• Journal of the Korean housing association
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• v.19 no.6
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• pp.95-104
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• 2008

This study was to develop the indicators for understanding social inclusion exclusion of the dwellers living in permanent rental apartment, and to present a important base about priority order of national housing policy for social inclusion. The ultimate purpose of this study was to provide basic information for the development of permanent rental apartment renewal techniques. The first phase of the study was to review of the social inclusion exclusion indicators mentioned in the literature. The indicators of EU (2001, 2006), KIHASA (2005), and Jehoel-Gijsbers & Brooman (2007), which were applied in many studies about social inclusion, or included various items about dwellers' subjective attitudes, were selected to construct the framework for the study. On the basis of 3 kinds of indicators at the above, the dimensions of social inclusion exclusion were categorized as material deprivation and access to social rights in an economicstructural exclusion view, and social participation and cultural normative accommodations in a socio-cultural exclusion view. And then, the domains of social inclusion exclusion were decided as follows: income, employment, education service, housing, health, family networks and social networks. The detail contents of indicators were adopted from the prior studies as many as possible, and the dwellers' subjective attitudes and housing domains were intensified with reference to UN housing rights and the study of "residents' satisfaction of housing facilities living in permanent rental housing". The developed indicators were modified through the advisory committee that consist of the specialists from the various fields of studies. The final indicators that were overlapped or not able to be measured were eliminated, and added, in a housing domain, the standards of convenient facilities, the management condition, safety, location, crime and etc. in the apartment complex, which were required to complement in the advisory committee.

• Journal of the Korea Society for Simulation
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• v.21 no.1
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• pp.27-34
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• 2012

Proposed in the paper is an agent based and object-oriented methodology to create a virtual logistics support system model. The proposed virtual logistics support system model consists of three types of objects: the logistics force agent model(static model), the military supplies transport manager model(function model), the military supplies state manager model(dynamic model). A logistic force agent model consists of two agent: main function agent and function agent. To improve the reusability and composability of a logistics force agent model, the function agent is designed to adapt to different logistics force agent configuration. A military supplies transport manager is agent that get information about supply route, make decisions based on decision variables, which are maintained by the military supplies state manager, and transport military supplies. A military supplies state manager is requested military supplies from logistics force agent, provide decision variables such as the capacity, order of priority. For the implementation of the proposed virtual logistics force agent model, this paper employs Discrete Event Systems Specification(DEVS) formalism.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.11a
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• pp.239-250
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• 2003

In this research, we propose a hybrid group decision support mechanism (H-GDSM) based on Fuzzy AHP (Analytic Hierarchy Process) and FCM (Fuzzy Cognitive Map). The AHP elicits a corresponding priority vector interpreting the preferred information among the decision makers. Corresponding vector was composed of the pairwise comparison values of a set of objects. Since pairwise comparison values are the judgments obtained from an appropriate semantic scale. However, AHP couldn't represent the causal relationship among information, which were used by decision makers. In contrast to AHP, FCM could represent the causal relationship among variables or information. Therefore, FCMs were successfully developed and used in several ill-structured domains, such as strategic decision-making, policy making, and simulations. Nonetheless, many researchers used subjective and voluntary inputs to simulate the FCM. As a result of subjective inputs, it couldn't avoid the rebukes of businessman. To overcome these limitations, we incorporated the Fuzzy membership functions, AHP and FCM into a H-GDSM. In contrast to current AHP methods and FCMs, the H-GDSM method developed herein could concurrently tackle the pairwise comparison involving causal relationships under a group decision-making environment. The strengths and contributions of our mechanism were 1) handling of qualitative knowledge and causal relationships, 2) extraction of objective input value to simulate the FCM, 3) multi-phase group decision support based on H-GDSM. To validate our proposed mechanism we developed a simple prototype system to support negotiation-based decisions in electronic commerce (EC).

