In this study, text mining was conducted on the product names of skirts, pants, shirts/ blouses, and dresses to analyze the characteristics of keywords appearing in online shopping product names. As a result of frequency analysis, the number of keywords that appeared 0.5% or more for each item was around 30, and the number of keywords that appeared 0.1% or more was around 150. The cumulative distribution rate of 150 terms was around 80%. Accordingly, information on 150 key terms was analyzed, from which item, clothing composition, and material information were the found to be the most important types of information (ranking in the top five of all items). In addition, fit and style information for skirts and pants and length information for skirts and dresses were also considered important information. Keywords representing clothing composition information were: banding, high waist, and split for skirts and pants; and V-neck, tie, long sleeves, and puff for shirts/blouses and dresses. It was possible to identify the current design characteristics preferred by consumers from this information. However, there were also problems with terminology that hindered the connection between sellers and consumers. The most common problems were the use of various terms with the same meaning and irregular use of Korean and English terms. However, as a result of using co-appearance frequency analysis, it can be interpreted that there is little intention for product exposure, so it is recommended to avoid it.

쇠고기 이력추적제는 소 개체마다 이력번호를 부여하여 수입쇠고기가 한우고기로 둔갑하는 사례를 막고, 소비자 에게 구입한 한우고기의 세부 이력 정보들을 제공하는 데 도움을 준다. 이번 연구는 2021년-2022년 서울지역 대형 축산물판매업소에서 유통되는 한우고기 344건에서 DNA 동일성 검사를 실시하여 이력번호 등 주요 표시정보들의 진위를 판별하였다. 그 결과 45건(13.1%)에서 이력번호가 불일치한 것으로 확인되었다. 불일치율은 2021년(14.7%) 에 비해 2022년(11.3%) 감소하였고, 도심서북권 20.7%, 동 북권 14.4%, 서남권 및 동남권 10.2% 순으로, 북부권 (16.9%)이 남부권(10.2%)에 비해 높게 나타났다. 또한 6개 브랜드 중 B사 및 D사는 이력관리가 양호한 반면, E사 및 A사는 이력관리가 취약한 것으로 확인되었고, 통계적 으로 유의한 결과 차이를 보였다(P<0.001). 이력번호 불일 치 시료의 실제 이력번호는 업소 내 입(출)고 거래내역 자 료를 근거로 조사하였고, 그 결과 실제 이력번호 확인율 은 53.9%에 불과하였으나, 확인된 범위 내에서 시료의 표 시정보 진위 판별 결과, 거짓 표시는 이력번호 13.1%, 성 별 2.9%, 도축장명 2.2%, 등급 1.6% 순으로 나타났고, 품종 (한우) 거짓 표시는 없었다. 거짓 표시 축산물의 유통 차 단을 위해 표시정보의 신속한 진위 판별이 중요하므로 업 소 내 이력번호가 기재된 날짜별 부분육 소분할 작업내역 작성을 의무화하는 법적 근거 마련이 필요하다. 본 연구 결과는 투명한 축산물 유통 거래 질서 정착을 위한 이력 관리 방향 설정에 참고자료로 활용하고자 한다.

본 연구는 중국 C2C 중고거래 플랫폼의 사용자 연구대상으 로 정보기술 수용과 사용 태도에 대해 설명력이 높다고 인정받 고 있는 기술수용모델(TAM)을 토대로 핵심 변수 외 다양화된 정보시스템 환경을 반영하는 변수로 주목받고 있는 지각된 유 희성을 추가 변수로 지정하였다. 본 연구는 가설을 검증하기 위해 중국 C2C 중고거래 플랫폼에 대한 경험 있는 사용자들을 대상으로 조사를 실시하였다. 총 400부의 설문지를 배포하였으 며 회수된 설문지를 선별하여 총 362부 유효 설문지가 선출되 었다. 또한, C2C 중고거래 플랫폼 특성 변인인 정보 대칭성을 규명하고, 이를 바탕으로 정보의 이용 가치를 높이고 활성하기 위한 전략 방향에 시사점을 제시하는 데 그 목적을 둔다. 그리 고 마케팅 연구의 학문적 발전에 기여하고 기업에는 중고 플랫 폼을 활용한 마케팅 전략 수립 시 실무적인 도움을 제공할 수 있을 것으로 기대한다.

In 2022, the Serious Accident Punishment Act was implemented, emphasizing the responsibility of managers at workplaces where serious accidents occur in order to reduce serious accidents that occur frequently throughout the industry and promote worker safety. Currently, it is applied only to workplaces with 50 or more workers, but from 2024, it will be applied to small businesses with fewer than 50 workers. Although these small-scale workplaces act as steppingstones in various fields, the rate of serious accidents is high due to the relatively poor environment and lack of human resources and financial capabilities. In this regard, we intend to examine effects of the Serious Accident Punishment Act on small-scale information and communication companies and to drive countermeasures.

