• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.409-418
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• 2019

For the success of construction projects, construction companies have begun to recognize the innovation ability of members who participate in projects that can adapt and cope with environmental changes caused by knowledge-based informatization and globalization. The questionnaire of the research selected 254 final valid samples of the members participating in the construction project using online. An empirical analysis of the research model used the structural equation model (Smart-PLS 2.0). The purpose of this study is to investigate the effect of psychological ownership on person-job fit and rewards system in the construction project. First, person-job fit has a positive effect on psychological ownership. Second, intrinsic rewards and extrinsic rewards in the rewards system have a positive effect on the psychological ownership. Third, psychological ownership has a positive effect on innovative behavior. Finally, the mediating effects of psychological ownership were found to have no mediating effect on person-job fit and rewards system. In order to induce innovation behavior, the managers of construction companies need to recognize the importance of psychological ownership and build a model of construction project organization activation through development of person-job fit and rewards program.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.867-874
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• 2023

Recently, many problems are occurring in the bee ecosystem due to rapid climate change. The decline in the bee population and changes in the flowering period are having a huge impact on the harvest of bee-keepers. Since it is impossible to continuously observe the beehives in the hive with the naked eye, most people rely on knowledge based on experience about the state of the hive.Therefore, interest is focused on smart beekeeping incorporating IoT technology. In particular, with regard to swarming, which is one of the most important parts of beekeeping, we know empirically that the swarming time can be determined by the sound of the queen bee, but there is no way to systematically analyze this with data.You may think that it can be done by simply recording the sound of the queen bee and analyzing it, but it does not solve various problems such as various noise issues around the hive and the inability to continuously record.In this study, we developed a system that records queen bee sounds in a real-time cloud system and analyzes sound patterns.After receiving real-time analog sound from the hive through multiple channels and converting it to digital, a sound pattern that was continuously output in the queen bee sound frequency band was discovered. By accessing the cloud system, you can monitor sounds around the hive, temperature/humidity inside the hive, weight, and internal movement data.The system developed in this study made it possible to analyze the sound patterns of the queen bee and learn about the situation inside the hive. Through this, it will be possible to predict the swarming period of bees or provide information to control the swarming period.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.571-578
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• 2013

The IHO S-100 is a standard on the universal hydorgraphic data model for supporting information services that integrate various data in maritime and provide proper information for safety of vessels. The S-100 is used to develop S-10x product specifications which are standards on guideline for creation and delivery of specific data set in maritime. The product specification for feature-based data such as ENC(Electronic Navigational Chart) data includes a feature catalogue that describes characteristics of features in that feature-based data. The feature catalogue is developed by domain experts with knowledge on data of the target domain. However, it is not feasible to develop a feature catalogue according to the XML schema by manual. In the IHO TSMAD committee meeting, needs of developing technology on building feature catalogue has been discussed. Therefore, we present a feature catalogue builder that is a GUI(Graphic User Interface) system supporting domain experts to build feature catalogues in XML. The feature catalogue builder is developed to connect with the FCD(Feature Concept Dictionary) register in the IHO(International Hydrographic Organization) GI(Geographic Information) registry. Also, it supports domain experts to select proper feature items based on the relationships between register items.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.147-168
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• 2011

As personalized recommendation of products and services is rapidly growing in importance, a number of studies provided fundamental knowledge and techniques for developing recommendation systems. Among them, the CF technique has been most widely used and has proven to be useful in many practices. However, current collaborative filtering (CF) technique has still considerable rooms for improving the effectiveness of recommendation systems: 1) a similarity function most systems use to find so-called like-minded people is not well defined in that similarity is computed from a single perspective of similarity concept; and 2) temporal information that contains the changing preference of customers needs to be taken into account when making recommendations. We hypothesize that integration of multiple aspects of similarity and utilization of temporal information will improve the accuracy of recommendations. The objective of this paper is to test the hypothesis through a series of experiments using MovieLens data. The experimental results show that the proposed recommendation system highly outperforms the conventional CF-based systems, confirming our hypothesis.

• Journal of the Korea Institute of Building Construction
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• v.10 no.5
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• pp.45-54
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• 2010

Recently more and more construction projects have become high-rise, complex and intelligent. Accordingly, such projects require an integrated management system for tasks, with a lean approach to construction with work processes for management and productivity. In particular, Construction Information Technology (CIT) fields are concerned with Building Information Modeling (BIM), which represents the process of generating and managing building data during its life cycle. Constructability research has progressed for the project goal which is a cost-time-quality of optimization by integrated construction knowledge and experience. However, the current constructability process has not been performed efficiently, as the existing 2D drawings and papers lack consistent and accurate information, it is difficult to share the contents of work, and the use of information is inefficient. This study proposes that the reformation and enhancement of BIM-based constructability work process can lead to brilliant performance in the framework of the construction phase through achieving collaboration between the design team and the workers at the site.

