• Journal of Information Technology Services
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• v.22 no.5
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• pp.71-86
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• 2023

Recently, various geographic information systems have been used based on spatial information of geographic information systems. Accordingly, it is essential to produce a large-scale map as a small-scale map for various uses of spatial information. However, maps currently being produced have inconsistencies between data due to production timing and limitations in expression, and productivity efficiency is greatly reduced due to errors in products or overlapping processes. In order to improve this, various efforts are being made, such as publishing research and reports for automating domestic mapping, but because there is no specific result, it relies on editors to make maps. This is mainly done by hand, so the time required for mapping is excessive, and quality control for each producer is different. In order to solve these problems, technology that can be automatically produced through computer programs is needed. Research has been conducted to apply the rule base to geometric generalization. The algorithm tolerance setting applied to rule-based modeling is a factor that greatly affects the result, and the level of the result changes accordingly. In this paper, we tried to study the effectiveness of mapping according to tolerance setting. To this end, the utility was verified by comparing it with a manually produced map. In addition, the original data and reduction rate were analyzed by applying generalization algorithms and tolerance values. Although there are some differences by region, it was confirmed that the complexity decreased on average. Through this, it is expected to contribute to the use of spatial information-based services by improving tolerances suitable for small-scale mapping regulations in order to secure spatial information data that guarantees consistency and accuracy.

• Korean Journal of Agricultural Science
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• v.51 no.1
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• pp.63-77
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• 2024

Yield monitoring systems have become integral to precision agriculture, providing insights into the spatial variability of crop yield and playing an important role in modern harvesting technology. This paper aims to review current research trends in yield monitoring systems, specifically designed for non-grain crops, including cabbages, radishes, potatoes, and tomatoes. A systematic literature survey was conducted to evaluate the performance of various monitoring methods for non-grain crop yields. This study also assesses both mass- and volume-based yield monitoring systems to provide precise evaluations of agricultural productivity. Integrating load cell technology enables precise mass flow rate measurements and cumulative weighing, offering an accurate representation of crop yields, and the incorporation of image-based analysis enhances the overall system accuracy by facilitating volumetric flow rate calculations and refined volume estimations. Mass flow methods, including weighing, force impact, and radiometric approaches, have demonstrated impressive results, with some measurement error levels below 5%. Volume flow methods, including paddle wheel and optical methodologies, yielded error levels below 3%. Signal processing and correction measures also play a crucial role in achieving accurate yield estimations. Moreover, the selection of sensing approach, sensor layout, and mounting significantly influence the performance of monitoring systems for specific crops.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.471-485
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• 2024

This study explores the effective utilization of generative AI for conducting in-depth interviews within the lean startup environment. With recent technological advancements, the application of generative AI in enhancing operational productivity has been on the rise across various organizations, and this trend extends to the lean startup milieu. The research develops specific guidelines and a guidebook aimed at assisting practitioners in lean startups to conduct in-depth interviews using AI, even amidst the constraints of limited time and capital. The proposed guidebook facilitates practitioners to swiftly design and conduct interviews, thereby promoting an agile and flexible working environment within lean startups. Moreover, this study investigates practical methods for applying text-based generative AI services like ChatGPT 4 and Luyten in the fields of design and interviewing, thereby contributing to the academic discussion and practical implementation in these areas. The significance of this research lies in its potential to broaden the horizon of scholarly debate and practical application of generative AI in lean startups.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.957-964
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• 2024

Universities own several campuses and many buildings within the campuses. During the operation & maintenance phase, some of the buildings have architectural components and MEPFs that must be maintained. In the authors' study, university campus Facility Manager uses paper drawings and paper documents for operations and maintenance of MEPFs, and building components, which are managed by human power. In this study, As-Built 3D model of school buildings, was developed by 3D scanning with MatterPort Pro2 camera. A digital twin of the school building was developed from integrating the As-Built 3D model with a COBie Sheet information that defines the building and facility components for FMr. This developed digital twin was used to verify the efficiency of conventional Facility Management (FM) operations. The specific procedures are as follows. (1) Conducted an interview survey on FM of conventional university campuses to organize the current operations. (2) The following building items, which are annual inspection items, were extracted from the conventional FM operations being performed, Speakers, fire alarms, fire doors, guide lights, air conditioning, and fire extinguishing equipment. (3) Since these items listed above are currently documented in different formats, the authors organized them into a database using COBie format. (4) The components of the organized COBie format and the As-Built 3Dmodel were integrated to complete the digital twin. (5) To verify the effectiveness of the digital twin, experiments were conducted on information search in current FM operations and workflows using the digital twin. (6) We also verified the effectiveness of the AS-Built 3D model by comparing between the As-Built 3D model and the BIM model. Finally, we discussed how process innovation through digitalization of FM operations contributes not only to the improvement of daily operations, but also to the productivity improvement of university management.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.447-454
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• 2024

