• Fashion & Textile Research Journal
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• v.21 no.5
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• pp.640-655
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• 2019

Technology status was investigated by analyzing patents and development cases of wearable robots. Development direction of wearable robot for wearability was also suggested by understanding the problems of wearability from development cases through the FGI technique. The number of patents per technical field was the most in the field of strength support, but AI in the technology field was different in each country; Korea was found to be poor in the category of daily living assistance. The number of patents by technology category was the most in the category of muscular strength assistance. However, the values of AI in the technology category were different in each country; Korea was found to be poor in the category of daily living assistance. Development cases were focused on rehabilitation, so development is not fulfilled uniformly by use purpose. By wearing body parts, robots with single function type were mainly developed. Rigid material robots were mainly developed. It was confirmed that wearable robot technology is not developed evenly in the category of application because it is in the early stage of the technical proposal and centered on main performance improvement. We derived twelve wearable conditions for wearable robots: Shape and Size Appropriateness, Movement Appropriateness, Composition Appropriateness, Physiological Appropriateness, Performance Satisfaction, Ease of Operation, Safety, Durability, Ease of Dressing, Ease of Cleaning, Portability and Ease of Storage and Appearance Satisfaction. Finally, the development direction of a wearable robot for each wearable condition was suggested.

• Journal of Adhesion and Interface
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• v.25 no.2
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• pp.43-49
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• 2024

In recent years, the flexible organic synaptic transistor (FOST) has garnered attention for its flexibility, biocompatibility, ease of processability, and reduced complexity, which arise from using organic semiconductors as channel layers. These transistors can emulate the plasticity of the human brain with a simpler structure and lower fabrication costs compared to conventional inorganic synaptic devices. This makes them suitable for applications in next-generation wearable devices and soft robotics technologies. In FOST, the organic substrate is sensitive to the device preparation temperature; high-temperature treatment processes can cause thermal deformation of the organic substrate. Therefore, low-temperature solution-based processing techniques are essential for fabricating high-performance devices. This review summarizes the current research status of low-temperature solution-based FOST devices and presents the problems and challenges that need to be addressed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.750-758
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• 2016

In general, a system can be stable when it is designed with a rigid material. However, the use of a rigid system can be limited, such as grasping a glass or using a small surgical instrument. To resolve this limitation, a variable stiffness mechanism was developed using a flexible material. Previous research verified the variable stiffness mechanism where flexible segments and rigid segments were connected alternately in series. However, research into the design parameters of the variable stiffness structure is needed to satisfy the desired stiffness. Therefore, a variable stiffness structure was tested by varying the design parameters to confirm the trend of the stiffness variation. When the radius of the structure becomes larger, the stiffness increases. The stiffness increased with decreasing length of the flexible segments. Under the same design parameters, the length of the flexible segments had a greater effect on the stiffness than the length of the rigid segments. In addition, the stiffness was estimated using the pseudo rigid body model and was compared with the experimental results. This parametric study can be used as a design guideline for designing the variable stiffness mechanism to satisfy the desired stiffness.

• Journal of Appropriate Technology
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• v.7 no.2
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• pp.196-205
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• 2021

As industrial safety increases, various industrial accident prevention technologies using smart factory technology are being studied. However, small and medium enterprises (SMEs), which account for the majority of industrial accidents, are having difficulties in preventing industrial accidents by applying these smart factory technologies due to practical problems. In this study, customized monitoring and warning systems for each type of industrial accident were developed and applied to the actual field. Through this, we demonstrated industrial accident prevention technology through appropriate smart factory technology used by SMEs. A customized monitoring system using vision, current, temperature, and gas sensors was established for the four major disaster types: worker body access, short circuit and overcurrent, fire and burns due to high temperature, and emission of hazardous gas. In addition, a notification method suitable for each work environment was applied so that the monitored risk factors could be recognized quickly, and real-time data transmission and display enabled workers and managers to understand the disaster risk effectively. Through the application and demonstration of these appropriate smart factory technologies, the spread of these industrial safety technologies is to be discussed.

