• 산업경영시스템학회지
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• 제23권60호
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• pp.73-81
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• 2000

The testing processes for VLSI finished devices are considerably complex because they require different types of ATE to be linked together. Due to the interaction effect between two or more linked ATEs, it is difficult to trace down the cause of the unexpected longer ATE setup time and random yields, which frequently occur in the VLSI circuit-testing laboratory. The goal of this paper is to develop and demonstrate the methodology designed to eliminate the possible interaction factors that might affect the random yields and/or unexpected longer setup time as well as increase the productivity. The statistical method such as design of experiment or multivariate analysis cannot be applied to the final testing floor here directly due to the environmental constraints. Expanded product data information (PDI) is constructed by combining product data information and ATE control information. An architecture utilizing expanded PDI is designed, which enables the engineer to conduct statistical approach investigation and reduce the setup time, as well as increase yield.

• 대한수학회지
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• 제58권4호
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• pp.819-833
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• 2021

Hawkes process is a self-exciting simple point process with clustering effect whose jump rate depends on its entire past history and has been widely applied in insurance, finance, queueing theory, statistics, and many other fields. Seol [27] proposed the inverse Markovian Hawkes processes and studied some asymptotic behaviors. In this paper, we consider an extended inverse Markovian Hawkes process which combines a Markovian Hawkes process and inverse Markovian Hawkes process with features of several existing models of self-exciting processes. We study the limit theorems for an extended inverse Markovian Hawkes process. In particular, we obtain a law of large number and central limit theorems.

• Journal of information and communication convergence engineering
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• 제21권3호
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• pp.198-207
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• 2023

Responding to changes in artificial intelligence models and the data environment is crucial for increasing data-learning accuracy and inference stability of industrial applications. A learning model that is overfitted to specific training data leads to poor learning performance and a deterioration in flexibility. Therefore, an early stopping technique is used to stop learning at an appropriate time. However, this technique does not consider the homogeneity and independence of the data collected by heterogeneous nodes in a differential network environment, thus resulting in low learning accuracy and degradation of system performance. In this study, the generalization performance of neural networks is maximized, whereas the effect of the homogeneity of datasets is minimized by achieving an accuracy of 99.7%. This corresponds to a decrease in delay time by a factor of 2.33 and improvement in performance by a factor of 2.5 compared with the conventional method.

• 한국경영과학회지
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• 제38권4호
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• pp.11-33
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• 2013

We analyzed the structures and properties of the global financial market networks using social network analysis approach. The Minimum Spanning Tree (MST) lengths and networks of the global financial markets based on the correlation coefficients have been analyzed. Firstly, similar to the previous studies on the global stock indices using MST length, the diversification effects in the global multi-asset portfolio can disappear during the crisis as the correlations among the asset class and within the asset class increase due to the system risks. Second, through the network visualization, we found the clustering of the asset class in the global financial markets network, which confirms the possible diversification effect in the global multi-asset portfolio. Meanwhile, we found the changes in the structure of the network during the crisis. For the last one, in terms of the degree centrality, the stock indices were the most influential to other assets in the global financial markets network, while in terms of the betweenness centrality, Gold, Silver and AUD. In the practical perspective, we propose the methods such as MST length and network visualization to monitor the change of the correlation risk for the risk management of the multi-asset portfolio.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2006년도 6th International Meeting on Information Display
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• pp.1219-1224
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• 2006

This study investigates the effect of $NH_3$ gas upon the growth of carbon nanotubes (CNTs) using thermal chemical vapor deposition. It is considered that the CNT synthesis occurs mainly through two steps, clustering of catalyst particles and subsequent growth of CNTs. We thus introduced $NH_3$ during either an annealing or growth step. When $NH_3$ was fed only during annealing, CNTs grew longer and more highly crystalline with diameters unchanged. An addition of $NH_3$ during growth, however, resulted in shorter CNTs with lower crystallinity while increased their diameters. Vertically aligned, highly populated CNT samples showed poor field emission characteristics, leading us to apply post-treatments onto the CNT surface. The CNTs were treated by adhesive tapes or etched back by dc plasma of $N_2$ to reduce the population density and the radius of curvatures of CNTs. We discuss the morphological changes of CNTs and their field emission properties upon surface treatments.

• Wind and Structures
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• 제15권2호
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• pp.87-109
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• 2012

A substantial part of South Africa is subject to more than one strong wind source. The effect of that on extreme winds is that higher quantiles are usually estimated with a mixed strong wind climate estimation method, compared to the traditional Gumbel approach based on a single population. The differences in the estimated quantiles between the two methods depend on the values of the Gumbel distribution parameters for the different strong wind mechanisms involved. Cluster analysis of the distribution parameters provides a characterization of the effect of the relative differences in their values, and therefore the dominance of the different strong wind mechanisms. For gusts, cold fronts tend to dominate over the coastal and high-lying areas, while other mechanisms, especially thunderstorms, are dominant over the lower-lying areas in the interior. For the hourly mean wind speeds cold fronts are dominant in the south-west, south and east of the country. On the West Coast the ridging of the Atlantic Ocean high-pressure system dominate in the south, while the presence of a deep trough or coastal low pressure system is the main strong wind mechanism in the north. In the central interior cold fronts tend to share their influence almost equally with other synoptic-scale mechanisms.

