Recently, steel dampers are widely used as seismic reinforcement devices. Steel dampers have the advantage of being easy to manufacture and being able to absorb a lot of energy through stable hysteresis behavior. However, there is a possibility that the steel damper may be damaged due to fatigue caused by repeated seismic loads. In this study, the seismic performance of steel dampers and engineering plastic dampers with different physical characteristics were compared and analyzed. In addition, numerical analysis was performed on a hybrid damper that combines a steel damper and an engineering plastic damper. It is more effective to apply engineering plastic dampers to structures that experience significant displacement due to seismic loads. The behavior of hybrid dampers combining steel dampers and engineering plastic dampers is dominated by steel dampers. A hybrid damper in which an engineering plastic damper yields after a steel damper yields can effectively respond to various seismic loads and secure high ductility and excellent seismic performance.

최근 인공지능 분야에서 가장 활발히 연구되고 있는 거대 언어 모델은 교육에 대한 응용 가능성을 보 이며, 교육학의 거의 모든 분야에서 그 활용 방안이 연구되고 있다. 이러한 연구는 공학 교육에서도 주목 받고 있다. 그러나 구체적인 활용 분야와 방법에 대해서는 아직 많은 연구가 필요한 상황이다. 특히, 거대 언어 모델을 이용한 교육과정 설계와 개선에 대한 연구는 인공지능 공학과 교육학 두 분야에서 모두 중요한 연구 과제로 부각되고 있다. 이러한 응용 필요성에 대한 예시이자 전략으로써, 본 연구는 OpenAI에서 발표한 최신 거대 언어 모델인 ChatGPT-4o를 이용하여 한국과학기술원(KAIST) 공과대학 학부 전공 과 목과 S전자 DS부문(반도체사업부) 직무 사이의 연관성을 분석하고, 그 결과를 기반으로 대학과 기업체 양측에 반도체 산업 인력 양성과 채용에 대한 실질적인 응용 전략을 제안한다. 이를 위해 KAIST 공과대 학 학부과정에 개설된 모든 전공 과목과 S전자 DS부문(반도체사업부)의 직무기술서를 ChatGPT-4o에 학습시켜 각 과목이 특정 제품군, 직무와 가지는 연관성을 특정 범위와 기준에 의거하여 정량화된 점수로 평가했다. 또한, 각각의 직무, 전공, 과목별로 확보한 데이터를 기초적인 통계 분석을 통해 평가했으며, 구직자와 구인자의 활용 가능성에 초점을 두고 특정 전공의 각 직무별 연관성과 특정 직무의 각 전공별 연관성, 그리고 특정 직무 및 전공의 반도체 제품군별 연관성 등 다양한 조건에서 분석을 진행하였다. 또 한 본 전략에 대한 반도체 산업 실무자 견해를 수집하여 실제 전략으로의 활용 가능성을 검증하였다. 분 석 결과, 간단한 질문과 분석만으로도 전공, 교과목별로 유의미한 직무 연관성의 차이를 확인했다. 이러한 결과를 바탕으로 본 연구는 대학 교육과정의 개선과 기업 채용 및 양성 과정에서의 응용 전략을 제시한 다. 이 연구는 대학과 산업 간의 협력을 통해 인적자원 개발과 채용 효율성 증대에 기여할 것으로 기대한 다. 또한, 후속 연구로 구직자와 구인자, 교수자 등 본 연구의 효과를 확인할 수 있는 집단을 대상으로 한 대규모 설문조사 및 전문가그룹 대상 질적연구 등을 제안하여 실제 활용도와의 비교 분석 연구를 제안 한다. 결론적으로, 본 연구는 거대 언어 모델을 활용하여 필요한 인재를 양성하기 위한 교육 과정 설계의 구체적인 응용 가능성을 제시함으로써, 인공지능을 이용한 교육 분야에 대한 기여 방안을 모색한다.

