• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.596-604
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• 2020

Previous studies on pipe auto-routing algorithms generally used such algorithms as A*, Dijkstra, Genetic Algorithm, Particle Swarm Optimization, and Ant Colony Optimization, to satisfy the relevant constraints of its own field and improve the output quality. On the other hand, this study aimed to significantly improve path-finding speed by applying the Jump Point Search (JPS) algorithm, which requires lower search cost than the abovementioned algorithms, for pipe routing. The existing JPS, however, is limited to two-dimensional spaces and can only find the shortest path. Thus, it requires several improvements to be applied to pipe routing. Pipe routing is performed in a three-dimensional space, and the path of piping must be parallel to the axis to minimize its interference with other facilities. In addition, the number of elbows must be reduced to the maximum from an economic perspective, and preferred spaces in the path must also be included. The existing JPS was improved for the pipe routing problem such that it can consider the above-mentioned problem. The fast path-finding speed of the proposed algorithm was verified by comparing it with the conventional A* algorithm in terms of resolution.

• Tribology and Lubricants
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• v.37 no.1
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• pp.1-6
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• 2021

This paper presents the experimental results of hydrophobic surfaces developed using a stereolithography-based additive-manufacturing technique. The additive manufacturing technique can be used to manufacture objects with complex geometries from computer-aided design data. Several additive manufacturing methods, such as selective laser sintering, fused deposition modeling, stereolithography apparatus (SLA), and inkjet-based system, have been developed. The SLA is a form of three-dimensional printing technology used to create prototypes, patterns, and production parts in successive layers through photochemical processes. Light causes chemical monomers and oligomers to cross-link together to form objects composed of polymers. Moreover, this method is economical for fabricating surfaces with high output resolution and quality. Here, we fabricate various surfaces using different shapes using an SLA. The surfaces with micro-patterns are fabricated for 10 cases, including the biomimetic surface. The fabricated surfaces with various micro-patterns are evaluated for hydrophobicity performance based on the static contact angle. The contact angle is measured three times for each case, and the averaged value is used. The results indicate that the arrangements in a staggered structure have a larger contact angle than those in a line when the same micro-pattern is applied. Moreover, the mimetic surfaces exhibit more hydrophobic characteristics than those of artificial micro-patterns.

• New & Renewable Energy
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• v.17 no.2
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• pp.24-31
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• 2021

Renewable energy has become more popular with the increase in the use of solar power. Consequently, the disposal of defective and old solar panels is gradually increasing giving rise to a new problem. Furthermore, the efficiency and power output decreases with aging. Researchers worldwide are engaged in solving this problem by developing eco-module technologies that restore and reuse the solar panels according to the defect types rather than simple disposal. The eco-module technology not only solves the environmental problem, but also has economic advantages, such as extending the module life. Replacement of encapsulants contributes to a major portion of the module maintenance plan, as the degradation of encapsulants accounts for 60% of the problems found in modules over the past years. However, the current International Electrotechnical Commission (IEC) standard testing was designed for the commercialization of solar modules. As the problem caused by long-term use is not considered, this method is not suitable for the quality assurance evaluation of the eco-module. Therefore, to design a new accelerated test, this paper provides an overview of EVA degradation and comparison with the IEC and accelerated tests.

• Journal of Korea Multimedia Society
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• v.25 no.9
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• pp.1273-1283
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• 2022

This paper presents a locally adaptive HDR algorithm using the integral image and MSRCR for LDR images with inadequate exposure. There are two categories in controlling the dynamic range, which are global and local tone mappings. Since the global ones are relatively simple but have some limitations at considering regional characteristics, the local ones are often utilized and MSRCR is a representative method. MSRCR gives moderate results, but it requires lots of computations for multi-scale surround Gaussian functions and produces the Halo effect around the edges. Therefore, in order to resolve these main problems, the proposed algorithm remarkably reduces the computation of the surrounds due to the use of the integral image. And a set of variable-sized windows is adopted to decrease the Halo effect, according to the type of pixel's region. In addition, an offset controlling function is presented, which is mainly affected to the subjective image quality and based on the global input and the desired output means. As the results, the proposed algorithm no more use Gaussian functions and can reduce the computation amount and the Halo effect.

• Design & Manufacturing
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• v.16 no.3
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• pp.50-57
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• 2022

The qualities of the products produced by injection molding are strongly influenced by the process variables of the injection molding machine set by the engineer. It is very difficult to predict the qualities of the injection molded product considering the stochastic nature of the manufacturing process, since the processing conditions have a complex impact on the quality of the injection molded product. It is recognized that the artificial neural network(ANN) is capable of mapping the intricate relationship between the input and output variables very accurately, therefore, many studies are being conducted to predict the relationship between the results of the product and the process variables using ANN. However in the condition of a small number of data sets, the predicting performance and robustness of the ANN model could be reduced due to too many input variables. In the present study, the ANN model that predicts the length of the injection molded product for multiple combinations of process variables was developed. And the accuracy of each ANN model was compared for 8 process variables and 4 important process inputs that were determined by the feature selection. Based on the comparison, it was verified that the performance of the ANN model increased when only 4 important variables were applied.

