• Korean System Dynamics Review
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• v.9 no.1
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• pp.57-71
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• 2008

This research paper describes a complex and vague settings in which organization makes a decision and explains a role of decision maker's learning process. The original paper, written by Cohen, March, Olsen in 1972, said that all members of organization depended on the technology taken through trials and errors, which is the 'learning' process literally. But they intended to exclude the learning process in their simulation model because their PORTRAN model couldn't replicate the learning concept. As a result, they couldn't explain how all agents of garbage can simulation model resolve the problem dynamically. To overcome this original paper's limitations, we try to rebuild a learning process simulation model using by system dynamics approach that can capture the linkage between organization leanings and agents-based decision-makings. Our learning simulation results reveal two points. First, decision maker's leanings process improves the efficiency of decision making in complex situation. Second, group learning shows a superior efficiency to an individual learning because group members share organizational memory and energy.

• Proceedings of the Korean System Dynamics Society
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• 2007.11a
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• pp.17-31
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• 2007

• Proceedings of the Korea Technology Innovation Society Conference
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• 2015.11a
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• pp.501-507
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• 2015

• Safety and Health at Work
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• v.3 no.4
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• pp.268-277
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• 2012

Objectives: 1) To determine mercury levels in urine samples from garbage workers in Southern Thailand, and 2) to describe the association between work characteristics, work positions, behavioral factors, and acute symptoms; and levels of mercury in urine samples. Methods: A case-control study was conducted by interviewing 60 workers in 5 hazardous-waste-management factories, and 60 matched non-exposed persons living in the same area of Southern Thailand. Urine samples were collected to determine mercury levels by cold-vapor atomic absorption spectrometer mercury analyzer. Results: The hazardous-waste workers' urinary mercury levels (10.07 ${\mu}g/g$ creatinine) were significantly higher than the control group (1.33 ${\mu}g/g$ creatinine) (p < 0.001). Work position, duration of work, personal protective equipment (PPE), and personal hygiene, were significantly associated with urinary mercury level (p < 0.001). The workers developed acute symptoms - of head-aches, nausea, chest tightness, fatigue, and loss of consciousness at least once a week - and those who developed symptoms had significantly higher urinary mercury levels than those who did not, at p < 0.05. A multiple regression model was constructed. Significant predictors of urinary mercury levels included hours worked per day, days worked per week, duration of work (years), work position, use of PPE (mask, trousers, and gloves), and personal hygiene behavior (ate snacks or drank water at work, washed hands before lunch, and washed hands after work). Conclusion: Changing garbage workers' hygiene habits can reduce urinary mercury levels. Personal hygiene is important, and should be stressed in education programs. Employers should institute engineering controls to reduce urinary mercury levels among garbage workers.

• STI Policy Review
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• v.6 no.2
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• pp.54-86
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• 2015

The study examines the U.S. Small Business Innovation Research (SBIR) program, with a focus on the recent Reauthorization, and compares, in the political context, the U.S. and East Asian countries-Japan, Korea and Taiwan-that adopted the U.S. SBIR program. For the systematic analysis and cross-country comparison, the study employs Kingdon (2003)'s framework-his political theory and Garbage Can Model-to identify political participants and processes underlying the SBIR Reauthorization and to analyze the differences in problem, policy, and politics streams between the U.S. and East Asian countries. For the cross-country comparison, specifically, the study uses various data sources such as OECD, Global Entrepreneurship Monitor, Hofstede's Cultural Dimensions, and World Value Survey. Based on the analysis outcomes, implications of U.S. practices on East Asian countries are extracted as follows. East Asian countries tend to: Have higher entrepreneurial aspiration while lower entrepreneurial activity and attitude than the U.S.; bear higher long term orientation and uncertainty avoidance while lower individualism than the U.S.; and have greater expectations of technology development and higher confidence in political parties while participating less in political action than the U.S. Drawing on the differences, the following policy recommendations are suggested. East Asian countries should: Improve entrepreneurs' access to resources (in particular, financial resource) in order to link their high entrepreneurial aspiration to actual entrepreneurial activities; cultivate failure-tolerating culture and risk-taking entrepreneurs, for instance, by providing a second chance to SBIR-participating businesses that failed to materialize their innovative ideas; and leverage their high expectations of new technology in order to take bold actions regarding their SBIR programs, and update the programs by drawing out constructive dialogues between SBIR stakeholders.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.355-361
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• 1999

