• Title/Summary/Keyword: Validate

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Mass spectrometry-based ginsenoside profiling: Recent applications, limitations, and perspectives

  • Hyun Woo Kim;Dae Hyun Kim;Byeol Ryu;You Jin Chung;Kyungha Lee;Young Chang Kim;Jung Woo Lee;Dong Hwi Kim;Woojong Jang;Woohyeon Cho;Hyeonah Shim;Sang Hyun Sung;Tae-Jin Yang;Kyo Bin Kang
    • Journal of Ginseng Research
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    • v.48 no.2
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    • pp.149-162
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    • 2024
  • Ginseng, the roots of Panax species, is an important medicinal herb used as a tonic. As ginsenosides are key bioactive components of ginseng, holistic chemical profiling of them has provided many insights into understanding ginseng. Mass spectrometry has been a major methodology for profiling, which has been applied to realize numerous goals in ginseng research, such as the discrimination of different species, geographical origins, and ages, and the monitoring of processing and biotransformation. This review summarizes the various applications of ginsenoside profiling in ginseng research over the last three decades that have contributed to expanding our understanding of ginseng. However, we also note that most of the studies overlooked a crucial factor that influences the levels of ginsenosides: genetic variation. To highlight the effects of genetic variation on the chemical contents, we present our results of untargeted and targeted ginsenoside profiling of different genotypes cultivated under identical conditions, in addition to data regarding genome-level genetic diversity. Additionally, we analyze the other limitations of previous studies, such as imperfect variable control, deficient metadata, and lack of additional effort to validate causation. We conclude that the values of ginsenoside profiling studies can be enhanced by overcoming such limitations, as well as by integrating with other -omics techniques.

HRTF Interpolation Using a Spherical Head Model (원형 머리 모델을 이용한 머리 전달 함수의 보간)

  • Lee, Ki-Seung;Lee, Seok-Pil
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.7
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    • pp.333-341
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    • 2008
  • In this paper, a new interpolation model for the head related transfer function (HRTF) was proposed. In the method herein, we assume that the impulse response of the HRTF for each azimuth angle is given by linear interpolation of the time-delayed neighboring impulse responses of HRTFs. The time delay of the HRTF for each azimuth angle is given by sum of the sound wave propagation time from the ears to the sound source, which can be estimated by using azimuth angle, the physical shape of the underlying head and the distance between the head and sound source, and the refinement time yielding the minimum mean square error. Moreover, in the proposed model, the interpolation intervals were not fixed but varied, which were determined by minimizing the total number of HRTFs while the synthesized signals have no perceptual difference from the original signals in terms of sound location. To validate the usefulness of the proposed interpolation model, the proposed model was applied to the several HRTFs that were obtained from one dummy-head and three human heads. We used the HRTFs that have 5 degree azimuth angle resolution at 0 degree elevation (horizontal plane). The experimental results showed that using only $30\sim40%$ of the original HRTFs were sufficient for producing the signals that have no audible differences from the original ones in terms of sound location.

Research on the Development of Distance Metrics for the Clustering of Vessel Trajectories in Korean Coastal Waters (국내 연안 해역 선박 항적 군집화를 위한 항적 간 거리 척도 개발 연구)

  • Seungju Lee;Wonhee Lee;Ji Hong Min;Deuk Jae Cho;Hyunwoo Park
    • Journal of Navigation and Port Research
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    • v.47 no.6
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    • pp.367-375
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    • 2023
  • This study developed a new distance metric for vessel trajectories, applicable to marine traffic control services in the Korean coastal waters. The proposed metric is designed through the weighted summation of the traditional Hausdorff distance, which measures the similarity between spatiotemporal data and incorporates the differences in the average Speed Over Ground (SOG) and the variance in Course Over Ground (COG) between two trajectories. To validate the effectiveness of this new metric, a comparative analysis was conducted using the actual Automatic Identification System (AIS) trajectory data, in conjunction with an agglomerative clustering algorithm. Data visualizations were used to confirm that the results of trajectory clustering, with the new metric, reflect geographical distances and the distribution of vessel behavioral characteristics more accurately, than conventional metrics such as the Hausdorff distance and Dynamic Time Warping distance. Quantitatively, based on the Davies-Bouldin index, the clustering results were found to be superior or comparable and demonstrated exceptional efficiency in computational distance calculation.

