Journal of Korea Society of Digital Industry and Information Management
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v.17
no.1
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pp.57-73
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2021
The purpose of this study is to analyze the diffusion period and productivity of smartwork in an organization. Firms are increasingly interested in smartwork for non contact work and working from home because of the corona 19. The smartwork is a new technology that changes face-to-face work in an organization. It helps the work of individuals and organizations regardless of time and place. The theoretical background describes the complexity, system thinking, diffusion theory, smart work, organizational resistance, and productivity. This study analyzes the diffusion period and productivity of smart work through business simulation techniques. A simulation study progresses four stages. There are problem definition, hypothesis establishment and causal loop diagram, model construction and verification, and policy evaluation. The simulation models contain an individual's resistance variables organizational investment and leadership variables related to the operation of smartwork. The organizational investment variables include organizational culture, legal system, implement systems and technology investment. The individual resistance variables include cognitive, attitude, structure and technological resistance. The leadership includes leadership interest variables and performance linkage variables. The simulation executed the changes of a people number adopting smart work and the organizational productivity monthly. As a result of the simulation, many organization members have accepted the smart work innovation after 20 months. The organizational productivity through smart work showed very high value after 16 months. In scenario analysis, the individuals' awareness and attitude resistance showed very important variables to productivity and a personal change of smart work adoption. Meanwhile, The organizational investment showed that the high driving-force increased not productivity and the low driving-force showed decreased low productivity. Also, leadership variables showed a powerful driver for changing smart work productivity. The implication of the study has suggested extending complexity, diffusion theory and organization resistance theory based on simulation methods.
International Journal of Internet, Broadcasting and Communication
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v.14
no.1
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pp.85-94
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2022
Recently, consumers who prefer contactless consumption are increasing due to pandemic trends such as Corona 19. This is the driving force for developing the last mile-based logistics ecosystem centered on the online e-commerce market. Lastmile led to the continued development of the logistics industry, but increased the amount of cargo in urban area, and caused social problems such as overcrowding of logistics. The courier service in the logistics base area utilizes the process of visiting the delivery site directly because the courier must precede the loading work of the cargo in the truck for the delivery of the ordered product. Currently, it's carried out as automated logistics equipment such as conveyor belt in unloading or classification stage, but the automation system isn't applied, so the work efficiency is decreasing and the intensity of the courier worker's labor is increased. In particular, small-scale courier workers belonging to the sub-terminal unload at night at underdeveloped facilities outside the city center. Therefore, the productivity of the work is lowered and the risk of safety accidents is exposed, so robot-based loading technology is needed. In this paper, we have derived the top-level concept and requirements of robot-based loading system to increase the flexibility of logistics processing and to ensure the safety of courier drivers. We defined algorithms and motion concepts to increase the cargo loading efficiency of logistics sub-terminals through the requirements of end effector technology, which is important among concepts. Finally, the control technique was proposed to determine and position the load for design input development of the automatic conveyor system.
We investigate 20 post-coronal mass ejection (CME) blobs formed in the post-CME current sheet (CS) that were observed by K-Cor on 2017 September 10. By visual inspection of the trajectories and projected speed variations of each blob, we find that all blobs except one show irregular "zigzag" trajectories resembling transverse oscillatory motions along the CS, and have at least one oscillatory pattern in their instantaneous radial speeds. Their oscillation periods are ranging from 30 to 91 s and their speed amplitudes from 128 to 902 km s-1. Among 19 blobs, 10 blobs have experienced at least two cycles of radial speed oscillations with different speed amplitudes and periods, while 9 blobs undergo one oscillation cycle. To examine whether or not the apparent speed oscillations can be explained by vortex shedding, we estimate the quantitative parameter of vortex shedding, the Strouhal number, by using the observed lateral widths, linear speeds, and oscillation periods of the blobs. We then compare our estimates with theoretical and experimental results from MHD simulations and fluid dynamic experiments. We find that the observed Strouhal numbers range from 0.2 to 2.1, consistent with those (0.15-3.0) from fluid dynamic experiments of bluff spheres, while they are higher than those (0.15-0.25) from MHD simulations of cylindrical shapes. We thus find that blobs formed in a post-CME CS undergo kinematic oscillations caused by fluid dynamic vortex shedding. The vortex shedding is driven by the interaction of the outward-moving blob having a bluff spherical shape with the background plasma in the post-CME CS.
