• Journal of Nutrition and Health
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• v.55 no.1
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• pp.174-187
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• 2022

Purpose: This study was performed to evaluate an education program for housewives to reduce sodium intake based on the social cognitive theory. Methods: Housewives (n = 387) received 2 education sessions focused on food purchase and cooking, and completed a questionnaire on their perceptions of environmental, cognitive, and behavioral factors and the stages of behavioral change to reducing sodium intake both before and after the education program. Results: After the education program, the recognition of social efforts for sodium reduction and sodium labeling and experience with low-sodium products increased. Positive expectancies for the prevention of osteoporosis by the reduction of sodium were enhanced while the main barriers in practicing sodium reduction decreased, especially 'interrupting social relationships when dining with others', 'bad taste', 'preference for soup or stew', and 'limited knowledge and skills to practice'. In addition, cognition and nutrition knowledge related to reducing sodium intake were improved on all scores, but the effect on self-efficacy and dietary behavior was limited to only a few items. The percentage of participants in the pre-action stage (including pre-contemplation, contemplation, and preparation stages) for reducing sodium intake decreased from 43.2% before education to 21.5% after education, while that in the action stage increased from 19.6% before education to 43.5% after education (p < 0.001). The education program had the most significant impact on participants who were in the pre-action stage and showed improved scores in all sections. Conclusion: These results suggest that a customized education program for housewives could be an effective tool to reduce sodium intake by improving personal expectancies, cognition, and nutrition knowledge regarding sodium reduction and enabling a greater section of the population to move to the action stage of reducing sodium intake.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.114-129
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• 2023

In the era of the 4th industrial revolution, the importance of the 4th industrial revolution technology is increasing in the service industry. The purpose of this study is to identify the development and utilization status of the 4th industrial revolution technology in the service industry and to derive the characteristics and implications of the 4th industrial revolution technology innovation in the service industry. In this study, research and analysis were conducted based on the business activity survey data in order to identify the technological innovation characteristics of the 4th industrial revolution in the service industry. The 4th industrial revolution technology in the service industry was analyzed in terms of company ratio, technology development and utilization rate, development/utilization technology, technology application field, and technology development method. In addition, the trend of the 4th industrial revolution technology change in the service industry was also analyzed. The 4th industrial revolution technology utilization and development status of other industries was compared and analyzed. In particular, the service industry 4th industrial revolution technology innovation type was divided into 4 types from the perspective of the 4th industrial revolution company ratio and the 4th industrial revolution company ratio growth rate, and types for each service industry were derived. The characteristics and implications of the 4th industrial revolution technology innovation in the service industry were presented from nine perspectives. As a result of the study, it was found that companies in the service industry were developing or using 4th industrial revolution technologies more actively than companies in other industries, and it was analyzed that the gap was further widening. By service industry, information and communication, finance and insurance, and educational service showed relatively high rates of developing or utilizing 4th industrial revolution technologies. The service industries in which the share of 4th industrial revolution companies increased the most were real estate, education service, health and social welfare service. In particular, cloud, big data, and artificial intelligence were analyzed as the three core technologies of the fourth industrial revolution. The service industry can be classified into 4 types in terms of the 4th industrial revolution company ratio and growth rate, and service industry innovation measures that reflect the differentiated innovation characteristics of each type are needed.

• Journal of Life Science
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• v.33 no.10
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• pp.820-827
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• 2023

Since COVID-19 began at the end of 2019, the wearing time of protective clothing used to prevent pathogenic bacteria and virus infection has increased, and the development of safe protective materials that are human-friendly and have antibacterial and antiviral functions has been required. In this study, we investigated the possibility of developing natural antibacterial protection materials using ethanol extract of the medicinal plant Zanthoxylum Piperitum DC. The antibacterial activity assay of the 80% ethanol extract of Z. piperitum DC leaves against various nosocomial infectious bacteria, using the disk diffusion method, showed that Staphylococcus aureus ATCC 25923, Klebsiella pneumoniae ATCC 13883, Salmonella typhimurium, and Aeromonas hydrophila are sensitive to the inhibitory action of the extract. The IC₅₀ values of the ethanol extract against S. aureus, K. pneumoniae, P. vulgaris and A. hydrophila were about 0.59 mg/ml, 0.50 mg/ml, 1.06 mg/ml, and 0.06 mg/ml, respectively. To determine whether the ethanol extract of Z. piperitum DC leaves can be applied to the development of antibacterial protective fabric, the ethanol extract was tested using a protective fabric from the KM Health Care Corp. using the JIS L1902-Absorption method. As a result, the bacteriostatic and bactericidal activity values of S. aureus ATCC 25923 and K. pneumoniae ATCC 13883 appeared to be more than 2.0 when treated with the ethanol extract at a concentration of 1% (w/v). Together, these results suggest that Z. piperitum DC leaves can be applied to develop natural antibacterial functional protective fabrics.

