• Journal of Korean Society of Forest Science
• /
• v.108 no.3
• /
• pp.440-453
• /
• 2019

This study was carried out to investigate the effect of watching a two-dimensional (2D) forest video and a virtual reality (VR) forest video on stress reduction in adults. Experiments were conducted in an artificial climate room, and 40 subjects participated. After inducing stress in the subjects, subjects watched a 2D gray video, 2D forest video, or VR forest video for 5 mins. The autonomic nervous system activity was evaluated continuously in terms of measured heart rate variability during the experiment. After each experiment, the subject's psychological state was evaluated using a questionnaire. The 2D forest video decreased the viewer's stress index, increased HF, and reduced heart rate compared with the 2D gray video. The VR forest video had a greater stress index reduction effect, LF/HF increase effect, and heart rate reduction effect than the 2D gray video. Psychological measurements showed that subjects felt more comfortable, natural, and calm when watching the 2D gray video, 2D forest video or VR forest video. We also found that the 2D forest video and VR forest video increased positive emotions and reduced negative emotions compared to the 2D gray video. Based on these results, it can be concluded that watching the 2D forest and VR forest videos reduces the stress index and heart rate compared with watching the 2D gray video. Thus, it is considered that the 2D forest video increases the activity of the parasympathetic nervous system, and the VR forest video increases the activity of the sympathetic nervous system. The increased activity of the sympathetic nervous system upon watching the VR forest video is judged to be positive sympathetic nerve activity, such as novelty and curiosity, and not negative sympathetic activity, such as stress and tension. The results of this study are expected to be the basis for examining the visual effects of forest healing, with hope that the utilization of VR, the technology of the fourth industrial revolution in the forestry field, will broaden.

• Management & Information Systems Review
• /
• v.37 no.4
• /
• pp.1-20
• /
• 2018

This study aimed to examine earnings quality of firms selected as Global Champs project which has been promoted by the government since 2013 to support small and medium sized enterprises, for the screening year(t-1) and selected year(t). Earing quality is measured as the value of discretionary accruals estimated by Dechow et al.(1995) adjusted Jones model and Kothari et al.(2005) model, respectively. I analyze the differences of earning quality between the Global Champ firms and the paired firms selected through criteria of the similar total assets and the same industry in the screening year and the selected year. This study is motivated by the needs of measurement of the performance of the Project from the accounting transparent point of view. As the results of this study, major findings are summarized as follows. Firstly the earnings quality of the selected firms was lower than that of the paired firms. This can be explained as a result of motivation of earnings management by companies eager to meet the requirements to be selected for the Project. Secondly, in the selected year, the earnings quality was proved to improve, comparing to the screening year. This can be explained by the efforts of companies to reinforce management innovation and transparent management, which in turn led to positive effects on the earnings quality. These findings were found to be consistent in the additional analyses, where the earning quality of the reconstructed sample with only selected companies was compared for the screening year and the selected year, based on the year before the screening year(t-2).

• The Journal of Korean society of community based occupational therapy
• /
• v.10 no.3
• /
• pp.37-52
• /
• 2020

Objective : This study was conducted to identify occupational therapists working in public health centers, the characteristics and actual conditions of occupational therapists in the community, and use them as basic data on occupational therapists in the community as of 2020. Methods : 77 questionnaires were replied by e-mail from OTs work at nationwide health public centers. Job characteristics and status were analysed by descriptive statistics and check correlation between job satisfaction and other factors. Results : Most survey respondents were female(77.9%) and 20-30(96.1%).. Some occupational therapists worked for dementia related team(72.7%) and others worked for like visiting care, health care, and rehabilitation center etc. Rate of experiences of public health center was 1-2 years(67.5%), the most common type of contract was flexible part-time worker(61%) and work intensity(94.8%) and satisfaction of work was very high(85.7%). The highest difficulty of their job was budget administrative work(26.7%) and of non-work difficulty was inequality under contracts(27.2%). They usually participated at dementia shelter, visiting OT, group OT. Difficulty of their job was high in budget administration, dementia shelters, and visiting work treatments. Goals of treatment were high in improvement of cognitive ability and, family support. Frequency of treatment was high in improvement of cognitive therapy, family support, and evaluation. Occupational therapy targets for health centers were dementia, the general elderly, and adult brain lesions, including those for ordinary people, psychiatric disorders and children. It was found that the primary occupations for evaluation were nurses (35.7%) and occupational therapists (33.7%), and that MMSE-DS, SGDS, and SMCQ were used a lot. Conclusion : This study could identify the job characteristics and status of community OTs. We hope that this result could be basic data for building expertise and role for community OTs in changing situations like community cares.

