• Clean Technology
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• v.7 no.2
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• pp.99-107
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• 2001

Optimization methodologies have been proposed of find the best environment-friendly recycling pathways of plastic materials based on life-cycle assessment (LCA) methodology. The main difficulty in conducting this optimization study is that multiple environmental burdens have to be considered simultaneously as the cost functions. Instead of generating conservative Pareto or noninferior solutions following multi-objective optimization approaches, we have proposed some practical criteria on how to combine the different environmental burdens into a single measure. The obtained single objective optimization problem can then be solved by conventional nonlinear programming techniques or, more effectively, by a tree search method based on decision flows. The latter method reduces multi-dimensional optimization problems to a set of one-dimensional problems in series. It is expected the suggested tree search approach can be applied to many LCA studies as a new promising optimization tool.

• Environmental Engineering Research
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• v.25 no.1
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• pp.52-61
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• 2020

The article examines the impact differences between producing concrete and asphalt. Both materials are widely used in the construction industry. Construction activities account for a large portion of greenhouse gases. Therefore, it is important to consider the Life Cycle Analysis (LCA) to reduce environmental impacts. In this study, the material processes were inputted into an LCA program called SimaPro. The database used for the study was Ecoinvent as it is one of the major databases within SimaPro. The materials were compared against impacts per kg of material produced as the functional unit. Each process was created using the materials, energy and transportation required to produce the materials. Waste streams were also included in the process to determine the impacts after the product was done with its useful life. Using the ReCiPe method, an LCA was conducted. Midpoint and endpoint categories were examined for both the productions. The processes had similar results for the human health and ecosystems categories; however asphalt was marginally higher for both. Asphalt had exceeded concrete in the resource impact category by 100 mPt. The results indicate that concrete is the more sustainable building material. Determination of various impacts of the materials is important for material selection.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.5
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• pp.358-366
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• 2023

Due to the International Maritime Organization's (IMO) environmental regulations on NOx and SOx, LNG-fueled eco-friendly ships are gaining attention worldwide, and various eco-friendly ships are being proposed and demanded for conversion to eco-friendly ships in Korea, as the eco-friendly ship law has recently been enforced. In this study, the initial basic design was performed to convert an existing Marine Gas Oil (MGO) fueled ship into an LNG-DF propulsion ship, targeting medium-sized ship, to select the fuel tank capacity and main dimensions and appropriate fuel ratio between the two fuels. In particular, Sustainable basic design method considering environmental impact were proposed by performing a Life Cycle Assessment (LCA) throughout the design process, and various design options were compared and analyzed to meet different design conditions by applying them.

• Steel and Composite Structures
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• v.51 no.4
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• pp.417-440
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• 2024

Artificial neural networks (ANN) have been the focus of several studies when it comes to evaluating the pile's bearing capacity. Nonetheless, the principal drawbacks of employing this method are the sluggish rate of convergence and the constraints of ANN in locating global minima. The current work aimed to build four ANN-based prediction models enhanced with methods from the black hole algorithm (BHA), league championship algorithm (LCA), shuffled complex evolution (SCE), and symbiotic organisms search (SOS) to estimate the carrying capacity of piles in cold climates. To provide the crucial dataset required to build the model, fifty-eight concrete pile experiments were conducted. The pile geometrical properties, internal friction angle 𝛗 shaft, internal friction angle 𝛗 tip, pile length, pile area, and vertical effective stress were established as the network inputs, and the BHA, LCA, SCE, and SOS-based ANN models were set up to provide the pile bearing capacity as the output. Following a sensitivity analysis to determine the optimal BHA, LCA, SCE, and SOS parameters and a train and test procedure to determine the optimal network architecture or the number of hidden nodes, the best prediction approach was selected. The outcomes show a good agreement between the measured bearing capabilities and the pile bearing capacities forecasted by SCE-MLP. The testing dataset's respective mean square error and coefficient of determination, which are 0.91846 and 391.1539, indicate that using the SCE-MLP approach as a practical, efficient, and highly reliable technique to forecast the pile's bearing capacity is advantageous.

• Korean Journal of Construction Engineering and Management
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• v.16 no.4
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• pp.41-49
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• 2015

The amount of energy consumed in air ventilation systems of public facilities accounts for 40% of their total energy consumption. To reduce their energy consumption, applying variable speed operation controlled by an inverter with a high-efficiency motor is suggested. Since these methods require higher initial investment costs compared to the existing systems, economic evaluation should be conducted from a long-term perspective. While LCCA(Life Cycle Cost Analysis) model is useful to estimate net savings of alternatives that differs with respect to initial costs and operating costs, the environmental burdens are not considered. On the contrary LCA(Life Cycle Assesment) model is suitable to assess environmental impacts associated with the stages of a product's life but it does not consider costs. In this study, the high-efficient motors are introduced into the air ventilation system of a subway station and a comprehensive analysis on the economic and environmental impacts of the proposed method is conducted by using LCCA and LCA model.

