• Parasites, Hosts and Diseases
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• v.49 no.3
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• pp.221-228
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• 2011

Rodent malaria parasites, such as Plasmodium berghei, are practical and useful model organisms for human malaria research because of their analogies to the human malaria in terms of structure, physiology, and life cycle. Exploiting the available genetic sequence information, we constructed a cDNA library from the erythrocytic stages of P. berghei and analyzed the expressed sequence tag (EST). A total of 10,040 ESTs were generated and assembled into 2,462 clusters. These EST clusters were compared against public protein databases and 48 putative new transcripts, most of which were hypothetical proteins with unknown function, were identified. Genes encoding ribosomal or membrane proteins and purine nucleotide phosphorylases were highly abundant clusters in P. berghei. Protein domain analyses and the Gene Ontology functional categorization revealed translation/protein folding, metabolism, protein degradation, and multiple family of variant antigens to be mainly prevalent. The presently-collected ESTs and its bioinformatic analysis will be useful resources to identify for drug target and vaccine candidates and validate gene predictions of P. berghei.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.372-377
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• 2007

For more than 2,500 years, surgical teaching has been based on the so called "see one, do one, teach one" paradigm, in which the surgical trainee learns by operating on patients under close supervision of peers and superiors. However, higher demands on the quality of patient care and rising malpractice costs have made it increasingly risky to train on patients. Minimally invasive surgery, in particular, has made it more difficult for an instructor to demonstrate the required manual skills. It has been recognized that, similar to flight simulators for pilots, virtual reality (VR) based surgical simulators promise a safer and more comprehensive way to train manual skills of medical personnel in general and surgeons in particular. One of the major challenges in the development of VR-based surgical trainers is the real-time and realistic simulation of interactions between surgical instruments and biological tissues. It involves multi-disciplinary research areas including soft tissue mechanical behavior, tool-tissue contact mechanics, computer haptics, computer graphics and robotics integrated into VR-based training systems. The research described in this paper addresses the problem of characterizing soft tissue properties for medical virtual environments. A system to measure in vivo mechanical properties of soft tissues was designed, and eleven sets of animal experiments were performed to measure in vivo and in vitro biomechanical properties of porcine intra-abdominal organs. Viscoelastic tissue parameters were then extracted by matching finite element model predictions with the empirical data. Finally, the tissue parameters were combined with geometric organ models segmented from the Visible Human Dataset and integrated into a minimally invasive surgical simulation system consisting of haptic interface devices and a graphic display.

• Steel and Composite Structures
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• v.18 no.6
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• pp.1369-1389
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• 2015

In order to investigate the behaviour of lying multi-stud connectors in cable-pylon anchorage zone, twenty-four push-out tests are carried out with different stud numbers and diameters. The effect of concrete block width and tensile force on shear strength is investigated using the developed and verified finite element model. The results show that the shear strength of the lying multi-stud connectors is reduced in comparison with the lying single-stud connector. The reduction increases with the increasing of the number of studs in the vertical direction. The influence of the stud number on the strength reduction of the lying multi-stud connectors is decreased under combined shear and tension loads compared with under pure shear. Yet, due to multi-stud effect, they still can't be ignored. The concrete block width has a non-negligible effect on the shear strength of the lying multi-stud connectors and therefore should be chosen properly when designing push-out specimens. No obvious difference is observed between the strength reductions of the studs with 22 mm and 25 mm diameters. The shear strengths obtained from the tests are compared with those predicted by AASHTO LRFD and Eurocode 4. Eurocode 4 generally gives conservative predictions of the shear strength, while AASHTO LRFD overestimates the shear strength. In addition, the lying multi-stud connectors with the diameters of 22 m and 25 mm both exhibit adequate ductility according to Eurocode 4. An expression of load-slip curve is proposed for the lying multi-stud connectors and shows good agreement with the test results.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.131-131
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• 2021

