• International conference on construction engineering and project management
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• 2024.07a
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• pp.375-382
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• 2024

Large Language Models (LLMs) still encounter challenges in comprehending domain-specific expressions within construction documents. Analogous to humans acquiring unfamiliar expressions from dictionaries, language models could assimilate domain-specific expressions through the use of a thesaurus. Numerous prior studies have developed construction thesauri; however, a practical issue arises in effectively leveraging these resources for instructing language models. Given that the thesaurus primarily outlines relationships between terms without indicating their relative importance, language models may struggle in discerning which terms to retain or replace. This research aims to establish a robust framework for guiding language models using the information from the thesaurus. For instance, a term would be associated with a list of similar terms while also being included in the lists of other related terms. The relative significance among terms could be ascertained by employing similarity scores normalized according to relevance ranks. Consequently, a term exhibiting a positive margin of normalized similarity scores (termed a pivot term) could semantically replace other related terms, thereby enabling LLMs to comprehend domain-specific terms through these pivotal terms. The outcome of this research presents a practical methodology for utilizing domain-specific thesauri to train LLMs and analyze construction documents. Ongoing evaluation involves validating the accuracy of the thesaurus-applied LLM (e.g., S-BERT) in identifying similarities within construction specification provisions. This outcome holds potential for the construction industry by enhancing LLMs' understanding of construction documents and subsequently improving text mining performance and project management efficiency.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.516-523
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• 2024

This study introduces a comprehensive framework for 4D safety analysis in construction site layout planning (CSLP), using a Site Information Model (SIM) environment to enhance spatial hazard identification and effectively integrate it with activity-based safety management. The framework, grounded in a continuous-space layout approach, accurately positions objects to mirror temporary facilities' actual boundaries, incorporating spatial relationships and inherent safety hazards. It also features rasterization to translate layouts into a grid system. Central to this framework are three modules for spatial hazard identification: Visibility Analysis, Spatial Hazard Mapping, and Travel Path Analysis, designed to identify less visible spaces, assess spatial hazards, and simulate optimal travel paths considering safety aspects. By applying this framework to case studies of a residential complex and a commercial office project, the research demonstrates its practical utility in improving visibility and spatial hazard assessment, despite the inherently complex dynamics of construction sites. The study acknowledges challenges, such as the reliance on safety managers' experiential knowledge for setting hazard parameters and the need for further development in integrating these insights with activity-based safety management. It underscores the framework's significant potential to advance construction safety management by offering a method to preemptively recognize and mitigate spatial hazards. The approach promises not only to contribute to accident prevention but also to enhance overall project performance by incorporating spatial and temporal dimensions of safety into CSLP. This research marks a significant step toward a more holistic and integrated approach to construction safety, highlighting the importance of continuous improvement and adaptation in safety practices.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1049-1056
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• 2024

Human-robot collaboration (HRC) is an emerging form of work anticipated to improve construction productivity by integrating robotic capabilities with human expertise. With the expected transition towards tasks that demand more cognitive efforts for human workers, considering the cognitive status of each co-worker, such as task engagement and vigilance, can become crucial to achieve high-quality human performance during HRC, potentially contributing to a more productive HRC in construction. However, the potential cognitive changes of each co-worker have remained unclear during HRC, as studies have primarily focused on identifying general trends from aggregated cognitive responses of people, in which an individual's response can be overlooked. In this study, we examine the cognitive response of each co-worker during HRC for a construction task. We observed the cognitive responses of 18 people while they were experiencing different collaborating conditions, such as the robot's different movement speed, during a bricklaying task with an arm-type collaborative robot. For each participant, we analyzed electroencephalogram (EEG) signals to identify the changes in cognitive status by using a wearable EEG headset. The results present that the cognitive responses of almost all the participants were significantly and differently affected during HRC, impacting the estimated productivity of their human-robot teams. The findings of the study present the importance of considering each co-worker's potentially unique cognitive response as a way to achieve cognitive wellbeing while pursuing high productivity within human-robot teams, potentially contributing to overall productive HRC in construction.

