• 한국산학기술학회논문지
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• 제17권5호
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• pp.294-304
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• 2016

이 연구의 목적은 충남지역 경제 발전에서 중요한 역할을 수행하는 민간 중간지원조직의 현황을 조사 분석하고 이들의 역량을 강화시키는 정책적 방안을 도출하는 것이다. 이 연구에서는 중간지원조직을 민간단체와 정부 사이에서 다양한 주체들 간에 원활한 관계를 형성, 유지하도록 하는 모든 기관과 프로그램이라고 정의하였다. 지금까지 대부분의 연구들은 공공기관 중간지원조직의 기능과 역할에 대한 분석이 중심이었지만, 이 연구에서는 충남지역을 활동 범위로 하는 민간분야 경제관련 단체 9곳을 선정하여 중간지원조직으로서의 역할과 기능에 대해 설문지와 면담조사를 통해서 조사하였다. 그 결과 아직까지 과거 산업화시대 이익단체로서의 역할에 국한된 활동에 초점을 두고 있으며, 자신들이 중간지원조직으로서의 역할을 수행해야 한다는 인식이 매우 미흡한 것으로 나타났다. 또한 재정적으로 열악한 상황에 직면해 있기 때문에 중앙부처에서 예산을 지원하는 사업 이외에 자체사업을 추진할 수 있는 능력이 부족한 실정이다. 따라서 이들이 충남지역에서 지역산업체의 요구를 수용해서 새로운 협력적 활동을 주도하는 중간지원조직으로서의 활동을 수행하기 위해서는 우선적으로 각종 지역개발사업의 운영과정에 참여하도록 함으로써 다양한 지역산업의 문제를 다룰 수 있는 역량을 향상시키도록 하는 정책적 지원이 필요하다.

• 한국콘텐츠학회논문지
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• 제21권9호
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• pp.34-41
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• 2021

본 연구의 목적은 AI 스피커를 활용한 영어 말하기 수업과 활동이 초등영어학습자들의 정의적 특성과 학습 만족도에 미치는 영향을 살펴보기 위함이다. 총 46명의 초등영어학습자가 실험에 참여하였으며설문지를 사전-사후 배포하여 양적으로 분석하였다. 본 연구를 통해 밝혀낸 결과를 정리하면 다음과 같다. 첫째, AI 기반 영어 학습에 대한 전반적인 이해도 관련 수업 후 AI 기반 활동의 교육적 장점과 효능에 대한 인식이 넓어진 것을 알 수 있었다. 둘째, AI 기반 영어 말하기 활동에 대한 정의적 특성의 변화를 살펴본 결과 사전대비 사후의 평균값이 상승하고 대응표본 t-검정 결과 흥미도, 가치관, 태도 영역에 있어 유의미한 차이가 발견되었다. AI 활용 영어 학습에 대한 만족도를 살펴본 결과 실험 전에 비해 평균 만족도가 상승하고 특히 효능감, 학업 성취감 및 몰입도면에서 높은 상승을 보였다. 끝으로 AI 기반 영어 학습의 만족도과 정의적 특성 간의 상관관계를 분석한 결과 AI 기반 영어 학습에 대한 만족도는 학습자들의 자신감, 흥미도, 태도와 관련이 있는 것으로 나타났다.

• 대한한방내과학회지
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• 제39권6호
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• pp.1105-1115
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• 2018

Objectives: The aim of this review is to investigate clinical studies on Oriental medicine treatment for aphasia after cerebrovascular disease. Methods: Using the keywords 'Aphasia', 'Oriental medicine', 'Stroke' 'Cerebral infarction', 'Cerebral hemorrhage', and 'Clinic', we searched domestic databases, including "NDSL (National Discovery for Science Leaders)", "Korean Traditional Knowledge Portal", "OASIS (Oriental Medicine Advanced Searching Integrated System)", and "RISS (Research Information Sharing Service)". Each keyword was not searched individually, but combined in various ways. To investigate recent trends, we limited our search to papers published after 2000. Papers that did not include a specific treatment method or did not match the subject "Aphasia after stroke" were excluded. Results: Using the searching method, 13 studies were found. Of these, 12 studies were in the form of case reports, while one was in the form of a non-randomized controlled trial. These studies showed positive results for the use of Oriental medicine in terms of the Korean version of the Western Aphasia Battery (K-WAB), the evaluation form on functional performance capability and accuracy of articulatory organs developed by Lee, aphasia screening test refered in 'Assessment in Speech-Language Pathology' and adapted properly to Korean, the Communicative Ability in Daily Living Test (CADLT), the Korean Version-Boston Naming Test (K-BNT), and language assessment items included in CNS, and NIHSS. Conclusions: Of the 12 case reports, 11 studies showed positive results of the use of Oriental medicine for treatment of aphasia after cerebrovascular disease. However, more sophisticated and large-scale clinical research on aphasia should be conducted.

