• Advances in nano research
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• v.16 no.2
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• pp.111-125
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• 2024

Recently, a lot of research has been done on the analysis of axial vibrations of homogeneous and FG nanotubes (nanorods) with various aspects of vibrations that have been fully mentioned in history. However, there is a lack of investigation of the dynamic internal resonances of FG nanotubes (nanorods) between them. This is one of the essential or substantial characteristics of nonlinear vibration systems that have many applications in various fields of engineering (making actuators, sensors, etc.) and medicine (improving the course of diseases such as cancers, etc.). For this reason, in this study, for the first time, the dynamic internal resonances of FG nanorods in the simultaneous presence of large-amplitude size dependent behaviour, inertial and shear effects are investigated for general state in detail. Such theoretical patterns permit as to carry out various numerical experiments, which is the key point in the expansion of advanced nano-devices in different sciences. This research presents an AFG novel nano resonator model based on the axial vibration of the elastic nanorod system in terms of derivation from large-amplitude size dependent internal modals interactions. The Hamilton's Principle is applied to achieve the basic equations in movement and boundary conditions, and a harmonic deferential quadrature method, and a multiple scale solution technique are employed to determine a semi-analytical solution. The interest of the current solution is seen in its specific procedure that useful for deriving general relationships of internal resonances of FG nanorods. The numerical results predicted by the presented formulation are compared with results already published in the literature to indicate the precision and efficiency of the used theory and method. The influences of gradient index, aspect ratio of FG nanorod, mode number, nonlinear effects, and nonlocal effects variations on the mechanical behavior of FG nanorods are examined and discussed in detail. Also, the inertial and shear traces on the formations of internal resonances of FG nanorods are studied, simultaneously. The obtained valid results of this research can be useful and practical as input data of experimental works and construction of devices related to axial vibrations of FG nanorods.

• Structural Engineering and Mechanics
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• v.89 no.3
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• pp.225-238
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• 2024

In this paper, a quasi-3D hyperbolic shear deformation theory for the bending responses of a functionally graded (FG) porous micro-beam is based on a modified couple stress theory requiring only one material length scale parameter that can capture the size influence. The model proposed accounts for both shear and normal deformation effects through an illustrative variation of all displacements across the thickness and satisfies the zero traction boundary conditions on the top and bottom surfaces of the micro-beam. The effective material properties of the functionally graded micro-beam are assumed to vary in the thickness direction and are estimated using the homogenization method of power law distribution, which is modified to approximate the porous material properties with even and uneven distributions of porosity phases. The equilibrium equations are obtained using the virtual work principle and solved using Navier's technique. The validity of the derived formulation is established by comparing it with the ones available in the literature. Numerical examples are presented to investigate the influences of the power law index, material length scale parameter, beam thickness, and shear and normal deformation effects on the mechanical characteristics of the FG micro-beam. The results demonstrate that the inclusion of the size effects increases the microbeams stiffness, which consequently leads to a reduction in deflections. In contrast, the shear and normal deformation effects are just the opposite.

• Geomechanics and Engineering
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• v.36 no.5
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• pp.417-426
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• 2024

Shield tunneling method is widely used to build tunnels in complex geological environment. Stability control of tunnel face is the key to the safety of projects. To improve the excavation efficiency or perform equipment maintenance, the excavation chamber sometimes is not fully filled with support medium, which can reduce the load and increase tunneling speed while easily lead to ground collapse. Due to the high risk of the face failure under non-fully support mode, the tunnel face stability should be carefully evaluated. Whether compressive air is required for compensation and how much air pressure should be provided need to be determined accurately. Based on the upper bound theorem of limit analysis, a non-fully support rotational failure model is developed in this study. The failure mechanism of the model is verified by numerical simulation. It shows that increasing the density of supporting medium could significantly improve the stability of tunnel face while the increase of tunnel diameter would be unfavorable for the face stability. The critical support ratio is used to evaluate the face failure under the nonfully support mode, which could be an important index to determine whether the specific unsupported height could be allowed during shield tunneling. To avoid of face failure under the non-fully support mode, several charts are provided for the assessment of compressed air pressure, which could help engineers to determine the required air pressure for face stability.

