• Design & Manufacturing
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• v.16 no.3
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• pp.1-8
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• 2022

In this study, an artificial neural network(ANN) was constructed to establish the relationship between process condition prameters and the qualities of the injection-molded product in the injection molding process. Six process parmeters were set as input parameter for ANN: melt temperature, mold temperature, injection speed, packing pressure, packing time, and cooling time. As output parameters, the mass, nominal diameter, and height of the injection-molded product were set. Two learning structures were applied to the ANN. The single-task learning, in which all output parameters are learned in correlation with each other, and the multi-task learning structure in which each output parameters is individually learned according to the characteristics, were constructed. As a result of constructing an artificial neural network with two learning structures and evaluating the prediction performance, it was confirmed that the predicted value of the ANN to which the multi-task learning structure was applied had a low RMSE compared with the single-task learning structure. In addition, when comparing the quality specifications of injection molded products with the prediction values of the ANN, it was confirmed that the ANN of the multi-task learning structure satisfies the quality specifications for all of the mass, diameter, and height.

• Physical Therapy Korea
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• v.19 no.3
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• pp.40-50
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• 2012

The purpose of this study was to investigate the effect of visual feedback on the postural control of stroke patients, by systematically varying conditions of visual feedback [eye-open condition (EO) vs. eye-closed condition (EC)], and base-support (both-side support, affected-side support, and unaffected-side support). In this study, we allocated 41 stroke patients with no damage in the cerebellum and visual cortex who can walk at least 10 meters independently, and 35 normal adults who have no experience of stroke to the control group. Both groups were asked to perform a "sit-to-stand" task three to five times, and their postural control ability was measured and compared in terms of asymmetric dependence (AD) instead of the traditional symmetric index (SI) in the literature. The results showed that although both subject groups maintained better postural control in the EO condition than in the EC condition, the patient group appeared to be more stable in EC than in EO when they were required to perform the task of the support condition given on the affected side. These results implied that visual feedback can impair stroke patients' postural control when it is combined with a specific support condition.

• Journal of the Ergonomics Society of Korea
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• v.28 no.3
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• pp.73-79
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• 2009

Driving is a complex psychomotor task often interrupted by secondary activities that increase cognitive workload and divert attention away from the roadway. The risk of inattentive driving is known to vary with age. To assess the characteristics of advancing age on driver's cognitive workload under dual task condition, we evaluate the performance of 96 drivers divided into three age groups: 20's, 40's, and 60's. This study considers driver's cognitive workload in the context of urban and highway driving. Error rate & Dual task cost are used to measure driver's cognitive workload. Results indicate that age impacts cognitive workload during dual task driving conditions.

• Wind and Structures
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• v.14 no.6
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• pp.517-536
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• 2011

The assessment of wind-induced motion plays an important role in the development and design of the majority of today's structures that push the limits of engineering knowledge. A vital part of the design is the prediction of wind-induced tall building motion and the assessment of its effects on occupant comfort. Little of the research that has led to the development of the various international standards for occupant comfort criteria have considered the effects of the low-frequency motion on task performance and interference with building occupants' daily activities. It has only recently become more widely recognized that it is no longer reasonable to assume that the level of motion that a tall building undergoes in a windstorm will fall below an occupants' level of perception and little is known about how this motion perception could also impact on task performance. Experimental research was conducted to evaluate the performance of individuals engaged in a manual tracking task while subjected to low level vibration in the frequency range of 0.125 Hz-0.50 Hz. The investigations were carried out under narrow-band random vibration with accelerations ranging from 2 milli-g to 30 milli-g (where 1 milli-g = 0.0098 $m/s^2$) and included a control condition. The frequencies and accelerations simulated are representative of the level of motion expected to occur in a tall building (heights in the range of 100 m -350 m) once every few months to once every few years. Performance of the test subjects with and without vibration was determined for 15 separate test conditions and evaluated in terms of time taken to complete a task and accuracy per trial. Overall, the performance under the vibration conditions did not vary significantly from that of the control condition, nor was there a statistically significant degradation or improvement trend in performance ability as a function of increasing frequency or acceleration.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2266-2268
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• 2009

In this paper, a simple method of angle velocity estimation is presented for a passive dynamic biped robot. The estimation problem is not an easy task because its dynamic model is a hybrid system involved with an impact condition. Instead of designing a complex observer for hybrid systems we simply utilize the impact condition to reset the initial condition of the high-pass filter when the non-support leg hits the slope. The approach has been verified by simulation results.