• Journal of the Korean Institute of Landscape Architecture
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• v.13 no.2
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• pp.13-26
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• 1985

^x The enviroment defines the living conditions for people and has at the same time the possibility to create new environment. In Korea, where the rate of urbanization reached more than 50% in 1970′s the priority has been put on the economic development and administrative function. Under the circumstance, visual environmental field was dealt lightly and it resulted in undesirable environment. The techniques of Mordern Arts (Montage, Depeysment, Tromp L′oeil, P.O.P Art, etc.) helped Super Graphics appear in the urban areas. Environmental Art has been expended into the public space and people came to recognize the Arts as the "Street Art" or "Street as Gallery". Super Graphics has four types 1) Resident′s Super Graphics ; Minority groups came to maintain social equality and rights, in cooperation with each other. Such maintenance required general urbanites to form communities which gave birth to the community art, Mural Painting. 2) Environmental Super Graphics ; Beauty has come to be stressed in order to improve the quality of urban lives in the course of inescapable urban development. Instead of renewal of all established construction conservation oriented renewal was encouraged. 3) Super Graphics as Population Arts ; In the 1960′s artists repulsed the establishments in an efforts to open new phase independent from the expressional in the arts. They recognized the relationship between painting, society and the public in different angle and tried to describe all living space on canvas. 4) Super Graphics as Advertisement ; Super Graphics functions as efficient media to deliver images to the urbanites. Super Graphics as media plays the role for political propaganda and commercial advertisements according to their purposes. In Korea, especially, it is required to introduce the environmental Super Graphics. But it is desirable to introduce Super Graphics with Korean culture and sense of beauty. Designers themselves are also required to have responsibility to improve the quality of urban culture.

• Journal of KIISE
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• v.43 no.1
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• pp.80-86
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• 2016

A speech-act is a behavior intended by users in an utterance. Speech-act classification is important in a dialogue system. The machine learning and rule-based methods have mainly been used for speech-act classification. In this paper, we propose a speech-act classification method based on the combination of support vector machine (SVM) and transformation-based learning (TBL). The user's utterance is first classified by SVM that is preferentially applied to categories with a low utterance rate in training data. Next, when an utterance has negative scores throughout the whole of the categories, the utterance is applied to the correction phase by rules. The results from our method were higher performance over the baseline system long with error-reduction.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.94-107
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• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• Elastomers and Composites
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• v.58 no.1
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• pp.32-43
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• 2023

The worldwide use of polyurethane foam products generates large amounts of waste, which in turn has detrimental effects on the surroundings. Hence, finding an economical and environmentally friendly way to dispose of or recycle foam waste is an utmost priority for researchers to overcome this problem. In that sense, the glycolysis of waste flexible polyurethane foam (WFPF) from automotive seat cushions using different industrial-grade glycols and potassium hydroxide as a catalyst to produce recovered polyol was investigated. The effect of different molecular weight polyols, catalyst concentration, and material ratio (PU foam: Glycols) on the reaction conversion and viscosity of the recovered polyols was determined. The obtained recovered polyols are obtained as single or split-phase reaction products. Besides, the foaming characteristics and physical properties such as cell morphology, thermal stability, and compressive stress-strain nature of the regenerated flexible foams based on the recovered polyols were discussed. It was observed that the regenerated flexible foams displayed good seating comfort properties as a function of hardness, sag factor, and hysteresis loss compared to the reference virgin foam. With the growing demand for a sustainable and circular economy, a global valorization of glycolysis products from polyurethane scraps can be realized by transforming them into profitable substances.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.10
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• pp.1869-1879
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• 2000