This study explores the perceptions of Chinese engineering-major students towards their English learning experience after taking a mandatory English composition course in an EMI college. The investigation centers on first-year students’ perceptions of transitioning to EMI, with a focus on how the composition course has assisted students’ transition as a primary language support. Data were collected through a metaphor elicitation technique in which students expressed their perceptions of English learning, complemented by a thematic analysis of 86 reflection essays on the composition class. An analysis of the 334 metaphors identified students’ enhanced confidence in English, the importance of the English-using environment, positive views of learning communities, and increased agency in the learning process. It also revealed that many students were stressed and unaware of learning strategies, therefore suggesting institutional-level language support. One implication is to promote the culture of the learning community. The findings can be particularly useful for programs that are implementing language support for non-English major students.

The advent of big data has brought about the need for analytics. Natural language processing (NLP), a field of big data, has received a lot of attention. Topic modeling among NLP is widely applied to identify key topics in various academic journals. The Korean Society of Industrial and Systems Engineering (KSIE) has published academic journals since 1978. To enhance its status, it is imperative to recognize the diversity of research domains. We have already discovered eight major research topics for papers published by KSIE from 1978 to 1999. As a follow-up study, we aim to identify major topics of research papers published in KSIE from 2000 to 2022. We performed topic modeling on 1,742 research papers during this period by using LDA and BERTopic which has recently attracted attention. BERTopic outperformed LDA by providing a set of coherent topic keywords that can effectively distinguish 36 topics found out this study. In terms of visualization techniques, pyLDAvis presented better two-dimensional scatter plots for the intertopic distance map than BERTopic. However, BERTopic provided much more diverse visualization methods to explore the relevance of 36 topics. BERTopic was also able to classify hot and cold topics by presenting ‘topic over time’ graphs that can identify topic trends over time.

Topic modeling has been receiving much attention in academic disciplines in recent years. Topic modeling is one of the applications in machine learning and natural language processing. It is a statistical modeling procedure to discover topics in the collection of documents. Recently, there have been many attempts to find out topics in diverse fields of academic research. Although the first Department of Industrial Engineering (I.E.) was established in Hanyang university in 1958, Korean Institute of Industrial Engineers (KIIE) which is truly the most academic society was first founded to contribute to research for I.E. and promote industrial techniques in 1974. Korean Society of Industrial and Systems Engineering (KSIE) was established four years later. However, the research topics for KSIE journal have not been deeply examined up until now. Using topic modeling algorithms, we cautiously aim to detect the research topics of KSIE journal for the first half of the society history, from 1978 to 1999. We made use of titles and abstracts in research papers to find out topics in KSIE journal by conducting four algorithms, LSA, HDP, LDA, and LDA Mallet. Topic analysis results obtained by the algorithms were compared. We tried to show the whole procedure of topic analysis in detail for further practical use in future. We employed visualization techniques by using analysis result obtained from LDA. As a result of thorough analysis of topic modeling, eight major research topics were discovered including Production/Logistics/Inventory, Reliability, Quality, Probability/Statistics, Management Engineering/Industry, Engineering Economy, Human Factor/Safety/Computer/Information Technology, and Heuristics/Optimization.

When evaluating effectiveness of a R&D program, there is a tendency to simply compare the performances of the beneficiaries before and after the program or to compare the differences in the performances of the beneficiaries and the non-beneficiaries before-after the program. However, these ways of evaluating effectiveness of a program have some problems because they can not differentiate between complement effect, which facilitates corporate R&D investment, and substitute effect, which, literally, substitutes corporate R&D investment. Therefore, these problems could bring about wrong policies concerning R&D programs.In this paper, a new approach using path analysis is suggested as a means to overcome these problems and it is utilized, as an application, to evaluate the effectiveness of Plant Engineering Program conducted by Ministry of Trade, Industry & Energy, Korea. First, the direct impact of government R&D investment on corporate R&D investment is analyzed, through which it is identified which of crowding-in effect (complement effect) and crowding-out effect (substitute effect) is dominant. Next, the direct effect of government R&D investment on corporate performance and the direct effect of corporate R&D investment on corporate performance is analyzed respectively. Finally, by combining the two previous analysis, the total effect of government R&D investment on corporate performance is identified.As a result, it turns out that, in Plant Engineering Program, crowding-in effect is more dominant than crowding-out effect and that Plant Engineering Program has definitely positive effect on the beneficiary in terms of corporate performance indirectly and directly.

