• Interaction and multiscale mechanics
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• v.5 no.3
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• pp.229-265
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• 2012

Hygroexpansion of wood is a known and undesired characteristic in civil engineering. When wood is exposed to changing environmental humidity, it adsorbs or desorbs moisture and warps. The resulting distortions or - at restrained conditions - cracks are a major concern in timber engineering. We herein present a multiscale model for prediction of the macroscopic hygroexpansion behavior of individual pieces of softwood from their microstructure, demonstrated for spruce. By applying poromicromechanics, we establish a link between the swelling pressure, driving the hygroexpansion of wood at the nanoscale, and the resulting macroscopic dimensional changes. The model comprises six homogenization steps, which are performed by means of continuum micromechanics, the unit cell method and laminate theory, all formulated in a poromechanical framework. Model predictions for elastic properties of wood as functions of the moisture content closely approach corresponding experimental data. As for the hygroexpansion behavior, the swelling pressure has to be back-calculated from macroscopic hygroexpansion data. The good reproduction of the anisotropy of wood hygroexpansion, based on only a single scalar calibration parameter, underlines the suitability of the model. The multiscale model constitutes a valuable tool for studying the effect of microstructural features on the macroscopic behavior and for assessing the hygroexpansion behavior at smaller length scales, which are inaccessible to experiments. The model predictions deliver input parameters for the analysis of timber at the structural scale, therewith enabling to optimize the use of timber and to prevent moisture-induced damage or failure.

• Earthquakes and Structures
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• v.7 no.2
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• pp.141-157
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• 2014

The Conditional Mean Spectrum represents a powerful link between the seismic hazard information and the selection of strong ground motion records at a particular site. The scope of the paper is to apply for the city of Bucharest for the first time the method to obtain the Conditional Mean Spectrum (CMS) presented by Baker (2011) and to select, on the basis of the CMS, a suite of strong ground motions for performing elastic and inelastic dynamic analyses of buildings and structures with fundamental periods of vibration in the vicinity of 1.0 s. The major seismic hazard for Bucharest and for most of Southern and Eastern Romania is dominated by the Vrancea subcrustal seismic source. The ground motion prediction equation developed for subduction-type earthquakes and soil conditions by Youngs et al. (1997) is used for the computation of the Uniform Hazard Spectrum (UHS) and the CMS. The disaggregation of seismic hazard is then performed in order to determine the mean causal values of magnitude and source-to-site distance for a particular spectral ordinate (for a spectral period T = 1.0 s in this study). The spectral period of 1.0 s is considered to be representative for the new stock of residential and office reinforced concrete (RC) buildings in Bucharest. The differences between the Uniform Hazard Spectrum (UHS) and the Conditional Mean Spectrum (CMS) are discussed taking into account the scarcity of ground motions recorded in the region of Bucharest and the frequency content characteristics of the recorded data. Moreover, a record selection based on the criteria proposed by Baker and Cornell (2006) and Baker (2011) is performed using a dataset consisting of strong ground motions recorded during seven Vrancea seismic events.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.3
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• pp.1125-1131
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• 2014

Background: Schistosomiasis is a parasitic disease causing chronic ill health in humans with a serious consequences for socio-economic development in tropical and subtropical regions. There is also evidence linking Schistosoma mansoni to colonic carcinoma occurrence. The aim of this study was to evaluate some inflammatory and oxidative stress biomarkers, as well as L-fucose as linkers between intestinal schistosomiasis and colonic dysplasia development in mice. Materials and Methods: This study was conducted upon 80 mice that were divided the control group (10 non infected mice) and infected group which was subdivided into 7 sub-groups (10 mice each) according to the time of sacrifaction in the post infection (p.i.) period, 10 mice being sacrificed every two weeks from 6 weeks p.i. to 18 weeks p.i. Tumor necrosis factor alpha (TNF-${\alpha}$), inducible nitric oxide synthase (iNOS), and pentraxin 3 (PTX3) levels were estimated by immunoassay. The L-fucose level, and thioredoxin reductase (TrxR) and lactate dehydrogenase (LDH) activities were also evaluated in colonic tissue. Results: The current study revealed statistically significant elevation in the studied biochemical markers especially at 16 and 18 weeks p.i. The results were confirmed by histopathological examination that revealed atypical architectural and cytological changes in the form of epithelial surface serration and nuclear hyper-chromatizia at 14, 16 and 18 weeks p.i. Conclusions: inflammation, oxidative stress and L-fucose together may form an important link between Schistosomal mansoni infection and colonic dysplasia and they can be new tools for prediction of colonic dysplasia development in experimental schistosomiasis.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.5
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• pp.113-118
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• 2015

Mobile wireless networks have received a lot of attention as a future wireless network due to its rapid deployment without communication infrastructure. In these networks communication path between two arbitrary nodes break down because some links in the path are beyond transmission range($r_0$) due to the mobility of the nodes. The set of total path break down time(${\bigcup}T_i$), which is the union of path break down time of every node pair, can be a good measure of the connectivity of the dynamic mobile wireless network. In this paper we show that the distribution of the total path break down time can be approximated as a exponential probability density function and confirms it through experimental data. Statistical knowledge of break down time enables quantitative prediction of delay, packet loss between two nodes, thus provides confidence in the simulation results of mobile wireless networks.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.209-214
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• 2018

