• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.7
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• pp.47-57
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• 2018

As a preliminary step for developing vulnerability assessment model of terrorism, this study aims to deduce and classify architectural design elements of multi-use buildings to protect them from terrorism using explosives. For these objectives, eleven domestic and foreign guidelines of anti-terrorism, including RVS which is one of the commonly used tools for assessing vulnerability to terrorism, were analyzed. As results, 2 scenarios of explosive attack, 4 layers of defense, and 58 architectural design elements for risk assessment of terrorism were deduced. And the design elements were categorized into 18 groups based on their purpose and function to take into account the supplementary effects among them. Then, the design measures applicable for each element were classified into several grades on the basis of its protection or risk level. Lastly, 11 multi-use buildings were selected and investigated how the elements suggested in this study were applied to them.

• Smart Structures and Systems
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• v.31 no.4
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• pp.383-392
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• 2023

Post-earthquake building condition assessment is crucial for subsequent rescue and remediation and can be automated by emerging computer vision and deep learning technologies. This study is based on an endeavour for the 2nd International Competition of Structural Health Monitoring (IC-SHM 2021). The task package includes five image segmentation objectives - defects (crack/spall/rebar exposure), structural component, and damage state. The structural component and damage state tasks are identified as the priority that can form actionable decisions. A multi-task Convolutional Neural Network (CNN) is proposed to conduct the two major tasks simultaneously. The rest 3 sub-tasks (spall/crack/rebar exposure) were incorporated as auxiliary tasks. By synchronously learning defect information (spall/crack/rebar exposure), the multi-task CNN model outperforms the counterpart single-task models in recognizing structural components and estimating damage states. Particularly, the pixel-level damage state estimation witnesses a mIoU (mean intersection over union) improvement from 0.5855 to 0.6374. For the defect detection tasks, rebar exposure is omitted due to the extremely biased sample distribution. The segmentations of crack and spall are automated by single-task U-Net but with extra efforts to resample the provided data. The segmentation of small objects (spall and crack) benefits from the resampling method, with a substantial IoU increment of nearly 10%.

• Journal of Dairy Science and Biotechnology
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• v.41 no.2
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• pp.45-56
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• 2023

This review serves two purposes: first, to promote the use of improved optimization techniques in response surface methodology (RSM); and second, to enhance the optimum conditions for the fermentation of probiotics. According to research in dairy science, Lactiplantibacillus plantarum K79 is a candidate probiotic that has beneficial health effects, such as lowering blood pressure. The optimum conditions for L. plantarumK79 to produce peptides with angiotensin-converting enzyme (ACE) inhibitory activity were proposed, through modeling each of ACE inhibitory activity and pH as a function of the four factors that are skim milk concentration (%), incubation temperature (℃), incubation time (hours), and starter added amount (%). To estimate optimum conditions, the researchers employed a desirability-based multi-response optimization approach, utilizing third-order models with a nonsignificant lack of fit. The estimated optimum fermentation conditions for L. plantarum K79 were as follows: a skim milk concentration of 10.76%, an incubation temperature of 36.9℃, an incubation time of 23.76 hours, and a starter added amount of 0.098%. Under these conditions, the predicted ACE inhibitory activity was 91.047%, and the predicted pH was 4.6. These predicted values achieved the objectives of the multi-response optimization in this study.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1654-1666
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• 2024

The goal of this research is to propose a way to maximize small modular reactor (SMR) utilization to gain better market feasibility in support of carbon neutrality. For that purpose, a comprehensive tool was developed, combining off-design thermohydraulic models, economic objective models (levelized cost of electricity, annual profit), non-economic models (saved CO2), a parameter input sampling method (Latin hypercube sampling, LHS), and a multi-objective evolutionary algorithm (Non-dominated Sorting Algorithm-2, NSGA2 method) for optimizing a SMR-combined heat and power cycle (CHP) system design. Considering multiple objectives, it was shown that NSGA2+LHS method can find better optimal solution sets with similar computational costs compared to a conventional weighted sum (WS) method. Out of multiple multi-objective optimal design configurations for a 105 MWe design generation rating, a chosen reference SMR-CHP system resulted in its levelized cost of electricity (LCOE) below $60/MWh for various heat prices, showing economic competitiveness for energy market conditions similar to South Korea. Examined economic feasibility may vary significantly based on CHP heat prices, and extensive consideration of the regional heat market may be required for SMR-CHP regional optimization. Nonetheless, with reasonable heat market prices (e.g. district heating prices comparable to those in Europe and Korea), SMR can still become highly competitive in the energy market if coupled with a CHP system.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.127-135
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• 2008

Generally, optimum shortest path algorithms adopt single attribute objective among several attributes such as travel time, travel cost, travel fare and travel distance. On the other hand, multi-objective shortest path algorithms find the shortest paths in consideration with multi-objectives. Up to recently, the most of all researches about multi-objective shortest paths are proceeded only in single transportation mode networks. Although, there are some papers about multi-objective shortest paths with multi-modal transportation networks, they did not consider transfer problems in the optimal solution level. In particular, dynamic programming method was not dealt in multi-objective shortest path problems in multi-modal transportation networks. In this study, we propose a multi-objective shortest path algorithm including dynamic programming in order to find optimal solution in multi-modal transportation networks. That algorithm is based on two-objective node-based label correcting algorithm proposed by Skriver and Andersen in 2000 and transfer can be reflected without network expansion in this paper. In addition, we use non-dominated paths and tree sets as labels in order to improve effectiveness of searching non-dominated paths. We also classifies path finding attributes into transfer and link travel attribute in limited transit networks. Lastly, the calculation process of proposed algorithm is checked by computer programming in a small-scaled multi-modal transportation network.

