• Korean Journal of Comparative Education
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• v.27 no.3
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• pp.129-159
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• 2017

This study examines the social recognition of teachers' treatment and teaching profession through the comparison and analysis of the teachers' remuneration systems in the Republic of Korea(hereafter, Korea) and Canada. For this purpose, literature review and qualitative research were conducted. As a result of comparing and analyzing the orientation of teachers' remuneration systems in both countries and perception of teachers, the following differences were found. First, in terms of the management philosophy of the remuneration system, Korea emphasized the efficiency of the national competitiveness dimension, while Canada focused on the interrelationship with development of individual-oriented competency. Second, although the remuneration systems for teachers in both countries are quite different, they have aimed at establishing a reasonable remuneration system, which considers equality in common. But the position on equality was different between the two countries. In the case of Korea, equity was considered by comparing the pay scale with those of other government employees, while equity in Canada mainly had to do with gender equality. Third, the teachers of both countries regarded the sense of duty and ethics as important qualities of the teaching profession, and they recognized the social safety net as an indicator of their social status. However, there was a difference in attitude toward the teaching profession. In Korea, it was deemed to be a stable and socially desirable profession, but the entry barriers were quite high and the remuneration system was relatively rigid. In Canada, on the other hand, it was easy to enter the teaching profession and the remuneration system was far less rigid. But teachers were more likely to quit or take a second job, and their social status fluctuated.

• Journal of the Korea Society of Computer and Information
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• v.18 no.8
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• pp.65-75
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• 2013

This paper proposes a method of tracking the hand region and detecting the fingertip using only depth images. In order to eliminate the influence of lighting conditions and obtain information quickly and stably, this paper proposes a tracking method that relies only on depth information, as well as a method of using region growing to identify errors that can occur during the tracking process and a method of detecting the fingertip that can be applied for the recognition of various gestures. First, the closest point of approach is identified through the process of transferring the center point in order to locate the tracking point, and the region is grown from that point to detect the hand region and boundary line. Next, the ratio of the invalid boundary, obtained by means of region growing, is used to calculate the validity of the tracking region and thereby judge whether the tracking is normal. If tracking is normal, the contour line is extracted from the detected hand region and the curvature and RANSAC and Convex-Hull are used to detect the fingertip. Lastly, quantitative and qualitative analyses are performed to verify the performance in various situations and prove the efficiency of the proposed algorithm for tracking and detecting the fingertip.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1965-1974
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• 2021

Satellite remote sensing approach can be actively used for forest monitoring. Especially, it is much meaningful to utilize Korea multi-purpose satellites, an independently operated satellite in Korea, for forest monitoring of Korea, Recently, several studies have been performed to exploit meaningful information from satellite remote sensed data via machine learning approaches. The forest information produced through machine learning approaches can be used to support the efficiency of traditional forest monitoring methods, such as in-situ survey or qualitative analysis of aerial image. The performance of machine learning approaches is greatly depending on the characteristics of study area and data. Thus, it is very important to survey the best model among the various machine learning models. In this study, the performance of deep neural network to classify artificial or natural forests was analyzed in Samcheok, Korea. As a result, the pixel accuracy was about 0.857. F1 scores for natural and artificial forests were about 0.917 and 0.433 respectively. The F1 score of artificial forest was low. However, we can find that the artificial and natural forest classification performance improvement of about 0.06 and 0.10 in F1 scores, compared to the results from single layered sigmoid artificial neural network. Based on these results, it is necessary to find a more appropriate model for the forest type classification by applying additional models based on a convolutional neural network.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.183-190
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• 2011

In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as 'gun', 'scream', 'siren', 'crash', 'bomb' via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.1
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• pp.443-467
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• 2021

The purpose of this study was to conduct interviews with librarians who have experience in establishing local authority data by participating in the national authority sharing system of the National Library of Korea and to understand librarians' recognition and support for the joint utilization of national authority data. For this purpose, a total of 10 librarians who participated in the national authority sharing system project were interviewed by telephone using semi-structured questionnaires. Through this, it was possible to investigate the benefits, difficulties, utilization plans, revision plans of headings, and opinions on necessary support. The results of this study showed that the participants recognized that the joint utilization of national authority data provides the basis for the authority work of the local library and brings about the efficiency of the authority work, but they recognized the difficulty of modifying, selecting, creating new data, lacking knowledge, and lacking support system. The necessary support for the joint utilization of national authority data was provided with education and manuals related to authority, provision of rules related to authority that fully consider the position of the institution, budget and manpower support for system development and maintenance, establishment of communication channel and council, system and data advancement, and incentive to participating libraries. Based on the results of the study, the method and direction for the future operation of the joint utilization of national authority data were presented.

