• The Journal of Korean Physical Therapy
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• 제35권2호
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• pp.43-47
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• 2023

Purpose: This study compared the movement control ability of the ankle joint according to the type of muscle contraction, namely, eccentric or concentric contractions. Methods: Thirty-four healthy adult subjects participated in this study. As a single group, before the experiment, the subjects were trained on achieving the required position of the ankle around the target point by manually controlling the ankle dorsiflexion by 10°. Concentric contraction starts at 0° and continues until the target point of 10° is reached. During an eccentric contraction, the ankle joint starts at 20° ankle dorsiflexion and continues till the target point is reached. Movements using eccentric contraction and concentric contraction were randomly performed 3 times each. Results: The results of comparing the difference in the movement control ability of each type of muscle contraction of ankle dorsiflexion showed that the measurement-remeasurement error was significant in eccentric contraction. Conclusion: In this study, we found a difference in the ability to control movement according to whether the contraction is eccentric or concentric. Therefore, we propose that the ability to control movement is affected by the type of muscle contraction.

• 한국생산제조학회지
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• 제21권2호
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• pp.208-213
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• 2012

In this paper, the radial error of a rotary table at five-axis machine tool is evaluated by utilizing ISO 230-2 and estimation method using double ball-bar. The geometric error of a rotary table is defined as position dependent geometric errors or position independent geometric errors according to their physical character. Then estimation method of geometric errors using double ball-bar is simply summarized including measurement path, parametric modeling and least squares approach. To estimate representative radial error, offset error, set-up error which affect to the double ball-bar data, mean value of measured data including CCW/CW-direction are used at estimation process. Radial errors are separated from measured data and used for evaluation with ISO 230-2. Finally, suggested evaluation method is applied to a rotary table at five-axis machine tool and its result is analyzed to improve the accuracy of the rotary table.

• 한국콘텐츠학회논문지
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• 제6권7호
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• pp.69-78
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• 2006

본 논문에서는 네트워크 물리층이 광소자들로 구성된 액티브 광 링네트워크 시스템에서의 전송 능력과 그에 따른 효율성에 관하여 기술한다. 실험을 위한 시뮬레이션은 광 전송 시스템에서 광 전송 품질을 측정 할 수 있는 트랜스미션메이커 WDM(Transmissionmaker WDM)이 사용되었다. 광액티브 네트워크는 메인링과 서브링에 의한 두 개의 링으로 구성되었다. 서브링의 노드 개수와 각 노드들 간의 간격에 따른 비트 에러율 (Bit Error Rate)의 특성을 측정한다. 이러한 물리층에서의 성능 분석은 액티브 광 링네트워크의 성능 최적화를 위한 설계의 기준이 된다. 따라서 궁극적으로는 실제 가입자망에서 각 노드의 물리적 거리, 트래픽 요구량, 가입자 수를 반영한 효율적인 광전송 시스템을 구성할 수 있다.

• PNF and Movement
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• 제18권2호
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• pp.287-296
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• 2020

Purpose: The study aims were to develop a wearable inertial sensor-based gait analysis device that uses machine learning algorithms, and to validate this novel device using temporal gait parameters. Methods: Thirty-four healthy young participants (22 male, 12 female, aged 25.76 years) with no musculoskeletal disorders were asked to walk at three different speeds. As they walked, data were simultaneously collected by a motion capture system and inertial measurement units (Reseed®). The data were sent to a machine learning algorithm adapted to the wearable inertial sensor-based gait analysis device. The validity of the newly developed instrument was assessed by comparing it to data from the motion capture system. Results: At normal speeds, intra-class correlation coefficients (ICC) for the temporal gait parameters were excellent (ICC [2, 1], 0.99~0.99), and coefficient of variation (CV) error values were insignificant for all gait parameters (0.31~1.08%). At slow speeds, ICCs for the temporal gait parameters were excellent (ICC [2, 1], 0.98~0.99), and CV error values were very small for all gait parameters (0.33~1.24%). At the fastest speeds, ICCs for temporal gait parameters were excellent (ICC [2, 1], 0.86~0.99) but less impressive than for the other speeds. CV error values were small for all gait parameters (0.17~5.58%). Conclusion: These results confirm that both the wearable inertial sensor-based gait analysis device and the machine learning algorithms have strong concurrent validity for temporal variables. On that basis, this novel wearable device is likely to prove useful for establishing temporal gait parameters while assessing gait.

• 인지과학
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• 제34권3호
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• pp.243-257
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• 2023

이 논문의 목적은 고유수용성 감각(proprioception)이 자신의 신체와 신체적 행위(physical action)에 대해 소유감(sense of ownership)을 부여하는 것을 검토하는 데 있다. 고유수용성 감각은 외부 자극을 받아들이는 외수용기가 아닌 신체 내부의 신경조직인 내수용기에 의존하는 감각으로, 신체 부분(bodily parts)의 존재, 위치, 움직임을 아는데 있어 인식적으로 중요하다. 본고에서는 고유수용성 감각의 중요한 특징 중 하나인 일인칭성에 주목하여 슈메이커의 '오식별 오류에의 면역성Immunity to Error through Misidentification(이하 IEM)'이 고유수용성 감각에 적용할 수 있음을 논증하고자 한다. 필자는 다음 두 가지 주장을 비판적으로 검토하고 심리철학자 마르셀이 제기하는 병리적 반증사례를 차례대로 모두 격파함으로써 두 주장을 공고히 한다. 첫째, 고유수용성 감각은 내 신체와 신체적 행위에 관한 소유감을 제공한다는 점에서는 오류불가능하다. 둘째, 고유수용성 감각은 내 신체와 신체적 행위의 소유감을 위해 필수불가결하다.

