• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.2
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• pp.151-158
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• 2019

Wireless communication technology (WAVE) for vehicles, which is the core technology behind the next-generation intelligent transport system (C-ITS), is used to deliver information about vehicles to prevent traffic accidents and traffic situations that may arise between vehicles and infrastructure. Similar traffic issues often arise in marine scenarios. Currently, AIS is being used as a means of transmitting information such as the status of relative vessels, but research is being carried out to solve problems with AIS such as overloading by applying wireless communication technology for vehicles to the sea. In this study, a collision warning system suitable for small-sized vessels was developed based on the marine application of WAVE for vehicles verified through prior research, and the adequacy of this collision warning system was reviewed through a practical test. It is expected that this system will contribute greatly to future e-Navigation applications or self-driving ships as well as to preventing marine accidents.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1285-1294
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• 2021

In recent years, as rainfall is concentrated and rainfall intensity increases worldwide due to climate change, the scale of flood damage is increasing. Rainfall of a previously unobserved magnitude falls, and the rainy season lasts for a long time on record. In particular, these damages are concentrated in ASEAN countries, and at least 20 million people among ASEAN countries are affected by frequent flooding due to recent sea level rise, typhoons and torrential rain. Korea supports the domestic flood warning system to ASEAN countries through various ODA projects, but the communication network is unstable, so there is a limit to the central control method alone. Therefore, in this study, an artificial intelligence-based flood prediction model was developed to develop an observation station that can observe water level and rainfall, and even predict and warn floods at once at one observation station. Training, validation and testing were carried out for 0.5, 1, 2, 3, and 6 hours of lead time using the rainfall and water level observation data in 10-minute units from 2009 to 2020 at Junjukbi-bridge station of Seolma stream. LSTM was applied to artificial intelligence algorithm. As a result of the study, it showed excellent results in model fit and error for all lead time. In the case of a short arrival time due to a small watershed and a large watershed slope such as Seolma stream, a lead time of 1 hour will show very good prediction results. In addition, it is expected that a longer lead time is possible depending on the size and slope of the watershed.

• Journal of Korean Academy of Nursing
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• v.33 no.8
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• pp.1145-1152
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• 2003

Propose. An effective rehabilitation program had been developed for psychiatric patients' self management of medication and symptoms in Korea. The rehabilitation program was designed to allow the patients to understand their illness, cope with their medical regimen, and prevent a relapse by recognizing any of the symptoms when they recur. Methods. The developed program utilizes the self efficacy method reported by Bandura, it includes manuals and videotapes focusing on real life situations, small group discussions, and telephone coaching. This study investigated the effects of this program with respect to various predictable variables in psychiatric rehabilitation. Thirty eight patients were selected for this study, 18 in the experimental program and 20 as controls. Results. The results showed that the subjects who attended this educational program reported significantly more improvement in attitude toward medication compliance (p=0.033), and significantly less relapse warning symptom scores (p=0.000) than the controls. Conclusion. This program may be a useful psychoeducational resource for professionals in the field of clinical practice in psychiatry.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1427-1431
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• 2007

In this study, the new methodology which combines Kohonen self-organizing map(KSOM) neural networks model and the conventional neural networks models such as feedforward neural networks model and generalized neural networks model is introduced to forecast flood stage in Nakdong river, Republic of Korea. It is possible to train without output data in KSOM neural networks model. KSOM neural networks model is used to classify the input data before it combines with the conventional neural networks model. Four types of models such as SOM-FFNNM-BP, SOM-GRNNM-GA, FFNNM-BP, and GRNNM-GA are used to train and test performances respectively. From the statistical analysis for training and testing performances, SOM-GRNNM-GA shows the best results compared with the other models such as SOM-FFNNM-BP, FFNNM-BP, and GRNNM-GA and FFNNM-BP shows vice-versa. From this study, we can suggest the new methodology to forecast flood stage and construct flood warning system in river basin.

• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.637-651
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• 2019

In the event of a major accident such as an explosion in a refinery or a petrochemical plant, it has caused a serious loss of life and property and has had a great impact on the insurance market. In the case of catastrophic incidents occurring in process industries such as refinery and petrochemical plants, only the proximate causes of loss have been drawn and studied from inspectors or claims adjustors responsible for claims of property insurers, incident cause investigators, and national forensic service workers. However, it has not been done well for conducting root cause analysis (RCA) and identifying the factors that contributed to the failure and establishing preventive measures before leading to chemical plant's catastrophic incidents. In this study, the criteria of warning signs on CCPS catastrophic incident waning sign self-assessment tool which was derived through the RCA method and the contribution factor analysis method using the swiss cheese model principle has been reviewed first. Secondly, in order to determine the major incident warning signs in an actual chemical plant, 614 recommendations which have been issued during last the 17 years by loss control engineers of global reinsurers were analyzed. Finally, in order to facilitate the assessment index for catastrophic incident warning signs, the criteria for the catastrophic incident warning sign index at chemical plants were grouped by type and classified into upper category and lower category. Then, a catastrophic incident warning sign index for a chemical plant was developed using the weighted values of each category derived by applying the analytic hierarchy process (pairwise comparison method) through a questionnaire answered by relevant experts of the chemical plant. It is expected that the final 'assessment index for catastrophic incident warning signs' can be utilized by the refinery and petrochemical plant's internal as well as external auditors to assess vulnerability levels related to incident warning signs, and identify the elements of incident warning signs that need to be tracked and managed to prevent the occurrence of serious incidents in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.171-178
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• 2020

Many countries are establishing and operating blended learning that combines the advantages of online and offline education. However, online education lecture-based Mooc courses have a very low level, with a graduation rate of less than 5-10%. Therefore, in order to increase the graduation rate of students taking online Mooc distance education lectures that anyone can easily take lectures anytime, anywhere on the web-based basis, it is necessary to introduce automatic analysis of students' understanding level of lectures and an automatic academic warning system. Moreover, in order to enter an advanced education country, it is necessary to develop an automatic judgment SW for wrong answer rate, automatic summary SW for lectures, and automatic analysis SW education for lecture-based weak subjects based on mixed learning levels. In order to improve this problem, in this paper, we proposed and simulated an automatic summarization system for lecture contents, an automatic warning system for incorrect answers, and an automatic judgment algorithm for weak subjects.

