• Journal of Biomedical Engineering Research
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• v.45 no.4
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• pp.162-172
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• 2024

To analyse the overall research trends in digital therapeutics, this study conducted a quantitative bibliometric analysis of articles published in the last 10 years from 2014 to 2023. We extracted bibliographic information of studies related to digital therapeutics from the Web of Science (WOS) database and performed publication status, citation analysis and keyword analysis using R (version 4.3.1) and VOSviewer (version 1.6.18) software. A total of 1,114 articles were included in the study, and the annual publication growth rate for digital therapeutics was 66.1%, a very rapid increase. "health" is the most used keyword based on Keyword Plus, and "cognitive-behavioral therapy", "depression", "healthcare", "mental-health", "meta-analysis" and "randomized controlled-trial" are the research keywords that have driven the development and impact of digital therapeutic devices over the long term. A total of five clusters were observed in the co-occurrence network analysis, with new research keywords such as "artificial intelligence", "machine learning" and "regulation" being observed in recent years. In our analysis of research trends in digital therapeutics, keywords related to mental health, such as depression, anxiety, and disorder, were the top keywords by occurrences and total link strength. While many studies have shown the positive effects of digital therapeutics, low engagement and high dropout rates remain a concern, and much research is being done to evaluate and improve them. Future studies should expand the search terms to ensure the representativeness of the results.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Korean Journal of Environment and Ecology
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• v.32 no.5
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• pp.469-477
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• 2018

Hanabusaya asiatica is an endemic species whose distribution is limited in the mid-eastern part of the Korean peninsula. Due to its narrow range and small population, it is necessary to protect its habitats by identifying it as Key Biodiversity Areas (KBAs) adopted by the International Union for Conservation of Nature (IUCN). In this paper, we estimated potential natural habitats for H. asiatica using maximum entropy model (MaxEnt) and identified candidate sites for KBA based on the model results. MaxEnt is a machine learning algorithm that can predict habitats for species of interest unbiasedly with presence-only data. This property is particularly useful for the study area where data collection via a field survey is unavailable. We trained MaxEnt using 38 locations of H. asiatica and 11 environmental variables that measured climate, topography, and vegetation status of the study area which encompassed all locations of the border region between South and North Korea. Results showed that the potential habitats where the occurrence probabilities of H. asiatica exceeded 0.5 were $778km^2$, and the KBA candidate area identified by taking into account existing protected areas was $1,321km^2$. Of 11 environmental variables, elevation, annual average precipitation, average precipitation in growing seasons, and the average temperature in the coldest month had impacts on habitat selection, indicating that H. asiatica prefers cool regions at a relatively high elevation. These results can be used not only for identifying KBAs but also for the reference to a protection plan for H. asiatica in preparation of Korean reunification and climate change.

• Korean Journal of Organic Agriculture
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• v.26 no.3
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• pp.439-452
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• 2018

This study was carried out to establish of environment-friendly control system and to survey the occurrence status of Ricania shanthungensis in Jeonnam province from 2016 to 2017. R. shanthungensis occurred at 1,344 ha in 61 towns of 15 cities in Gwangju and Jeonnam province. At four sites in the stationary area, the densities of eggmass and pupae were lower in 2017 than in 2016, the hatching rate decreased, and the first hatching time, emergence of adults, and the start of spawning tended to be slower. Telenomus sp., an egg parasitoid of R. shanthungensis, was found in most areas. Sunchon had the highest rate of 46.1%, followed by Muan 40.6, Goksung 29.2, Gurye 25.8, and Gwangju 17, respectively. The optimum spraying time for the control of R. shanthungensis was early March. The spraying material and the dilution multiples are 10 times of the machine oil at environmental friendly cultivation and 500 times of the chlorpriphosphate wp. at normal cultivation. When sprayed these materials, 95% of egg prohibited to hatch. There was more than 80% of the insecticidal effects on the organic materials of the machine oil emulsion, the Sophora root extrect + microbial extract agent, and the castor emulsion. For adults, Sophora root extrect + microbial extract, neem extract, and machine oil were better. Four kinds of chemical pesticides such as dinotefuran wp were effective for nymph and adult control. We have developed an adult catching device using the most preferred daylight color and behavioral habits of R. shanthungensis. The capture device consisted of two daylight compact lamps (30W and 20W), a yellow plate, and a catcher using water, and caught about 700 individuals a day. Based on the above results, we have established a system for controlling and life cycle of R. shanthungensis in Jeonnam province.

