• Steel and Composite Structures
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• v.51 no.2
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• pp.185-202
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• 2024

In this research paper, and for the first time, wave propagations in sigmoidal imperfect functionally graded material plates are investigated using a simplified quasi-three-dimensionally higher shear deformation theory (Quasi-3D HSDTs). By employing an indeterminate integral for the transverse displacement in the shear components, the number of unknowns and governing equations in the current theory is reduced, thereby simplifying its application. Consequently, the present theories exhibit five fewer unknown variables compared to other Quasi-3D theories documented in the literature, eliminating the need for any correction coefficients as seen in the first shear deformation theory. The material properties of the functionally graded plates smoothly vary across the cross-section according to a sigmoid power law. The plates are considered imperfect, indicating a pore distribution throughout their thickness. The distribution of porosities is categorized into two types: even or uneven, with linear (L)-Type, exponential (E)-Type, logarithmic (Log)-Type, and Sinus (S)-Type distributions. The current quasi-3D shear deformation theories are applied to formulate governing equations for determining wave frequencies, and phase velocities are derived using Hamilton's principle. Dispersion relations are assumed as an analytical solution, and they are applied to obtain wave frequencies and phase velocities. A comprehensive parametric study is conducted to elucidate the influences of wavenumber, volume fraction, thickness ratio, and types of porosity distributions on wave propagation and phase velocities of the S-FGM plate. The findings of this investigation hold potential utility for studying and designing techniques for ultrasonic inspection and structural health monitoring.

• International Journal of Heart Failure
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• v.6 no.1
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• pp.11-19
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• 2024

The prevalence of heart failure (HF) is increasing, necessitating accurate diagnosis and tailored treatment. The accumulation of clinical information from patients with HF generates big data, which poses challenges for traditional analytical methods. To address this, big data approaches and artificial intelligence (AI) have been developed that can effectively predict future observations and outcomes, enabling precise diagnoses and personalized treatments of patients with HF. Machine learning (ML) is a subfield of AI that allows computers to analyze data, find patterns, and make predictions without explicit instructions. ML can be supervised, unsupervised, or semi-supervised. Deep learning is a branch of ML that uses artificial neural networks with multiple layers to find complex patterns. These AI technologies have shown significant potential in various aspects of HF research, including diagnosis, outcome prediction, classification of HF phenotypes, and optimization of treatment strategies. In addition, integrating multiple data sources, such as electrocardiography, electronic health records, and imaging data, can enhance the diagnostic accuracy of AI algorithms. Currently, wearable devices and remote monitoring aided by AI enable the earlier detection of HF and improved patient care. This review focuses on the rationale behind utilizing AI in HF and explores its various applications.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.343-350
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• 2024

Mobile electroencephalography (EEG) can continuously and objectively monitor construction workers' psychological stress, thereby contributing to enhanced safety and health. Traditional EEG-based stress assessment techniques utilize headset-type devices that cover the scalp, including the frontal area, which is the most relevant brain part to stress. Yet, the invasiveness of such devices may pose a potential barrier to their field application. In response, ear-EEG technology presents a less intrusive alternative for continuous monitoring, potentially overcoming the limitations of scalp-EEG. The temporal regions monitored by ear-EEG hold anatomical and functional significance in the brain's response to stress, suggesting that ear-EEG could effectively detect stress. Despite its advantage, the effectiveness of ear-EEG in stress detection remains underexplored, largely due to the existing literature's focus on frontal brain regions. To address this gap, the authors aim to evaluate ear-EEG's effectiveness in measuring stress and compare it to high-density scalp-EEG. EEG signals were collected with ear- and scalp-EEGs from 10 subjects in a controlled laboratory while they performed the mental arithmetic tasks under time pressure and socio-evaluative threats to induce stress at different levels (high vs. low). Subsequently, the authors performed t-tests and point-biserial analysis to analyze differences between high and low-stress conditions in the most reliable stress biomarkers in literature: high-beta power in temporal regions for ear-EEG, and alpha asymmetry in frontal regions for scalp-EEG. The results indicate that both EEG techniques could effectively differentiate between stress levels, with statistical significance (p <0.001 for both) and moderate effect size. Furthermore, the results demonstrate ear-EEG's comparable effectiveness to scalp-EEG in detecting stress-induced brain activity given the comparable statistical metrics, such as p-value and effect size. This study provides a groundwork for further explorations into leveraging ear-EEG as a practical tool for the early detection of stress, aiming to enhance stress management strategies within the construction industry.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.5
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• pp.571-580
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• 2012

