• Composites Research
• /
• v.37 no.1
• /
• pp.32-39
• /
• 2024

Solid-state hydrogen storage is gaining prominence as a crucial subject in advancing the hydrogen-based economy and innovating energy storage technology. This storage method shows superior characteristics in terms of safety, storage, and operational efficiency compared to existing methods such as compression and liquefied hydrogen storage. In this study, we aim to evaluate the solid hydrogen storage performance on the nanotube surface by various structural design factors. This is accomplished through molecular dynamics simulations (MD) with the aim of uncovering the underlying ism. The simulation incorporates diverse carbon nanotubes (CNTs) - encompassing various diameters, multi-walled structures (MWNT), single-walled structures (SWNT), and boron-nitrogen nanotubes (BNNT). Analyzing the storage and effective release of hydrogen under different conditions via the radial density function (RDF) revealed that a reduction in radius and the implementation of a double-wall configuration contribute to heightened solid hydrogen storage. While the hydrogen storage capacity of boron-nitrogen nanotubes falls short of that of carbon nanotubes, they notably surpass carbon nanotubes in terms of effective hydrogen storage capacity.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.19 no.3
• /
• pp.551-562
• /
• 2024

This study relates to a method and device for extracting and tracking moving objects. In particular, objects are extracted using different images between adjacent images, and the location information of the extracted object is continuously transmitted to provide accurate location information of at least one moving object. It relates to a method and device for extracting and tracking moving objects based on tracking moving objects. People tracking, which started as an expression of the interaction between people and computers, is used in many application fields such as robot learning, object counting, and surveillance systems. In particular, in the field of security systems, cameras are used to recognize and track people to automatically detect illegal activities. The importance of developing a surveillance system, that can detect, is increasing day by day.

• Clinical Nutrition Research
• /
• v.12 no.4
• /
• pp.269-282
• /
• 2023

Vitamin D participates in the biological function of the innate and adaptive immune system and inflammation. We aim to specify the effectiveness of the vitamin D supplementation on the side effects BioNTech, Pfizer vaccination, and immunoglobulin G response against severe acute respiratory syndrome coronavirus 2 in subjects tested positive for coronavirus disease 2019 (COVID-19). In this multi-center randomized clinical trial, 498 people tested positive for COVID-19 were divided into 2 groups, receiving vitamin D capsules or a placebo (1 capsule daily, each containing 600 IU of vitamin D) over 14-16 weeks. Anthropometric indices and biochemical parameters were measured before and after the second dose of vaccination. Fourteen to 16 weeks after supplementation, the intervention group had an immunoglobulin G (IgG) increase of 10.89 ± 1.2 g/L, while the control group had 8.89 ± 1.3 g/L, and the difference was significant between both groups (p = 0.001). After the second dose of vaccination, the supplement group significantly increased their 25-hydroxy vitamin D from initially 28.73 ± 15.6 ng/mL and increased to 46.48 ± 27.2 ng/mL, and the difference between them was significant. Those with a higher body mass index (BMI) had the most of symptoms, and the difference of side effects according to BMI level was significantly different. In 8 weeks after supplementation obese participants had the lowest IgG levels than overweight or normal subjects. The proportion of all types of side effects on the second dose was significantly diminished compared with the first dose in the intervention group. Supplementation of 600 IU of vitamin D3 can reduce post-vaccination side effects and increase IgG levels in participants who received BioNTech, Pfizer vaccine.

• International Journal of Computer Science & Network Security
• /
• v.23 no.12
• /
• pp.151-160
• /
• 2023

