• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.869-877
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• 2018

The area of desert in East Asia is increasing every year, and it cause a great cost of social damage. Because desert is widely distributed and it is difficult to approach people, remote sensing using satellites is commonly used. But the study of desert area comparison is insufficient which is calculated by satellite sensor. It is important to recognize the characteristics of the desert area data that are calculated for each sensor because the desert area calculated according to the selection of the sensor may be different and may affect the climate prediction and desertification prevention measures. In this study, the desert area of Northeast Asia in 2001-2013 was calculated and compared using Moderate Resolution Imaging Spectroradiometer (MODIS) and Vegetation. As a result of the comparison, the desert area of Vegetation increased by $3,020km^2/year$, while in the case of MODIS, it decreased by $20,911km^2/year$. We performed indirect validation because It is difficult to obtain actual data. We analyzed the correlation with the occurrence frequency of Asian dust affected by desert area change. As a result, MODIS showed a relatively low correlation with R = 0.2071 and Vegetation had a relatively high correlation with R = 0.4837. It is considered that Vegetation performed more accurate desert area calculation in Northeast Asian desert area.

• Journal of Chest Surgery
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• v.52 no.4
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• pp.248-329
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• 2019

Background: Though clinical practice guidelines (CPGs) for cardiac rehabilitation (CR) are an effective and widely used treatment method worldwide, they are as yet not widely accepted in Korea. Given that cardiovascular disease is the second leading cause of death in Korea, it is urgent that CR programs be developed. In 2008, the Government of Korea implemented CR programs at 11 university hospitals as part of its Regional Cardio-Cerebrovascular Center Project, and 3 additional medical facilities will be added in 2019. In addition, owing to the promotion of CR nationwide and the introduction of CR insurance benefits, 40 medical institutions nationwide have begun CR programs even as a growing number of medical institutions are preparing to offer CR. The purpose of this research was to develop evidence-based CPGs to support CR implementation in Korea. Methods: This study is based on an analysis of CPGs elsewhere in the world, an extensive literature search, a systematic analysis of multiple randomized control trials, and a CPG management, development, and assessment committee comprised of 33 authors-primarily rehabilitation specialists, cardiologists, and thoracic surgeons in 21 university hospitals and 2 general hospitals. Twelve consultants, primarily rehabilitation, sports medicine, and preventive medicine specialists, CPG experts, nurses, physical therapists, clinical nutritionists, and library and information experts participated in the research and development of these CPGs. After the draft guidelines were developed, 3 rounds of public hearings were held with staff members from relevant academic societies and stakeholders, after which the guidelines were further reviewed and modified. Results: CR involves a more cost-effective use of healthcare resources relative to that of general treatments, and the exercise component of CR lowers cardiovascular mortality and readmission rates, regardless of the type of coronary heart disease and type and setting of CR. Conclusion: Individualized CR programs should be considered together with various factors, including differences in heart function and lifestyle, and doing so will boost participation and adherence with the CR program, ultimately meeting the final goals of the program, namely reducing the recurrence of myocardial infarction and mortality rates.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.177-192
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• 2021

The Development Assistance Committee of the Organization for Economic Cooperation and Development discusses the reorganization of the five evaluation criteria of the Public Development Assistance Committee, which are used internationally, and the five evaluation criteria including adequacy, efficiency, effectiveness, impact, and sustainability when assessing public development assistance in 1991. This study is to derive alternatives by applying the evaluation criteria of the Development Assistance Committee of the Organization for Economic Cooperation and Development in the evaluation of the inclusive business program being implemented in Nepal since 2019. As a result of the study, the adequacy of Nepal's inclusive business program was consistent with continuous employment and job creation for vulnerable groups such as disabled and orphan women. Efficiency can be said to be efficient in that processes such as work order and work confirmation are made with an electronic management tool, and delivery of the result is transmitted online, saving time and cost compared to other industries. The effectiveness of this project can be said to be an effective program in that it provides high-quality jobs such as providing specialized computer graphics education for the vulnerable, such as disabled and orphan women in Nepal, and hiring graduates as employees. Sustainability is the point that KOICA's inclusive business program has enabled vulnerable groups in the existing fields of agriculture and manufacturing to engage in the computer graphics industry, and the scalability of movies, characters, education businesses, and role models in other countries.However, considering that the scale of public development assistance will continue to increase in the future, it is necessary to establish a systematic monitoring system and a recirculation system so that the project between the donor and recipient countries can continue.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.105-120
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• 2020

