• Textile Coloration and Finishing
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• v.33 no.4
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• pp.238-249
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• 2021

In this study, the effect on flame retardancy and various physical properties when TiO₂ was added with a citric acid/phosphate complex acid catalyst together with Pyrovatex CP new (N-methylol dimethylphosphonopropionamide), a phosphorus-based flame retardant, was studied on cotton fibers. SEM-EDS analysis was performed to confirm the surface characteristics and surface element analysis of the flame-retardant treated cotton fibers, and a vertical carbonization test was performed to confirm the char formation capability and flame retardancy according to the phosphoric acid ratio. By comparing the LOI index before and after washing 10 times, the washing durability of the flame retardant solution containing the phosphoric acid catalyst and TiO₂ was tested by LOI index after ten washing cycles. In addition, the influence of the flame-retardant processing on the physical properties were compared including thermogravimetric analysis (TGA), tear strength and whiteness.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.171-171
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• 2023

This study investigates the capability of Physics-Informed Neural Networks (PINNs) for solving the solution of partial differential equations. Particularly, the 1D Saint-Venant Equations (SVEs) were considered, which describe the movement of water in a domain with shallow depth compared to its horizontal extent, and are widely adopted in hydrodynamics, river, and coastal engineering. The core contribution of this work is to combine the robustness of neural networks with the physical constraints of the SVEs. The PINNs method utilized a neural network to approximate the solutions of SVEs, while also enforcing the underlying physical principles of the equations. This allows for a more effective and reliable solution, especially in areas with complex geometry and varying bathymetry. To validate the robustness of the PINNs method, numerical experiments were conducted on several benchmark problems. The results show that the PINNs could be achieved high accuracy when compared with the solution from the numerical solution. Overall, this study demonstrates the potential of using PINNs and highlights the benefits of integrating neural network and physics information for improved efficiency and accuracy in solving SVEs.

• The Journal of Korean Physical Therapy
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• v.17 no.3
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• pp.339-350
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• 2005

This study is the quasi-experimental study on the gait training rehabilitation. The purpose of this study is to prepare the baseline data for most suitable of gait while we were scrutinizing how the walking characters, functional walking ability, gait quality of stroke patients were affected by the gait on BWSTT (Body Weight Supported Treadmill Training) through the change of treadmill velocity and body weight support. To accomplish this purpose, this study used thirty subjects, more than 3 months post stroke, for rehabilitation who were divided between two gait training groups they received the neurophysiological physical therapy. For 6 weeks, 5 times a week for 15 minutes per session, the BWSTT group participated in 30 sessions structured speed-dependent treadmill training with 30% body weight supported, and the ratio of body weight support was gradually decreased as the patients advanced the capability of more self-support. The OGT(Over Ground Training) group received the same quantity of equal sessions like BWSTT. Firstly, we measured the absolute improvement of walking velocity (m/s), capacity(min/m) and cadence(steps/min) among walking characters. Secondly, we measured the functional walking ability such as Functional Ambulatory Category(FAC, score out of 5), Modified Motor Assesment Scale(MMAS, score out of 6) and Gait Quality Chart(score out of 41). Data analysis was performed with using SPSS 10.0 win program. The descriptive analysis was used to obtain average and standard deviation. The independent t-test and the paired t-test were used to compare both the groups about pre and post training test. Treatment effects were established by pre and post assessment. Subjects tolerated the training well without side-effects. Therefore, the results of this study were as follows; 1. There was a more significant difference from the improvement of walking velocity(0.09m/s), endurance(4.53min/m), cadence(4.20steps/min), FAC(0.26score), MMAS(0.33 score) and hip joint and pelvic of gait quality(0.39 score) ever before in the BWSTT group(p<.05). 2. There was a more significant increase from the walking velocity(0.01m/s) in the OGT group(p<.05). 3. There was a more statistical significant increase from comparing the average of walking velocity in both groups ever before(0.42m/s in BWSTT group and 0.31m/s in OGT group)(p<.05). There was a statistical significant difference from the average of cadence in both groups(61.87step/min in BWSTT group and 3.60steps/min in OGT group)(p<.05). As we can see from above, the findings suggest that BWSTT may be more effective than the OGT for improving some gait parameters such as gait velocity and cadency. This conclusion also suggest that BWSTT is more effective for the improvement of gait of stroke patients.

• Journal of Korean Society of Water and Wastewater
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• v.23 no.6
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• pp.769-778
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• 2009

Performances and internal behaviors of the upflow hybrid anaerobic filters treating a dairy wastewater were analyzed to identify the functions and roles of the modular crossflow media and sludge bed layer and to discover their interrelationship in the filter. The media could perform independent biological and physical separation role without buildup of sludge bed, while the role of sludge bed was dependent on the function of the media. The filter packed with the crossflow media did not necessarily require the formation of sludge bed when treating a dairy wastewater. Biological contribution of the media was controlled by that of biologically active sludge bed complementing mutually each other. The gas-liquid-solid separation capability of the media was indispensible to ensure the active biological role of sludge bed, since sludge bed buildup without the media had no independently effective biological function. It was believed that the filter in itself could also function as a selector for physical gas-liquid-solid separation resulting in selectively concentrating particles with superior settleability in sludge bed. The sludge bed in the filter played a key role in the physical solids capture from influent as well as biological organics removal.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6590-6596
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• 2013