• Clean Technology
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• v.30 no.3
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• pp.188-194
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• 2024

This study investigates the impact of reduction temperature on the structure and performance of cobalt-manganese (CM) based catalysts in the direct hydrogenation reaction of carbon dioxide (CO₂). It was observed that at a reduction temperature of 350 ℃, these catalysts could successfully facilitate the conversion of CO₂ into long-chain hydrocarbons. This efficiency is attributed to the optimal conditions provided by the core-shell structure of the catalysts, which effectively catalyzes both the reverse water-gas shift (RWGS) and Fischer-Tropsch (FT) reactions. However, as the reduction temperature increased to 600 ℃, the effectiveness of the reaction process was hindered, and there was a shift in selectivity towards methane. This shift is due to the excessive reduction of the catalyst's outer shell, which reduces the number of RWGS sites and subsequently suppresses the production of CO. These findings highlight the importance of carefully controlling the reduction temperature in the design and optimization of cobalt-based catalysts. Maintaining a balance between the RWGS and FT reactions is crucial. This emphasizes that the reduction temperature is a key factor in efficiently generating long-chain hydrocarbons from CO₂.

• Steel and Composite Structures
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• v.52 no.6
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• pp.647-656
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• 2024

This paper discusses the study of concrete composite walls of algorithmic modeling, in which steel tubes are embedded. The load-bearing capacity of STHC composite walls increases with the increase of axial load coefficient, but its ductility decreases. The load-bearing capacity can be improved by increasing the strength of the steel pipes; however, the elasticity of STHC composite walls was found to be slightly reduced. As the shear stress coefficient increases, the load-bearing capacity of STHC composite walls decreases significantly, while the deformation resistance increases. By analyzing actual cases, we demonstrate the effectiveness of the research results in real situations and enhance the persuasiveness of the conclusions. The research results can provide a basis for future research, inspire more explorations on seismic design and construction, and further advance the development of this field. Emphasize the importance of research results, promote interdisciplinary cooperation in the fields of structural engineering, earthquake engineering, and materials science, and improve overall seismic resistance. The emphasis on these aspects will help highlight the practical impact of the research results, further strengthen the conclusions, and promote progress in the design and construction of earthquake-resistant structures. The goals of this work are access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient architecture, sustainable planning and management of human settlements. Simulation results of linear and nonlinear structures show that this method can detect structural parameters and their changes due to damage and unknown disturbances. Therefore, it is believed that with the further development of fuzzy neural network artificial intelligence theory, this goal will be achieved in the near future.

• Applied Chemistry for Engineering
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• v.35 no.5
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• pp.361-371
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• 2024

This study reviews recent advancements in Ni-based catalysts for CO₂ methanation, emphasizing high thermal stability and catalytic performance at elevated temperatures. Ni catalysts are preferred for their strong hydrogen adsorption, high activity, and methane selectivity. Strategies such as optimizing metal loading, using efficient supports, and introducing promoters enhance thermal stability by preventing sintering and carbon deposition. The produced methane serves as a valuable feedstock for synthetic fuels and chemicals, improving the economic feasibility of the CO₂ methanation process. These findings underscore the importance of thermal stability in developing effective Ni catalysts for large-scale CO₂ methanation.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.3
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• pp.478-486
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• 2013

The purpose of this study was to analyze consumer consumption and product concept demands of Korean rice-wine. An online survey, conducted from April 28, 2010 to May 6 2010, targeted 200 consumers in Seoul and the Gyeonggi-do area. More than half of the respondents (51.3%) drank rice-wine because of the taste. The common reasons for dissatisfaction with rice-wine were hangovers (35.7%) and taste (16.9%). From analyzing rice-wine preferences, the most preferred ingredient was rice (57.8%), while the most preferred aroma and taste was derived from the fruit (48.7% and 58.4%, respectively). The most common methods consumers observed for promoting rice-wine consumption were the "development and management of rice-wine brands" (59.7%), and "continuous promotion" (44.8%). The most important attributes of a rice-wine product included its taste (4.60), followed by its quality (4.41) using 5-point Likert scale. An importance-performance analysis (IPA) was performed for the 17 attributes of rice-wine and identified targets for product management strategies, including the "usage of domestic ingredients", "ease of purchase", clarity of "product information", and "external image". Therefore, developing solid concepts in marketing strategy are required and may be achieved by understanding the consumer preferences and demands of rice-wine.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• Journal of the Korean Society of Food Science and Nutrition
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• v.40 no.7
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• pp.1032-1042
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• 2011

