics with heavy rainfall system in summer. Firstly, depth of convection was narrow due to absence of moisture convergence and strong ascending air current in middle layer. Secondly, warm air advection by veering wind with height only existed in low layer. Thirdly, unstable layer was limited in the narrow depth due to low surface temperature although it formed, and also values of instability indices were not high. Fourthly, total water vapor amounts containing into atmosphere was small due to low temperature distribution so that precipitable water vapor could be little amounts. As result of OSE conducting with upper level data of Incheon and Boseong station, 12 hours accumulated precipitation distributions of control experiment and experiments with additional upper level data were similar with ones of observation data at 610 stations. Although Equitable Threat Scores (ETS) were different according to cases and thresholds, it was verified positive influence of upper level data for precipitation predictability as resulting with high improvement rates of 33.3% in experiment with upper level data of Incheon (INC_EXP), 85.7% in experiment with upper level data of Boseong (BOS_EXP), and 142.9% in experiment with upper level data of both Incheon and Boseong (INC_BOS_EXP) about accumulated precipitation more than 5 mm / 12 hours on 31 January 2012.

구름미세물리 모수화 방안 내 빗방울의 특성을 정의하는 매개변수가 한반도 여름철 강수 모의에 미치는 영향 (Effects of Parameters Defining the Characteristics of Raindrops in the Cloud Microphysics Parameterization on the Simulated Summer Precipitation over the Korean Peninsula)

  • 김기병;김권일;이규원;임교선
    • 대기
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    • 제34권3호
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    • pp.305-317
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    • 2024
  • The study examines the effects of parameters that define the characteristics of raindrops on the simulated precipitation during the summer season over Korea using the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) cloud microphysics scheme. Prescribed parameters, defining the characteristics of hydrometeors in the WDM6 scheme such as aR, bR, and fR in the fall velocity (VR) - diameter (DR) relationship and shape parameter (𝜇R) in the number concentration (NR) - DR relationship, presents different values compared to the observed data from Two-Dimensional Video Disdrometer (2DVD) at Boseong standard meteorological observatory during 2018~2019. Three experiments were designed for the heavy rainfall event on August 8, 2022 using WRF version 4.3. These include the control (CNTL) experiment with original parameters in the WDM6 scheme; the MUR experiment, adopting the 50th percentile observation value for 𝜇R; and the MEDI experiment, which uses the same 𝜇R as MUR, but also includes fitted values for aR, bR, and fR from the 50th percentile of the observed VR - DR relationship. Both sensitivity experiments show improved precipitation simulation compared to the CNTL by reducing the bias and increasing the probability of detection and equitable threat scores. In these experiments, the raindrop mixing ratio increases and its number concentration decreases in the lower atmosphere. The microphysics budget analysis shows that the increase in the rain mixing ratio is due to enhanced source processes such as graupel melting, vapor condensation, and accretion between cloud water and rain. Our study also emphasizes that applying the solely observed 𝜇R produces more positive impact in the precipitation simulation.