Deep learning models, especially those based on long short-term memory (LSTM), have presented their superiority in addressing time series data issues recently. This study aims to comprehensively evaluate the performance of deep learning models that belong to the supervised learning category in streamflow prediction. Therefore, six deep learning models-standard LSTM, standard gated recurrent unit (GRU), stacked LSTM, bidirectional LSTM (BiLSTM), feed-forward neural network (FFNN), and convolutional neural network (CNN) models-were of interest in this study. The Red River system, one of the largest river basins in Vietnam, was adopted as a case study. In addition, deep learning models were designed to forecast flowrate for one- and two-day ahead at Son Tay hydrological station on the Red River using a series of observed flowrate data at seven hydrological stations on three major river branches of the Red River system-Thao River, Da River, and Lo River-as the input data for training, validation, and testing. The comparison results have indicated that the four LSTM-based models exhibit significantly better performance and maintain stability than the FFNN and CNN models. Moreover, LSTM-based models may reach impressive predictions even in the presence of upstream reservoirs and dams. In the case of the stacked LSTM and BiLSTM models, the complexity of these models is not accompanied by performance improvement because their respective performance is not higher than the two standard models (LSTM and GRU). As a result, we realized that in the context of hydrological forecasting problems, simple architectural models such as LSTM and GRU (with one hidden layer) are sufficient to produce highly reliable forecasts while minimizing computation time because of the sequential data nature.

• Ocean and Polar Research
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• v.34 no.2
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• pp.197-199
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• 2012

According to the IPCC climate change scenario (A1B scenario), the surface seawater temperature of the South Sea of Korea by 2100 may be $2-3.5^{\circ}C$ higher than at present, and seawater pH may decrease from 8.1 to 7.8, due to the increase in atmospheric $CO_2$, which is predicted to increase in concentration from 380 to 750 ppm. These changes may not only intensify the strength of typhoons/storm surges but also affect the function and structure the marine ecosystem. In order to assess the impact of climate change on the marine ecosystem in Korean waters, the project named the 'Assessment of the impact of climate change on marine ecosystem in the South Sea of Korea' has been supported by the Ministry of Land, Transport and Maritime Affairs, from 2008. The goal of this project is to enhance our ability to adapt and prepare for the future environmental changes through the reliable predictions based on the knowledge obtained from projects like this. In this respect, this project is being conducted to investigate the effects of climate/marine environment changes (ocean warming and acidification), and to predict future changes of the structure and function of the ecosystem in the South Sea of Korea. This special issue contains 6 research articles, which are the highlights of the studies carried out through this project.

• Journal of the Korean Geotechnical Society
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• v.19 no.3
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• pp.65-74
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• 2003

The dragload on pile groups in consolidating ground was investigated based on a numerical analysis. The case of a single pile and subsequently the response of groups were analyzed by 2D and 3D finite element studies. Conventional continuum elements and special slip elements were used in the analyses for comparison. Based on a limited parametric study, it is shown that dragload for a single pile and group effect are normally overestimated by continuum analyses, compared with the predictions by the slip analyses. The group effect was examined from the slip analysis by considering various factors such as pile configurations, surface loading, interface friction coefficient, and axial loading on piles. An examplary analysis and one previous experimental observation of dragload and group effects were back-analysed. The case histories demonstrated that the slip analysis might predict a better estimate of dragload and group effect compared to the no-slip continuum analysis.

• Journal of Power Electronics
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• v.14 no.1
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• pp.175-182
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• 2014

Tracking harmonic current quickly and precisely is one of the keys to designing active power filters (APF). In the past, the current state feedback decoupling PI control was an effective means for three-phase systems in the current control of constant voltage constant frequency inverters and high frequency PWM reversible rectifiers. This paper analyzes in detail the limitation of the conventional PI conditioner in the APF application field and presents a novel PI control method. Canceling the delay of one sampling period and the misadjustment for tracking the harmonic current is the key problem of this PI control. In this PI control, the predictive output current value is obtained by a state observer. The delay of one sampling period is remedied in this digital control system by the state observer. The predictive harmonic command current value is obtained by a repetitive predictor synchronously. The repetitive predictor can achieve better predictions of the harmonic current. By this means, the misadjustment of the conventional PI control for tracking the harmonic current is cancelled. The experiment results with a three-level NPC APF indicate that the steady-state accuracy and dynamic response of this method are satisfying when the proposed control scheme is implemented.

