• Journal of the Korean Institute of Gas
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• v.27 no.2
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• pp.25-31
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• 2023

The purpose of this study is to increase the thermal efficiency of a landfill gas (LFG) power generation engine by capturing carbon dioxide (CO₂) from landfill gas (LFG) using monoethanolamine (MEA), which is widely used in the chemical CO₂ absorption process. Since the use of LFG as an energy source can be a means of reducing greenhouse gas emissions, MEA can be used to reduce CO₂ in LFG and increase the concentration of CH₄ to improve the efficiency of power generation. In this study, experiments were conducted to measure the solubility of CO₂ and CH₄ in MEA solution, increase the solubility under different conditions, and analyse the dissolution characteristics. It was found that the CO₂ absorption rate increased as the ratio of MEA to reaction gas increased. There is an optimum MEA concentration to maximise CO₂ solubility, and even if the concentration is increased above this concentration, the solubility does not improve significantly. This study provided fundamental work to develop a more practical fuel by capturing CO₂ from LFG and increasing the concentration of CH₄ while reducing greenhouse gas emissions.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.599-608
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• 2023

The increasing interest in soil moisture data using satellite data for applications of hydrology, meteorology, and agriculture has led to the development of methods for generating soil moisture maps of variable resolution. This study demonstrated the capability of generating soil moisture maps using Sentinel-1 and Sentinel-2 data provided by Google Earth Engine (GEE). The soil moisture map was derived using synthetic aperture radar (SAR) image and optical image. SAR data provided by the Sentinel-1 analysis ready data in GEE was applied with normalized difference vegetation index (NDVI) based on Sentinel-2 and Environmental Systems Research Institute (ESRI)-based Land Cover map. This study produced a soil moisture map in the research area of Victoria, Australia and compared it with field measurements obtained from a previous study. As for the validation of the applied method's result accuracy, the comparative experimental results showed a meaningful range of consistency as 4-10%p between the values obtained using the algorithm applied in this study and the field-based ones, and they also showed very high consistency with satellite-based soil moisture data as 0.5-2%p. Therefore, public open data provided by GEE and the algorithm applied in this study can be used for high-resolution soil moisture mapping to represent regional land surface characteristics.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.214-224
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• 2024

Sonobuoys are disposable devices that utilize sound waves for information gathering, detecting engine noises, and capturing various acoustic characteristics. They play a crucial role in accurately detecting underwater targets, making them effective detection systems in anti-submarine warfare. Existing sonobuoy deployment methods in multistatic systems often rely on fixed patterns or heuristic-based rules, lacking efficiency in terms of the number of sonobuoys deployed and operational time due to the unpredictable mobility of the underwater targets. Thus, this paper proposes an optimal sonobuoy placement strategy for Unmanned Aerial Vehicles (UAVs) to overcome the limitations of conventional sonobuoy deployment methods. The proposed approach utilizes reinforcement learning in a simulation-based experimental environment that considers the movements of the underwater targets. The Unity ML-Agents framework is employed, and the Proximal Policy Optimization (PPO) algorithm is utilized for UAV learning in a virtual operational environment with real-time interactions. The reward function is designed to consider the number of sonobuoys deployed and the cost associated with sound sources and receivers, enabling effective learning. The proposed reinforcement learning-based deployment strategy compared to the conventional sonobuoy deployment methods in the same experimental environment demonstrates superior performance in terms of detection success rate, deployed sonobuoy count, and operational time.

• Journal of the Korean Applied Science and Technology
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• v.29 no.3
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• pp.450-458
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• 2012

In order to reduce the effects of greenhouse gas (GHG) emissions, the South Korean government has announced a special platform of technologies as part of an effort to minimize global climate change. To further this effort, the Korean government has pledged to increase low-carbon and carbon neutral resources for biofuel derived from biomass to replace fossil and to decrease levels of carbon dioxide. In general, second generation biofuel produced form woody biomass is expected to be an effective avenue for reducing fossil fuel consumption and greenhouse gas (GHG) emissions in road transport. It is important that under the new Korean initiative, pilot scale studies evolve practices to produce biomass-to-liquid (BTL) fuel. This study reports the quality characteristics of F-T(Fischer-Tropsch) diesel for production of BTL fuel. Synthetic F-Tdiesel fuel can be used in automotive diesel engines, pure or blended with automotive diesel, due to its similar physical properties to diesel. F-T diesel fuel was synthesized by Fischer-Tropsch (F-T) process with syngas($H_2$/CO), Fe basedcatalyst in low temperature condition($240^{\circ}C$). Synthetic F-T diesel with diesel compositions after distillation process is consisted of $C_{12}{\sim}C_{23+}$ mixture as a kerosine, diesel compositions of n-paraffin and iso-paraffin compounds. Synthetic F-T diesel investigated a very high cetane number, low aromatic composition and sulfur free level compared to automotive diesel. Synthetic F-T diesel also show The wear scar of synthetic F-T diesel show poor lubricity due to low content of sulfur and aromatic compounds compared to automotive diesel.