Experimental study on structural integrity assessment of utility tunnels using coupled pulse-impact echo method (결합된 초음파-충격 반향 기법 기반의 일반 지하구 구조체의 건전도 평가에 관한 실험적 연구)

  • Jin Kim;Jeong-Uk Bang;Seungbo Shim;Gye-Chun Cho
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.25 no.6
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    • pp.479-493
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    • 2023
  • The need for safety management has arisen due to the increasing number of years of operated underground structures, such as tunnels and utility tunnels, and accidents caused by those aging infrastructures. However, in the case of privately managed underground utility ducts, there is a lack of detailed guidelines for facility safety and maintenance, resulting in inadequate safety management. Furthermore, the absence of basic design information and the limited space for safety assessments make applying currently used non-destructive testing methods challenging. Therefore, this study suggests non-destructive inspection methods using ultrasonic and impact-echo techniques to assess the quality of underground structures. Thickness, presence of rebars, depth of rebars, and the presence and depth of internal defects are assessed to provide fundamental data for the safety assessment of box-type general underground structures. To validate the proposed methodology, different conditions of concrete specimens are designed and cured to simulate actual field conditions. Applying ultrasonic and impact signals and collecting data through multi-channel accelerometers determine the thickness of the simulated specimens, the depth of embedded rebar, and the extent of defects. The predicted results are well agreed upon compared with actual measurements. The proposed methodology is expected to contribute to developing safety diagnostic methods applicable to general underground structures in practical field conditions.

The Impact of Location-based Mobile Curation Characteristics on Behaviors of Art Gallery Visitors (위치기반 모바일 큐레이션 특성이 미술관 관람객의 관람행태에 미치는 영향)

  • Sangwoo Seo;Taeksoo Shin
    • Information Systems Review
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    • v.22 no.2
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    • pp.167-199
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    • 2020
  • The ICT-based curation as a series of experiences with the mobile exhibition-guide applications or guide programs in art galleries helps visitors fully immersed in the exhibition and allows them to have more informative and convenient guide experience at art galleries. This study aims to verify how the factors of ICT-based curation affects the commitment and satisfaction of visitors at art galleries, figure out whether the visitors' commitment has effects on their satisfaction, and then finally test the impact of their commitment and satisfaction on their revisit intention. In order to validate the cause-and-effect relationships between these factors, the ICT-based curation in this paper is categorized into five factors - gamification, quality of image/video information, quality of sound/text information, contextual offer, and instant connectivity. The main results of the study are as follows. First, only the gamification has significantly positive effects on the commitment of art gallery visitors, while other two factors - the instant connectivity, and the quality of sound/text information - have significantly positive effects on the satisfaction of visitors. Second, the commitment of visitors also has significantly positive effects on their satisfaction. Third, the commitment of the visitors don't have significantly positive relationship with their intention of revisit, but the satisfaction of the visitors have significantly positive relationship with their intention of revisit.

Preparation and Characterization of Lipid Nanoparticles Containing Fat-Soluble Vitamin C Derivatives and Gallic Acid (지용성 비타민 C 유도체 및 갈릭산을 함유한 지질나노입자 제조 및 특성)

  • Ji Soo Ryu;Ja In Kim;Jae Yong Seo;Young-Ah Park;Yu-Jin Kang;Ji Soo Han;Jin Woong Kim
    • Journal of the Society of Cosmetic Scientists of Korea
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    • v.50 no.2
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    • pp.103-110
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    • 2024
  • Lipid nanoparticles (LNPs) are a stable and an effective system that protects cell-impermeable biologically active compounds such as nucleic acids, proteins, and peptides against degradation caused by subtle environmental changes. This study focuses on developing LNPs encapsulating gallic acid (GA), an antioxidant, to effectively prolong the half-life of tetrahexyldecyl ascorbate (THDC), a oil-soluble vitamin C derivative. These LNPs were synthesized in small, uniform sizes at room temperature and pressure conditions using a microfluidics chip. Compared to liposomes manufactured under high pressure and high temperature conditions through conventional microfluidizers, LNPs manufactured through microfluidics chips had excellent dispersion and temperature stability, and improved skin absorption as well as improved oxidative stability of fat-soluble vitamin C derivatives. Future studies will focus on ex vivo and in vivo evaluations to study skin improvement to further validate these results.

Agent Model Construction Methods for Simulatable CPS Configuration (시뮬레이션 가능한 CPS 구성을 위한 에이전트 모델 구성 방법)

  • Jinmyeong Lee;Hong-Sun Park;Chan-Woo Kim;Bong Gu Kang
    • Journal of the Korea Society for Simulation
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    • v.33 no.2
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    • pp.1-11
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    • 2024
  • A cyber-physical system is a technology that connects the physical systems of a manufacturing environment with a cyber space to enable simulation. One of the major challenges in this technology is the seamless communication between these two environments. In complex manufacturing processes, it is crucial to adapt to various protocols of manufacturing equipment and ensure the transmission and reception of a large volume of data without delays or errors. In this study, we propose a method for constructing agent models for real-time simulation-capable cyberphysical systems. To achieve this, we design data collection units as independent agent models and effectively integrate them with existing simulation tools to develop the overall system architecture. To validate the proposed structure and ensure reliability, we conducted empirical testing by integrating various equipment from a real-world smart microfactory system to assess the data collection capabilities. The experiments involved testing data delay and data gaps related to data collection cycles. As a result, the proposed approach demonstrates flexibility by enabling the application of various internal data collection methods and accommodating different data formats and communication protocols for various equipment with relatively low communication delays. Consequently, it is expected that this approach will promote innovation in the manufacturing industry, enhance production line efficiency, and contribute to cost savings in maintenance.

