• ETRI Journal
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• v.39 no.1
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• pp.124-134
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• 2017

Data races are one of the most difficult types of bugs in concurrent multithreaded systems. It requires significant time and cost to accurately detect bugs in complex large-scale programs. Although many race detection techniques have been proposed by various researchers, none of them are effective in all aspects. In this paper, we compare the performance of five recent dynamic race detection techniques: FastTrack, Acculock, Multilock-HB, SimpleLock+, and causally precedes (CP) detection. We experimentally demonstrate the strengths and weaknesses of these dynamic race detection techniques in terms of their detection capability, running time, and runtime overhead using 20 benchmark programs with different characteristics. The comparison results show that the detection capability of CP detection does not differ from that of FastTrack, and that SimpleLock+ generates the lowest overhead among the hybrid detection techniques (Acculock, SimpleLock+, and Multilock-HB) for all benchmark programs. SimpleLock+ is 1.2 times slower than FastTrack on average, but misses one true data race reported from Mutilock-HB on the large-scale benchmark programs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.565-568
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• 2009

This paper is a derivation of test item and a method evaluation about induced printer toner Software in enterprise.

• Journal of Magnetics
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• v.18 no.1
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• pp.14-20
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• 2013

For the treatment of osteoarthritis, pulsed electromagnetic field stimulus has been suggested as a useful therapeutic method in rehabilitative medicine. Most studies have been performed under low-frequency and low-energy to find out biological properties for stimulating chondrocyte with pulsed magnetic field. In this study, the effect of strong pulse magnetic field on the human chondrosarcoma cells (SW-1353) has been investigated by means of cell counting, morphologies, and gene expression of cartilage extracellular matrix genes. The SW-1353 cells were exposed under the field intensities of 270, 100, 55, 36, and 26 mTesla during 6 hours a day in 5 consecutive days. The pulse magnetic field with an LRC oscillating signal has the pulse width of 0.126 msec and stimulation period of 1 sec. For the 270 and 100 mTesla stimulation, the cell proliferation significantly increased in 21-24% as compared with the non-stimulated cells. Gene expression of cartilage extracellular matrix genes (ACAN, COMP and COL2A1) was assayed by quantitative real time-PCR method. The ACAN gene expression showed a significant brightness, which means the increase on gene expression, compared with the non-stimulated cells. Our results suggest that the strong pulse magnetic field stimulation can be utilized to accelerate cell proliferation and gene expression on human chondrosarcoma cells.

• Ocean Systems Engineering
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• v.12 no.4
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• pp.403-411
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• 2022

Annually, about 48-60% of sediment discharge of the Mekong River is delivered near the mouths of the Mekong River branches which is mostly coinciding with the southwest (SW) monsoon. This sediment budget in turn will be southwestwardly transported along the coast of the Mekong Delta (MD) during the northeast (NE) monsoon. Analysis of monsoonal changes in grain-size distribution (GSD) of surface sediment contributes to a better understanding of erosion and deposition processes along the MD. This study aims to figure out changes in GSD and sediment textures along the MD between SW and NE monsoons based on 183 surficial sediment samples collected along the MD during two field surveys carried-out in October 2016 and February-March 2017. Compared to the GSD during the SW and NE monsoon, the GSD along the MD changed significantly, especially in the estuary areas and along the coast of Bac Lieu and Ganh Hao. Whereas, in the west coast of the MD, GSD seem no changes between the two seasons. These changes in seabed sediment suggest that sediment with grain-sizes ranging from silt to fine sand can be transported during only a NE season.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2828-2835
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• 2015

In this paper, we analyse the effect of redundancy types and non-stop forwarding scheme on network service availability. We use stochastic reward net models as enabling modeling approach for the analytical evaluation. We first design stochastic reward nets for redundancy models with or without non-stop forwarding and then evaluate their availability using Stochastic Petri Net Package.

• Journal of Aerospace System Engineering
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• v.15 no.6
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• pp.42-49
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• 2021

To develop a high-resolution electro-optical/infrared (EO/IR) payload to be mounted on a high-speed and performance fighter aircraft in an external POD for acquiring daytime and nighttime image information on tactical targets, simulations, including flight environments and maneuvers, should be performed. Such simulations are pertinent to predicting the performance of several variables, such as aerodynamic force and inertia load acting on the payload. This paper describes the development of a flight data acquisition and analysis system based on flight simulation software (SW) for mission simulation of super-maneuverability fighter equipped with EO/IR payload. The effectiveness of the system is verified through comparison with actual flight data. The proposed flight data acquisition and analysis system based on FlightGear can be used as an M&S tool for system performance analysis in the development of the EO/IR payload.

