• The Korean Journal of Archival Studies
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• no.25
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• pp.3-46
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• 2010

Digital records management is one whole system in which many social and technical elements are interacting. To maintain the trustworthiness, the repository needs periodical audit and certification. Thus, individual electronic records management agency needs toolkit that can be used to self-evaluate their trustworthiness continuously, and self-assess their atmosphere and system to recognize deficiencies. The purpose of this study is development of self-certification toolkit for repositories, which synthesized and analysed such four international standard and best practices as OAIS Reference Model(ISO 14721), TRAC, DRAMBORA, and the assessment report conducted and published by TNA/UKDA, as well as MoRe2 and current national laws and standards. As this paper describes and demonstrate the development process and the framework of this self-certification toolkit, other electronic records management agencies could follow the process and develop their own toolkit reflecting their situation, and utilize the self-assessment results in-house. As a result of this research, 12 areas for assessment were set, which include (organizational) operation management, classification system and master data management, acquisition, registration and description, storage and preservation, disposal, services, providing finding aids, system management, access control and security, monitoring/audit trail/statistics, and risk management. In each 12 area, the process map or functional charts were drawn and business functions were analyzed, and 54 'evaluation criteria', consisted of main business functional unit in each area were drawn. Under each 'evaluation criteria', 208 'specific evaluation criteria', which supposed to be implementable, measurable, and provable for self-evaluation in each area, were drawn. The audit and certification toolkit developed by this research could be used by digital repositories to conduct periodical self-assessment of the organization, which would be used to supplement any found deficiencies and be used to reflect the organizational development strategy.

• Journal of Hospice and Palliative Care
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• v.22 no.1
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• pp.39-47
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• 2019

Purpose: This study was performed to investigate the current status of pediatric palliative care provision and how it is perceived by the palliative care experts. Methods: A descriptive study was conducted with 61 hospice institutions. From September through October 2017, a questionnaire was completed by experts from the participating institutions. Data were analyzed using SPSS 21.0. Results: Among 61 institutions, palliative care is currently provided for pediatric cancer patients by 11 institutions (18.0%), all of which are concentrated in Seoul, Incheon and Gyeonggi and Gyengsang provinces; 85.2% of all do not plan to provide specialized pediatric palliative care in the future. According to the experts, the main barriers in providing pediatric palliative care were the insufficient number of trained specialists regardless of the delivery type. Experts said that it was appropriate to intervene when children were diagnosed with cancer that was less likely to be cured (33.7%) and to move to palliative care institutions when their conditions worsened (38.2%); and it was necessary to establish a specialized pediatric palliative care system, independent from the existing institutions for adult patients (73.8%). Conclusion: It is necessary to develop an education program to establish a nationwide pediatric palliative care centers. Pediatric palliative care intervention should be provided upon diagnosis rather than at the point of death. Patients should be transferred to palliative care institutions after intervention by their existing pediatric palliative care team at the hospital is started.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.118-131
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• 2019

In order to provide 8K UHD contents of terrestrial broadcasting with a large capacity, the terrestrial broadcasting system has various problems such as limited bandwidth and so on. To solve these problems, UHD contents transmission technology has been actively studied, and an 8K UHD broadcasting system using terrestrial broadcasting network and communication network has been proposed. The proposed technique is to solve the limited bandwidth problem of terrestrial broadcasting network by segmenting 8K UHD contents and transmitting them to heterogeneous networks through hierarchical separation. Through the terrestrial broadcasting network, the base layer corresponding to FHD and the additional enhancement layer data for 4K UHD are transmitted, and the additional enhancement layer data corresponding to 8K UHD is transmitted through the communication network. When 8K UHD contents are provided in such a way, user can receive up to 4K UHD broadcasting by terrestrial channels, and also can receive up to 8K UHD additional communication networks. However, in order to transmit the 4K UHD contents within the allocated bit rate of the domestic terrestrial UHD broadcasting, the compression rate is increased, so a certain level of image deterioration occurs inevitably. Due to the nature of UHD contents, video quality should be considered as a top priority over other factors, so that video quality should be guaranteed even within a limited bit rate. This requires packet scheduling of content generators in the broadcasting system. Since the multiplexer sends out the packets received from the content generator in order, it is very important to make the transmission time and the transmission rate of the process from the content generator to the multiplexer constant and accurate. Therefore, we propose a variable transmission scheduler between the content generator and the multiplexer to guarantee the image quality of a certain level of UHD contents in this paper.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.99-106
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• 2019