Big Data Analytics in RNA-sequencing (RNA 시퀀싱 기법으로 생성된 빅데이터 분석)

  • Sung-Hun WOO;Byung Chul JUNG
    • Korean Journal of Clinical Laboratory Science
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    • v.55 no.4
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    • pp.235-243
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    • 2023
  • As next-generation sequencing has been developed and used widely, RNA-sequencing (RNA-seq) has rapidly emerged as the first choice of tools to validate global transcriptome profiling. With the significant advances in RNA-seq, various types of RNA-seq have evolved in conjunction with the progress in bioinformatic tools. On the other hand, it is difficult to interpret the complex data underlying the biological meaning without a general understanding of the types of RNA-seq and bioinformatic approaches. In this regard, this paper discusses the two main sections of RNA-seq. First, two major variants of RNA-seq are described and compared with the standard RNA-seq. This provides insights into which RNA-seq method is most appropriate for their research. Second, the most widely used RNA-seq data analyses are discussed: (1) exploratory data analysis and (2) pathway enrichment analysis. This paper introduces the most widely used exploratory data analysis for RNA-seq, such as principal component analysis, heatmap, and volcano plot, which can provide the overall trends in the dataset. The pathway enrichment analysis section introduces three generations of pathway enrichment analysis and how they generate enriched pathways with the RNA-seq dataset.

The Influencing Mechanism of Manufacturing SMEs' Smart Factory Advancement Acceptance Intention: Based on the Information Systems Success Model (중소제조기업의 스마트팩토리 고도화수용의도 영향 메커니즘: 정보시스템 성공모형을 기반으로)

  • Yoon Jae Kim;Chang-Geun Jeong;Sung-Byung Yang
    • Information Systems Review
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    • v.25 no.3
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    • pp.199-220
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    • 2023
  • Projects to deploy and diffuse smart factories in South Korea are aimed at enhancing national manufacturing competitiveness. However, a significant portion of deployed companies remain at the basic stage and struggle to utilize smart factories regularly. Existing studies have primarily focused on the technical aspects of smart factories, using data analytics and case studies, leading to a gap in empirical research on continuous use and upgrade intentions. This study identifies key factors influencing smart factory usage and user satisfaction, drawing on the Information Systems Success Model (ISSM) and previous research. It empirically examines the impact of these factors on continuous use intention, management performance, and advancement acceptance intention through smart factory usage and user satisfaction. A structural equation model is employed to validate the research hypotheses, using survey data from 287 small and medium-sized manufacturing enterprises (SMEs) that have adopted smart factories. Results demonstrate that system quality, information quality, service quality, and government support significantly affect smart factory usage, while service quality and government support influence user satisfaction. Furthermore, smart factory usage and user satisfaction have positive effects on management performance, continuous use intention, and subsequently advancement acceptance intention. This study provides novel insights by demonstrating the specific impact mechanisms of smart factory user satisfaction on the business and the intentions of manufacturing SMEs regarding continuous use and advancement acceptance, leveraging the ISSM.

Diagnosis of Scoliosis Using Chest Radiographs with a Semi-Supervised Generative Adversarial Network (준지도학습 방법을 이용한 흉부 X선 사진에서 척추측만증의 진단)

  • Woojin Lee;Keewon Shin;Junsoo Lee;Seung-Jin Yoo;Min A Yoon;Yo Won Choi;Gil-Sun Hong;Namkug Kim;Sanghyun Paik
    • Journal of the Korean Society of Radiology
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    • v.83 no.6
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    • pp.1298-1311
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    • 2022
  • Purpose To develop and validate a deep learning-based screening tool for the early diagnosis of scoliosis using chest radiographs with a semi-supervised generative adversarial network (GAN). Materials and Methods Using a semi-supervised learning framework with a GAN, a screening tool for diagnosing scoliosis was developed and validated through the chest PA radiographs of patients at two different tertiary hospitals. Our proposed method used training GAN with mild to severe scoliosis only in a semi-supervised manner, as an upstream task to learn scoliosis representations and a downstream task to perform simple classification for differentiating between normal and scoliosis states sensitively. Results The area under the receiver operating characteristic curve, negative predictive value (NPV), positive predictive value, sensitivity, and specificity were 0.856, 0.950, 0.579, 0.985, and 0.285, respectively. Conclusion Our deep learning-based artificial intelligence software in a semi-supervised manner achieved excellent performance in diagnosing scoliosis using the chest PA radiographs of young individuals; thus, it could be used as a screening tool with high NPV and sensitivity and reduce the burden on radiologists for diagnosing scoliosis through health screening chest radiographs.