Biometrics is an interesting study due to the incredible progress in security. Electrocardiogram (ECG) signal analysis is an active research area for diagnoses. Various techniques have been proposed... Show More

Biometrics is an interesting study due to the incredible progress in security. Electrocardiogram (ECG) signal analysis is an active research area for diagnoses. Various techniques have been proposed in human identification system based on ECG. This work investigates in ECG as a biometric trait which based on uniqueness represented by physiological and geometrical of ECG signal of person.In this paper, a proposed non-fiducial identification system is presented with comparative study using Radial Basis Functions (RBF) neural network, Back Propagation (BP) neural network and Support Vector Machine (SVM) as classification methods. The Discrete Wavelet Transform method is applied to extract features from the ECG signal. The experimental results show that the proposed scheme achieves high identification rate compared to the existing techniques. Furthermore, the two classifiers RBF and BP are integrated to achieve higher rate of human identification.

Securing vehicles, especially against theft, has become a significant concern. Smart antitheft solutions have emerged to provide better protection. However, most existing smart vehicle antitheft... Show More

Securing vehicles, especially against theft, has become a significant concern. Smart antitheft solutions have emerged to provide better protection. However, most existing smart vehicle antitheft solutions use (GSM) and (GPS) technologies to track stolen vehicles and these technologies are not sufficiently efficient in tracking vehicles in real-time. Hence, there is a need to optimise solutions to incorporate new technologies such as Internet of Things (IoT), Fog Computing (FC), and Face Recognition (FR) technologies. This paper introduces the new concept of Fog Computing to existing tracking systems and presents the design and the development of the Internet of Things (IoT) Cloud-based vehicle anti-theft system to pinpoint the exact location of the stolen vehicle in real-time. The proposed system extends the existing tracking systems to include advanced features influenced by advanced computing technologies such as Fog, Cloud, IoT and FR. Furthermore, it sheds light on the benefits of using FC combined with Cloud Computing (CC) to provide a more accurate and reliable tracking system.

Ballots are often hold for fair decisions such as party theme selecting, however, the existing traditional ballot has some problems involving amount of human resources, cost of places, equipment... Show More

Ballots are often hold for fair decisions such as party theme selecting, however, the existing traditional ballot has some problems involving amount of human resources, cost of places, equipment, time and traffic, and repeated procedures. In order to solve the issues aforementioned, a ballot blockchain system is designed and implemented based on the smart contract of Ethereum. It is designed on the core blockchain technologies of the decentralized ledger technology, using a secure hash algorithm, anonymous user, incorruptible data, and adopting a public blockchain. The ballot blockchain system is implemented based on the MetaMask verification and the Remix interface development environment. The smart contract plays the role of the decision-maker for controlling ballot activities instead of numerous human tasks. All ballot transactions are recorded in the ballot blockchain permanently when the ballot completed. The aim of the ballot blockchain system is to achieve a fair, less time-consuming, secured, and transparent environment.