In the era of the fourth industrial revolution technology, the inclusion of personalized nutrition for healthcare (PNH), when establishing a healthcare platform to prevent chronic diseases such as obesity, diabetes, cerebrovascular and cardiovascular disease, pulmonary disease, and inflammatory diseases, enhances the national competitiveness of global healthcare markets. Furthermore, since the government experienced COVID-19 and the population dead cross in 2020, as well as numerous health problems due to an increasing super-aged Korean society, there is an urgent need to secure, develop, and utilize PNH-related technologies. Three conditions are essential for the development of PNH technologies. These include the establishment of causality between obesity genome (genotype) and prevalence (phenotype) in Koreans, validation of clinical intervention research, and securing PNH-utilization technology (i.e., algorithm development, artificial intelligence-based platform, direct-to-customer [DTC]-based PNH, etc.). Therefore, a national control tower is required to establish appropriate PNH infrastructure (basic and clinical research, cultivation of PNH-related experts, etc.). The post-corona era will be aggressive in sharing data knowledge and developing related technologies, and Korea needs to actively participate in the large-scale global healthcare markets. This review provides the importance of scientific evidence based on a huge dataset, which is the primary prerequisite for the DTC obesity gene-based PNH technologies to be competitive in the healthcare market. Furthermore, based on comparing domestic and internationally approved DTC obese genes and the current status of Korean obesity genome-based PNH research, we intend to provide a direction to PNH planners (individuals and industries) for establishing scientific PNH guidelines for the prevention of obesity.
Due to the 3 years and 4 months of corona, many things have changed throughout society, such as social activities, free movement, and lifestyle. One of them is the increasing public interest and demand for walking tours. Public awareness of health and leisure activities has increased due to lifestyle changes, aging, and urbanization following the spread of infectious diseases such as COVID-19, and demand for walking tour services is also increasing. As of 2019, nationwide About 560 'Walking Trails' of 1,849 courses were created, with a total length of 18,000 km. In this study, in a situation where social interest and necessity for walking tours are increasing, studies related to walking tours are reviewed, and sustainable management plans for walking tours are proposed. To this end, the concept and research trends of walking tours were examined through literature related to walking tours, and in-depth interviews were conducted with a total of 17 people, 8 visitors and 9 officials, with Ansan Daebudo Haesol-gil as the target. Visitors In-depth interviews with 180 contents were coded, and 147 effective contents were divided into 20 subcategories and organized into 7 upper categories. In-depth interviews with 101 stakeholders were individually coded, 96 effective contents were divided into 14 subcategories, and organized into 5 upper categories. After that, it was reviewed based on the contents organized through qualitative content analysis, and the Five implications were derived. The significance of this study is that the study was conducted on specific Haesol-gil in the suburbs of the metropolitan area. The limitation of this study was that more detailed investigations and considerations were not conducted on the positive and negative effects of walking tours on the Daebudo area. As a follow-up study, academic arrangements and case studies on regional regeneration through walking tours are required.
Park, Hakgwon;Lim, Young-Hwan;Park, Hyeokgon;Hwang, Joongwon;Lee, Sangran;Cho, Eunsang;Lin, Bin
The Journal of the Convergence on Culture Technology
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v.8
no.3
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pp.463-468
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2022
The prolonged of the Post Corona made many industry's paradigm. It's become very important In the industries products that customers directly touch and use. To cope with this situation, The Cosmetics industry has recently introduced various untact services. many customers would like to try these new services. Typically, online survey services recommend personalized products. but these services reached its limit later. This paper research how to recommend products and define skine type with AI Image diagnosis module combine with legacy survey system.