Epidemiologic studies of air pollution need accurate exposure assessments at unmonitored locations. A land use regression (LUR) model has been used successfully for predicting traffic-related pollutants, although its application has been limited to Europe, North America, and a few Asian region. Therefore, we modeled traffic-related pollutants by LUR then examined whether LUR models could be constructed using a regulatory monitoring network in Metropolitan area in Korea. We used the annual-mean nitrogen dioxide ($NO_2$) in 2010 in the study area. Geographic variables that are considered to predict traffic-related pollutants were classified into four groups: road type, traffic intensity, land use, and elevation. Using geographical variables, we then constructed a model to predict the monitored levels of $NO_2$. The mean concentration of $NO_2$ was 30.71 ppb (standard deviation of 5.95) respectively. The final regression model for the $NO_2$ concentration included five independent variables. The LUR models resulted in $R^2$ of 0.59. The mean concentration of $NO_2$ of elementary schools was 34.04 ppb (standard deviation of 5.22) respectively. The present study showed that even if we used regulatory monitoring air quality data, we could estimate $NO_2$ moderately well. These analyses confirm the validity of land use regression modeling to assign exposures in epidemiological studies, and these models may be useful tools for assessing health effects of long-term exposure to traffic related pollution.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.71-81
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• 2011

The EMR management services can monitoring the patients' record with any doctors in any hospital by using the internet and smartphones online. To handle the real time, multidimensional, continuous data, database management systems (DBMS) must cope with high insert rates for updates, however the traditional DBMS suffers from processing these kinds of data due to its serious design bottlenecks. So the researchers put forward to Data Stream Management System (DSMS). In this paper we describe the real-time Data Stream Server for Continuity of Care Record (CCR) that including continuos query processor. This system is compiled with DSMS and DBMS in EMR system for processing and monitoring the coming CCR data stream, and also storing the processed result with high-efficiency. The system enables users not only to query stored CCR information from DBMS, but also to execute continue query on real-time CCR Data Stream, and health information can be transferred between different healthcare providers that would reduce medical error. At last, we develop a IPhone mobile application to test the proposed real-time data stream server.

• Analytical Science and Technology
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• v.25 no.4
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• pp.250-256
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• 2012

Two marker compounds of Achyranthis Radix, ecdysterone and inokosterone, were analyzed by HPLC on an ODS column ($250{\times}4.6$ mm, 5 ${\mu}m$) with a mobile phase of 15% acetonitrile containing 0.08% formic acid at a flow rate of 1.0 mL/min and a detection wavelength of UV 254 nm. The method was validated by ICH guideline and applied to the monitoring of marker compounds in 93 samples of Achyranthis Radix collected at various areas in Korea and China. The new content criteria of ecdysterone and inokosterone, established using linear regression method were 0.033% and 0.020%, respectively. When the new content criteria were applied to the quality control test of commercial Achyranthis Radix, 95.4% of total samples including 100% of Korean and 92.6% of Chinese samples were passed the test. Application of new content criteria could protect the Korean products and decrease the distribution of Chinese products with lower quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.7
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• pp.573-586
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• 2013

Recently, the research, utilizing bio and environment sensors in agricultural and cattle industries, are drawing attention among the various IT convergence technologies. Among such research IT convergence techniques which aim to improve the quality of cattle industry management are necessary in particular. Real-time monitoring of the cattles health condition, identification of the cause of the diseases and timely response to such epidemic based on IT convergence techniques are among them. In order to achieve the better management of cattle industry, we propose a cattles management system which based on various bio environment sensors and wireless network technologies. The system consists of wireless environmental sensor data acquisition nodes, sensor data processing nodes, the gateway and the server. The proposed system is able to actively monitor the cattle field, to respond quickly in the case of massive cattle diseases and to control the environment of the cattle fields. We believe the proposed system will demonstrate the successful application of IT technologies to an applied field such as farming industries because of real-time crisis management capability in case of epidemic and optimal management of cattle industry.

