• Korean Journal of Heritage: History & Science
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• v.54 no.3
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• pp.4-23
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• 2021

The purpose of this study was to classify the types of tweezers used across time and to examine the social culture of periods through the use of tweezers. Chapter II summarized the terms for tweezers and looked at the use of tweezers in two cases related to the social culture and politics of a period. The first is the use of tweezers for beauty purposes. Men used tweezers as a kind of self-management to maintain their social status and power, and thus they helped develop a wide range of tweezers cultures. People with gray hair are usually old. The perception that we should step down from politics when we are aged has become strong. Therefore, politicians pulled out gray hairs with tweezers to maintain only black hair and show youth, which indicates that their social influence is still strong. The second is the use of tweezers for first aid. Chapter III classified tweezers by type during the Goryeo and Joseon periods. The tweezers are largely divided into basic and composite types. The basic type of tweezers is a form that has been continued since the Three Kingdoms Period and consists of tongs and handles, and a fixed type of tweezers with a fixed ring appeared. Composite tweezers are made by grafting earpick or multipurpose knives. Composite tweezers are all-in-one tweezers with an earpick and an all-in-one knife. Tweezers are usually all-in-one. Among the composite tweezers, rivet separation and ring separation are characterized by separation, unlike the all-in-one tweezers. The method of connecting is divided into rivets and connection rings. The all-in-one tweezers appear only during the Goryeo Dynasty and are characterized by the lifestyle that provides a glimpse of the tastes of contemporary users. The manufacturing takes shape after making a thin metal plate. Decorative techniques are carved on soft metal tweezers, such as silver and bronze with a line, point, and a pressed angle. These tweezers are presumed to have been used by the royal family or aristocrats. However, most tweezers are made of strong bronze or iron. Therefore, the majority of simple X-shaped patterns are sampled or without patterns. The biggest reason why there are such diverse types of tweezers is that the culture of tweezers was widespread regardless of the times. In addition, the basic type of tweezers has been used since the Three Kingdoms Period and has been modified and used together as necessary because the shape of tweezers is a practical daily tool. Study of metal crafts have been limited to royal objects and Buddhist crafts. We hope that research on everyday tools such as tweezers will continue to serve as an opportunity to examine the social and cultural aspects of the times in various ways.

• MISULJARYO - National Museum of Korea Art Journal
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• v.97
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• pp.69-86
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• 2020

Haenghaeng Ilgi (Diary of a Royal Trip) (koo 7152; hereafter Ilgi) in the collection of the National Museum of Korea provides an account of Crown Prince Sado's incognito royal visit to Pyeongyang in the fourth month of 1761. Ilgi was written by Ham Daeil, a low-ranking military officer in Pyeongyang. Ham was singled out for praise by Crown Prince Sado (1735-1762) and served the prince from the seventh day of the fourth month to the first day of the fifth month. Ilgi documented the deeds of Crown Prince Sado during this period and provides detailed information on his incognito visit to Pyeongyang, which was not officially recorded. Ilgi shows characteristics differentiating it from many other diaries. For example, the quality of the paper, neat handwriting, and well-organized sentences differ from those of common diaries. These distinctions indicate that Ilgi is closer to an official document than a private diary written by an individual. Since Ilgi records Crown Prince Sado's incognito visit to Pyeongyang, is only vaguely known otherwise, its contents need to be examined in terms of whether or not they are fully factual. As the first step in such verification, It is traced that Ham Daeil's family history which turned out to match what is written in Ilgi. Moreover, Ilgi mentions about Prince Crown Sado's writing a piece of calligraphy, and a matching piece of calligraphy written by Sado still survives today. It can be confirmed that the contents of Ilgi are factual in at least these regards. However, although Crown Prince Sado was known to have met people from various social classes during his visit to Pyeongyang, Ilgi focuses only on Crown Prince Sado and Ham Daeil. This suggests the possibility that the surviving version of Ilgi may be an edited condensation based on original texts containing more complete information on Crown Prince Sado's visit. Ilgi is presumed to have been produced during the generation of Ham Jeonghui, a son of Ham Daeil. The dates of birth and death of Ham Daeil fall during the reign of King Yeongjo. It is unlikely that any records regarding Crown Prince Sado would have been published while King Yeongjo, who was hostile to Sado, ruled the country. Ilgi also provides strong evidence that Ham Jeonghui presented the subsequent king, King Jeongjo, with the calligraphy by Crown Prince Sado and the diary. It is unclear if the book Ham Jeonghui presented him was the same as the extant version of Ilgi. Nonetheless, considering the situation at the time when King Jeongjo was pursuing several projects to honor his father Sado, it is highly probable that Ilgi was produced during the reign of King Jeongjo. The periods of presenting the calligraphy and the diary respectively overlapped with the production of Hyeollyungwon, the royal tomb of Crown Prince Sado, and Sado's sixtieth birthday. Therefore, is it considered reasonable that Ham Jeonghui produced Ilgi to promote his own social ambitions.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.41-59
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• 2022