Construction site monitoring is pivotal for overseeing project progress to ensure that projects are completed as planned, within budget, and in compliance with applicable laws and safety standards. Additionally, it seeks to improve operational efficiency for better project execution. To achieve this, many researchers have utilized computer vision technologies to conduct automatic site monitoring and analyze the operational status of equipment. However, most existing studies estimate real-world 3D information (e.g., object tracking, work status analysis) based only on 2D pixel-based information of images. This approach presents a substantial challenge in the dynamic environments of construction sites, necessitating the manual recalibration of analytical rules and thresholds based on the specific placement and the field of view of cameras. To address these challenges, this study introduces a novel method for 3D visualization and status analysis of construction site objects using 3D reconstruction technology. This method enables the analysis of equipment's operational status by acquiring 3D spatial information of equipment from single-camera images, utilizing the Sam-Track model for object segmentation and the One-2-3-45 model for 3D reconstruction. The framework consists of three main processes: (i) single image-based 3D reconstruction, (ii) 3D visualization, and (iii) work status analysis. Experimental results from a construction site video demonstrated the method's feasibility and satisfactory performance, achieving high accuracy in status analysis for excavators (93.33%) and dump trucks (98.33%). This research provides a more consistent method for analyzing working status, making it suitable for practical field applications and offering new directions for research in vision-based 3D information analysis. Future studies will apply this method to longer videos and diverse construction sites, comparing its performance with existing 2D pixel-based methods.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1312-1312
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• 2024

BIM, as a means of integrating information into the entire lifecycle of construction, greatly enhances productivity in the AEC (Architecture, Engineering, and Construction) field. With the advent of the Fourth Industrial Revolution, new-generation technologies such as AI and automation have also entered the researchers' field of vision. Nowadays, there is an increasing number of studies combining these two powerful tools for applications in the AEC domain, particularly focusing on their deep and proactive integration into construction project scheduling. This study aims to systematically review the current research status of AI technology in construction project scheduling based on Building Information Modeling (BIM). Through meticulous selection, we ultimately identified 46 peer-reviewed articles as the subject of our investigation. Building upon these sources, we delve into the following inquiries: firstly, we analyze which specific AI algorithms and technologies have been widely researched and practically applied in BIM-based construction project scheduling. Secondly, we examine the challenges and limitations of AI application in construction project scheduling within the BIM environment. Lastly, we explore strategies for further advancing AI technology in supporting construction project scheduling with BIM, aiming to better meet the demands of the construction industry. In terms of technological application, we observe that while decision-making was the primary focus of AI technology in the past, automation now occupies a more significant position in construction project scheduling. Looking ahead, we anticipate that advanced technologies such as deep learning and genetic algorithms will play a more substantial role in this field, offering more efficient and accurate solutions for construction project scheduling. This paper systematically delineates the current research status of AI in construction project scheduling within the BIM environment, providing not only technical guidance for innovation in current construction project management but also valuable insights into the future development directions of AI technology in project scheduling.

• Journal of Korean Library and Information Science Society
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• v.55 no.3
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• pp.337-356
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• 2024

This study aims to retrospectively review how school libraries utilized digital educational tools in a non-face-to-face environment during the pandemic, and to suggest types of digital educational tools suitable for use in the New Normal. Initially, a list of edutech used in schools during the pandemic was compiled by reviewing previous studies. By grasping the frequency of use of edutech expert teachers and librarian teachers, the list of edutech was readjusted to the type of edutech that can be used in school libraries. The use of edutech by school libraries during the pandemic, as reported in the 'School Library Journal,' was analyzed and integrated the previous list of edutech. As a result, edutech suitable for school libraries was categorized into five main areas: management, communication, productivity, consumption, and evaluation. Additionally, specific edutch examples for each category were presented, based on insights from the 'School Library Journal.'