• 대한인간공학회지
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• 제23권4호
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• pp.9-21
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• 2004

As menu structure of household appliance is complicated, user's cognitive workload frequently occurs errors. In existing studies, errors didn't present that interpretation for cognitive factors and alternatives, but are only considered as statistical frequency. Therefore, error classification and analysis in tasks is inevitable in usability evaluation. This study classified human error throughout information process model and navigation behavior. Human error is defined as incorrect decision and behavior reducing performance. And navigation is defined as unrelated behavior with target item searching. We searched and analyzed human errors and its causes as a case study, using mobile phone which could control appliances in near future. In this study, semantic problems in menu structure were elicited by SAT. Scenarios were constructed by those. Error analysis tests were performed twice to search and analyze errors. In 1st prototype test, we searched errors occurred in process of each scenario. Menu structure was revised to be based on results of error analysis. Henceforth, 2nd Prototype test was performed to compare with 1st. Error analysis method could detect not only mistakes, problems occurred by semantic structure, but also slips by physical structure. These results can be applied to analyze cognitive causes of human errors and to solve their problems in menu structure of electronic products.

• 한국정밀공학회지
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• 제19권10호
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• pp.99-106
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• 2002

This paper proposes an error compensation method that improves accuracy with geometry information of injection molding parts. Geometric information can give an improved accuracy in reverse engineering. Measuring data can not lead to get accurate geometric model, including errors of physical parts and measuring machines. Measuring data include errors which can be classified into two types. One is molding error in product, the other is measuring error. Measuring error includes optical error of laser scanner, deformation by probe forces of CMM and machine error. It is important to compensate these in reverse engineering. Least square method (LSM) provides the cloud data with a geometry compensation, improving accuracy of geometry. Also, the functional shape of a part and design concept can be reconstructed by error compensation using geometry information.

• 천문학회보
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• 제46권2호
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• pp.46.3-47
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• 2021

Recently a multilayer spectral inversion (MLSI) model has been proposed to infer the physical parameters of plasmas in the solar chromosphere. The inversion solves a three-layer radiative transfer model using the strong absorption line profiles, H alpha and Ca II 8542 Å, taken by the Fast Imaging Solar Spectrograph (FISS). The model successfully provides the physical plasma parameters, such as source functions, Doppler velocities, and Doppler widths in the layers of the photosphere to the chromosphere. However, it is quite expensive to apply the MLSI to a huge number of line profiles. For example, the calculating time is an hour to several hours depending on the size of the scan raster. We apply deep neural network (DNN) to the inversion code to reduce the cost of calculating the physical parameters. We train the models using pairs of absorption line profiles from FISS and their 13 physical parameters (source functions, Doppler velocities, Doppler widths in the chromosphere, and the pre-determined parameters for the photosphere) calculated from the spectral inversion code for 49 scan rasters (~2,000,000 dataset) including quiet and active regions. We use fully connected dense layers for training the model. In addition, we utilize a skip connection to avoid a problem of vanishing gradients. We evaluate the model by comparing the pairs of absorption line profiles and their inverted physical parameters from other quiet and active regions. Our result shows that the deep learning model successfully reproduces physical parameter maps of a scan raster observation per second within 15% of mean absolute percentage error and the mean squared error of 0.3 to 0.003 depending on the parameters. Taking this advantage of high performance of the deep learning model, we plan to provide the physical parameter maps from the FISS observations to understand the chromospheric plasma conditions in various solar features.

• 한국안전학회지
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• 제16권4호
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• pp.168-174
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• 2001

For human error analysis, the structure and situation of a task should be analyzed in advance. The paper introduces Structured Information Analysis (SIA) as a task analysis method for error analysis, and delineates the result of application on the emergency procedure of Korean Standard Nuclear Plants (KSNPs). From the task analysis about emergency procedure of KSNP, total 72 specific task goals were identified in the level of system function, and 86 generic tasks were classified from the viewpoint of physical sameness of the task description. Human errors are dependent on task types so that the result of task analysis would be used as a basis for the error analysis on the emergency tasks in nuclear power plants.

• 한국공작기계학회논문집
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• 제17권4호
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• pp.8-14
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• 2008

This paper aims at finding out dominant robot configurations with maximal position errors, which can be attributed to the parameter errors, by using Monte-Carlo simulation for error analysis of a 3-axis SCARA(Selective Compliance Assembly Robot Arm) type robot. In particular, the Monte-Carlo simulation is used for virtually measuring on the position errors, instead of physical measurement. In order to measure the observability of the model parameters with respect to a set of robot configurations, we propose the observability index which is defined as the product of singular values for error propagation matrices. Thus the index can be used for discriminating dominant robot configurations from a set of simulated ones in conjunction with standard deviation of positional errors, This paper analyzed error by robot positional error.