• Journal of Sensor Science and Technology
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• v.31 no.5
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• pp.301-306
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• 2022

With the recent widespread implementation of Internet of Things (IoT) technology driven by Industry 4.0, self-powered sensors for wearable and implantable systems are increasingly gaining attention. Piezoelectric nanogenerators (PENGs) and triboelectric nanogenerators (TENGs), which convert biomechanical energy into electrical energy, can be considered as efficient self-powered sensor platforms. These are energy harvesters that are used as low-power energy sources. However, they can also be used as sensors when an output signal is used to sense any mechanical stimuli. For sensors, collecting high-quality data is important. However, the accuracy of sensing for practical applications is equally important. This paper provides a brief review of the performance advanced by the materials and structures of the latest PENG/TENG-based wearable sensors and intelligent applications applied using artificial intelligence (AI)

• The Journal of Fisheries Business Administration
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• v.53 no.3
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• pp.65-83
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• 2022

In addition to simply providing quality food to the people, the fishery industry must be maintained and developed because it has various functions such as national food security, preservation of natural scenery, protection of national territory, and revitalization of the local economy. However, risk factors such as climate changes and environmental destruction have raised concerns about the sustainable development of the industry. Since these risk factors are becoming larger and more complex over time, it is time to conduct research related to the risk of the fishery industry. Therefore, the purpose of this study is to explore the risk factors facing the fisheries at this point, to analyze the economic ripple effect of regional fishery product supply shortage, and to draw implications. As a result of this study, the economic ripple effect of fishery product shortage per won was highest in Busan, followed by Gangwon, Gyeongnam, and Gyeongbuk. Considering the size of the local fishery industry, Busan had the highest supply shortage per 1% of local fisheries production. It is also necessary to prepare special risk management and countermeasures for these regions since the effect of supply shortage in regions such as Jeonnam, Gyeongnam, and Jeju is large compared to other regions.

• Microbiology and Biotechnology Letters
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• v.51 no.1
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• pp.1-9
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• 2023

Arsenic (As), which is ubiquitous throughout the environment, represents a major environmental threat at higher concentration and poses a global public health concern in certain geographic areas. Most of the conventional arsenic remediation techniques that are currently in use have certain limitations. This situation necessitates a potential remediation strategy, and in this regard bioremediation technology is increasingly important. Being the oldest representativse of life on Earth, microbes have developed various strategies to cope with hostile environments containing different toxic metals or metalloids including As. Such conditions prompted the evolution of numerous genetic systems that have enabled many microbes to utilize this metalloid in their metabolic activities. Therefore, within a certain scope bacterial isolates could be helpful for sustainable management of As-contamination. Research interest in microbial As(III) oxidation has increased recently, as oxidation of As(III) to less hazardous As(V) is viewed as a strategy to ameliorate its adverse impact. In this review, the novelty of As(III) oxidation is highlighted and the implication of As(III)-oxidizing microbes in environmental management and their prospects are also discussed. Moreover, future exploitation of As(III)-oxidizing bacteria, as potential plant growth-promoting bacteria, may add agronomic importance to their widespread utilization in managing soil quality and yield output of major field crops, in addition to reducing As accumulation and toxicity in crops.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.1
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• pp.49-55
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• 2023

Business is an important entity in every economy with its role in job creation, budget contribution, and national output. It can be said that enterprises are also one of the leading units that play a key role in implementing digital transformation, grasping science and technology, and improving labor productivity. Developing a team of enterprises that are both strong in quantity and strong in quality is an urgent requirement in many countries, including Vietnam. Vietnam is a developing country and home to many textile and garment enterprises operating due to the advantages of cheap labor and a large market, the textile and garment industry is capable of creating many jobs for the economy. Studying the factors affecting corporate financial performance across 250 textile and garment enterprises in Hanoi capital and Bac Ninh province, the research results show that when enterprises have the ability to mobilize capital, the cost is cheap, appropriate, and optimal, most businesses often achieve higher business efficiency and financial performance. In contrast, enterprises that are difficult to raise capital in the economy often achieve low financial efficiency and financial performance. The study also confirms the role of human capital in enterprises, enterprises with high human capital often achieve high profits.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.70.4-70.4
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• 2019

Image super-resolution (SR) is a technique that enhances the resolution of a low resolution image. In this study, we use three SR models (RCAN, ProSRGAN and Bicubic) for enhancing solar SDO/HMI magnetograms using deep learning. Each model generates a high resolution HMI image from a low resolution HMI image (4 by 4 binning). The pixel resolution of HMI is about 0.504 arcsec. Deep learning networks try to find the hidden equation between low resolution image and high resolution image from given input and the corresponding output image. In this study, we trained three models with HMI images in 2014 and test them with HMI images in 2015. We find that the RCAN model achieves higher quality results than the other two methods in view of both visual aspects and metrics: 31.40 peak signal-to-noise ratio(PSNR), Correlation Coefficient (0.96), Root mean square error (RMSE) is 0.004. This result is also much better than the conventional bi-cubic interpolation. We apply this model to a full-resolution SDO/HMI image and compare the generated image with the corresponding Hinode NFI magnetogram. As a result, we get a very high correlation (0.92) between the generated SR magnetogram and the Hinode one.