• Korean Journal of Optics and Photonics
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• v.35 no.4
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• pp.150-156
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• 2024

One of the key factors in research regarding long-distance laser beam propagation, as in free-space optical communication or laser power transmission, is the transmission efficiency of the laser beam. As a way to improve efficiency, we perform extensive numerical simulations of the effect of modifying the laser beam's profile, especially replacing the fundamental Gaussian beam with a super-Gaussian beam. Numerical simulations of the transmitted power in the ideal diffraction-limited beam diameter determined by the optical system of the transmitter, after about 1-km propagation, reveal that the second-order super-Gaussian beam can yield superior performance to that of the fundamental Gaussian beam, in both single-channel and coherently combined multi-channel laser transmitters. The improvement of the transmission efficiency for a 1-km propagation distance when using a second-order super-Gaussian beam, in comparison with a fundamental Gaussian beam, is estimated at over 1.2% in the singlechannel laser transmitter, and over 4.2% and over 4.6% in coherently combined 3- and 7-channel laser transmitters, respectively. For a range of the propagation distance varying from 750 to 1,250 m, the improvement in transmission efficiency by use of the second-order super-Gaussian beam is estimated at over 1.2% in the single-channel laser transmitter, and over 4.1% and over 4.0% in the coherently combined 3- and 7-channel laser transmitters, respectively. These simulation results will pave the way for future advances in the generation of higher-order super-Gaussian beams and the development of long-distance optical energy-transfer technology.

• Journal of The Korean Institute of Defense Technology
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• v.5 no.3
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• pp.8-17
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• 2023

The current weapon system is operated as a complex weapon system with various standards and protocols applied, so there is a risk of failure in smooth information exchange during combined and joint operations on the battlefield. The interoperability of weapon systems to carry out precise strikes on key targets through rapid situational judgment between weapon systems is a key element in the conduct of war. Since the Korean military went into service, there has been a need to change the configuration and improve performance of a large number of software and hardware, but there is no verification system for the impact on interoperability, and there are no related test tools and facilities. In addition, during combined and joint training, errors frequently occur during use after arbitrarily changing the detailed operation method and software of the weapon/power support system. Therefore, periodic verification of interoperability between weapon systems is necessary. To solve this problem, rather than having people schedule an evaluation period and conduct the evaluation once, AI should continuously evaluate the interoperability between weapons and power support systems 24 hours a day to advance warfighting capabilities. To solve these problems, To this end, preliminary research was conducted to improve defense interoperability capabilities by applying natural language processing techniques (①Word2Vec model, ②FastText model, ③Swivel model) (using published algorithms and source code). Based on the results of this experiment, we would like to present a methodology (automated evaluation of interoperability requirements evaluation / level measurement through natural language processing model) to implement an automated defense interoperability evaluation tool without relying on humans.

• Journal of Platform Technology
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• v.11 no.5
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• pp.59-71
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• 2023

This paper proposes a method of estimating the illumination chromaticity of a scene in which an image is taken. Storring and Bianco proposed a method of estimating illuminant chromaticity using skin color. Storring et al. used skin color distribution characteristics and black body locus, but there is a problem that the link between the locus and CIE-xy data is reduced. Bianco et al. estimated the illuminant chromaticity by comparing the skin color distribution in standard lighting with the skin color distribution in the input image. This method is difficult to measure and secure as much skin color as possible in various illumination. The proposed method can estimate the illuminant chromaticity for any input image by analyzing the relationship between the skin color information and the illuminant chromaticity. The estimation method is divided into an analysis stage and a test stage, and the data set was classified into an analysis group and a test group and used. Skin chromaticity is calculated by obtaining skin color areas from all input images of the analysis group, respectively. A mapping is obtained by analyzing the correlation between the average set of skin chromaticity and the reference illuminant chromaticity set. The calculated mapping is applied to all input images of the analysis group to estimate the illuminant chromaticity, calculate the error with the reference illuminant chromaticity, and repeat the above process until there is no change in the error to obtain a stable mapping. The obtained mapping is applied to the test group images similar to the analysis stage to estimate the illuminant chromaticity. Since there is no independent data set containing skin area and illuminant reference information, the experimental data set was made using some of the images of the Intel TAU data set. Compared to Finlayson, a similar theory-based existing method, it showed performance improvement of more than 40%, Zhang 11%, and Kim 16%.