Large-scale adoption of alternative agricultural practices is needed to manage farm productivity and resources under global changes. Ecosystem models are a tool for developing and evaluating potential solutions at management and policy scales. However, data collection and compilation often lack documentation that hinders model calibration and testing. The objectives of this study were to describe the current soil datasets and to combine soil property data from various sources that are sufficient to support the use of agricultural models under Korean conditions. Numerous sources provide soil data that describe the farm environment by land cover, such as rice and other field crops. The interquartile range of soil organic carbon was 9.10–14.50 g kg-1 across paddy and non-rice field systems. The results suggest that it is premature to perform site-specific simulations of farming systems due to no direct carbon accounting and hydrological conditions of the soil. Global gridded soil information, such as SoilGrids, may supplement the local data, especially soil organic carbon (the interquartile range of 23.43–36.92 g kg-1). However, the descriptive statistics of soil properties extracted from the datasets were not in agreement. Because the Korean agricultural land is characterized by small size (less than 1 ha) and family operation as a management unit, it is crucial to build datasets more representative of small-size farms and relevant to the new generation of models.

To efficiently manage the waste packages like drums, it is meaningful to utilize the data of placement and emplacement of disposed waste in geological storage. For the transparent and real-time management of disposal data, both technical as well as administrative factors must be included. To this end, MIRAE-EN Co., Ltd. has developed a radioactive waste tracking and management system (m-trekⓇ v1.0) through radioactive waste management life cycle which is supported by KETEP. Enhancing the functional features of m-trekⓇ, IoT-based drum location measuring and data of those drums, such as position, radionuclides, activity, and dose etc., are to be collected and monitored through data modeling and visualization, which might be utilized in emplacing the loaded drums according to specifically certain criteria of internal and external data of disposal site. Position measuring using Beacon utilizes Received Signal Strength Indicator (RSSI) to locate the correct position in 3D area. Since RSSI is affected by the surrounding environment, it is required to corrective optimization. In addition, error and deviation of previously applied Gaussian filter method, was corrected and improved through AI learning model. According to this location information and those data, the prototype in future provides the visualization of drum position and its relevant data for administrative purpose such as monitoring, emplacement and other management policy.

CYPRUS is a web-based waste disposal research comprehensive information management program developed by the Korea Atomic Energy Research Institute over three years from 2004. This program is stored as existing quality assurance documents and data, and the research results can be viewed at any time. In addition, it helps to perform all series of tasks related to the safety evaluation study of the repository in accordance with the quality assurance system. In the future, it is necessary to improve the user convenience by clarifying the relationship between FEP and scenarios and upgrading output functions such as visualization and automatic report generation. This purpose of this study is to research and develop the advanced program of CYPRUS. This study is based on building FEP, DIM and scenario databases. It is necessary to develop an algorithm to analyze and visualize the FEP, DIM and scenario relationship. This project is an integrated information processing platform for DB management and visualization considering user convenience. The first development goal is to build long-term evolutionary FEP, DIM, and scenarios as a database. The linkage by FEP item was designed in consideration of convenience by using a mixed delimiter of letters and numbers. This design provides information on detailed interactions and impacts between FEP items. Scenario data lists a series of events and characteristic change information for performance evaluation in chronological order. In addition, it includes information on FEP occurrence and mutual nutrition by period, and information on whether or not the repository performance is satisfied by item. The second development goal is to realize the relationship analysis and visualization function of FEP and scenario based on network analysis technique. Based on DIM, this function analyzes and visualizes interactions between FEPs in the same way as PID, RES, etc. In addition, this function analyzes FEP and DIM using network analysis technique and visualizes it as a diagram. The developed platform will be used to construct and visualize the FEP DB covering research results in various disposal research fields, to analyze and visualize the relationship between core FEP and scenarios, and finally to construct scenarios and calculation cases that are the evaluation target of the comprehensive performance evaluation model. In addition, it is expected to support the knowledge exchange of experts based on the FEP and scenario integrated information processing platform, and to utilize the platform itself as a part of the knowledge transfer system for knowledge preservation.

Numerous spent nuclear fuels are generated every year in Korea. To solve the spent nuclear fuel problem within saturated temporary storage, the authorities are readying to build an interim storage and a permanent disposal facility in the country. At the same time, the authorities are readying to establish a management procedure for spent nuclear fuel. In the future, the authorities need to make and apply the Database of spent nuclear fuel to practice the management procedure. However, the structure of a traditional database is not reasonable for information management because it has a problem with listing data and identifying data features due to its structure. In addition, the traditional database always exists human error from working in Excel program by a human. Therefore, this research proposes a new standard information management model based on Semantic Web technique. Semantic Web uses a data structure named ontology. By using the ontology in the information database of the spent nuclear fuel, users, such as institutions related to management, could more easily recognize and understand the Database. Furthermore, since this task proceeds in the ontology construction program, the human error in the new model reduces rather than an environment of the traditional database.

