• The Korea Journal of Herbology
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• v.34 no.2
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• pp.33-39
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• 2019

Objectives : The pores are the openings of sebaceous glands or apocrine glands. They are enlarged by various factors such as sex, age, genetic influence, sebum secretion, acne and so on. When the pores are visually recognizable, they become aesthetically problematic. There are various methods of treating pores, but we have tried to develop a method to reduce pore size by using daily cleanser. Methods : Facial skin examination was performed on 104 students of A university. Among them, 10 persons with large pore size were selected. We surveyed 72 students to determine their subjective skin condition, lifestyle, and washing habits etc. We made herbal fermented soaps using Seosiokyongsan and distributed them to experiment participants. We let them wash their face in the morning and evening for 6 weeks using herbal fermented soap. Prior to the experiment, their skin condition was checked and assessed using A-ONE Smart One-Click Automatic Facial Diagnosis System three times at 3-week intervals. After the experiment, the changes of skin were measured and analyzed through facial analysis test. Results : In our experiment, the early 20s, 9.6% of the students had slightly larger pores. For students with large pores, there was a high likelihood of side effects from using facial products. Using the fermented soap made of Seosiokyongsan, the average size of the pores and the number of large-sized pores were significantly reduced. Conclusion : Seosiokyongsan fermented soap can effectively reduce especially the large size of pores.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.617-624
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• 2022

The small electric vehicles equipped with V2X(vehicle to everything) systems may provide more information and function to the existing navigation system of the vehicle. The key components of V2X technology include V2V (vehicle to vehicle), V2N(vehicle to network) and V2I (vehicle to infrastructure). This study is to design and implementation of VI type E-PTO which is interfaced with external equipments, the work designs the components of E-PTO such as DC/DC converter, DC/AC converter, battery bidirectional charging system etc. Also, it implements the devices and control systems for driving. The test results of VI type E-PTO components showed allowable 10% requirements of transient voltage variation rate and recovery time within 100ms for start/stop and normal operation.

• Journal of Drive and Control
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• v.19 no.1
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• pp.43-50
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• 2022

The aim of this study was to conduct basic research on the development of a dual-clutch transmission(DCT) and automatic transmission for agricultural tractors. The DCT layout and the DCT simulation model were developed using commercial software. Power transmission efficiency of the DCT and component power loss were analyzed to verify the developed simulation model. Power loss analysis of the components was conducted according to previous studies and ISO(International Organization for Standardization) standards. The power transmission efficiency of the DCT simulation model was 68.4-91.5% according to the gear range. The power loss in the gear, bearing, and clutch DCT system components was 0.75-1.49 kW, 0.77-2.99 kW, and 5.24-10.52 kW, respectively. The developed simulation model not include the rear axle, differential gear, final reduction gear. Therefore actual power transmission efficiency of DCT will be decreased. In a future study, an actual DCT can be developed through the simulation model in this study, and optimization design of DCT can be possible by comparing simulation results and actual vehicle test.

• Korean Journal of Veterinary Service
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• v.46 no.1
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• pp.29-34
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• 2023

Mycobacterium tuberculosis complex (M. tuberculosis complex) is a causative agent of contagious chronic disease in a wide range of mammalian hosts, mainly cattle, goat, pigs, wildlife, and humans. The definite diagnosis of tuberculosis is made based on culture of M. tuberculosis, but it takes a long time. In the present study, we analyzed whether the detection time of M. tuberculosis could be reduced when cultured in the medium containing the culture-promoting ingredients-107 (CPI-107) using the BacT/Alert 3D system, an automatic culture system. The time to detection (TTD) tended to decrease as the added concentration of CPI-107 increase. In the case of low numbers of M. tuberculosis, it decreased by 21.0% at 1.2 mg/mL of CPI-107 and by 15.9% in the case of high numbers of M. tuberculosis. In the culture using clinically isolated M. tuberculosis strains, the shortening of the culture time by CPI was more evident. In conclusion, the detection time of M. tuberculosis was shortened in the medium added with CPI-107, and this could be used for isolation, culture and drug susceptibility test of M. tuberculosis.

• Journal of Animal Science and Technology
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• v.65 no.3
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• pp.588-595
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• 2023

The aim of this study was to investigate the effects of heat stress on milk traits in South Korea using comprehensive data (dairy production and climate). The dataset for this study comprised 1,498,232 test-day records for milk yield, fat- and protein-corrected milk, fat yield, protein yield, milk urea nitrogen (MUN), and somatic cell score (SCS) from 215,276 Holstein cows (primiparous: n = 122,087; multiparous: n = 93,189) in 2,419 South Korean dairy herds. Data were collected from July 2017 to April 2020 through the Dairy Cattle Improvement Program, and merged with meteorological data from 600 automatic weather stations through the Korea Meteorological Administration. The segmented regression model was used to estimate the effects of the temperature-humidity index (THI) on milk traits and elucidate the break point (BP) of the THI. To acquire the least-squares mean of milk traits, the generalized linear model was applied using fixed effects (region, calving year, calving month, parity, days in milk, and THI). For all parameters, the BP of THI was observed; in particular, milk production parameters dramatically decreased after a specific BP of THI (p < 0.05). In contrast, MUN and SCS drastically increased when THI exceeded BP in all cows (p < 0.05) and primiparous cows (p < 0.05), respectively. Dairy cows in South Korea exhibited negative effects on milk traits (decrease in milk performance, increase in MUN, and SCS) when the THI exceeded 70; therefore, detailed feeding management is required to prevent heat stress in dairy cows.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.55-67
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• 2023

