방대한 빅데이터를 기반으로 발전한 인공지능 기술은 창작과 영상 예술, 인간의 고유 영역으로 여겨졌던 분야에 큰 영향을 미치기 시작했다. 전통적으로 선형적이었던 3D 애니메이션 제작 방식은 AI 이미지 생성 모델을 활용해 초기 기획, 컨셉 및 아이디어를 빠르게 비주얼화하고, 실시간 게임 엔진을 통해 실시간으로 수정 및 개선 작업을 반복하며 완성도를 높이는 비선형 적 방식으로 변화하고 있다. 본 논문에서는 Stable Diffusion의 노드 기반 비주얼 스크립트인 ComfyUI를 활용한 사전 제작 과정과 iClone 및 언리얼 엔진을 통해 디지털 휴먼을 제작하고 구체화하는 일련의 파이프라인을 분석한다. 이를 통해 전통적인 파이프라인을 넘어서는 새로운 예술적 표현의 가능성을 모색한다.

This study aimed to develop a new convergence course applying project-based learning (PBL) and collaborative teaching methods and identify its educational effects. The course development proceeded as follows: First, three instructors collaborated to define course goals, plan objectives, content, and methods, and create a syllabus for a PBL-based fashion studio course. Roles were divided to maximize expertise: one instructor focused on fashion design, another on three-dimensional cutting, and the third on flat cutting, and digital techniques. Second, the classes were conducted and feedback on student progress was shared, enhancing class quality and engagement. Third, teaching effectiveness was assessed through learner evaluation questionnaires, reflection journals, and performance assessments. Lastly, based on the results from these evaluations, positive aspects of the course were reviewed, and ways to modify it and enhance course quality for continuous improvement were explored. The results showed high satisfaction with the learning effects on major competencies, indicating that students not only effectively learned major skills but also improved their communication and teamwork. The students perceived the teaching methods positively allowing them to be more active in class. Instructors noted that the course produced higher-quality design and production outcomes compared to previous courses. Overall, the course applying PBL and collaborative teaching methods was found to improve educational quality and effectiveness, making it a valuable approach for learnercentered education.

The 4th Industrial Revolution and the continuous development of Science and Technology have also required a speedy business promotion method in the defense industry. Advanced countries including the United States are already boldly innovating the existing high-cost and long-term acquisition system with the highest priority in weapons development to cope with the military rise of Russia and China. The Ministry of National Defense and the Defense Acquisition Program Administration have also recently introduced a quick acquisition system and are applying it to business promotion. In addition, some small-scale projects and weapons systems are being reorganized so that they can be managed by the units demanding them. After an organizational diagnosis of the Project Acquisition Group by the Ministry of National Defense in 2020, it has been reassigned as a subordinate unit of the Army Logistics Command from a direct unit managed by the Army HQ. As a result, problems such as work conflict or redundancy have been identified. In addition, a system has been implemented to shorten the acquisition period by applying a rapid acquisition program in the field of weapons systems by benchmarking the rapid acquisition program of advanced countries. The force support system project process will also need to introduce such a quick acquisition system. In addition, the Ministry of National Defense is considering ways to delegate some weapon systems to each military, which will then carry out tasks ranging from requirements determination to project management. Accordingly, it is now time to expand the organization for the management of the Army's weapons system acquisition project. Therefore, in this paper, the Army Project Acquisition Group was analyzed on its organization, acquisition procedures, and cooperation systems, with presentations of development plans for each field.

