• PNF and Movement
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• v.18 no.1
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• pp.23-34
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• 2020

Purpose: To explore the effects of action observation combined with modified constraint-induced movement therapy on upper-extremity function and the activities of daily living in subacute stroke patients. Methods: Twenty-four subacute stroke patients were randomly assigned to the experimental group or the control group (n = 12 each). Both groups received therapy based on motor learning concepts, including repetitive and task-specific practice. The experimental group watched video clips for 10 minutes related to tasks performed during modified constraint-induced movement therapy while the control group watched videos unrelated to upper-extremity movement. These programs were performed for 40 minutes a day five times a week for four weeks. Their scores on the Fugl-Meyer assessment of upper extremities (FMA-UE), the action research arm test (ARAT), a motor activity log (amount of use [AOU] and quality of movement [QOM]), and the modified Barthel index (MBI) were recorded. Results: In both groups, all variables were significantly different between the pre-test and post-test periods (p < 0.05). The post-test variables were significantly different within each group (p < 0.05). In the experimental group, the changes between pre-test and post-test scores in the FMA-UE (14.39 ± 4.31 versus 6.31 ± 4.63), the ARAT (16.00 ± 4.73 versus 11.46 ± 3.73), MAL-AOU (1.57 ± 0.15 versus 1.18 ± 0.28), and MBI (27.54 ± 4.65 versus 18.08 ± 8.52) were significantly higher than those of the control group (p < 0.05). Conclusion: These findings suggest that action observation combined with modified constraint-induced movement therapy may be a beneficial rehabilitation option to improve upper-extremity function in subacute stroke patients with moderate impairment.

• The Korean Journal of Archival Studies
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• no.68
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• pp.41-72
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• 2021

In order to analyze big data, documents should be converted to a open standard format to increase machine readability. It also need natural language processing tools. This study focused on the background of intelligent document processing and the status of research in the public sector, and predicted the changes in work that intelligent document processing would bring. This study noted the changes that intelligent document processing would bring to the archival work, and also considered changes in the role of archivist and their required competencies. Changes in archival work could be anticipated across a wide range of Records Management work and Archives Management work. In particular, it was expected to have a significant impact on the automation of repetitive archival tasks or the description and utilization of records. This study proposed the need to prepare new archival work procedures, methods, and necessary competencies in response to these change in archival work.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.199-212
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• 2019

Digitalization is creating a variety of changes and innovations in our business environment. In manufacturing, robots have long been used for automation to innovate processing speed and quality. The RPA brings these innovations in manufacturing sites to the office space. The purpose of this study is to improve productivity for simple, repetitive tasks in these office space. For identify the potential of automation related to productivity improvement, I looked at the concept of business automation, and then simulated the five areas of business documentation works with agile methodology. In conclusion, I confirmed that productivity improvement of 97.3% in quality inspection and 31.7% in editorial design is possible, and examined the direction to apply to actual work. Based on these results, future study will explore the application of Intelligent Process Automation (IPA).

• Plant Journal
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• v.17 no.3
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• pp.37-41
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• 2021

P&ID((Piping and Instrument Diagram) is a key drawing in the engineering industry because it contains information about the units and instrumentation of the plant. Until now, simple repetitive tasks like listing symbols in P&ID drawings have been done manually, consuming lots of time and manpower. Currently, a deep learning model based on CNN(Convolutional Neural Network) is studied for drawing object detection, but the detection time is about 30 minutes and the accuracy is about 90%, indicating performance that is not sufficient to be implemented in the real word. In this study, the detection of symbols in a drawing is performed using 1-stage object detection algorithms that process both region proposal and detection. Specifically, build the training data using the image labeling tool, and show the results of recognizing the symbol in the drawing which are trained in the deep learning model.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.465-470
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• 2021

This study was attempted to predict the direction for ward nursing work through robotic systemization. Robot systems have not been universalized due to difficulties in operation, space constraints, and high prices. The robotic systemization should be focused on the robotic systemization of simple and repetitive tasks. The idea of a robot system for measuring vital signs and a robot system that helps bed sheet exchange is worth discussing with the engineering field. In addition, for successful nursing and interdisciplinary convergence, a detailed analysis of nursing work is required, and in order to overcome the trial and error of convergence, it is necessary to establish a converging society between nursing and interdisciplinary systems. Robotic systemization of successful ward nursing work will not only generate profits for hospitals, but also raise the status of nurses and will be the starting point for innovation in nursing work.

