ALBERT

Description: Surrounded by the ocean, Taiwan has been increasingly developing coastal tourism projects. Concerns that negative impacts might be brought about by prosperous tourism have resulted in a recent focus on sustainable tourism. Sustainable tourism involves policies that acknowledge the interdependences among the environment, the community, and the economy. The goal of sustainable tourism is to enhance and protect the environment while satisfying basic human requirements, as well as those of the contemporary and future tourism industries to improve quality of life. On the other hand, unsustainable coastal tourism might undermine the natural environment and society, resulting in air, water, and soil pollution, wildlife habitat disruption, and changes of local community cultural characteristics. Therefore, performance evaluation of coastal tourism, using an indicator framework to facilitate sustainable development and enhance the effectiveness of coastal resources exploitation, is critical. Through a literature review and expert surveys using the methods of the fuzzy Delphi method (FDM) and the fuzzy analytic hierarchy process (FAHP), this study builds a performance indicator framework and identifies the key factors affecting the sustainable development of coastal tourism in Taiwan. The results can serve as a reference for the public sector to be used for the sustainable planning and development of coastal tourism.

Description: With the emergence of new technologies, mobile devices are capable of undertaking computational and sensing tasks. A large number of users with these mobile devices promote the formation of the Mobile Crowdsourcing Systems (MCSs). Within a MCS, each mobile device can contribute to the crowdsourcing platform and get rewards from it. In order to achieve better performance, it is important to design a mechanism that can attract enough participants with mobile devices and then allocate the tasks among participants efficiently. In this paper, we are interested in the investigation of tasks allocation and price determination in MCSs. Two truthful auction mechanisms are proposed for different working patterns. A Vickrey–Clarke–Groves (VCG)-based auction mechanism is proposed to the continuous working pattern, and a suboptimal auction mechanism is introduced for the discontinuous working pattern. Further analysis shows that the proposed mechanisms have the properties of individual rationality and computational efficiencies. Experimental results suggest that both mechanisms guarantee all the mobile users bidding with their truthful values and the optimal maximal social cost can be achieved in the VCG-based auction mechanism.

Description: This paper is focused on the template-free synthesis of nanosized ferric oxide (nano-Fe2O3) and its application in quartz crystal microbalance (QCM) resonators to detect dimethyl methylphosphonate (DMMP), a simulant of Sarin. The X-ray diffraction (XRD) patterns confirm that the synthesized samples are made of Fe2O3 and the scanning electron microscopy (SEM) pictures show that the samples have ball-like shapes. The DMMP sensors with a sensing film of hollow ball-like and solid ball-like Fe2O3 are fabricated and their sensing characteristics are compared. The sensitivity of the hollow ball-like Fe2O3 sensor is more than 500% higher than the one of the solid ball-like Fe2O3 sensor. The hollow ball-like nano-Fe2O3 can be synthesized by a novel low temperature hydrothermal method. The sensors with the hollow ball-like Fe2O3 film perform well in a range of 1 to 6 ppm, with a sensitivity of 29 Hz/ppm at room temperature, while the appropriate recoverability and selectivity are maintained. In addition, the performance of different thicknesses of the sensing film of the hollow ball-like nano-Fe2O3 is investigated and the optimized relative film thickness of the hollow ball-like nano-Fe2O3 is found to be 20 μg/mm2.

Description: IJERPH, Vol. 15, Pages 1256: Impact of Indoor Physical Environment on Learning Efficiency in Different Types of Tasks: A 3 × 4 × 3 Full Factorial Design Analysis International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15061256 Authors: Lilin Xiong Xiao Huang Jie Li Peng Mao Xiang Wang Rubing Wang Meng Tang Indoor physical environments appear to influence learning efficiency nowadays. For improvement in learning efficiency, environmental scenarios need to be designed when occupants engage in different learning tasks. However, how learning efficiency is affected by indoor physical environment based on task types are still not well understood. The present study aims to explore the impacts of three physical environmental factors (i.e., temperature, noise, and illuminance) on learning efficiency according to different types of tasks, including perception, memory, problem-solving, and attention-oriented tasks. A 3 × 4 × 3 full factorial design experiment was employed in a university classroom with 10 subjects recruited. Environmental scenarios were generated based on different levels of temperature (17 °C, 22 °C, and 27 °C), noise (40 dB(A), 50 dB(A), 60 dB(A), and 70 dB(A)) and illuminance (60 lx, 300 lx, and 2200 lx). Accuracy rate (AC), reaction time (RT), and the final performance indicator (PI) were used to quantify learning efficiency. The results showed ambient temperature, noise, and illuminance exerted significant main effect on learning efficiency based on four task types. Significant concurrent effects of the three factors on final learning efficiency was found in all tasks except problem-solving-oriented task. The optimal environmental scenarios for top learning efficiency were further identified under different environmental interactions. The highest learning efficiency came in thermoneutral, relatively quiet, and bright conditions in perception-oriented task. Subjects performed best under warm, relatively quiet, and moderately light exposure when recalling images in the memory-oriented task. Learning efficiency peaked to maxima in thermoneutral, fairly quiet, and moderately light environment in problem-solving process while in cool, fairly quiet and bright environment with regard to attention-oriented task. The study provides guidance for building users to conduct effective environmental intervention with simultaneous controls of ambient temperature, noise, and illuminance. It contributes to creating the most suitable indoor physical environment for improving occupants learning efficiency according to different task types. The findings could further supplement the present indoor environment-related standards or norms with providing empirical reference on environmental interactions.