This paper investigates seismic damage potential of recent September 12 M5.8 Gyeongju earthquake from diverse earthquake engineering perspectives using the accelerograms recorded at three stations near the epicenter. In time domain, strong motion durations are evaluated based on the accelerograms and compared with statistical averages of the ground motions with similar magnitude, epicentral distance and soil conditions, while Fourier analysis using FFT is performed to identify damaging frequency contents contained in the earthquake. Effective peak ground accelerations are evaluated from the calculated response spectra and compared with apparent peak ground accelerations and the design spectrum in KBC 2016. All these results are used to consistently explain the reason why most of seismic damage in the earthquake was concentrated on low-rise stiff buildings but not quite significant. In order to comparatively appraise the damage potential, the constant ductility spectrum constructed from the Gyeongju earthquake is compared with that of the well-known 1940 El Centro earthquake. Deconvolution analysis by using one accelerogram speculated to be recorded at a stiff soil site is also performed to estimate the soil profile conforming to the response spectrum characteristics. Finally, response history analysis for 39- and 61-story tall buildings is performed as a case study to explain significant building vibration felt on the upper floors of some tall buildings in Busan area during the Gyeongju earthquake. Seismic design and retrofit implications of M5.8 Gyeongju earthquake are summarized for further research efforts and improvements of relevant practice.

The vehicle weight and alternative light materials development like aluminum alloys are hot issues around the world. In order to obtain the goal of the weight reduction of automobiles, the researches about lighter and stronger suspension links have been studies without sacrificing the safety of automotive components. Therefore, in present study, the structure analysis of the torque strut links made by aluminum alloys (A356) was performed by using CAE (computer aided engineering) to investigate the light weight design process from the reference of the rear suspension torque strut link which was made by STKM11A steel and was already proven in the commercial market. Especially, the simulated maximum von Mises stresses after strength analysis were normalized as fatigue limit and these were converted to the WF (weight factor) of the same type as the fatigue safety factor suggested and named like that in present study. From these, it was suggested that the fatigue properties of the torque strut could be simply predicted only from this static CAE simulation.

용융염 전해정련공정은 사용후핵연료로부터 전기화학적인 방법을 통해 음극에서 우라늄을 회수 하는 공정이다. 이 때 우라 늄은 약 30wt%의 염을 포함하고 있어 순수한 우라늄을 얻기 위해서는 염을 제거하는 Cathode Process (CP)가 필수적이다. CP는 대량의 우라늄을 처리해야 하므로 파이로공정의 난관중의 하나로 인식되고 있으며, 우라늄의 순도가 최종적으로 결정 되는 단계이므로 매우 중요한 공정이다. 현재, 이에 대한 연구는 주로 실험적 방법에 근거 하고 있어 염 제거 공정 중 온도, 압력, 염 가스의 거동을 관찰하기 어렵다. 따라서 본 연구에서는, 공정의 운전 조건에 대해 적합한 수학적 모델을 이용하여 전산모사 해석을 진행하였다. 본 연구는 증류부에서 염 가스의 증류 량, 확산계수에 의해 계산된 장치 내 염 가스의 이동 그 리고 응축부에서의 응결속도를 중점적으로 연구하였다. 장치내의 각각의 염 가스 거동을 정의하기 위해 Hertz-Langmuir 관 계식, Chapman-Enskog Theory, ANSYS-CFX의 상용 코드를 사용하였다. 그리고 HSC Chemistry에서 염의 물성 값을 이용 하여 모델을 구성하였다. 본 연구의 전산모사 해석을 통해 얻은 연구 결과를 이용하여 염 가스의 거동과 장치의 최적 운전 조건을 예측하였다. 따라서 본 해석 결과는 CP의 물리적 현상을 깊게 이해하는데 쓰일 뿐 아니라, 공학규모의 CP 장치를 상 용규모로 확장하는데 이용 할 수 있다.

In order to investigate of technology competitiveness for domestic engineering enterprise, using the quantitative and objective patent. In these result, the technology competitiveness(Patent Activity Index, Patent Family Size Index, Patent Impact Index, Technology strength) of our enterprise is far inferior to another country. So we should try to achieve our superiority in competitive power, we devote ourself to put through technical improvements of our domestic engineering enterprise in many ways.