• Journal of Korean society of Dental Hygiene
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• v.18 no.3
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• pp.385-397
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• 2018

Objectives: The study was a cross-sectional research to examine dental hygiene students' multi-cultural experiences, emotional intelligence and cultural competency and to understand the correlations among them. Methods: The study was conducted from September $1^{st}$ to October $31^{st}$ 2016, based on the survey of 449 students in the department of dental hygiene at 7 Universities. The questionnaire consisted of 57 questions including general characteristics (n=7), multi-cultural experiences (n=7), emotional intelligence (n=16) and cultural competency (n=27). Results: Each score of students' emotional intelligence and cultural competency is 3.43 and 3.01 respectively in 5-point scale. An analysis of correlations between emotional intelligence and cultural competency shows that the higher the emotional intelligence, the higher the cultural competency (r=0.342). The factors affecting the cultural competency include use of emotions (${\beta}=0.327$, p<0.001), control of emotions (${\beta}=0.254$, p=0.001), frequency of multi-cultural media (${\beta}=0.221$, p<0.001) and experience of multi-cultural class (${\beta}=0.221$, p=0.002). The modified explanatory power in this model is 28.2% (F=10.856, p<0.001). Conclusions: There was a positive correlation between emotional intelligence and cultural competency, and the contacts with multi-culture and experience of class are identified as the affecting factors. Dental hygiene students should acquire theoretical experiences regarding the multi-culture through curriculum or continuous educations and it is necessary to promote such educations in order to develop and apply the programs for the enhancement of emotional intelligence.

• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.841-848
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• 2004

Evolutionary a1gorithms are well-suited for multi-objective optimization problems involving several, often conflicting objectives. Pareto-based evolutionary algorithms, in particular, have shown better performance than other multi-objective evolutionary algorithms in comparison. However, generalized evolutionary multi-objective optimization algorithms have a weak point, in which the distribution of solutions are not uni-formly distributed onto Pareto optimal front. In this paper, we propose an evolutionary a1gorithm for multi-objective optimization which uses seed individuals in order to overcome weakness of algorithms Published. Seed individual means a solution which is not located in the crowded region on Pareto front. And the idea of our algorithm uses seed individuals for reproducing individuals for next generation. Thus, proposed a1go-rithm takes advantage of local searching effect because new individuals are produced near the seed individual with high probability, and is able to produce comparatively uniform distributed pareto optimal solutions. Simulation results on five testbed problems show that the proposed algo-rithm could produce uniform distributed solutions onto pareto optimal front, and is able to show better convergence compared to NSGA-II on all testbed problems except multi-modal problem.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.3
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• pp.1-14
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• 2008

Mass transit information should contribute many benefits to users. Especially transportation information technology is developing highly with information technology in Korea recently. Hereafter it is expected to provide customized transportation information to users individually with the advent of ubiquitous age in earnest. This public transportation information service can be realized by path finding algorithms in public transportation networks including travel and transfer attributes. In this research, multi objectives such as travel time, transfer time, and number of transfer and so on are constructed with the primary facts influencing users. Moreover, the method reducing user's path finding alternatives arbitrarily is proposed by selecting the best alternative which provides maximum utility to users among non dominated paths. Therefore, the ultimate goal of this study proposes a multi objective shortest paths finding algorithm which can take into account multiple user classes in a transit network with multiple travel modes. The proposed algorithm is demonstrated based on the two case studies - a small toy network and the large-scaled Seoul Metropolitan subway network.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.738-743
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• 1991

A multiobjective analysis technique was applied for the optimum operation of pumps and reservoirs in service water transmission systems. Three major objectives were identified and assessed on the normally operating service water transmission systems. They are, 1) stability of pump operation; 2) economic point of view in minimizing the energy cost for pumping; 3) reliability in meeting the stochasticaly varying demands. The measures of these objectives were required times of pump on-offs in stability, required total energy cost in economics, and minimum required storage during the operating horizon in reliability. In order to find the best meeting solution to the decision maker, a set of non-dominated solutions which show the tradeoff relationships between the considering objectives were generated. The DM selects the best solution from this explicit tradeoff relationships using his heuristic decision rules or experience. The theory was verified by applying to the Kumi Service Water System. A combined technique of the ${\varepsilon}-constraint$ and the weighting methods was used to generate the nondominated solutions, and the dynamic programming algorithm was applied to find the optimal solution for the discretized multi-objective analysis problems.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.34 no.2
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• pp.76-92
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• 2023

Objectives: This study aimed to analyze research trends in autism spectrum disorder (ASD) and savant syndrome and their cognitive characteristics through a systematic literature review. The objectives of this study were to establish an overview of research trends in ASD and savant syndrome, analyze the overall characteristics of individuals with ASD and savant syndrome, and examine their cognitive characteristics. Methods: For the systematic literature review, three criteria were used to select review articles: 1) literature from peer-reviewed journals, published in the past 15 years, from 2008 to 2022; 2) subjects with ASD and savant syndrome; 3) study objectives focused on the basic phenomenon and cognitive characteristics of ASD and savant syndrome. Finally, based on the selection criteria, a total of 40 articles were included. Results: Five themes and nine subthemes were derived from the analysis of 40 studies. The five main themes were as follows: 1) What is savant syndrome? 2) Demographic characteristics of savant syndrome; 3) Spectra of savant syndrome; 4) Savant syndrome and ASD; and 5) Cognitive characteristics of ASD with savant syndrome. The subthemes of the cognitive characteristics were weak central coherence, detail-focused cognitive processing, enhanced perceptual functioning, and hyper-systemizing. Conclusion: Several studies have been conducted to understand ASD and savant syndrome; however, no single theory can specify the cognitive characteristics of people with ASD and savant syndrome. Therefore, further systematic and multi-layered research on ASD and savant syndrome are required for more comprehensive results.