• Journal of Power Electronics
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• v.3 no.4
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• pp.205-214
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• 2003

This paper proposes a simple control strategy based on the discontinuous PWM (DPWM) to balance the DC-link voltage of three-level neutral-point-clamped (NPC) inverter at low modulation index. It introduces new DPWM methods in multi-level inverter and one of them is used for balancing the DC-link voltage. The current flowing in the neutral point of the DC-link causes the fluctuation of the DC-link voltage of the NPC inverter. The proposed DPWM method changes the path and duration time of the neutral point current, which makes the overall fluctuation of the DC-link voltage zero during a sampling time of the reference voltage vector. Therefore, by using the proposed strategy, the voltage of the DC-link can be balanced fairly well and the voltage ripple of the DC-link is also reduced significantly. Moreover, comparing with conventional methods which have to perform the complicated calculation, the proposed strategy is very simple. The validity of the proposed DPWM method is verified by the experiment.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.923-930
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• 2021

The COVID-19 pandemic weakened the small- and medium-sized enterprise (SME) sector. The decline in turnover is one that is felt by the batik industry in East Java, and the decline in turnover in the batik industry is very drastic. This research was conducted to prove the influence of the COVID-19 pandemic on SMEs in the batik industry. One model is proposed to prove the existence of an increase in the performance of the batik industry's SMEs by implementing a customer relationship management strategy, business strategy, and market orientation. The study population was the batik industry entrepreneurs in East Java, Indonesia, using SEM analysis based on Amos, purposive sampling method, and a sample of 180 respondents. The results showed that the model was accepted. The results also show that customer relationship management and business strategy contributed to the performance of SMEs, while market orientation did not contribute to the performance of SMEs during the COVID-19 pandemic. To be able to maintain the sustainability of the company, the steps taken by the company are to lay off some of the employees, and during the production period the production stops, and focus on selling goods that have been previously produced.

• Wind and Structures
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• v.37 no.5
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• pp.383-397
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• 2023

In the Structural Health Monitoring (SHM) system of civil engineering, data missing inevitably occurs during the data acquisition and transmission process, which brings great difficulties to data analysis and poses challenges to structural health monitoring. In this paper, Convolution Neural Network (CNN) is used to recover the nonstationary wind speed data missing randomly at sampling points. Given the technical constraints and financial implications, field monitoring data samples are often insufficient to train a deep learning model for the task at hand. Thus, simulation combined transfer learning strategy is proposed to address issues of overfitting and instability of the deep learning model caused by the paucity of training samples. According to a portion of target data samples, a substantial quantity of simulated data consistent with the characteristics of target data can be obtained by nonstationary wind-field simulation and are subsequently deployed for training an auxiliary CNN model. Afterwards, parameters of the pretrained auxiliary model are transferred to the target model as initial parameters, greatly enhancing training efficiency for the target task. Simulation synergy strategy effectively promotes the accuracy and stability of the target model to a great extent. Finally, the structural dynamic response analysis verifies the efficiency of the simulation synergy strategy.

• The Plant Pathology Journal
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• v.29 no.2
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• pp.144-153
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• 2013

Diverse bacteria are known to colonize plants. However, only a small fraction of that diversity has been evaluated for their biopesticide potential. To date, the criteria for sampling and selection in such bioprospecting endeavors have not been systematically evaluated in terms of the relative amount of diversity they provide for analysis. The present study aimed to enhance the success of bioprospecting efforts by increasing the diversity while removing the genotypic redundancy often present in large collections of bacteria. We developed a multivariate sampling and marker-based selection strategy that significantly increase the diversity of bacteria recovered from plants. In doing so, we quantified the effects of varying sampling intensity, media composition, incubation conditions, plant species, and soil source on the diversity of recovered isolates. Subsequent sequencing and high-throughput phenotypic analyses of a small fraction of the collected isolates revealed that this approach led to the recovery of over a dozen rare and, to date, poorly characterized genera of plant-associated bacteria with significant biopesticide activities. Overall, the sampling and selection approach described led to an approximately 5-fold improvement in efficiency and the recovery of several novel strains of bacteria with significant biopesticide potential.

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.515-530
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• 2023

Purpose : This research aims to develop a data-driven inspection policy for radio stations utilizing the KS Q ISO 2859-1 sampling method, addressing potential regulatory relaxations and impending management challenges. Methods : Using radio station inspection big data from the past six years, we established a simulation model to evaluate the current policy. A new inspection sampling policy framework was designed based on the KS Q ISO 2859-1 method. The study compares the performance of the current and proposed inspection systems, offering insights for an improved inspection strategy. Results : This study introduced a simulation model for inspection system based on the KS Q ISO 2859-1 sampling method. Through various experimental designs, key performance indicators such as non-detection rate and sample proportion were derived, providing foundational data for the new inspection policy. Conclusion : Using big data from radio station inspections, we evaluated current inspection systems and quantitatively compared a new system across diverse scenarios. Our simulation model effectively verified the feasibility and efficiency of the proposed framework. For practical implementation, essential factors such as lot size, inspection cycle, and AQL standards need precise definition and consideration. Enhancing radio station inspections requires a policy-driven approach that factors in socio-economic impacts and solicits feedback from industry participants. Future study should also explore various perspectives related to legislative, institutional, and operational aspects of inspection organizations.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.708-710
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• 2004