To treat the novel COronaVIrus Disease (COVID), comparatively fewer medicines have been approved. Due to the global pandemic status of COVID, several medicines are being developed to treat patients. The modern COVID medicines development process has various challenges, including predicting and detecting hazardous COVID medicine responses. Moreover, correctly predicting harmful COVID medicine reactions is essential for health safety. Significant developments in computational models in medicine development can make it possible to identify adverse COVID medicine reactions. Since the beginning of the COVID pandemic, there has been significant demand for developing COVID medicines. Therefore, this paper presents the transferlearning methodology and a multilabel convolutional neural network for COVID (MLCNN-COV) medicines development model to identify negative responses of COVID medicines. For analysis, a framework is proposed with five multilabel transfer-learning models, namely, MobileNetv2, ResNet50, VGG19, DenseNet201, and Inceptionv3, and an MLCNN-COV model is designed with an image augmentation (IA) technique and validated through experiments on the image of three-dimensional chemical conformer of 17 number of COVID medicines. The RGB color channel is utilized to represent the feature of the image, and image features are extracted by employing the Convolution2D and MaxPooling2D layer. The findings of the current MLCNN-COV are promising, and it can identify individual adverse reactions of medicines, with the accuracy ranging from 88.24% to 100%, which outperformed the transfer-learning model's performance. It shows that three-dimensional conformers adequately identify negative COVID medicine responses.
Journal of the Korea Academia-Industrial cooperation Society
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v.19
no.1
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pp.603-608
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2018
Although the voltage-applied discharge method is most widely used in the semiconductor and display industries, periodic management costs are incurred because the method causes defects due to the absorption of ambient fine dust and causes emitter tip contamination due to the discharge. The emitter tip contamination problem is caused by the accumulation of fine particles in ambient air due to the corona discharge of the ionizer. Fuzzy ball generation accelerates the wear of the emitter tip and deteriorates the performance of the ionizer. Although a mechanical cleaning method using a manual brush or an automatic brush is effective for contaminant removal, it requires management of additional mechanical parts by the user. In some cases, contaminants accumulated in the emitter may be transferred to the wafer or product. In order to solve this problem, we developed an ionizer for a clean environment that can remove the pencil-type emitter tip and directly ionize the surrounding gas molecules using the tungsten wire located inside the ion tank. As a result of testing and certification by the Korea Institute of Machinery and Materials, the average concentration was $0.7572particles/ft^3$, the decay time was less than two seconds, and the ion valance was 7.6 V, which is satisfactory.
Currently, the method of user-follwoing in intelligent cooperative robots usually based in vision system and using Lidar is common and have excellent performance. But in the closed space of Corona 19, which spread worldwide in 2020, robots for cooperation with medical staff were insignificant. This is because Medical staff are all wearing protective clothing to prevent virus infection, which is not easy to apply with existing research techniques. Therefore, in order to solve these problems in this paper, the ultrasonic sensor is separated from the transmitting and receiving parts, and based on this, this paper propose that estimating the user's position and can actively follow and cooperate with people. However, the ultrasonic sensors were partially applied by improving the Median filter in order to reduce the error caused by the short circuit in communication between hard reflection and the number of light reflections, and the operation technology was improved by applying the curvature trajectory for smooth operation in a small area. Median filter reduced the error of degree and distance by 70%, vehicle running stability was verified through the training course such as 'S' and '8' in the result.
The purpose of this study is to examine the current status and components of Korean National Debt and to analyze the effects of each component on National Debt. In the Korean Statistical Information Service (KOSIS), we searched for data such as General Accounting Deficit Conservation, For Foreign Exchange Market Stabilization, For Common Housing Stability, Local Government Net Debt Public Funds, etc that constitute National Debt. The analysis period used a total of 23 annual data from 1997 to 2019. The data collected in this study use the rate of change compared to the previous year for each component. Using this, this study attempted index analysis, numerical analysis, and model analysis. Correlation analysis result, the National Debt has a high relationship with the For Common Housing Stability. For Foreign Exchange Market Stabilization, Public Funds, etc., but has a low relationship with the Local Government Net Debt. Since 1997, National Debt has been increasing similarly to the For Foreign Exchange Market Stabilization, For Common Housing Stability and Public Funds etc. Since 2020, Korea is expected to increase significantly in terms of For Common Housing Stability and Public Funds, etc due to Corona19. At a time when the global economic situation is difficult, Korea's National Debt is expected to increase significantly due to the use of national disaster subsidies. However, if possible, the government expects to operate efficiently for economic growth and financial market stability.
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