• Journal of Korean Society of Disaster and Security
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• v.13 no.1
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• pp.59-75
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• 2020

This study is a case study that applied 'UNDRR's Urban Disaster Resilience Scorecard', an evaluation tool necessary for Incheon Metropolitan City to be certified as an international safe city. I would like to present an example that the results derived from this scorecard contributed to the Incheon Metropolitan City Disaster Reduction Plan. Of course, the Disaster Resilience Scorecard can't provide a way to improve the resilience of every disaster facing the city. However, it is to find the weakness of the resilience that the city faces, and to propose a solution to reduce the city's disaster risk. This is to help practitioners to recognize the disaster risks that Incheon Metropolitan City faces. In addition, the solution recommended by UNDRR was suggested to provide resilience in areas vulnerable to disasters. It was confirmed that this process can contribute to improving the disaster resilience of Incheon Metropolitan City. UNDRR has been spreading 'Climate Change, Disaster-resistant City Creation Campaign', aka MCR (Making Cities Resilient) Campaign, to cities all over the world since 2010 to reduce global cities' disasters. By applying the disaster relief guidelines adopted by UNDRR, governments, local governments, and neighboring cities are encouraged to collaborate. As a result of this study, Incheon Metropolitan city's UN Urban Resilience Scorecard was evaluated as a strong resilience field by obtaining scores of 4 or more (4.3~5.0) in 5 of 10 essentials; 1. Prepare organization for disaster resilience and prepare for implementation, 4. Strong resilience Urban development and design pursuit, 5. Preservation of natural cushions to enhance the protection provided by natural ecosystems, 9. Ensure effective disaster preparedness and response, 10. Rapid restoration and better reconstruction. On the other hand, in the other five fields, scores of less than 4 (3.20~3.85) were obtained and evaluated as weak resilience field; 2. Analyze, understand and utilize current and future risk scenarios, 3. Strengthen financial capacity for resilience, 6. Strengthen institutional capacity for resilience, 7. Understanding and strengthening social competence for resilience, 8. Strengthen resilience of infrastructure. In addition, through this study, the risk factors faced by Incheon Metropolitan City could be identified by priority, resilience improvement measures to minimize disaster risks, urban safety-based urban development plans, available disaster reduction resources, and integrated disasters. Measures were prepared.

• Journal of Korean Physical Therapy Science
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• v.18 no.1
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• pp.1-10
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• 2011

Purpose: Study on the effect of the use of Proprioceptive Neuromuscular Facilitation(PNF) method by use of the direction and charge regulation which is the advantage of the Thera-band therapy on the walks and balances in old people and comparison with the result after applying the general PNF technique. Method: The study has been performed on 30 females over 65 years old. The study has been done by dividing the object group in 3 patterns, which are number 1, the comparison group of 10, two ones that are applied the PNF technique using Thera-band and third, the ones that are applied only the PNF technique. For the PNF and the Thera-band using PNF, we have divided the group into Combination of Isotonic technique and the Rhythmical stabilization technique according to the patient's acquaintance pattern and applied them to the patient's body. Evaluation was the balancing ability which was calculated by using the BIODEX Balance system / FRT and for the evaluation of walking ability, we have used the speed of walking for 10M / TUG. Result: In the comparison group of 10, the balancing ability and the walking ability did not change much before and after the experiment, which made it possible to compare the group with the other two easily(p>0.05). For the other two groups, we have recognized the enhancement both in the balancing ability and the walking ability, but they did not know much difference between themselves(p<0.05). Conclusion: Though there were not a big difference in the sense of improvement between the Thera-band using PNF and the PNF technique only, we could infer that these two therapy has enhanced much in the walking and balancing ability for people over 65 and through these result we can foresee that not only using the method shown in this study but also by using many advantages of Thera-band, we could diminish the tiredness of healer, enhance the efficiency of exercise in them and also by forming self training program for older people we could help them build the prevention program from falls.

