• Journal of the Korean Society of Visualization
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• v.15 no.1
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• pp.32-40
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• 2017

Interaction between fluid and a rigid object is frequently observed in everyday life. However, it is difficult to simulate their interaction as the medium and the object have different representations. One of the challenging issues arises especially in handling deformation of the object visually as well as rendering haptic feedback. In this paper, we propose a real-time simulation technique for multimodal interaction between particle-based fluids and soluble solids. We have developed the dissolution behavior model of solids, which is discretized based on the idea of smoothed particle hydrodynamics, and the changes in physical properties accompanying dissolution is immediately reflected to the object. The user is allowed to intervene in the simulation environment anytime by manipulating the solid object, where both visual and haptic feedback are delivered to the user on the fly. For immersive visualization, we also adopt the screen space fluid rendering technique which can balance realism and performance.

• Journal of Preventive Medicine and Public Health
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• v.51 no.1
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• pp.1-5
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• 2018

Smokers keep smoking despite knowing that tobacco claims many lives, including their own and others'. What makes it hard for them to quit smoking nonetheless? Tobacco companies insist that smokers choose to smoke, according to their right to self-determination. Moreover, they insist that with motivation and willpower to quit smoking, smokers can easily stop smoking. Against this backdrop, this paper aims to discuss the addictive disease called tobacco use disorder, with an assessment of the addictiveness of tobacco and the reasons why smoking cessation is challenging, based on neuroscientific research. Nicotine that enters the body via smoking is rapidly transmitted to the central nervous system and causes various effects, including an arousal response. The changes in the nicotine receptors in the brain due to continuous smoking lead to addiction symptoms such as tolerance, craving, and withdrawal. Compared with other addictive substances, including alcohol and opioids, tobacco is more likely to cause dependence in smokers, and smokers are less likely to recover from their dependence. Moreover, the thinning of the cerebral cortex and the decrease in cognitive functions that occur with aging accelerate with smoking. Such changes occur in the structure and functions of the brain in proportion to the amount and period of smoking. In particular, abnormalities in the neural circuits that control cognition and decision-making cause loss of the ability to exert self-control and autonomy. This initiates nicotine dependence and the continuation of addictive behaviors. Therefore, smoking is considered to be a behavior that is repeated due to dependence on an addictive substance, nicotine, instead of one's choice by free will.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3018-3040
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• 2018

The mobility model is one of the most important factors that impacts the evaluation of any transportation vehicular networking protocols via simulations. However, to obtain a realistic mobility model in the dynamic urban environment is a very challenging task. Several studies extract mobility models from large-scale real data sets (mostly taxi GPS data) in recent years, but they do not consider the statuses of taxi, which is an important factor affected taxi's mobility. In this paper, we discover three simple observations related to the taxi statuses via mining of real taxi trajectories: (1) the behavior of taxi will be influenced by the statuses, (2) the macroscopic movement is related with different geographic features in corresponding status, and (3) the taxi load/drop events are varied with time period. Based on these three observations, a novel taxi mobility model (T-START) is proposed with respect to taxi statuses, geographic region and time period. The simulation results illustrate that proposed mobility model has a good approximation with reality in trajectory samples and distribution of nodes in four typical time periods.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.45-48
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• 2008

The mechanical behavior of small-sized materials has been investigated for many industrial applications, including MEMS and semiconductors. It is challenging to obtain accurate mechanical properties measurements for thin films due to several technical difficulties, including measurement of strain, specimen alignment, and fabrication. In this work, we used the micro-tensile testing unit with the real-time DIC (Digital Image Correlation) strain measurement system. This system has advantages of real time strain monitoring up to 50 nm resolution during the micro-tensile test, and ability to measure the young's modulus and Poisson's ratio at the same time. The mechanical properties of SCS (Single Crystal Silicon) are measured by uniaxial tension test from freestanding SCS which are $2.5{\mu}m$ thick, $200-500{\mu}m$ wide specimens on the (100) plane. Young's modulus, Poisson's ratio and tensile strength in the <110> direction are measured by micro-tensile testing system.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.6
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• pp.558-566
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• 2000

Object recognition is a challenging application for high-performance computing. Currently, the superscalar architecture dominates todays microprocessor marketplace. As more transistors are integrated onto larger die, however, an on-chip multiprocessor is regarded as a promising alternative to the superscalar microprocessor. This paper examines the behavior of the object recognition on the on-chip multiprocessor, which will be employed in general-purpose parallel machines. To obtain the performance characteristics of the microprocessor, a program-driven simulator and its programming environment were developed. The simulation results showed that the on-chip multiprocessor can exploit thread level parallelisms effectively and offer a promising architecture for the object recognition application.