The purpose of this study was to examine the attitudes and satisfaction level towards military foodservices as well as suggest effective ways to increase foodservice quality. A questionnaire survey was administered to 413 subjects, which included 400 soldiers and 13 foodservice managers. The survey period was from August 6 to August 25, 2008. The collected data were statistically treated using SPSS V12.0. Most of the investigated soldiers were 20~25 years old. The foodservice managers were male general officials and the majority of them had no prior food service training. None of the foodservice managers had a dietician certificate. Menu was planned through a local foodservice conference, and most food materials were delivered in the form of center-type and military unit-type. Deficiency and deterioration of food service facilities (28.6%) as well as deficiency in the number of cooking personnel (14.3%) increased the difficulty of operational management. Soldiers expressed a desire for increases in Western (25.7%) and Korean traditional foods (21.5%), which meant menu diversity. To increase the quality of military foodservices, taste of food (40.6%), increased portion size (30.4%), and improvement in hygienic conditions (13.6%) were demanded by the soldiers. Food taste (30.8%), improvement in hygienic conditions (23.1%), and better job management were all demanded by the foodservice managers. After factor analysis, quality attributes were rearranged into five dimensions, including facilities, food, menu, service, and sanitation most attributes were over 4 points out of 5 total in importance, but only 3 points in performance. The importance score was higher than the performance score. Soldiers' overall satisfaction level was on average 3.43 points out of 5 points.

• Journal of muscle and joint health
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• v.8 no.1
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• pp.122-140
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• 2001

The aims of this study were to understand and to predict the determinent factors affecting the exercise behaviors and physical fitness by testing the Pender's revised health promotion model, and to help the patients with rheumatoid arthritis and osteoarthritis perform the continous exercise program, and to help them maximize the physical effect such as muscle strength, endurance, and functional status and mental effects including self efficacy and quality of life, and improve the physical and mental well being, and to provide a basis for the nursing intervention strategies. Of the selected variables in this study, the endogenous variables included the physical fitness, exercise score, exercise participation, perceived benefits of action, perceived barriers of action to exercise, activity-related affect(depression) and perceived self-efficacy, interpersonal influences(family support), situational factors(duration of arthritis, fatigue) and the exogenous variables included personal sociocultural factor(education level), personal biologic factor(body mass index), personal psychologic factor(perceived health status) and prior related behavior factors(previous participation in exercise, life-style). We analyzed the clinical records of 208 patients with rheumatoid arthritis and degenerative arthritis who visited the outpatient clinics at H university hospital in Seoul. Data were composed of self reported qustionnaire and good of fitness score which were obtained by padalling the ergometer of bicycle for 9 minutes. SPSS Win 8.0 and Window LISREL 8.12a were used for statistical analysis. Of 75 hypothetical paths that influence on physical fitness, exercise participation, exercise score, perceived benefits of action, perceived barriers of action to exercise, activity-related affect(depression) and perceived self-efficacy, interpersonal influences(family support), situational factors(duration of arthritis, fatigue), 40 were supported. The physical fitness was directly influenced by life-style, perceived health status, education level, family support, fatigue, which explained 12% of physical fitness. The exercise participation were directly influenced by life-style, education level, past exercise behavior, perceived benefits of action, perceived barriers of action, depression and duration of arthritis, which explained 47% of exercise participation. Exercise score were directly affected by perceived self efficacy. BMI, life-style, past exercise behavior, perceived benefits of action, family support, perceived health status. perceived barriers of action, and fatigue, which explained 70%. Perceived benefits of action was directly influenced by BMI, life-style, which explained 39%. Perceived barriers of action were directly influeced by past exercise behavior, perceived health status, which explained 7%. Perceived self efficacy were directly influeced by level of education, perceived health status, life-style, which explained 57%. Depression were directly influeced by past exercise behavior, BMI, life-style, which explained 27%. Family support were directly influeced by life-style, perceived health status, which explained 29%. Fatigue were directly influeced by BMI, life-style, perceived health status. which explained 41%. Duration of arthritis were directly influeced by life-style, past exercise behavior, BMI, which explained 6%. In conclusion, important variables for physical fitness were life-style, and variable affecting exercise participation were life-style. Perceived self-efficacy of exercise was a significant predictor of exercise score. BMI, Life-style, perceived benefits of action, family support, past exercise behavior showed direct effects on perceived self-efficacy. Therefore, disease related factor should be minimized for physical performance and well being in nursing intervention for patients with rheumatoid arthritis, and plans to promote and continue exercise should be seeked to reduce disability. In addition, Exercise program should be planned and performed by the exact evaluation of exercise according to the ability of the patients and the contents to improve the importance of exercise and self efficacy in self control program, dedicated educational program should be involved. This study suggest that the methods to reduce the disease related factors, the importance of daily life-style, recognition of benefit of exercise, and educational program to promote self efficacy should be considered in the exercise behavior promotion and nursing intervention for continous performance. The significance of this study is also thought to provide patients with chronic arthritis the specific data for maximal physical and mental well being through exercise, chronic therapeutic procedure, daily adaptation and confrontation in nursing intervention.