• The Journal of Bigdata
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• v.8 no.2
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• pp.73-82
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• 2023

With 78% of current fisheries workers being elderly, there's a pressing need to address labor shortages. Consequently, active research on smart aquaculture technologies, centered on object detection and tracking algorithms, is underway. These technologies allow for fish size analysis and behavior pattern forecasting, facilitating the development of real-time monitoring and automated systems. Our study utilized video data from cameras outside aquaculture facilities and implemented fish detection and tracking algorithms. We aimed to tackle high maintenance costs due to underwater conditions and camera corrosion from ammonia and pH levels. We evaluated the performance of a real-time system using YOLOv7 for fish detection and the SORT algorithm for movement tracking. YOLOv7 results demonstrated a trade-off between Recall and Precision, minimizing false detections from lighting, water currents, and shadows. Effective tracking was ascertained through re-identification. This research holds promise for enhancing smart aquaculture's operational efficiency and improving fishery facility management.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.99-107
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• 2024

While the demand for extrapolating video content horizontally or vertically is increasing, even the most advanced techniques cannot successfully extrapolate all videos. Therefore, it is important to determine if a given video can be well extrapolated before attempting the actual extrapolation. This can help avoid wasting computing resources. This paper proposes a video classifier that can identify if a video is suitable for horizontal extrapolation. The classifier utilizes optical flow and an adaptive Gaussian blur network, which can be applied to flow-based video extrapolation methods. The labeling for training was rigorously conducted through user tests and quantitative evaluations. As a result of learning from this labeled dataset, a network was developed to determine the extrapolation capability of a given video. The proposed classifier achieved much more accurate classification performance than methods that simply use the original video or fixed blur alone by effectively capturing the characteristics of the video through optical flow and adaptive Gaussian blur network. This classifier can be utilized in various fields in conjunction with automatic video extrapolation techniques for immersive viewing experiences.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.23-41
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• 2024

Recently, various virtual avatar music content that showcases singing and dancing have been produced, and as virtual artists gain popularity, offline virtual avatar concerts have also emerged. However, there are few examples of virtual avatar band content where avatars play instruments. In addition, offline virtual avatar concerts using large screens at the front are limited in their ability to utilize the fantastical effects and high degree of freedom unique to virtual reality. In this paper, inspired by these limitations of virtual avatar music content, we introduce the production case of virtual avatar band content and immersive interactive concert of virtual band idol Verse'day. Firstly, we present a case study on creating band performance animations and music videos using motion capture systems and real-time engines. Then, we introduce a production case of an immersive interactive concert using projection mapping technology and a light stick that allows real-time interaction in an offline concert. Finally, based on these production cases, we discussed the future research directions of developing virtual avatar music content creation. We expect that our production cases will inspire the creation of diverse virtual avatar music content and the development of immersive interactive offline virtual avatar concerts in the future.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.81-86
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• 2024

The Image Signal Processor (ISP) converts RAW images captured by the camera sensor into user-preferred sRGB images. While RAW images contain more meaningful information for image processing than sRGB images, RAW images are rarely shared due to their large sizes. Moreover, the actual ISP process of a camera is not disclosed, making it difficult to model the inverse process. Consequently, research on learning the conversion between sRGB and RAW has been conducted. Recently, the ParamISP[1] model, which directly incorporates camera parameters (exposure time, sensitivity, aperture size, and focal length) to mimic the operations of a real camera ISP, has been proposed by advancing the simple network structures. However, existing studies, including ParamISP[1], have limitations in modeling the camera ISP as they do not consider the degradation caused by lens shading, optical aberration, and lens distortion, which limits the restoration performance. This study introduces Positional Encoding to enable the camera ISP neural network to better handle degradations caused by lens. The proposed positional encoding method is suitable for camera ISP neural networks that learn by dividing the image into patches. By reflecting the spatial context of the image, it allows for more precise image restoration compared to existing models.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.711-719
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• 2024

This study examined the policy of opening up the Chinese A-share market and its performance in four aspects: institutional investors system, cross-trading system with overseas stock markets, inclusion of A-shares into global indices, and establishment of a new board. Then, the impact of these policies on the Stock Index was empirically analyzed, and it was confirmed that institutional investors system such as QFII and RQFII, cross-trading system with overseas stock markets such as Shanghai-Hong Kong Stock Connect and Shenzhen-Hong Kong Stock Connect, inclusion of A-shares into global indices such as the MSCI EM index and FTSE Russell index, and the establishment of a new board of the Science Innovation Board all had statistically significant positive impacts on the stock index. Based on the results of these analysis, we conclude that China should further expand its stock market opening to the outside world, that mutual efforts are needed to alleviate political conflicts and improve understanding, and that easing industry regulations, including real estate, will help China's economic recovery and foreigners' investment in the A-share market.