• Korean Journal of Radiology
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• v.24 no.8
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• pp.807-820
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• 2023

Objective: To assess whether computed tomography (CT) conversion across different scan parameters and manufacturers using a routable generative adversarial network (RouteGAN) can improve the accuracy and variability in quantifying interstitial lung disease (ILD) using a deep learning-based automated software. Materials and Methods: This study included patients with ILD who underwent thin-section CT. Unmatched CT images obtained using scanners from four manufacturers (vendors A-D), standard- or low-radiation doses, and sharp or medium kernels were classified into groups 1-7 according to acquisition conditions. CT images in groups 2-7 were converted into the target CT style (Group 1: vendor A, standard dose, and sharp kernel) using a RouteGAN. ILD was quantified on original and converted CT images using a deep learning-based software (Aview, Coreline Soft). The accuracy of quantification was analyzed using the dice similarity coefficient (DSC) and pixel-wise overlap accuracy metrics against manual quantification by a radiologist. Five radiologists evaluated quantification accuracy using a 10-point visual scoring system. Results: Three hundred and fifty CT slices from 150 patients (mean age: 67.6 ± 10.7 years; 56 females) were included. The overlap accuracies for quantifying total abnormalities in groups 2-7 improved after CT conversion (original vs. converted: 0.63 vs. 0.68 for DSC, 0.66 vs. 0.70 for pixel-wise recall, and 0.68 vs. 0.73 for pixel-wise precision; P < 0.002 for all). The DSCs of fibrosis score, honeycombing, and reticulation significantly increased after CT conversion (0.32 vs. 0.64, 0.19 vs. 0.47, and 0.23 vs. 0.54, P < 0.002 for all), whereas those of ground-glass opacity, consolidation, and emphysema did not change significantly or decreased slightly. The radiologists' scores were significantly higher (P < 0.001) and less variable on converted CT. Conclusion: CT conversion using a RouteGAN can improve the accuracy and variability of CT images obtained using different scan parameters and manufacturers in deep learning-based quantification of ILD.

• Journal of Appropriate Technology
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• v.7 no.2
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• pp.127-135
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• 2021

To respond to the threat of global warming, countries around the world are promoting the spread of renewable energy and reduction of carbon emissions. In accordance with the United Nation's Sustainable Development Goal to combat climate change and its impacts, global automakers are pushing for a full transition to electric vehicles within the next 10 years. Electric vehicles can be a useful means for reducing carbon emissions, but in order to reduce carbon generated in the stage of producing electricity for charging, a power generation system using eco-friendly renewable energy is required. In this study, we propose a smart electric mobility operating system integrated with off-grid solar power plants established in Tanzania, Africa. By applying smart monitoring and communication functions based on Arduino-based computing devices, information such as remaining battery capacity, battery status, location, speed, altitude, and road conditions of an electric vehicle or electric motorcycle is monitored. In addition, we present a scenario that communicates with the surrounding independent solar power plant infrastructure to predict the drivable distance and optimize the charging schedule and route to the destination. The feasibility of the proposed system was verified through test runs of electric motorcycles. In considering local environmental characteristics in Tanzania for the operation of the electric mobility system, factors such as eco-friendliness, economic feasibility, ease of operation, and compatibility should be weighed. The smart electric mobility operating system proposed in this study can be an important basis for implementing the SDGs' climate change response.

• Journal of Appropriate Technology
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• v.7 no.2
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• pp.162-171
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• 2021

The Korean government proposed the K-SDGs in 2019 to promote the UN SDGs, but the role and tasks of science and technology, an important means of implementing the SDGs, have not been materialized. Accordingly, the role of science and technology ODA for the SDGs was established through the Ministry of Science and ICT's policy research project 'Science and Technology ODA Promotion Roadmap for Spreading the New Southern Policy and Realizing the 2030 SDGs'. In addition, goals, strategies, and core tasks for the next 10 years were derived in 10 fields such as water, climate change, energy, and ICT. In this paper, we analyze 30 key tasks of the ODA promotion roadmap for science and technology for the realization of SDGs, and propose mid- and short-term tasks and implementation plans for effective roadmap promotion. Among the key tasks in each field, four common elements were derived: ICT/smartization, a global problem-solving center, cooperation/communication platform, and business model/startup support platform/living lab that can create and integrate roadmap implementation conditions. In addition, the four mid- and short-term tasks, 1) Establishment of science and technology ODA network, 2) Establishment of living lab business platform linked to start-up support business, 3) Local smartization of recipient countries, and 4) Expand and secure sustainability of global problem-solving centers, were set in relation to the implementation of the detailed roadmap. For the derived mid- and short-term tasks, detailed implementation plans based on the ICTization of global problem-solving centers were presented. The implementation of the mid- and short-term tasks presented in this paper can contribute to the more effective achievement of the science and technology ODA roadmap, and it is expected that Korea's implementation of SDGs will also achieve high performance.