Muhammad Ahmad^1,*, Rana Aamir Raza², Manuel Mazzara³, Salvatore Distefano⁴, Ali Kashif Bashir⁵, Adil Khan³, Muhammad Shahzad Sarfraz¹, Muhammad Umar Aftab¹

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1673-1692, 2021, DOI:10.32604/cmc.2021.016232

Abstract Smartphones have ubiquitously integrated into our home and work environments, however, users normally rely on explicit but inefficient identification processes in a controlled environment. Therefore, when a device is stolen, a thief can have access to the owner’s personal information and services against the stored passwords. As a result of this potential scenario, this work proposes an automatic legitimate user identification system based on gait biometrics extracted from user walking patterns captured by smartphone sensors. A set of preprocessing schemes are applied to calibrate noisy and invalid samples and augment the gait-induced time and frequency domain features, then further optimized… More >

Imran Ashraf, Soojung Hur, Yousaf Bin Zikria, Yongwan Park^*

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2597-2620, 2021, DOI:10.32604/cmc.2021.016214

Abstract Predominantly the localization accuracy of the magnetic field-based localization approaches is severed by two limiting factors: Smartphone heterogeneity and smaller data lengths. The use of multifarious smartphones cripples the performance of such approaches owing to the variability of the magnetic field data. In the same vein, smaller lengths of magnetic field data decrease the localization accuracy substantially. The current study proposes the use of multiple neural networks like deep neural network (DNN), long short term memory network (LSTM), and gated recurrent unit network (GRN) to perform indoor localization based on the embedded magnetic sensor of the smartphone. A voting scheme… More >

Mohammed Alshehri^1,*, Purushottam Sharma², Richa Sharma², Osama Alfarraj³

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2525-2538, 2021, DOI:10.32604/cmc.2021.012469

Abstract Sensors and physical activity evaluation are quite limited for motion-based commercial devices. Sometimes the accelerometer of the smartwatch is utilized; walking is investigated. The combination can perform better in terms of sensors and that can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated, also with biometric authentication. The result shows that using the different computing techniques in phones and watch for biometric can provide a suitable output based on the mentioned activities. This indicates that the high feasibility and results… More >

Chunping Lu^1,#, Liye Zou^2,#, Benjamin Becker³, Mark D. Griffiths⁴, Qian Yu², Si-Tong Chen⁵, Zsolt Demetrovics⁶, Can Jiao⁷, Xinli Chi⁷, Aiguo Chen⁸, Albert Yeung⁹, Shijie Liu¹⁰, Yanjie Zhang^2,11,*

International Journal of Mental Health Promotion, Vol.22, No.4, pp. 271-282, 2020, DOI:10.32604/IJMHP.2020.014419

Abstract Purpose: The purpose of the present study was to compare the effectiveness of mind-body exercise (ME) and cognitive behavioral therapy (CBT) on addiction level and psychological well-being among college students with problematic smartphone use (PSU). Methods: A 12-week randomized controlled study was carried out at a university in central China. A total of 95 PSU college students who met the inclusion criteria were randomly assigned to a ME group (ME, n = 31), CBT group (CBT, n = 30), or control group (CG, n = 34). Both ME intervention and CBT, twice per week for 90 min per session, lasting… More >

Jaafar Hallal^1,2,3,*, Mohammad Hammoud^2,3, Mahmoud Fakih^2,3,4, Ali Hallal^2,3

Sound & Vibration, Vol.54, No.4, pp. 225-236, 2020, DOI:10.32604/sv.2020.011513

Abstract The vibrations behavior analysis is an essential step in the mechanical design process. Several methods such as analytical modelling, numerical analysis and experimental measurements can be used for this purpose. However, the numerical or analytical models should be validated through experimental measurements, usually expensive. This paper introduces an inexpensive smartphone as an accurate, non-intrusive vibrations’ behavior measurement device. An experimental measurement procedure based on the video processing method is presented. This procedure allows the measurement of the natural frequencies and the mode shapes of a vibrating structure, simply by using a smartphone built-in camera. The experimental results are compared to… More >

Ye Zhang^∗

Computer Systems Science and Engineering, Vol.35, No.3, pp. 207-214, 2020, DOI:10.32604/csse.2020.35.207

Abstract Considering the issue of Chinese college students that are not interested in learning English and have a lack of enthusiasm for learning overall, a feedback and motivation application based on cloud computing to teach English vocabulary to Chinese college students has been developed. The mobile application can collect and analyze the problems that users encounter in the process of learning English through the cloud server in real-time, and advise on how to resolve these problems. The feedback system also allows users to access this data. In the case of uploading to designated teachers, teachers can adjust their teaching methods and… More >

Juan C. Quiroz^a, Amit Banerjee^b, Sergiu M. Dascalu^c, Sian Lun Lau^a

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 785-793, 2018, DOI:10.1080/10798587.2017.1342400

Abstract We use the public Human Activity Recognition Using Smartphones (HARUS) data-set to investigate and identify the most informative features for determining the physical activity performed by a user based on smartphone accelerometer and gyroscope data. The HARUS data-set includes 561 time domain and frequency domain features extracted from sensor readings collected from a smartphone carried by 30 users while performing specific activities. We compare the performance of a decision tree, support vector machines, Naive Bayes, multilayer perceptron, and bagging. We report the various classification performances of these algorithms for subject independent cases. Our results show that bagging and the multilayer… More >

Hsing‐Chung Chen^1,2, Shyi‐Shiun Kuo^1,3

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 217-228, 2019, DOI:10.31209/2018.100000057

Abstract Nowadays, more and more smartphones communicate to each other’s by using some popular Next Generation Instant Messaging (NGIM) applications (Apps) which are based on the blockchain (BC) technologies, such as XChat, via IPv4/IPv6 dual stack network environments. Owing to XChat addresses are soon to be implemented as stealth addresses, any DoS attack activated form malicious XChat node will be treated as a kind of DDoS attack. Therefore, the huge NGIM usages with stealth addresses in IPv4/IPv6 dual stack mobile networks, mobile devices will suffer the Distributed Denial of Service (DDoS) attack from Internet. The probing method is deployed in this… More >

M. Vilasini^{1, *}, P. Ramamoorthy²

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1445-1472, 2020, DOI:10.32604/cmc.2020.08857

Abstract Leaf species identification leads to multitude of societal applications. There is enormous research in the lines of plant identification using pattern recognition. With the help of robust algorithms for leaf identification, rural medicine has the potential to reappear as like the previous decades. This paper discusses CNN based approaches for Indian leaf species identification from white background using smartphones. Variations of CNN models over the features like traditional shape, texture, color and venation apart from the other miniature features of uniformity of edge patterns, leaf tip, margin and other statistical features are explored for efficient leaf classification. More >

Yu Sun^1,2,*, Qiyuan Gao³, Xiaofan Du³, Zhao Gu³

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1365-1375, 2019, DOI:10.32604/cmc.2019.06294

Abstract In this advanced age, when smart phones are the norm, people utilize social networking, online shopping, and even private information storage through smart phones. As a result, identity authentication has become the most critical security activity in this period of the intelligent craze. By analyzing the shortcomings of the existing authentication methods, this paper proposes an identity authentication method based on the behavior of smartphone users. Firstly, the sensor data and touch-screen data of the smart phone users are collected through android programming. Secondly, the eigenvalues of this data are extracted and sent to the server. Thirdly, the Support Vector… More >