• KIPS Transactions on Software and Data Engineering
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• v.5 no.4
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• pp.181-186
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• 2016

Recently, the surveillance system research has focused because Unmanned Aerial Vehicle(UAV) has the ability to monitor wide area. When the wide area are monitored, controlling UAVs repeatedly by pilots invokes the cost problem to operate UAVs. If monitoring path can be defined in advance, the cost problem can be solved by controlling UAVs autonomously based on the monitoring path. The traditional approach generates multiple motor primitives based on flied GPS locations. However, the monitoring points by UAVs are not considered by the generated motor primitives, the surveillance by UAVs is not performed properly. This paper proposes a motor primitive structure for surveillance UAVs to be flied autonomously. Motor primitives are generated automatically by setting surveillance points to denote surveillance targets accurately.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.147-152
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• 2023

Mostly in motor fault detection the instantaneous values 3 axis vibration and 3phase current in time domain are acquired and converted to frequency domain. Vibrations are more useful in diagnosing the mechanical faults and motor current has remained more useful in electrical fault diagnosis. With having some experience and knowledge on the behavior of acquired data the electrical and mechanical faults are diagnosed through signal processing techniques or combine machine learning and signal processing techniques. In this paper, a single-layer LSTM based condition monitoring system is proposed in which the instantaneous values of three phased motor current are firstly acquired in simulated motor in in health and supply imbalance conditions in each of three stator currents. The acquired three phase current in time domain is then used to train a LSTM network, which can identify the type of fault in electrical supply of motor and phase in which the fault has occurred. Experimental results shows that the proposed single layer LSTM algorithm can identify the electrical supply faults and phase of fault with an average accuracy of 88% based on the three phase stator current as raw data without any processing or feature extraction.

• Journal of Practical Engineering Education
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• v.10 no.1
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• pp.25-33
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• 2018

As the IT industry develops, The field of e-learning based on existing theoretical subjects has expanded to fields requiring actual education. Courses that require practical training in e-learning must be evaluated to have learning outcomes through on-line practice. In this research, a student at Cyber University mechatronics engineering studies 'PLC Control' and 'Servo Motor Control', which are subjects of the undergraduate major, through 'Prime College's CyberLAB' for learning by e-learning investigated whether there was a learning result. For this reason, CyberLAB was conducted. And for the students who took the course for two years, We confirmed through the 5 - point scale questionnaire and grades that the practical subjects had a significant effect on e - learning.

• Asia Marketing Journal
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• v.15 no.3
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• pp.159-172
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• 2013

In the present study, we apply the multiple cue probability learning (MCPL) paradigm to examine consumer learning from feedback in repeated trials. This paradigm is useful in investigating consumer learning, especially learning the relationships between the overall quality and attributes. With this paradigm, we can analyze what people learn from repeated trials by using the lens model, i.e., whether it is knowledge or consistency. In addition to introducing this paradigm, we aim to demonstrate that knowledge people gain from repeated trials with feedback is robust enough to weaken one of the most often examined contextual effects, the asymmetric dominance effect. The experiment consists of learning session and a choice task and stimuli are sport rafting boats with motor engines. During the learning session, the participants are shown an option with three attributes and are asked to evaluate its overall quality and type in a number between 0 and 100. Then an expert's evaluation, a number between 0 and 100, is provided as feedback. This trial is repeated fifteen times with different sets of attributes, which comprises one learning session. Depending on the conditions, the participants do one (low) or three (high) learning sessions or do not go through any learning session (no learning). After learning session, the participants then are provided with either a core or an extended choice set to make a choice to examine if learning from feedback would weaken the asymmetric dominance effect. The experiment uses a between-subjects experimental design (2 × 3; core set vs. extended set; no vs. low vs. high learning). The results show that the participants evaluate the overall qualities more accurately with learning. They learn the true trade-off rule between attributes (increase in knowledge) and become more consistent in their evaluations. Regarding the choice task, there is a significant decrease in the percentage of choosing the target option in the extended sets with learning, which clearly demonstrates that learning decreases the magnitude of the asymmetric dominance effect. However, these results are significant only when no learning condition is compared either to low or high learning condition. There is no significant result between low and high learning conditions, which may be due to fatigue or reflect the characteristics of learning curve. The present study introduces the MCPL paradigm in examining consumer learning and demonstrates that learning from feedback increases both knowledge and consistency and weakens the asymmetric dominance effect. The latter result may suggest that the previous demonstrations of the asymmetric dominance effect are somewhat exaggerated. In a single choice setting, people do not have enough information or experience about the stimuli, which may lead them to depend mostly on the contextual structure among options. In the future, more realistic stimuli and real experts' judgments can be used to increase the external validity of study results. In addition, consumers often learn through repeated choices in real consumer settings. Therefore, what consumers learn from feedback in repeated choices would be an interesting topic to investigate.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.293-297
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• 2018