• Journal of Bio-Environment Control
• /
• v.31 no.3
• /
• pp.170-179
• /
• 2022

Glutamic acid is a precursor of essential amino acids that play an important role in plant growth and development. It is one of the biostimulants that reduce cold stress damage by stimulating biosynthetic pathways leading to cryoprotectants. This study evaluated the effects of glutamic acid foliar application on Kimchi cabbage under low-temperature stress. There were six treatments, combining three photo-/dark periods temperature levels (11/-1℃ extremely low, E; 16/4℃ moderately low, M; and 21/9℃ optimal, O) with and without glutamic acid foliar application (0 and 10 mg·L^-1; Glu 0 and Glu 10). Glutamic acid foliar application was sprayed once 10 days after transplanting, and then temperature treatment immediately after glutamic acid foliar application was conducted for up to four days. After four days of treatment, abscisic acid (ABA), phaseic acid (PA), dihydrophaseic acid (DPA), and abscisic acid-glucose ester (ABA-GE) contents were higher with Glu 10 treatment than Glu 0 treatment in M treatment. Glucose content was highest in E with Glu 10 treatment (52.1 mg·100 g^-1 dry weight), while fructose content was highest in O with Glu 0 treatment (134.6 mg·100 g^-1 dry weight). The contents of glucolepiddin (GLP), glucobrassicin (GBS), 4-methoxyglucobrassicin (4MGBS), neoglucobrassicin (GNBS), and gluconasturtiin (GNS) were highest among all treatments in E with Glu 10 treatments (0.72, 2.05, 1.67, 9.40 and 0.85 µmol·g^-1 dry weight). After two days of treatment, rapid changes in PA and DPA contents of E with Glu 10 treatments were confirmed, and several individual glucosinolate contents (GLP, GBS, 4MGBS, GNBS, and GNS) were significantly different depending on low temperature and glutamic acid treatment. In addition, the content of fructose was significantly lower than that of O treatment in E and M treatments after four days of treatment. Therefore, although the changes in PA, DPA, glucose, fructose, and individual glucosinolates according to low temperature and glutamic acid foliar treatment were shown. A clear correlation between low temperature and glutamic acid effects could not be evaluated. Results indicated that Brassica crops are cryophilic vegetables, do not react sensitively to low temperatures, and mostly have cold resistance.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.5A
• /
• pp.557-564
• /
• 2009

In recent years, there have been numerous explosion-related accidents due to military and terrorist activities. Such incidents caused not only damages to structures but also human casualties, especially in urban areas. To protect structures and save human lives against explosion accidents, better understanding of the explosion effect on structures is needed. In an explosion, the blast overpressure is applied to concrete structures as an impulsive load of extremely short duration with very high pressure and heat. Generally, concrete is known to have a relatively high blast resistance compared to other construction materials. However, information and test results related to the blast experiment of internal and external have been limited due to military and national security reasons. Therefore, in this paper, to evaluate blast effect on reinforced have concrete structure and its protective performance, blast tests are carried out with $1.0m{\times}1.0m{\times}150mm$ reinforce concrete slab structure at the Agency for Defence Development. The standoff blast distance is 1.5 m and the preliminary tests consists with TNT 9 lbs and TNT 35 lbs and the main tests used ANFO 35 lbs. It is the first ever blast experiment for nonmilitary purposes domestically. In this paper, based on the basic experiment procedure and measurement details for acquiring structural behavior data, the blast experimental measurement system and procedure are established details. The procedure of blast experiments are based on the established measurement system which consists of sensor, signal conditioner, DAQ system, software. It can be used as basic research references for related research areas, which include protective design and effective behavior measurements of structure under blast loading.

