무형문화재 분야는 AI 스마트 음성 대화 기술 활용에 중요한 분야 중 하나이다. AI 스마트 음성 대화 기술은 무형문화재의 계승과 보호에 기 술 지원을 제공하며 무형문화재의 보급과 촉진을 위한 새로운 방법을 제 공한다. 본 연구는 통합기술수용모형2(UTAUT2)와 기술준비도(TRI) 모형 을 기반으로 의인성 인지, 관계성 인지 변수를 도입하여 무형문화재 앱 AI 스마트 음성 대화 이용자 사용에 영향을 미치는 행동의 요인 탐색을 목적으로 한다. 이를 통해 무형문화재의 보급, 전시를 위한 이론적 근거 와 실천적 지침을 제공한다. 본 연구는 무형문화재 AI 스마트 음성 대화 앱을 사용하는 이용자의 행동에 영향을 미치는 요인을 정량적 데이터 분 석 방법으로 탐색한다. 연구 결과에 따르면 높은 노력 기대, 성과 기대, 촉진 조건, 사회적 영향, 쾌락적 동기, 혁신성, 낙관성 및 관계성 인지가 이용자의 사용 의도에 유의한 정(+)의 영향을 미친다. 궁극적으로 이용자 의 사용 행동에 영향을 미칠 수 있음을 증명한다. 반면 높은 불편감, 불 안감, 의인성 인지는 이용자의 사용 의도에 유의한 부(-)의 영향을 미치 고 이용자의 사용 행동을 자극하는 데 도움이 되지 않음을 증명한다. 또 한, 가격 가치는 사용 의도와 사용 행동에 유의한 영향을 미치지 않는다.

계명대학교 인텔리전트건설시스템핵심지원센터(이하 INTEL센터)는 2020년 교육부 주관 핵심연구지 원센터 조성지원과제로 선정되어 현재 2단계 2차년도(5년차)를 진행하고 있습니다. INTEL센터는 사용 률이 낮고 노후화된 기존의 유휴 연구장비를 집적하여 성능을 보완하고, 다양한 분야 및 연구에 장비 및 전담인력을 지원하는 역할을 하고 있습니다. 또한 계명대학교 성서캠퍼스 내 첨단건설실험센터 및 사용성평가연구센터의 건설 및 IoT 분야의 첨단장비를 접목하여 대내외 연구원 및 산업계에 공동연구 및 장비활용을 할 수 있도록 서비스를 지원하고 있습니다. INTEL센터는 4차 산업혁명의 핵심기술인 IoT 분야를 구축 시스템에 융합하여 지능형 평가 시스템 구축을 목표로 하고 있습니다. 원격실험제어시스템 도입 및 인프라 구축을 통하여 실험의 실시간 협업 이 가능한 서비스를 제공하며, 디지털트윈 기반 3D 공간건설시스템을 구축하여 웹을 통한 시험시설환 경과 보유 장비들의 탐색이 가능한 서비스를 제공하고 있어 사용자 요구에 맞는 장비를 선택, 예약까 지 진행할 수 있는 One-Stop 서비스 제공이 가능합니다. INTEL센터가 갖춘 첨단화된 인프라와 IoT, 건설, 기계, 의용공학 등의 다양한 분야의 전문가들을 바탕으로 차세대 융복합 연구 및 연구지원을 이어가고 있으며, 혁신적인 연구 및 전문인력 양성을 통 해 연구장비 공동활용 및 산학연 공동연구에 기여하도록 노력하고 있습니다.