최근 디지털 의상으로 제품을 만드는 것이 활성화됨에 따라서 삼차원 공간의 컴퓨터 그래픽을 이용하는 게 임엔진을 및 3D Tool로 샘플을 만들기 시작했다. 이러한 트렌드에 따라서 밴드 기업들은 디지털 의류 모델 을 화상 회의 프로그램을 이용하여 협업하기 시작했다. 하지만 화상 회의에서의 원격화면 공유 기능은 각 공유자의 바탕화면 혹은 각 사용자가 사용하고 있는 데스크탑에 보여지는 화면만을 공유하여 발표화면을 보여주는 기능에 그치고 있어 협업작업에서 필요한 사용자 간의 상호작용을 지원하기에는 부족한 점이 있 다. 본 연구에서는 디지털 의상 협업 작업 시 화상 회의를 사용함에 있어서 불편한 점들을 개선하고 회의를 효율적으로 진행하기 위한 Framework를 제작했다. 프레임워크 제작을 위해 Unity3D 게임엔진과 WebRTC 그 리고 Javascript를 사용하였으며, 중계서버 제작을 위하여 클라우드 AWS 서비스를 사용했다. 시연 결과 화상 회의 참여자들은 스크린에 인터랙션을 할 수 있었으며 따로 프로그램을 설치할 필요가 없었다. 그리고 최대 해상도를 1440p까지 높여 기존의 화상 회의에서의 화질을 더 개선할 수 있었다. 해당 시연 결과를 통하여 기존의 다른 화상 회의 앱과 기능들을 비교하여 제안한 Framework의 효용성을 검증했다.

This study reports the results of an open-ended questionnaire on the experiences of Korean university students who worked on task-based L2 bimodal collaborative writing enhanced by technology. Thirty-six English major students developed a reading text for 2nd-grade middle school students. Using Microsoft TEAMS as the main platform, participants conducted the collaborative writing task using real-time video conferencing, chatting, commenting, file and image posting, and (a)synchronous feedback/revision functions. Participants 1) used multiple tools to maximize their functions, 2) interacted collaboratively in every writing stage to achieve success, and 3) evaluated the quality of collaborative writing more highly than individual writing and perceived the positive impacts of collaborative writing on L2 writing in audience awareness, paraphrasing technique, and linguistic expressions. The levels of visual editing skills and awareness of online image copyright among students varied.

Laboratory testing to simulate the drying of spent fuel is most often done using a cooling rate of approximately 5°C per hour because there are so many restricted test conditions like R&D project duration limit, budget and temporary electronic supply blackout at laboratory building. However, in a real dry cask storage system, the fuel cools much slower. Early data from KAERI on unirradiated, pre-hydrided cladding has shown that slower cooling may result in more brittle behavior than is currently observed based on these short-term tests. Given the potential safety and future handling implications of failed fuel, it is important to determine if the material properties of spent fuel cladding measured in these laboratory tests are the same as would be observed on fuel that has undergone a much longer, slower cooling, which may provide more time for hydrides to precipitate in the radial direction. KAERI and PNNL have started a collaborative I-NERI R&D project on this topic and each organization will perform tests on unirradiated & irradiated cladding under various hoop stress and cooling rate combinations. Scope of collaborative work is to evaluate long-term cooling (slow cooling rate) on hydride reorientation and subsequent material properties of cladding to determine if past and current research activities on spent nuclear fuel are bounding. The results will be used to direct future testing and help predict cladding performance over a wide range of burnups during extended storage and transportation.

종래의 게임에서, 널리 사용되고 있는 난수는 게임 서비스 제공자에 의하여 일방적으로 제공되기 때문에, 게 임 이용자가 제공받은 난수가 어떠한 개입이나 조작이 있었는지를 검증하는 것은 어렵다. 본 논문은 상호 참 여형 난수 발생기인 TogetheRand를 제안한다. 제안된 방법은 이더리움 블록체인 시스템 위에서 작동되는 스 마트 컨트랙트이다. 제안된 방법의 난수성을 Dieharder tests를 이용하여 테스트하였다. 제안된 방법은 많은 사람들이 난수 생성에 참여할 수 있고, 모든 입력값을 확인할 수 있으며, 블록체인 시스템으로 인하여 정상 작동 여부가 보장되기 때문에 게임 이용자와 제공자 모두가 신뢰할 수 있는 방법이다. 제안된 방법은 게임 등의 신뢰성 있는 난수가 필요한 응용 분야에서 두루 적용될 수 있을 것이다. 본 논문에서 사용된 코드는 ht tps://github.com/TyeolRik/TogetheRand 에 공개되어 있다.