The purpose of this study was to determine the influence of video modeling observational learning intervention on the learning and performance of a bowling skill in adolescents with intellectual disabilities. Thirty special middle school students whose ages ranged from 14 to 16 years were recruited from Daegu, Korea. Intellectual disabilities of the participants were assessed by Korean version of the Wechsler intelligence scale for adolescent and a social maturity scale. During the experiment, participants repeatedly watched the one-minute action observation film for three minutes before beginning each frame and played 60 frames. Statistical comparisons were performed using a 2 (groups) ${\times}$ 6 (trials) ANOVA, with repeated measures on the last factor of the acquisition stage (p<0.05). Factors of the retention stage scores were analyzed by one-way ANOVA. The sources of any significant main effects were tested using a Tukey's HSD (honest significant difference) approach. SPSS 21.0 was used for statistical analyses. The performance scores of the action observation group were significantly higher than those of the control group. The findings showed that observational learning in the form video modeling has the potential to enhance acquisition and learning of a bowling sport skill in intellectual disability individuals; however, these findings are limited to adolescents with moderate intellectual disabilities.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2290-2295
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• 2005

In this paper, it is developed simulator system of 3 D.O.F parallel robot for educate of expertness. This simulator system is composed of three parts ? 3 D.O.F parallel robot, controller (hardware) and software. First, basic structure of the robot is 3 active rotary actuator that small geared step motor with fixed base. An input-link is connected to this actuator, and this input-link can connect two ball joints. Thus, two couplers can be connected to the input-link as a pair. An end-plate, which is jointed by a ball joint, can be connected to the opposite side of the coupler. A sub-link is produced and installed to the internal spring, and then this sub-link is connected to the upper and bottom side of the coupler in order to prevent a certain bending or deformation of the two couplers. The robot has the maximum diameter of 230 mm, 10 kg of weight (include the table), and maximum height of 300 mm. Hardware for control of the robot is composed of computer, micro controller, pulse generator, and motor driver. The PC used in the controller sends commands to the controller, and transform signals input by the user to the coordinate value of the robot by substituting it into equations of kinematics and inverse kinematics. A controller transfer the coordinate value calculated in the PC to a pulse generator by transforming it into signals. A pulse generator analyzes commands, which include the information received from the micro controller. A motor driver transfer the pulse received from the pulse generator to a step motor, and protects against the over-load of the motor Finally, software is a learning purposed control program, which presents the principle of a robot operation and actual implementation. The benefit of this program is that easy for a novice to use. Developed robot simulator system can be practically applied to understand the principle of parallel mechanism, motors, sensor, and various other parts.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.10
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• pp.516-523
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• 2000