Breast cancer is the most dangerous and deadly form of cancer. Initial detection of breast cancer can significantly improve treatment effectiveness. The second most common cancer among Indian women in rural areas. Early detection of symptoms and signs is the most important technique to effectively treat breast cancer, as it enhances the odds of receiving an earlier, more specialist care. As a result, it has the possible to significantly improve survival odds by delaying or entirely eliminating cancer. Mammography is a high-resolution radiography technique that is an important factor in avoiding and diagnosing cancer at an early stage. Automatic segmentation of the breast part using Mammography pictures can help reduce the area available for cancer search while also saving time and effort compared to manual segmentation. Autoencoder-like convolutional and deconvolutional neural networks (CN-DCNN) were utilised in previous studies to automatically segment the breast area in Mammography pictures. We present Automatic SegmenAN, a unique end-to-end adversarial neural network for the job of medical image segmentation, in this paper. Because image segmentation necessitates extensive, pixel-level labelling, a standard GAN's discriminator's single scalar real/fake output may be inefficient in providing steady and appropriate gradient feedback to the networks. Instead of utilising a fully convolutional neural network as the segmentor, we suggested a new adversarial critic network with a multi-scale L1 loss function to force the critic and segmentor to learn both global and local attributes that collect long- and short-range spatial relations among pixels. We demonstrate that an Automatic SegmenAN perspective is more up to date and reliable for segmentation tasks than the state-of-the-art U-net segmentation technique.

• Structural Engineering and Mechanics
• /
• v.90 no.3
• /
• pp.233-252
• /
• 2024

This research explores a new finite element model for the free vibration analysis of bi-directional functionally graded (BDFG) beams. The model is based on an efficient higher-order shear deformation beam theory that incorporates a trigonometric warping function for both transverse shear deformation and stress to guarantee traction-free boundary conditions without the necessity of shear correction factors. The proposed two-node beam element has three degrees of freedom per node, and the inter-element continuity is retained using both C1 and C0 continuities for kinematics variables. In addition, the mechanical properties of the (BDFG) beam vary gradually and smoothly in both the in-plane and out-of-plane beam's directions according to an exponential power-law distribution. The highly elevated performance of the developed model is shown by comparing it to conceptual frameworks and solution procedures. Detailed numerical investigations are also conducted to examine the impact of boundary conditions, the bi-directional gradient indices, and the slenderness ratio on the free vibration response of BDFG beams. The suggested finite element beam model is an excellent potential tool for the design and the mechanical behavior estimation of BDFG structures.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.44 no.3
• /
• pp.329-336
• /
• 2024

In the case of multi-function weirs installed in Korea, the free hydraulic jump or the submerged hydraulic jump is occurred depending on the height of the gate opening and the tailwater level when the sluice gate of the movable weir is partially opened. In this study, the submerged hydraulic jump for the flows under the sluice gate were simulated and the mean flow, turbulence statistics, and relative water depth are investigated using numerical simulation. For numerical simulation, the unsteady Reynolds-averaged Navier-Stokes equation, volume of fluid method, and k-ωSST turbulence model were used. The numerical model was validated using the results of other researchers' previously performed experiments, and it was investigated that the numerical model appropriately simulates the two-phase flow in the hydraulic jump. In addition, the distribution of mean flow, turbulence statistics, and the length of recirculation region was investigated.

• Clinics in Shoulder and Elbow
• /
• v.27 no.2
• /
• pp.237-246
• /
• 2024

Proximal humeral fractures (PHFs) are a common injury among the older population. An ideal therapeutic protocol has yet to be developed, and numerous clinical trials are being conducted to find the best therapeutic approach. The purpose of this study is to evaluate the current body of knowledge available via interventional clinical trials. In December 2022, interventional clinical trials relating to PHFs on Clinicaltrials.gov were screened. Trial characteristics included duration, status, intervention, phase, outcomes, location, and study design. Publications associated with each trial were searched on PubMed/Medline using the ClinicalTrials.gov registry number. The final dataset comprised 64 trials. The most common trial status was completed (36%). The majority did not have a Food and Drug Administration-defined phase (67%), was randomized (81%), involved a single facility (72%), used a parallel assignment intervention model (80%), and used an open-label approach (45%). Eleven trials were associated with a publication, and the publication rate was 17%. Average enrollment was 86 participants, and mean trial duration was 51.4 months. Europe/UK/Russia/Turkey participated in the most trials (70%). Most of the trials were initiated after 2010 (87.5%). Procedure-related interventions (55%) were most common. Disability/function was the most common primary outcome assessed (61%). The low publication rate and the multitude of trials conducted after 2010 highlight the urgency and need for trial results to be published to establish an ideal therapeutic protocol. Since the majority of the trials involved a single institution and an open-label approach, reinforcing blinding and establishing multi-centered trials can improve the validity of the clinical trial results.