In this paper, we propose a method for diagnosing overload and working load of collaborative robots through performance analysis of machine learning algorithms. To this end, an experiment was conducted to perform pick & place operation while changing the payload weight of a cooperative robot with a payload capacity of 10 kg. In this experiment, motor torque, position, and speed data generated from the robot controller were collected, and as a result of t-test and f-test, different characteristics were found for each weight based on a payload of 10 kg. In addition, to predict overload and working load from the collected data, machine learning algorithms such as Neural Network, Decision Tree, Random Forest, and Gradient Boosting models were used for experiments. As a result of the experiment, the neural network with more than 99.6% of explanatory power showed the best performance in prediction and classification. The practical contribution of the proposed study is that it suggests a method to collect data required for analysis from the robot without attaching additional sensors to the collaborative robot and the usefulness of a machine learning algorithm for diagnosing robot overload and working load.

Sales force automation tools can increasingly be used collaboratively across the company borders. We have focused on this topical issue by conducting a multiple-case study of industrial manufacturers and their distributors. The main contribution of the research is a model that distinguishes the drivers and challenges of the collaborative tools.

최근 리더의 유머행동과 조직의 다양성 풍토는 조직행동 분야의 주요한 이슈로 떠오르고 있다. 이는 이 2가지가 현재의 한국 사회의 분위기나 한국 기업의 조직문화와는 상당한 거리감이 있기 때문일 것이다. 이러한 점에 착안하여 본 연구는 리더의 유머행동과 조직의 다양성 풍토가 구성원의 협력적 갈등해결이라는 기업 조직의 중요한 성과 요소에 영향을 미치는지, 그리고 이 관계를 부정적 정서조절이라는 정서적 요소가 매개하는지 검증하고자 하였다. 한국의 근로자를 대상으로 해서 수집한 242명의 데이터를 바탕으로 신뢰성, 타당성 검증을 실시하였으며, 구조방정식을 이용하여 가설을 검증하였다. 그 결과 리더의 유머행동과 조직의 다양성 풍토 모두 구성원의 협력적 갈등해결에 유의한 정(+)의 영향을 미치는 것으로 나타났다. 이와 더불어 부정적 정서조절은 상사의 유머행동과 구성원의 협력적 갈등해결, 조직의 다양성 풍토와 구성원의 협력적 갈등해결의 관계를 모두 매개하는 것으로 나타났다.

Collaborative apparel consumption is proposed as more sustainable alternative to conven-tional consumption. The purpose of this study is the exploration of consumers’ motives to participate in collaborative apparel consumption. Findings suggest that consumers’ inten-tion to participate in collaborative apparel consumption is mainly influenced by financial benefits, convenience and sustainability awareness.

This study explores how the shared reflections of two university instructors influenced their approaches and perspectives of English language teaching. The primary source of data was derived from the two teachers’ e-mail mediated, collaborative reflective journals and two dialogical interviews served as a secondary data source. A qualitative, narrative inquiry approach was employed to gather data in a direct and in-depth way. The data were selectively coded to investigate the teacher’s reported beliefs, behaviors, and interactions as well as how they relate to the process of professional development. The findings indicate that the process of sharing and reflecting upon their pedagogical philosophy and strategies supported their ongoing efforts to develop professionally. Moreover, this study addresses the notion that more attention should be paid towards improving reflective teaching among teachers as a means of enhancing professional development.