• Cross-Cultural Studies
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• v.52
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• pp.277-312
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• 2018

First-order cybernetics during the 1940s and 1950s aimed for control of an observed system, while second-order cybernetics during the mid-1970s aspired to address the mechanism of an observing system. The former pursues an objective, subjectless, approach to a system, whereas the latter prefers a subjective, personal approach to a system. Second-order observation must be noted since a human observer is a living system that has its unique cognition. Maturana and Varela place the autopoiesis of this biological system at the core of second-order cybernetics. They contend that an autpoietic system maintains, transforms and produces itself. Technoscientific recreation of biological autopoiesis opens up to a new step in cybernetics: what I describe as third-order cybernetics. The formation of technoscientific autopoiesis overlaps with the Fourth Industrial Revolution or what Erik Brynjolfsson and Andrew McAfee call the Second Machine Age. It leads to a radical shift from human centrism to posthumanity whereby humanity is mechanized, and machinery is biologized. In two versions of the novel Demon Seed, American novelist Dean Koontz explores the significance of technoscientific autopoiesis. The 1973 version dramatizes two kinds of observers: the technophobic human observer and the technology-friendly machine observer Proteus. As the story concludes, the former dominates the latter with the result that an anthropocentric position still works. The 1997 version, however, reveals the victory of the techno-friendly narrator Proteus over the anthropocentric narrator. Losing his narrational position, the technophobic human narrator of the story disappears. In the 1997 version, Proteus becomes the subject of desire in luring divorcee Susan. He longs to flaunt his male egomaniac. His achievement of male identity is a sign of technological autopoiesis characteristic of third-order cybernetics. To display self-producing capabilities integral to the autonomy of machinery, Koontz's novel demonstrates that Proteus manipulates Susan's egg to produce a human-machine mixture. Koontz's demon child, problematically enough, implicates the future of eugenics in an era of technological autopoiesis. Proteus creates a crossbreed of humanity and machinery to engineer a perfect body and mind. He fixes incurable or intractable diseases through genetic modifications. Proteus transfers a vast amount of digital information to his offspring's brain, which enables the demon child to achieve state-of-the-art intelligence. His technological editing of human genes and consciousness leads to digital standardization through unanimous spread of the best qualities of humanity. He gathers distinguished human genes and mental status much like collecting luxury brands. Accordingly, Proteus's child-making project ultimately moves towards technologically-controlled eugenics. Pointedly, it disturbs the classical ideal of liberal humanism celebrating a human being as the master of his or her nature.

• Quality Improvement in Health Care
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• v.1 no.2
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• pp.60-72
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• 1994

Background: The number of outpatients visiting large university teaching hospitals has increased drastically with the introduction of a nationwide health care insurance in 1989 and the improvement of the socio-economic status of the population. This resulted in long waiting times for services, particularly prescribed drugs, which have been patients' chief complaints. Hospitals have tried to solve the problem with limited success because their approach lacked comprehensive research. The objective of this study is to investigate associations between waiting times and variables defining a total work system. Methods: Data for the outpatient pharmacy department in a tertiary care university teaching hospital located in Seoul was analyzed to achieve the study objective. Associations of pharmacy system variables -- work load, work force, pharmacist work schedule, machine problems, and inventory control -- with mean and 99th percentile of waiting times were examined by the hierarchical stepwise regression method. Day was a unit of the analyses. Results: The regression models explained 65.8% of variance in the mean waiting time and 61.34% in the 99th percentile of waiting times. The break-down of the printer for drug envelops, Automatic Tablet Counters (ATCs), and main computer system lasted longer than 30 minutes increased the mean for 7.7 minutes, 4.5 minutes, and 7.0 minutes, respectively, and the 99th percentile for 14.8 minutes, 9.0 minutes, and 15.7 minutes, respectively. Concerning the work force, study results showed that there were significant differences in the productivity of pharmacists with work experience more than three years, one to three years, and less than one year, and showed that peak time aid work by pharmacists at job assignments other than the outpatient pharmacy, part-time pharmacists, and the installation of ATCs were effective in reducing waiting times, Finally, study findings indicated that the operational policy of work assignment and rotation schedule, supply and inventory of drugs at work tables, and readiness for undisrupted work during the work hours could have a significant effect on waiting times. Conclusion: The study results indicated that efforts to reduce waiting times for prescribed drugs should be geared toward every components of the pharmacy work system ranging from work schedule of pharmacists and supply of dugs at work tables. These findings should provide hospital managers with right directions in battling the problem.