An application of case-based reasoning is proposed to build an influence diagram for identifying successful new ventures. The decision to invest in new ventures in characterized by incomplete information and uncertainty, where some measures of firm performance are quantitative, while some others are substituted by qualitative indicators. Influence diagrams are used as a model for representing investment decision problems based on incomplete and uncertain information from a variety of sources. The building of influence diagrams needs much time and efforts and the resulting model such as a decision model is applicable to only one specific problem. However, some prior knowledge from the experience to build decision model can be utilized to resolve other similar decision problems. The basic idea of case-based reasoning is that humans reuse the problem solving experience to solve a new decision. In this paper, we suggest a case-based reasoning approach to build an influence diagram for the class of investment decision problems. This is composed of a retrieval procedure and an adaptation procedure. The retrieval procedure use two suggested measures, the fitting ratio and the garbage ratio. An adaptation procedure is based on a decision-analytic knowledge and decision participants knowledge. Each step of procedure is explained step by step, and it is applied to the investment decision problem in new ventures.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.706-716
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• 2016

Because of efficient space utilization and fast key search times, B-trees have been widely accepted for the use of indexes in HDD-based DBMSs. However, when the B-ree is stored in flash memory, its costly operations of node updates may impair the performance of a DBMS. This is because the random updates in B-tree's leaf nodes could tremendously enlarge I/O costs for the garbage collecting actions of flash storage. To solve the problem, we make all the parents of leaf nodes the virtual nodes, which are not stored physically. Rather than, those nodes are dynamically generated and buffered by referring to their child nodes, at their access times during key searching. By performing node updates and tree reconstruction within a single flash block, our proposed B-tree can reduce the I/O costs for garbage collection and update operations in flash. Moreover, our scheme provides the better performance of key searches, compared with earlier flash-based B-trees. Through a mathematical performance model, we verify the performance advantages of the proposed flash B-tree.

• Journal of Environmental Impact Assessment
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• v.17 no.5
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• pp.321-330
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• 2008

Methane is a potent greenhouse gas and methane emissions from landfills have been linked to global warming. In this study, LandGEM (Landfill Gas Emission Model) was applied to predict landfill gas quantity over time, and then this result was compared with the data surveyed on the site, Cheongju Megalo Landfill. LandGEM allows the input of site-specific values for methane generation rate (k) and potential methane generation capacity $L_o$, but in this study, k value of 0.05/yr and $L_o$ value of $170m^3/Mg$ were considered to be most appropriate for reflecting non-arid temperate region conventional landfilling, Cheongju Megalo Landfill. High discrepancies between the surveyed data and the predicted data about landfill gas seems to be derived from insufficient compaction of daily soil-cover, inefficient recovery of landfill gas and banning of direct landfilling of food garbage waste in 2005. This study can be used for dissemination of information and increasing awareness about the benefits of recovering and utilizing LFG (landfill gas) and mitigating greenhouse gas emissions.

• Advances in Computational Design
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• v.2 no.4
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• pp.313-331
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• 2017

In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.

• The Journal of Bigdata
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• v.6 no.1
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• pp.179-196
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• 2021

With the spread of untact culture resulting from the Covid-19 pandemic, the size of the car camping market has expanded to minimize contact with others. As a result, SUVs have exceeded sales of sedans, and sales of recreational vehicles (RVs) have increased by 101% compared to the same period last year. Despite the explosive increase in demand for car camping, research on car camping has not matched this increase. Therefore, in this study, we intended to conduct a study focused on car camping users. According to a survey of Naver's famous car camping cafe, it was difficult to find articles, maps, and websites with car camping places. Analysis of car camping websites showed that most only post information about the camping itself, so details of car camping places were not available. Furthermore, according to a survey derived from related prior studies and literature surveys, most users urged solutions to the problem of unauthorized garbage dumping in the car camping locations. In addition, car camping users wanted to receive information on amenities near the car camping places. Therefore, we aimed to establish a car camping website that provides basic information on car camping places and nearby convenience facilities. Moreover, to solve the problem of garbage dumping, we provided a category wherein users can post pictures of clean camping campaigns. We also developed a business model utilizing the certification process of clean camping. The business model is designed with a structure wherein car camping users are rewarded through the clean camping certification process. Compensation for clean camping certification was proposed to be provided through partnerships with domestic automakers, Korea Tourism Organization, and Small Business Market Promotion Agency.