• Journal of Chest Surgery
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• v.57 no.3
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• pp.255-262
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• 2024

Background: Sutureless aortic valves may enable shorter procedure times, which benefits patients with elevated surgical risk. We describe the outcomes of patients with aortic stenosis who underwent aortic valve replacement (AVR) using the sutureless Perceval aortic bioprosthesis. Methods: Data from a retrospective cohort were obtained from a clinical database. The study enrolled patients with symptomatic severe aortic stenosis who underwent surgical AVR with a sutureless bioprosthesis between August 2015 and December 2020. In total, 113 patients were included (mean age, 75.3±8.4 years; 57.5% women; median Society of Thoracic Surgeons score, 9.7%; mean follow-up period, 51.19±20.6 months). Of these patients, 41 were octogenarians (36.2%) and 3 were nonagenarians (2.6%). Transthoracic echocardiography was employed to assess changes in ejection fraction (EF), left ventricular mass index (LVMI), and mean pressure gradient (MPG). Results: The in-hospital mortality rate was 2.6%, and 13 patients developed new-onset atrial fibrillation. A permanent pacemaker was implanted in 3 patients (2.6%). The median intensive care unit stay was 1 day (interquartile range [IQR], 1-2 days), and the median hospital stay was 12 days (IQR, 9.5-15 days). The overall survival rate at 5 years was 95.9%. LVMI and MPG were reduced postoperatively, while EF increased over the follow-up period. No structural valve deterioration was observed, and no meaningful paravalvular leakage developed during follow-up. Conclusion: The use of a sutureless valve in the aortic position is safe and feasible, even for high-risk elderly patients requiring surgical AVR. LVMI and MPG decreased postoperatively, while EF increased over the follow-up period.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.73-81
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• 2013

Ordinary least squares (OLS) regression is the primary statistical method in previous studies for vegetation distribution patterns in relation to landform. However, this global regression lacks the ability to uncover some local-specific relationships and spatial autocorrelation in model residuals. This study employed geographically weighted regression (GWR) to examine the spatially varying relationships between NDVI (Normalized Difference Vegetation Index) patterns and changing trends of landform (elevation, slope) and solar intensity (insolation and duration of sunshine) in Mt Geum-gang of North-Korea. Results denoted that GWR was more powerful than OLS in interpreting relationships between NDVI patterns and landform/solar intensity, since GWR was characterized by higher adjusted R2, and reduced spatial autocorrelations in model residuals. Unlike OLS regression, GWR allowed the coefficients of explanatory variables to differ by locality by giving relatively more weight to NDVI patterns which are affected by local landform and solar factors. The strength of the regression relationships in the GWR increased significantly, by showing regression coefficient of higher than 70% (0.744) in the southern ridge of the experimental area. It is anticipated that this research output will serve to increase the scientific and objective vegetation monitoring in relation to landform and solar intensity by overcoming serious constraints suffered from the past non-GWR-based approach.

• Korean Journal of Agricultural Science
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• v.23 no.1
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• pp.138-149
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• 1996

This study was aimed at predicting to running speed related to alignment factors of forest road, and recommending the improvement method of forest road construction using the running speed of vehicles. For these purposes, this study proceeds to select forest roads after reviewing the planning papers and maps, to measure the road alignment factors such as longitudinal gradient, width of roadway, radius of curve, length of curve, superelevation, and conditions of road surface on the subject forest road. It was found that the average running speed of logging truck showed lower value than that of the expected speed of 'Forest Road Construction Regulations and Rules', and the average running speed of loaded truck showed 70-85% of the speed of empty truck. According to the road conditions, speed index (reductive ratio of running speed) was also calculated with respect to radius of curve, longitudinal dradient. The results of the study on the running speed of vehicle subject to the alignment of forest roads make it possible for one to judge the quality of the existed and to be constructed forest roads, to select the structure of forest road to improve the running speed of vehicle on forest road.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.22 no.4
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• pp.258-271
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• 2010