• 기술혁신학회지
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• 제22권2호
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• pp.186-206
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• 2019

한국의 공적개발원조(ODA) 규모는 매년 꾸준히 증가하고 있지만 ODA 사업의 수행 방법과 효과성에 대한 비판은 계속 제기되고 있다. 과학기술 분야도 ODA 규모는 늘어나는 추세이지만 여러 문제점이 있는 것으로 보인다. 첫째, 국내외적으로 과학기술 ODA에 대한 정의가 명확하게 확립되어 있지 않고 학문적 논의도 미흡한 편이다. 둘째, 과학기술 ODA 사업의 성과에 대한 분석도 미흡한 것으로 보인다. 셋째, 과학기술 ODA 사업을 체계적으로 수행할 수 있는 기획 관리 역량이 전반적으로 부족하다. 본 논문에서는 과학기술 정책 자문 사업을 대상으로 하여 과학기술 ODA 사업의 성과에 영향을 미치는 요인들을 분석하였다. 그 결과, 과학기술 지식을 이전하는 이전역량뿐만 아니라 이를 흡수 활용하는 흡수역량이 중요함을 발견하였다. 이런 점에서 보면, 과학기술정책 자문 사업이 성공하기 위해서는 우리의 이전역량과 상대 개도국의 흡수역량을 동시에 고려하여 사업을 기획, 관리하는 체제가 요구된다.

• Advances in robotics research
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• 제2권3호
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• pp.201-217
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• 2018

Agriculture production is a critical human intensive task, which takes place in all regions of the world. The process to grow and harvest crops is labor intensive in many countries due to the lack of automation and advanced technology. Much of the difficult, dangerous and dirty labor of crop production can be automated with intelligent and robotic platforms. We propose an intelligent, agent-oriented robotic team, which can enable the process of harvesting, gathering and collecting crops and fruits, of many types, from agricultural fields. This paper describes a novel robotic organization enabling humans, robots and agents to work together for automation of gathering and collection functions. The focus of the research is a model, called HARMS, which can enable Humans, software Agents, Robots, Machines and Sensors to work together indistinguishably. With this model, any capability-based human-like organization can be conceived and modeled, such as in manufacturing or agriculture. In this research, we model, design and implement a technology application of knowledge-based robot-to-robot and human-to-robot collaboration for an agricultural gathering and collection function. The gathering and collection functions were chosen as they are some of the most labor intensive and least automated processes in the process acquisition of agricultural products. The use of robotic organizations can reduce human labor and increase efficiency allowing people to focus on higher level tasks and minimizing the backbreaking tasks of agricultural production in the future. In this work, the HARMS model was applied to three different robotic instances and an integrated test was completed with satisfactory results that show the basic promise of this research.

• Journal of Information Science Theory and Practice
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• 제9권2호
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• pp.66-82
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• 2021

Recommender Systems have gained immense popularity due to their capability of dealing with a massive amount of information in various domains. They are considered information filtering systems that make predictions or recommendations to users based on their interests and preferences. The more recent technology, Linked Open Data (LOD), has been introduced, and a vast amount of Resource Description Framework data have been published in freely accessible datasets. These datasets are connected to form the so-called LOD cloud. The need for semantic data representation has been identified as one of the next challenges in Recommender Systems. In a LOD-enabled recommendation framework where domain awareness plays a key role, the semantic information provided in the LOD can be exploited. However, dealing with a big chunk of the data from the LOD cloud and its integration with any domain datasets remains a challenge due to various issues, such as resource constraints and broken links. This paper presents the challenges of interconnecting and extracting the DBpedia data with the MovieLens 1 Million dataset. This study demonstrates how LOD can be a vital yet rich source of content knowledge that helps recommender systems address the issues of data sparsity and insufficient content analysis. Based on the challenges, we proposed a few alternatives and solutions to some of the challenges.

