• Journal of the Korea Society of Computer and Information
• /
• v.27 no.6
• /
• pp.43-52
• /
• 2022

We can sense somebody's feeling fatigue, which means that fatigue can be detected through sensing human biometric signals. Numerous researches for assessing fatigue are mostly focused on diagnosing the edge of disease-level fatigue. In this study, we adapt quantitative analysis approaches for estimating qualitative data, and propose video analysis models for measuring fatigue state. Proposed three deep-learning based classification models selectively include stages of video analysis: object detection, feature extraction and time-series frame analysis algorithms to evaluate each stage's effect toward dividing the state of fatigue. Using frontal face videos collected from various fatigue situations, our CNN model shows 0.67 accuracy, which means that we empirically show the video analysis models can meaningfully detect fatigue state. Also we suggest the way of model adaptation when training and validating video data for classifying fatigue.

• The Research Journal of the Costume Culture
• /
• v.30 no.4
• /
• pp.608-630
• /
• 2022

The purpose of this study is to examine the relationships between citations and the research trends of The Research Journal of the Costume Culture (RJCC) using bibliometric and network analyses. The results are as follows. First, the RJCC has been cited by a greater number of journals and high-reputation journals today. The RJCC has been mentioned in global academic journals in various fields, and it has been noted the most in environmental science. Second, because of examining the articles published in the RJCC over the past three years (2019 - 2021), it was found that the number of topics was evenly distributed in various subfields of the clothing and textiles sector. The RJCC principally deals with traditional clothing, ethics and sustainability, and technology, which means that the RJCC reflects the past, present, and future. As a result of conducting a cluster analysis using the Wakita-Tsurumi algorithm, the subjects of ethical fashion and sustainability were derived from the subdivisions of the RJCC. This suggests that the RJCC is a journal specialized in ethical fashion and sustainability sectors such as environmental, animal, and labor ethics. This study outlined the current status and future direction of academic journals in the field of clothing through an analysis of the RJCC's influence change and the relationship between citations. In addition, it is academically significant because it identifies research trends and knowledge-structure changes in the apparel science field by identifying changes in research keywords and significant research topics by sector.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.12-12
• /
• 2023

지하수자원 관리의 정량적 및 정성적 측면에 있어, 최첨단 인공지능 언어 모델인 ChatGPT의 혁신적인 기능이 활용될 수 있다. 본 발표에서는 지하수 자료에 대한 분석과 도출된 문제의 중요도에 따른 목표를 설정, 그리고 지하수 관리 전략 개발에 있어서의 ChatGPT 활용 방법을 논의할 것이다. 이를 위한 구체적 사례로, 지하수자원 관리에 활용될 수 있는 다양한 도구들의 개발과 고도화에 ChatGPT가 기여하는 방식을 살펴볼 것이다. 이러한 개별 도구들은 지하수자원 관리 결정에 있어 더 나은 예측 및 평가를 제공하여, 지하수 자원 관리의 효율성을 도모할 수 있다. 또한, ChatGPT의 문제 발견 및 해결책 제안 능력에 대해서도 다룰 것이다. 이를 통해 지하수 관리에 있어서의 다양한 문제를 식별하고, 이해당사자들이 보다 효과적으로 대응할 수 있는 방안을 찾아낼 수 있을 것이다. 또한 ChatGPT가 제공하는 다양한 정보 및 문제에 대한 솔루션 접근 방식을 활용한 브레인스토밍 방법을 설명할 것이다. 추가적으로, 일반 인공지능(AGI)의 개발에 근접하면서 지하수 관리의 자동화 및 가속화 그리고 산업 및 환경에 미칠 수 있는 영향에 대해 고찰해 볼 것이다. 이를 위하여, ChatGPT와 같은 인공지능 기술이 더욱 고도화되고 향상되면서, 지하수 관리 및 관련 분야에서의 의사결정, 계획 수립, 그리고 모니터링과 같은 작업들이 어떻게 변화할지에 대하여 토의할 것이다. 본 발표는 지하수 자원 관리 분야에서 ChatGPT와 같은 인공지능 기반 접근법의 가치를 보여주며, 복잡한 지하수 환경 문제를 해결하는 데 있어 첨단 기술의 활용 가능성을 강조할 것이다. 또한, AGI가 등장할 때까지 여전히 요구되는 지하수 분야 도메인 지식과 전문기술의 중요성을 강조할 것이다. 지하수 관리자들의 도메인 지식과 전문적 기술은 인공지능 기반 도구와 결합되어 보다 정확한 분석, 예측 및 해결책 도출을 가속화하며 정교화할 것이다. 결론적으로, 지하수 관리에 대한 종합적인 이해와 전문성을 갖춘 전문가들의 인공지능 기술활용은 지속가능한 지하수의 첨단 관리 효과적 달성에 중요한 계기가 될 것으로 판단한다.