• Journal of The Korean Association of Information Education
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• v.24 no.4
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• pp.313-325
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• 2020

There is a growing interest and need for the educational use of artificial intelligence as artificial intelligence technologies such as machine learning and deep learning, the core technologies of the intelligent information society, owing to the recent innovative technological advances. Consequently, the Ministry of Education announced the First Information Education Comprehensive Plan for introducing artificial intelligence competence enhancing education into the education field in preparation for the intelligent information society based on artificial intelligence technologies. Therefore, this study collected 416 overseas papers related to the educational use of artificial intelligence from the Web of Science (WoS) in order to explore the potential for using artificial intelligence educationally. This study analyzed the research status and research topic by country, citation counts, network analysis on keywords of the collected data by using the bibliometrix package of R program. Through this, it was possible to identify the research trend on the educational use of artificial intelligence, currently being conducted in foreign countries. It is believed that it will be possible to obtain implications for the topics and directions to be studied in the information education for strengthening artificial intelligence education based on the results of this study.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1256-1262
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• 2010

The game has been rapidly evolving through various media such as computer, console game machine, cellular phone and PMP based on the advanced development of scientific technology. In terms of demand, the interest in and desire to consume the game as a way of spending people's spare time have been on the increase constantly while the level of income has been improved. Eventually, the game has gradually expanded its scope of supply and demand, has established its own status as one of the media that is scientifically-intensive and has been developed into a game industry, a large-scale industry. Unlike image media, the methods of exposure in PPL are varied in accordance with the genre of games. This study divides the causes that have influence over the effect of PPL in the game into the genre of game and the skill of gamer. The results of the experiment on how much the aforementioned two elements have influence over the effect of PPL are as in the following: It has been demonstrated that the effect of PPL could appear different according to the genre of game and the skill of gamer on the game. Besides, the genre of game that is dynamic in its screen change in the game has relatively lower effect of PPL than that is not dynamic. Meanwhile, the persons who are highly skilled in the game have higher degree of recognition and preference to the inserted PPL than those who are lowly skilled. In this regard, it has given us a theoretical ground that the fees system for PPL ads should be established variously in accordance with the genre of game and the level of online game users.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.12 no.1
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• pp.1-9
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• 2018

This study is intended to identify how horseback riding affect the bone density of the elderly. A total of 31 normal senior citizens participated in the research, who were randomly divided into two groups: 15 in horseback riding exercise group and 16 in horseback riding machine exercise group. A horseback riding exercise program was carried out for 25 minutes twice a week for 12 weeks. A pre-test was conducted before starting the program and two post-tests were conducted 6 weeks and 12 weeks after exercises in the same way as the pre-test. Measured items were bone density of lumbar vertebrae and femur. In order to identify the changes in measurement variables before exercises and 6 weeks and 12 weeks after exercises, two-way repeated analysis of variance were used. The comparison of changes in the bone density in both groups revealed that there were significant differences in lumbar vertebrae L3, L4, femur trochanter in both groups over time. This study suggests that three-dimensional movements of horses through horseback riding exercises induce normal movements of senior citizens, providing positive effects on their bone density. If appropriate horse riding exercise programs are used considering the health status, time and economic conditions, and preferences of senior citizens, it would improve their quality of life.

• Journal of Preventive Medicine and Public Health
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• v.10 no.1
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• pp.16-24
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• 1977

This is a result of clinical examination for workers working with Chromic acid and Chromium compounds in the plating room of their companies. I selected two companies that the plating process and the kinds of plating were similar. One (SW Co.) was more or less improved the operating environment with the ventilation machine so on and another (SR Co.) did not it so. The former was examined at March 29th 1977, the latter was at June 28th 1976. But the respiratory communicable diseases, flue or common cold so on were not spreaded there at that time. The clinical aspects were compared between the group of SW, and SR. The swelling and hyperemic signs of nasal mucous membrane and the experience of nasal bleeding were about 50%, generally, in all the groups. The following problem was dizziness or vertigo. The nasal signs in the group of SW (improved ventilation of the room air) were relatively weak, but in another, it was some what severe; - there was necrotic sign with thick nasal clast. They were only used of gauze mask when the vapors of various solvents were deeply full in the room. And there was very high rate of bronchial signs, sputum or coughing in the group of SW improved ventilation so called, than another one. I suppose that it means chronic inflammatory change of the bronchial mucous membrane with deeper signs, due to the individual protectors were carelessly or not used according to the improving of the operating environment. Theses nasal signs mentioned the above were not nearly in the other groups had not been done the Chromium plating. The Status of RBC, Hb and Ht, of urine protein and urobilinogen were mostly in normal range. But the number of WBC was more or less showed with a positive correlation to the working duration.