• Journal of The Korean Association For Science Education
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• v.27 no.1
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• pp.1-8
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• 2007

The purpose of this study was to examine the effects of science-related and scientific attitudes in Small-Scale Science (SSS) experimental learning on 3rd grade middle school students. Two classes were chosen from a middle school in Pohang and classified into two groups: the first group, the experimental group, composed of twenty-six students, undergoing SSS and the other group, comparison group, composed of twenty-five students who were taught experimental learning by the traditional teaching method. The major observations of this study are as follows: The SSS experimental learning significantly influenced the students' science-related and scientific attitudes within the experimental group. Also, there was a meaningful difference in the subcategory of science-related attitudes and scientific attitudes before and after the SSS experimental learning. Otherwise, there was no significant difference in comparison group. In conclusion, the class using the SSS was positively influenced in forming students' science-related and scientific attitudes. In particular, the effect on subcategories of science-related attitudes such as attitude towards science are more remarkable. The SSS experimental learning helps students to enhance the subcategorial factors of scientific attitude such as their curiosity, critical thinking, cooperation, self-participation, persistence and ingenuity. The SSS experimental learning, therefore, can improve learning attitudes.

• Smart Structures and Systems
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• v.21 no.3
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• pp.335-347
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• 2018

The fast-growing number of mobile and wearable applications has driven several innovations in small-scale electret-based energy harvesting due to the compatibility with standard microfabrication processes and the ability to generate electrical energy from ambient vibrations. However, the current modeling methods used to design these small scale transducers or microgenerators are applicable only for constant-speed rotations and small sinusoidal translations, while in practice, large amplitude sinusoidal vibrations can happen. Therefore, in this paper, we formulate an analytical model for electret-based microgenerators under general sinusoidal excitations. The proposed model is validated using finite element modeling combined with numerical simulation approaches presented in the literature. The new model demonstrates a good agreement in estimating both the output voltage and power of the microgenerator. This new model provides useful insights into the microgenerator operating mechanism and design trade-offs, and therefore, can be utilized in the design and performance optimization of these small structures.

• Smart Structures and Systems
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• v.31 no.1
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• pp.69-78
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• 2023

The purpose of this paper is to develop a scalable grey predictive controller with unavoidable random delays. Grey prediction is proposed to solve problems caused by incorrect parameter selection and to eliminate the effects of dynamic coupling between degrees of freedom (DOFs) in nonlinear systems. To address the stability problem, this study develops an improved gray-predictive adaptive fuzzy controller, which can not only solve the implementation problem by determining the stability of the system, but also apply the Linear Matrix Inequality (LMI) law to calculate Fuzzy change parameters. Fuzzy logic controllers manipulate robotic systems to improve their control performance. The stability is proved using Lyapunov stability theorem. In this article, the authors compare different controllers and the proposed predictive controller can significantly reduce the vibration of offshore platforms while keeping the required control force within an ideal small range. This paper presents a robust fuzzy control design that uses a model-based approach to overcome the effects of modeling errors. To guarantee the asymptotic stability of large nonlinear systems with multiple lags, the stability criterion is derived from the direct Lyapunov method. Based on this criterion and a distributed control system, a set of model-based fuzzy controllers is synthesized to stabilize large-scale nonlinear systems with multiple delays.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.545-559
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• 2010

This paper presents the results of a pilot study and verification of a concept of a novel methodology for damage detection and assessment of water distribution system. The unique feature of the proposed noninvasive methodology is the use of accelerometers installed on the pipe surface, instead of pressure sensors that are traditionally installed invasively. Experimental observations show that a sharp change in pressure is always accompanied by a sharp change of pipe surface acceleration at the corresponding locations along the pipe length. Therefore, water pressure-monitoring can be transformed into acceleration-monitoring of the pipe surface. The latter is a significantly more economical alternative due to the use of less expensive sensors such as MEMS (Micro-Electro-Mechanical Systems) or other acceleration sensors. In this scenario, monitoring is made for Maximum Pipe Acceleration Gradient (MPAG) rather than Maximum Water Head Gradient (MWHG). This paper presents the results of a small-scale laboratory experiment that serves as the proof of concept of the proposed technology. The ultimate goal of this study is to improve upon the existing SCADA (Supervisory Control And Data Acquisition) by integrating the proposed non-invasive monitoring techniques to ultimately develop the next generation SCADA system for water distribution systems.

