• Journal of Life Science
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• v.20 no.7
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• pp.1107-1112
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• 2010

In this study, the stable maintenance of bioactivity in alkaline ionized water (AIW) and antibacterial effects of AIW were evaluated to confirm benefits of AIW. As controls, purified water (PW) and tap drinking water (DW) were used. The pH and ORP (oxidation-reduction potential) of AIW, PW and DW used were 9.5 and 120 mV, 7.2 and 144 mV, and 7.3 and 564 mV, respectively. High level of minerals was observed in DW (DW>AIW>PW of mineral contents). Concentrations of $Ca^{++}$ and $Na^+$ in DW were 14.5, and 8.4 mg/l, respectively, while no $Ca^{++}$, $Mg^{++}$, $K^+$, and $Na^+$ were detected in PW. Evaluation of antioxidant activities for AIW, PW and DW showed that the waters did not act as antioxidants. However, the DPPH (1,1-diphenyl-2-picryl hydrazyl) or superoxide radical scavenging activities or reducing power of vitamin C were stably maintained in AIW and PW, though not in DW, against heat treatment ($60^{\circ}C$) or vigorous shaking (120 rpm) at $37^{\circ}C$. Similarly, after aspirin treatment at $60^{\circ}C$ for 1 hr, the antithrombosis activity in PW and AIW was 62.6% and 55.3%, while that of DW was 52.1%. Furthermore, cell growth analysis and viable cell count of Escherichia coli H7:O157 in PW, AIW and DW showed that AIW and DW, not DW, have antibacterial activities. Our results suggest that the state of water, for example pH, ORP and mineral contents of water, should be considered in medicine or food industries, and that AIW has high potential for utilization in various fields.

• Journal of the Korean Wood Science and Technology
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• v.36 no.3
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• pp.30-38
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• 2008

Petroleum-based resin adhesives have extensively been used for the production of wood panels. However, with the increase of manufacturing cost and the environmental issue, such as the emission of volatile organic compounds, of the adhesive resins, it is necessary to be developed new adhesive systems. In this study, the potential of okara, which is a residue wasted from the production of tofu, for the development of bio-based adhesives was investigated. At first, the physical and chemical properties of okara were examined. After okara was hydrolyzed in acidic and/or alkaline solutions, okara-based adhesive resins were formulated with the mixtures of the okara hydrolyzates and phenol formaldehyde (PF) prepolymer. The adhesive resins were used for the fabrication of plywood panels, and then the adhesive strength and formaldehyde emission of the plywood panels were measured to examine the applicability of the resin adhesives for the production of plywood panels. The solids content and pH of the okara used in this study were around 20% and weak acidic state, respectively. In the analysis of its chemical composition, the content of carbohydrate was the highest, and followed by protein. The shear strengths of plywood fabricated with okara-based resin adhesives exceeded a minimum requirement of KS standard for ordinary plywood, but its wood failure did not reach the minimum requirement. In addition, the formaldehyde emissions of all plywood panels were higher than that of E1 specified in the KS standard. Based on these results, okara has the potential to be used as a raw material of environmentally friendly adhesive resin systems for the production of wood panels, but further researches - biological hydrolysis of okara and various formulations of PF prepolymer - are required to improve the adhesive strength and formaldehyde emission of okara-based resin adhesives.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.761-774
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• 2022

Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.48 no.3
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• pp.189-196
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• 2022

Plasma refers to an ionized gas that is often referred to as "the fourth phase of matter", following solid, liquid, and gas. Plasma has traditionally been utilized for industrial applications such as welding and neon signs, but its promise in biomedical fields such as cancer treatment and dermatology has lately been recognized. Indeed, due to its beneficial effects in promoting collagen production, improving skin tone, and eliminating harmful bacteria in the skin, plasma treatment constitutes an important target for dermatological research. In this study, a plasma device for cosmetic manufacturing based on nitrogen, the main component of the atmosphere, was designed and assembled. Moreover, nitric oxide (NO) was selected since is easier to follow and evaluate than other nitrogen plasma active species, and its contents were measured to perform a quantitative and qualitative evaluation of plasma. First, an injection method, using different proximities labeled "sinking" and "non sinking" treatments, was performed to test the most efficient plasma treatment method. As a result, it was observed that the formulation obtained by a non sinking treatment was more effective. Furthermore, toner and ampoule were selected as cosmetics formulations, and the characteristics of the formulation and changes in the injected plasma state were observed. In both formulations, the successful injection of NO plasma was 2 times higher in toner formulation than ampoule formulation, and it gradually decreased with time, having dissipated after a week. It was confirmed that the nitrogen plasma used did not affect the stability of the toner and ampoule formulations at low temperature (4 ℃), room temperature (25 ℃), and high temperature (37 ℃ and 50 ℃) conditions. The results of this study demonstrate the potential of plasma cosmetics and highlight the importance of securing the stability of the injected plasma.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.172-189
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• 2023