The purpose of this study is to analyze the effects of the simulation-based professional cardiac resuscitation training on the performance of professional cardiac resuscitation performed by paramedics in the pre-hospital stage and to provide basic data for effective cardiac resuscitation. This study is an experimental study of the design before and after the control of non-equality. The subjects of this study were 16 newly recruited paramedics from K firefighting school. The simulation training program and evaluation papers used as the evaluation tool were reviewed and commented by 6 ACLS simulation experts (2 emergency medical doctor, 2 emergency medical professors, 2 KALS instructors)Respectively. The training consisted of 30 minutes of theory and 150 minutes of practical training. The lecturer first demonstrated for 5 minutes, and after training by individual debriefing after individual training, individual and team education was conducted The evaluation scale was given a 5 - point Likert scale. The SPSS 22.0 program for Windows was used. The general characteristics of the subjects were analyzed for frequency, the examination of homogeneity between the experimental group and the control group wasfulfilled by t test, and the difference test between the groups of the two groups was performed using the paired t-test. The homogeneity test was able to confirm the homogeneity between experimental group and control group. In the evaluation of six ACLS techniques, it was proven that the experimental group that received the simulation training had better performance in all aspects than the non - training control group. The following are the technical items to be performed. 1. Electrocardiogram 2. Specialized instrument 3. Treatment of fluid 4. Leadership and teamwork 5. Medical guidance 6. Evaluation during transfer. It was proved that paramedics who received simulation training were improved on their job performance ability than general lecture and training group. Therefore, if simulation training and education are applied to a student in the synthetic course or an emergency resident who is engaged in clinical practice, he / she will be able to perform his / her duties more proficiently. It is expected that emergency services provided to patients with cardiac arrest will be improved.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.175-197
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• 2021

Recently, with the development of deep learning technology, research on unstructured data analysis is being actively conducted, and it is showing remarkable results in various fields such as classification, summary, and generation. Among various text analysis fields, text classification is the most widely used technology in academia and industry. Text classification includes binary class classification with one label among two classes, multi-class classification with one label among several classes, and multi-label classification with multiple labels among several classes. In particular, multi-label classification requires a different training method from binary class classification and multi-class classification because of the characteristic of having multiple labels. In addition, since the number of labels to be predicted increases as the number of labels and classes increases, there is a limitation in that performance improvement is difficult due to an increase in prediction difficulty. To overcome these limitations, (i) compressing the initially given high-dimensional label space into a low-dimensional latent label space, (ii) after performing training to predict the compressed label, (iii) restoring the predicted label to the high-dimensional original label space, research on label embedding is being actively conducted. Typical label embedding techniques include Principal Label Space Transformation (PLST), Multi-Label Classification via Boolean Matrix Decomposition (MLC-BMaD), and Bayesian Multi-Label Compressed Sensing (BML-CS). However, since these techniques consider only the linear relationship between labels or compress the labels by random transformation, it is difficult to understand the non-linear relationship between labels, so there is a limitation in that it is not possible to create a latent label space sufficiently containing the information of the original label. Recently, there have been increasing attempts to improve performance by applying deep learning technology to label embedding. Label embedding using an autoencoder, a deep learning model that is effective for data compression and restoration, is representative. However, the traditional autoencoder-based label embedding has a limitation in that a large amount of information loss occurs when compressing a high-dimensional label space having a myriad of classes into a low-dimensional latent label space. This can be found in the gradient loss problem that occurs in the backpropagation process of learning. To solve this problem, skip connection was devised, and by adding the input of the layer to the output to prevent gradient loss during backpropagation, efficient learning is possible even when the layer is deep. Skip connection is mainly used for image feature extraction in convolutional neural networks, but studies using skip connection in autoencoder or label embedding process are still lacking. Therefore, in this study, we propose an autoencoder-based label embedding methodology in which skip connections are added to each of the encoder and decoder to form a low-dimensional latent label space that reflects the information of the high-dimensional label space well. In addition, the proposed methodology was applied to actual paper keywords to derive the high-dimensional keyword label space and the low-dimensional latent label space. Using this, we conducted an experiment to predict the compressed keyword vector existing in the latent label space from the paper abstract and to evaluate the multi-label classification by restoring the predicted keyword vector back to the original label space. As a result, the accuracy, precision, recall, and F1 score used as performance indicators showed far superior performance in multi-label classification based on the proposed methodology compared to traditional multi-label classification methods. This can be seen that the low-dimensional latent label space derived through the proposed methodology well reflected the information of the high-dimensional label space, which ultimately led to the improvement of the performance of the multi-label classification itself. In addition, the utility of the proposed methodology was identified by comparing the performance of the proposed methodology according to the domain characteristics and the number of dimensions of the latent label space.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.67-86
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• 2020