For the matter of elevator, one of the multi-use facilities for unspecified public, the JIS has re-established and reformed to apply to the environment in South Korea for the past 20 years. In the aspect of safety assurance, it was inevitable to suggest improved measures. The government, Ministry of Public Administration and Security has secured the safety by enhancing the safety management functions in the elevator inspection standards and expanding its safety device measures. Further, the international inspection standard has been introduced, which is about unifying inspection standard system into the international standard code. In March 14th 2012, the international standard (EN) has been amended and fully announced. Escalator and passenger conveyor among lift devices have several common danger factor that cause safety accident. First, the accident caused by decreased braking power of brake. Second, the accident caused by the rate difference between handrail and tread-board. Third, the accident caused by defects of contraflow preventing device or carelessness inspection. Fourth, the accident caused by wet tread-board or wet floor of platform which makes passenger slip and fall. As the improvements to prevent and reduce these negligent accidents, the inspection list to check and methods should be subdivided and applied for each accident likelihood cause for safety management enhancement and safety assurance of existing escalator and passenger conveyors. The escalators and passenger conveyors without safety devices in existence should be obliged to modify the part of the system or install additional safety device. With making these measures obligations, it requires to improve the system to be suitable for the international inspection standard and to have measures to prevent safety accidents. It also needs to arrange improvements for skid accident of tread-board by the external environment factors such as snow and rain.

The paper reviews the methodologies of confirmatory data analysis(CDA) and exploratory data analysis(EDA) in statistical quality control(SQC), design of experiment(DOE) and reliability engineering(RE). The study discusses the properties of flexibility, openness, resistance and reexpression for EDA.

This study was conducted to evaluate the menu of a Japanese restaurant in a first class tourism hotel. The calculations used for the menu analysis were conducted using MS Excel 2003. Several previous studies have been conducted to analyze menus. For example, Pavesic used of the weighted contribution margins (WCM) and potential food cost (PFC%) to evaluate menus, while Kasavana & Smith used the mix margin (MM%) and unit contribution margin (CM) to evaluate menus. The menu engineering method focused on the customer's viewpoints, while the Cost/Margin analysis method considered the manager's viewpoints. The menus that need continuous keeping Kasavana & Smith (Star) and Pavesic (Standard) included 'Assorted sashimi with side dishes (big), 'Lunch box special', 'Tempura course', 'Broiled Spanish mackerel and side dishes', 'Shrimp tempura', 'Special sushi', 'Seafood Udong', 'Buckwheat noodles'. The results of this study should increase customer satisfaction and profits at the Japanese Restaurant.

This study was designed to : (a) analyze the menus of the French restaurant in tourism hotel using the menu analysis techniques of Kasavana & Smith and Pavesic, (b) compare the characteristics of the two analysis techniques. The calculations for the menu analysis were done using the MS 2000 Excel spreadsheet program. The menu mix % and unit contribution margin were used as variables by Kasavana & Smith and weighted contribution margins (WCM) and potential food cost % (PFC%) by Pavesic. In two cases, a four-cell matrix was created and menu items were located in each according they achieved high or low scores with respect to two variables. The items that scored favorably on both variables were rated in the top category (e.g., star, prime) and those that scored below average on both were rated in the lowest category (e.g., dog, problem). While Kasavana & Smith's method focused on customer's viewpoints, Pavesic's method considered the manager's viewpoints. Therefore, it is more likely to be desirable for decision-making on menus if the menu analysis techniques chosen is suited to its purpose.

This research focuses on analyzing characteristics and needs of engineering students in an EFL context, which is designed as a preliminary study of content-based language instruction to develop NURI English model. For the purpose of this study, I conduct surveys and interviews on 147 engineering students to find out students’ needs and interests as well as 9 professors to recognize their notions of what language skills would benefit engineering students. The results of surveys and interviews strongly suggest the need to adopt a learner-centered level approach with which NURI English can incorporate communicative English for general and specific purposes in the field of engineering as well as TOEIC instruction. The results of this study also lead to an instructional parameter for NURI English program that requires for taking into account an instruction model of the integration of language and content for engineering students. The present study offers a few pedagogical implications for language educators who want to design a content-based language instruction model for engineering students in EFL contexts.