Suitability Evaluation of Cultivated Land Reserved Resources in Arid Areas Based on Regional Water Balance

With rapid socioeconomic and population growth, high-quality arable land resources are decreasing daily, especially in arid areas, which makes arable land reserve resources an important way to supplement arable land. How to accurately evaluate cultivated land reserve resources is of great significance to socioeconomic development and sustainable land use in arid areas. Therefore, this study selected Hangjin Banner as a typical area and calculated the regional maximum available irrigation water based on the principle of regional water balance. Then, the "irrigation area check algorithm" was used to evaluate the amount of cultivated land reserve resources, and policy recommendations were proposed for the development and utilization of cultivated land resources. The results showed that Hangjin Banner had no cultivated land reserve resources under the current irrigation method and had cultivated land reserve resources under the efficient water-saving irrigation method, but only in the southern zone during normal and partially abundant water years. Therefore, we believe that arid areas should adhere to the "set land by water" principle, the allocation of water resources should be optimized, and cultivated land resources with high quality should be utilized based on the actual regional conditions.

     

A non-invasive learning branch to capture leaf-image attention for tree species classification

Multimedia Tools and Applications - Tree species classification is a necessary and challenging task for both multimedia technique and forestry engineering. Continuous developments in multimedia and...     

Special Issue on Artificial Intelligence and Technology: Trend,Challenges, and Opportunities

Mobile Networks and Applications -     

Finite-time adaptive fuzzy control for a class of output constrained nonlinear systems with dead-zone

The article investigates the finite-time adaptive fuzzy control for a class of nonlinear systems with output constraint and input dead-zone. First, by skillfully combining the barrier Lyapunov function, backstepping design method, and finite-time control theory, a novel adaptive state-feedback tracking controller is constructed, and the output constraint of the nonlinear system is not violated. Second, the fuzzy logic system is used to approximate unknown function in the nonlinear system. Third, the finite-time command filter is introduced to avoid the problem of “complexity explosion” caused by repeated differentiations of the virtual control signal in conventional backstepping control schemes. Meanwhile, a new saturation function is added in the compensating signal for filter error to improve control accuracy. Finally, based on Lyapunov stability analysis, all the signals of the closed-loop are proved to be semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood region of the origin in a finite time. A simulation example is presented to demonstrate the effectiveness for the proposed control scheme.     

COVID-19 crisis impact on the stability between parties in crowdfunding and crowdsourcing

This research reviews challenges in building sustainable relationships between the parties involved in the crowdfunding and crowdsourcing projects, which are running in extreme situations, such as the COVID-19 pandemic. This study aims to solve problems that generate the crowdsourcing concerns and to find better alternatives to increase trust for crowdfunding among donors, as this impacts their strategic sustainability in the conditions of turbulence and COVID-induced financial crisis. It was found that factors influence donor decisions in different ways, yet the common tendency for donor activity is non-monotonicity. Future development in the field of sustainable relationships should focus on creating a donor classification system.

     

Visual privacy attacks and defenses in deep learning: a survey

The concerns on visual privacy have been increasingly raised along with the dramatic growth in image and video capture and sharing. Meanwhile, with the recent breakthrough in deep learning technologies, visual data can now be easily gathered and processed to infer sensitive information. Therefore, visual privacy in the context of deep learning is now an important and challenging topic. However, there has been no systematic study on this topic to date. In this survey, we discuss algorithms of visual privacy attacks and the corresponding defense mechanisms in deep learning. We analyze the privacy issues in both visual data and visual deep learning systems. We show that deep learning can be used as a powerful privacy attack tool as well as preservation techniques with great potential. We also point out the possible direction and suggestions for future work. By thoroughly investigating the relationship of visual privacy and deep learning, this article sheds insights on incorporating privacy requirements in the deep learning era.

     

Failure Prediction of Municipal Water Pipes Using Machine Learning Algorithms

Pipe failure prediction has become a crucial demand of operators in daily operation and asset management due to the increase in operation risks of water distribution networks. In this paper, two machine learning algorithms, namely, random forest (RF) and logistic regression (LR) algorithms are employed for pipe failure prediction. RF algorithm consists of a group of decision trees that predicts pipe failure independently and makes the final decision by voting together. For the LR algorithm, the mapping relationship between existing data and decision variables is expressed by the logistic function. Then, the prediction is made by comparing the conditional probability with the fixed threshold value. The proposed algorithms are illustrated using an actual water distribution network in China. Results indicate that the RF algorithm performs better than the LR algorithm in terms of accuracy, recall, and area under the receiver operating characteristic curve. The effects of seven characteristics on pipe failures are analyzed, and diameter and length are identified as the top two influential factors.

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Homogeneous reinforcement as a strategy for the efficient preparation of high-strength,insulating and high heat-resistant PBO composite paper

Journal of Materials Science - Poly(p-phenylene benzobisoxazole) (PBO) fibre-based specialty paper has become a promising candidate for high-performance insulating materials due to the remarkable...     

Engineering A-site cation deficiency into LaCoO3 thin sheets for improved microwave absorption performance

Journal of Materials Science - Rationally designing microwave absorption materials with highly efficient and tunable bandwidth is in great demand but remains a huge challenge. In this study,...