• Smart Structures and Systems
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• 제31권5호
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• pp.531-543
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• 2023

Base isolation is one of the most widely implemented and well-known technique to reduce structural vibration and damages during an earthquake. However, while the base-isolated structure reduces storey drift significantly, it also increases the base drifts causing many practical problems. This study proposes the use of Shape Memory Alloys (SMA) wires for the reduction in base drift while controlling the overall structure vibrations. A multi-degree-of-freedom (MDOF) structure along with base isolators and Shape-Memory-Alloys (SMA) wires in diagonal is tested experimentally and analytically. The isolation bearing considered in this study consists of laminates of steel and silicon rubber. The performance of the proposed structure is evaluated and studied under different loadings including harmonic loading and seismic excitation. To assess the seismic performance of the proposed structure, shake table tests are conducted on base-isolated MDOF frame structure incorporating SMA wires, which is subjected to incremental harmonic and historic seismic loadings. Root mean square acceleration, displacement and drift are analyzed and discussed in detail for each story. To better understand the structure response, the percentage reduction of displacement is also determined for each story. The result shows that the reduction in the response of the proposed structure is much better than conventional base-isolated structure.

• Smart Structures and Systems
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• 제29권5호
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• pp.677-691
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• 2022

Water cycle algorithm (WCA) has been a very effective optimization technique for complex engineering problems. This study employs the WCA for simultaneous prediction of heating load (L_H) and cooling load (L_C) in residential buildings. This algorithm is responsible for optimally tuning a neural network (NN). Utilizing 614 records, the behavior of the L_H and L_C is explored and the captured knowledge is then used to predict for 154 unanalyzed building conditions. Since the WCA is a population-based algorithm, different numbers of the searching agents were tested to find the most optimum configuration. It was observed that the best solution is discovered by 500 agents. A comparison with five newly-developed benchmark optimizers, namely equilibrium optimizer (EO), multi-tracker optimization algorithm (MTOA), slime mould algorithm (SMA), multi-verse optimizer (MVO), and electromagnetic field optimization (EFO) revealed that the WCANN predicts the desired parameters with considerably larger accuracy. Obtained root mean square errors (1.4866, 2.1296, 2.8279, 2.5727, 2.5337, and 2.3029 for the L_H and 2.1767, 2.6459, 3.1821, 2.9732, 2.9616, and 2.6890 for the L_C) indicated that the most reliable prediction was presented by the proposed model. The EFONN, however, provided a more time-effective solution. Lastly, an explicit predictive formula was elicited from the WCANN.

• Smart Structures and Systems
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• 제31권6호
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• pp.561-571
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• 2023

Ensuring the safety of a structure necessitates that repairs are carried out based on accurate inspections and records of damage information. Traditional methods of recording damage rely on individual paper-based documents, making it challenging for inspectors to accurately record damage locations and track chronological changes. Recent research has suggested the adoption of building information modeling (BIM) to record detailed damage information; however, localizing damages on a BIM model can be time-consuming. To overcome this limitation, this study proposes a method to automatically localize damages on a BIM model in real-time, utilizing consecutive images and measurements from an inertial measurement unit in close proximity to damages. The proposed method employs a visual-inertial odometry algorithm to estimate the camera pose, detect damages, and compute the damage location in the coordinate of a prebuilt BIM model. The feasibility and effectiveness of the proposed method were validated through an experiment conducted on a campus building. Results revealed that the proposed method successfully localized damages on the BIM model in real-time, with a root mean square error of 6.6 cm.

• International journal of advanced smart convergence
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• 제11권4호
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• pp.88-95
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• 2022

Vacuum simulation is associated with the prediction and calculation of how materials, pumps and systems will perform using mathematical equations. In this investigation, three different high vacuum systems were simulated and estimated with each vacuum characteristics by VacTran simulator. In each of modelled vacuum systems, selection of gas loads into vessel, combination of rough and high vacuum pumps and dimension of conductance elements were proposed as system variables. In pump station model, the pumping speed to pressures by the combination of root pump was analyzed under the variations of vessel volume. In this study, the effects of outgassing dependent on vessel materials was also simulated and aluminum vessel was estimated to optimum materials. It was obtained from the modelling with diffusion pump that the diameter, length of 50×250[mm]roughing line was characterized as optimum variables to reach the ultimate pressure of 10E-7[torr]. Optimum design factors for vacuum characteristics of modelled vacuum system were achieved by VacTran simulator. Feasibility of VacTran as vacuum simulator was verified and applications of VacTran in high tech process expected to be increased.