Description: This paper is focused on the template-free synthesis of nanosized ferric oxide (nano-Fe2O3) and its application in quartz crystal microbalance (QCM) resonators to detect dimethyl methylphosphonate (DMMP), a simulant of Sarin. The X-ray diffraction (XRD) patterns confirm that the synthesized samples are made of Fe2O3 and the scanning electron microscopy (SEM) pictures show that the samples have ball-like shapes. The DMMP sensors with a sensing film of hollow ball-like and solid ball-like Fe2O3 are fabricated and their sensing characteristics are compared. The sensitivity of the hollow ball-like Fe2O3 sensor is more than 500% higher than the one of the solid ball-like Fe2O3 sensor. The hollow ball-like nano-Fe2O3 can be synthesized by a novel low temperature hydrothermal method. The sensors with the hollow ball-like Fe2O3 film perform well in a range of 1 to 6 ppm, with a sensitivity of 29 Hz/ppm at room temperature, while the appropriate recoverability and selectivity are maintained. In addition, the performance of different thicknesses of the sensing film of the hollow ball-like nano-Fe2O3 is investigated and the optimized relative film thickness of the hollow ball-like nano-Fe2O3 is found to be 20 μg/mm2.

Description: Energies, Vol. 10, Pages 1196: Icing Forecasting of Transmission Lines with a Modified Back Propagation Neural Network-Support Vector Machine-Extreme Learning Machine with Kernel (BPNN-SVM-KELM) Based on the Variance-Covariance Weight Determination Method Energies doi: 10.3390/en10081196 Authors: Dongxiao Niu Yi Liang Haichao Wang Meng Wang Wei-Chiang Hong Stable and accurate forecasting of icing thickness is of great significance for the safe operation of the power grid. In order to improve the robustness and accuracy of such forecasting, this paper proposes an innovative combination forecasting model using a modified Back Propagation Neural Network-Support Vector Machine-Extreme Learning Machine with Kernel (BPNN-SVM-KELM) based on the variance-covariance (VC) weight determination method. Firstly, the initial weights and thresholds of BPNN are optimized by mind evolutionary computation (MEC) to prevent the BPNN from falling into local optima and speed up its convergence. Secondly, a bat algorithm (BA) is utilized to optimize the key parameters of SVM. Thirdly, the kernel function is introduced into an extreme learning machine (ELM) to improve the regression prediction accuracy of the model. Lastly, after adopting the above three modified models to predict, the variance-covariance weight determination method is applied to combine the forecasting results. Through performance verification of the model by real-world examples, the results show that the forecasting accuracy of the three individual modified models proposed in this paper has been improved, but the stability is poor, whereas the combination forecasting method proposed in this paper is not only accurate, but also stable. As a result, it can provide technical reference for the safety management of power grid.

Description: Background: Driving fatigue affects the reaction ability of a driver. The aim of this research is to analyze the relationship between driving fatigue, physiological signals and driver’s reaction time. Methods: Twenty subjects were tested during driving. Data pertaining to reaction time and physiological signals including electroencephalograph (EEG) were collected from twenty simulation experiments. Grey correlation analysis was used to select the input variable of the classification model. A support vector machine was used to divide the mental state into three levels. The penalty factor for the model was optimized using a genetic algorithm. Results: The results show that α/β has the greatest correlation to reaction time. The classification results show an accuracy of 86%, a sensitivity of 87.5% and a specificity of 85.53%. The average increase of reaction time is 16.72% from alert state to fatigued state. Females have a faster decrease in reaction ability than males as driving fatigue accumulates. Elderly drivers have longer reaction times than the young. Conclusions: A grey correlation analysis can be used to improve the classification accuracy of the support vector machine (SVM) model. This paper provides basic research that online detection of fatigue can be performed using only a simple device, which is more comfortable for users.

Description: Fundamental understanding of micro-mechanical behaviors in bitumen, including phase separation, micro-friction, micro-abrasion, etc., can help the pavement engineers better understand the bitumen mechanical performances at macroscale. Recent researches show that the microstructure evolution in bitumen will directly affect its surface structure and micro-mechanical performance. In this study, the bitumen microstructure and micro-mechanical behaviors are studied using Atomic Force Microscopy (AFM) experiments, Phase Dynamics Theory and Molecular Dynamics (MD) Simulation. The AFM experiment results show that different phase-structure will occur at the surface of the bitumen samples under certain thermodynamic conditions at microscale. The phenomenon can be explained using the phase dynamics theory, where the effects of stability parameter and temperature on bitumen microstructure and micro-mechanical behavior are studied combined with MD Simulation. Simulation results show that the saturates phase, in contrast to the naphthene aromatics phase, plays a major role in bitumen micro-mechanical behavior. A high stress zone occurs at the interface between the saturates phase and the naphthene aromatics phase, which may form discontinuities that further affect the bitumen frictional performance.

Description: Materials, Vol. 11, Pages 1343: Thermodynamic Analysis of Ti3O5Nanoparticles Formed in Melt and Their Effects on Ferritic Steel Microstructure Materials doi: 10.3390/ma11081343 Authors: Yanlin Wang Meng Zhou Xiaolu Pang Xiaohua Chen Zidong Wang Alex A. Volinsky Hao Tang Based on the Wagner’s formalism combined with mass conservation, a thermodynamic analysis method has been developed previously. This method enables the calculation of the equilibrium matrix composition, precipitate composition and precipitate total molar fraction for TixOy(s) in molten metal, which can be determined at any appropriate temperature. In this present study, the Ti3O5 phase precipitation and the quantitative relationship between the addition of Ti, O and Ti3O5 in the molten steel were studied using the thermodynamic model. Using the combined multipoint dispersion supply method, electromagnetic stirring and well-dispersed 5-nm Ti3O5 nanoparticles were fabricated in the ferrite matrix of the as-cast high-strength steel with 0.05 wt % Ti—0.002 wt % O. The as-cast microstructure was improved by the homogeneously dispersed Ti3O5 nanoparticles through heterogeneous nucleation and grain refinement.