• Korean Journal of Plant Resources
• /
• v.36 no.5
• /
• pp.435-445
• /
• 2023

The aim of this study was to explore the effects of vinegar extract from seed of common buckwheat (Fagopyrum esculentum Moench) and seed of tartary buckwheat (F. tataricum Gaertner) on acute ethanol-induced hangover in Sprague-Dawley rats. Vinegar extract from buckwheat is rich choline, quercetin and its glycoside, rutin known as flavonoid antioxidants. The test extract containing buckwheat was proven to alleviate hangovers through a significant reduction in the concentration of alcohol and acetaldehyde in the context of an alcohol-induced hangover model. Hepatic alcohol dehydrogenase (ADH) and acetaldehyde dehydrogenase (ALDH) activities were significantly higher in buckwheat vinegar-treated rats than in ethanol-treated rats. Moreover, tartary buckwheat vinegar upregulated antioxidant enzyme such as superoxide dismutase and Catalase activities in liver tissues. These results suggest that buckwheat vinegar extract could alleviate ethanol-induced hangover symptoms by elevating activities related to hepatic ethanol-metabolizing enzymes against ethanol induced metabolites, and in particular, tartary buckwheat should be further developed to be a novel anti-hangover material.

• Journal of Wetlands Research
• /
• v.26 no.2
• /
• pp.147-159
• /
• 2024

Lack of streamflow observations makes model calibration difficult and limits model performance improvement. Satellite-based remote sensing products offer a new alternative as they can be actively utilized to obtain hydrological data. Recently, several studies have shown that artificial intelligence-based solutions are more appropriate than traditional conceptual and physical models. In this study, a data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed, and the utilization of satellite remote sensing information for AI training is investigated. The satellite imagery used in this study is from MODIS and SMAP. The proposed approach is validated using publicly available data from 25 watersheds. Inspired by the traditional regionalization approach, a strategy is adopted to learn one data-driven model by integrating data from all basins, and the potential of the proposed approach is evaluated by using a leave-one-out cross-validation regionalization setting to predict streamflow from different basins with one model. The GRU + Light GBM model was found to be a suitable model combination for target basins and showed good streamflow prediction performance in ungauged basins (The average model efficiency coefficient for predicting daily streamflow in 25 ungauged basins is 0.7187) except for the period when streamflow is very small. The influence of satellite remote sensing information was found to be up to 10%, with the additional application of satellite information having a greater impact on streamflow prediction during low or dry seasons than during wet or normal seasons.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.1-23
• /
• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