In this paper, intelligent methods using digital protective relay in power supervisory control system is developed in order to protect power systems by means of timely fault detection and diagnosis during operation for induction motor which has various load environments and capacities in power systems. The spectrum pattern of input currents was used to monitor to state of induction motors, and by clustering the spectrum pattern of input currents, the newly occurrence of spectrums pattern caused by faults were detected. For diagnosis of the fault detected, the fuzzy fault tree was derived, and the fuzzy relation equation representing the relation between an induction motor fault and each fault type, was solved. The solution of the fuzzy relation equation shows the possibility of each fault's occurring. The results obtained are summarized as follows: 1) The test result on the basis of KEMC1120 and IEC60255, show that the operation time error of the digital motor protective relay is improved within ${\pm}5%$. 2) Using clustering algorithm by unsupervisory learning, an on-line fault detection method, not affected by the characteristics of loads and rates, was implemented, and the degree of dependency by experts during fault detection was reduced. 3) With the fuzzy fault tree, fault diagnosis process became systematic and expandable to the whole system, and the diagnosis for sub-systems can be made as an object-oriented module.

• Physical Therapy Korea
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• v.9 no.3
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• pp.67-76
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• 2002

We report the reorganization of motor network resulted from intensive unilateral coordination training and the effect of cross education on the untrained side in patient with traumatic brain injury using functional magnetic resonance imaging (fMRI). A 22 year-old male patient who had suffered from diffuse axonal injury for 58 months showed coordination deficit in the left hand at initial examination. Intensive motor training including complex finger movements and coordination activities using a metronome was introduced to the patient 4 hours per day for a week. FMRI was performed on a 3T ISOL Forte scanner. All functional images were analyzed using SPM-99 software. Hand function was improved after training not only in the trained left hand, but also in the untrained right hand. There was no activation in the right primary motor area (M1) during left hand movement before training whereas robust activation of left M1 was demonstrated by the right hand movement. Profuse activation of bilateral prefrontal lobes was seen during both hand movements before training. After training of left hand, right M1 became prominently activated during the left hand motion. The activation of bilateral prefrontal lobes disappeared after training not only for the left hand movement but also for the right, which clearly demonstrated the effect of cross education. This case report demonstrated the learning-dependent reorganization of the M1 and the effect of cross education.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.3
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• pp.273-281
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• 2001

In this paper, we propose a CMAC(Cerebellar Model Articulation Controller) neural network for controlling a non-linear system. CMAC is a neural network that models the human cerebellum. CMAC uses a table look-up method to resolve the complex non-linear system instead of numerical calculation method. It is very fast learn compared with other neural networks. It does not need a calculation time to generate control signals. The simulation results show that the proposed CMAC controllers for a simple non-linear function and a DC Motor speed control reduce tracking errors and improve the stability of its learning controllers. The validity of the proposed CMAC controller is also proved by the real-time tension control.

• The Journal of Korean Physical Therapy
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• v.24 no.6
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• pp.398-404
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• 2012

Purpose: This is designed to study the effect of weight-support walking training through motor learning on motor functions of children with cerebral palsy, in particular their activity of daily living and balance. Methods: Thirteen children with spastic cerebral palsy, at gross motor function classification system (GMFCS) levels III~IV, underwent treadmill walking training. It used principles of weight support, 4 times a week for 7 weeks, 10 minutes at a time, before and after neurodevelopmental physical therapy. Everyday functions were measured using Functional Independence Measure for Children (Wee-FIM). The ability to keep their balance was measured using electronic measuring equipment from good balance system and the assessment was made before and after the experiment. Results: There were significant differences (p<0.05) between pre and post experiment levels of functional independence in everyday life, in self-care activities, mobility, locomotion and social cognition. With regard to changes in standing balance, there were significant differences before and after the experiment (p<0.05) in GMFCS level III. There was a reduction in the agitation velocity in the x- and y-axes which measures the left-to-right shaking; in GMFCS level IV, velocity moment was reduced. Conclusion: Walking training using a treadmill can help improve the everyday activity and balance in children with spastic cerebral palsy. It can also be served as a useful purpose as a method of intervention in pediatric care.