Study of Third-Grade Fluid under the Fuzzy Environment with Couette and Poiseuille FlowsRead the full article
Mathematical Problems in Engineering is a broad-based journal publishing results of rigorous engineering research across all disciplines, carried out using mathematical tools.
Chief Editor, Professor Guangming Xie, is currently a full professor of dynamics and control with the College of Engineering, Peking University. His research interests include complex system dynamics and control and intelligent and biomimetic robots.
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Strategic Alliance Pattern Evaluation Model for Taiwan’s Machine Tool Industry: A Hierarchical DEMATEL Method
The worldwide machine tool market is anticipated to reach a value of USD 68.9 billion by 2021, from USD 65.6 billion in 2020. This projection is based on the progressive production drop within the car industry, which is the largest customer of machine devices, and supply chain disruption. The machine tool industry in Taiwan faces a severe challenge and has been unobtrusively experiencing an inner reshuffling and innovative transformation. The developing strategic alliances reflect a basic endeavor by numerous firms to improve their specialized capabilities. This study applied the DEMATEL, a suitable method for gathering group knowledge to form a structural model and visualize the casual relationship between subsystems through a casual diagram, revealing that the causal relationships between measurement criteria and the proposed model can provide a viable assessment of the alliance with satisfactory criteria that fit the decision-makers requirements, especially when the assessment criteria are various and interrelated. Financial resources were the strongest factor within the strategic behavior dimension (D1), whereas the minimize manufacturing cost was the foremost basic determinant in the cost perspective (D2). The specialists also demonstrated that obtaining dominant technology was a determinative component within organizational learning (D3). This paper offers proposals for government authorities to plan a machine tools industry strategy for Taiwan and for companies to formulate business directions for long-run advancement.
Existence of Fixed Points in Fuzzy Strong b-Metric Spaces
In the present research, modern fuzzy technique is used to generalize some conventional and latest results. The objective of this paper is to construct and prove some fixed-point results in complete fuzzy strong b-metric space. Fuzzy strong b-metric (sb-metric) spaces have very useful properties such as openness of open balls whereas it is not held in general for b-metric and fuzzy b-metric spaces. Due to its properties, we have worked in these spaces. In this way, we have generalized some well-known fixed-point theorems in fuzzy version. In addition, some interesting examples are constructed to illustrate our results.
Development of Machine Learning Methods in Hybrid Energy Storage Systems in Electric Vehicles
The hybrid energy storage systems are a practical tool to solve the issues in single energy storage systems in terms of specific power supply and high specific energy. These systems are especially applicable in electric and hybrid vehicles. Applying a dynamic and coherent strategy plays a key role in managing a hybrid energy storage system. The data obtained while driving and information collected from energy storage systems can be used to analyze the performance of the provided energy management method. Most existing energy management models follow predetermined rules that are unsuitable for vehicles moving in different modes and conditions. Therefore, it is so advantageous to provide an energy management system that can learn from the environment and the driving cycle and send the needed data to a control system for optimal management. In this research, the machine learning method and its application in increasing the efficiency of a hybrid energy storage management system are applied. In this regard, the energy management system is designed based on machine learning methods so that the system can learn to take the necessary actions in different situations directly and without the use of predicted select and run the predefined rules. The advantage of this method is accurate and effective control with high efficiency through direct interaction with the environment around the system. The numerical results show that the proposed machine learning method can achieve the least mean square error in all strategies.
A Low-Cost and Ultralight Unmanned Aerial Vehicle-Borne Multicamera Imaging System Based on Smartphones
Newly developed oblique photogrammetry (OP) techniques based on unmanned aerial vehicles (UAVs) equipped with multicamera imaging systems are widely used in many fields. Smartphones cost less than the cameras commonly used in the existing UAV OP system, providing high-resolution images from a built-in imaging sensor. In this paper, we design and implement a novel low-cost and ultralight UAV OP system based on smartphones. Firstly, five digital cameras and their accessories detached from the smartphones are then fitted into a very small device to synchronously shoot images at five different perspective angles. An independent automatic capture control system is also developed to realize this function. The proposed smartphone-based multicamera imaging system is then mounted on a modified version of an existing lightweight UAV platform to form a UAV OP system. Three typical application examples are then considered to evaluate the performance of this system through practical experiments. Our results indicate that both horizontal and vertical location accuracy of the generated 3D models in all three test applications achieve centimeter-level accuracy with respect to different ground sampling distances (GSDs) of 1.2 cm, 2.3 cm, and 3.1 cm. The accuracy of the two types of vector maps derived from the corresponding 3D models also meet the requirements set by the surveying and mapping standards. The textural quality reflected by the 3D models and digital ortho maps (DOMs) are also distinguishable and clearly represent the actual color of different ground objects. Our experimental results confirm the quality and accuracy of our system. Although flight efficiency and the accuracy of our designed UAV OP system are lower than that of the commercial versions, it provides several unique features including very low-cost, ultralightweight, and significantly easier operation and maintenance.
Survey on Reverse-Engineering Tools for Android Mobile Devices
With the presence of the Internet and the frequent use of mobile devices to send several transactions that involve personal and sensitive information, it becomes of great importance to consider the security aspects of mobile devices. And with the increasing use of mobile applications that are utilized for several purposes such as healthcare or banking, those applications have become an easy and attractive target for attackers who want to get access to mobile devices and obtain users’ sensitive information. Developing a secure application is very important; otherwise, attackers can easily exploit vulnerabilities in mobile applications which lead to serious security issues such as information leakage or injecting applications with malicious programs to access user data. In this paper, we survey the literature on application security on mobile devices, specifically mobile devices running on the Android platform, and exhibit security threats in the Android system. In addition, we study many reverse-engineering tools that are utilized to exploit vulnerabilities in applications. We demonstrate several reverse-engineering tools in terms of methodology, security holes that can be exploited, and how to use these tools to help in developing more secure applications.
Backward Trajectory and Multifractal Analysis of Air Pollution in Zhengzhou Region of China
With the continuous promotion of industrialization and urbanization, China's environmental pollution is becoming increasingly serious, which has caused considerable damage to the natural balance. Air pollution seriously harms people's physical and mental health, the ecological environment, and the social sustainable development of society. In this study, the backward trajectory model and multifractal methods were adopted to analyze air pollution in Zhengzhou. The backward trajectory analysis showed that most clusters of air pollution were from southern Hebei, eastern Shandong, and mid-western Henan, which were then transported to Zhengzhou. For the PSCF and CWT analyses, we selected four representative cities to explore how close the air pollution of Zhengzhou is to other areas on the basis of air polluted concentration. The results of several multifractal methods indicated that multifractality existed in the AQI time series of Zhengzhou and cross-correlations between Zhengzhou and each of the four cities. The widths of multifractal spectra showed that the air pollution in Zhengzhou was closest to that in Jinan, followed by Shijiazhuang, Zibo, and Luoyang. The CDFA analysis showed that carbon monoxide (CO), nitrogen dioxide (NO2), and inhalable particulate matter (PM10) had important influences on air pollution in Zhengzhou. These findings offer a useful reference for air pollution sources and their potential contributions in Zhengzhou, which can support policy makers in environmental governance and in achieving sustainable urban development.