• The Journal of Korean Physical Therapy
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• v.23 no.1
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• pp.7-11
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• 2011

Purpose: Driving is essential to maintain independent living status in modern times. Many patients want to know when they can drive again, but it's only possible if they have the ability to control lower extremity muscles. In this study, we compared the effects of velocity on onset time of lower extremity muscles during driving tasks. Methods: Twelve participants (5 male, 7 female) were enrolled. EMGs were used to test the onset time of lower extremity muscles; tibialis anterior, soleus, rectus femoris. To analyze the data, we used two way ANOVA. Results: According to brake pedaling velocity, there was a significant difference in brake response time (p<0.05). Further, when comparing the lower extremity muscles, there was a significant difference in onset time (p<0.05). The order of muscle recruitment was tibialis anterior, rectus femoris, and soleus for achieving maximal velocity, but the order was rectus femoris, tibialis anterior, soleus for achieving submaximal velocity. Conclusion: Brake pedaling velocity has significant effects on onset time of muscle contractions in the lower extremities. We suggested that a future study needs more subjects and more detailed research such as evaluat-ions of visuo-motor coordination and fine motor dexterity.

• Smart Structures and Systems
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• v.28 no.6
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• pp.799-810
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• 2021

When monitoring the structural integrity of a bridge using data collected through accelerometers, identifying the profile of the load exerted on the bridge from the vehicles passing over it becomes a crucial task. In this study, the speed and location of vehicles on the deck of a bridge is reconfigured using real-time video to implicitly associate the load applied to the bridge with the response from the bridge sensors to develop an image-based deep learning network model. Instead of directly measuring the load that a moving vehicle exerts on the bridge, the intention in the proposed method is to replace the correlation between the movement of vehicles from CCTV images and the corresponding response by the bridge with a neural network model. Given the framework of an input-output-based system identification, CCTV images secured from the bridge and the acceleration measurements from a cantilevered beam are combined during the process of training the neural network model. Since in reality, structural damage cannot be induced in a bridge, the focus of the study is on identifying local changes in parameters by adding mass to a cantilevered beam in the laboratory. The study successfully identified the change in the material parameters in the beam by using the deep-learning neural network model. Also, the method correctly predicted the acceleration response of the beam. The proposed approach can be extended to the structural health monitoring of actual bridges, and its sensitivity to damage can also be improved through optimization of the network training.

• Journal of Platform Technology
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• v.11 no.6
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• pp.79-88
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• 2023

Recently, industrial accidents have continued to increase due to the industrialization, and worker safety management is recognized as essential to reduce losses due to hazardous factors at work places. To manage the safety of workers, it is required to apply customized safety management artificial intelligence technology that takes into account the characteristics of industrial sites, and a service for real-time risk detection and response to workers depending on the situation based on safety accident types and risk analysis for each task and process. The proposed safety management service consists of worker devices to acquire sensor data, edge devices to collect from IoT-based sensors, and a voice chatbot to support workers' disaster response. The voice chatbot plays a major role in interacting with workers at disaster sites to respond to risks. This paper focuses on real-time risk response using an IoT-based system and voice chatbot on a server for work safety according to the worker's situation. A Scenario-based voice chatbot is used to process responses at the edge level to provide safety management services.

• Smart Structures and Systems
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• v.6 no.1
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• pp.17-27
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• 2010

The approach to damage detection and localization adopted in this paper is based on a statistical comparison of models built from the response time histories collected at different stages during the structure lifetime. Some of these time histories are known to have been recorded when the structural system was undamaged. The consistency of the models associated to two different stages, both undamaged, is first recognized. By contrast, the method detects the discrepancies between the models from measurements collected for a damaged situation and for the undamaged reference situation. The damage detection and localization is pursued by a comparison of the SSE (sum of the squared errors) histograms. The validity of the proposed approach is tested by applying it to the analytical benchmark problem developed by the ASCE Task Group on Structural Health Monitoring (SHM). In the paper, the results of the benchmark studies are presented and the performance of the method is discussed.

• International Journal of Contents
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• v.2 no.1
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• pp.39-44
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• 2006

Load sharing is a critical resource in computer system. In sender-initiated load sharing algorithms, the sender continues to send unnecessary request messages for load transfer until a receiver is found while the system load is heavy. Meanwhile, in the receiver initiated load sharing algorithms, the receiver continues to send an unnecessary request message for load acquisition until a sender is found while the system load is light. These unnecessary request messages result in inefficient communications, low CPU utilization, and low system throughput in distributed systems. To solve these problems, we propose a genetic algorithm based approach for improved sender-initiated and receiver-initiated load sharing in distributed systems. And we expand this algorithm to an adaptive load sharing algorithm. Compared with the conventional sender-initiated and receiver-initiated algorithms, the proposed algorithm decreases the response time and task processing time.