• Advances in concrete construction
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• v.9 no.4
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• pp.355-365
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• 2020

The influence of temperature on the material of concrete filled columns (CFCs) under axial loading has been quantitatively studied in this research. CFCs have many various advantages and disadvantages. One of the important inefficiency of classic CFCs design is the practical lack of hooped compression under the operational loads because of the fewer variables of Poisson's rate of concrete compared to steel. This is the reason why the holder tends to break away from the concrete core in elastic stage. It is also suggested to produce concrete filled steel tube columns with an initial compressed concrete core to surpass their design. Elevated temperatures have essentially reduced the strengths of steel tubes and the final capacity of CFCs exposed to fire. Thus, the computation of bearing capacity of concrete filled steel tube columns is studied here. Sometimes, the structures of concrete could be exposed to the high temperatures during altered times, accordingly, outcomes have shown a decrement in compressive-strength, then an increase with the reduction of this content. In addition, the moisture content at the minimal strength is declined with temperature rising. According to Finite Element (FE), the column performance assessment is carried out according to the axial load carrying capacities and the improvement of ductility and strength because of limitations. Self-stress could significantly develop the ultimate stiffness and capacity of concrete columns. In addition, the design equations for the ultimate capacity of concrete columns have been offered and the predictions satisfactorily agree with the numerical results. The proposed based model (FE model of PEC column) 65% aligns with the concrete exposed to high temperature. Therefore, computed solutions have represented a better perception of structural and thermal responses of CFC in fire.

• Analytical Science and Technology
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• v.28 no.3
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• pp.187-195
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• 2015

The heat of sublimation (HOS) is an essential parameter used to resolve environmental problems in the transfer of organic contaminants to the atmosphere and to assess the risk of toxic chemicals. The experimental measurement of the heat of sublimation is time-consuming, expensive, and complicated. In this study, quantitative structural property relationships (QSPR) were used to develop a simple and predictive model for measuring the heat of sublimation of organic compounds. The population-based forward selection method was applied to select an informative subset of descriptors of learning algorithms, such as by using multiple linear regression (MLR) and the support vector machine (SVM) method. Each individual model and consensus model was evaluated by internal validation using the bootstrap method and y-randomization. The predictions of the performance of the external test set were improved by considering their applicability to the domain. Based on the results of the MLR model, we showed that the heat of sublimation was related to dispersion, H-bond, electrostatic forces, and the dipole-dipole interaction between inter-molecules.

• Ocean and Polar Research
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• v.27 no.2
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• pp.189-195
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• 2005

Several models predict large and potentially abrupt ocean circulation changes due to anthropogenic greenhouse-gas emissions. These circulation changes drive-in the models-considerable oceanic oxygen trend. A sound estimate of the observed oxygen trends can hence be a powerful tool to constrain predictions of future changes in oceanic deepwater formation, heat and carbon dioxide uptake. Estimating decadal scale oxygen trends is, however, a nontrivial task and previous studies have come to contradicting conclusions. One key potential problem is that changes in the historical observation network might introduce considerable errors. Here we estimate the likely magnitude of these errors for a subset of the available observations in the Southern Ocean. We test three common data analysis methods south of Australia and focus on the decadal-scale trends between the 1970's and the 1990's. Specifically, we estimate errors due to sparsely sampled observations using a known signal (the time invariant, temporally averaged, World Ocean Atlas 2001) as a negative control. The crossover analysis and the objective analysis methods are for less prone to spatial sampling location biases than the area averaging method. Subject to numerous caveats, we find that errors due to sparse sampling for the area averaging method are on the order of several micro-moles $kg^{-1}$. for the crossover and the objective analysis method, these errors are much smaller. For the analyzed example, the biases due to changes in the spatial design of the historical observation network are relatively small compared to the tends predicted by many model simulations. This raises the possibility to use historic oxygen trends to constrain model simulations, even in sparsely sampled ocean basins.