• Journal of Korean Academy of Nursing
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• v.33 no.6
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• pp.829-838
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• 2003

Purpose: In South Korea, as growing the need of psychological support in disaster situation psychological assessment on stress after disaster is important to find out the factors affecting coping, and to plan intervention in the community. Method: The volunteers of Korea Redcross who live around K city, and the research team visited all homes at Jirye town, one of the high-impact area, 4 month after the typhoon. One of the family members who is over 18 years old, answered the self-report questionnaire composed of disaster experience, damage, exposure to traumatic event, and posttraumatic stress with IES-K (Impact of Event Scale-korea) He also, described his family members symptom related to re-experiencing, hyper-arousal, and avoidance. Six hundreds households were surveyed. Result: The prevalence of moderate to severe PTSD symptom was 36% of the subjects. The severity of PTSD was affected by gender, economic status and affected by damaged property, physical injury, worsening existing disease, getting infectious disease, amount of experienced traumatic event before disaster, warning, taking shelter, and subjects revealed differences in somatization as severity of PTSD. According to the description, community members had re-experiencing, hyper-arousal and avoidance. Conclusion: At a rural area, South Korea, community members have suffered from psychological distress after disaster. So psychological interventions are required as affecting factors and also to plan for warning and shelter in disaster situation is needed for preventing PTSD.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.7
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• pp.4307-4312
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• 2013

Breast cancer is the most frequent malignancy of women worldwide. It is the leading cause of female cancer related disability and mortality. In Saudi Arabia breast cancer ranks first among cancerous diseases in females. In the Gulf region, and especially in Saudi Arabia, few studies have been conducted to address breast cancer awareness. The purpose of the current study was therefore to investigate the level of breast cancer awareness among Saudi females in Jeddah, focusing on knowledge of breast cancer warning signs, risk factors, screening programs and breast self-examination (BSE). The design of this study was an exploratory correlational analysis. The sample comprised 200 Saudi females aged 20 and older living in Jeddah. Data were collected using face-to-face interviews. Breast cancer awareness was measured using a modified Arabic version of the Breast Cancer Awareness Measure (Breast CAM) version 2. Descriptive statistical analysis, Pearson's Product Moment correlation coefficients and ANOVA test were used to answer study questions. Out of 200 participants, 50.5% were aware of breast lump as a warning sign of breast cancer, 57.5% claimed that family history was risk factor, 20.5% had undergone breast screening, 79% heard about BSE, and 47.5% knew how to perform BSE. Findings indicated that Saudi females level of awareness of breast cancer is very inadequate. Public awareness interventions are needed in order to overcome an ever-increasing burden of this disease among Saudi females.

• Journal of Korean Public Health Nursing
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• v.35 no.2
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• pp.283-296
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• 2021

Purpose: The aim of this study was to investigate the influence of threat perception and psychological reactance to graphic health warnings on cigarette packages on intention to quit smoking among smoking adolescents. Methods: The participants were 185 smoking adolescents attending two industrial specialized high schools, who had witnessed graphic health warnings on cigarette packages within the previous 30 days. Collected data were analyzed using descriptive statistics, the t-test, one-way analysis of variance, Pearson's correlation coefficients, and hierarchical multiple regression analysis using SPSS/WIN Ver. 25.0. Results: The results showed that participant threat perception (𝛽=.14, p=.037) after witnessing a cigarette warning message had a positive influence on intention to quit smoking. On the other hand, psychological reactance (𝛽=-.23, p=.001) showed a negative influence on intention to quit smoking. Conclusion: When designing and developing a message for smoking adolescents, customized messages are required to reflect teenagers' characteristics and raise threat perception and lower psychological reactance. In addition, we propose a future study be conducted to determine the influences of various psychological determinants, including self-efficacy and skills, on threat perception and psychological reactance to graphic health warnings on cigarette packages among smoking adolescents.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.83-89
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• 2021

To improve the performance of self-driving cars, the introduction of V2X, a communication technology that connects vehicles, infrastructure, and vehicles, is essential. Even if traffic information of the other vehicle is known, the structure of the intersection and a distance calculation algorithm are required for accurate calculations at roundabouts. This paper proposes a design algorithm for a rotating intersection and implemented in Matlab that complies with the national design rules and enables accurate calculations. Assuming the roundabout and the entrance/exit path to be a circle, a method for measuring the distance between vehicles at an arbitrary point was proposed using the horizontal shift of the entrance circle to the main circle. The algorithm could be used in fully autonomous vehicles by designing a roundabout suitable for the terrain by arbitrarily varying the angle between branches and the radius of curvature of the entrance and exit roads, and transmitting a warning signal when a collision between two driving vehicles is expected.