• Korean Journal of Environmental Biology
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• v.38 no.4
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• pp.634-649
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• 2020

Recently, stream longitudinal connectivity has been a topic of investigation due to the frequent disconnections and the impact of aquatic ecosystems caused by the construction of small and medium-sized weirs and various artificial structures (fishways) directly influencing the stream ecosystem health. In this study, the international and domestic research trends of the longitudinal connectivity in aquatic ecosystems were evaluated and the applicability of fish-based longitudinal connectivity models used in developed countries was analyzed. For these purposes, we analyzed the current status of research on longitudinal connectivity and structural problems, fish monitoring methodology, monitoring approaches, longitudinal disconnectivity of fish movement, and biodiversity. In addition, we analyzed the current status and some technical limitations of physical habitat suitability evaluation, ecology-based water flow, eco-hydrological modeling for fish habitat connectivity, and the s/w program development for agent-based model. Numerous references, data, and various reports were examined to identify worldwide longitudinal stream connectivity evaluation models in European and non-European countries. The international approaches to longitudinal connectivity evaluations were categorized into five phases including 1) an approach integrating fish community and artificial structure surveys (two types input variables), 2) field monitoring approaches, 3) a stream geomorphological approach, 4) an artificial structure-based DB analytical approach, and 5) other approaches. the overall evaluation of survey methodologies and applicability for longitudinal stream connectivity suggested that the ICE model (Information sur la Continuite Ecologique) and the ICF model (Index de Connectivitat Fluvial), widely used in European countries, were appropriate for the application of longitudinal connectivity evaluations in Korean streams.

• Journal of Food Hygiene and Safety
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• v.7 no.2
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• pp.121-132
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• 1992

Pesticides are regarded as one of indispensable materials used in agriculture to protect pests and to keep the agricultural productions steadily. However, food contamination arisen from their application has brought about public concerns for safety suspicion to human health. A brief presentation is given in this paper on what has been conducted against pesticide residues to evaluate and ensure the safety of agro-porducts. The commonest countermeasures to keep safety would be tile establishment of MRls and safe-use guidelines of pesticides according to good agricultural practices. Korean MRls have been established on 38 chemicals with 56 commodities and in the case of safe-use guidelines 344 formulation items have been done by the government On the other hand, no satisfactory information is still available to evalute the actual residue levels in domestic agro-products, but a cautious proposal could be suggested through the fragmentary monitoring data of pesticide residues, so that the current residue levels would be far from potent hazard enough to cause chronic impact on human. The most important thing is to have the farmers keep safe use guidelines at pesticide application for the production of safe agricultural commodities.

• Proceedings of the Korean Society of Food Hygiene and Safety Conference
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• 1992.07a
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• pp.21-32
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• 1992

Pesticides are regarded as one of indispensable materials used in agriculture to protect pests and to keep the agriculture productions steadily. However, food contamination arisen from their application has brought about public concerns for safety suspicion to human health. A brief presentation is given in this paper on what has been conducted against pesticide residues to evaluate and ensure the safety of agro-products. The commonest countermeasures to keep safety would be the establishment of MRLs and safe-use guidelines of pesticides according to good agricultural practices. Korean MRLs have bun established on 38 chemicals with 56 commodities and in the case of safe-use guidelines 344 formulation items have been done by the government. On the other hand, no satisfactory information is still available to evalute the actual residue levels in domestic agro-products, but a cautious proposal could be suggested through the fragmentary monitoring data of pesticide residues, so that the current residue levels would be far from potent hazard enough to cause chronic impact on human. The most important thing is to have the farmers keep safe use guidelines at pesticide application for the production of safe agriculture commodities.