• Journal of Hospice and Palliative Care
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• v.14 no.4
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• pp.212-217
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• 2011

Purpose: Since 2005, the Ministry of Health & Welfare has provided financial support to promote palliative care for terminal cancer patients. We analyzed how palliative care facilities used the funding between 2006 and 2010. Methods: Frequency analysis was conducted by the item of expenditure based on fiscal reports of the palliative care facilities. Linear regression analysis was performed to examine a trend over time. Kruskal-Wallis test and Wilcoxon rank-sum test were used to compare expenditure items, the number of provision of financial support and type of palliative care units. Results: About a half of the fund was spent to pay care givers salary, improve facilities and purchase equipment regardless of the year, the number of financial support provided or facility type. By year, the operation cost for palliative care program and the education cost for health care workers have significantly increased in linear regression analysis (P<0.01). However, the amount of financial support for the low income group has decreased over years (P=0.024). This trend was affected by evaluation criteria and weight. Conclusion: The government aid for palliative care units has been used to improve facilities and equipment. Moreover, desirable changes were noted such as a higher portion of expenses for program operation and care giver training to enhance the quality of care. However, the evaluation criteria need to be adjusted to prevent any further decrease in the support provided to the low income group.

• Journal of Korean Society of Disaster and Security
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• v.12 no.1
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• pp.11-21
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• 2019

This study assessed the risk of disaster by using QRE(Quick Risk Estimation - UNISDR Roll Model City of Basic Evaluation Tool) tools for three natural disasters and sixteen social disasters managed by the Seoul Metropolitan Government. The criteria for selecting 19 disaster types in Seoul are limited to disasters that occur frequently in the past and cause a lot of damage to people and property if they occur. We also considered disasters that are likely to occur in the future. According to the results of the QRE tools for disaster type in Seoul, the most dangerous type of disaster among the Seoul city disasters was "suicide accident" and "deterioration of air quality". Suicide risk is high and it is not easy to take measures against the economic and psychological problems of suicide. This corresponds to the Risk ratings(Likelihood ranking score & Severity rating) "M6". In contrast, disaster types with low risk during the disaster managed by the city of Seoul were analyzed as flooding, water leakage, and water pollution accidents. In the case of floods, there is a high likelihood of disaster such as localized heavy rains and typhoons. However, the city of Seoul has established a comprehensive plan to reduce floods and water every five years. This aspect is considered to be appropriate for disaster prevention preparedness and relatively low disaster risk was analyzed. This corresponds to the disaster Risk ratings(Likelihood ranking score & Severity rating) "VL1". Finally, the QRE tool provides the city's leaders and disaster managers with a quick reference to the risk of a disaster so that decisions can be made faster. In addition, the risk assessment using the QRE tool has helped many aspects such as systematic evaluation of resilience against the city's safety risks, basic data on future investment plans, and disaster response.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.202-217
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• 2022

