• Title/Summary/Keyword: External R&D

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Stand-alone Real-time Healthcare Monitoring Driven by Integration of Both Triboelectric and Electro-magnetic Effects (실시간 헬스케어 모니터링의 독립 구동을 위한 접촉대전 발전과 전자기 발전 원리의 융합)

  • Cho, Sumin;Joung, Yoonsu;Kim, Hyeonsu;Park, Minseok;Lee, Donghan;Kam, Dongik;Jang, Sunmin;Ra, Yoonsang;Cha, Kyoung Je;Kim, Hyung Woo;Seo, Kyoung Duck;Choi, Dongwhi
    • Korean Chemical Engineering Research
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    • v.60 no.1
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    • pp.86-92
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    • 2022
  • Recently, the bio-healthcare market is enlarging worldwide due to various reasons such as the COVID-19 pandemic. Among them, biometric measurement and analysis technology are expected to bring about future technological innovation and socio-economic ripple effect. Existing systems require a large-capacity battery to drive signal processing, wireless transmission part, and an operating system in the process. However, due to the limitation of the battery capacity, it causes a spatio-temporal limitation on the use of the device. This limitation can act as a cause for the disconnection of data required for the user's health care monitoring, so it is one of the major obstacles of the health care device. In this study, we report the concept of a standalone healthcare monitoring module, which is based on both triboelectric effects and electromagnetic effects, by converting biomechanical energy into suitable electric energy. The proposed system can be operated independently without an external power source. In particular, the wireless foot pressure measurement monitoring system, which is rationally designed triboelectric sensor (TES), can recognize the user's walking habits through foot pressure measurement. By applying the triboelectric effects to the contact-separation behavior that occurs during walking, an effective foot pressure sensor was made, the performance of the sensor was verified through an electrical output signal according to the pressure, and its dynamic behavior is measured through a signal processing circuit using a capacitor. In addition, the biomechanical energy dissipated during walking is harvested as electrical energy by using the electromagnetic induction effect to be used as a power source for wireless transmission and signal processing. Therefore, the proposed system has a great potential to reduce the inconvenience of charging caused by limited battery capacity and to overcome the problem of data disconnection.

Development of Electret to Improve Output and Stability of Triboelectric Nanogenerator (마찰대전 나노발전기의 출력 및 안정성 향상을 위한 일렉트렛 개발)

  • Kam, Dongik;Jang, Sunmin;Yun, Yeongcheol;Bae, Hongeun;Lee, Youngjin;Ra, Yoonsang;Cho, Sumin;Seo, Kyoung Duck;Cha, Kyoung Je;Choi, Dongwhi
    • Korean Chemical Engineering Research
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    • v.60 no.1
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    • pp.93-99
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    • 2022
  • With the rapid development of ultra-small and wearable device technology, continuous electricity supply without spatiotemporal limitations for driving electronic devices is required. Accordingly, Triboelectric nanogenerator (TENG), which utilizes static electricity generated by the contact and separation of two different materials, is being used as a means of effectively harvesting various types of energy dispersed without complex processes and designs due to its simple principle. However, to apply the TENG to real life, it is necessary to increase the electrical output. In addition, stable generation of electrical output, as well as increase in electrical output, is a task to be solved for the commercialization of TENG. In this study, we proposed a method to not only improve the output of TENG but also to stably represent the improved output. This was solved by using the contact layer, which is one of the components of TENG, as an electret for improved output and stability. The utilized electret was manufactured by sequentially performing corona charging-thermal annealing-corona charging on the Fluorinated ethylene propylene (FEP) film. Electric charges artificially injected due to corona charging enter a deep trap through the thermal annealing, so an electret that minimizes charge escape was fabricated and used in TENG. The output performance of the manufactured electret was verified by measuring the voltage output of the TENG in vertical contact separation mode, and the electret treated to the corona charging showed an output voltage 12 times higher than that of the pristine FEP film. The time and humidity stability of the electret was confirmed by measuring the output voltage of the TENG after exposing the electret to a general external environment and extreme humidity environment. In addition, it was shown that it can be applied to real-life by operating the LED by applying an electret to the clap-TENG with the motif of clap.