• Smart Structures and Systems
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• 제32권5호
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• pp.297-308
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• 2023

Dynamic deflection is important for evaluating the performance of a long-span cable-stayed bridge, and its continuous measurement is still cumbersome. This study proposes a dynamic deflection monitoring method for cable-stayed bridge based on Bi-directional Long Short-term Memory (BiLSTM) neural network taking advantages of the characteristics of spatial variation of cable acceleration response (CAR) and main girder deflection response (MGDR). Firstly, the relationship between the spatial and temporal variation of the CAR and the MGDR is described based on the geometric deformation of the bridge. Then a data-driven relational model based on BiLSTM neural network is established using CAR and MGDR data, and it is further used to monitor the MGDR via measuring the CAR. Finally, numerical simulations and field test are conducted to verify the proposed method. The root mean squared error (RMSE) of the numerical simulations are less than 4 while the RMSE of the field test is 1.5782, which indicate that it provides a cost-effective and convenient method for real-time deflection monitoring of cable-stayed bridges.

• 한국해양공학회지
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• 제38권2호
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• pp.43-52
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• 2024

Investigating ship motion under real conditions is vital for evaluating the seakeeping performance, particularly in the design process stage. This study examined the influence of the principal particulars of a trawler on its seakeeping performance. The wave conditions in the Bering Sea are investigated using available data. The length-to-beam (L/B) and beam-to-draft (B/T) ratios of the ship are changed by 10% for the numerical simulation. The response amplitude operator (RAO) motion, root mean square (RMS) value and sensitivity analysis are calculated to evaluate the influence of the trawler dimensions on ship motions. The peak RAO motion affected the ship motions noticeably because of the resonance at the natural frequency. The L/B and B/T ratios are important geometric parameters of a ship that significantly influence its RMS motion, particularly in the case of roll and pitch. The change in the B/T ratio has a good seakeeping performance based on a comparison of the roll and pitch with the seakeeping criteria. The present results provide insights into the seakeeping performance of ships due to the influence of the principal dimensions in the design stage.

• 대한원격탐사학회지
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• 제39권1호
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• pp.47-63
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• 2023

Unmanned aerial vehicle (UAV) and sensor technologies are rapidly developing and being usefully utilized for spatial information-based agricultural management and smart agriculture. Until now, there have been many difficulties in obtaining production information in a timely manner for large-scale agriculture on reclaimed land. However, smart agriculture that utilizes sensors, information technology, and UAV technology and can efficiently manage a large amount of farmland with a small number of people is expected to become more common in the near future. In this study, we evaluated the productivity of forage maize grown on reclaimed land using UAV and sensor-based technologies. This study compared the plant height, vegetation cover ratio, fresh biomass, and dry biomass of maize grown on general farmland and reclaimed land in South Korea. A biomass model was constructed based on plant height, cover ratio, and volume-based biomass using UAV-based images and Farm-Map, and related estimates were obtained. The fresh biomass was estimated with a very precise model (R² =0.97, root mean square error [RMSE]=3.18 t/ha, normalized RMSE [nRMSE]=8.08%). The estimated dry biomass had a coefficient of determination of 0.86, an RMSE of 1.51 t/ha, and an nRMSE of 12.61%. The average plant height distribution for each field lot was about 0.91 m for reclaimed land and about 1.89 m for general farmland, which was analyzed to be a difference of about 48%. The average proportion of the maize fraction in each field lot was approximately 65% in reclaimed land and 94% in general farmland, showing a difference of about 29%. The average fresh biomass of each reclaimed land field lot was 10 t/ha, which was about 36% lower than that of general farmland (28.1 t/ha). The average dry biomass in each field lot was about 4.22 t/ha in reclaimed land and about 8 t/ha in general farmland, with the reclaimed land having approximately 53% of the dry biomass of the general farmland. Based on these results, UAV and sensor-based images confirmed that it is possible to accurately analyze agricultural information and crop growth conditions in a large area. It is expected that the technology and methods used in this study will be useful for implementing field-smart agriculture in large reclaimed areas.

• 현장농수산연구지
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• 제24권4호
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• pp.53-61
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• 2022

적절한 기후와 토양 조건을 조성하여 제어되는 온실에서 농작물을 재배하는 것은 중요한 연구 및 적용 과제가 되어왔다. 온실의 적절한 환경 조건은 최적의 식물 성장, 작물 수확량 향상을 위해 필요하다. 본 연구는 온도센서, 토양 센서, 작물 센서, 카메라 등 각종 센서와 장비를 연결하는 온실 IT기술을 적용하여 농작물 재배 환경과 생육 상태를 실시간으로 모니터링하는 웹 기반 원격 모니터링 시스템 구축을 목적으로 하였다. 측정항목은 기온, 상대습도, 일사량, CO₂ 농도, 양액 EC, pH, 배지온도, 배지 EC, 배지 수분함량, 수액 흐름, 줄기 직경, 과실 직경 등이다. 개발된 온실 모니터링 시스템은 네트워크 시스템, 센서가 부착된 데이터 수집 장치, 카메라로 구성되었다. 원격 모니터링 시스템은 서버/클라이언트 환경에서 구현되었다. 온실 환경 및 작물에 대한 정보는 데이터베이스에 저장된다. 저장된 정보 중 성장 및 환경에 대한 항목을 추출 비교하고 분석할 수 있다. 스마트 온실을 위한 통합 모니터링 시스템은 스마트 온실 관리를 위한 환경 및 작물성장을 이해하고 응용 실무에 사용될 것이다.