A series of experiments were conducted for modeling the fate and effect of the coupled oxidation reduction reaction of ethanol and propionate recognized as important intermediates in anaerobic degradation metabolism. Anaerobic kinetics for conversion of propionate and the interaction with ethanol were investigated using the model of specific substrate priority utilization effect. Seed cultures for the experiment were obtained from an anaerobically enriched steady-state propionate master culture reactor (HPr-MCR), ethanol-propionate master culture reactor (EtPr-MCR) and glucose master culture reactor (Glu-MCR). Experiments were consisted of four phases. Phase I, II and III were conducted by fixing the propionate organic loading as 1.0 g COD/L with increasing ethanol loading of 0, 100, 200, 400 and 1,000 mg/L, to find metabolic interaction of ethanol and propionate degradation by each enriched anaerobic culture. In phase IV, different mixing ratios of Glu-MCR and HPr-MCR cultures with fixed propionate organic loading, 1.0 g COD/L, were applied to observe the propionate degradation metabolic behavior. In the results of this study, different pathways of propionate and ethanol conversion were found using a modified competitive inhibition kinetic model. Increase of $K_{s2}$ value reflected the formation of acetate followed by ethanol degradation. In addition. $K_3$ value was increased slightly as the reactions of acetate formation and degradation were occurred in acetoclastic methanogenesis.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.144-155
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• 2014

The industrial areas including large industrial complexes formed by the process of the growth-oriented industrialization in the past have been attributed to worsening the urban competitiveness of cities due to their infrastructure shortages and aging. Government-led regeneration projects for old industrial complexes have been implemented on a trial basis, but there is a problem with applying a uniform regeneration planning to all the regional industrial complexes with different circumstances and physical environments. In this context, this study diagnosed the social conditions and physical characteristics of the Sasang industrial area in the city of Busan formed by private-led projects in the past and then tried to suggest its regeneration directions. The study area was characterized as its weakening industrial function, infrastructure shortage, and increasing development pressure. Based on these regional characteristics, the regeneration directions were suggested. In the planning phase, pubic-led infrastructure expansion is first needed and urban renewal needs to be applied to some areas designated as priority maintenance areas. In the implementation phase, stepwise projects are required in the medium to long term and it is important to build upon the consensus with private companies through establishing collaborative governance.

• Computers and Concrete
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• v.19 no.5
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• pp.457-465
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• 2017

The Taiwanese liquid crystal display (LCD) industry has traditionally produced a huge amount of waste glass that is placed in landfills. Waste glass recycling can reduce the material costs of concrete and promote sustainable environmental protection activities. Concrete is always utilized as structural material; thus, the concrete compressive strength with a variety of mixtures must be studied using predictive models to achieve more precise results. To create an efficient waste LCD glass concrete (WLGC) design proportion, the related studies utilized a multivariable regression analysis to develop a compressive strength waste LCD glass concrete equation. The mix design proportion for waste LCD glass and the compressive strength relationship is complex and nonlinear. This results in a prediction weakness for the multivariable regression model during the initial growing phase of the compressive strength of waste LCD glass concrete. Thus, the R ratio for the predictive multivariable regression model is 0.96. Neural networks (NN) have a superior ability to handle nonlinear relationships between multiple variables by incorporating supervised learning. This study developed a multivariable prediction model for the determination of waste LCD glass concrete compressive strength by analyzing a series of laboratory test results and utilizing a neural network algorithm that was obtained in a related prior study. The current study also trained the prediction model for the compressive strength of waste LCD glass by calculating the effects of several types of factor combinations, such as the different number of input variables and the relevant filter for input variables. These types of factor combinations have been adjusted to enhance the predictive ability based on the training mechanism of the NN and the characteristics of waste LCD glass concrete. The selection priority of the input variable strategy is that evaluating relevance is better than adding dimensions for the NN prediction of the compressive strength of WLGC. The prediction ability of the model is examined using test results from the same data pool. The R ratio was determined to be approximately 0.996. Using the appropriate input variables from neural networks, the model validation results indicated that the model prediction attains greater accuracy than the multivariable regression model during the initial growing phase of compressive strength. Therefore, the neural-based predictive model for compressive strength promotes the application of waste LCD glass concrete.