This study explores the process of the actual content production and distribution, by creating a YouTube channel to promote the popular music contents produced by the researcher, which thus reflects the reality where the production of video contents rapidly increases. A YouTube channel titled "Alida Music", of which the focus was to promote indie musicians, was created on February 2019. The contents of 10 indie musicians were produced in one-take live format. The information of the indie musicians was displayed in the form of a screen business card, with their e-mail address and SNS account at the top. Therefore, this promotional design was named "Card Live". Promotional video contents marked with the QR code in the lower right on the screen were produced, along with the promotional phrase "Communicate directly with the artist through the QR code", which allows viewers to watch other contents of the indie musician when they scan the QR code. This research conducted a study on how to improve and promote "Card Live" contents of "Alida Music", which were produced through this process. A group interview targeting five indie musicians, among whom one participant deemed significant was selected to conduct a one-to-one in-depth interview. As a result of the study, the following three conclusions were drawn. First, YouTube was found to be the medium with the greatest influence and highest efficiency at the lowest cost. Second, the evaluation of the participants on "Card Live" were divided into the three categories: need for one-take live, the design elements of "Card Live", and scanning issues of the QR code. Third, there is a need for promotional methods that can effectively utilize the media aspects of YouTube: the channel management issues such as raising public awareness as well as the number of subscribers of "Alida Music" should be resolved and measures to effectively use various media including other SNS should be developed. In terms of its content, it is imperative to recruit diverse performers to make various contents, as well as to come up with ways to link "Card Live" contents with offline. Based on these results, "Card Live" contents should be further revised and complemented in order to provide interesting contents to consumers, which will further develop "Alida Music" as a platform where various musicians and companies meet, thereby inducing contracts with popular music agencies and generating advertising revenues. However, since this study was carried out only with the limited number of participants, future studies should include more participants to bring forth a variety of promotional plans and improvement measures. Also, in the era of consuming contents through smart devices, the fact that some features of "Card Live" were available only on PC, did not fully reflect the characteristics of the times. In the future research, various contents that smartphone users can access and view freely without PC should be produced.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.69-77
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• 2022

The 3D spatial model is an analysis framework for solving urban problems and is used in various fields such as urban planning, environment, land and housing management, and disaster simulation. The utilization of drones that can capture 3D images in a short time at a low cost is increasing for the construction of 3D spatial model. In terms of building a virtual city and utilizing simulation modules, high location accuracy of aerial survey and precision of 3D spatial model function as important factors, so a method to increase the accuracy has been proposed. This study analyzed location accuracy of aerial survey and precision of 3D spatial model by each condition of aerial survey for urban areas where buildings are densely located. We selected Daerim 2-dong, Yeongdeungpo-gu, Seoul as a target area and applied shooting angle, shooting altitude, and overlap rate as conditions for the aerial survey. In this study, we calculated the location accuracy of aerial survey by analyzing the difference between an actual survey value of CPs and a predicted value of 3D spatial Model. Also, We calculated the precision of 3D spatial Model by analyzing the difference between the position of Point cloud and the 3D spatial Model (3D Mesh). As a result of this study, the location accuracy tended to be high at a relatively high rate of overlap, but the higher the rate of overlap, the lower the precision of 3D spatial model and the higher the shooting angle, the higher precision. Also, there was no significant relationship with precision. In terms of baseline-height ratio, the precision tended to be improved as the baseline-height ratio increased.