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.4
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• pp.365-369
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• 2016

Red sorrel (Rumex acetosella L.), as one of exotic weeds in Korea, was dominated in grassland and reduced the quality of forage. Improving current pasture productivity by precision management requires practical tools to collect site-specific pasture weed data. Recent development in unmanned aerial vehicle (UAV) technology has offered cost effective and real time applications for site-specific data collection. To map red sorrel on a hill pasture, we tested the potential use of an UAV system with digital cameras (visible and near-infrared (NIR) camera). Field measurements were conducted on grazing hill pasture at Hanwoo Improvement Office, Seosan City, Chungcheongnam-do Province, Korea on May 17, 2014. Plant samples were obtained at 20 sites. An UAV system was used to obtain aerial photos from a height of approximately 50 m (approximately 30 cm spatial resolution). Normalized digital number values of Red, Green, Blue, and NIR channels were extracted from aerial photos. Multiple linear regression analysis results showed that the correlation coefficient between Rumex content and 4 bands of UAV image was 0.96 with root mean square error of 9.3. Therefore, UAV monitoring system can be a quick and cost effective tool to obtain spatial distribution of red sorrel data for precision management of hilly grazing pasture.

• Journal of Korean Library and Information Science Society
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• v.20
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• pp.317-349
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• 1993

The purpose of this study lies in identifying Korean scientists' dependency on foreign scientific and technical information (STI), with emphasis on investigating the causes and results. Especially, this study intends to investigate the impacts that a growing dependency on foreign STI might have brought and will bring about on the development of indigenous STI in ROK. To the end, the present discussion covers the following specific research questions: 1) what are the major information sources used by Korean scientists to locate STI necessary for research-related activities\ulcorner 2) to what extent do Korean scientists use foreign STI for research-related activates, as compared to the use of domestic STI\ulcorner 3) what are the major factors causing the information dependency among Korean scientists and what are the results of the growing information dependency\ulcorner And finally, 4) what suggestions can be made for ROK to further its indigenous STI development, while minimizing its dependency on foreign STI\ulcorner Survey method, together with citation analysis method, is employed as the major data collection technique. The survey sample consists of 167 most 'representative' Korean scientists selected on the basis of their research productivity. 167 specially-designed questionnaires were mailed and 104 out of 167 were responded. Follow-up interviews were carried out for 32 out of 104 respondents, who returned the questionnaire but did not answer some specific questions. The data collected from these 104 respondents were analyzed on the basis of two distinguished groups namely, junior and senior scientist groups. Among the 104 respondents, 58 a n.0, ppeared to belong to a group of senior scientists (older than age 45 and finished their final degrees since 1980), and 46 belonged to a group of junior scientists (younger than age 45 and finished their final degrees before 1980). The major findings of the present study include: 1) Korean scientists regard 'scientific and technical journals and books'as the most important information source to obtain the recent STI; 2) their dependency on foreign STI, for the purposes of research and teaching, is extremely high (information dependency for research activities is 88.5%, and that for teaching activities 91.2%); 3) the information dependency of junior scientists are higher than that of senior scientists; 4) Korean scientists' growing information dependency is closely related to both small quantity and low quality of domestically-produced STI, and has a statistically significant relationship with their educational background; and finally, 5) in order to theoretically explain the growing information dependency of Korean scientists, a hypothesis - 'chronic cycle of information dependency' was developed and introduced. The present study suggests the promotion of indigenous STI as a desirable alternative to escape from the 'chronic cycle of information dependency. Localization of the imported foreign STI is suggested as a good strategy for the indigenous STI development, and also suggested are STI policies for both success of localization process and promotion of more efficient STI flows at national and international level.

• The Journal of Small Business Innovation
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• v.19 no.3
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• pp.57-74
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• 2016

This paper analyzes the role of strategic fit, cooperation, and performance in small-sized subpart suppliers' interactions with large businesses. For this purpose, this paper analyzes survey data from 90 first-tier suppliers of Samsung Electronics and evaluates how strategic fit and cooperative relationships affect their performance. Empirical analysis suggests that strategic fit positively affects small companies' business and innovation performance. This finding aligns with theories arguing for strategies that accommodate specific business environments. In addition, strategic fit is crucial for innovativeness of SMEs (Small and Medium-sized Enterprises). With regard to forming relationships with large companies, findings also show that high quality technological and personnel cooperation boosts subpart suppliers' productivity and efficiency as notably reflected in SMEs' business performance. Moreover, such cooperation between small and large companies reinforces the benefits associated with strategic fit and innovation. This means that if the business environment of small-sized subpart suppliers is uncertain, harnessing differentiated strategies and pursuing collaborations with prime companies will produce innovative outcomes (e.g., increased patent publications). On the other hand, when degree of uncertainty is small, pursuing cost leadership strategies and collaborating with prime companies in areas, such as technology and personnel, will help small-sized subpart suppliers produce innovative outcomes. Based on these findings, this paper argues that choosing the right competitive strategy for a specific business context is intrinsically tied to (1) augmenting technological and human collaborations with prime companies, (2) improving the quality of these interactions, and (3) generating competitiveness among small subpart suppliers. Both competition and cooperation are necessary for strengthening the competitiveness of small companies.