• The Korean Journal of Nuclear Medicine
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• v.39 no.6
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• pp.413-420
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• 2005

Purpose: Neuroreceptor PET studies require 60-120 minutes to complete and head motion of the subject during the PET scan increases the uncertainty in measured activity. In this study, we investigated the effects of the data-driven head mutton correction on the evaluation of endogenous dopamine release (DAR) in the striatum during the motor task which might have caused significant head motion artifact. Materials and Methods: $[^{11}C]raclopride$ PET scans on 4 normal volunteers acquired with bolus plus constant infusion protocol were retrospectively analyzed. Following the 50 min resting period, the participants played a video game with a monetary reward for 40 min. Dynamic frames acquired during the equilibrium condition (pre-task: 30-50 min, task: 70-90 min, post-task: 110-120 min) were realigned to the first frame in pre-task condition. Intra-condition registrations between the frames were performed, and average image for each condition was created and registered to the pre-task image (inter-condition registration). Pre-task PET image was then co-registered to own MRI of each participant and transformation parameters were reapplied to the others. Volumes of interest (VOI) for dorsal putamen (PU) and caudate (CA), ventral striatum (VS), and cerebellum were defined on the MRI. Binding potential (BP) was measured and DAR was calculated as the percent change of BP during and after the task. SPM analyses on the BP parametric images were also performed to explore the regional difference in the effects of head motion on BP and DAR estimation. Results: Changes in position and orientation of the striatum during the PET scans were observed before the head motion correction. BP values at pre-task condition were not changed significantly after the intra-condition registration. However, the BP values during and after the task and DAR were significantly changed after the correction. SPM analysis also showed that the extent and significance of the BP differences were significantly changed by the head motion correction and such changes were prominent in periphery of the striatum. Conclusion: The results suggest that misalignment of MRI-based VOI and the striatum in PET images and incorrect DAR estimation due to the head motion during the PET activation study were significant, but could be remedied by the data-driven head motion correction.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.267-274
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• 2014

The purpose of this study is to identify a relationship between the time taken and the characteristics of touch key for touch-screen-based in-vehicle information system (IVIS) and to suggest a new Fitts' law formula that is added a driving speed parameter. Many studies already have shown that Fitts' law is well fitted in various devices for primary tasks, but there is no study of Fitts' law for secondary task in dual-task situation. Fitts' law may not be applied to the secondary task as it is, because the secondary task performance can be affected by the amount of attention for the primary task. To verify this, we carried out an experiment that showed whether pointing task to touch-screen-based IVIS during driving is affected by driving speeds or not. In the experiment, 30 people were volunteered for participants and the participants carried out driving task and pointing task on the screen of IVIS simultaneously. We measured the time to point a touch key on IVIS for every condition (3 driving speeds${\times}5$ touch key sizes${\times}7$ distances between steering wheel and touch key). As a result, there was an effect of driving speed on the pointing time. As we extended the index of difficulty of the conventional Fitts' law formula by incorporating driving speed, we established an extended Fitts' law formula for pointing on IVIS, which showed better accordance with dual task situation. This study can be evidence that secondary task performance is affected by degree of concentration on primary task, and the extended Fitts' law formula can be useful to design interfaces of IVIS.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.6
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• pp.549-557
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• 2000

Distributed Memory Machine(DMM) is necessary for the effective computation of the data which is complicated and very large. Task scheduling is a method that reduces the communication time among tasks to reduce the total execution time of application program and is very important for the improvement of DMM. Task Duplicated based Scheduling(TDS) method improves execution time by reducing communication time of tasks. It uses clustering method which schedules tasks of the large communication time on the same processor. But there is a problem that cannot optimize communication time between task sending data and task receiving data. Hence, this paper proposes a new method which solves the above problem in TDS. Modified Task Duplicated based Scheduling(MTDS) method which can approximately optimize the communication time between task sending data and task receiving data by checking the optimal condition, resulted in the minimization of task execution time by reducing the communication time among tasks. Also system modeling shows that task execution time of MTDS is about 70% faster than that of TDS in the best case and the same as the result of TDS in the worst case. It proves that MTDS method is better than TDS method.

