• Proceedings of the ESK Conference
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• 1997.04a
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• pp.56-60
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• 1997

The study of human erroneous actions has traditionally taken place along two different lines of approach. One has been concerned with finding and explaining the causes of erroneous actions, such as studies in the psychology of "error". The other has been concerned with the qualitative and quantitative prediction of possible erroneous actions, exemplified by the field of human reliability analysis (HRA). Another distinction is also that the former approach has been dominated by an academic point of view, hence emphasising theories, models, and experiments, while the latter has been of a more pragmatic nature, hence putting greater emphasis on data and methods. We have been developing a method to make predictions about error modes. The input to the method is a detailed task description of a set of scenarios for an experiment. This description is then analysed to characterise thd nature of the individual task steps, as well as the conditions under which they must be carried out. The task steps are expressed in terms of a predefined set of cognitive activity types. Following that each task step is examined in terms of a systematic classification of possible error modes and the likely error modes are identified. This effectively constitutes a qualitative analysis of the possibilities for erroneous action in a given task. In order to evaluate the accuracy of the predictions, the data from a large scale experiment were analysed. The experiment used the full-scale nuclear power plant simulator in the Halden Man-Machine Systems Laboratory (HAMMLAB) and used six crews of systematic performance observations by experts using a pre-defined task description, as well as audio and video recordings. The purpose of the analysis was to determine how well the predictions matiched the actually observed performance failures. The results indicated a very acceptable rate of accuracy. The emphasis in this experiment has been to develop a practical method for qualitative performance prediction, i.e., a method that did not require too many resources or specialised human factors knowledge. If such methods are to become practical tools, it is important that they are valid, reliable, and robust.

• Science of Emotion and Sensibility
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• v.21 no.2
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• pp.145-158
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• 2018

The purpose of this study was to investigate the visuo-spatial attention ability and the emotional perception ability of people across the normal range of the scores on the bipolar disorder scale. The Korean version of the Mood Disorder Questionnaire (K-MDQ) was used to measure the bipolar disorder tendency of normal people. A useful field of view (UFOV) task and an emotional perception task were used to measure visuo-spatial attention and emotional perception ability, respectively. The participants did not have any mental illness history or other medical problems. The participants were divided into three groups according to K-MDQ score (low, normal, and high), and their performances were compared. In the UFOV task, the high K-MDQ score group had lower level of performance than the other groups, suggesting that a high bipolar tendency is associated with reduction of visuo-spatial attention ability. In the emotional perception task, the group with the high K-MDQ score showed higher perception of negative emotion bias than the other groups, suggesting a high bipolar tendency to associate with reduction of emotional perception ability. These results suggest that visuo-spatial and emotional attention abilities are related with bipolar disorder tendency even in the normal population.

• The KIPS Transactions:PartA
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• v.18A no.6
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• pp.255-264
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• 2011

A sensor network is a special network that makes physical data sensed by sensor nodes and manages the data. The sensor network is a technology that can apply to many parts of field. It is very important to transmit the data to a user at real-time. The core of the sensor network is a sensor node and small operating system that works in the node. TinyOS developed by UC Berkeley is a sensor network operating system that used many parts of field. It is event-driven and component-based operating system. Basically, it uses non-preemptive scheduler. If an urgent task needs to be executed right away while another task is running, the urgent one must wait until another one is finished. Because of that property, it is hard to guarantee real-time requirement in TinyOS. According to recent study, Priority Level Scheduler, which can let one task preempt another task, was proposed in order to have fast response in TinyOS. It has restrictively 5 priorities, so a higher priority task can preempt a lower priority task. Therefore, this paper suggests Preemptive EDF(Earliest Deadline First) Scheduler that guarantees a real-time requirement and reduces average respond time of user tasks in TinyOS.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.12
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• pp.363-370
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• 2023

Object detection technology that accurately recognizes the road and surrounding conditions is a key technology in the field of autonomous driving. In the field of autonomous driving, object detection technology requires real-time performance as well as accuracy of inference services. Task offloading technology should be utilized to apply object detection technology for accuracy and real-time on resource-constrained devices rather than high-performance machines. In this paper, experiments such as performance comparison of task offloading, performance comparison according to input image resolution, and performance comparison according to camera object resolution were conducted and the results were analyzed in relation to the application of task offloading for real-time object detection of autonomous driving in resource-constrained devices. In this experiment, the low-resolution image could derive performance improvement through the application of the task offloading structure, which met the real-time requirements of autonomous driving. The high-resolution image did not meet the real-time requirements for autonomous driving due to the increase in communication time, although there was an improvement in performance. Through these experiments, it was confirmed that object recognition in autonomous driving affects various conditions such as input images and communication environments along with the object recognition model used.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1057-1062
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• 1991

Recently, due to the development of new technology and products, FA has been accelerating for obtaining high-quality and saving of resources and power. Introduction of automation to the field which has bad working condition is needed and welding is one of these field. In this study, solving algorithm for down hand control which requires in the automatic are welding system is proposed. For the verification of the algorithm, numerical examples are shown and visualization is carried out using developed graphic tools.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.115-132
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• 2017

