• Journal of Welding and Joining
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• v.34 no.4
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• pp.62-66
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• 2016

The trend of the fabrication technology of high strength, high toughness aluminum alloys by the severe plastic deformation(SPD) process and the welding technology of lightweight alloys in the automobile has been studied. The lightweight aluminum alloys can reduce vehicle weight, while stringently demanding the high quality and efficient welding techniques, to produce the best weldments. Among the production technologies, welding plays an important role in the fabrication of lightweight vehicle structure. This paper covers the scientometric analysis of the severe plastic deformations of lightweight alloys and the welding technology in the automobile which are based on the published research works in the 'HPT, ECAP and rolling', and 'welding technology of the automobile' obtained from Web of Science, and deals with the details of the background data of the HPT, ECAP, and rolling of lightweight alloys, and welding technology of the automobile technology.

• Proceedings of the KSR Conference
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• 2009.05b
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• pp.233-237
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• 2009

In this study, we suggest that several approaches to evaluate the collision acceleration value of a car in the article 35 and the guideline 16 of Korean rolling stock safety regulation. There are various methods to evaluate collision acceleration such as; a displacement comparison method by the double integration of filtered acceleration data, a velocity comparison method by the integration of filtered acceleration data, an analysis method of time-velocity curve, or a differential method of time-velocity curve. We compared these methods one another using 1D dynamic simulation model composed of nonlinear dampers, springs and bars, and masses. Also, we applied these methods to a hybrid model, which is made of 3D shell element model and 2D collision dynamics model, in order to evaluate whether 1D force-displacement curve modeling for energy absorbing structures have an effect on the collision acceleration levels or not.

• Annual Conference of KIPS
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• 2012.11a
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• pp.1587-1590
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• 2012

인터넷의 활용이 보편화 됨에 따라 정보의 양은 급격히 늘어나고 있다. 이에 취업을 희망하는 구직자의 경우 IR 로부터 원하는 정보를 검색하기 위해 과거보다 더 많은 시간과 노력이 필요하게 되었다. 이에 본 논문에서는 TF(Term Frequency)기법을 통해 문서를 추출하고 추출된 문서의 Doc_ID 빈도수를 기준으로 한 내용기반과 군집기법을 혼합한 하이브리드 검색 시스템을 제안한다. 구직자들이 클릭한 취업정보들의 링크번호들을 K-means 알고리즘을 이용하여 군집화를 한다. 생성된 군집들은 각기 하나의 문서로 가정하고, 기존 문서과 더불어 검색 주제와 연관성을 갖고 있는 문서들을 동적비율로 검색 랭킹 하는 방식이다. 기존의 IR 기술과의 비교 실험을 통해 성능을 평가하였다. 실험결과 본 논문에서 제안한 방법이 기존의 방법보다 우수함을 확인할 수 있었다

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.911-917
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• 2021

As software gets an increasing amount of patches, lots of software bugs are increasingly caused by such software patches, collectively known as regression bugs. To proactively detect the regressions bugs, both industry and academia are actively searching for a way to augment fuzz testing, one of the most popular automatic bug detection techniques. In this paper, we investigate the status quo of the studies on augmenting fuzz testing for regression bug detection and, based on the limitations of current proposals, provide an outlook of the relevant research.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.63-69
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• 2019

Recently, ultra-low latency flash storage devices such as Z-SSD and Optane SSD were introduced with the significant technological improvement in the storage devices which provide much faster response time than today's other NVMe SSDs. With such ultra-low latency, $10{\mu}s$, storage devices the cost of context switch could be an overhead during interrupt-driven I/O completion process. As an interrupt-driven I/O completion process could bring an interrupt handling overhead, polling or hybrid-polling for the I/O completion is known to perform better. In this paper, we analyze tail latency problem in a polling process caused by process scheduling in data center environment where multiple applications run simultaneously under one system and we introduce our adaptive polling selection technique which dynamically selects efficient processing method between two techniques according to the system's conditions.

