• Journal of Broadcast Engineering
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• 제26권1호
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• pp.3-13
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• 2021

We propose a moire artifacts removal algorithm for screen-shot images using multiple domain learning. First, we estimate clean preliminary images by exploiting complementary information of the moire artifacts in pixel value and frequency domains. Next, we estimate a clean edge map of the input moire image by developing a clean edge predictor. Then, we refine the pixel and frequency domain outputs to further improve the quality of the results using the estimated edge map as the guide information. Finally, the proposed algorithm obtains the final result by merging the two refined results. Experimental results on a public dataset demonstrate that the proposed algorithm outperforms conventional algorithms in quantitative and qualitative comparison.

• Journal of the Korean Society of Propulsion Engineers
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• 제25권2호
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• pp.24-33
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• 2021

Numerical study is conducted to analyze combustion instability in the partially premixed combustor. The simulations are performed according to fuel conditions, and Large Eddy Simulation(LES) model and PaSR combustion model are implemented in the solver. Comparison with the experimental result is conducted to confirm the validity of simulation, and quantitative and qualitative agreement is confirmed. The flame characteristics in the combustor are subsequently investigated, and the association with the occurrence of combustion instability is clarified. According to the simulation results, the flame length varies greatly depending on the fuel conditions. When the flame length becomes sufficiently long, flame-vortex interactions occurred around the wall sections, which works as the main cause of combustion instability.

• Journal of the Korean Society of Visualization
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• 제20권3호
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• pp.102-108
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• 2022

In the fan module of the intercooling refrigerator, a drain hole structure was designed for stable drainage of defrost water. However, the airflow passing through the drain hole can disturb flow features around the evaporator. Since this backflow leads to an increase in flow loss, the accurate experimental and numerical analyses are important to understand the flow characteristics around the fan module. Considering the complex geometry around the fan module, three different turbulence models (Standard k-ε model, SST k-ω model, Reynolds stress model) were used in computational fluid dynamics (CFD) analysis. According to the quantitative and qualitative comparison results, the Standard k-ε model was most suitable for the research object. High-accuracy results well match with the experiment result and overcome the limitation of the experiment setup. The method used in this study can be applied to a similar research object with an orifice outflow driven by a rotating blade.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.55-60
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• 2022

Acceleration of the pace of life, increasing the amount of information, the emergence of "clip way of thinking" as a phenomenon has led to the problem of choosing forms of presentation of educational materials to students. One of the ways to solve this problem is to use the means of visualization of information flow, forasmuch as the thinking of modern youth is more effective in perceiving visual images than verbal means. The purpose of the research is to prove the effectiveness of the use of visualization in the process of teaching Ukrainian as a foreign language to students with clip way of thinking. The following methods have been used, namely: analysis, synthesis, comparison, systematization and generalization of scientific literature; testing and surveys; pedagogical experiment; quantitative and qualitative analysis of data, interpretation and generalization of the research results. The essence of visualization means has been revealed; the expediency of their use in the methodology of teaching foreign students the Ukrainian language has been substantiated. It has been proven that the role of Ukrainian teachers lies in taking into account all new trends in teaching, integrating computer perception of information by foreign students into teaching technology and using cognitive visualization in order to intensify the learning process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권8호
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• pp.2552-2570
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• 2022

Underwater images usually have various problems, such as the color cast of underwater images due to the attenuation of different lights in water, the darkness of image caused by the lack of light underwater, and the haze effect of underwater images because of the scattering of light. To address the above problems, the channel attention mechanism, strengthen-operate-subtract (SOS) boosting mechanism and gated fusion module are introduced in our paper, based on which, an underwater image recovery network is proposed. First, for the color cast problem of underwater images, the channel attention mechanism is incorporated in our model, which can well alleviate the color cast of underwater images. Second, as for the darkness of underwater images, the similarity between the target underwater image after dehazing and color correcting, and the image output by our model is used as the loss function, so as to increase the brightness of the underwater image. Finally, we employ the SOS boosting module to eliminate the haze effect of underwater images. Moreover, experiments were carried out to evaluate the performance of our model. The qualitative analysis results show that our method can be applied to effectively recover the underwater images, which outperformed most methods for comparison according to various criteria in the quantitative analysis.

