In recent years, the concept of the Internet of Things has been introduced. Information, communication, and network technology can be integrated, so that the unmanned aerial vehicle (UAV) from consumer leisure and entertainment toys can be utilized in high value commercial, agricultural, and defense field applications, and become a killer product. In this paper, a traceable and privacy-preserving authentication is proposed to integrate the elliptic curve cryptography (ECC), digital signature, hash function, and other cryptography mechanisms for UAV application. For sensitive areas, players must obtain flight approval from the ground control station before they can control the UAV in these areas. The traditional cryptography services such as integrity, confidentiality, anonymity, availability, privacy, non-repudiation, defense against DoS (Denial-of-Service) attack, and spoofing attack can be ensured. The feasibility of mutual authentication was proved by BAN logic. In addition, the computation cost and the communication cost of the proposed scheme were analyzed. The proposed scheme provides a novel application field.

With the rapid development of the social economy, our lives are flooded with all kinds of counterfeit products. The public’s attitude of greedy for petty and cheap has encouraged unscrupulous manufacturers to take advantage of the opportunity to provide low-cost counterfeit products, suppress the profits of legitimate manufacturers, and also make the public lose confidence in the quality of the products. At present, the most widely used anti-counterfeiting system based on QR codes on the market. However, existing traceability systems are still mostly built in a centralized manner, and the central agency provides trust guarantees, but the public still has great doubts about the credibility of the central agency. The introduction of blockchain technology can perfectly solve the lack of existing architecture and the environment. In this research, we propose an IoT-based traceable drug anti-counterfeiting management system, a comprehensive plan from drug research and development, certification, production to sales. The framework we propose meets the requirements of information security for data integrity, resistance to replay attacks, irreversible information, and non-repudiation.

In recent years, with the rapid levels of economic development, there have been more and more problems in property inheritance and distribution. In today’s society, people still have many taboos when writing a will. Writing a will not only involves various laws and regulations but also costs a lot of money and time, which can be daunting. However, with the development of the Internet, blockchain technology has gradually been applied to many applications. Blockchain technology uses consensus algorithms to ensure consistency and records transaction information in blocks to ensure the effectiveness of transactions. In this paper, we use the cryptography mechanism to propose an online will system based on blockchain and smart contract technology. The architecture considers effectiveness and cost reduction. By combining this with blockchain technology, will assets are saved in blocks, which provides comprehensive will security and non-tamperable security protection. In addition, combined with a smart contract, it realizes the method of automatic property distribution. At the same time, this mechanism also proposes an arbitration solution when there are disputes over wills, and ensures the integrity of data, public verifiability, unforgeability, nonrepudiation, irreversibility of information, and the ability to resist counterfeiting attacks.

To optimize the power and economic performance of battery electric passenger vehicles, an 8.5-m-long battery electric passenger vehicle was selected as the research subject. The simulated-annealing particle-swarm-optimization (SAPSO) algorithm was applied to optimize the two-speed gearbox and transmission ratio of the vehicle. With the opening of the accelerator pedal and speed as variables, a comprehensive gear shift schedule that considered both the power and economic performance was established. The comprehensive gear shift schedule curve was defined in the model built in the ADVISOR software. The transmission ratio was jointly optimized using the ADVISOR and ISIGHT software, and then the ADVISOR simulation software was used to analyze the economic and dynamic performances corresponding to the optimized transmission ratio. Finally, we compared the power and economic performances of the vehicle before and after transmission ratio optimization, the results of which showed that after the optimization, the maximum speed, climbing gradient, and 0–50 km/h acceleration time of the vehicle were greatly improved, and the driving range was slightly shortened. This enabled performance advantages of the battery electric passenger vehicle by balancing the power and economic performances of the vehicle.

To effectively predict the life of high voltage dc power relay, the authors design the structure of the relay to extending its life. The contact failure mechanism of relay products is analyzed by observing the appearance of several contact failures. The electromagnetic-thermal field coupling model is established and the state of heat flow and distribution of temperature increase between electrical and thermal coupling contacts are analyzed through simulations and experiments. An adaptive neural network control system is established to conduct sample training, obtain the best stiffness coefficient of the main spring, and optimize the design of the main spring structure composed of composite springs. The action voltage, release voltage, contact resistance, contact pressure, action time, and release time as characteristic parameters, and the relative error, correlation degree, variance ratio, and small error probability of each characteristic parameter, are calculated. The precision grade index of contact resistance and action time is defined as level 1. The two characteristic parameters are selected as the prediction variables to establish the life-prediction model based on gray theory. The relative error between the predicted and test life is 5.31%–5.6%, indicating that the life-prediction model has high accuracy. The test results show that the combined main spring structure can extend the life of a relay by 18.15%.