• Smart Structures and Systems
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• v.25 no.6
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• pp.765-778
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• 2020

The present study intends to find a proper solution for the estimation of the physical behaviors of enlarged piles through a combination of small-scale laboratory tests and a hybrid computational predictive intelligence process. In the first step, experimental program is completed considering various critical influential factors. The results of the best multilayer perceptron (MLP)-based predictive network was implemented through three mathematical-based solutions of dragonfly algorithm (DA), whale optimization algorithm (WOA), and ant lion optimization (ALO). Three proposed models, after convergence analysis, suggested excellent performance. These analyses varied based on neurons number (e.g., in the basis MLP hidden layer) and of course, the level of its complexity. The training R² results of the best hybrid structure of DA-MLP, WOA-MLP, and ALO-MLP were 0.996, 0.996, and 0.998 where the testing R² was 0.995, 0.985, and 0.998, respectively. Similarly, the training RMSE of 0.046, 0.051, and 0.034 were obtained for the training and testing datasets of DA-MLP, WOA-MLP, and ALO-MLP techniques, while the testing RMSE of 0.088, 0.053, and 0.053, respectively. This obtained result demonstrates the excellent prediction from the optimized structure of the proposed models if only population sensitivity analysis performs. Indeed, the ALO-MLP was slightly better than WOA-MLP and DA-MLP methods.

• Smart Structures and Systems
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• v.18 no.3
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• pp.601-623
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• 2016

Precast concrete elements are widely used in the construction of buildings and civil infrastructures as they provide higher construction quality and requires less construction time. However, any abnormalities in precast concrete surfaces such as non-flatness or distortion, can influence the erection of the elements as well as the functional performance of the connections between elements. Thus, it is important to undertake surface flatness and distortion inspection (SFDI) on precast concrete elements before their delivery to the construction sites. The traditional methods of SFDI which are conducted manually or by contact-type devices are, however, time-consuming, labor-intensive and error-prone. To tackle these problems, this study proposes techniques for SFDI of precast concrete elements using laser scanning technology. The proposed techniques estimate the $F_F$ number to evaluate the surface flatness, and estimate three different measurements, warping, bowing, and differential elevation between adjacent elements, to evaluate the surface distortion. The proposed techniques were validated by experiments on four small scale test specimens manufactured by a 3D printer. The measured surface flatness and distortion from the laser scanned data were compared to the actual ones, which were obtained from the designed surface geometries of the specimens. The validation experiments show that the proposed techniques can evaluate the surface flatness and distortion effectively and accurately. Furthermore, scanning experiments on two actual precast concrete bridge deck panels were conducted and the proposed techniques were successfully applied to the scanned data of the panels.

• Korean Journal of Environmental Agriculture
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• v.27 no.1
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• pp.18-26
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• 2008

Behavior and decomposition velocity of pollutants on various forms from domestic sewage in sewage treatment plant were investigated in order to obtain the basic data for improving the removal efficiency of pollutants and to reduce the area in constructed wetland by natural purification method. The removal amounts of BODs and CODs in aerobic bed were significantly higher than those of the other beds. In aerobic bed, the removal amounts of IBOD and ICOD were more than those for SBOD and SCOD, respectively, whereas the removal amounts of BODs and CODs in anoxic and anaerobic beds were little different. The removal amounts of SSs in aerobic bed were also higher than those for the other beds, and the removal amounts of VSS in all beds were more than those for FSS. The removal amounts of DTN and DTP in all beds were more than those for STN and STP, respectively. In addition, the decomposition velocities of TBOD, TCOD and TSS in aerobic bed were 30.79, 17.15 and 29.96 $day^{-1}$. Moreover, the decomposition velocities of BODs, CODs and SSs in aerobic bed were very rapid than those in the other beds. On the other hand, the decomposition velocities of BODs, CODs and SSs in anoxic and anaerobic beds were a little different regardless of the forms of pollutant. The decomposition velocities constants of T-N in aerobic, anoxic and anaerobic beds were 4.78, 0.12 and 0.10 $day^{-1}$, respectively. Moreover, the decomposition velocities constants of T-P in aerobic, anoxic and anaerobic beds were 13.09, 0.12 and 0.13 $day^{-1}$ respectively. The decomposition velocity of T-Ns and T-Ps in aerobic bed were slightly rapid than those in the other beds, whereas the decomposition velocities of T-Ns and T-Ps in anoxic and anaerobic beds were slightly different regardless of the forms of pollutant.

• Smart Structures and Systems
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• v.21 no.4
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• pp.397-405
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• 2018

In this paper, a novel simple shear deformation theory for buckling analysis of single layer graphene sheet is formulated using the nonlocal differential constitutive relations of Eringen. The present theory involves only three unknown and three governing equation as in the classical plate theory, but it is capable of accurately capturing shear deformation effects, instead of five as in the well-known first shear deformation theory (FSDT) and higher-order shear deformation theory (HSDT). A shear correction factor is, therefore, not required. Nonlocal elasticity theory is employed to investigate effects of small scale on buckling of the rectangular nano-plate. The equations of motion of the nonlocal theories are derived and solved via Navier's procedure for all edges simply supported boundary conditions. The results are verified with the known results in the literature. The influences played by Effects of nonlocal parameter, length, thickness of the graphene sheets and shear deformation effect on the critical buckling load are studied. Verification studies show that the proposed theory is not only accurate and simple in solving the buckling nanoplates, but also comparable with the other higher-order shear deformation theories which contain more number of unknowns.