In order to figure out hydrodynamic and water quality changes after completion of dike construction of the Saemangeum, which behaves as a semi-enclosed estuarine lake, numerical simulations based on fine grid structure by using EFDC were intensively carried out. In this study some limitations of precedent study has been improved and gate operation were considered. Also 3 phases such as air-water-sediment interaction modeling was considered. It is clear that inner mixing of the Saemangeum is dominated by Mankyeong and Dongjin riverine discharges rather than the gate opening influence through the Lagrangian particle tracking simulations. Vertical DO structure after the dike completion shows steep gradient especially at Dongjin river estuary due to lessen of outer sea water exchange. Increasing SOD at stagnantly changed man-made reservoir might cause oxygen deficiency and accelerating degradation of water quality. According to TSI evaluation test representing eutrophication status, it shows high possibility of eutrophication along Mankyeong waterway in spite of dike completion, while the index is getting high after final closing along Dongjin waterway. Numerical tests with gate operations show significant differences in water quality. Thus it should be noted that proper gate operation plays a major role in preserving target water quality and management for inner development plan.

• Magazine of the Korean Society of Agricultural Engineers
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• v.25 no.4
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• pp.50-60
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• 1983

305 samples of alluvial deposit in inland and harbour districts were selected and consolidation charateristics of the alluvium were put in order statiscally. The correlations between them were as follows. 1. The relationships between LL(liguid limit) and Cc (compression index) were explained as Cc=0. 03(LL-21. 7) in case of inland district soil and as Cc=0. 019(LL-19) in case of harbour district soil. As compared with formular proposed by Skernpton, the gradient of this linear line was slight steep. 2. The relationships between PI(plastic index) and Cc were explained as Cc=0. 063 PI-0. 52 in case of inland district soil and Cc=0. 043 PI-0. 31 in case of harbour district soil. 3. As void ratio and natural moisture content were increased, Cc was increased, and as wet density was increased, Cc was decreased with a gentle curve. 4. As LL and P1 increased, mv(coefficient of volume compressibility) was increased but if LL and P1 was increased beyond a certain extend, mv has a tendency of constant value, that is, mv show a tendency to take constant value in the very soft clay. and mv in P=2. 5kg/cm$^2$ was about l${\times}$ l0-$^1$cm$^2$/kg in case of land district soil and 6x 10-$^1$crn$^2$/kg in case of harbour district soil lower than that in P=0. 25kg/crn2. 5. Cv(coefficient of consolidation) was a tendency to decrease with a gentle curve as LL was increased, and Cv in P=0. 25kg/crn2 was about 3x l0-$^1$crn$^2$/min larger than that in P=2. 5kg/crn$^2$. 6. Relationships between Py(pre-consolidation pressure) which is included over consolidation soil and ∑r1h(effective over-burden pressure) were explained as Py=l. 12 ∑r'h in case of land district soil and as Py=l. l5∑r'h in case of harbour district soil. 7. Some of the properties show good correlations between them, practical and effective applications of these correlations are expected in the planning and excution of soil investigation and also in the evaluation of the results.

• Journal of Environmental Health Sciences
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• v.35 no.6
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• pp.517-525
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• 2009

The water quality of Lake Shihwa had been rapidly deteriorating since 1994 due to wastewater input from the watersheds, limited water circulation and the lack of a wastewater treatment policy. In 2000, the government decided to open the tidal embankment and make a comprehensive management plan to improve the water quality, especially inflowing stream water around Shihwa and Banwol industrial complex. However, the water quality and microbial community have not as yet been fully evaluated. The purpose of this study is to investigate the influent water quality around the industrial area based on chemical and biological analysis, and collected surface water sample from the Siheung Stream, up-stream to down-stream through the industrial complex, Samples were collected in July 2009. The results show that the downstream site near the industrial complex had higher concentrations of heavy metals (Cu, Mn, Fe, Mg, and Zn) and organic matter than upstream sites. A combination of DGGE (Denaturing Gradient Gel Electrophoresis) gels, lists of K-WQI (Korean Water Quality Index), cluster analysis, MDS (Multi-Dimensional Scaling) and PCA (Principal Component Analysis) has demonstrated clear clustering between Siheung stream 3 and 4 and with a high similarity and detected metal reducing bacteria (Shewanella spp.) and biodegrading bacteria (Acinetobacter spp.). These results suggest that use of both chemical and microbiological marker would be useful to fully evaluate the water quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.