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Most of the traditional athletic performance dynamic change prediction platforms use gray correlation and neural networks to establish prediction methods, and the prediction results are inaccurate and time-consuming. Therefore, the construction of a mobile prediction platform for dynamic changes in athletic performance based on screening factors is proposed to improve the accuracy of its prediction results and shorten the prediction time. On the basis of hardware, the main body of students is determined, the athletic performance data of students is collected by the physical education management system of colleges and universities, and the missing data is filled by the criterion function of K-average algorithm. The KNN algorithm is used to make decisions to obtain the most representative predictors of athletic performance data, and the characteristics of students' athletic performance are extracted. The effective factors are selected according to the tenfold cross-validation fold MSE minimum principle of SVM, and the mandatory screening based on SVM is used to assign weights to each reserved factor. According to the weighted result of the obtained factors, the influencing factors of athletic performance are analyzed, and the weighting process is completed for the factors, and the athletic performance prediction is realized by using support vector machine. In the platform established in this paper, the students' 1000-m running results are predicted. The simulation results show that, compared with the traditional platform, the constructed platform has higher prediction accuracy and takes less time. [ABSTRACT FROM AUTHOR]

To solve the problem of low recognition accuracy and long recognition time in conventional methods for digital moving image feature recognition, a method for digital image feature recognition on mobile platforms based on machine learning is proposed. The support vector machine method is used to cluster the dataset, and then the weight reconstruction method is used to reduce the dimension of digital moving image data. The reduced dimension of the digital moving image is embedded in the coordinates to obtain the reduced dimension of the image data information and complete the feature recognition of the digital moving image. The simulation results show that the recognition accuracy of this method in recognizing features of moving digital images is basically stable at more than 95% and the running time is 0.42s. The recognition effect of the proposed method is good, the recognition efficiency is high, and it has some practical application value. [ABSTRACT FROM AUTHOR]

The Android operating system is the most popular mobile operating system resulting in a great number of applications being developed for the platform. This makes them vulnerable to security threats such as social engineering, shoulder surfing and Malware. Therefore, Android devices require a secure authentication scheme in order to control access to the device. This paper briefly discusses the mobile security threats, the authentication protocols and Android Security. Then the paper presents an analysis of some of the authentication schemes that are used in mobile devices and some of the threats and technical issues faced. Authentication schemes discussed include password/pin, pattern based authentication, fingerprint recognition, facial recognition, vocal recognition and iris based authentication. In discussing the various authentication methods, it was observed that while biometric based authentication schemes offered the greatest level of security, there was always a trade-off between computational complexity and ease of use/implementation/cost that ensured that more traditional authentication schemes, while not as secure as biometric schemes, are still widely used in mobile devices. [ABSTRACT FROM AUTHOR]

The number of mobile applications downloaded recently from Google stores increase steadily. It is believed that mobile applications market revenues will grow fast and receive more attention from software developers. Even though, hardware technologies and operating systems have made a big contribution to improve the battery capacity, power consumption is one of the most important and crucial non-functional properties of mobile applications. Many approaches have been dedicated for analyzing and optimizing the power consumption at different levels. This paper proposes a method for analyzing energy leaks of Android application at the design phase. First, it introduces a formalization of an event-based power consumption model. After that, the paper presents a method to translate this model to Event-B notations. Based on the target model, it is able to check if the application leads to energy leaks or violates the power consumption constraints based on formal proofs. Finally, the motivating examples are shown for the illustration purpose. [ABSTRACT FROM AUTHOR]