• Annual Conference of KIPS
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• 2004.05a
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• pp.165-168
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• 2004

기존 장면 전환 검출 방법들은 대부분 특정 영역에 제한되어 사용할 수 있는 방법들이며, 많은 중요한 특징 정보들을 유실하여 장면 전환 검출에 효율적이지 못하였다. 또한 장면 전환 검출을 통하여 의미 정보를 추출하기가 어렵고, 카메라와 객체의 동작을 정확히 인식하지 못하기 때문에 하이브리드 장면전환 검출 기법을 적용하여 의미 있는 정보를 효율적으로 검출 하였다.

• Steel and Composite Structures
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• v.45 no.6
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• pp.877-894
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• 2022

Geopolymer concrete (GPC) has emerged as a feasible choice for construction materials as a result of the environmental issues associated with the production of cement. The findings of this study contribute to the development of machine learning methods for estimating the properties of eco-friendly concrete to help reduce CO₂ emissions in the construction industry. The compressive strength (f_c) of GPC is predicted using artificial intelligence approaches in the present study when ground granulated blast-furnace slag (GGBS) is substituted with natural zeolite (NZ), silica fume (SF), and varying NaOH concentrations. For this purpose, two machine learning methods multi-layer perceptron (MLP) and radial basis function (RBF) were considered and hybridized with arithmetic optimization algorithm (AOA), and grey wolf optimization algorithm (GWO). According to the results, all methods performed very well in predicting the f_c of GPC. The proposed AOA - MLP might be identified as the outperformed framework, although other methodologies (AOA - RBF, GWO - RBF, and GWO - MLP) were also reliable in the fc of GPC forecasting process.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.116-122
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• 2023

Sentiment categorization technique be commonly isolated interested in threes significant classifications name Machine Learning Procedure (ML), Lexicon Based Method (LB) also finally, the Hybrid Method. In Machine Learning Methods (ML) utilizes phonetic highlights with apply notable ML algorithm. In this paper, in classification and identification be complete base under in optimizations technique called sequential minimal optimization with Random Forest algorithm (SMORF) for expanding the exhibition and proficiency of sentiment classification framework. The three existing classification algorithms are compared with proposed SMORF algorithm. Imitation result within experiential structure is Precisions (P), recalls (R), F-measures (F) and accuracy metric. The proposed sequential minimal optimization with Random Forest (SMORF) provides the great accuracy.

• Annual Conference of KIPS
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• 2008.05a
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• pp.1061-1064
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• 2008

SMC로 불리는 안전한 다자간 계산 프로토콜은 이론적으로 완벽한 프라이버시 보호 기능 및 데이터 정확성을 가지고 있지만 현재의 컴퓨팅 환경에서는 구현이 불가능할 정도로 비효율적이다. 매우 효율적이어서 실용화 되어 있는 랜덤화 기법은 상대적으로 낮은 수준의 프라이버시 보호 기능을 지니고 있다. 최근 SMC와 랜덤화 기법을 적절히 혼합한 형태의 프라이버시 보호 기술이 Teng-Du(2007)에 의해서 제안되었다. 본 논문에서 우리는 Teng-Du의 기법을 면밀히 분석하여 새롭게 구현한 연구 결과를 제시한다. SMC 기술로는 Vaidya-Clifton의 스칼라곱 프로토콜을 채택하고, Agrawal-Jayant-Haritsa가 제안한 랜덤대치 기법을 랜덤화 기술로 선택하여 복합적으로 사용한 프라이버시 보호 기법을 제안한다.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3787-3800
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• 2023

Reactivity Initiated Accident (RIA) scenarios require special attention using advanced simulation techniques due to their complexity and importance for nuclear power plant (NPP) safety. While the conservative approach has traditionally been used for safety analysis, it may lead to unrealistic results which calls for the use of best estimate plus uncertainty (BEPU) approach, especially with the current advances in computational power which makes the BEPU analysis feasible. In this work an Uncontrolled Control Element Assembly (CEA) Withdrawal at Full Power accident scenario is analyzed using the BEPU approach by loosely coupling the thermal hydraulics best-estimate system code (RELAP5/SCDAPSIM/MOD3.4) to the statistical analysis software (DAKOTA) using a Python interface. Results from the BEPU analysis indicate that a realistic treatment of the accident scenario yields a larger safety margin and is therefore encouraged for accident analysis as it may enable more economic and flexible operation.