This study investigated the potential contribution of ChatGPT, a massive language and information model, in the decision-making process of public design policies, focusing on the characteristics inherent to public design. Public design utilizes the principles and approaches of design to address societal issues and aims to improve public services. In order to formulate public design policies and plans, it is essential to base them on extensive data, including the general status of the area, population demographics, infrastructure, resources, safety, existing policies, legal regulations, landscape, spatial conditions, current state of public design, and regional issues. Therefore, public design is a field of design research that encompasses a vast amount of data and language. Considering the rapid advancements in artificial intelligence technology and the significance of public design, this study aims to explore how massive language and information models like ChatGPT can contribute to public design policies. Alongside, we reviewed the concepts and principles of public design, its role in policy development and implementation, and examined the overview and features of ChatGPT, including its application cases and preceding research to determine its utility in the decision-making process of public design policies. The study found that ChatGPT could offer substantial language information during the formulation of public design policies and assist in decision-making. In particular, ChatGPT proved useful in providing various perspectives and swiftly supplying information necessary for policy decisions. Additionally, the trend of utilizing artificial intelligence in government policy development was confirmed through various studies. However, the usage of ChatGPT also unveiled ethical, legal, and personal privacy issues. Notably, ethical dilemmas were raised, along with issues related to bias and fairness. To practically apply ChatGPT in the decision-making process of public design policies, first, it is necessary to enhance the capacities of policy developers and public design experts to a certain extent. Second, it is advisable to create a provisional regulation named 'Ordinance on the Use of AI in Policy' to continuously refine the utilization until legal adjustments are made. Currently, implementing these two strategies is deemed necessary. Consequently, employing massive language and information models like ChatGPT in the public design field, which harbors a vast amount of language, holds substantial value.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1286-1288
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• 2024

The construction industry, known for its inherent risks and multiple hazards, necessitates effective solutions for hazard identification and mitigation [1]. To address this need, the implementation of machine learning models specializing in object detection has become increasingly important because this technological approach plays a crucial role in augmenting worker safety by proactively recognizing potential dangers on construction sites [2], [3]. However, the challenge in training these models lies in obtaining accurately labeled datasets, as conventional methods require labor-intensive labeling or costly measurements [4]. To circumvent these challenges, synthetic data generation (SDG) has emerged as a key method for creating realistic and diverse training scenarios [5], [6]. The paper reviews the evolution of synthetic data generation tools, highlighting the shift from earlier solutions like Synthpop and Data Synthesizer to advanced game engines[7]. Among the various gaming platforms, Unity 3D and Unreal Engine stand out due to their advanced capabilities in replicating realistic construction hazard environments [8], [9]. Comparing Unity 3D and Unreal Engine is crucial for evaluating their effectiveness in SDG, aiding developers in selecting the appropriate platform for their needs. For this purpose, this paper conducts a comparative analysis of both engines assessing their ability to create high-fidelity interactive environments. To thoroughly evaluate the suitability of these engines for generating synthetic data in construction site simulations, the focus relies on graphical realism, developer-friendliness, and user interaction capabilities. This evaluation considers these key aspects as they are essential for replicating realistic construction sites, ensuring both high visual fidelity and ease of use for developers. Firstly, graphical realism is crucial for training ML models to recognize the nuanced nature of construction environments. In this aspect, Unreal Engine stands out with its superior graphics quality compared to Unity 3D which typically considered to have less graphical prowess [10]. Secondly, developer-friendliness is vital for those generating synthetic data. Research indicates that Unity 3D is praised for its user-friendly interface and the use of C# scripting, which is widely used in educational settings, making it a popular choice for those new to game development or synthetic data generation. Whereas Unreal Engine, while offering powerful capabilities in terms of realistic graphics, is often viewed as more complex due to its use of C++ scripting and the blueprint system. While the blueprint system is a visual scripting tool that does not require traditional coding, it can be intricate and may present a steeper learning curve, especially for those without prior experience in game development [11]. Lastly, regarding user interaction capabilities, Unity 3D is known for its intuitive interface and versatility, particularly in VR/AR development for various skill levels. In contrast, Unreal Engine, with its advanced graphics and blueprint scripting, is better suited for creating high-end, immersive experiences [12]. Based on current insights, this comparative analysis underscores the user-friendly interface and adaptability of Unity 3D, featuring a built-in perception package that facilitates automatic labeling for SDG [13]. This functionality enhances accessibility and simplifies the SDG process for users. Conversely, Unreal Engine is distinguished by its advanced graphics and realistic rendering capabilities. It offers plugins like EasySynth (which does not provide automatic labeling) and NDDS for SDG [14], [15]. The development complexity associated with Unreal Engine presents challenges for novice users, whereas the more approachable platform of Unity 3D is advantageous for beginners. This research provides an in-depth review of the latest advancements in SDG, shedding light on potential future research and development directions. The study concludes that the integration of such game engines in ML model training markedly enhances hazard recognition and decision-making skills among construction professionals, thereby significantly advancing data acquisition for machine learning in construction safety monitoring.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.1
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• pp.1-9
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• 2006