• Smart Structures and Systems
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• v.23 no.2
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• pp.123-139
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• 2019

Impact forces induced by external object collisions can cause serious damages to civil engineering structures. While accurate and prompt identification of such impact forces is a critical task in structural health monitoring, it is not readily feasible for civil structures because the force measurement is extremely challenging and the force location is unpredictable for full-scale field structures. This study proposes a novel approach for identification of impact force including its location and time history using a small number of multi-metric observations. The method combines an augmented Kalman filter (AKF) and Genetic algorithm for accurate identification of impact force. The location of impact force is statistically determined in the way to minimize the AKF response estimate error at measured locations and then time history of the impact force is accurately constructed by optimizing the error co-variances of AKF using Genetic algorithm. The efficacy of proposed approach is numerically demonstrated using a truss and a plate model considering the presence of modelling error and measurement noises.

• Korean Journal of Cognitive Science
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• v.28 no.1
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• pp.27-42
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• 2017

Stroop effect(Stroop, 1935) is a reliable paradigm which has been used in various psychological research. Although classic Stroop experiment used color and color name for experimental stimuli, subsequent research reported that a color(e.g. green) and an object(e.g. grass) which displays a typical color show similar effects depending on color-object congruency(Klein, 1964). Because past research that used Stroop effect to investigate semantic representation tested association between concrete object and color, they predominantly used concrete nouns and their corresponding color names as stimuli(e.g. Dalrymple-Alford, 1968, 1972; Klein, 1964). Recently, Sherman and Clore(2009) reported that response time to white or black words is affected by moral value of words (e.g., honesty, crime) even when the words do not have specific referents. Based on this result, we tested association between thermesthesia-related adjectives(e.g., 따스한, 냉정한) and color(warm color, cold color) using Stroop task. The results showed that subjects were faster in their response to color when adjective-color was congruent than when incongruent, and there was an interaction between color and meaning of adjectives. The Stroop effect in this research is unique because, contrary to previous research that used concrete nouns, the effect was obtained even with abstract adjectives which do not have specific referents. In addition, unlike Sherman and Clore(2009) that used achromatic color, our results show that Stroop effect obtains between abstract adjectives and chromatic color.

• Science of Emotion and Sensibility
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• v.22 no.4
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• pp.75-84
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• 2019

Addicts pay more attention to addiction-related cues, such as substance or behavior. And increased attention to these cues is associated with craving. Methamphetamine is the most abused drug among domestic drug offenders, with continually increasing rates of recidivism. Of the total number of reported drug offenders in the last three years, 21.1 percent have been women. Even so, research on female drug offenders is inadequate, rendering policies and fundamental data for the development of psychotherapy programs insufficient. The present study intended to investigate whether female methamphetamine addicts displayed an attention bias towards drug cues. A dot probe task was conducted on 22 female methamphetamine addicts (addiction group) and 22 non-addicts (control group). The task allowed the correct response rates and correct reaction times of the participants to be calculated according to the positioning of the drug and neutral cues. The analysis results revealed that the control group displayed no difference in correct reaction rates and correct reaction times between the drug or neutral cues. While, the addiction group showed lower correct response rate and slower response time for drug cues in comparison to neutral cues. The results of this study are significant in that it identified the attention bias characteristics toward drug cues of female methamphetamine addicts who were disconnected from drugs.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.347-360
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• 2001

The most expensive spatial operation in spatial databases is a spatial join which computes a combined table of which tuple consists of two tuples of the two tables satisfying a spatial predicate. Although the execution time of sequential processing of a spatial join has been so far considerably improved, the response time is not tolerable because of not meeting the requirements of interactive users. It is usually appropriate to use parallel processing to improve the performance of spatial join processing. However, as the number of processors increases, the efficiency of each processor decreases rapidly because of the disk bottleneck and the overhead of message passing. This paper proposes the method of task allocation to soften the disk bottleneck caused by accessing the shared disk at the same time, and to minimize message passing among processors. In order to evaluate the performance of the proposed method in terms of the number of disk accesses and message passing, we conduct experiments on the two kinds of parallel spatial join algorithms. The experimental tests on the MIMD parallel machine with shared disks show that the proposed semi-dynamic task allocation method outperforms the static and dynamic task allocation methods.

• Journal of the Korea Convergence Society
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• v.5 no.4
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• pp.137-146
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• 2014

This study investigated the effects of response prompting through 3-steps compliance training to reaction time for child with Asperger's syndrome(AS). The participant was 3 and 8 year-old boy who was diagnostic As with non-compliant, delayed receptive language. Study design was multiple-baseline across behaviors. Target Behaviors were hands-up, following direction, and answering behavior. Dependent variable was latency reaction time during compliance training. This results mean that reaction time was increased raise hands-up behavior, compliance behavior and response ask questions. During intervention, the participant improve the rate on-task behavior as well as reduce off-task behaviors.