• Korean Journal of Radiology
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• v.25 no.7
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• pp.613-622
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• 2024

Objective: In Korea, radiology has been positioned towards the early adoption of artificial intelligence-based software as medical devices (AI-SaMDs); however, little is known about the current usage, implementation, and future needs of AI-SaMDs. We surveyed the current trends and expectations for AI-SaMDs among members of the Korean Society of Radiology (KSR). Materials and Methods: An anonymous and voluntary online survey was open to all KSR members between April 17 and May 15, 2023. The survey was focused on the experiences of using AI-SaMDs, patterns of usage, levels of satisfaction, and expectations regarding the use of AI-SaMDs, including the roles of the industry, government, and KSR regarding the clinical use of AI-SaMDs. Results: Among the 370 respondents (response rate: 7.7% [370/4792]; 340 board-certified radiologists; 210 from academic institutions), 60.3% (223/370) had experience using AI-SaMDs. The two most common use-case of AI-SaMDs among the respondents were lesion detection (82.1%, 183/223), lesion diagnosis/classification (55.2%, 123/223), with the target imaging modalities being plain radiography (62.3%, 139/223), CT (42.6%, 95/223), mammography (29.1%, 65/223), and MRI (28.7%, 64/223). Most users were satisfied with AI-SaMDs (67.6% [115/170, for improvement of patient management] to 85.1% [189/222, for performance]). Regarding the expansion of clinical applications, most respondents expressed a preference for AI-SaMDs to assist in detection/diagnosis (77.0%, 285/370) and to perform automated measurement/quantification (63.5%, 235/370). Most respondents indicated that future development of AI-SaMDs should focus on improving practice efficiency (81.9%, 303/370) and quality (71.4%, 264/370). Overall, 91.9% of the respondents (340/370) agreed that there is a need for education or guidelines driven by the KSR regarding the use of AI-SaMDs. Conclusion: The penetration rate of AI-SaMDs in clinical practice and the corresponding satisfaction levels were high among members of the KSR. Most AI-SaMDs have been used for lesion detection, diagnosis, and classification. Most respondents requested KSR-driven education or guidelines on the use of AI-SaMDs.

• Journal of the Korea Institute of Building Construction
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• v.24 no.4
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• pp.447-458
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• 2024

This study investigates the effectiveness of Building Information Modeling(BIM) software, specifically SketchUp and Revit, in reducing errors during quantity take-off(QTO) for complex building elements. While 3D modeling offers advantages, existing software may not fully account for manufacturing discrepancies, such as variations in concrete cover thickness and reinforcing bar radius. To address this limitation, this research proposes a BIM-based QTO method for high-insulation wall panels with intricate details. The method utilizes a BIM family library, focusing on key parameters like concrete cover thickness and inner radius of shear reinforcement. A case study compared the cross-sectional details of a wall panel modeled in Revit with the actual manufactured specimen. The analysis revealed a 12% reduction in modeled concrete cover thickness and a 1.27 times larger modeled inner radius of the shear bar compared to the real-world values. The proposed method incorporates these manufacturing variations into the Revit model of the high-insulation wall panel. Software like Navisworks facilitates the identification and correction of any material interferences arising from these adjustments. Furthermore, the method employs a unit wall concept(1m²) to account for the volume of various materials, including insulation and splice sleeves at joints. This allows for the identification of a similar existing family within the BIM library(e.g., "Double RC wall with embedded insulation") that reflects the actual material quantities used in the wall panel. By incorporating these manufacturing-induced variations, the proposed method offers a more accurate QTO process for complex high-insulation wall panels. The "Double RC wall with embedded insulation" family within the Revit program serves as a valuable tool for material quantity estimation in such scenarios.