• 한국HCI학회논문지
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• 제10권2호
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• pp.13-19
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• 2015

디스플레이 기술은 비약적으로 발전되었다. 특히 플렉서블 디스플레이에 대한 연구를 관련 기업들이 앞다투어 진행하고 있다. 현재 시장에는 플렉서블 디스플레이의 초기 단계인 커브드 디스플레이를 사용한 스마트폰, TV 등이 출시되어 있고, 데스크탑용 커브드 모니터 역시 최근에 출시되어 사무용 또는 엔터테인먼트용으로 이용되고 있다. 본 연구의 목적은 엔터테인먼트용으로 50" 멀티 모니터를 사용시 모니터의 곡률이 사용 자세 제어에 미치는 영향에 관한 것이다. 실험에는 두 종류의 곡률 (평면, 곡률반경 600mm)이 사용되었다. 총 10명의 근골격계질환이 없고, 양안 시력이 모두 0.8이상이고, 색맹 또는 색약이 아닌 평균 (SD) 20.9 (1.5)세의 대학생들이 실험에 참여하였다. 피험자들은 일반적인 VDT 환경의 실험실에서 각 곡률당 30분씩 핸들과 페달을 사용해 운전 게임을 하였다. 각 피험자가 운전 게임을 하는 동안 의자 위에 놓여진 압력 매트를 통해 이들의 COP (Center of Pressure)가 측정되었다. 자세 제어 분석을 위하여, 총 4개의 COP 측정치, Mean Velocity, Median Power Frequency, Root-Mean-Square (RMS) Distance, 그리고 95% Confidence Ellipse Area를 사용하였다. 실험 결과, 곡면대비 평면 디스플레이에서 전후 방향 (Anterior-Posterior; AP)의 RMS distance값이 더 큰 경향을 보였다. 이 결과를 통해 평면 디스플레이를 사용하여 운전 게임을 하는 동안 피험자의 전후 방향으로 몸을 더 많이 움직였다고 할 수 있다. 이는 평면 디스플레이가 곡면 디스플레이보다 화면의 가로방향으로 시거리 차이가 더 크기 때문에, 초점의 이동시간이 더 길어지는 것과 관련이 있을 수 있다. 또한, 평면 디스플레이 대비 곡면 디스플레이에서 더 높은 몰입감을 느끼거나, 더 집중할 수 있는 것과 관련이 있을 수 있다. 디스플레이 곡률에 따른 이런 행동상의 차이가 근골격계 질환에 미치는 영향에 대한 추가 연구가 필요하다.

• 한국정보전자통신기술학회논문지
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• 제12권3호
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• pp.242-250
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• 2019

본 논문에서는 인공신경망(Artificial Neural Network) 모델 중, 시계열 데이터의 변환을 위한 모델인 Seq2Seq(Sequence to Sequence) 모델을 이용한 산업용 로봇 고장 예지 기술에 대하여 제안한다. 제안 방법은 고장 예지를 위한 추가적인 센서의 부착 없이 로봇 자체적으로 측정 가능한 관절 별 전류와 각도 값을 데이터로 사용하였고, 측정된 데이터를 모델이 학습할 수 있도록 전처리한 후, Seq2Seq 모델을 통해 전류를 각도로 변환하도록 지도 학습 하였다. 고장 진단을 위한 이상 정도(Abnormal degree)는 예측 각도와 실제 각도 간의 단위시간 동안의 RMSE(Root Mean Squared Error)를 사용하였다. 제안 방법의 성능평가는 로봇의 정상 및 결함 조건을 달리한 상태에서 측정한 테스트 데이터를 이용하여 수행되었고 이상 정도가 임계값 넘어가면 고장으로 분류하게 하여, 실험으로부터 96.67% 고장 진단 정확도를 보였다. 제안 방법은 별도의 추가적인 센서 없이 고장 예지 수행이 가능하다는 장점이 있으며, 로봇에 대한 깊은 전문지식을 요구하지 않으면서 수행할 수 있는 방법으로 높은 진단 성능과 효용성을 실험으로부터 확인하였다.