The timely procurement of military supplies is essential to maintain the military's operational capabilities, and contract work is the first step toward timely procurement. In addition, rapid signing of a contract enables consumers to set a leisurely delivery date and increases the possibility of budget execution, so it is essential to improve the contract process to prevent early execution of the budget and transfer or disuse. Recently, research using big data has been actively conducted in various fields, and process analysis using big data and process mining, an improvement technique, are also widely used in the private sector. However, the analysis of contract work in the military is limited to the level of individual analysis such as identifying the cause of each problem case of budget transfer and disuse contracts using the experience and fragmentary information of the person in charge. In order to improve the contract process, this study analyzed using the process mining technique with data on a total of 560 contract tasks directly contracted by the Department of Finance of the Air Force Logistics Command for about one year from November 2019. Process maps were derived by synthesizing distributed data, and process flow, execution time analysis, bottleneck analysis, and additional detailed analysis were conducted. As a result of the analysis, it was found that review/modification occurred repeatedly after request in a number of contracts. Repeated reviews/modifications have a significant impact on the delay in the number of days to complete the cost calculation, which has also been clearly revealed through bottleneck visualization. Review/modification occurs in more than 60% of the top 5 departments with many contract requests, and it usually occurs in the first half of the year when requests are concentrated, which means that a thorough review is required before requesting contracts from the required departments. In addition, the contract work of the Department of Finance was carried out in accordance with the procedures according to laws and regulations, but it was found that it was necessary to adjust the order of some tasks. This study is the first case of using process mining for the analysis of contract work in the military. Based on this, if further research is conducted to apply process mining to various tasks in the military, it is expected that the efficiency of various tasks can be derived.

• Journal of the Korean Electrochemical Society
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• v.26 no.1
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• pp.1-10
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• 2023

The cathode, which is one of the four major components of a lithium secondary battery, is an important component responsible for the energy density of the battery. The mixing process of active material, conductive material, and polymer binder is very essential in the commonly used wet manufacturing process of the cathode. However, in the case of mixing conditions of the cathode, since there is no systematic method, in most cases, differences in performance occur depending on the manufacturer. Therefore, LiMn₂O₄ (LMO) cathodes were prepared using a commonly used THINKY mixer and homogenizer to optimize the mixing method in the cathode slurry preparation step, and their characteristics were compared. Each mixing condition was performed at 2000 RPM and 7 min, and to determine only the difference in the mixing method during the manufacture of the cathode other experiment conditions (mixing time, material input order, etc.) were kept constant. Among the manufactured THINKY mixer LMO (TLMO) and homogenizer LMO (HLMO), HLMO has more uniform particle dispersion than TLMO, and thus shows higher adhesive strength. Also, the result of the electrochemical evaluation reveals that HLMO cathode showed improved performance with a more stable life cycle compared to TLMO. The initial discharge capacity retention rate of HLMO at 69 cycles was 88%, which is about 4.4 times higher than that of TLMO, and in the case of rate capability, HLMO exhibited a better capacity retention even at high C-rates of 10, 15, and 20 C and the capacity recovery at 1 C was higher than that of TLMO. It's postulated that the use of a homogenizer improves the characteristics of the slurry containing the active material, the conductive material, and the polymer binder creating an electrically conductive network formed by uniformly dispersing the conductive material suppressing its strong electrostatic properties thus avoiding aggregation. As a result, surface contact between the active material and the conductive material increases, electrons move more smoothly, changes in lattice volume during charging and discharging are more reversible and contact resistance between the active material and the conductive material is suppressed.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.5
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• pp.489-496
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• 1997