• Korean Journal of Ecology and Environment
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• v.56 no.3
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• pp.187-195
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• 2023

Almost all of the water from agricultural dams located to the upper of the Yeongsan river is supplied as irrigation water for farmland and thus is not discharged to the main stream of the river. Also, most of the irrigation water does not return to the river after use, adding to the lack of flow in the main stream. As a result, the water quality and aquatic health of the river have become the poorest among the four major rivers in Korea. Therefore, in this study, several strategies for water quality improvement of the river were developed considering pollution reduction and flow rate increase, and their effect analysis was performed using a water quality model. The results of this study showed that the target water quality of the Yeongsan river could be achieved if flow increase strategies (FISs) are intensively pursued in parallel with pollution reduction. The reason is because the water quality of the river has been steadily improved through pollution reduction but this method is now nearing the limit. In addition, rainfall-related FISs such as dam construction and water distribution adjustment may be less effective or lost if a megadrought continues due to climate change and then rainfall does not occur for a long time. Therefore, in the future, if the application conditions for the FISs are similar, the seawater desalination facility, which is independent of rainfall, should be considered as the priority installation target among the FISs. The reason is that seawater desalination facilities can replace the water supply function of dams, which are difficult to newly build in Korea, and can be useful as a climate change adaptation facility by preventing water-related disasters in the event of a long-term megadrought.

• Information Systems Review
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• v.19 no.2
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• pp.1-19
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• 2017

Original scripts of e-learning lectures for the CEOs of corporation S were analyzed using topic analysis, which is a text mining method. Twenty-two topics were extracted based on the keywords chosen from five-year records that ranged from 2011 to 2015. Research analysis was then conducted on various issues. Promising topics were selected through evaluation and element analysis of the members of each topic. In management and economics, members demonstrated high satisfaction and interest toward topics in marketing strategy, human resource management, and communication. Philosophy, history of war, and history demonstrated high interest and satisfaction in the field of humanities, whereas mind health showed high interest and satisfaction in the field of in lifestyle. Studies were also conducted to identify topics on the proportion of content, but these studies failed to increase member satisfaction. In the field of IT, educational content responds sensitively to change of the times, but it may not increase the interest and satisfaction of members. The present study found that content production for CEOs should draw out deep implications for value innovation through technology application instead of simply ending the technical aspect of information delivery. Previous studies classified contents superficially based on the name of content program when analyzing the status of content operation. However, text mining can derive deep content and subject classification based on the contents of unstructured data script. This approach can examine current shortages and necessary fields if the service contents of the themes are displayed by year. This study was based on data obtained from influential e-learning companies in Korea. Obtaining practical results was difficult because data were not acquired from portal sites or social networking service. The content of e-learning trends of CEOs were analyzed. Data analysis was also conducted on the intellectual interests of CEOs in each field.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.187-201
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• 2024

Osteoporosis is a major health issue globally, often remaining undetected until a fracture occurs. To facilitate early detection, deep learning (DL) models were developed to classify osteoporosis using abdominal computed tomography (CT) scans. This study was conducted using retrospectively collected data from 3,012 contrast-enhanced abdominal CT scans. The DL models developed in this study were constructed for using image data, demographic/clinical information, and multi-modality data, respectively. Patients were categorized into the normal, osteopenia, and osteoporosis groups based on their T-scores, obtained from dual-energy X-ray absorptiometry, into normal, osteopenia, and osteoporosis groups. The models showed high accuracy and effectiveness, with the combined data model performing the best, achieving an area under the receiver operating characteristic curve of 0.94 and an accuracy of 0.80. The image-based model also performed well, while the demographic data model had lower accuracy and effectiveness. In addition, the DL model was interpreted by gradient-weighted class activation mapping (Grad-CAM) to highlight clinically relevant features in the images, revealing the femoral neck as a common site for fractures. The study shows that DL can accurately identify osteoporosis stages from clinical data, indicating the potential of abdominal CT scans in early osteoporosis detection and reducing fracture risks with prompt treatment.