• Communications of Mathematical Education
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• v.34 no.1
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• pp.17-39
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• 2020

The purpose of this study is to analyze the mathematical beliefs of students and teachers by Latent Class Analysis(LCA). This study surveyed 60 teachers about beliefs of 'nature of mathematics', 'mathematic teaching', 'mathematical ability' and also asked 1850 students about beliefs of 'school mathematics', 'mathematic problem solving', 'mathematic learning' and 'mathematical self-concept'. Also, this study classified each student and teacher into a class that are in a similar response, analyzed the belief systems and built a profile of the classes. As a result, teachers were classified into three types of belief classes about 'nature of mathematics' and two types of belief classes about 'teaching mathematics' and 'mathematical ability' respectively. Also, students were classfied into three types of belief classes about 'self concept' and two types of classes about 'School Mathematics', 'Mathematics Problem Solving' and 'Mathematics Learning' respectively. This study classified the mathematics belief systems in which students were categorized into 9 categories and teachers into 7 categories by LCA. The belief categories analyzed through these inductive observations were found to have statistical validity. The latent class analysis(LCA) used in this study is a new way of inductively categorizing the mathematical beliefs of teachers and students. The belief analysis method(LCA) used in this study may be the basis for statistically analyzing the relationship between teachers' and students' beliefs.

• Land and Housing Review
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• v.12 no.2
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• pp.109-120
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• 2021

Global warming due to increased carbon dioxide is perceived as one of the factors threatening the future. Efforts are being made to reduce carbon dioxide emissions in each industry around the world. In particular, environmental loads and impacts during the life cycle of SOC structures and buildings have been quantitatively assessed through a quantitative method called Life Cycle Assessment (LCA). However, the construction sector has gone through difficulty in quantitative assessment for several reasons: 1) LCI DB is not fully established; 2) the life cycle is very long; 3) the building structures are unique. Therefore, it takes enormous effort and time to carry out LCA. Rather than estimating carbon emissions with accuracy, this study aims to present a simplified estimation model that allows owners or designers to easily estimate carbon dioxide emissions with little effort, given that rapid and rough decisions regarding environmental load reduction are to be made. This study performs the LCA using data from 25 road construction projects across the country, followed by multiple regression analyses to derive a simplified carbon estimation model (SLCA). The study also carries out a comparative analysis with values estimated by performing a typical LCA. The comparison analysis shows an error rate of less than 5% for 16 road projects.

• Journal of the Korean Society for Railway
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• v.17 no.3
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• pp.178-185
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• 2014

This study investigates the characteristics of environmental impact from the construction phase of a high-speed railway through a Life Cycle Assessment method based on the materials used and the energy consumption of the equipment used according to the design statement. The results reveal that the contributions to environmental impact in the construction sector of a high-speed railway were 89% for civil engineering, 7% for the track system, 2% for stations and 2% for the energy and telecommunication system. In particular, the highest contribution to the impact in the civil engineering category were 54% for Global Warming, 25% for Abiotic Resource Depletion and 8% for Photochemical Oxidant Creation. The main influence factors were the use of remicon and cement. In future, the application of Life Cycle Assessment for the construction sector of railway construction will introduce efficient reduction methods according to the quantitative calculation of environmental impact.

• Clean Technology
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• v.20 no.3
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• pp.241-250
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• 2014

In this study, performance and environmental characteristics of cyclone vacuum cleaners are analyzed and product improvement methods are investigated to minimize environmental effect of the cleaners using the result. A simplified LCA method is used to analyze environmental characteristics of the cyclone vacuum cleaners. Two cyclone vacuum cleaners with similar specifications are chosen for the experiment. Typical characteristics of cyclone vacuum cleaners such as energy consumption, suction force, noise and temperature are measured and compared. Most environmental effect was caused by the energy consumption in use phase of life cycle. Some ideas are created to reduce energy consumption of the vacuum cleaners in use phase like installing baffle, and methods to extend exchange period of filter. It is analyzed how recyclability rate of vacuum cleaners could be improved to reduce the environmental effect in whole life of the vacuum cleaners.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.721-732
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• 2018

Latent class analysis (LCA) is an important tool to explore unseen latent groups in multivariate categorical data. In practice, it is important to select a suitable set of variables because the inclusion of too many variables in the model makes the model complicated and reduces the accuracy of the parameter estimates. Dean and Raftery (Annals of the Institute of Statistical Mathematics, 62, 11-35, 2010) proposed a headlong search algorithm based on Bayesian information criteria values to choose meaningful variables for LCA. In this paper, we propose a new variable selection procedure for LCA by utilizing posterior probabilities obtained from each fitted model. We propose a new statistic to measure the adequacy of LCA and develop a variable selection procedure. The effectiveness of the proposed method is also presented through some numerical studies.