The number of individuals using peer-to-peer and access-based services through collaborative consumption platforms (CCP) has been grown dramatically for a few reasons. CCP makes consumers convenient because it enables individuals trade directly without contacting each other. Thus, CCP, a digital platform, encourages more consumers to use access-based. CCP is temporal access-based service to a good. A good is usually accessed and traded in the absence of a service provider representative through CCP, and thus, misbehavior can occur and then be diffused into other consumers. Most of CCPs are based on digital platform, which provides participants with space where they can trade. Because the interactions in CCP is usually non-face to face communication and the participants tend to have similar interests and chat with task-oriented and low socio-emotional content, they can feel submerged in a crowd and indistinguishable from others. That is, participants feel like the sense of deindividuation which means to lose all sense of individuality. When participants face misbehavior of multiple previous customers, such deindividuation makes them conform social norm that they think that others do misbehavior as well. Based on social identity theory and deindividuation, this research examines the mediating effect of deindividuation on the relationship between previous misbehavior and misbehavior and the moderating effect of the self-disclosure on the relationship between previous misbehavior and deindividuation.

본 연구의 목적은 전문가와 교사의 협력적 실행연구를 통해 유아교육현장에서 만나게 되는 유아의 정서조절과 관련된 행동문제에 대한 유아교사의 인식 및 지도가 어떻게 변화되었는지를 알아보는 것이다. 이를 위해 본 연구는 D광역시에 위치한 유치원의 만 3세반 교실에서 약 3개월 동안 진행되었으며 유아교육과 현직교수 2인과 유치원 교사 3인이 참여하였다. 협력적 실행연구의 순환과정을 통해 나타난 유아교사의 변화를 파악하기 위해 교사들이 작성한 유아관찰 기록지, 교사저널, 연구일지와 교실관찰, 전화통화 및 이메일 교신, 면담내용의 자료를 근거이론의 절차방법을 통해 분석하였다. 연구결과, 유아교사들은 협력적 실행연구에 참여하면서 정서조절 행동문제는 유아가 정서적인 어려움을 호소하는 메시지이고, 유아가 처한 환경적 맥락에서의 어려움을 반영하며, 행동문제를 하는 유아가 곧 문제유아를 의미하는 것은 아님을 인식하게 되었다. 다음으로 협력적 실행연구에 참여한 유아교사들은 정서조절 행동문제에 대한 자신의 지도실제를 반성적인 사고를 통해 살펴보기 시작했으며, 다양한 방법으로 관찰하고 객관적으로 분석하게 되었다. 또한 정서조절 행동문제를 지도하기 위하여 유아에게 관심을 가지고 믿고 이해하고 존중하기 시작했으며, 유아에게 가장 적합한 방법을 찾아 적용하였고, 정서조절 행동문제를 지도하는 과정에서 부모 및 동료교사들과 협력하였다.

Collaborative filtering, one of the most widely used techniques to build recommender systems, is based on the idea that users with similar preferences can help one another find useful items. Credit card user behavior analytics show that most customers hold three or less credit cards without duplicates. This behavior is one of the most influential factors to data sparsity. The ‘cold-start’ problem caused by data sparsity prevents recommender system from providing recommendation properly in the personalized credit card recommendation scenario. We propose a personalized credit card recommender system to address the cold-start problem, using multiple user profiles. The proposed system consists of a training process and an application process using five user profiles. In the training process, the five user profiles are transformed to five user networks based on the cosine similarity, and an integrated user network is derived by weighted sum of each user network. The application process selects k-nearest neighbors (users) from the integrated user network derived in the training process, and recommends three of the most frequently used credit card by the k-nearest neighbors. In order to demonstrate the performance of the proposed system, we conducted experiments with real credit card user data and calculated the F1 Values. The F1 value of the proposed system was compared with that of the existing recommendation techniques. The results show that the proposed system provides better recommendation than the existing techniques. This paper not only contributes to solving the cold start problem that may occur in the personalized credit card recommendation scenario, but also is expected for financial companies to improve customer satisfactions and increase corporate profits by providing recommendation properly.