• Atmosphere
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• v.30 no.4
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• pp.335-346
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• 2020

Three free parameters included in a cumulus parameterization are optimized by using micro-genetic algorithm for three precipitation cases occurred in the Korea Peninsula during the summer season in order to reduce biases in a regional model associated with the uncertainties of the parameters and thus to improve the predictability of precipitation. The first parameter is the one that determines the threshold in convective trigger condition. The second parameter is the one that determines boundary layer forcing in convective closure. Finally, the third parameter is the one used in calculating conversion parameter determining the fraction of condensate converted to convective precipitation. Optimized parameters reduce the occurrence of convections by suppressing the trigger of convection. The reduced convection occurrence decreases light precipitation but increases heavy precipitation. The sensitivity experiments are conducted to examine the effects of the optimized parameters on the predictability of precipitation. The predictability of precipitation is the best when the three optimized parameters are applied to the parameterization at the same time. The first parameter most dominantly affects the predictability of precipitation. Short-range forecasts for July 2018 are also conducted to statistically assess the precipitation predictability. It is found that the predictability of precipitation is consistently improved with the optimized parameters.

• Current Optics and Photonics
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• v.6 no.4
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• pp.381-391
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• 2022

Two-photon-polymerization additive-manufacturing systems feature high resolution and precision. However, there are few reports on specific methods and possible problems concerning the use of small lasers to independently build such platforms. In this paper, a femtosecond-laser two-photon-polymerization additive-manufacturing system containing an optical unit, control unit, monitoring unit, and testing unit is built using a miniature femtosecond laser, with a detailed building process and corresponding control software that is developed independently. This system has integrated functions of light-spot detection, interface searching, micro-/nanomanufacturing, and performance testing. In addition, possible problems in the processes of platform establishment, resin preparation, and actual polymerization for two-photon-polymerization additive manufacturing are explained specifically, and the causes of these problems analyzed. Moreover, the impacts of different power levels and scanning speeds on the degree of polymerization are compared, and the influence of the magnification of the object lens on the linewidth is analyzed in detail. A qualitative analysis model is established, and the concepts of the threshold broadening and focus narrowing effects are proposed, with their influences and cooperative relation discussed. Besides, a linear structure with micrometer accuracy is manufactured at the millimeter scale.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.1
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• pp.31-40
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• 2023

Recent advances in flash technologies, such as 3D processing and multileveling schemes, have successfully increased the flash capacity. Unfortunately, these technology advances significantly degrade flash's reliability due to a smaller cell geometry and a finer-grained cell state control. In this paper, we propose an asymmetric BER-aware reliability optimization technique (aBARO), new flash optimization that improves the flash reliability. To this end, we first reveal that bit errors of 3D NAND flash memory are highly skewed among flash cell states. The proposed aBARO exploits the unique per-state error model in flash cell states by selecting the most error-prone flash states and by forming narrow threshold voltage distributions (for the selected states only). Furthermore, aBARO is applied only when the program time (tPROG) gets shorter when a flash cell becomes aging, thereby keeping the program latency of storage systems unchanged. Our experimental results with real 3D MLC and TLC flash devices show that aBARO can effectively improve flash reliability by mitigating a significant number of bit errors. In addition, aBARO can also reduce the read latency by 40%, on average, by suppressing the read retries.

• Smart Structures and Systems
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• v.31 no.2
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• pp.183-197
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• 2023

For long-span bridges with a structural health monitoring (SHM) system, environmental temperature-driven responses are proved to be a main component in measurements. However, anomalous structural behavior may be hidden incomplicated recorded data. In order to receive reliable assessment of structural performance, it is important to study therelationship between temperature and monitoring data. This paper presents an application of the cointegration based methodology to detect anomalies that may be masked by temperature effects and then forecast the temperature-induced deflection (TID) of long-span suspension bridges. Firstly, temperature effects on girder deflection are analyzed with fieldmeasured data of a suspension bridge. Subsequently, the cointegration testing procedure is conducted. A threshold-based anomaly detection framework that eliminates the influence of environmental temperature is also proposed. The cointegrated residual series is extracted as the index to monitor anomaly events in bridges. Then, wavelet separation method is used to obtain TIDs from recorded data. Combining cointegration theory with autoregressive moving average (ARMA) model, TIDs for longspan bridges are modeled and forecasted. Finally, in-situ measurements of Xihoumen Bridge are adopted as an example to demonstrate the effectiveness of the cointegration based approach. In conclusion, the proposed method is practical for actual structures which ensures the efficient management and maintenance based on monitoring data.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.411-411
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• 2023

미래 대기 이산화탄소 농도가 증가함에 따라 강수 등 기후의 변화하고, 이는 유출량을 포함한 수문 순환 뿐 아니라 지면 식생 생장에 영향을 줄 것으로 예상된다. 이에 본 연구에서는 미래 CO2 증가에 따른 식생의 변화와 이로 인한 지표 유출량의 변화에 대해 이해하고자 한다. Intergovernmental Panel on Climate Change (IPCC) 6차 평가보고서에서 제시한 표준 온실가스 경로 중 탄소 모듈이 포함된 Coupled Model Intercomparison Project phase 6 biogeochemistry (CMIP6-BGC) 모델과 탄소 모듈이 포함안된 CMIP6 모델 결과를 활용하였다. 공통 사회경제경로 시나리오(Shared Socio-economic Pathway; SSP) 중 고탄소 시나리오인 SSP585에 따른 모델 결과물을 활용하였다. 표면 유출량 자료에 과거 기간 임계수준 방법을 (Threshold Level Method) 적용하여 동아시아 지역 극한 건조 및 습윤 상태의 빈도와 강도를 CMIP6-BGC와 CMIP6에 대해 평가하였다. CMIP6-BGC 경우, 건조 및 습윤 상태의 빈도는 각각 6.17%, 5.03% , CMIP6 경우 각각 9.29%, 6.70% 으로 예측되어, CMIP6-BGC가 CMIP6 보다 극한 상태를 과소평가하는 경향을 보였다. 또한, 잎 면적 지수(Leaf Area Index; LAI), 증산량 등의 변수를 분석하여, 기 도출된 CMIP6-BGC와 CMIP6 간의 극한 건조 및 습윤 상태 예측의 차이가 발생한 메카니즘을 이해하고자 하였다.