This study was carried out to develop and investigate integrated mechanization system on polyethylene(P.E.) film mulching culture in sesame. Field trials were carried out to develop optimum mechanics for each step of manual operation in sesame culture and demonstrated those developed mechanics of sesame dibbling vinyl mulcher, sesame binder, sesame thresher and sesame grader at the farmer, s field of Hwasong (Kyunggi-do) in 1994 and 1995. Newly developed sesame dibbling vinyl mulcher brought saving manpower 280 hrs /ha for sowing and P.E. film mulching with it's 98％ of labour saving for the harvesting operation of sesame. Sesame Binder showed 93％ labour saving for cutting and binding with only 22 hrs /ha compared to 330 hrs /ha that of conventional. Sesame thresher was appeared to have 85％ effects of labour saving for threshing with completely dry sesame bundles at one time by 23 hrs /ha compared to 151 hrs /ha that of conventional. Sesame grader was appeared to have 72％ effects for sesame grain grading with 12 hrs /ha compared to that of conventional 54 hrs /ha. Grain yield of integrated mechanization culture system showed 6％ higher than that of coventional. Integrated mechanization culture system (sesame dibbling vinyl mulcher ＋ sesame binder ＋ sesame thresher ＋ sasame grader) showed 62％ of labour saving effects through whole steps of sesame culture by 472 hrs /ha compared to that of conventional 1, 230 hrs /ha.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.1-17
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• 2023

With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.11
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• pp.471-480
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• 2023

The Korean construction order volume in South Korea grew significantly from 91.3 trillion won in public orders in 2013 to a total of 212 trillion won in 2021, particularly in the private sector. As the size of the domestic and overseas markets grew, the scale and complexity of EPC (Engineering, Procurement, Construction) projects increased, and risk management of project management and ITB (Invitation to Bid) documents became a critical issue. The time granted to actual construction companies in the bidding process following the EPC project award is not only limited, but also extremely challenging to review all the risk terms in the ITB document due to manpower and cost issues. Previous research attempted to categorize the risk terms in EPC contract documents and detect them based on AI, but there were limitations to practical use due to problems related to data, such as the limit of labeled data utilization and class imbalance. Therefore, this study aims to develop an AI model that can categorize the contract terms based on the FIDIC Yellow 2017(Federation Internationale Des Ingenieurs-Conseils Contract terms) standard in detail, rather than defining and classifying risk terms like previous research. A multi-text classification function is necessary because the contract terms that need to be reviewed in detail may vary depending on the scale and type of the project. To enhance the performance of the multi-text classification model, we developed the ELECTRA PLM (Pre-trained Language Model) capable of efficiently learning the context of text data from the pre-training stage, and conducted a four-step experiment to validate the performance of the model. As a result, the ensemble version of the self-developed ITB-ELECTRA model and Legal-BERT achieved the best performance with a weighted average F1-Score of 76% in the classification of 57 contract terms.

• Journal of Industrial Convergence
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• v.22 no.2
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• pp.73-83
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• 2024

The purpose of this study is to diagnose various problems arising around social enterprises in the sport field from the perspective of the organization and derive necessary tasks and implications. In order to achieve the purpose of the study, the study was largely divided into three stages, and the results were derived. First, the main status and characteristics of social enterprises in the sport field were examined. The current status was analyzed focusing on aspects such as background and origin, legislation and policy, organizational goals, organizational structure and procedures, and organizational characteristics. Social enterprises in the sport sector were in their early stages, and the government's social enterprise policy goal tended to focus on increasing the number of social enterprises in a short period of time through financial input. In addition, it was found that most individual companies rely on government subsidy support due to insufficient profit generation capacity. In the second stage, we focused on the situational factors that affect the functional performance of social enterprises in the sport field. As a result of reviewing the value, ideology, technology, and history of the organization, which are situational factors, it was derived that when certified as a social enterprise in the sport field and supported by the central government or local governments, political control is strong to some extent and exposure to the market is not severe. In the last third step, tasks and implications were derived to form an appropriate organization for social enterprises in the sport field. After the social enterprise ecosystem in the sport sector has been established to some extent, it is necessary to gradually move from the current "government-type" organization to the "national enterprise" organization. This is true in light of the government's limited financial level, not in the short term, but in order for the organization of social enterprises in the sports sector to survive in the long term.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.