• IEMEK Journal of Embedded Systems and Applications
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• 제17권5호
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• pp.273-280
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• 2022

Along with the advancement of deep learning technology, securing high-quality dataset for verification of developed technology is emerging as an important issue, and developing robust deep learning models to the domestic road environment is focused by many research groups. Especially, unlike expressways and automobile-only roads, in the complex city driving environment, various dynamic objects such as motorbikes, electric kickboards, large buses/truck, freight cars, pedestrians, and traffic lights are mixed in city road. In this paper, we built our dataset through multi camera-based processing (collection, refinement, and annotation) including the various objects in the city road and estimated quality and validity of our dataset by using YOLO-based model in object detection. Then, quantitative evaluation of our dataset is performed by comparing with the public dataset and qualitative evaluation of it is performed by comparing with experiment results using open platform. We generated our 2D dataset based on annotation rules of KITTI/COCO dataset, and compared the performance with the public dataset using the evaluation rules of KITTI/COCO dataset. As a result of comparison with public dataset, our dataset shows about 3 to 53% higher performance and thus the effectiveness of our dataset was validated.

• Educational Technology International
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• 제25권1호
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• pp.27-65
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• 2024

The purpose of this study was to identify differences in learning patterns according to content complexity in video-based learning environments and to derive variables that have an important effect on learning achievement within particular learning contexts. To achieve our aims, we observed and collected data on learners' cognitive processes through perceived affordances, using behavioral logs and eye movements as specific indicators. These two types of reaction data were collected from 67 male and female university students who watched two learning videos classified according to their task complexity through the video learning player. The results showed that when the content complexity level was low, learners tended to navigate using other learners' digital logs, but when it was high, students tended to control the learning process and directly generate their own logs. In addition, using derived prediction models according to the degree of content complexity level, we identified the important variables influencing learning achievement in the low content complexity group as those related to video playback and annotation. In comparison, in the high content complexity group, the important variables were related to active navigation of the learning video. This study tried not only to apply the novel variables in the field of educational technology, but also attempt to provide qualitative observations on the learning process based on a quantitative approach.

• The Korean Fashion and Textile Research Journal
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• 제26권4호
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• pp.353-365
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• 2024

Despite the growing importance of corporate social responsibility (CSR) in the apparel industry, most existing research focuses on the CSR activities of well-known apparel brands and retailers, not manufacturers. The purpose of this study was to examine the CSR activities of global apparel manufacturers using the two most widely accepted global CSR frameworks: the United Nations' Sustainable Development Goals (SDGs) and Global Reporting Initiative (GRI) standards. A comparison was employed based on the legitimacy theory. For this purpose, a content analysis was conducted on five apparel manufacturers' CSR activities disclosed in their annual sustainability reports published on the firms' official websites. The analysis was both quantitative (frequency) and qualitative (intensity). The results revealed that all firms conducted CSR activities related to environmental and social activities more actively than they conducted economic activities, with higher frequency and intensity scores for both the GRI and SDGs. However, based on each firm's economic development level, size, and years of experience, their applications of resources/technology to CSR and approaches to certain issues (e.g., gender and diversity issues) differed, supporting the legitimacy theory. The results provide academic implications by providing empirical information on apparel manufacturers' CSR activities as well as practical implications for other manufacturers seeking to develop CSR programs that meet the global standards.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제47권2호
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• pp.57-64
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• 2024

The use of big data needs to be emphasized in policy formulation by public officials in order to improve the transparency of government policies and increase efficiency and reliability of government policies. 'Hye-Ahn', a government-wide big data platform was built with this goal, and the subscribers of 'Hye-Ahn' has grown significantly from 2,000 at the end of 2016 to 100,000 at August 2018. Additionally, the central and local governments are expanding their big data related budgets. In this study, we derived the costs and benefits of 'Hye-Ahn' and used them to conduct an economic feasibility analysis. As a result, even if only some quantitative benefits are considered without qualitative benefits, the net present value, the benefit/cost, and internal rate of return turned out to be 22,662 million won, 2.3213, and 41.8%, respectively. Since this is larger than the respective comparison criteria of 0 won, 1.0, and 5.0%, it can be seen that 'Hye-Ahn' has had economic feasibility. As noticed earlier, the number of analysis using 'Hye-Ahn' is increasing, so it is expected that the benefits will increase as time passes. Finally, the socioeconomic value gained when the results of analysis using 'Hye-Ahn' are used in policy is expected to be significant.

• Journal of Energy Engineering
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• 제16권3호
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• pp.93-102
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• 2007

This paper presents a scenario evaluation model of the AHP (Analytic Hierarchy Process) to evaluate dismantling scenarios considering quantitative and qualitative considerations. And decommissioning information producing modules which can obtain a dismantling schedule, quantify radioactive waste, visualize a radioactive inventory, estimate a decommissioning cost, and estimate a worker's exposure was developed to assess qualitatively decommissioning information. The digital mock-up (DMU) system was developed to verify dismantling processes and find error of scenarios in virtual space. It combines and manages the decommissioning information producing modules, the decommissioning DB, and the dismantling evaluation module synthetically. By using AHP model and DMU system, the thermal column in KRR-1 was evaluated on plasma arc cutting scenario and nibbler cutting scenario using the developed decommissioning DMU system.