• Trans-
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• v.16
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• pp.1-31
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• 2024

The advent of digital media has facilitated easy access for adolescents to environments conducive to the purchase of narcotics. In particular, there's an increasing trend in the purchase and consumption of narcotics mediated through Social Network Services (SNS) and messenger services. Adolescents, sensitive to such environments, are at risk of experiencing neurological and mental health issues due to narcotic addiction, increasing their exposure to criminal activities, hence necessitating national-level management and support. Consequently, the quest for sustainable treatment methods for adolescents exposed to narcotics emerges as a critical challenge. In the context of high relapse rates in narcotic addiction, the necessity for cost-effective and user-friendly treatment programs is emphasized. This study conducts a literature review aimed at utilizing digital platforms to create an environment where adolescents can voluntarily participate, focusing on the development of therapeutic content through art. Specifically, it reviews societal perceptions and treatment statuses of adolescent drug addiction, analyzes the impact of narcotic addiction on adolescent brain activity and cognitive function degradation, and explores approaches for developing digital therapeutics to promote the rehabilitation of the addicted brain through analysis of precedential case studies. Moreover, the study investigates the benefits that the integration of digital therapeutic approaches and art therapy can provide in the treatment process and proposes the possibility of enhancing therapeutic effects through various treatment programs such as drama therapy, music therapy, and art therapy. The application of art therapy methods is anticipated to offer positive effects in terms of tool expansion, diversification of expression, data acquisition, and motivation. Through such approaches, an enhancement in the effectiveness of treatments for adolescent narcotic addiction is anticipated. Overall, this study undertakes foundational research for the development of digital therapeutics and related applications, offering economically viable and sustainable treatment options in consideration of the societal context of adolescent narcotic addiction.

• Journal of Nutrition and Health
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• v.57 no.4
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• pp.451-467
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• 2024

Purpose: This study aimed to develop a four-hour food additive education program for elementary school students to provide them with accurate information on food additives. Methods: A survey was conducted among 133 elementary school students living in Gyeonggi Province to identify the level of food additive awareness. A four-hour food additive education program and educational materials (PPT, activity sheets, and teacher guidelines) were developed based on the results of the food additive awareness survey. The developed educational programs were based on the Theoretical Model of Stages of Behavior Change. An elementary school nutrition teacher conducted a pilot education for 83 elementary school students to evaluate the feasibility of the developed education program. A survey was conducted to evaluate the effectiveness and satisfaction of the pilot education program. Results: The results of the Food Additive Awareness Survey showed that only 42.1% of people were aware of food additives; 46.3% wanted to know more about food additives, and 54.3% required food additive education. Food coloring (44.7%) and artificial sweeteners (18.7%) were the most common food additives of interest. What they wanted to know about food additives was the safety of food additives (36.8%) and the role and function of food additives (20.3%). After the pilot training on food additives, the level of awareness of food additives was improved significantly, and the percentage of participants who recognized the need for food additive education and promotion increased. According to the satisfaction survey of the food additives education, the interest, understanding, real-life application, learning method, and content amount were approximately 90%. Conclusion: The educational program developed through this study will change the negative perceptions of food additives in elementary school students to a positive one. It will do so by helping nutrition educators educate students on this important subject.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.107-118
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• 2016

