• Journal of Smart Tourism
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• 제2권3호
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• pp.5-15
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• 2022

As the utilization of technology in the tourism field becomes familiar, it greatly impacts people's tourism activities. These changes could also affect the behavior of tourists during the pandemic. To investigate consumers' adaptation to the self-service technology (SST) environment during the coronavirus disease of 2019 (COVID-19) pandemic, we adopted a model of absorptive capacity as the main framework for empirical research. To track the social effects of COVID-19, consumers' behavioral intentions for four different points in time are collected. The analysis was conducted using latent growth and structural equation modeling. We set the organizational and environmental characteristics as the first step of the model, with assimilation and trust as a middle step. Intention to use a kiosk is placed at the final step as an exploit. Findings indicate that organizational characteristics and environmental characteristics positively influenced assimilation and trust, except for environmental characteristics. Consumers' assimilation in SST encourages immediate intention to use a kiosk. Consumers' trust in kiosks positively impacts both immediate and continuance intention to use a kiosk during COVID-19.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.256-274
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• 2022

The continuous information technology and telecommunication (ICT) developments inspire several Saudi Arabia citizens to transact and interact online. However, when using online platforms, several people are likely to lose their personal information to cybercriminals. In the survey, 553 Saudi Arabia citizens and 103 information technology (IT) specialists confirm the expansion of digital economy and the need for smart cities with various services, including e-commerce and solid cyber security. 96.6% of the participants believe Saudi Arabia is digitalizing its economy; yet, 33.3% of the participants believe that residents are uninformed about living and operating in smart cities. Several people (47.29%) with medium internet speed are more aware about smart cities than those with fastest internet speed (34%). Besides, online transactions via credit cards subjected 55.5% of the participants to privacy and security issues. These findings validate the essence of cyber security awareness programs among Saudi Arabia citizens and IT professionals to boost public trust and acceptance of cybersecurity frameworks.

• Steel and Composite Structures
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• 제50권3호
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• pp.337-345
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• 2024

This research proposed a particle swarm optimization (PSO) based seismic retrofit design of moment frame structures using a steel frame assembly. Two full scale specimens of the steel frame assembly with different corner details were attached to one-story RC frames for seismic retrofit, and the lateral load resisting capacities of the retrofitted frames subjected to cyclic loads were compared with those of a bare RC frame. The open source software framework Opensees was used to develop an analytical model for validating the experimental results. The developed analytical model and the optimization scheme were applied to a case study structure for economic seismic retrofit design, and its seismic performance was assessed before and after the retrofit. The results show that the developed steel frame assembly was effective in increasing seismic load resisting capability of the structure, and the PSO algorithm could be applied as convenient optimization tool for seismic retrofit design of structures.

• International journal of advanced smart convergence
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• 제13권3호
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• pp.335-344
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• 2024

This study explores advanced machine learning techniques for improving crop yield prediction in smart farming, utilizing multi-temporal spectral data from drone-based multispectral imagery. Conducted in garlic orchards in Andong, Gyeongbuk Province, South Korea, the research examines the effectiveness of various vegetation indices and cutting-edge models, including LSTM, CNN, Random Forest, and XGBoost. By integrating these models with the Analytic Hierarchy Process (AHP), the study systematically evaluates the factors that influence prediction accuracy. The integrated approach significantly outperforms single models, offering a more comprehensive and adaptable framework for yield prediction. This research contributes to precision agriculture by providing a robust, AI-driven methodology that enhances the sustainability and efficiency of farming practices.

• Smart Structures and Systems
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• 제13권4호
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• pp.501-515
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• 2014

This paper presents a linear computational homogenization framework to evaluate the effective (or generalized) electromechanical coupling coefficient (EMCC) of adaptive structures with piezoelectric structural fiber (PSF) composite elements. The PSF consists of a silicon carbide (SiC) or carbon core fiber as reinforcement to a fragile piezo-ceramic shell. For the micro-scale analysis, a micromechanics model based on the variational asymptotic method for unit cell homogenization (VAMUCH) is used to evaluate the overall electromechanical properties of the PSF composites. At the macro-scale, a finite element (FE) analysis with the commercial FE code ABAQUS is performed to evaluate the effective EMCC for structures with the PSF composite patches. The EMCC is postprocessed from free-vibrations analysis under short-circuit (SC) and open-circuit (OC) electrodes of the patches. This linear two-scale computational framework may be useful for the optimal design of active structure multi-functional composites which can be used for multi-functional applications such as structural health monitoring, power harvest, vibration sensing and control, damping, and shape control through anisotropic actuation.

