• 조명전기설비학회논문지
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• 제27권5호
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• pp.89-94
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• 2013

The fire testing performed for smoke detector model approval in Korea tests only one kind of fire smoke. A photoelectric spot-type smoke detector using Mie scattering is affected by the wavelength of light beam and the particle diameter. According to UL (Underwriters Laboratories Inc.) 268 standard, this paper analyze the characteristic of the response for a photoelectric spot-type smoke detector on sale in Korea using various fire smokes. Probability that the response time is included in non-defective range is 100% in paper fire, 90% in wood fire and 75% in flammable liquid fire, 90% in wood fire and 75% in flammable liquid fire. According to the estimation for population mean of the response time choosing a confidence level of 99%, a maximum of 19% for wood fire and that of 38% for flammable liquid fire are defective. As the result of analysis of smoke particle, this paper is found that these results are caused by the smoke particles are wide variations in size or have very black.

• 한국통신학회논문지
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• 제39C권9호
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• pp.852-860
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• 2014

본 논문에서 임펄스성 잡음의 유무를 검증하는 알고리즘을 제안한다. 본 알고리즘을 제안하는 이유는 기존의 Kolmogorov-Smirnov 검증의 단점으로 낮은 분류 성공률 및 높은 복잡도가 있기 때문이다. 이는 이론적으로 문제가 없으나 실제로 구현함에 있어 많은 문제를 야기한다. 먼저 기존의 검증 방법을 설명 후 제안하는 알고리즘을 설명한다. 이 알고리즘은 기존의 Kolmogorov-Smirnov 검증 방법의 이론적 배경으로부터 제안된다. 알고리즘의 효율성을 증명하기 위해 임펄스성 잡음의 샘플을 이용하여 실험 후, 검증 실패 확률을 조사한다. 검증 실패 확률에 기반한 실험 결과는 제안한 알고리즘의 효율성을 증명한다.

• Structural Engineering and Mechanics
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• 제66권3호
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• pp.399-409
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• 2018

This paper demonstrates the potential application of machine learning algorithms for approximate prediction of the load and deflection capacities of the novel type of Laced Steel Concrete-Composite (LSCC) beams proposed by Anandavalli et al. (Engineering Structures 2012). Initially, global and local responses measured on LSCC beam specimen in an experiment are used to validate nonlinear FE model of the LSCC beams. The data for the machine learning algorithms is then generated using validated FE model for a range of values of the identified sensitive parameters. The performance of four well-known machine learning algorithms, viz., Support Vector Regression (SVR), Minimax Probability Machine Regression (MPMR), Relevance Vector Machine (RVM) and Multigene Genetic Programing (MGGP) for the approximate estimation of the load and deflection capacities are compared in terms of well-defined error indices. Through relative comparison of the estimated values, it is demonstrated that the algorithms explored in the present study provide a good alternative to expensive experimental testing and sophisticated numerical simulation of the response of LSCC beams. The load carrying and displacement capacity of the LSCC was predicted well by MGGP and MPMR, respectively.

• 한국정밀공학회지
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• 제20권3호
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• pp.178-186
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• 2003

In order to investigate the fracture behaviors (penetration modes) and the resistance to penetration during ballistic impact of Al 5052-H34 alloy laminates, cold-rolled Al 5052-H34 alloy laminates, anodized Al 5052-H34 alloy laminates, and anodized Al 5052-H34 alloy after cold-rolling, a ballistic testing was conducted. In general, superior armor materials are brittle materials which have a high hardness. Ballistic resistance of these materials was measured by a protection ballistic limit (V$_{50}$), a statistical velocity with 50% probability fur incompletete penetration. Fracture begaviors and ballistic tolerance, described by penetration modes, ate observed from the results from the results of V$_{50}$ test and Projectile Through Plates (PTP) test at velocities greater than V$_{50}$, respectively. PTP tests were conducted with 0$_{\circ}$obliquity at room temperature using 5.56mm ball projectile. V$_{50}$ tests with 0$_{\circ}$obliquity at room temperature were concucted with projectiles that could achieve neat or complete penetration during PTP tests. Surface hardness, resistance to penetration, and penetration modes of Al 5052-H34 alloy laminates are compared to those of cold-rolled Al 5052-H34 alloy laminates and anodized Al 5052-H34 alloy laminates and anodized Al 5052-H34 cold-rolled alloy.

• Nuclear Engineering and Technology
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• 제53권6호
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• pp.1846-1857
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• 2021

Ultrasonic nondestructive testing is important for monitoring the structural integrity of dissimilar metal welds (DMWs) in pressure vessels and piping in nuclear power plants. However, there is a low probability of crack detection via inspection of DMWs using ultrasonic waves because the grain structures (grain orientations) of the weld area cause distortion and splitting of ultrasonic beams propagating in anisotropic media. To overcome this issue, the grain orientation should be known, and a precise ultrasonic wave simulation technique in anisotropic media is required to model the distortion and splitting of the waves accurately. In this study, a method for nondestructive prediction of the DMW grain orientations is presented for accurate simulation of ultrasonic wave propagation behavior in the weld area. The ultrasonic wave propagation behavior in anisotropic media is simulated via finite-element analysis when ultrasonic waves propagate in a transversely isotropic material. In addition, a methodology to predict the DMW grain orientation is proposed that employs a simulation technique for ultrasonic wave propagation behavior calculation and an optimization technique. The simulated ultrasonic wave behaviors with the grain orientations predicted via the proposed method demonstrate its usefulness. Moreover, the method can be used to determine the focal law in DMWs.