• Journal of Internet of Things and Convergence
• /
• v.10 no.3
• /
• pp.25-33
• /
• 2024

In tomographic image reconstruction, the focus is on developing CT image reconstruction methods that can maintain high image quality while reducing patient radiation exposure. Typically, statistical image reconstruction methods have the ability to generate high-quality and accurate images while significantly reducing patient radiation exposure. However, in cases like CT image reconstruction, which involve multi-dimensional parameter estimation, the degree of the Hessian matrix of the penalty function is very large, making it impossible to calculate. To solve this problem, the author proposed the PEMG-1 algorithm. However, the PEMG-1 algorithm has issues with the convergence speed, which is typical of statistical image reconstruction methods, and increasing the penalty log-likelihood. In this study, we propose a reconstruction algorithm that ensures fast convergence speed and monotonic increase in likelihood. The basic structure of this algorithm involves sequentially updating groups of pixels instead of updating all parameters simultaneously with each iteration.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.13 no.2
• /
• pp.73-84
• /
• 1993

In this research, configuration design optimization of plane truss structure has been tested by using decomposition technique. In the first level, the problem of transferring the nonlinear programming problem to linear programming problem has been effectively solved and the number of the structural analysis necessary for doing the sensitivity analysis can be decreased by developing stress constraint into member stress approximation according to the design space approach which has been proved to be efficient to the sensitivity analysis. And the weight function has been adopted as cost function in order to minimize structures. For the design constraint, allowable stress, buckling stress, displacement constraint under multi-condition and upper and lower constraints of the design variable are considered. In the second level, the nodal point coordinates of the truss structure are used as coordinating variable and the objective function has been taken as the weight function. By treating the nodal point coordinates as design variable, unconstrained optimal design problems are easy to solve. The decomposition method which optimize the section areas in the first level and optimize configuration variables in the second level was applied to the plane truss structures. The numerical comparisons with results which are obtained from numerical test for several truss structures with various shapes and any design criteria show that convergence rate is very fast regardless of constraint types and configuration of truss structures. And the optimal configuration of the truss structures obtained in this study is almost the identical one from other results. The total weight couldbe decreased by 5.4% - 15.4% when optimal configuration was accomplished, though there is some difference.

• Korean Journal of Environment and Ecology
• /
• v.33 no.4
• /
• pp.472-480
• /
• 2019

Selection of the plant material for planting to reduce fine dust should comprehensively consider the visual characteristics, such as the shape and texture of the plant leaves and form of bark, which affect the adsorption function of the plant. However, previous studies on reduction of fine dust through plants have focused on the absorption function rather than the adsorption function of plants and on foliage plants, which are indoor plants, rather than the outdoor plants. In particular, the criterion for selection of fine dust reduction species is not specific, so research on the selection criteria for plant materials for fine dust reduction in urban areas is needed. The purpose of this study is to identify the priorities of eight indicators that affect the fine dust reduction by using the fuzzy multi-criteria decision-making model (MCDM) and establish the tree selection criteria for the urban planting to reduce fine dust. For the purpose, we conducted a questionnaire survey of those who majored in fine dust-related academic fields and those with experience of researching fine dust. A result of the survey showed that the area of leaf and the tree species received the highest score as the factors that affect the fine dust reduction. They were followed by the surface roughness of leaves, tree height, growth rate, complexity of leaves, edge shape of leaves, and bark feature in that order. When selecting the species that have leaves with the coarse surface, it is better to select the trees with wooly, glossy, and waxy layers on the leaves. When considering the shape of the leaves, it is better to select the two-type or three-type leaves and palm-shaped leaves than the single-type leaves and to select the serrated leaves than the smooth edged leaves to increase the surface area for adsorbing fine dust in the air on the surface of the leaves. When considering the characteristics of the bark, it is better to select trees that have cork layers or show or are likely to show the bark loosening or cracks than to select those with lenticel or patterned barks. This study is significant in that it presents the priorities of the selection criteria of plant material based on the visual characteristics that affect the adsorption of fine dust for the planning of planting to reduce fine dust in the urban area. The results of this study can be used as basic data for the selection of trees for plantation planning in the urban area.