Differences in reaction time and accuracy were compared among driver groups of middle-, old-, and stroke old-age drivers using various reaction time tasks including simple reaction task, 2-choice task, 4-choice task with different stimuli eccentricity, search task, and moving target detection task. The results can be summarized as followings. First, although overall reaction time tended to be slowed with age and stroke, stroke old drivers showed significantly slower reaction time than the other driver groups when the stimuli were presented in a large eccentricity. Second, differences in reaction time for 2-choice task and moving target detection task seemed to be determined mainly by participants' simple reaction time. Third, the search task which required temporary retention of previously presented stimuli was found to be more sensitive in discriminating difference in reaction time between middle-age drivers and old-age drivers (including stroke old drivers). Fourth, reaction accuracy of old (and stroke old) drivers decreased when more stimuli alternatives were presented and temporary retention for stimuli was required. Altogether, memory demand in reaction time task can be sensitive to evaluate performance for different age groups, whereas size of useful field of view for brain stroke.

• International Journal of Advanced Culture Technology
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• v.4 no.2
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• pp.1-6
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• 2016

Impervious surfaces are important indicators for urban development monitoring. Accurate mapping of urban impervious surfaces with observational satellites, such as VNREDSat-1, remains challenging due to the spectral diversity not captured by an individual PAN image. In this article, five multi-resolution image fusion techniques were compared for the task of classifting urban impervious surfaces. The result shows that for VNREDSat-1 dataset, UNB and Wavelet tranformation methods are the best techniques in reserving spatial and spectral information of original MS image, respectively. However, the UNB technique gives the best results when it comes to impervious surface classification, especially in the case of shadow areas included in non-impervious surface group.

• Progress in Superconductivity and Cryogenics
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• v.21 no.4
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• pp.6-8
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• 2019

Iron-based superconductors (IBSs) possess nematic phases in which rotational symmetry of the electronic structure is spontaneously broken. This novel phase has attracted much attention as it is believed to be closely linked to the superconductivity. However, observation of the symmetry broken phase by using a macroscopic experimental tool is a hard task because of naturally formed twin domains. Here, we report on a novel detwinning method by using a magnetic field on FeTe single crystal. Detwinning effect was measured by resistivity anisotropy using the Montgomery method. Our results show that FeTe was detwinned at 2T, which is a relatively weak field compared to the previously reported result. Furthermore, detwinning effect is retained even when the field is turned off after field cooling, making it an external stimulation-free detwinning method.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1459-1466
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• 2018

Robots which detect human and recognize action are important factors for human interaction, and many researches have been conducted. Recently, deep learning technology has developed and learning based robot's technology is a major research area. These studies require a database to learn and evaluate for intelligent human perception. In this paper, we propose a multi-modal sensor-based image database condition considering the security task by analyzing the image database to detect the person in the outdoor environment and to recognize the behavior during the running of the robot.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.41-76
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• 2020

This study confirmed factors affecting smart factory technology acceptance through empirical analysis. It is a study on what factors have an important influence on the introduction of the smart factory, which is the core field of the 4th industry. I believe that there is academic and practical significance in the context of insufficient research on technology acceptance in the field of smart factories. This research was conducted based on the Unified Theory of Acceptance and Use of Technology (UTAUT), whose explanatory power has been proven in the study of the acceptance factors of information technology. In addition to the four independent variables of the UTAUT : Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, Government Assistance Expectancy, which is expected to be an important factor due to the characteristics of the smart factory, was added to the independent variable. And, in order to confirm the technical factors of smart factory technology acceptance, the Task Technology Fit(TTF) was added to empirically analyze the effect on Behavioral Intention. Trust is added as a parameter because the degree of trust in new technologies is expected to have a very important effect on the acceptance of technologies. Finally, empirical verification was conducted by adding Innovation Resistance to a research variable that plays a role as a moderator, based on previous studies that innovation by new information technology can inevitably cause refusal to users. For empirical analysis, an online questionnaire of random sampling method was conducted for incumbents of domestic small and medium-sized enterprises, and 309 copies of effective responses were used for empirical analysis. Amos 23.0 and Process macro 3.4 were used for statistical analysis. For accurate statistical analysis, the validity of Research Model and Measurement Variable were secured through confirmatory factor analysis. Accurate empirical analysis was conducted through appropriate statistical procedures and correct interpretation for causality verification, mediating effect verification, and moderating effect verification. Performance Expectancy, Social Influence, Government Assistance Expectancy, and Task Technology Fit had a positive (+) effect on smart factory technology acceptance. The magnitude of influence was found in the order of Government Assistance Expectancy(β=.487) > Task Technology Fit(β=.218) > Performance Expectancy(β=.205) > Social Influence(β=.204). Both the Task Characteristics and the Technology Characteristics were confirmed to have a positive (+) effect on Task Technology Fit. It was found that Task Characteristics(β=.559) had a greater effect on Task Technology Fit than Technology Characteristics(β=.328). In the mediating effect verification on Trust, a statistically significant mediating role of Trust was not identified between each of the six independent variables and the intention to introduce a smart factory. Through the verification of the moderating effect of Innovation Resistance, it was found that Innovation Resistance plays a positive (+) moderating role between Government Assistance Expectancy, and technology acceptance intention. In other words, the greater the Innovation Resistance, the greater the influence of the Government Assistance Expectancy on the intention to adopt the smart factory than the case where there is less Innovation Resistance. Based on this, academic and practical implications were presented.