• Phonetics and Speech Sciences
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• v.10 no.4
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• pp.77-89
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• 2018

Speech articulators are coordinated for the purpose of segmental constriction in terms of a task. In particular, vertical jaw movements repeatedly contribute to consonantal as well as vocalic constriction. The current study explores vertical jaw movements in conjunction with bilabial constriction in bilabial stop /p/ in the context /a/-to-/a/. Revisiting kinematic data of /p/ collected using the electromagenetic midsagittal articulometer (EMMA) method from seven (four female and three male) speakers of Seoul Korean, we examined maximum vertical jaw position, its relative timing with respect to the upper and lower lips, and lip aperture minima. The results of those dependent variables are recapitulated in terms of linguistic (different word boundaries) and paralinguistic (different speech rates) factors as follows. Firstly, maximum jaw height was lower in the across-word boundary condition (across-word < within-word), but it did not differ as a function of different speech rates (comfortable = fast). Secondly, more reduction in the lip aperture (LA) gesture occurred in fast rate, while word-boundary effects were absent. Thirdly, jaw raising was still in progress after the lips' positional extrema were achieved in the within-word condition, while the former was completed before the latter in the across-word condition. Lastly, relative temporal lags between the jaw and the lips (UL and LL) were more synchronous in fast rate, compared to comfortable rate. When these results are considered together, it is possible to posit that speakers are not tolerant of lenition to the extent that it is potentially realized as a labial approximant in either word-boundary condition while jaw height still manifested lower jaw position in the across-word boundary condition. Early termination of vertical jaw maxima before vertical lower lip maxima across-word condition may be partly responsible for the spatial reduction of jaw raising movements. This may come about as a consequence of an excessive number of factors (e.g., upper lip height (UH), lower lip height (LH), jaw angle (JA)) for the representation of a vector with two degrees of freedom (x, y) engaged in a gesture-based task (e.g., lip aperture (LA)). In the task-dynamic application toolkit, the jaw angle parameter can be assigned numerical values for greater weight in the across-word boundary condition, which in turn gives rise to lower jaw position. Speech rate-dependent spatial reduction in lip aperture may be able to be resolved by means of manipulating activation time of an active tract variable in the gestural score level.

• Smart Structures and Systems
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• v.31 no.4
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• pp.383-392
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• 2023

Post-earthquake building condition assessment is crucial for subsequent rescue and remediation and can be automated by emerging computer vision and deep learning technologies. This study is based on an endeavour for the 2nd International Competition of Structural Health Monitoring (IC-SHM 2021). The task package includes five image segmentation objectives - defects (crack/spall/rebar exposure), structural component, and damage state. The structural component and damage state tasks are identified as the priority that can form actionable decisions. A multi-task Convolutional Neural Network (CNN) is proposed to conduct the two major tasks simultaneously. The rest 3 sub-tasks (spall/crack/rebar exposure) were incorporated as auxiliary tasks. By synchronously learning defect information (spall/crack/rebar exposure), the multi-task CNN model outperforms the counterpart single-task models in recognizing structural components and estimating damage states. Particularly, the pixel-level damage state estimation witnesses a mIoU (mean intersection over union) improvement from 0.5855 to 0.6374. For the defect detection tasks, rebar exposure is omitted due to the extremely biased sample distribution. The segmentations of crack and spall are automated by single-task U-Net but with extra efforts to resample the provided data. The segmentation of small objects (spall and crack) benefits from the resampling method, with a substantial IoU increment of nearly 10%.