Intelligent machines (e.g., artificial intelligence, algorithms, and robotics) with the capability to make decisions autonomously either augment or substitute human employees due to rapid evolution in technology (Man Tang et al., 2022; Larivière, et al., 2017). Therefore, studies have shown that in consumer services, the role of intelligent machines falls into two categories: augmentation or substitution of human employees (McLeay et al., 2021; Larivière, et al., 2017). Specifically, human employee augmentation means that the role of intelligent machines is to assist and complement human employee, with the two used together to produce better outcomes (Larivière, et al., 2017). For example, in a retail bank in Japan, collaborative robots work side by side with bank employees to serve customers (Marinova et al., 2017); IBM’s Watson can assist doctors with diagnosis (Larivière, et al., 2017). Human employee substitution reflects the role of intelligent machines to replace human workers (McLeay et al., 2021). For example, restaurants such as Spyce, where robots are replacing human employees to take orders for customers (Wang et al., 2022). However, there are still a lot of unexplored aspects concerning consumers’ specific reactions toward this new form of a service provider. The study examines customers responses when human employees are augmented or substituted by intelligent machines, including responses that promote beneficial consumption (e.g., join a health program) and those that promote harmful consumption (e.g., pursue high return-risk offerings, enhance preferences for risk-taking behavior). In this article, we attempt to answer the following questions:

The preliminary study was conducted on the use of navigation instruments and programs conducted in the previous demonstration and experiment of the training ship SAEBADA, real-time sharing and accuracy of land and sea information, and the development of real-time effective information transmission and reception and management system programs. Based on this, this study used the training ship CHAMBADA, which is similar in length to the tonnage of the fishing boat. The purpose is to present errors in ship situation-specific information data, alarm systems for marine information, and land and ship transmission and reception programs collected using intelligent information management systems to find out whether they can be applied and used in fishing boats. It plans to conduct research on direct and indirect safety and ship’s stability when the intelligent information management system operates in real time in the operation of ships considering the characteristics of small fishing boats and the characteristics of fishing.

본 연구는 대학에서 미래 일자리 지형변화에 대응하고 신기술분야의 주요 직무를 성공적으로 수행하기 위한 핵심 직무역량 도출을 국내 K대학의 사례를 통해 제시하는데 그 목적이 있다. 이를 위해 신기술분야 로 지능형드론 및 UAM 신기술분야를 선정하고 지역산업 및 K대학 역량 분석 기반으로 핵심직무역량 도출하고자 신기술분야 사례분석-신산업 분야 직무 역량 정의-산업체 전문가 의견 수렴(FGI)-대학 교원 인터뷰 및 설문조사-산업현장성 검증 단계로 연구를 진행하였다. 주요 연구결과는 다음과 같다. 첫째, 신 기술분야의 문헌 및 자료분석을 통해 직무역량을 정의하고 산업 전문가 의견수렴을 통해 직무기초역량 11개, 직무기술역량 43개, 및 초직능적 기술역량 28개 후보군이 도출되었다. 둘째, 관련 대학 교원을 대상 으로 설문조사 결과, 총 7개의 직무기초역량, 9개의 직무기술역량, 8개의 초직능적 기술역량으로 직무역 량 모델을 구성하였다. 셋째, 도출된 직무역량을 토대로 지역 산업 현장 검증을 설문조사를 실시하였고 최종 선정을 위해 각 역량에 대한 Needs Weight를 산출하였다. 그 결과 직무기초역량으로 ‘직업적 윤리 의식, 창의적 사고, 혁신적 사고, 융합적사고, 미래지향적 사고’, 초직능적기술역량은 ‘문제인식 및 문제해 결력, 자기주도성, 탐구정신, 협동 및 기술협력, 의사소통’ , 직무기술역량은 ‘이동체 제어기술, 설계/제작/ 제어능력, 무선통신기술, 센서시스템 활용기술, ICT 기술이해 및 활용’ 등으로 규명되었다. 결과를 토대로 신기술분야의 핵심직무역량 도출을 위한 시사점과 연구의 한계점을 제시하였다.

The need for an intelligent information-based ship accident prevention and control system for various marine accidents is very clearly emerging. As it is a variety of marine accidents, the causes are diverse. Therefore, it can be said that it is very important to prevent these marine accidents and their causes in advance. Therefore, a study was conducted on an intelligent information-based ship safety management decision support system that provides information necessary for decision-making at sea and land through an integrated management device for ships that informs safety-related risks in real-time ship operation. In the future, we intend to pursue the development of a system that can aim for safer and more economical ship operation by linking it to navigation instruments through the evaluation and analysis of AI, IoT, and big data.