• The Journal of Asian Finance, Economics and Business
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• 제8권5호
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• pp.689-695
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• 2021

In the current technology-driven era, Small and medium enterprises (SMEs) have been deemed as one of the leading and prominent drivers of sustainable economic progress in emerging and developing economies such as in the Bangladesh context. Hence, it is of significance to understand what might fuel accelerating performance of SME business as increased SME performance will bring about more sustainability and strong development of SME sector within the country, through which more employment is anticipated to be generated. Therefore, the current study examines the impact of three factors: risk-taking, innovativeness, and proactiveness on SME performance in Bangladesh. The study has gathered data from SME entities in Dhaka city of Bangladesh, by applying a non-probability sampling strategy. 250 SME owners were contacted to act as respondents and finally, 180 SME owners fully completed the survey questionnaire, indicating that the final sample size is n=180. SPSS is used as a purpose of testing the hypotheses by considering a 5% significance level as acceptance criteria of the hypothesis. Hierarchical regression analysis was run to understand the impact of control variables and independent variables on SME performance and found that age of business, risk-taking, innovativeness, and proactiveness have an important impact on SME performance in Bangladesh.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권7호
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• pp.3511-3532
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• 2019

Coverage-guided fuzzing is an efficient solution that has been widely used in software testing. By guiding fuzzers through the coverage information, seeds that generate new paths will be retained to continually increase the coverage. However, we observed that most samples follow the same few high-frequency paths. The seeds that exercise a high-frequency path are saved for the subsequent mutation process until the user terminates the test process, which directly affects the efficiency with which the low-frequency paths are tested. In this paper, we propose a fuzzing solution, ER-Fuzz, that truncates the recording of a high-frequency path to influence coverage. It utilizes a deep learning-based classifier to locate the high and low-frequency path transfer points; then, it instruments at the transfer position to promote the probability low-frequency transfer paths while eliminating subsequent variations of the high-frequency path seeds. We implemented a prototype of ER-Fuzz based on the popular fuzzer AFL and evaluated it on several applications. The experimental results show that ER-Fuzz improves the coverage of the original AFL method to different degrees. In terms of the number of crash discoveries, in the best case, ER-Fuzz found 115% more unique crashes than did AFL. In total, seven new bugs were found and new CVEs were assigned.

• 한국안전학회지
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• 제34권1호
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• pp.76-81
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• 2019

In this study, the causes of human error were identified through the survey of the drivers of the three organizations: Seoul Metro, Seoul Metropolitan Rapid Transit Corporation, and Korail. It was started with the aim of finding and eliciting causes in various directions including human factors, job factors, and environmental factors. The Cronbach alpha value was 0.95 for the reliability significance of the stress-induced factors in the operational area. The significance probability for organisational factors was shown to be 0.82, and the significance of the sub-accident experience and the driving skill factors in operation was 0.81 In addition, the analysis results showed that stress-induced in the field of driving is higher than the human factors in the reliability analysis. The results of the analysis confirmed that the reliability of the organizational and operational stress-induced factors was higher than other causes. In order to reduce urban railroad accidents, this paper suggests a method for operating safe urban railroad through the minimization human errors.

• 아태비즈니스연구
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• 제11권4호
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• pp.37-48
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• 2020

Purpose - This study empirically investigates whether the risk property included in fat-tails of return distributions is systematic or unsystematic based on the devised statistical methods. Design/methodology/approach - This study devised empirical designs based on two traditional methods: principal component analysis (PCA) and the testing method of portfolio diversification effect. The fatness of the tails in return distributions is quantitatively measured by statistical probability. Findings - According to the results, the risk property in the fat-tails of return distributions has the economic meanings of eigenvalues having a value greater than 1 through PCA, and also systematic risk that cannot be removed through portfolio diversification. In other words, the fat-tails of return distributions have the properties of the common factors, which may explain the changes of stock returns. Meanwhile, the fatness of the tails in the portfolio return distributions shows the asymmetric relationship of common factors on the tails of return distributions. The negative tail in the portfolio return distribution has a much closer relation with the property of common factors, compared to the positive tail. Research implications or Originality - This empirical evidence may complement the existing studies related to tail risk which is utilized in pricing models as a common factor.

• The Journal of Asian Finance, Economics and Business
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• 제8권2호
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• pp.1025-1032
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• 2021

The study investigates factors affecting the loyalty of Food Delivery Application (FDA) service in Thailand. This study employs quantitative research methodology with a non-probability sampling method to draw 510 FDA samples from the FDA users in Thailand. The online questionnaires with a Cronbach's alpha coefficient of 0.886 were used as a research tool to collect data from samples. By using the Structural Equation Modeling (SEM) to analyze data, the results show that trustworthiness, social influence, system design, and task-technology fit affect the user's technology acceptance, which also show the significant relationship with the loyalty of FDA users in Thailand. The study checks the harmony with the statistics; χ2 = 258.686, df. =160, χ2/df. = 1.616, p-value = 0.050, CMIN/DF = 1.616, GFI = 0.960, AGFI = 0.969, TLI = 0.953, CFI = 0.965, RMSEA = 0.047, significant level at 0.05, along with testing the weight factor. In conclusion, the research model was harmonious with the empirical data at the significant level 0.05. The finding of this study suggested that the FDA service provider might apply this research finding to develop a greater understanding of the FDA's customer loyalty, as well as determine marketing strategies, identify opportunities, and create a competitive advantage in the future.