Recommender Systems have been huge influence users and business more and more. Recently the importance of E-commerce has been reached rapid growth greatly in world-wide COVID-19 pandemic. Recommender system is the center of E-commerce lively. Top ranked E-commerce managers mentioned that recommender systems have a major influence on customer's purchase such as about 50% of Netflix, Amazon sales from their recommender systems. Most algorithms have been focused on improving accuracy of recommender system regardless of novelty, diversity, serendipity etc. Recommender systems with only high accuracy cannot satisfy business long-term profit because of generating sales polarization. In addition, customers do not experience enjoyment of shopping from only focusing accuracy recommender system because customer's preference is changed constantly. Therefore, recommender systems with various values need to be developed for user's high satisfaction. Reranking is the most useful methodology to realize diversity of recommender system. In this paper, diversity of recommender system is represented through constructing high similarity with users who have different preference using each user's purchased item's category algorithm. It is distinguished from past research approach which is changing the algorithm of recommender system without user's diversity preference level. We tried to discover user's diversity preference level and observed the results how the effect was different according to user's diversity preference level. In addition, graph-based recommender system was used to show diversity through user's network, not collaborative filtering. In this paper, Amazon Grocery and Gourmet Food data was used because the low-involvement product, such as habitual product, foods, low-priced goods etc., had high probability to show customer's diversity. First, a bipartite graph with users and items simultaneously is constructed to make graph-based recommender system. However, each users and items unipartite graph also need to be established to show diversity of recommender system. The weight of each unipartite graph has played crucial role changing Jaccard Distance of item's category. We can observe two important results from the user's unipartite network. First, the user's diversity preference level is observed from the network and second, dissimilar users can be discovered in the user's network. Through the research process, diversity of recommender system is presented highly with small accuracy loss and optimalization for higher accuracy is possible controlling diversity ratio. This paper has three important theoretical points. First, this research expands recommender system research for user's satisfaction with various values. Second, the graph-based recommender system is developed newly. Third, the evaluation indicator of diversity is made for diversity. In addition, recommender systems are useful for corporate profit practically and this paper has contribution on business closely. Above all, business long-term profit can be improved using recommender system with diversity and the recommender system can provide right service according to user's diversity level. Lastly, the corporate selling low-involvement products have great effect based on the results.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.150-162
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• 2021

Companies have recently become increasingly interested in corporate entrepreneurship to establish a core employment policy in order to secure and maintain core employees and to foster an innovation-oriented organizational culture. Therefore, The purpose of this study is to empirically analyze the causal relationship between core employment policies and the team leader's the perceived internal process organizational competency and job satisfaction, and to investigate whether corporate entrepreneurship has a moderation effect. Non-financial service industries including ICT companies were subject of the study and human capital corporate panel(HCCP) was utilized. The samples were 367 team leaders from 79 domestic companies. This study also applied Multi-Level Analysis(HLM), which simultaneously analyzes variables at both the individual level and the organizational level in order to improve the accuracy of the study. According to the result of the study analysis, core employment policies have a positive(+) impact on the perceived internal process organizational competency and job satisfaction. In addition, the moderation effect of corporate entrepreneurship was verified during the process when core employment policies influence the two outcome variables. corporate entrepreneurship was found to have a moderation effect that strengthens the influence on job satisfaction, but the moderation effect on the perceived internal process organizational competency was not statistically significant. These results confirm that organizational cultural factors such as corporate entrepreneurship are important influence variables in the process of influencing individual-level variables such as core employment policies. Academically, It suggests that in order to enhance the effectiveness of company strategies in respect of human resource management such as core employment policies, it is important to foster a cultural environment that suits the industry and characteristics of the organization. In addition, it suggested that companies in need of new innovation need to utilize corporate entrepreneurship.

