Machine Learning in Sensors and Imaging

Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens

Digital Communication System with High Security and High Immunity

Today, security issues are increased due to huge data transmissions over communication media such as mobile phones, TV cables, online games, Wi-Fi and satellite transmission etc. for uses such as medical, military or entertainment. This creates a challenge for government and commercial companies to keep these data transmissions secure. Traditional secure ciphers, either block ciphers such as Advanced Encryption Standard (AES) or stream ciphers, are not fast or completely secure. However, the unique properties of a chaotic system, such as structure complexity, deterministic dynamics, random output response and extreme sensitivity to the initial condition, make it motivating for researchers in the field of communication system security. These properties establish an increased relationship between chaos and cryptography that create strong and fast cipher compared to conventional algorithms, which are weak and slow ciphers. Additionally, chaotic synchronisation has sparked many studies on the application of chaos in communication security, for example, the chaotic synchronisation between two different systems in which the transmitter (master system) is driving the receiver (slave system) by its output signal. For this reason, it is essential to design a secure communication system for data transmission in noisy environments that robust to different types of attacks (such as a brute force attack). In this thesis, a digital communication system with high immunity and security, based on a Lorenz stream cipher chaotic signal, has been perfectly applied. A new cryptosystem approach based on Lorenz chaotic systems was designed for secure data transmission. The system uses a stream cipher, in which the encryption key varies continuously in a chaotic manner. Furthermore, one or more of the parameters of the Lorenz generator is controlled by an auxiliary chaotic generator for increased security. In this thesis, the two Lorenz chaotic systems are called the Main Lorenz Generator and the Auxiliary Lorenz Generator. The system was designed using the SIMULINK tool. The system performance in the presence of noise was tested, and the simulation results are provided. Then, the clock-recovery technique is presented, with real-time results of the clock recovery. The receiver demonstrated its ability to recover and lock the clock successfully. Furthermore, the technique for synchronisation between two separate FPGA boards (transmitter and receiver) is detailed, in which the master system transmits specific data to trigger a slave system in order to run synchronously. The real-time results are provided, which show the achieved synchronisation. The receiver was able to recover user data without error, and the real-time results are listed. The randomness test (NIST) results of the Lorenz chaotic signals are also given. Finally, the security analysis determined the system to have a high degree of security compared to other communication systems

Digital Communication System with High Security and High Immunity

Today, security issues are increased due to huge data transmissions over communication media such as mobile phones, TV cables, online games, Wi-Fi and satellite transmission etc. for uses such as medical, military or entertainment. This creates a challenge for government and commercial companies to keep these data transmissions secure. Traditional secure ciphers, either block ciphers such as Advanced Encryption Standard (AES) or stream ciphers, are not fast or completely secure. However, the unique properties of a chaotic system, such as structure complexity, deterministic dynamics, random output response and extreme sensitivity to the initial condition, make it motivating for researchers in the field of communication system security. These properties establish an increased relationship between chaos and cryptography that create strong and fast cipher compared to conventional algorithms, which are weak and slow ciphers. Additionally, chaotic synchronisation has sparked many studies on the application of chaos in communication security, for example, the chaotic synchronisation between two different systems in which the transmitter (master system) is driving the receiver (slave system) by its output signal. For this reason, it is essential to design a secure communication system for data transmission in noisy environments that robust to different types of attacks (such as a brute force attack). In this thesis, a digital communication system with high immunity and security, based on a Lorenz stream cipher chaotic signal, has been perfectly applied. A new cryptosystem approach based on Lorenz chaotic systems was designed for secure data transmission. The system uses a stream cipher, in which the encryption key varies continuously in a chaotic manner. Furthermore, one or more of the parameters of the Lorenz generator is controlled by an auxiliary chaotic generator for increased security. In this thesis, the two Lorenz chaotic systems are called the Main Lorenz Generator and the Auxiliary Lorenz Generator. The system was designed using the SIMULINK tool. The system performance in the presence of noise was tested, and the simulation results are provided. Then, the clock-recovery technique is presented, with real-time results of the clock recovery. The receiver demonstrated its ability to recover and lock the clock successfully. Furthermore, the technique for synchronisation between two separate FPGA boards (transmitter and receiver) is detailed, in which the master system transmits specific data to trigger a slave system in order to run synchronously. The real-time results are provided, which show the achieved synchronisation. The receiver was able to recover user data without error, and the real-time results are listed. The randomness test (NIST) results of the Lorenz chaotic signals are also given. Finally, the security analysis determined the system to have a high degree of security compared to other communication systems