Regardless of the recent observed warmer winters in Korea, more freeze injuries and associated economic losses are reported in fruit industry than ever before. Existing freeze-frost forecasting systems employ only daily minimum temperature for judging the potential damage on dormant flowering buds but cannot accommodate potential biological responses such as short-term acclimation of plants to severe weather episodes as well as annual variation in climate. We introduce 'dormancy depth', in addition to daily minimum temperature, as a complementary criterion for judging the potential damage of freezing temperatures on dormant flowering buds of grape vines. Dormancy depth can be estimated by a phonology model driven by daily maximum and minimum temperature and is expected to make a reasonable proxy for physiological tolerance of buds to low temperature. Dormancy depth at a selected site was estimated for a climatological normal year by this model, and we found a close similarity in time course change pattern between the estimated dormancy depth and the known cold tolerance of fruit trees. Inter-annual and spatial variation in dormancy depth were identified by this method, showing the feasibility of using dormancy depth as a proxy indicator for tolerance to low temperature during the winter season. The model was applied to 10 vineyards which were recently damaged by a cold spell, and a temperature-dormancy depth-freeze injury relationship was formulated into an exponential-saturation model which can be used for judging freeze risk under a given set of temperature and dormancy depth. Based on this model and the expected lowest temperature with a 10-year recurrence interval, a freeze risk probability map was produced for Hwaseong County, Korea. The results seemed to explain why the vineyards in the warmer part of Hwaseong County have been hit by more freeBe damage than those in the cooler part of the county. A dormancy depth-minimum temperature dual engine freeze warning system was designed for vineyards in major production counties in Korea by combining the site-specific dormancy depth and minimum temperature forecasts with the freeze risk model. In this system, daily accumulation of thermal time since last fall leads to the dormancy state (depth) for today. The regional minimum temperature forecast for tomorrow by the Korea Meteorological Administration is converted to the site specific forecast at a 30m resolution. These data are input to the freeze risk model and the percent damage probability is calculated for each grid cell and mapped for the entire county. Similar approaches may be used to develop freeze warning systems for other deciduous fruit trees.

• Journal of Soil and Groundwater Environment
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• v.13 no.1
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• pp.77-91
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• 2008

In this study, we developed a technique of applying DRASTIC, which is the most widely used tool for estimation of groundwater vulnerability to the aqueous phase contaminant infiltrated from the surface, and a groundwater flow model jointly to assess groundwater contamination potential. The developed technique is then applied to Buyeo-eup area in Buyeo-gun, Chungcheongnam-do, Korea. The input thematic data of a depth to water required in DRASTIC model is known to be the most sensitive to the output while only a few observations at a few time schedules are generally available. To overcome this practical shortcoming, both steady-state and transient groundwater level distributions are simulated using a finite difference numerical model, MODFLOW. In the application for the assessment of groundwater vulnerability, it is found that the vulnerability results from the numerical simulation of a groundwater level is much more practical compared to cokriging methods. Those advantages are, first, the results from the simulation enable a practitioner to see the temporally comprehensive vulnerabilities. The second merit of the technique is that the method considers wide variety of engaging data such as field-observed hydrogeologic parameters as well as geographic relief. The depth to water generated through geostatistical methods in the conventional method is unable to incorporate temporally variable data, that is, the seasonal variation of a recharge rate. As a result, we found that the vulnerability out of both the geostatistical method and the steady-state groundwater flow simulation are in similar patterns. By applying the transient simulation results to DRASTIC model, we also found that the vulnerability shows sharp seasonal variation due to the change of groundwater recharge. The change of the vulnerability is found to be most peculiar during summer with the highest recharge rate and winter with the lowest. Our research indicates that numerical modeling can be a useful tool for temporal as well as spatial interpolation of the depth to water when the number of the observed data is inadequate for the vulnerability assessments through the conventional techniques.