• Journal of Powder Materials
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• v.14 no.1 s.60
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• pp.26-31
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• 2007

Manufacturing bulk nanostructured materials with least grain growth from initial powders is challenging because of the bottle neck of bottom-up methods using the conventional powder metallurgy of compaction and sintering. In this study, bottom-up type powder metallurgy processing and top-down type SPD (Severe Plastic Deformation) approaches were combined in order to achieve both real density and grain refinement of metallic powders. ECAP (Equal Channel Angular Pressing), one of the most promising processes in SPD, was used for the powder consolidation method. For understanding the ECAP process, investigating the powder density as well as internal stress, strain distribution is crucial. We investigated the consolidation and plastic deformation of the metallic powders during ECAP using the finite element simulations. Almost independent behavior of powder densification in the entry channel and shear deformation in the main deformation zone was found by the finite element method. Effects of processing parameters on densification and density distributions were investigated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3496-3514
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• 2015

One of the challenging tasks in Mobile Ad hoc Network is to discover precise optimal routing solution due to the infrastructure-less dynamic behavior of wireless mobile nodes. Ant Colony Optimization, a swarm Intelligence technique, inspired by the foraging behaviour of ants in colonies was used in the past research works to compute the optimal path. In this paper, we propose a Recurrent Ant Colony Optimization (RECACO) that executes the actual Ant Colony Optimization iteratively based on recurrent value in order to obtain an optimal path convergence. Each iteration involves three steps: Pheromone tracking, Pheromone renewal and Node selection based on the residual energy in the mobile nodes. The novelty of our approach is the inclusion of new pheromone updating strategy in both online step-by-step pheromone renewal mode and online delayed pheromone renewal mode with the use of newly proposed metric named ELD (Energy Load Delay) based on energy, Load balancing and end-to-end delay metrics to measure the performance. RECACO is implemented using network simulator NS2.34. The implementation results show that the proposed algorithm outperforms the existing algorithms like AODV, ACO, LBE-ARAMA in terms of Energy, Delay, Packet Delivery Ratio and Network life time.

• International Journal of Railway
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• v.7 no.1
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• pp.16-23
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• 2014

Reduction in railway-induced vibrations in urban areas is a very challenging task in railway transportation. Many mitigation measures can be considered and applied. Among these, a little attention has been paid to trenches. In this study, a numerical investigation on the effectiveness of in-filled trenches with pipes in reducing railway vibrations due to passing trains is presented. Particularly, a series of two-dimensional dynamic analysis was performed to model the behavior of ballasted railway track under harmonic load with ABAQUS software as a Finite Element method. In so doing, two types of in-filled trenches with pipes with steel and concrete materials have been investigated in this paper. In addition, effectiveness of pipes made of steel and concrete, filled with loose sand and clay in railway-induced vibration reduction has been assessed. The results point out that using in-filled trench with pipes does not effective a lot on railway-induced vibration reduction in comparison to other railway-induced vibration reduction methods. However, in-filled trenches with steel pipes are much more effective than in-filled trenches with concrete pipes. Moreover, filling pipes with loose sand and clay does not have any effect on vibration reduction efficiency of these in-filled trenches.

• Smart Structures and Systems
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• v.4 no.6
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• pp.809-828
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• 2008

Real-time hybrid testing is an attractive method to evaluate the response of structures under earthquake loads. The method is a variation of the pseudodynamic testing technique in which the experiment is executed in real time, thus allowing investigation of structural systems with time-dependent components. Real-time hybrid testing is challenging because it requires performance of all calculations, application of displacements, and acquisition of measured forces, within a very small increment of time. Furthermore, unless appropriate compensation for time delays and actuator time lag is implemented, stability problems are likely to occur during the experiment. This paper presents an approach for real-time hybrid testing in which time delay/lag compensation is implemented using model-based response prediction. The efficacy of the proposed strategy is verified by conducting substructure real-time hybrid testing of a steel frame under earthquake loads. For the initial set of experiments, a specimen with linear-elastic behavior is used. Experimental results agree well with the analytical solution and show that the proposed approach and testing system are capable of achieving a time-scale expansion factor of one (i.e., real time). Additionally, the proposed method allows accurate testing of structures with larger frequencies than when using conventional time delay compensation methods, thus extending the capabilities of the real-time hybrid testing technique. The method is then used to test a structure with a rate-dependent energy dissipation device, a magnetorheological damper. Results show good agreement with the predicted responses, demonstrating the effectiveness of the method to test rate-dependent components.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.559-568
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• 2014

Induction motors are critical components in industrial processes since their failure usually lead to an unexpected interruption at the industrial plant. The studies of induction motor behavior during abnormal conditions and the possibility to diagnose different types of faults have been a challenging topic for many electrical machine researchers. In this regard, an efficient and new method to detect the induction motor-fault may be the application of the Time Synchronous Averaging (TSA) to the stator current Park's Vector. The aim of this paper is to present a methodology by which defects in a three-phase wound rotor induction motor can be diagnosed. By exploiting the cyclostationarity characteristics of electrical signals, the TSA method is applied to the stator current Park's Vector, allowing the monitoring of the induction motor operation. Simulation and experimental results are presented in order to show the effectiveness of the proposed method. The obtained results are largely satisfactory, indicating a promising industrial application of the hybrid Park's Vector-TSA approach.