• Steel and Composite Structures
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• v.43 no.1
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• pp.55-66
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• 2022

To develop high-efficiency lateral force resistance components for high-rise buildings, a novel energy dissipation shear wall with concrete-filled steel tubular (CFST) column elements was proposed. An energy dissipation shear wall specimen with CFST column elements (GZSW) and an ordinary reinforced concrete shear wall (SW) were constructed, and experimented by low-cycle reversed loading. The mechanical characteristics of these two specimens, including the bearing capacity, ductility, energy dissipation, and stiffness degradation process, were analyzed. The finite-element model of the GZSW was established by ABAQUS. Based on this finite-element model, the effect of the placement of steel-plate energy dissipation connectors on the seismic performance of the shear wall was analyzed, and optimization was performed. The experiment results prove that, the GZSW exhibited a superior seismic performance in terms of bearing capacity, ductility, energy dissipation, and stiffness degradation, in comparison with the SW. The results calculated by the ABAQUS finite-elements model of GZSW corresponded well with the results of experiment, and it proved the rationality of the established finite-elements model. In addition, the optimal placement of the steel-plate energy dissipation connectors was obtained by ABAQUS.

• Convergence Security Journal
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• v.24 no.2
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• pp.89-104
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• 2024

This study is an empirical study to examine the factors that influence the intention to use artificial intelligence (AI) technology for SW engineering-related tasks, and the purpose of the study is to understand the key factors that influence the use in terms of AI augmentation characteristics and interactive UI/UX characteristics. For this purpose, a survey was conducted among information and communication workers who have experience in using AI-related technologies and the collected data was analyzed. The results of the empirical analysis showed that perceived usefulness was positively influenced by the factors of expertise, interestingness, realism, aesthetics, efficiency, and flexibility, and perceived ease of use was positively influenced by the factors of expertise, interestingness, realism, aesthetics, and flexibility. Variety had no effect on both perceived ease of use and perceived usefulness. Perceived ease of use had a significant effect on perceived immersion, which positively influenced intention to use. These findings are significant in that they provide an academic understanding of the factors that influence the use of AI-enhanced tools in SW engineering-related tasks such as application design, development, testing, and process automation, as well as practical directions for the creators of tools that provide AI-enhanced development services to develop user acquisition strategies.

• Journal of the Korea Safety Management & Science
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• v.15 no.1
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• pp.11-19
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• 2013

In modern systems design and development, one of the key issues is considered to be related with how to reflect faithfully the stakeholder requirements including customer requirements therein, thereby successfully implementing the system functions derived from the requirements. On the other hand, the issue of safety management is also becoming greatly important these days, particularly in the operational phase of the systems under development. An approach to safety management can be based on the use of the failure mode effect and analysis (FMEA), which has been a core method adopted in automotive industry to reduce the potential failure. The fact that a successful development of cars needs to consider both the complexity and failure throughout the whole life cycle calls for the necessity of applying the systems engineering (SE) process. To meet such a need, in this paper a method of FMEA is developed based on the SE concept. To do so, a process model is derived first in order to identify the required activities that must be satisfied in automotive design while reducing the possibility of failure. Specifically, the stakeholder requirements were analyzed first to derive a set of functions, which subsequentially leads to the task of identifying necessary HW/SW components. Then the derived functions were allocated to appropriate HW/SW components. During this design process, the traceability between the functions and HW/SW components were generated. The traceability can play a key role when FMEA is performed to predict the potential failure that can be described with the routes from the components through the linked functions. As a case study, the developed process model has been applied in a project carried out in practice. The results turned out to demonstrate the usefulness of the approach.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.333-335
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• 2022

본 논문에서는 기존에 두 가지 모델이 필요했던 작업을 하나의 모델로 처리할 수 있는 자연어 처리 아키텍처를 제안한다. 단일 모델로 알츠하이머 환자의 언어패턴과 대화맥락을 분석하고 두 가지 결과인 환자분류와 챗봇의 대답을 도출한다. 일상생활에서 챗봇으로 환자의 언어특징을 파악한다면 의사는 조기진단을 위해 더 정밀한 진단과 치료를 계획할 수 있다. 제안된 모델은 전문가가 필요했던 질문지법을 대체하는 챗봇 개발에 활용된다. 모델이 수행하는 자연어 처리 작업은 두 가지이다. 첫 번째는 환자가 병을 가졌는지 여부를 확률로 표시하는 '자연어 분류'이고 두 번째는 환자의 대답에 대한 챗봇의 다음 '대답을 생성'하는 것이다. 전반부에서는 셀프어탠션 신경망을 통해 환자 발화 특징인 맥락벡터(context vector)를 추출한다. 이 맥락벡터와 챗봇(전문가, 진행자)의 질문을 함께 인코더에 입력해 질문자와 환자 사이 상호작용 특징을 담은 행렬을 얻는다. 벡터화된 행렬은 환자분류를 위한 확률값이 된다. 행렬을 챗봇(진행자)의 다음 대답과 함께 디코더에 입력해 다음 발화를 생성한다. 이 구조를 DementiaBank의 쿠키도둑묘사 말뭉치로 학습한 결과 인코더와 디코더의 손실함수 값이 유의미하게 줄어들며 수렴하는 양상을 확인할 수 있었다. 이는 알츠하이머병 환자의 발화 언어패턴을 포착하는 것이 향후 해당 병의 조기진단과 종단연구에 기여할 수 있음을 보여준다.