Purpose: The recent increased use of Personal Mobility (PM) has been accompanied by a rise in the annual number of accidents. Accordingly, the safety requirements for PM use are being strengthened, but the laws/systems, infrastructure, and management systems remain insufficient for fostering a safe environment. Therefore, this study comprehensively searches the main problems and improvement methods through a review of previous studies that are related to PM. Then the priorities according to the importance of the improvement methods are presented through the Delphi survey. Method: The research method is mainly composed of a literature study and an expert survey (Delphi survey). Prior research and improvement cases (local governments, government departments, companies, etc.) are reviewed to derive problems and improvements, and a problem/improvement classification table is created based on keywords. Based on the classification contents, an expert survey is conducted to derive a priority improvement plan. Result: The PM-related problems were in 'non-compliance with traffic laws, lack of knowledge, inexperienced operation, and lack of safety awareness' in relation to human factors, and 'device characteristics, road-drivable space, road facilities, parking facilities' in relation to physical factors. 'Management/supervision, product management, user management, education/training' as administrative factors and legal factors are divided into 'absence/sufficiency of law, confusion/duplication, reduced effectiveness'. Improvement tasks related to this include 'PM education/public relations, parking/return, road improvement, PM registration/management, insurance, safety standards, traffic standards, PM device safety, PM supplementary facilities, enforcement/management, dedicated organization, service providers, management system, and related laws/institutional improvement', and 42 detailed tasks are derived for these 14 core tasks. The results for the importance evaluation of detailed tasks show that the tasks with a high overall average for the evaluation items of cost, time, effect, urgency, and feasibility were 'strengthening crackdown/instruction activities, education publicity/campaign, truancy PM management, and clarification of traffic rules'. Conclusion: The PM market is experiencing gradual growth based on shared services and a safe environment for PM use must be ensured along with industrial revitalization. In this respect, this study seeks out the major problems and improvement plans related to PM from a comprehensive point of view and prioritizes the necessary improvement measures. Therefore, it can serve as a basis of data for future policy establishment. In the future, in-depth data supplementation will be required for each key improvement area for practical policy application.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.3
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• pp.335-344
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• 2022

This study was conducted for 4 weeks on the preparation of the science teaching/learning course plan for 109 students in 4 classes of the 2nd year intensive course at B University of Education. Pre-service elementary teachers attended a two-week field training practice after listening to a lecture on how to write a science teaching and learning course plan. Pre-service elementary teachers tried to find out about the selection of materials and the degree of connection between the course plan and the class to prepare the science teaching/learning course plan. The researcher completed the questionnaire by reviewing and deliberation on the questionnaire questions together with 4 pre-service elementary teachers. The questionnaire related to the writing of the science teaching and learning course plan consists of 8 questions. Preferred reference materials when writing the course plan, the level of interest in learning, the success or failure of the science course plan and class, the science preferred model, the evaluation method in unit time, and the science teaching and learning One's own efforts to write the course plan, the contents of this course are the science faculty. It is composed of the preparation of the learning process plan and how helpful it is to the class. The results of this study are as follows. First, it was found that elementary school pre-service elementary teachers preferred teacher guidance the most when drafting science teaching and learning curriculum plans. Second, it is recognized that the development stage is very important in the teaching and learning stage of the science department. Third, Pre-service elementary teachers believe that the science and teaching and learning process plan has a high correlation with the success of the class. Fourth, it was said that the student's level, the teacher's ability, and the appropriate lesson plan had the most influence on the class. Fifth, it was found that pre-service elementary teachers prefer the inquiry learning class model. Sixth, it was found that reports and activity papers were preferred for evaluation in 40-minute classes. Seventh, it was stated that the teaching and learning process plan is highly related to the class, so it will be studied and studied diligently. Eighth, the method of writing a science teaching and learning course plan based on the instructional design principle is interpreted as very beneficial.

• Korean Journal of Culture and Social Issue
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• v.21 no.2
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• pp.227-252
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• 2015

This study was intended to examine child abuse experience, response to child abuse, perception of the cause of child abuse, and need for counseling to prevent and eliminate child abuse among 514 day care center teachers across the country. First, 17.9% (92) of the teachers had experience of witnessing child abuse at day care centers. After such witness, the teachers mostly "paid attention to abused children and provided them with warm treatment" when they were abused by other teachers and "took no actions" when they were abused by directors of the day care centers. The biggest reason of not taking any actions was: they "had no authority to intervene in child care of other teachers" in case of child abuse by other teachers and "were afraid of responsibilities or roles that could be placed on them after reporting" in case of child abuse by day care center directors. Second, the biggest reason of child abuse by teachers was job stress followed by excessive work and mental health of teachers. Third, necessary actions when child abuse cases were found and confirmed were suspension of involved teachers and psychological evaluation for involved children and parents. Fourth, 88.9% (457) of the teachers responded that they would use an organization specialized in child abuse if such organization was built and that the organization would help them to decide on whether to report child abuse and prevention of and intervention in child abuse. They also said that such organization should be installed in the Counseling Center in the Comprehensive Child Care Support Center. Fifth, 95.3% (490) of the teachers answered professional counselors specialized in development and counseling of infants and toddlers were needed to address child abuse at day care centers. They demanded that such counselors should be able to administer psychological evaluation for young children and assess child abuse cases. Qualification of the counselors was at least college graduates who majored in psychology and child care, three to five years of experience in the field, and appropriate certificates or licenses. Finally, the teachers said that training and professional counseling about child abuse were required to prevent and eliminate child abuse at day care centers. Implications and follow-up studies were provided and suggested based on these findings.