• Environmental Mutagens and Carcinogens
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• v.24 no.1
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• pp.15-18
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• 2004

There are significant differences in the extent of drug interactions between subjects. The influence of the genetic make up of drug metabolizing enzyme activities (CYP3A5, CYP2C19 and UDP-glucuronosyl transferase) on the pharmacokinetic drug interaction potential were studied in vivo. Nineteen healthy volunteers were grouped with regard to the $CYP3A5^{*}3$ allele, into homozygous wild-type (CYP3A5^{*}1/1^{*}1$, n=6), heterozygous $(CYP3A5^{*}1/^{*}3$, n=6), and homozygous variant-type $(CYP3A5^{*}3/^{*}3$, n=7) subject groups. The pharmacokinetic profile of intravenous midazolam was characterized before and after itraconazole administration (200 mg once daily for 4 days), and also following rifampin pretreatment (600 mg once daily for 10 days), with a washout period of 2 weeks in between. For omeprazole and moclobemide pharmacokinetic interaction study 16 healthy volunteers were recruited. The volunteer group comprised 8 extensive metabolizers and 8 poor metabolizers of CYP2C19, which was confirmed by genotyping. Subjects were randomly allocated into two sequence groups, and a single-blind, placebo-controlled, two-period crossover study was performed. In study I, a placebo was orally administered for 7 days. On the eighth morning, 300 mg of moclobemide and 40 mg of placebo were coadministered with 200 mL of water, and a pharmacokinetic study was performed. During study n, 40 mg of omeprazole was given each morning instead of placebo, and pharmacokinetic studies were performed on the first and eighth day with 300 mg of moclobemide coadministration. In the UGT study pharmacokinetics and dynamics of 2 mg intravenous lorazepam were evaluated before and after rifampin pretreatment (600 mg once daily for 10 days), with a washout period of 2 weeks in between. The subjective and objective pharmacodynamic tests were done before and 1, 2, 4, 6, 8, and 12 hrs after lorazepam administration. The pharmacokinetic profiles of midazolam and of its hydroxy metabolites did not show differences between the genotype groups under basal and induced metabolic conditions. However, during the inhibited metabolic state, the $CYP3A5^{*}3/^{*}3$ group showed a greater decrease in systemic clearance than the $CYP3A5^{*}1/^{*}1$ group $(8.5\pm3.8$ L/h/70 kg vs. $13.5\pm2.7$ L/h/70 kg, P=0.027). The 1'-hydroxymidazolam to midazolam AUC ratio was also significantly lower in the $CYP3A5^{*}3/^{*}3$,/TEX> group $(0.58\pm0.35,$ vs. $1.09\pm0.37$ for the homozygous wild-type group, P=0.026). The inhibition of moclo-bemide metabolism was significant in extensive metabolizers even after a single dose of omeprazole. After daily administration of omeprazole for 1 week, the pharmacokinetic parameters of moclobemide and its metabolites in extensive metabolizers changed to values similar to those in poor metabolizers. In poor meta-bolizers, no remarkable changes in the pharmacokinetic parameters were observed. The area under the time-effect curves of visual analog scale(VAS), choice reaction time, and continuous line tracking test results of lorazepam was reduced by 20%, 7%, 23% respectively in induced state, and in spite of large interindividual variablity, significant statistical difference was shown in VAS(repeated measures ANOVA, p=0.0027).

• The Journal of Korean Academy of Sensory Integration
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• v.9 no.2
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• pp.51-60
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• 2011

Objective : The characteristics of physiological responses of ADHD children to sensory stimulation were examined by types of sensory stimulation, measurement tools, and responses. In addition the behavioral characteristics were examined by analyzing items of common problems according to the measuring tool, frequency, and measurement tools. Methods : A systematic review methods were used. Papers published in the Journal between January, 1990 and December 31, 2011 were searched through Riss4U, MEDLINE /PubMed, CINAH. The main terms searched were "ADHD, Children, Sensory processing, Sensory integration, SP, SSP, SOR, TIE, CSP, SEP, EDR", and 15 papers were analyzed. Results : 1. The number of studies on physiological responses of children with ADHD to sensory stimulation was five (33.33 percent), the number of studies on behavioral responses was ten(66.67%), and the number of studies combined the two kinds of study was two (13.33%), where a total of 15 (100%) papers were analyzed. 2. In five studies on the physiological response, there were three studies using tactile and proprioceptive stimulations and two studies using olfactory, auditory, visual, tactile, and vestibular sensories. 3. In ten studies on the behavioral responses, there were five studies using SP, three studies using SSP, two studies using SOR, one study using TIE, and one study using CSP. Conclusion : In the characteristics of physiological responses of children with ADHD children to sensory stimulation, there was in the action potential of the cells in hand region of the primary sensorimotor cortex neurons. It was analyzed that there was an initial state and it appeared show a obvious and fast habituation in the later state; the time of recovery seemed to have many non-specific responses. In the characteristics of behavioral responses, there were inattention / distraction, vestibular processing, sensory processing related to endurance / tone, modulation of sensory input affecting emotional responses, low energy/weak.