Lightweight face recognition models, as one of the most popular and long-standing topics in the field of computer vision, has achieved vigorous development and has been widely used in many real-world applications due to fewer number of parameters, lower floating-point operations, and smaller model size. However, few surveys reviewed lightweight models and reimplemented these lightweight models by using the same calculating resource and training dataset. In this survey article, we present a comprehensive review about the recent research advances on the end-to-end efficient lightweight face recognition models and reimplement several of the most popular models. To start with, we introduce the overview of face recognition with lightweight models. Then, based on the construction of models, we categorize the lightweight models into: (1) artificially designing lightweight FR models, (2) pruned models to face recognition, (3) efficient automatic neural network architecture design based on neural architecture searching, (4) Knowledge distillation and (5) low-rank decomposition. As an example, we also introduce the SqueezeFaceNet and EfficientFaceNet by pruning SqueezeNet and EfficientNet. Additionally, we reimplement and present a detailed performance comparison of different lightweight models on the nine different test benchmarks. At last, the challenges and future works are provided. There are three main contributions in our survey: firstly, the categorized lightweight models can be conveniently identified so that we can explore new lightweight models for face recognition; secondly, the comprehensive performance comparisons are carried out so that ones can choose models when a state-of-the-art end-to-end face recognition system is deployed on mobile devices; thirdly, the challenges and future trends are stated to inspire our future works.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.93-104
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• 2023

Recently, the technology of drones is developing remarkably. The role of military drones is so great that they can cause serious damage to the enemy's important strategic assets without any damage to our allies in all battlefield environments (land, sea, air). However, the battleship combat management system currently operated by the Korean Navy is vulnerable to defense because there is no customized defense system against drones. As drones continue to develop, they are bound to pose a major threat to navy in the future. This paper proposes a way for the warfare software of naval combat management system sets a combat mode suitable for anti-drone battle, evaluates the threat priority in order to preemptively respond to drone threats and eliminate drone threats through automatic allocation of self-ship-mounted weapons and sensors, and through a test of the improved warfare software in a simulated environment, it was proved that the time to respond to the drone was improved by 62%.

• Journal of Korean Society for Quality Management
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• v.51 no.2
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• pp.283-296
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• 2023

Purpose: The purpose of this study is to actually implement and verify whether welding defects can be detected in real time by utilizing deep learning AI solutions in the welding process of electric vehicle hairpin winding motors. Methods: AI's function and technological elements using synthetic neural network were applied to existing electric vehicle hairpin winding motor laser welding process by making special hardware for detecting electric vehicle hairpin motor laser welding defect. Results: As a result of the test applied to the welding process of the electric vehicle hairpin winding motor, it was confirmed that defects in the welding part were detected in real time. The accuracy of detection of welds was achieved at 0.99 based on mAP@95, and the accuracy of detection of defective parts was 1.18 based on FB-Score 1.5, which fell short of the target, so it will be supplemented by introducing additional lighting and camera settings and enhancement techniques in the future. Conclusion: This study is significant in that it improves the welding quality of hairpin winding motors of electric vehicles by applying domestic artificial intelligence solutions to laser welding operations of hairpin winding motors of electric vehicles. Defects of a manufacturing line can be corrected immediately through automatic welding inspection after laser welding of an electric vehicle hairpin winding motor, thus reducing waste throughput caused by welding failure in the final stage, reducing input costs and increasing product production.

• Korean Journal of Cognitive Science
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• v.34 no.3
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• pp.197-226
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• 2023

Generative Text Summarization is one of the Natural Language Processing tasks. It generates a short abbreviated summary while preserving the content of the long text. ROUGE is a widely used lexical-overlap based metric for text summarization models in generative summarization benchmarks. Although it shows very high performance, the studies report that 30% of the generated summary and the text are still inconsistent. This paper proposes a methodology for evaluating the performance of the summary model without using the correct summary. AggreFACT is a human-annotated dataset that classifies the types of errors in neural text summarization models. Among all the test candidates, the two cases, generation summary, and when errors occurred throughout the summary showed the highest correlation results. We observed that the proposed evaluation score showed a high correlation with models finetuned with BART and PEGASUS, which is pretrained with a large-scale Transformer structure.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.51-60
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• 2024

Aiming at the problem of low contrast and difficult to recognize video images in low-light environment, we propose an adaptive contrast compensation enhancement algorithm based on human visual perception. First of all, the video image characteristic factors in low-light environment are extracted: AL (average luminance), ABWF (average bandwidth factor), and the mathematical model of human visual CRC(contrast resolution compensation) is established according to the difference of the original image's grayscale/chromaticity level, and the proportion of the three primary colors of the true color is compensated by the integral, respectively. Then, when the degree of compensation is lower than the bright vision precisely distinguishable difference, the compensation threshold is set to linearly compensate the bright vision to the full bandwidth. Finally, the automatic optimization model of the compensation ratio coefficient is established by combining the subjective image quality evaluation and the image characteristic factor. The experimental test results show that the video image adaptive enhancement algorithm has good enhancement effect, good real-time performance, can effectively mine the dark vision information, and can be widely used in different scenes.