• 스마트미디어저널
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• 제4권3호
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• pp.56-61
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• 2015

빅데이터와 관련하여 많은 성공사례들이 보고되었지만 실제로 시스템을 구축하는 데 있어서는 여전히 많은 어려움이 있다. 기술적인 측면에서 데이터의 수집과 저장, 처리와 분석, 그리고 표현과 사용에 이르는 전 과정을 포괄적으로 이해해야 하고, 비즈니스적 측면에서는 구축된 시스템으로부터 얻을 수 있는 가치를 미리 파악하여 투자를 감행해야 하는 경영진에게 설명해야 한다. 본 연구는 빅데이터 정보시스템을 구축하는 것과 관련된 사항들을 쉽게 파악할 수 있는 5W 1H 프레임워크를 제공하고, 제시된 프레임워크를 기존의 빅데이터 사례들에 적용한 예시를 보여주었다. 투자를 위한 경영진의 의사결정을 이끌어내고 빅데이터 프로젝트의 종합적인 이해와 관리에 도움을 줄 수 있을 것으로 기대된다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2019년도 학술발표회
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• pp.161-161
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• 2019

Water security issues, stimulated by increasing population and changing climate, are growing and pausing major challenges for water resources managers around the world. Proper utilization, management and distribution of all available water resources is key to sustainable development for achieving water security To alleviate the water shortage, most of the current research on multi-sources combined water supplies depends on an overall generalization of regional water supply systems, which are seldom broken down into the detail required to address specific research objectives. This paper proposes the concept of optimization framework on multi water sources selection. A multi-objective water allocation model with four objective functions is introduced in this paper. Harmony search algorithm is employed to solve the applied model. The objective functions addresses the economic, environmental, and social factors that must be considered for achieving a sustainable water allocation to solve the issue of water security.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권8호
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• pp.2849-2864
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• 2021

The emerging of cloud data sharing can create great values, especially in multi-cloud environments. However, "data island" between different cloud service providers (CSPs) has drawn trust problem in data sharing, causing contradictions with the increasing sharing need of cloud data users. And how to ensure the data value for both data owner and data user before sharing, is another challenge limiting massive data sharing in the multi-cloud environments. To solve the problems above, we propose a Uniform Encoding and Parsing Framework (UEPF) with blockchain to support trustworthy and valuable data sharing. We design namespace-based unique identifier pair to support data description corresponding with data in multi-cloud, and build a blockchain-based data encoding protocol to manage the metadata with identifier pair in the blockchain ledger. To share data in multi-cloud, we build a data parsing protocol with smart contract to query and get the sharing cloud data efficiently. We also build identifier updating protocol to satisfy the dynamicity of data, and data check protocol to ensure the validity of data. Theoretical analysis and experiment results show that UEPF is pretty efficient.

• 스마트미디어저널
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• 제13권3호
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• pp.53-61
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• 2024

본 논문은 기존 방법보다 우수한 성능을 달성하는 피부 병변 분할을 위한 새로운 M자 모양 인코더-디코더 아키텍처를 제안한다. 제안된 아키텍처는 왼쪽과 오른쪽 다리를 활용하여 다중 스케일 특징 추출을 가능하게 하고, 스킵 연결 내에서 어텐션 메커니즘을 통합하여 피부 병변 분할 성능을 더욱 향상시킨다. 입력 영상은 네 가지 다른 패치로 분할되어 입력되며 인코더-디코더 프레임워크 내에서 피부 병변 분할 성능의 향상된 처리를 가능하게 한다. 제안하는 방법에서 어텐션 메커니즘을 통해 입력 영상의 특징에 더 많은 초점을 맞추어 더욱 정교한 영상 분할 결과를 도출하는 것이다. 실험 결과는 제안된 방법의 효과를 강조하며, 기존 방법과 비교하여 우수한 정확도, 정밀도 및 Jaccard 지수를 보여준다.

• 융합정보논문지
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• 제10권9호
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• pp.1-7
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• 2020

제조 혁신을 위한 스마트 팩토리의 구현을 위하여 점차 디지털 트윈이 많이 개발되고 또 적용될 것이다. 특히 개발된 디지털 트윈에 대하여 시뮬레이션 및 최적화 분석을 실시함으로써 설비의 예지보전과 같은 중요한 의사결정을 지원할 수 있다. 본 연구는 사용자 관점에서 이러한 분석을 지원하는 체계인 디지털 트윈 관리시스템(DTMS: Digital Twin Management System)의 개념적 구조를 제시한다. 디지털 트윈은 다양한 분석 모듈과 데이터 등으로 매우 복잡하게 구성되어 있다. 스마트 팩토리가 진행될수록 디지털 트윈의 관리는 더욱 어려워지게 될 것이다. 따라서 이를 체계적으로 관리를 가능하게 하는 DTMS가 필요하다. 본 연구는 DTMS의 개발을 위하여 제조공학, 의사결정지원시스템, 그리고 최적화 분야에서 제시된 이론 및 체계들을 문제 해결 관점에서 통합한다. 그리고 제시된 프레임워크의 현실적용 가능성을 보이기 위하여 DTMS를 디스플레이 제조공정에 적용해 본다. 본 연구에서 제시된 DTMS는 전형적인 DSS(Decision Support System) 구조를 띤다. 즉 DTMS는 대화관리시스템, 모델관리시스템, 그리고 데이터관리시스템 등과 같은 3개의 서브시스템과 분석용 디지털 트윈 및 최적화 툴로 구성된다. 본 연구를 통하여 제시한 DTMS는 스마트 펙토리를 지향하는 경쟁력이 있으며 복잡한 산업 영역에 적용될 수 있다. 학문적으로는 새로운 시각에서 디지털 트윈의 분석을 조명한 것으로 추후 연구의 방향을 제시했다는 점에서 의미가 있다.