• Journal of the Korean Society of Safety
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• v.23 no.2
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• pp.30-36
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• 2008

This paper suggests the best work conditions, including short break time and number of mouse clicks on a computer, to prevent MSDs(Musculoskeletal Disorders) on VDT(Visual Display Terminal) work. Discomfort measures are calculated according to the Borg's CR-10 Scale. The short break time conditions are grouped into 7, 15, and 30 seconds after every 10-minute work period and the number of mouse clicks are divided into 10 clicks/min, 20clicks/min, and 30clicks/min. The result of the ANOVA on the shift value of subjective discomfort shows the following: 1) Regarding the break time and the number of mouse clicks, there are statistical differences between the measured values for the neck and the wrist(p<0.05). 2) Regarding the number of mouse clicks, there are statistical differences between the measured values for the shoulder and the forearm(p<0.1). 3) Regarding the break time and the number of mouse clicks, there are no statistical differences between the measures values for the eyes, upper arms and back(p<0.1).

• Journal of the Ergonomics Society of Korea
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• v.26 no.4
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• pp.41-47
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• 2007

This paper suggested the best work conditions including short break time and the number of mouse clicks on the computer work for the prevention of MSDs on VDT work. Fatigue measures included EMG based parameters. The short break time conditions are grouped into 7, 15, and 30 seconds after every work for 10 min and the number of mouse clicks are divided into 10, 20, and 30 clicks/min. The result of the ANOVA of the shift value of %MVC(Maximum Voluntary Contraction) showed the following: 1) There was a considerable difference as regards to the break time except the number of mouse clicks on the upper trapezius muscle(p$<$0.05). The best conditions were shown in 15 sec after every 10 min and 30 clicks/min. 2) There were considerable differences as regards to the number of mouse clicks except the break time on the extensor digitorum muscle and extensor carpi ulnaris muscle(p$<$0.05). The best conditions were shown in 7 sec after every 10min and 10 clicks/min.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.47-56
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• 2015

Automated detection of interesting web pages could be used in many different application domains. Determining a user's interesting web pages can be performed implicitly by observing the user's behavior. The task of distinguishing interesting web pages belongs to a classification problem, and we choose white box learning methods (fixed effect logit regression and support vector machine) to test empirically. The result indicated that (1) fixed effect logit regression, fixed effect SVMs with both polynomial and radial basis kernels showed higher performance than the linear kernel model, (2) a personalization is a critical issue for improving the performance of a model, (3) when asking a user explicit grading of web pages, the scale could be as simple as yes/no answer, (4) every second the duration in a web page increases, the ratio of the probability to be interesting increased 1.004 times, but the number of scrollbar clicks (p=0.56) and the number of mouse clicks (p=0.36) did not have statistically significant relations with the interest.

• KSBB Journal
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• v.27 no.1
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• pp.40-44
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• 2012

The laboratory animal group separation is dividing animal population into subgroups, which have similar average and standard deviation values among the subgroups, based on the biological characteristics such as body weight, glucose level in blood, etc. Although group separation is very important and initial step in experimental design, it needs a labor intensive process for researchers because of making similar average and standard deviation values among the subgroups using the raw biological characteristics. To reduce the labor cost and increase the efficiency of animal grouping, we developed a web program named as laboratory animal group separation (LAGS) program. This LAGS uses biological characteristics of population, number of group, and the number of elements per each subgroup as input data. The LAGS automatically separates the population into each subgroup that has similar statistical data such as average and standard deviation values among subgroups. It also provides researchers with the extraordinary data generated in the process of grouping and the final grouping results by graphical display. Through our LAGS, researchers can validate and confirm results of laboratory animal group separation by just a few mouse clicks.

• Journal of Biomedical Engineering Research
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• v.24 no.5
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• pp.411-419
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• 2003

This paper aims at developing 'gyro-mouse' which provides decent and comfortable human-computer interface that supports the usage of such software as an internet-browser in PC for the people paralyzed in upper limbs. This interface operates on information collected from head movement to get the cursor control. The interface is composed of two modules. One is hardware module in which the head horizontal and vertical angular velocities are detected and transmitted into PC. The other is a PC software that translates the received data into movement and click signals of the mouse. The ANN (artificial neural network) learns the quick nodding pattern of each user as click input so that it can provide user-friendly interface. The performance of the system was evaluated by three indices that are click recognition rate. error in cursor position control. and click rate of the moving target box. The performance result of the gyro-mouse was compared with that of the optical-mouse to assess the efficiency of the gyro-mouse. The average click recognition rate was 93%, average error in cursor position control was 1.4∼5 times of optical mouse. and the click rate with 50 pixels target box was 40%(30 clicks/min) to that of optical mouse. The click rate increased monotonously with the number of trial from 35% to 44%. The suggested system is expected to provide a new possibility to communicate with the society.

• Journal of Internet Computing and Services
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• v.6 no.5
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• pp.111-121
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• 2005

As the scale of e-commerce has been increasing, information about products and service become diversified, Most current internet shopping mall. however, provides product information to consumers in collective arrangement. thus they devote a lot of efforts and time to select the product they want, In this paper, as providing consumers convenient interfaces adapting feature inquirer and parallel coordinate, a method for selecting a right product through searching the wanted products easily and comparing their features efficiently has been proposed. To evaluate the efficiency of the method proposed in this paper, several experiments to measure the time spent and the number of clicks of mouse taken in finding the product they want have been conducted. The results verify the effectiveness of the proposed method.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.37-44
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• 2021

This study is about a strategy to analyze learning activities in an intelligent learning system. To this end, the conceptual definition of the intelligent learning system and the type of learning using the intelligent learning system were analyzed. The learning types were presented as individual, adaptive, competency-based, and blended learning, and although there are some differences, most of them have similar characteristics. In addition, learning activity analysis is based on data such as mouse clicks, keyboarding, and uploads generated by the system. Through this, basic analysis such as viewing time and number of uploads can be performed. However, more diverse learning analysis is needed for personalization and adaptation. It can judge not only learning attitude and achievement level, but also metacognitive level and creativity level. However, since the level of metacognition includes complex human cognitive activities, the teacher's intervention is required in the judgment of the intelligent learning system.