• Journal of Nutrition and Health
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• v.54 no.2
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• pp.179-198
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• 2021

Purpose: This study examined general characteristics, health status, accessibility to medical services, health-related quality of life, dietary behavior, and energy and nutrient intakes of the elderly at different levels of food security utilizing data from the 7th Korea National Health and Nutrition Examination Survey (2016-2018). Methods: The elderly subjects (1,721 males and 2,271 females) were divided into 3 groups (secure, mildly insecure, moderately/severely insecure) according to their food security levels. Health and nutrient status was determined using energy intake, nutrient density, the prevalence of insufficient nutrient intake, dietary behavior, and health status. Results: The elderly with food insecurities had a lower self-evaluated health status and a higher prevalence of physician-diagnosed chronic diseases such as arthritis, osteoarthritis, rheumatoid arthritis, osteoporosis for males, and hypertension, stroke, arthritis, and osteoarthritis for females. The associated financial burden was the major reason for not accessing medical services in the food insecure group. Furthermore, the food insecure group had a higher risk of impaired health-related quality of life compared to the secure group. The proportion of subjects with an energy intake below the estimated energy requirement was higher in the food insecure group and a significantly higher prevalence of insufficient intake was observed for all the nutrients (proteins, vitamin A, vitamin B₁, vitamin B₂, niacin, vitamin C, calcium, and iron) assessed in this study compared to the food secure group. Conclusion: This study suggests that food insecurity poses a challenge to the health and nutritional status of the elderly population in Korea and needs proper management. It would be helpful to develop food and nutrition assistance programs to ensure the food stability of the elderly population and assure quality to address gaps in their nutrient intake.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.191-206
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• 2022

Recently, it is a de-facto approach to utilize a pre-trained language model(PLM) to achieve the state-of-the-art performance for various natural language tasks(called downstream tasks) such as sentiment analysis and question answering. However, similar to any other machine learning method, PLM tends to depend on the data distribution seen during the training phase and shows worse performance on the unseen (Out-of-Distribution) domain. Due to the aforementioned reason, there have been many efforts to develop domain-specified PLM for various fields such as medical and legal industries. In this paper, we discuss the training of a finance domain-specified PLM for the Korean language and its applications. Our finance domain-specified PLM, KB-BERT, is trained on a carefully curated financial corpus that includes domain-specific documents such as financial reports. We provide extensive performance evaluation results on three natural language tasks, topic classification, sentiment analysis, and question answering. Compared to the state-of-the-art Korean PLM models such as KoELECTRA and KLUE-RoBERTa, KB-BERT shows comparable performance on general datasets based on common corpora like Wikipedia and news articles. Moreover, KB-BERT outperforms compared models on finance domain datasets that require finance-specific knowledge to solve given problems.

• Journal of agricultural medicine and community health
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• v.47 no.4
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• pp.211-219
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• 2022

Objective: This study was conducted to investigate the awareness of work-related disease prevention of farmers. Method: As a research method, a qualitative focus group interview was conducted in 18 participants. Results: Prevention and management services for work-related diseases of farmers mostly are based on research from other fields and so are not highly effective because their content is not relevant to agricultural work. It has been suggested that such program designers be required to have some appropriate related knowledge, and that incentives and a certification system for participation in such education be established. To analyze work-related diseases of farmers, fields of prevention, diagnosis, treatment, and rehabilitation should be created. They demanded the designation of hospitals and the actualization of compensation for farmers' safety insurance. The work-related diseases to address were include musculoskeletal diseases, pesticide poisoning-related diseases (cardiovascular disease, respiratory disease), psychiatric diseases such as depression, and allergic diseases. However, this must have been the result of the harmful factors they felt during agricultural work. And for farmer patients diagnosed with work-related diseases, it was said to strengthen farmer safety insurance. Conclusion: In order to increase the safely and health effects of agricultural work, it is necessary to prevent and manage work-related diseases of farmers. Projects should be developed in consideration of cultural and economic barriers of farmers and the characteristics of the work.