• Journal of Microbiology and Biotechnology
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• 제24권11호
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• pp.1473-1483
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• 2014

Reports of herbicide resistance events are proliferating worldwide, leading to new cultivation strategies using combinations of pre-emergence and post-emergence herbicides. We analyzed the impact during a one-year cultivation cycle of several herbicide combinations on the rhizobacterial community of glyphosate-tolerant Bt-maize and compared them to those of the untreated or glyphosate-treated soils. Samples were analyzed using pyrosequencing of the V6 hypervariable region of the 16S rRNA gene. The sequences obtained were subjected to taxonomic, taxonomy-independent, and phylogeny-based diversity studies, followed by a statistical analysis using principal components analysis and hierarchical clustering with jackknife statistical validation. The resilience of the microbial communities was analyzed by comparing their relative composition at the end of the cultivation cycle. The bacterial communites from soil subjected to a combined treatment with mesotrione plus s-metolachlor followed by glyphosate were not statistically different from those treated with glyphosate or the untreated ones. The use of acetochlor plus terbuthylazine followed by glyphosate, and the use of aclonifen plus isoxaflutole followed by mesotrione clearly affected the resilience of their corresponding bacterial communities. The treatment with pethoxamid followed by glyphosate resulted in an intermediate effect. The use of glyphosate alone seems to be the less aggressive one for bacterial communities. Should a combined treatment be needed, the combination of mesotrione and s-metolachlor shows the next best final resilience. Our results show the relevance of comparative rhizobacterial community studies when novel combined herbicide treatments are deemed necessary to control weed growth.

• 융합신호처리학회논문지
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• 제7권4호
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• pp.201-206
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• 2006

유전자 알고리즘은 공학 분야에서 필요한 여러 가지 최적화 문제에 대하여 최적에 가까운 해를 제공해주는 반복적 알고리즘으로 알려져 있다. 본 논문에서는 특정 교배방법에서 유전자의 배열순서가 적합도가 높은 스키마의 길이에 미치는 영향을 고찰하였다. 또한 이에 따른 유전자 알고리즘의 성능 변화를 두 개의 예제를 이용한 실험을 통하여 관찰하였다. 예제로 사용된 그래프 분할과 knapsack 문제를 위해 몇 가지 유전자 재배열 방법을 제시하였다. 실험결과에 따르면 유전자 재배열 방법마다 서로 다른 유전자 알고리즘 성능을 보여주었으며, 적합도가 높은 스키마의 길이를 고려한 재배열 방법이 재배열을 하지 않았을 때 보다 유전자 알고리즘의 성능을 향상시켜 주는 것을 관찰하였다. 따라서 주어진 문제에 적합한 유전자 재배열 방법을 찾는 것이 대단히 중요함을 확인하였다.

• 아태비즈니스연구
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• 제11권3호
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• pp.1-20
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• 2020

Purpose - This paper shows an unexplored area related to involuntary delisting. Specifically, this research investigates the effect of target firm information asymmetry on the likelihood that the acquirer or newly merged firm will be forcibly delisted post-merger. Design/methodology/approach - The research uses a sample gathered on local US mergers and acquisitions from the Thomson Reuters Securities Data Company (SDC) Platinum Mergers and Acquisitions database. It applies the logistic regression with industry and year effects and corrects the error term using clustering at the industry level. The research also matches the forced delisted firms to control firms based on industry, acquisition completion year, and firm size and then employs a matched sample analysis. Findings - Findings show that M&As between firms where the target firm is opaque and burdened with high information asymmetry issues are likely to be paid for using majority stock and that M&As involving such opaque targets also have a higher likelihood of getting delisted post-merger. Research implications or Originality - Our results are relevant given the very nature of M&As which involve two players: the acquirer and target who both may have different incentives. Acquirers especially have the tendency to suffer losses and even get delisted if they over-pay for or get merged to a poor target which conceals its poor performance evidenced by higher accruals quality.

• 천문학회보
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• 제44권2호
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• pp.52.2-52.2
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• 2019

In the last decades, the use of type Ia supernovae (SN) as standard candles has allowed us to understand the geometry of the Universe as they help to measure the expansion rate of the Universe, especially in combination with other cosmological probes such as the study of cosmic microwave background radiation anisotropies or the study of the imprint of baryonic acoustic oscillations on the galaxy clustering. Cosmological parameter constraints obtained with type Ia SN are mainly affected by intrinsic systematic errors. But there are other systematic effects related with the correlation of the observed brightness of Supernova and the large-scale structure of the Universe such as the effect of peculiar velocities and gravitational lensing. The former is relevant for SN at low redshifts while the latter starts being relevant for SN at higher redshifts. Gravitational lensing depends on how much matter is along the trajectory of each SN light beam. In order to account for this effect, we consider a statistical approach by defining the probability distribution (PDF) that a given supernova brightness is magnified by a given amount, for a particular redshift. We will show that different theoretical approaches to define the matter density along the light trajectory hugely affect the shape and width of the PDF. This may have catastrophic effects on cosmology fits using Supernova lensing as planned for surveys such as the Dark Energy Survey or future surveys such the Large Synoptic Survey Telescope.