• The Journal of the Acoustical Society of Korea
• /
• v.42 no.5
• /
• pp.422-428
• /
• 2023

Ultrafast ultrasound imaging has been applied to various imaging approaches, including shear wave elastography, ultrafast Doppler, and super-resolution imaging. However, these methods are still challenging in real-time implementation for three Dimension (3D) or portable applications because of their massive data rate required. In this paper, we proposed an adaptive quantization method that effectively reduces the data rate of large Radio Frequency (RF) data. In soft tissue, ultrasound backscatter signals require a high dynamic range, and thus typical quantization used in the current systems uses the quantization level of 10 bits to 14 bits. To alleviate the quantization level to expand the application of ultrafast ultrasound imaging, this study proposed a depth-sectional quantization approach that reduces the quantization errors. For quantitative evaluation, Field II simulations, phantom experiments, and in vivo imaging were conducted and CNR, spatial resolution, and SSIM values were compared with the proposed method and fixed quantization method. We demonstrated that our proposed method is capable of effectively reducing the quantization level down to 3-bit while minimizing the image quality degradation.

• Fisheries and Aquatic Sciences
• /
• v.26 no.3
• /
• pp.188-203
• /
• 2023

Lysozymes are well-known antibacterial enzymes that mainly target the peptidoglycan layer of the bacterial cell wall. Animal lysozymes are mainly categorized as g-type, c-type, and i-type based on protein sequence and structural differences. In this study, c-type (AcLysC) and g-like-type (AcLysG-like) lysozymes from Amphiprion clarkii were characterized in silico via expressional and functional approaches. According to in silico analysis, open reading frames of AcLysC and AcLysG-like were 429 bp and 570 bp, respectively, encoding the corresponding polypeptide chains with 142 and 189 amino acids. Elevated expression levels of AcLysC and AcLysG-like were observed in the liver and the heart tissues, respectively, as evidenced by quantitative real-time polymerase chain reaction assays. AcLysC and AcLysG-like transcript levels were upregulated in gills, head kidney, and blood cells following experimental immune stimulation. Recombinant AcLysC exhibited potent lytic activity against Vibrio anguillarum, whereas recombinant AcLysG-like showed remarkable antibacterial activity against Vibrio harveyi and Streptococcus parauberis, which was further evidenced by scanning electron microscopic imaging of destructed bacterial cell walls. The findings of this study collectively suggest the potential roles of AcLysC and AcLysG-like in host immune defense.

• Journal of Veterinary Science
• /
• v.23 no.1
• /
• pp.3.1-3.12
• /
• 2022

Background: Domestic yaks are the most important livestock species on the Qinghai-Tibetan Plateau. Adult female yaks normally breed in the warm season (July to September) and enter anestrous in the cold season (November to April). Nevertheless, it is unclear how ovarian activity is regulated at the molecular level. Objectives: The peculiarities of yak reproduction were assessed to explore the molecular mechanism of postpartum anestrus ovaries in yaks after pregnancy and parturition. Methods: Sixty female yaks with calves were observed under natural grazing in Haiyan County, Qinghai Province. Three yak ovaries in pregnancy and postpartum anestrus were collected. RNA sequencing and quantitative proteomics were employed to analyze the pregnancy and postpartum ovaries after hypothermia to identify the genes and proteins related to the postpartum ovarian cycle. Results: The results revealed 841 differentially expressed genes during the postpartum hypoestrus cycle; 347 were up-regulated and 494 genes were down-regulated. Fifty-seven differential proteins were screened: 38 were up-regulated and 19 were down-regulated. The differential genes and proteins were related to the yak reproduction process, rhythm process, progesterone-mediated oocyte maturation, PI3K/AKT signaling pathway, and MAPK signaling pathway categories. Conclusions: Transcriptome and proteomic sequencing approaches were used to investigate postpartum anestrus and pregnancy ovaries in yaks. The results confirmed that BHLHE40, SF1IX1, FBPX1, HSPCA, LHCGR, BMP15, and ET-1R could affect postpartum hypoestrus and control the state of estrus.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.1
• /
• pp.1-12
• /
• 2023