• Journal of Korea Port Economic Association
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• v.38 no.1
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• pp.1-14
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• 2022

The change in the management environment of the logistics industry in the era of global competition is becoming an era in which customers choose companies. Differentiation from competitors through the provision of products and services suitable for customers As customers' choices change depending on their superiority, companies are constantly striving to receive or retain customers' choices. Ultimately, this competitive structure can be seen as the importance of long-term relationship building. Therefore, in this study, we examined how factors related to transaction characteristics performed by logistics companies for customer satisfaction in the transaction relationship between cargo companies and shippers affect performance and long-term transaction intentions. First, we derived the factors of logistics service, cost, logistics infrastructure, and company competency, which are transaction characteristics factors of a logistics company that must be specifically realized for customer satisfaction in transactions between logistics companies. Second, we analyzed how the transaction characteristics factors of a logistics company affect the company's performance, and finally, how the company's performance factors affect long-term transaction intentions. As a result of empirical analysis, there were no statistically significant results on the relationship between transaction characteristics and performance of logistics companies, which can be attributed to the small size of the logistics companies that were the sample. In other words, logistics companies that do not have sufficient capacity to provide services at low prices have no choice but to engage in constant bleeding competition. It can be seen that it reflects the characteristics of the industry. On the other hand, the relationship between corporate performance factors and long-term transaction intention was found to have a positive relationship. The higher the level of partnership with logistics companies and visible financial performance is, the higher the transaction will be in the future, and the more the transaction volume will be gradually increased. And even if it costs a little more, it can be seen that the intention to continue trading is greatly expressed.

• The Journal of Bigdata
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• v.8 no.1
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• pp.111-129
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• 2023

With the diffusion of digital innovation, the adoption of innovative medical technologies based on artificial intelligence is increasing in the medical field. This is driving the launch and adoption of AI-based SaMD(Software as a Medical Device), but there is a lack of research on the factors that influence the adoption of SaMD by medical institutions. The purpose of this study is to identify key factors that influence medical institutions' decisions to adopt AI-based SaMDs, and to analyze the weights and priorities of these factors. For this purpose, we conducted Delphi surveys based on the results of literature studies on technology acceptance models in healthcare industry, medical AI and SaMD, and developed a research model by combining HOTE(Human, Organization, Technology and Environment) framework and HABIO(Holistic Approach {Business, Information, Organizational}) framework. Based on the research model with 5 main criteria and 22 sub-criteria, we conducted an AHP(Analytical Hierarchy Process) analysis among the experts from domestic medical institutions and SaMD providers to empirically analyze SaMD adoption factors. The results of this study showed that the priority of the main criteria for determining the adoption of AI-based SaMD was in the order of technical factors, economic factors, human factors, organizational factors, and environmental factors. The priority of sub-criteria was in the order of reliability, cost reduction, medical staff's acceptance, safety, top management's support, security, and licensing & regulatory levels. Specifically, technical factors such as reliability, safety, and security were found to be the most important factors for SaMD adoption. In addition, the comparisons and analyses of the weights and priorities of each group showed that the weights and priorities of SaMD adoption factors varied by type of institution, type of medical institution, and type of job in the medical institution.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.171-180
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• 2023

The three major sleep disorders in Korea are snoring, sleep apnea, and insomnia. Lack of sleep is the root of all diseases. Some of the most serious potential problems associated with sleep deprivation are cardiovascular problems, cognitive impairment, obesity, diabetes, colitis, prostate cancer, etc. To solve these problems, the Korean government provided low-cost national health insurance benefits for polysomnography tests in July 2018. However, insomnia patients still have problems getting treated in terms of time, space, and economic perspectives. Therefore, it would be better for insomnia patients to be allowed to test at home. The measuring device can measure six biosignals (eye movement, tossing and turning, body temperature, oxygen saturation, heart rate, and audio). A gyroscope sensor (MPU9250, InvenSense, USA) was used for eye movement, tossing, and turning. The input range of the sensor was in 258°/sec to 460°/sec, and the data range was in the input range. Body temperature, oxygen saturation range, and heart rate were measured by a sensor (MAX30102, Analog Devices, USA). The body temperature was measured in 30 ℃ to 45 ℃, and the oxygen saturation range was 0% for the unused state and 20 % to 90 % for the used state. The heart rate measurement range was in 40 bpm to 180 bpm. The measurement of audio signal was performed by an audio sensor (AMM2742-T-R, PUIaudio, USA). The was -42 dB ±1 dB frequency range was 20 Hz to 20 kHz. The measured data was successfully received in wireless network conditions. The system configuration was consisted of a PC and a mobile app for bio-signal measurement and data collection. The measured data was collected by mobile phones and desktops. The data collected can be used as preliminary data to determine the stage of sleep and perform the screening function for sleep induction and sleep disturbances. In the future, this convenient sleep measurement device could be beneficial for treating insomnia.