• PNF and Movement
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• v.17 no.3
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• pp.369-378
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• 2019

Purpose: This study investigated the effects of virtual reality-based task training (VRBTT) using a smart glove on upper extremity function and activity of daily living in stroke patients. Methods: Twenty-nine patients with chronic stroke disease were randomly allocated to two groups: the VRBTT group (n=14) and the control group (n=15). All patients received 30 minutes of standard occupational therapy, 5 times a week, for 8 weeks. The VRBTT group performed an additional 30 minutes of virtual reality-based rehabilitation training, 5 times a week, for 8 weeks. Results: Both groups showed significant improvements in upper extremity function, yielding an increase in FMA and K-WMFT (p<0.05). There was a more significant increase in the VRBTT group before and after interventions (p<0.05). There was no significant difference in MAS for the control group (p>0.05); however, there was a significant increase for the VRBTT group (p<0.05). In the activities of daily living, there was a significant difference in the values for K-MBI (p<0.05). In addition, both groups showed a significant increase for K-MBI and K-RNLI (p<0.05). Conclusion: This study showed that VRBTT using smart gloves can have a more positive effect on upper extremity function and activities of daily living in stroke patients than conventional intervention methods. A variety of virtual reality-based contents and glove-shaped wearable devices will help stroke patients in rehabilitation clinics recover and return to society.

• Journal of Mechanical Science and Technology
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• v.16 no.12
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• pp.1633-1642
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• 2002

Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. The maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system using electro-hydraulic manipulator because hydraulic manipulators have the advantage of electric insulation. Meanwhile it is relatively difficult to realize autonomous assembly tasks particularly in the case of manipulating flexible objects such as electric lines. In this report, a discrete event control system is introduced for automatic assembly task of electric lines into sleeves as one of the typical task of active electric power lines. In the implementation of a discrete event control system, LVQNN (linear vector quantization neural network) is applied to the insertion task of electric lines to sleeves. In order to apply these proposed control system to the unknown environment, virtual learning data for LVQNN is generated by fuzzy inference. By the experimental results of two types of electric lines and sleeves, these proposed discrete event control and neural network learning algorithm are confirmed very effective to the insertion tasks of electric lines to sleeves as a typical task of active electric power maintenance tasks.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.1061-1062
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• 2009

• ETRI Journal
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• v.32 no.5
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• pp.695-703
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• 2010

Training is one of the representative application fields of virtual reality technology where users can have virtual experience in a training task and working environment. Widely used in the medical and military fields, virtual-reality-based training systems are also useful in industrial fields, such as the aerospace industry, since they show superiority over real training environments in terms of accessibility, safety, and cost. The shipbuilding industry is known as a labor-intensive industry that demands a lot of skilled workers. In particular, painting jobs in the shipbuilding industry require a continuous supplement of human resources since many workers leave due to the poor working environment. In this paper, the authors present a virtual-reality-based training system for spray painting tasks in the shipbuilding industry. The design issues and implementation details of the training system are described, and also its advantages and shortcomings are discussed based on use cases in actual work fields.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5234-5251
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• 2018

It is well-known that virtualization technology can bring many benefits not only to users but also to service providers. From the view of system security and resource utility, higher resource sharing degree and higher system reliability can be obtained by the introduction of virtualization technology in distributed cloud. The small size time-sharing multiplexing technology which is based on virtual machine in distributed cloud platform can enhance the resource utilization effectively by server consolidation. In this paper, the concept of memory block and user satisfaction is redefined combined with user requirements. According to the unbalanced memory resource states and user preference requirements in multi-virtual machine environments, a model of proper memory resource allocation is proposed combined with memory block and user satisfaction, and at the same time a memory optimization allocation algorithm is proposed which is based on virtual memory block, makespan and user satisfaction under the premise of an orderly physical nodes states also. In the algorithm, a memory optimal problem can be transformed into a resource workload balance problem. All the virtual machine tasks are simulated in Cloudsim platform. And the experimental results show that the problem of virtual machine memory resource allocation can be solved flexibly and efficiently.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.120-120
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• 2000

In this study, in order to control real system under the environment of graphic user interface, study on the technique which can control real system without additional hardware drivers using virtual machine driver operated on the windows operating system. Consider the problem which is the error and the delay of a sampling time on the multi task processing through the load test of the experiment using graphic user interface.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.103.4-103
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• 2001

This paper presents a scaled teleoperation scheme for 3-D microassembly on the experimental microassembly workcell. A workspace mapping between a master and a slave microrobot system is presented to teleoperatively control the microrobot system for microassembly such as peg-in-hole task. Based on this result, a scaling factor is designed and applied to the teleoperated micromanipulation for peg-in-hole task in a mesoscale. Using 3-D virtual simulator, the workspace of microrobot system, and the working path trajectory for microassembly is visually represented. The proposed method is validated through the execution of 3-D microassembly such as peg-in-hole task on the experimental microassembly workcell. The proposed method in the developed ...

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.128-130
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• 2021

Smart cities collect data from thousands of IoT-based sensor devices for intelligent application-based services. Centralized cloud servers support application tasks with higher computation resources but introduce network latency. Fog layer-based data centers bring data processing at the edge, but fewer available computation resources and poor task allocation strategy prevent real-time data analysis. In this paper, tasks generated from devices are distributed as high resource and low resource intensity tasks. The novelty of this research lies in deploying a virtual node assigned to each cluster of IoT sensor machines serving a joint application. The node allocates tasks based on the task intensity to either cloud-computing or fog computing resources. The proposed Task Allocation Strategy provides seamless allocation of jobs based on process requirements.

• Educational Technology International
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• v.20 no.2
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• pp.137-168
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• 2019

This study examined the effects of information volume and distribution on learners' cognitive load and recall in a mobile augmented reality (AR) environment. Information volume refers to the degree of information users are provided in a learning task, while information distribution indicates the way in which information is distributed, either in a virtual or real format. Sixteen undergraduate students participated in the study, which employed a 2 × 3 randomized block factorial design with repeated measures. Information volume and distribution were independent variables, and factors in learners' cognitive load (mental effort, perceived ease of use, and perceived task difficulty) and recall test scores were the dependent variables. Information volume had significant main effects on perceived ease of use and task difficulty, and recall test scores, while information distribution had significant main effects on perceived task difficulty and test scores. A detailed discussion and implications are provided.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.79-90
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• 2012

In digital virtual manufacturing simulation, Digital Human widely used to optimal workplace design, enhancing worker safety in the workplace, and improving product quality. However, the case of ergonomics simulation solutions to support digital human modeling, Optimal DHM (Digital Human Model) data needed to develop and perform DHM will collect information related to the production process. So simulation developer has burden of collecting information. In this study, to overcome the limitations of existing solutions, we proposed the ADAGIO(Automated Digital humAn model development for General assembly usIng Ontology) framework. The ADAGIO framework was developed for DHM ontology to support optimal deployment of digital virtual environment and in order to ensure consistency of simulation components that are required for simulation modeling was made of a library.