Maritime navigation is an important mode of transportation in the country. With the development of the country and the world, there will inevitably be higher requirements for the safe transportation of ships in the future. Therefore, intelligent ships have become the latest research direction in ship design. And with the gradual development and improvement of big data and artificial intelligence technology in the industrial field, smart ships are an inevitable trend in the development of the shipbuilding industry. Smart ships need to maintain the stability of the ship to ensure the safety of the ship when operating at sea. Therefore, the research on the autonomous stowage of ballast water for smart ships in the future is very important. This paper analyzes the development background of intelligent ships, introduces the ship optimization model and optimization design algorithm, and speculates the future development direction of intelligent ships.

The Korean Ritual Studies Series is a compilation of the works about Korean ritual studies, which makes a great contribution to scholarship in this area. Relying on a number of major national programs in China and South Korea, digital collation and research the Korean Ritual Studies Series was made to create into a “literature database of Korean ritual studies” by cooperation between the Center for the Study and Application of Chinese Characters (CSACC) of East China Normal University (ECNU) which is a key research institute of humanities and social science approved by the Ministry of Education of the People’s Republic of China, and the research institutions of Kyungsung University including the Center for the Study of Chinese Characters in Korea, the Research Society of Korean Ritual Studies and the Academy of Korean Studies. The basic framework of the database contains six sub-databases, which are fully correlated with each other according to relevant attributes. The database provides search capability, with three search functions, including catalog index, full-text retrieval and a word index. It is a major achievement of an international cooperation program supported by a multilevel international platform. It provides a large sustainable development space for the “literature database of Korean ritual studies”, which is an indispensable and important part of the “public database of Chinese characters” created by the Center for the Study and Application of Chinese Characters (CSACC) of East China Normal University (ECNU). The three key breakthroughs are needed for its further development: (I) Achieving the data association, comparative research and web publishing of Chinese and Korean ritual literature, establishing an Asian big data ritual research and application platform, supporting the research of Chinese and Korean ritual cultures, the communication history of ritual culture, the development history of Chinese characters and the research of many other disciplines, and meeting the multi-functional needs of ritual research, teaching and communication while completing a comprehensive digital connection of the internal resources of the database. (II) Deeply tapping into the massive Chinese character writing and memory data to create a 21st century database for written texts in the Sinosphere on the basis of digital processing and research of Korean ritual literature. (III) Realizing the multidimensional intelligent automatic recognition and interpretation of original literature written and memorized in Chinese characters such as ancient Chinese and Korean ritual literature, family mottoes and letters of noble families and great clans as well as folk handcopied books, and opening a new era of intelligent interpretation and research of the written texts in the Sinosphere through image recognition technology.

There are a lot of problems in the existing databases of ancient characters, such as the digital processing obstacles of Gaiji (characters excluded in character sets), the defects of information technology, and a lack of completeness. The newly released “digital resource library for intelligent Internet search of ancient characters” makes the following breakthrough: it achieves full coverage of all types of ancient characters in all dynasties, and realizes the carrier conversion of character data with strict digital standards, allows the the further processing of materials and the intelligent recognition search technology, and forms the series of thematic databases. There are two major tasks for the future development of the digital resource library of Chinese characters: the development of international standards for ancient character sets, and the further processing and sorting of ancient character materials for the intelligent research of ancient characters.

Through the process of chemical vapor deposition, Tungsten Hexafluoride (WF6) is widely used by the semiconductor industry to form tungsten films. Tungsten Hexafluoride (WF6) is produced through manufacturing processes such as pulverization, wet smelting, calcination and reduction of tungsten ores. The manufacturing process of Tungsten Hexafluoride (WF6) is required thorough quality control to improve productivity. In this paper, a real-time detection system for oxidation defects that occur in the manufacturing process of Tungsten Hexafluoride (WF6) is proposed. The proposed system is implemented by applying YOLOv5 based on Convolutional Neural Network (CNN); it is expected to enable more stable management than existing management, which relies on skilled workers. The implementation method of the proposed system and the results of performance comparison are presented to prove the feasibility of the method for improving the efficiency of the WF6 manufacturing process in this paper. The proposed system applying YOLOv5s, which is the most suitable material in the actual production environment, demonstrates high accuracy (mAP@0.5 99.4 %) and real-time detection speed (FPS 46).