Carbon dioxide should be removed to increase the productivity of dimethyl ether(DME) from the DME manufacturing process. In this study, carbon dioxide can be removed using a physical absorbent through a solvent absorption method and membrane separation method. After performing the simulation for the carbon dioxide removal process, the energy consumption of the processes was compared. Methanol was used as a physical absorbent for the rectisol process, dimethyl ethers of polyethylene glycol for the Selexol process and N-methyl pyrrolidone for the Purisol process. By performing the simulation for each process, the energy consumption was compared. The Purisol process had the lowest energy consumption, followed in order by the Selexol process, Rectisol process and Membrane process. Therefore, the Purisol process was the most suitable method for the carbon dioxide process in the DME manufacturing process.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.122.2-122.2
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• 2011

For more than a decade, NEA (Near-Earth Asteroid) survey teams equipped with 1 meter-class telescopes discovered thousands of NEAs in the northern sky. As of August 2011, some 8,200 NEAs have been cataloged, yet only five percent of them has been investigated for their physical and chemical properties. In order to improve current situation, we propose a deep ecliptic survey utilizing KMTNet, for detection and characterization of NEAs in the southern sky. Thanks to the wide-field capability (four square degrees) of the telescopes, we will be able to considerably expand the search volume carrying out precision photometry down to 21.5th magnitude. We plan to focus our survey on opposition and two "sweet spots" in the ecliptic belt. Since SDSS colors characterize mineralogical properties of NEAs, g', r', i', z' filters will be employed. Based on the round-the-clock observation, we will study their rotational properties; for multiple systems, mass, density and other physical parameters can be obtained. We plan to maintain a dedicated database of the physical and mineralogical properties of NEAs. With this archive, it is expected that our understanding on the population will see a drastic change. We also plan to participate in the GAIA Follow-Up Network for ground based observation of the Solar System Objects (GAIA-FUN-SSO). The follow- up astrometry will be performed upon alerts issued by the GAIA-FUN-SSO Central Node in France.

• Journal of Family Resource Management and Policy Review
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• v.17 no.2
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• pp.173-194
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• 2013

The purpose of this study was to examine the association between time-income availability and health-promoting behavior (physical practice, smoking, alcohol consumption) of older males (55-69). This study attempted to shed light on health-behavior changes during the transition period of male retirement. The availability of time resources was examined by addressing the amount of weekly paid labor hours. The availability of financial resources was calculated by using the debt-income ratio. The study sample comprised 1,372 (age range 55-69) male respondents of the 2006 Korean Longitudinal Study of Aging (2006 KLOSA wave 1). The results of CHAID (CHi-squared Automatic Interaction Detection) analysis uncovered four distinctive combinations of resource types: time-money poor, time rich, money rich, time-money rich. According to logit results, these four groups had different socio-demographic profiles and different health-behavior risks. The time-money poor males were unlikely to perform physical activities needed to improve their health or to quit smoking or alcohol consumption. This group was also more likely to consume alcohol compared to the time-money resource types. In contrast, the time-money rich group was more likely to exercise longer and more frequently than the reference group (time and money poor). The time-rich types, those who have time-only resources and less money, were likely to be smokers and have problems with alcohol consumption.

• Neurospine
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• v.15 no.4
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• pp.329-337
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• 2018

Objective: Machine learning algorithms excel at leveraging big data to identify complex patterns that can be used to aid in clinical decision-making. The objective of this study is to demonstrate the performance of machine learning models in predicting postoperative complications following anterior cervical discectomy and fusion (ACDF). Methods: Artificial neural network (ANN), logistic regression (LR), support vector machine (SVM), and random forest decision tree (RF) models were trained on a multicenter data set of patients undergoing ACDF to predict surgical complications based on readily available patient data. Following training, these models were compared to the predictive capability of American Society of Anesthesiologists (ASA) physical status classification. Results: A total of 20,879 patients were identified as having undergone ACDF. Following exclusion criteria, patients were divided into 14,615 patients for training and 6,264 for testing data sets. ANN and LR consistently outperformed ASA physical status classification in predicting every complication (p < 0.05). The ANN outperformed LR in predicting venous thromboembolism, wound complication, and mortality (p < 0.05). The SVM and RF models were no better than random chance at predicting any of the postoperative complications (p < 0.05). Conclusion: ANN and LR algorithms outperform ASA physical status classification for predicting individual postoperative complications. Additionally, neural networks have greater sensitivity than LR when predicting mortality and wound complications. With the growing size of medical data, the training of machine learning on these large datasets promises to improve risk prognostication, with the ability of continuously learning making them excellent tools in complex clinical scenarios.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.112-114
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• 2005

In today's hyper-competitive business environment, Radio Frequency Identification (RFID) technology is expected to enhance the operation efficiency of supplying chain management in both manufactures and retail industries. However, the widespread deployment of RFID tags may create new threats to user privacy, due to the powerful tracking capability of the tags. Many authentication protocols for RFID have been proposed. They are helpful preventing passersby being scanned to determine what articles they are carrying. However, most of them would not prevent the bigger physical tracking problem of RFID, especially when being tracked by the 'constellation' of products they carry. We proposed this RFID scheme to prevent these tracking problems.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.6
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• pp.1539-1544
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• 1995

Copper blow test to measure the forging capability of 35 ton counterblow hammer and upset of plasticine on the model hammer to investigate the change of the blow efficiency during the forging process have been performed together with finite element analyses of these experiments. The blow efficiency of the hammer has been found to be dependent on the friction and on the contact area between the die and the workpiece. The effects of the volume and the aspect ratio of the billet have not been found. Inferring from the experimental results and Schey's empirical formula on the forging load, we expect that the efficiency also varies with the flow stress of the workpiece material and with the shape complexity of the forging product.