Derivation of Constraint Factors Affecting Passenger's In-Vehicle Activity of Urban Air Mobility's Personal Air Vehicle and Design Criteria According to the Level of Human Impact (도심항공모빌리티 비행체 PAV 탑승자 실내행위에 영향을 미치는 제약 요소 도출 및 인체 영향 수준에 따른 설계 기준)

  • Jin, Seok-Jun;Oh, Young-Hoon;Ju, Da Young
    • Science of Emotion and Sensibility
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    • v.25 no.1
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    • pp.3-20
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    • 2022
  • Recently, prior to the commercialization of urban air mobility (UAM), the importance of R&D for air transportation-related industries in urban areas has significantly increased. To create a UAM environment, research is being conducted on personal air vehicles (PAVs). They are key means of air transportation, but research on the physical factors influencing their passengers is relatively insufficient. In particular, because the PAV is expected to be used as a living space for the passengers, research on the effects of the physical elements generated in the PAV on the human body is essential to design an interior space that supports the in-vehicle activities of the passengers. Therefore, the purpose of this study is to derive the constraint factors that affect the human body due to the air navigation characteristics of the PAV and to understand the impact of these constraint factors on the bodies of the passengers performing in-vehicle activities. The results of this study indicate that when the PAV was operated at less than 4,000 ft, which is the operating standard, the constraint factors were noise, vibration, and motion sickness caused by low-frequency motion. These constraint factors affect in-vehicle activity; thus, the in-vehicle activities that can be performed in a PAV were derived using autonomous cars, airplanes, and PAV concept cases. Furthermore, considering the impact of the constraint factors and their levels on the human body, recommended constraint factor criteria to support in-vehicle activities were established. To reduce the level of impact of the constraint factors on the human body and to support in-vehicle activity, the seat's shape and built-in functions of the seat (vibration reduction function, temperature control, LED lighting, etc.) and external noise reduction using a directional speaker for each individual seat were recommended. Moreover, it was suggested that interior materials for noise and vibration reduction should be used in the design of the interior space. The contributions of this study are the determination of the constraint factors affecting the in-vehicle PAV activity and the confirmation of the level of impact of the factors on the human body; in the future, these findings can be used as basic data for suitable PAV interior design.

An Analytical Study on Rational use of Undersea Space (해저공간의 합리적 활용을 위한 분석적 연구)

  • Won-Jo Jung;Nam-Ki Park
    • Journal of Navigation and Port Research
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    • v.47 no.3
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    • pp.147-154
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    • 2023
  • This study aims to determine the necessity, role, utilization, and operation and management plan in relation to the underwater space platform where humans can newly reside. It provides a comprehensive opinion on the need for creating undersea space and operation plans based on opinions of industry-university-affiliated organizations involved in the R&D project of the Ministry of Maritime Affairs and Fisheries for the utilization of undersea space and external experts participating in marine technology development. In this study, a survey was conducted on researchers participating in the construction of a Korean submarine space platform. FGI was conducted on marine technology development experts. Results were then derived. As a result of the analysis, the need for subsea space construction was found to be high. As for the role of subsea space, the most common opinion was to develop technology for utilizing subsea space and to secure marine science research functions. It was found that the creation of subsea space would have a positive impact on the domestic industry, especially the deep-sea development industry and the shipbuilding/offshore structure industry. In terms of utilization, after the end of the seabed space test bed, the response to utilization as a marine observation base and marine ecosystem research had the highest proportion. As for expected inconvenience, discomfort in the psychological environment was the highest. Experts suggest that securing a continuous budget is most important for stable operation in the future and that securing a manpower budget is essential for itemized budgets. In addition, it was judged that it would be appropriate to establish a prior agreement from the time of the prior agreement and prepare a countermeasure before proceeding with the project in order to ensure ownership issues, consignment management issues, and cost issues when using the project after the end of the project.

The Characteristics and Performances of Manufacturing SMEs that Utilize Public Information Support Infrastructure (공공 정보지원 인프라 활용한 제조 중소기업의 특징과 성과에 관한 연구)

  • Kim, Keun-Hwan;Kwon, Taehoon;Jun, Seung-pyo
    • Journal of Intelligence and Information Systems
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    • v.25 no.4
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    • pp.1-33
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    • 2019
  • The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

Deriving adoption strategies of deep learning open source framework through case studies (딥러닝 오픈소스 프레임워크의 사례연구를 통한 도입 전략 도출)

  • Choi, Eunjoo;Lee, Junyeong;Han, Ingoo
    • Journal of Intelligence and Information Systems
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    • v.26 no.4
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    • pp.27-65
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    • 2020
  • Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.