• The Journal of Sustainable Design and Educational Environment Research
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• v.21 no.4
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• pp.21-28
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• 2022

This study analyzes the reality of the overall operating system, such as recognition and satisfaction with school field support work system of the Education Facilities Management Center, recognition level of restructuring of work areas, and the direction of improvement for school facility maintenance support in various types of future learning environments. To analyze the problem of this study, a survey was conducted on 290 education administrative officials in Gyeonggi-do. First, school site awareness and work performance satisfaction of the Educational Facilities Management Center were evaluated as "below average," and it is necessary to improve the qualitative work area that is practically helpful to schools. Second, in the area of organizational operation, it is desirable to avoid simple tasks with a low evaluation of "below average" and to switch to an operating system that improves efficiency. Third, the need for the facility environment area (professionalism, safety) was the highest, but the center's ability and work processing level were evaluated very low as "below average," so it is urgent to improve the center's capacity. Fourth, in the area of social and educational policy change, the center received a high score for the need for access from the perspective of a learning environment linked to future education. Therefore, a policy review on the restructuring and improvement of work areas suitable for this is necessary.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.85-100
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• 2023

Corporate ESG performance (environmental, social, and corporate governance) reflecting a company's strategic sustainability has emerged as one of the main factors in today's investment decisions. The traditional ESG performance rating process is largely performed in a qualitative and subjective manner based on the institution-specific criteria, entailing limitations in reliability, predictability, and timeliness when making investment decisions. This study attempted to predict the corporate ESG rating through automated machine learning based on quantitative and disclosed corporate financial information. Using 12 types (21,360 cases) of market-disclosed financial information and 1,780 ESG measures available through the Korea Institute of Corporate Governance and Sustainability during 2019 to 2021, we suggested a deep neural network prediction model. Our model yielded about 86% of accurate classification performance in predicting ESG rating, showing better performance than other comparative models. This study contributed the literature in a way that the model achieved relatively accurate ESG rating predictions through an automated process using quantitative and publicly available corporate financial information. In terms of practical implications, the general investors can benefit from the prediction accuracy and time efficiency of our proposed model with nominal cost. In addition, this study can be expanded by accumulating more Korean and international data and by developing a more robust and complex model in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.969-974
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• 2006

Labor shortages are a serious problem for Korea's construction industry. The problem is both quantitative and qualitative. There is a shortage in supply as due to a decrease in the influx of new labor, and existing workers are less productive as they age. The problem will only get worse as more and more major public projects are being planned. Options for increasing the labor supply are somewhat limited, and thus efforts need to be made to adopt new technologies that can improve the productivity and efficiency of field work and their processes. This paper introduces seven innovation technologies that have the best potential to increase productivity and thus reduce the burden of labor shortage problems. These include 1) Substitution by use of robotics and automation, 2) development and applications of Innovative materials to reduce on site field work, 3) increase in productivity through the implementation of Information Technology, 4) improved productivity through the application of modules, and prefabrication, 5) prevention of rework and redesign, 6) diversification of labor by integrating labor skills, and 7) improved productivity by standardizing site processes.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.3
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• pp.1-12
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• 2024

In this paper, we fine-tuned KoAlpaca, a large-scale Korean language model, and implemented a blog text generation system utilizing it. Blogs on social media platforms are widely used as a marketing tool for businesses. We constructed training data of positive reviews through emotion analysis and refinement of collected sponsored blog texts and applied QLoRA for the lightweight training of KoAlpaca. QLoRA is a fine-tuning approach that significantly reduces the memory usage required for training, with experiments in an environment with a parameter size of 12.8B showing up to a 58.8% decrease in memory usage compared to LoRA. To evaluate the generative performance of the fine-tuned model, texts generated from 100 inputs not included in the training data produced on average more than twice the number of words compared to the pre-trained model, with texts of positive sentiment also appearing more than twice as often. In a survey conducted for qualitative evaluation of generative performance, responses indicated that the fine-tuned model's generated outputs were more relevant to the given topics on average 77.5% of the time. This demonstrates that the positive review generation language model for sponsored content in this paper can enhance the efficiency of time management for content creation and ensure consistent marketing effects. However, to reduce the generation of content that deviates from the category of positive reviews due to elements of the pre-trained model, we plan to proceed with fine-tuning using the augmentation of training data.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.645-661
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• 2024

Today, the development of new technologies due to the 4th industrial revolution requires work performance methods such as non-face-to-face collaboration. In response to this, various VR collaboration tools are emerging, but VR collaboration tools for brainstorming, which are used in collaboration or design development work, are not provided. Therefore, despite the advantages and possibilities of VR for non-face-to-face collaboration, there are limitations in practical use. Accordingly, the development of VR collaboration tools in a digitalized work environment is necessary, and research on UI design development for this is required. The purpose of this study is to propose a VR collaboration tool prototype by developing an interaction UI design that applies user hand behavior elements that appear during collaboration sessions through user research. This study was a qualitative study. The research method was to conduct user research through observation and in-depth interviews, and as a result of analyzing the data obtained from this, five types of user hand behavior elements were derived. In this study, an interaction UI design was developed that reflects hand gestures as behavioral elements. And using Unity and the Oculus Integration SDK Kit, we created a prototype VR collaboration tool that can be used without a controller. As a result of conducting a user evaluation of the prototype produced in this study, it was found that users had difficulty making hand gestures accurately, and it was possible to find areas for improvement in UI design. It is expected that this study will help develop interaction UI design for VR collaboration tools that can increase work efficiency.