• Journal of the Korean Applied Science and Technology
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• v.34 no.4
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• pp.874-882
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• 2017

As the interest on the air-pollution is gradually rising up at home and abroad, automotiv e and fuel researchers have been working on the exhaust emission reduction from vehicles through a lot of approaches, which consist of new engine design, innovative after-treatment systems, using clean (eco-friendly alternative) fuels and fuel quality improvement. This research has brought forward three main issues : evaporative, performance, air pollution. In addition, researcher studied the environment problems of the bio-ethanol, bio-butanol, bio-ETBE (Ethyl Tertiary Butyl Ether), MTBE (Methyl Tert iary Butyl Ether) fuel contained in the fuel as octane number improver. The researchers have many dat a about the health effects of ingestion of octane number improver. However, the data support the con clusion that octane number improver is a potential human carcinogen at high doses. Based on the bio-fuel and octane number improver types (bio-ethanol, bio-butanol, bio-ETBE, MTBE), this paper dis cussed the influence of gasoline fuel properties on the evaporative emission characteristics. Also, this p aper assessed the acceleration and power performance of gasoline vehicle for the bio-fuel property. As a result of the experiment, it was found that all the test fuels meet the domestic exhaust gas standards, and as a result of measurement of the vapor pressure of the test fuels, the bio - ethanol : 15 kPa and the biobutanol : 1.6 kPa. thus when manufacturing E3 fuel, Increasing the biobutanol content reduces evaporation gas and vapor pressure. In addition, Similar accelerating and powering performance was shown for the type of biofuel and when bio-butanol and bio-ethanol were compared accelerated perf ormance was improved by about 3.9% and vehicle power by 0.8%.

• Korean Journal of School Psychology
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• v.15 no.3
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• pp.399-431
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• 2018

The purpose of this study was to summarize the empirical literature on implementation of positive behavior support (PBS) within a multi-tiered system of supports in American and Korean schools and to compare its key features and outcomes in an attempt to suggest future directions for development of a Korean school-wide PBS model and implementation manuals as well as directions for future research. Twenty-four American articles and 11 Korean articles (total 35 articles) that reported the outcomes of implementation of PBS at a tier 1 and/or tier 2, or tier 3 level and that met established inclusion criteria were analyzed using systematic procedures. Comparisons were made in the areas of key features and outcomes of PBS in addition to general methodology (e.g., participants, design, implementation duration, dependent measures) at each tier of PBS. The results indicated that positive outcomes for student behavior and other areas were reported across tiers in all American and Korean studies. At the tier 1 level, teaching expectations and rules were the primary focus of PBS in American and Korean schools. However, Korean schools focused on modifying the school and classroom environments and teaching social skills whereas American schools focused on teacher training on standardized interventions or curricular by experts and teacher support during implementation of PBS. At the tier 2 level, more American studies reported implementation of tier 2 interventions within school-wide PBS, and Check/In Check/Out (CICO) was found to be the most commonly used tier 2 intervention. The results also indicated that in comparison to Korean schools, American schools were more likely to use systematic screening tools or procedures to identify students who need tier 2 interventions and more likely to promote parental involvement with implementing interventions. At the tier 3 level, more Korean studies reported the outcomes of individualized interventions, but more American studies reported that designing individualized intervention plans based on comprehensive functional behavior assessment results and establishment of systematic screening systems were focused when implementing individualized interventions. Furthermore, few Korean studies reported the assessment of procedural integrity, social validity, and contextual fit in implementing PBS across tiers, indicating the need for development of valid instruments that could be used in assessing these areas. Based on these results, limitations of the study and suggestions for future research are discussed.

• Journal of dental hygiene science
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• v.12 no.2
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• pp.163-170
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• 2012

The purpose of this study was determine the effects of professional tooth cleaning and plaque control instruction(PT & PCI) on reduction of peri-implantitis. A total 80 implant patients were investigated using O'Leary plague index(PI), L${\ddot{o}}$e & Silness gingival index(GI), implant bone loss(BL). While the PT & PCI was conducted by using 'Watanabe method' after scaling for the experimental group, the engine polishing and a plaque control instruction was operated by rolling method after scaling for the control group. The collected data were analyzed with t-test, ANOVA, paired t-test and stepwise multiple regression. PI and GI of the experimental group significantly decreased than the control group(p<0.05). BL, also tended to decreased in the experimental group than the control group(p=0.155). Multiple regression analysis, the factors that was highly correlated with PT & PCI on the PI and GI. According to the implant characteristics, implant location and duration were closely related to PI(p<0.05). Therefore, the PT & PCI is one of the effective methods to reduce the failure caused by the peri-implantitis. Based on this conclusion, that it would be meaningful if the proposed PT & PCI is applied to the oral health management programs of the implant patients.

• The Journal of Korean Academy of Sensory Integration
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• v.21 no.1
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• pp.59-73
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• 2023

Objective : To examine changes in participation patterns of children with Autism Spectrum Disorder (ASD) in play activities during COVID-19 by reviewing relevant literature. Methods : This scoping review was conducted via five steps. we created a research question and searched for relevant literature published in English through CINAHL, PubMed, ERIC, MEDLINE, Google Scholar and Google search engine. After selecting the literature based on inclusion criteria, data were charted based on 10 items (i.e., author name, journal name, publication year, nation, authors' majors, research method, participant' age and gender as well as quantitative and qualitative results of study). The results were analyzed using descriptive numerical and thematic analyses. Results : After reviewing 437 articles and 152 websites, six articles were included. Theses articles were conducted by experts from various fields and countries. Five themes were highlighted in selected articles: COVID-19 resulted in (1) decreased time of outdoor play, (2) increased play time on screen, (3) increased time spent with family, (4) increased sensory difficulties, and (5) recommendations for services for children with disabilities and during COVID-19. Conclusion : This study suggests telerehabilitation programs about parental behavior strategies in order to solve difficulties in which children with ASD may experience when participating in play activities during disasters. Study results can be used as fundamental evidence to emphasize importance of play activities and to systematize role of occupational therapists and service guidelines for supporting play activities of children with disabilities in disasters.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.