• Advances in concrete construction
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• 제11권5호
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• pp.429-445
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• 2021

With regard to economic efficiency, composite fix beams are widely used to pass longitudinal shear forces across the interface. The current knowledge of the composite beam load-slip activity and shear capability are restricted to data from measurements of push-off. Modelling and analysis of the composite beams based on Euro-code 4 regarding to shear, bending, and deflection under differing loads were carried out using Finite Element through an efficient computer simulation and the final loading and sections capacity based on the failure modes was analysed. In bending, the section potential was increased by an improvement of the strength in both steel and concrete, but the flexural and compressive resistance growth is very weak (3.2% 3.1% and 3.0%), while the strength of the concrete has increased respectively from 25 N/mm² to 30, 35, and 40 N/mm² compared to the increment of steel strength by 27% and 21% when it was raised from 275 to 355 and 460 N/mm², respectively. It was found that the final flexural load capacity of fix beams was declined with increase in the fix beam span for both three steel strength. The shear capacity of sections was remained unchanged at constant steel strength and different length, but raised with final yield strength increment of steel sections by 29%, and 67% when it was raised from 275 N/mm² to 355 N/mm² and 460 N/mm², respectively.

• 정보보호학회논문지
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• 제21권1호
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• pp.143-151
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• 2011

모바일 환경의 RFID 시스템에서는 백엔드 서버와 리더의 실시간 통신을 보장할 수 없으므로, 리더는 백엔드 서버와 통신이 불가능한 상황에서도 검색하고자 하는 특정 태그를 정확히 검색할 수 있는 능력을 보장할 수 있어야 한다. 모바일 리더 기반의 태그 검색 프로토콜에 대한 최근 연구들은 태그 및 리더의 프라이버시 문제를 다루고 있지만, 리더가 기존에 소유하던 태그 리스트의 재활용함으로써 발생할 수 있는 문제점은 고려하지 않고 있다. 다시 말해, 특정 태그에 대한 권한이 삭제된 리더가 기존에 소지하던 태그 리스트를 재활용함으로써 권한이 삭제된 태그를 검색할 수 있는 문제가 발생할 수 있다. 제안하는 프로토콜은 태그 리스트의 재활용을 방지함으로써 보안성이 향상된 태그 리스트를 제공하고, 모바일 리더 기반의 RFID 환경에 적합한 동적 ID 기반의 효율적인 태그 검색 프로토콜을 제공한다.

• Advances in aircraft and spacecraft science
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• 제9권3호
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• pp.195-215
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• 2022

The increasing interest in CubeSat platforms ant their capability of enlarging the frontier of possible missions impose technology improvements. Miniaturized electrical propulsion (EP) systems enable new mission for multi-unit CubeSats (6U+). While electric propulsion systems have achieved important level of knowledge at equipment level, the investigation of the mutual impact between EP system and CubeSat technology at system level can provide a decisive improvement for both the technologies. The interaction between CubeSat and EP system should be assessed in terms of electromagnetic emissions (both radiated and conducted), thermal gradients, high electrical power management, surface chemical deposition, and quick and reliable data exchanges. This paper shows how a versatile CubeSat Test Platform (CTP), together with standardized procedures and specialized facilities enable the acquisition fundamental and unprecedented information. Measurements can be taken both by specific ground support equipment placed inside the vacuum facility and by dedicated sensors and subsystems installed on the CTP, providing a completely new set of data never obtained before. CTP is constituted of a 6U primary structure hosting the EP system, representative CubeSat avionics and batteries. For the first test campaign, CTP hosts the ambipolar plasma propulsion system, called Regulus and developed by T4I. After the integration and the functional test in laboratory environment, CTP + Regulus performed a Test campaign in relevant environment in the vacuum chamber at CISAS, University of Padua. This paper is focused on the test campaign description and the main results achieved at different power levels for different duration of the firings.

• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.185-196
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• 2022

The Internet of Things (IoT) has become more and more widespread in recent years, thus attackers are placing greater emphasis on IoT environments. The IoT connects a large number of smart devices via wired and wireless networks that incorporate sensors or actuators in order to produce and share meaningful information. Attackers employed IoT devices as bots to assault the target server; however, because of their resource limitations, these devices are easily infected with IoT malware. The Distributed Denial of Service (DDoS) is one of the many security problems that might arise in an IoT context. DDOS attempt involves flooding a target server with irrelevant requests in an effort to disrupt it fully or partially. This worst practice blocks the legitimate user requests from being processed. We explored an intelligent intrusion detection system (IIDS) using a particular sort of machine learning, such as Artificial Neural Networks, (ANN) in order to handle and mitigate this type of cyber-attacks. In this research paper Feed-Forward Neural Network (FNN) is tested for detecting the DDOS attacks using a modified version of the KDD Cup 99 dataset. The aim of this paper is to determine the performance of the most effective and efficient Back-propagation algorithms among several algorithms and check the potential capability of ANN- based network model as a classifier to counteract the cyber-attacks in IoT environments. We have found that except Gradient Descent with Momentum Algorithm, the success rate obtained by the other three optimized and effective Back- Propagation algorithms is above 99.00%. The experimental findings showed that the accuracy rate of the proposed method using ANN is satisfactory.