Intrusion Detection System (IDS) is crucial to protect smartphones from imminent security breaches and ensure user privacy. Android is the most popular mobile Operating System (OS), holding above 85% market share. The traffic generated by smartphones is expected to exceed the one generated by personal computers by 2021. Consequently, this prevalent mobile OS will stay one of the most attractive targets for potential attacks on fifth generation mobile networks (5G). Although Android malware detection has received considerable attention, offered solutions mostly rely on performing resource intensive analysis on a server, assuming a continuous connection between the device and the server, or on employing supervised Machine Learning (ML) algorithms for profiling the malware's behaviour, which essentially require a training dataset consisting of thousands of examples from both benign and malicious profiles. However, in practice, collecting malicious examples is tedious since it entails infecting the device and collecting thousands of samples in order to characterise the malware's behaviour and the labelling has to be done manually. In this paper, we propose a novel Host-based IDS (HIDS) incorporating statistical and semi-supervised ML algorithms. The advantage of our proposed IDS is two folds. First, it is wholly autonomous and runs on the mobile device, without needing any connection to a server. Second, it requires only benign examples for tuning, with potentially a few malicious ones. The evaluation results show that the proposed IDS achieves a very promising accuracy of above 0.9983, reaching up to 1. [ABSTRACT FROM AUTHOR]

Humanfall detection has attracted broad attentions as sensors and mobile devices are increasingly adopted in real-life scenarios such as smart homes. The complexity of activities in home environments pose severe challenges to the fall detection research with respect to the detection accuracy. We propose a collaborative detection platform that combines two subsystems: a threshold-based fall detection subsystem using mobile phones and a support vector machine (SVM)-based fall detection subsystem using Kinects. Both subsystems have their respective confidence models and the platform detects falls by fusing the data of both subsystems using two methods: the logical rules-based and D-S evidence fusion theory-based methods. We have validated the two confidence models based on mobile phone and Kinect, which achieve the accuracy of 84.17% and 97.08%, respectively. Our collaborative fall detection approach achieves the best accuracy of 100%. [ABSTRACT FROM AUTHOR]

On going demands to connect massive amounts of the heterogeneous mobile devices and data traffics make the mobile operators in desperate need to find energy-efficient solutions for coverage and real-time services. Accordingly, mobile femtocells are found to be a promising solution in the coming few decades. This paper presents energy-based analysis for mobile femtocells in Ultra-Large Scale (ULS) applications such as the smart-grid. The potential reduction of the consumed energy and service interruption due to mobility and multihop communication effects are considered as well as various performance metrics such as throughput, availability, and delay. In that sense the smart-grid is modeled as a green wireless communication system for traffic offloading while considering mobility of the femtocell base-station (FBS) as well as the FBS cut-offs for energy-saving aspects. A typical scenario, called e-Mobility, is considered as a case study where a set of mobile femtocells are utilized inside a single macrocell in order to achieve optimized utilities’ usage. Numerical results achieved from the proposed smart-grid model have been verified and validated via extensive simulation results while considering typical operational conditions/parameters. [ABSTRACT FROM AUTHOR]

Thanks to the availability of various mobile applications, lots of users shift from desktop environments, e.g., PCs and laptops, to mobile devices, e.g., smartphones and tablets. However, there are still some desktop applications without counterparts on mobile devices, such as some integrated development environments (e.g., eclipse) and automatic industry control systems. In this paper, we propose Modeap, a platform-independent mobile cloud service that can push all desktop applications developed for various operating systems from cloud servers to mobile devices. Modeap follows a design principle of complete detachment and regeneration of desktop user interface, i.e., the essential graphical primitives of the original desktop applications will be intercepted and then translated into standard web-based graphical primitives such that the interactions between users and remote cloud applications become possible via mobile web browsers. In this way, all desktop applications built upon the same set of graphical primitives can be used on mobile devices in great flexibility without installing any new software. We have developed a proof-of-concept prototype that provides Windows applications from cloud server to mobile web browsers. The results of extensive experiments show that the proposed framework can achieve our design goals with low latency and bandwidth consumption. [ABSTRACT FROM AUTHOR]

The selected papers focus on different topics covered under the umbrella of Smart City concept such as: Lightweight security mechanisms for IoT; Blockchain-based IoT security; Physical-layer security; Security and privacy for mobile devices; Cybersecurity for Cyber Physical Production Systems (CPPSs); among others. In the third article with the title "A Physical-Layer Key Distribution Mechanism for IoT Networks", the authors focus on constrained IoT networks and propose physical layer security as a lightweight approach for key distribution mechanisms. Although physical layer security has been widely studied as a lightweight approach to transmit confidential information, authors in this article propose physical layer security for symmetric key agreement between multiple entities. [Extracted from the article]