It is very time-intensive to obtain data with labels on anomaly detection tasks for multivariate time series. Therefore, several studies have been conducted on unsupervised learning that does not require any labels. However, a well-done integrative survey has not been conducted on in-depth discussion of learning architecture and property for multivariate time series anomaly detection. This study aims to explore the characteristic of well-known architectures in anomaly detection of multivariate time series. Additionally, architecture was categorized by using top-down and bottom-up approaches. In order toconsider real-world anomaly detection situation, we trained models with dataset such as power grids or Cyber Physical Systems that contains realistic anomalies. From experimental results, we compared and analyzed the comprehensive performance of each architecture. Quantitative performance were measured using precision, recall, and F1 scores.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.4C
• /
• pp.255-264
• /
• 2006

The auxiliary reinforcement method is normally applied to prevent a possible collapse of the tunnel face where the ground condition is not favorable or geologic information is not sufficient. Recently, several engineering approaches have been made to choose the effective reinforcement methods using expert system such as neural network and fuzzy theory field, among others. Even if the expert system has offered many decision aid tools to properly select the reinforcement method, the quantitative assessment items are not easy to estimate and this is why the data mining technique, widely used in the field of social science, medical treatment, banking and agriculture, is introduced in this study. Using decision tree together with PDA, the decision aids for reinforcement method based on field construction data are created to derive the field rules and future study will be concentrated on the application of the proposed methods in a variety of underground development cases.

• Structural Engineering and Mechanics
• /
• v.87 no.3
• /
• pp.221-229
• /
• 2023

Urbanization and industrialization have significantly increased the amount of solid waste produced in recent decades, posing considerable disposal problems and environmental burdens. The practice of waste utilization in concrete has gained popularity among construction practitioners and researchers for the efficient use of resources and the transition to the circular economy in construction. This study employed Lytag aggregate, an environmentally friendly pulverized fuel ash-based lightweight aggregate, as a substitute for natural coarse aggregate. At the same time, fly ash, an industrial by-product, was used as a partial substitute for cement. Concrete mix M20 was experimented with using fly ash and Lytag lightweight aggregate. The percentages of fly ash that make up the replacements were 5%, 10%, 15%, 20%, and 25%. The Compressive Strength (CS), Split Tensile Strength (STS), and deflection were discovered at these percentages after 56 days of testing. The concrete cube, cylinder, and beam specimens were examined in the explorations, as mentioned earlier. The results indicate that a 10% substitution of cement with fly ash and a replacement of coarse aggregate with Lytag lightweight aggregate produced concrete that performed well in terms of mechanical properties and deflection. The cementitious composites have varying characteristics as the environment changes. Therefore, understanding their mechanical properties are crucial for safety reasons. CS, STS, and deflection are the essential property of concrete. Machine learning (ML) approaches have been necessary to predict the CS of concrete. The Artificial Fish Swarm Optimization (AFSO), Particle Swarm Optimization (PSO), and Harmony Search (HS) algorithms were investigated for the prediction of outcomes. This work deftly explains the tremendous AFSO technique, which achieves the precise ideal values of the weights in the model to crown the mathematical modeling technique. This has been proved by the minimum, maximum, and sample median, and the first and third quartiles were used as the basis for a boxplot through the standardized method of showing the dataset. It graphically displays the quantitative value distribution of a field. The correlation matrix and confidence interval were represented graphically using the corrupt method.

• Korean Journal of Culture and Social Issue
• /
• v.22 no.2
• /
• pp.165-182
• /
• 2016

Happiness research has primarily been conducted based on the American model of happiness. The agentic concept of happiness in the West emphasizes the positive feeling state stemming from individual achievement and positive interpersonal relationships. However, previous studies on lay theories of happiness in other East Asian countries, such as China and Japan, have suggested that these meanings of happiness differ from those of the Western cultural context. The present study examined the lay theory of happiness among Koreans using qualitative and quantitative approaches. Furthermore, the authors compared the Korean model of happiness with that of the Japanese and Americans from Uchida and Kitayama (2009). The findings from the present research indicate that the Korean model of happiness involves both positive and negative states and consequences of happiness, unlike the uniformly positively connoted happiness in Western cultural contexts. The paper concludes with a discussion of the implications of the current findings on happiness research in the Korean culture.