The advent of 5G mobile communications, which is expected in 2020, will provide many services such as Internet of Things (IoT) and vehicle-to-infra/vehicle/nomadic (V2X) communication. There are many requirements to realizing these services: reduced latency, high data rate and reliability, and real-time service. In particular, a high level of reliability and delay sensitivity with an increased data rate are very important for M2M, IoT, and Factory 4.0. Around the world, 5G standardization organizations have considered these services and grouped them to finally derive the technical requirements and service scenarios. The first scenario is broadcast services that use a high data rate for multiple cases of sporting events or emergencies. The second scenario is as support for e-Health, car reliability, etc.; the third scenario is related to VR games with delay sensitivity and real-time techniques. Recently, these groups have been forming agreements on the requirements for such scenarios and the target level. Various techniques are being studied to satisfy such requirements and are being discussed in the context of software-defined networking (SDN) as the next-generation network architecture. SDN is being used to standardize ONF and basically refers to a structure that separates signals for the control plane from the packets for the data plane. One of the best examples for low latency and high reliability is an intelligent traffic system (ITS) using V2X. Because a car passes a small cell of the 5G network very rapidly, the messages to be delivered in the event of an emergency have to be transported in a very short time. This is a typical example requiring high delay sensitivity. 5G has to support a high reliability and delay sensitivity requirements for V2X in the field of traffic control. For these reasons, V2X is a major application of critical delay. V2X (vehicle-to-infra/vehicle/nomadic) represents all types of communication methods applicable to road and vehicles. It refers to a connected or networked vehicle. V2X can be divided into three kinds of communications. First is the communication between a vehicle and infrastructure (vehicle-to-infrastructure; V2I). Second is the communication between a vehicle and another vehicle (vehicle-to-vehicle; V2V). Third is the communication between a vehicle and mobile equipment (vehicle-to-nomadic devices; V2N). This will be added in the future in various fields. Because the SDN structure is under consideration as the next-generation network architecture, the SDN architecture is significant. However, the centralized architecture of SDN can be considered as an unfavorable structure for delay-sensitive services because a centralized architecture is needed to communicate with many nodes and provide processing power. Therefore, in the case of emergency V2X communications, delay-related control functions require a tree supporting structure. For such a scenario, the architecture of the network processing the vehicle information is a major variable affecting delay. Because it is difficult to meet the desired level of delay sensitivity with a typical fully centralized SDN structure, research on the optimal size of an SDN for processing information is needed. This study examined the SDN architecture considering the V2X emergency delay requirements of a 5G network in the worst-case scenario and performed a system-level simulation on the speed of the car, radius, and cell tier to derive a range of cells for information transfer in SDN network. In the simulation, because 5G provides a sufficiently high data rate, the information for neighboring vehicle support to the car was assumed to be without errors. Furthermore, the 5G small cell was assumed to have a cell radius of 50-100 m, and the maximum speed of the vehicle was considered to be 30-200 km/h in order to examine the network architecture to minimize the delay.

• Journal of Nutrition and Health
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• v.42 no.1
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• pp.78-96
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• 2009

The purpose of this study was to analyze and evaluate the menu served in government offices foodservice by using Kasavana & Smith's Menu-Engineering. Sales and food costs were collected from the daily sales reports for a year from Jan 2 to Dec 31 in 2007. Calculation for menu analysis and customer's data were done by computer using the MS 2003 Excel spreadsheet program and SPSS 12.0 package program. Menu mix% (MM%) and unit contribution margin were used as variables by Kasavana & Smith. Four possible classifications by Menu-Engineering technique were turned out as 'STAR', 'PLOWHORSE', 'PUZZLE', 'DOG'. The main menus served during a year were 128 dishes and about 141 peoples visited this restaurant daily. The mean age of the men was $44.1\;{\pm}\;6.3$, women were $32.7\;{\pm}\;6.4$ and showed that was statistically higher than that of women (p < .0001). The rates of STAR menus were 'Western style (75.0%)', 'guk/tang-ryu (48.1%)', 'jjigae/ jeongol-ryu (23.1%)', 'bap-ryu (17.2%)' in sequence. There were no STAR menus in gui/jorim/jjim-ryu. PLOWHORSE menus were 'gui-ryu (75.0%)', 'guk/tang-ryu (29.6%)', 'bap-ryu (27.6%)' in sequence. There were no PUZZLE or DOG menus in 'jjigae/jeongol-ryu'. PUZZLE menus were 'jorim/jjim-ryu and Myeonryu (each 33.3%)', 'bap-ryu (31.0%)' in sequence. PUZZLE menus were a lots of 'Chinese food (75.0%)' and 'myeonryu (55.6%)'. This study provides the basic data based on regularly menu analysis method applied the scientific menu analysis techniques in government offices food services, I'd like to suggest that the menu management must be done based on the necessity and result of menu analysis according to the seasonal and middle, long-term plans.