• Asia Marketing Journal
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• v.18 no.3
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• pp.47-63
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• 2016

Rational choice theory holds that the alternative with largest expected utility in the choice set should always be chosen. However, it is often observed that an alternative with the largest expected utility is not always chosen while the choice task itself being avoided. Such a choice phenomenon cannot be explained by the traditional expected utility maximization principle. The current study posits shows that such a phenomenon can be attributed to the gap between the expected perceived gain (or loss) and the expected perceived value. This study mathematically analyses the relationship between the expectation of an alternative's gains or losses over the reference point and its expected value, when the perceived gains or losses follow continuous probability distributions. The proposed expected value (EV) function can explain the effects of loss aversion and uncertainty on the evaluation of an alternative based on the prospect theory value function. The proposed function reveals why the expected gain of an alternative should exceed some positive threshold in order for the alternative to be chosen. The model also explains why none of the two equally or similarly attractive options is chosen when they are presented together, but either of them is chosen when presented alone. The EV function and EG-EV curve can extract and visualize the core tenets of the prospect theory more clearly than the value function itself.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.295-303
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• 2022

This study investigates the impact of globalization, coal consumption, and economic growth on CO₂ emissions in Malaysia by applying the Kuznets Environmental Curve model. The study employed the Autoregressive Distributed Lag modeling technique on time series data over the period of 1970-2018 to determine the short and long-run relationship between CO₂ emissions and a number of variables, including globalization, coal consumption, and economic growth. The results show that globalization increase CO₂ emissions in both the short and long run in Malaysia. Furthermore, the results reveal that economic growth and coal consumption degrade the environmental quality by accelerating the CO₂ emissions in the short-run and long run. As a result, the findings validate the Kuznets Environmental Curve hypothesis of an inverted U-shaped relationship between economic growth and CO₂ emissions in the long run for Malaysia. The findings of this study suggest that higher globalization levels and usage of coal consumption degrade the environmental quality in Malaysia. The findings also indicate the effect of economic growth on environmental degradation is positive at the initial stage but improves after the economy achieves a threshold level of income per capita in the economic development process with an inverted U-shaped pattern in the long run.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.124-124
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• 2020

This study proposes a framework to evaluate extreme drought using the natural drought index and hot spot analysis. The study area was South Korea. Data were used from 59 automatic synoptic observing system stations. The variable infiltration capacity model was used for the period from 1981 to 2016. The natural drought index was constructed from precipitation, runoff and soil moisture data, which reflect the water cycle. The average interval, duration and severity of extreme drought events were determined following Run theory. The most extreme drought period occurred in 2014-2016, with 46 of 59 weather stations exhibition drought conditions and 78% exhibition extreme drought conditions. The Inje and Seosan station exhibited the longest drought duration of 6 months, and the most severe drought was 5 times higher than the extreme drought severity threshold. The hot spot analysis was used to explore the extreme drought conditions and showed an increasing trend in the middle and northeastern parts of South Korea. Overall, this study provides water resource managers with essential information about locations and significant trends of extreme drought.

• Tribology and Lubricants
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• v.39 no.5
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• pp.216-219
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• 2023

This study employs molecular dynamics simulations to investigate the material behavior of workpieces in waterjet machining processes. To gain fundamental insights into waterjet machining, simulations were conducted using pure water, excluding abrasive particles. The simulation model comprised thousands of water molecules interacting with a single crystal metal workpiece. Water molecule clusters were imparted with various velocities to initiate collisions with the metal workpiece. The material behavior of the metal surface was analyzed with respect to the applied velocity conditions, considering the intricate interplay between water molecules and the workpiece at the atomic scale. The results demonstrated that the machining of the metal workpiece occurred only when water molecules were endowed with velocities above a certain threshold. In cases where energy was insufficient, the metal workpiece exhibited a slight increase in surface roughness due to mild plastic deformation, without undergoing substantial material removal. When machining occurred, the ejection of material revealed a 3-fold symmetric pattern, confirming that material removal in waterjet machining of the metal workpiece is primarily driven by plastic deformation-induced material ejection. This research provides crucial insights into the mechanisms underlying waterjet machining and enhances our understanding of material behavior during the process. The findings can be valuable in optimizing waterjet machining techniques.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.167-177
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• 2024

With advancements in satellite technology, interest in target detection and identification is increasing quantitatively and qualitatively. Synthetic Aperture Radar(SAR) images, which can be acquired regardless of weather conditions, have been applied to various areas combined with machine learning based detection algorithms. However, conventional studies primarily focused on the detection of stationary targets. In this study, we proposed a method to identify moving targets using an algorithm that integrates sub-aperture SAR images and cosine similarity calculations. Utilizing a transformer-based deep learning target detection model, we extracted the bounding box of each target, designated the area as a region of interest (ROI), estimated the similarity between sub-aperture SAR images, and determined movement based on a predefined similarity threshold. Through the proposed algorithm, the quantitative evaluation of target identification capability enhanced its accuracy compared to when training with the targets with two different classes. It signified the effectiveness of our approach in maintaining accuracy while reliably discerning whether a target is in motion.