In this paper, we recognize the damage caused by a disaster to a facility in the event of a large-scale disaster and present the possible disasters in the form of a matrix. The typhoon was selected as a major disaster and covered mainly the flood damage, a possible damage caused by the typhoon. Flood damage is mainly caused by flooding, and damage is determined by flooding and flow rate, and the results of applying this to low-rise facilities are derived. In addition, the results were derived by applying a method of classification of disaster types in a matrix format to make it easy to see at a glance the connection between disasters caused by damage to a facility. Continuing research in the form presented in this paper will help us identify additional disasters as an occurrence of a disaster.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8S
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• pp.2608-2619
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• 2000

This paper proposes the Handover Scheme for the mobile and describes the result of the performance analysis. In the conventional scheme of handover request, the withdrawal of terminal may occur because handover request is performed based on fixed signal level without considering network load and terminal mobility. The proposed scheme offers the minimization of withdrawal and handover blocking probability by means of the handover request of terminal based on the network load and terminal mobility. Conventional handover scheme has the sequential procedure that network performs resource check and path rerouting on the handover by MT(Mobile Terminal). Proposed handover scheme pre-processes the resource check before the handover request by predicting the handover request timo so that handover latency can be reduced. Moreover, path optimization is executed after the completion of handover in order to reduce handover latency. The rdduction of handover latency prevents the dropping of service by minimizing backward handover blocking. In summary, we propose the prediction of handover request time and decision method based on terminal, validating the performance of proposed scheme considering various cases of simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.2
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• pp.95-101
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• 2017

In this study, we derived theoretical equations for the zigzag movement of a leading vehicle, which is the most frequent behavior in train accidents, by using a simplified spring-mass model for the rolling stock. In order to solve the equations of motion, we applied the Runge-Kutta method, which is the typical numerical analysis method used for differential equations. Furthermore, the lateral displacement of the wheel-set at the wheel-rail interface was estimated using kinetic energy. In order to verify the derived equations, we compared the theoretical and simulated results under various collision conditions. The maximum relative deviations of the lateral displacements were 0.8 [%] ~ 4.7 [%] in light collisions and 0.6 [%] ~ 5.1 [%] under derailment conditions. When an accident is simulated, these theoretical equations can be used to predict the overall behavior and obtain the offset of the body-to-body link as the initial perturbation.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.41-48
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• 2020

The sensor nodes in underwater IoT networks have practical limitations in power supply. Thus, the reduction of power consumption is one of the most important issues in underwater environments. In this regard, AMC(Adaptive Modulation and Coding) techniques are used by using the relation between SNR and BER. However, according to our hands-on experience, we observed that the relation between SNR and BER is not that tight in underwater environments. Therefore, we propose a deep learning based MLP classification model to reflect multiple underwater channel parameters at the same time. It correctly predicts BER with a high accuracy of 85.2%. The proposed model can choose the best parameters to have the highest throughput. Simulation results show that the throughput can be enhanced by 4.4 times higher than the conventionally measured results.

• The KIPS Transactions:PartC
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• v.12C no.6 s.102
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• pp.799-808
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• 2005

This paper proposes low latency handover procedure for seamless connectivity and QoS support between wired (e.g. Ethernet) and wireless (e.g. WLAN, WiBro(802.16-compatible), CDMA) networks by the mobile-assisted and server-initiated handover strategy. It is assumed that the server decides the best target network considering network status and user preferences. In this algorithm a mobile terminal associates with the wireless link decided at the server In advance and receives CoA as well. When handover occurs without the prediction in wired networks, the server performs fast binding update using physical handover trigger through the MIH(media independent handover) function. As a result, a mobile terminal does not need to perform L2 and L3 handover during handover so that this procedure decreases handover latency and loss.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.4
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• pp.367-379
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• 2010

Future climate changes over the Seoul metropolitan area (SMA) were predicted by the Weather Research and Forecasting (WRF) model using future land-use data from the urban growth model (SLEUTH) and forecast fields from ECHAM5/MPI-OM1 GCM (IPCC scenario A1B). Simulations from the SLEUTH model with GIS information (slope, urban, hill-shade, etc.) derived from the water management information system (WAMIS) and the intelligent transportation systems-standard nodes link (ITS-SNL) showed that considerable increase by 17.1% in the fraction of urban areas (FUA) was found within the SMA in 2020. To identify the effects of the urban growth on the temperature and wind variations in the future, WRF simulations by considering urban growth were performed for two seasons (summer and winter) in 2020s (2018~2022) and they were compared with those in the present (2003~2007). Comparisons of model results showed that significant changes in surface temperature (2-meter) were found in an area with high urban growth. On average in model domain, positive increases of $0.31^{\circ}C$ and $0.10^{\circ}C$ were predicted during summer and winter, respectively. These were higher than contributions forced by climate changes. The changes in surface temperature, however, were very small expect for some areas. This results suggested that surface temperature in metropolitan areas like the SMA can be significantly increased only by the urban growth during several decades.