• Journal of Venture Innovation
• /
• v.5 no.1
• /
• pp.107-127
• /
• 2022

Global challenges such as the corona pandemic, climate change and the war-on-tech ensure that the demand who the technologies of the future develops and monitors prominently for will be on the agenda. Development of, and applications in, agrifood, biotech, high-tech, medtech, quantum, AI and photonics are the basis of the future earning capacity of the Netherlands and contribute to solving societal challenges, close to home and worldwide. To be like the Netherlands and Europe a strategic position in the to obtain knowledge and innovation chain, and with it our autonomy in relation to from China and the United States insurance, clear choices are needed. Brainport Eindhoven: Building on Philips' knowledge base, there is create an innovative ecosystem where more than 7,000 companies in the High-tech Systems & Materials (HTSM) collaborate on new technologies, future earning potential and international value chains. Nearly 20,000 private R&D employees work in 5 regional high-end campuses and for companies such as ASML, NXP, DAF, Prodrive Technologies, Lightyear and many others. Brainport Eindhoven has a internationally leading position in the field of system engineering, semicon, micro and nanoelectronics, AI, integrated photonics and additive manufacturing. What is being developed in Brainport leads to the growth of the manufacturing industry far beyond the region thanks to chain cooperation between large companies and SMEs. South-Holland: The South Holland ecosystem includes companies as KPN, Shell, DSM and Janssen Pharmaceutical, large and innovative SMEs and leading educational and knowledge institutions that have more than Invest €3.3 billion in R&D. Bearing Cores are formed by the top campuses of Leiden and Delft, good for more than 40,000 innovative jobs, the port-industrial complex (logistics & energy), the manufacturing industry cluster on maritime and aerospace and the horticultural cluster in the Westland. South Holland trains thematically key technologies such as biotech, quantum technology and AI. Twente: The green, technological top region of Twente has a long tradition of collaboration in triple helix bandage. Technological innovations from Twente offer worldwide solutions for the large social issues. Work is in progress to key technologies such as AI, photonics, robotics and nanotechnology. New technology is applied in sectors such as medtech, the manufacturing industry, agriculture and circular value chains, such as textiles and construction. Being for Twente start-ups and SMEs of great importance to the jobs of tomorrow. Connect these companies technology from Twente with knowledge regions and OEMs, at home and abroad. Wageningen in FoodValley: Wageningen Campus is a global agri-food magnet for startups and corporates by the national accelerator StartLife and student incubator StartHub. FoodvalleyNL also connects with an ambitious 2030 programme, the versatile ecosystem regional, national and international - including through the WEF European food innovation hub. The campus offers guests and the 3,000 private R&D put in an interesting programming science, innovation and social dialogue around the challenges in agro production, food processing, biobased/circular, climate and biodiversity. The Netherlands succeeded in industrializing in logistics countries, but it is striving for sustainable growth by creating an innovative ecosystem through a regional industry-academic research model. In particular, the Brainport Cluster, centered on the high-tech industry, pursues regional innovation and is opening a new horizon for existing industry-academic models. Brainport is a state-of-the-art forward base that leads the innovation ecosystem of Dutch manufacturing. The history of ports in the Netherlands is transforming from a logistics-oriented port symbolized by Rotterdam into a "port of digital knowledge" centered on Brainport. On the basis of this, it can be seen that the industry-academic cluster model linking the central government's vision to create an innovative ecosystem and the specialized industry in the region serves as the biggest stepping stone. The Netherlands' innovation policy is expected to be more faithful to its role as Europe's "digital gateway" through regional development centered on the innovation cluster ecosystem and investment in job creation and new industries.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.12 no.3
• /
• pp.235-240
• /
• 2008

Purpose: At the beginning of PET/CT, Computed Tomography was mainly used only for Attenuation Correction (AC), but as the performance of the CT have been increase, it could give improved diagnostic information with Contrast Media. But it was controversial that Contrast Media could affect AC on PET/CT scan. Some submitted thesis' show that Contrast Media could overestimate when it is for AC data processing. On the contrary, the opinion that Contrast Media could be possible to affect the alteration of SUV because of the overestimated AC. But it does not have a definite effect on the diagnosis. Thus, the affection of Contrast Media on AC was investigated in this study. Materials and Methods: Patient inclusion criteria required a history of a malignancy and performance of an integrated PET/CT scan and contrast- enhanced CT scan within a 1-day period. Thirty oncologic patients who had PET/CT scan from December 2007 to June 2008 underwent staging evaluation and met these criteria. All patients fasted for at least 6 hr before the IV injection of approximately 5.6 MBq/kg (0.15 mCi/kg) of $^{18}F$-FDG and were scanned about 60 min after injection. All patients had a whole body PET/CT performed without IV contrast media followed by a contrast-enhanced CT on the Discovery STe PET/CT scanner. CT data were used for AC and PET images came out after AC. The ROIs drew and measured SUV. A paired t-test of these results was performed to assess the significance of the difference between the SUV obtained from the two attenuation corrected PET images. Results: The mean and maximum Standardized Uptake Values (SUV) for different regions averaged over all Patients. Comparing before using Contrast Media and after using, Most of ROIs have the increased SUV when it did Contrast Enhanced CT compare to Non-Contrast enhanced CT. All regions have increased SUV and also their p value was under 0.05 except the mean SUV of the Heart region. Conclusion: In this regard, the effect on SUV measurements that occurs when a contrast-enhanced CT is used for attenuation correction could have significant clinical ramifications. But some submitted thesis insisted that the percentage change in SUV that can determine or modify clinical management of oncology patients is small. Because there was not much difference that could be discovered by interpreter. But obviously the numerical change was occurred and on the stage finding primary region, small change would be base line, such as the region of liver which has greater change than the other regions needs more attention.