• Korean Journal of Construction Engineering and Management
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• v.8 no.4
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• pp.128-136
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• 2007

As the international-level concern has been focused on the environmental sustainability in recent years, many researches emphasized the needs for methods and techniques that would facilitate sustainability assessment at the various project level interfaces. As part of methods and techniques to facilitate sustainability assessment, this paper provides 'Computerized Waste Management Performance Evaluation Tool' for the purpose of assessing the level of management system in dealing with the onsite construction wastes. This tool applies twenty-three waste management performance factors for the purpose of evaluating the level of waste management performance by scoring those factors which were identified in the previous research. These twenty-three factors are classified into four categories: manpower, material, method, and management based on their characteristics. In order to quantitatively evaluate the effectiveness of waste management performance, the levels of actions executed in a site by each waste management performance factor were identified and their weight were analyzed throughout the expert interview and survey. Furthermore, an excel-based computerized tool was developed in order to facilitate the evaluation process. If this tool can be developed in more detail and be used as the method to control waste management at a project level for the future, it is expected that this tool can play an important role in the body of knowledge of environmental management in construction industry.

• Journal of the Korea Institute of Building Construction
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• v.23 no.4
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• pp.417-428
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• 2023

The demolition of domestic infrastructures mirrors other significant construction initiatives in presenting a markedly high accident rate. A comprehensive investigation into the origins of such accidents is crucial for the prevention of future incidents. Upon detailed inspection, the causes of demolition construction accidents are multifarious, encompassing unsafe worker behavior, hazardous conditions, psychological and physical states, and site management deficiencies. While statistics relating to demolition construction accidents are consistently collated and reported, there exists an exigent need for a more foundational cause categorization system based on accident type. Drawing from Heinrich's Domino Theory, this study classifies the origins of accidents(unsafe behavior, unsafe conditions) and human errors(human factors) as per the type of accidents experienced during demolition construction. In this study, a three-step model of QFD-FMEA(Quality Function Deployment - Failure Mode Effect Analysis) is employed to systematically categorize accident causes according to the types of accidents that occur during demolition construction. The QFD-FMEA method offers a technique for cause classification at each stage of the demolition process, including direct causes(unsafe behavior, unsafe environment), and human errors(human factors) through a tri-stage process. The results of this accident cause classification can serve as safety knowledge and reference checklists for accident prevention efforts.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.2 no.1
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• pp.133-151
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• 2007

In the era of 21st new century. reinforcement of regional competitiveness by establishing innovation system is taking its place of main small and medium sized enterprise policies in major developed countries. The model of regional balanced development for promoting small and medium sized enterprise is a main frame of governmental small and medium sized enterprise policies. which complements national innovation process. And in the level of local area, the model is regional network system, molded in the process of induction, application, modification, proliferation of new technologies and knowledge by local businessman and innovators. This study focused on the strategy development for small and medium sized businesses to increase local competitive power, in terms of regional balanced development. In order to find the real problems and improvement alternatives for local competitive power, this study both reviewed the common strategies and action programs advanced in developed countries for small businesses, and did research on the current economic conditions in local area. Based on the lessons from foreign cases and the analysis of the current situations in small business in local area, the study suggested the model of regional balanced development for promoting small and medium sized enterprise including formation of innovation network system through the invitation of leading firms in the area, industry-university partnerships, and development and attraction for small and medium sized businesses.

• Clean Technology
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• v.27 no.2
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• pp.160-167
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• 2021

This study investigated the environmental effects of improving the general-type activated carbon adsorption tower used at the Sihwa/Banwol Industrial Complex with use of a cartridge-type activated carbon adsorption tower for the application of an activated carbon co-regenerated system. Four general-type activated carbon adsorption towers and two cartridge-type activated carbon adsorption towers were selected to analyze the properties of activated carbon and to compare the efficiency of reducing environmental pollutants. The results showed that the activated carbon used in the cartridge-type activated carbon adsorption towers was high quality activated carbon with an iodine adsorption force of more than 800 mg/g and that a good adsorption performance was maintained within the replacement cycle. From an analysis of the environmental pollutant reduction efficiency, it was confirmed that the cartridge-type activated carbon adsorption tower functioned properly as a prevention facility for handling emissions pollutants with a treatment efficiency of total hydrocarbons (THC), toluene, and methylethylketone (MEK) components of 71%, 77%, and 80%, respectively. The general activated carbon adsorption tower, which was confirmed to use low-performance activated carbon, had a very low treatment efficiency and did not function properly as a prevention facility for dealing with emission pollutants. It is believed that it is possible to reduce pollutants during operations by changing from the general-type activated carbon adsorption tower to a cartridge-type activated carbon adsorption tower.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.11
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• pp.481-492
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• 2023

This study explores how to build a Korean dataset to extract information from text using generative large language models. In modern society, mixed information circulates rapidly, and effectively categorizing and extracting it is crucial to the decision-making process. However, there is still a lack of Korean datasets for training. To overcome this, this study attempts to extract information using text-based zero-shot learning using a generative large language model to build a purposeful Korean dataset. In this study, the language model is instructed to output the desired result through prompt engineering in the form of "system"-"instruction"-"source input"-"output format", and the dataset is built by utilizing the in-context learning characteristics of the language model through input sentences. We validate our approach by comparing the generated dataset with the existing benchmark dataset, and achieve 25.47% higher performance compared to the KLUE-RoBERTa-large model for the relation information extraction task. The results of this study are expected to contribute to AI research by showing the feasibility of extracting knowledge elements from Korean text. Furthermore, this methodology can be utilized for various fields and purposes, and has potential for building various Korean datasets.