The spent fuel safety information delivered from the consignor to the disposal facility operator directly affects the operation and safety of the disposal facility. Therefore, the operator of a disposal facility must perform data quality management to increase data reliability, and anomaly detection is a representative method among quality control methods. We propose a quality control method to detect anomalies using XGBoost, known for its excellent performance, prevention of overfitting, and fast training speed. First, we select significant variables such as release burnup, enrichment, and amount U from the spent fuel safety information and train models for each variable using only normal data. A model trained using only normal data generates a small error for a normal pattern and a large error for an abnormal pattern. Then, when the data error exceeds a set threshold, the data is determined as an anomaly. In this paper, we implement the XGBoost models using virtual spent fuel information and optimize the hyperparameter of XGBoost using a simulated annealing method for high accuracy. The optimized XGBoost models show high accuracy in a normal input and provide a stable prediction value even in an abnormal input. In addition, we perform anomaly detection by including defect input in the data to validate the presented method. The proposed method shows the result of effectively classifying normal values and anomalies.

By Foreign Trade Act and the relevant laws, any organization which intends to export strategic items shall be classified whether the products, S/W, or technology are strategic items and obtain an export license from the Nuclear Safety and Security Commission (NSSC) in case those are nuclearrelated strategic items. The NSSC and KINAC conduct outreach activities to enhance the recognition and implementation of nuclear export and import control. However, ensuring that all target organizations identify and comply with relevant legislation and laws is difficult. Therefore, the government and regulators should continuously make efforts to reduce blind spots for nuclear export and import control. KINAC established the National Nuclear Technology Information Collection and Analysis System (NNTICAS) to find nuclear-related companies through online website information of various companies and to list organizations that handle nuclear-related strategic items. Based on the NICE corporate information website, NNTICAS finds related companies using dynamic collection methods through interactions such as search word input, search button input, check box click, and collected text from each company website using static collection methods through URL address access and HTML source code extraction. After that, the text contained on the company website is analyzed to check whether the predefined normalized word is included, and if the normalized word appears at a certain number or higher, it is judged as a potential target company dealing with nuclearrelated strategic items. Information on the potential target company is compared with the export controlled item list and finally classified as a target company dealing with nuclear-related strategic items. According to the comparison a manually analyzed result of potential target companies and finally selected target companies NNTICAS, it is confirmed that predefined normalized words need to be more detailed, and a controlled item list such as axes (0B001.b.2) needs to be additionally processed. In addition, if the collection is repeated without completing the previous classification of the collected corporate information, it is also possible to collect companies in cosmetics, semiconductors, and displays. Although it was confirmed that some supplementation is needed to use this system to select target companies for the outreach activity, it is also confirmed that target companies for outreach activity can be expanded through this system and is expected to increase the implementation rate and reduce the blind spot for nuclear export and import control.

Purpose: Researchers have shown that aesthetic judgments of artworks depend on contexts, such as the authenticity of an artwork (Newman & Bloom, 2011) and an artwork’s location of display (Kirk et al., 2009; Silveira et al., 2015). The present study aims to examine whether contextual information related to the creator, such as whether an artwork was created by a human or artificial intelligence (AI), influences viewers’ preference judgments of an artwork. Methods: Images of Impressionist landscape paintings were selected as human-made artworks. AI-made artwork stimuli were created using Google’s Deep Dream Generator by mimicking the Impressionist style via deep learning algorithms. Participants performed a preference rating task on each of the 108 artwork stimuli accompanied by one of the two creator labels. After this task, an art experience questionnaire (AEQ) was given to participants to examine whether individual differences in art experience influence their preference judgments. Results: Setting AEQ scores as a covariate in a two-way ANCOVA analysis, the stimuli with the human-made context were preferred over the stimuli with the AI-made context. Regarding the types of stimuli, the viewers preferred AI-made stimuli to human-made stimuli. There was no interaction effect between the two factors. Conclusion: These results suggest that preferences for visual artworks are influenced by the contextual information of the creator when the individual differences in art experience are controlled.

게임플레이는 플레이어가 게임과 상호작용을 진행하면서 게임 상황에 대한 판단과 행동의 일련의 과정의 반복이라고 볼 수 있다. 잘 설계된 게임플레이는 플레이어로 하여금 게임에 몰입하도록 유도하며, 지속적으 로 몰입상태를 유지할 수 있도록 한다. RPG에서 게임플레이의 핵심과정중 하나는 몬스터와 상호작용하는 것이다. 일반적인 RPG의 몬스터는 패턴플레이로 구성되어 반복적으로 플레이가 진행되는 상황에서 지루함 을 유발하는 요인으로 작용한다. 이로 인해 게임을 플레이하는 플레이어중 고 레벨 플레이어는 레벨업을 위 해 습득해야 하는 경험치의 양의 증가로 인해 같은 필드에서 같은 몬스터를 오랜 시간동안 플레이하는 것 이 일반적이어서 시간이 지날수록 투자한 시간과 성취욕구 사이에서 만족도가 떨어지는 문제점이 발생한다. 본 연구에서는 플레이어의 성장과정에서 몬스터가 제공하는 정보에 대한 위계의 설정을 통하여 플레이어의 인지과정에 패턴의 변수를 인식하게 하여 다양한 게임플레이가 가능하도록 하며 이를 바탕으로 플로우 (Flow) 과정에서 경험하는 지루함의 요소를 극복하고 지속적으로 몰입과정을 느낄 수 있도록 한다.