• The Journal of Korean Society for Radiation Therapy
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• v.24 no.2
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• pp.123-135
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• 2012

Purpose: It is essential to minimize the movement of tumor due to respiratory movement at the time of respiration controlled radiotherapy of non-small cell lung cancer patient. Accordingly, this Study aims to evaluate the usefulness of restricted respiratory period by comparing and analyzing the treatment plans that apply free and restricted respiration period respectively. Materials and Methods: After having conducted training on 9 non-small cell lung cancer patients (tumor n=10) from April to December 2011 by using 'signal monitored-breathing (guided- breathing)' method for the 'free respiratory period' measured on the basis of the regular respiratory period of the patents and 'restricted respiratory period' that was intentionally reduced, total of 10 CT images for each of the respiration phases were acquired by carrying out 4D CT for treatment planning purpose by using RPM and 4-dimensional computed tomography simulator. Visual gross tumor volume (GTV) and internal target volume (ITV) that each of the observer 1 and observer 2 has set were measured and compared on the CT image of each respiratory interval. Moreover, the amplitude of movement of tumor was measured by measuring the center of mass (COM) at the phase of 0% which is the end-inspiration (EI) and at the phase of 50% which is the end-exhalation (EE). In addition, both observers established treatment plan that applied the 2 respiratory periods, and mean dose to normal lung (MDTNL) was compared and analyzed through dose-volume histogram (DVH). Moreover, normal tissue complication probability (NTCP) of the normal lung volume was compared by using dose-volume histogram analysis program (DVH analyzer v.1) and statistical analysis was performed in order to carry out quantitative evaluation of the measured data. Results: As the result of the analysis of the treatment plan that applied the 'restricted respiratory period' of the observer 1 and observer 2, there was reduction rate of 38.75% in the 3-dimensional direction movement of the tumor in comparison to the 'free respiratory period' in the case of the observer 1, while there reduction rate was 41.10% in the case of the observer 2. The results of measurement and comparison of the volumes, GTV and ITV, there was reduction rate of $14.96{\pm}9.44%$ for observer 1 and $19.86{\pm}10.62%$ for observer 2 in the case of GTV, while there was reduction rate of $8.91{\pm}5.91%$ for observer 1 and $15.52{\pm}9.01%$ for observer 2 in the case of ITV. The results of analysis and comparison of MDTNL and NTCP illustrated the reduction rate of MDTNL $3.98{\pm}5.62%$ for observer 1 and $7.62{\pm}10.29%$ for observer 2 in the case of MDTNL, while there was reduction rate of $21.70{\pm}28.27%$ for observer 1 and $37.83{\pm}49.93%$ for observer 2 in the case of NTCP. In addition, the results of analysis of correlation between the resultant values of the 2 observers, while there was significant difference between the observers for the 'free respiratory period', there was no significantly different reduction rates between the observers for 'restricted respiratory period. Conclusion: It was possible to verify the usefulness and appropriateness of 'restricted respiratory period' at the time of respiration controlled radiotherapy on non-small cell lung cancer patient as the treatment plan that applied 'restricted respiratory period' illustrated relative reduction in the evaluation factors in comparison to the 'free respiratory period.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.