• Journal of KIBIM
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• v.12 no.1
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• pp.42-54
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• 2022

BIM facilitates data transparency and consistency through three-dimensional parametric modeling and promotes the accurate managing and sharing of project information. In Korea, however, BIM-based detailed design of architectural interior finishes required during the Construction Documents phase increases the burden on architectural firms due to frequent design changes and manual workload. Therefore, the purpose of this study was to establish rule-based modules using parametric modeling that automates repetitive tasks that occur during the detailed design of interior finishing. Interviews with practitioners were conducted to analyze the major finishing elements. Of these floors, walls, and ceilings, which were the most rudimentary and common items, were selected as the subjects of the study. The modules developed in this study have two functions. One is to create new finish types, and the other is the automatic modeling of new types into rooms. For these functions, parameters that belonged to each finish and room element in a BIM model were analyzed and valid parameters directly used for parametric modeling were derived. Then, based on these parameters, rule-based modules for three elements, I.e., floors, walls, and ceilings were constructed with Revit Dynamo, and the effectiveness of the modules was verified with a pilot test. In conclusion, this study suggested a series of processes for automatic finishing to improve the efficiency of BIM-based architectural detailed design of finishes and to contribute in solving the chronic problems occuring during current design processes.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.521-528
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• 2021

Existing image analysis systems in use in the military field are carried out by readers analyzing and identifying images themselves, writing and disseminating related content, and in this process, repetitive tasks are frequent, resulting in workload. In this paper, to solve the previous problem, we proposed an algorithm that can operate the Seq2Seq model on a word basis, which operates on a sentence basis, and applied the Attention technique to improve accuracy. In addition, by applying the Beam Search technique, we would like to recommend various current identification sentences based on the past identification contents of a specific area. It was confirmed through experiments that the Beam Search technique recommends sentences more effectively than the existing greedy Search technique, and confirmed that the accuracy of recommendation increases when the size of Beam is large.

• Physical Therapy Korea
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• v.28 no.2
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• pp.93-100
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• 2021

Background: Lateral epicondylitis (LE) is the most common chronic musculoskeletal conditions of the upper extremity with pain and wrist extension disability. The tendon which is most affected is the extensor carpi radialis brevis (ECRB). Previous study evaluated the effect of taping technique on patient with LE, but no study investigated the changes of electromyography (EMG) on ECRB when using dynamic taping (DT) technique. Objects: The aim of this study was to investigate the effect of DT technique using dynamic tape on muscle activity of ECRB during wrist isometric extension, isotonic extension and flexion. Methods: Twenty-one healthy subjects volunteered to participate in this study. Subjects were instructed to perform wrist isometric extension, isotonic extension and flexion without and with DT on origin area of ECRB. Wrist isometric extension was performed at 75%, 50% and 25% (%maximal voluntary contraction force), respectively, based on maximum contraction force. Isotonic extension and flexion test used dumbbell. EMG data was collected from ECRB. Results: EMG of ECRB were statistically significant decrease in wrist isotonic extension after DT (p < 0.05). Significant increase in wrist isometric extension during 25% and 50% force task (p < 0.05). Conclusion: This study applied DT technique to suppress the wrist extensor muscles in 21 healthy adults in their twenties. Change in muscle activity was compared in the ECRB muscle during wrist isometric extension, isotonic extension and flexion task. Based on the results of this study, the DT technique applied to the wrist and forearm area can reduce the load on the wrist extensors when the wrist performs various movements during daily life movements or repetitive tasks, and by using these effects, excessive stress is applied to tennis elbow patients.

• Advances in nano research
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• v.12 no.2
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• pp.185-195
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• 2022

Deep learning is another field of artificial intelligence (AI) utilized for computer aided diagnosis (CAD) and image processing in scientific research. Considering numerous mechanical repetitive tasks, reading image slices need time and improper with geographical limits, so the counting of image information is hard due to its strong subjectivity that raise the error ratio in misdiagnosis. Regarding the highest mortality rate of Lung cancer, there is a need for biopsy for determining its class for additional treatment. Deep learning has recently given strong tools in diagnose of lung cancer and making therapeutic regimen. However, identifying the pathological lung cancer's class by CT images in beginning phase because of the absence of powerful AI models and public training data set is difficult. Convolutional Neural Network (CNN) was proposed with its essential function in recognizing the pathological CT images. 472 patients subjected to staging FDG-PET/CT were selected in 2 months prior to surgery or biopsy. CNN was developed and showed the accuracy of 87%, 69%, and 69% in training, validation, and test sets, respectively, for T1-T2 and T3-T4 lung cancer classification. Subsequently, CNN (or deep learning) could improve the CT images' data set, indicating that the application of classifiers is adequate to accomplish better exactness in distinguishing pathological CT images that performs better than few deep learning models, such as ResNet-34, Alex Net, and Dense Net with or without Soft max weights.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.513-523
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• 2023

Today more and more workers choosing dual(side) jobs due to economic reasons and self-development. Although the importance of working environments and individual life qulity of workers, research on the health of dual job worker is insufficient. Therefore, this study examined three aspects of factors influencing the subjective health status of dual job workers. As a result, it was statistically verified that there is a significant difference in subjective health status according to the status of the main job, and that it is important to increase satisfaction with the main job. Also, it was found that it is important not to provide physically performing repetitive tasks for a long time, and not to provide emotionally discriminatory experiences.