This paper studies a multirate sampled-data control for LTI systems by using the digital redesign (DR) method. In this note, to well tackle the problem associated with both the state matching and the stabilization, our nobel strategy is to minimize the linear quadratic cost function. The main features of the proposed method are that i) the delta-operator-based descretization method is applied to improve the state-matching performance in the fast sampling limit and/or the large input multiplicity; ii) the proposed multirate control scheme can improve the state-matching performance in the long sampling limit; iii) some sufficient conditions that guarantee the stability of the closed-loop discrete-time system and provide a guarantee cost for the cost function can be formulated in the LMIs format; and iv) an optimal sampled-data controller in the sense of minimizing the upper bound of the cost function is also given by means of an LMI optimization procedure.

• Journal of Environmental Science International
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• v.18 no.10
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• pp.1079-1088
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• 2009

The statistics of monitoring on soil quality is a report statistics which is made on the basis of Article 15, Environment Strategy Basic Law and Article 5, Soil Environment Conservation Law. This study was conducted according to quality assessment of Korea National Statistical Office. The assessment of quality infrastructure advised that the authority bring up and increase completely responsible officer and secure the budget. The assessment of user satisfaction and reflection of request propose that the statistics is focused on soil background concentration, decrease soil sampling points and extend survey period. The assessment of error management system per processes of detailed preparation suggest change of the statistics objective, a reduction of sampling points and improvement of survey period and soil measurement properties. Accuracy assessment of data proposed cuts of sampling points, accessibility increment and build up of management system linking subordinates and Ministry of Environment. The substantiality assessment of data service demonstrated information environment improvement for users including reference expression and records of statistics table and figure contents.

• Structural Engineering and Mechanics
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• v.75 no.6
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• pp.771-784
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• 2020

Reliability analysis techniques combining with various surrogate models have attracted increasing attention because of their accuracy and great efficiency. However, they primarily focus on the structures with continuous response, while very rare researches on the reliability analysis for structures with discontinuous response are carried out. Furthermore, existing adaptive reliability analysis methods based on importance sampling (IS) still have some intractable defects when dealing with small failure probability, and there is no related research on reliability analysis for structures involving discontinuous response and small failure probability. Therefore, this paper proposes a novel reliability analysis method called AGPC-IS for such structures, which combines adaptive Gaussian process classification (GPC) and adaptive-kernel-density-estimation-based IS. In AGPC-IS, an efficient adaptive strategy for design of experiments (DoE), taking into consideration the classification uncertainty, the sampling uniformity and the regional classification accuracy improvement, is developed with the purpose of improving the accuracy of Gaussian process classifier. The adaptive kernel density estimation is introduced for constructing the quasi-optimal density function of IS. In addition, a novel and more precise stopping criterion is also developed from the perspective of the stability of failure probability estimation. The efficiency, superiority and practicability of AGPC-IS are verified by three examples.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.6
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• pp.730-740
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• 2018

Hydrofoil is the direct component to generate thrust for underwater glider. It is significant to improve propulsion efficiency of hydrofoil. This study optimizes the shape of a hydrofoil using Free-Form Deformation (FFD) parametric approach and Surrogate-based Optimization (SBO) algorithm. FFD approach performs a volume outside the hydrofoil and the position changes of control points in the volume parameterize hydrofoil's geometric shape. SBO with adaptive parallel sampling method is regarded as a promising approach for CFD-based optimization. Combination of existing sampling methods is being widely used recently. This paper chooses several well-known methods for combination. Investigations are implemented to figure out how many and which methods should be included and the best combination strategy is provided. As the hydrofoil can be stretched from airfoil, the optimizations are carried out on a 2D airfoil and a 3D hydrofoil, respectively. The lift-drag ratios are compared among optimized and original hydrofoils. Results show that both lift-drag-ratios of optimized hydrofoils improve more than 90%. Besides, this paper preliminarily explores the optimization of hydrofoil with root-tip-ratio. Results show that optimizing 3D hydrofoil directly achieves slightly better results than 2D airfoil.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.825-836
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• 2019

One of the most challenging safety precautions for workers in dynamic, radioactive environments is avoiding radiation sources and sustaining low exposure. This paper presents a sampling-based algorithm, DL-RRT*, for minimum dose walk-path re-planning in radioactive environments, expedient for occupational workers in nuclear facilities to avoid unnecessary radiation exposure. The method combines the principle of random tree star ($RRT^*$) and $D^*$ Lite, and uses the expansion strength of grid search strategy from $D^*$ Lite to quickly find a high-quality initial path to accelerate convergence rate in $RRT^*$. The algorithm inherits probabilistic completeness and asymptotic optimality from $RRT^*$ to refine the existing paths continually by sampling the search-graph obtained from the grid search process. It can not only be applied to continuous cost spaces, but also make full use of the last planning information to avoid global re-planning, so as to improve the efficiency of path planning in frequently changing environments. The effectiveness and superiority of the proposed method was verified by simulating radiation field under varying obstacles and radioactive environments, and the results were compared with $RRT^*$ algorithm output.