Traditional traffic light system, which works based on fixed cycle can be a main reason for traffic jam, due to lack of adaptation to road conditions. Traffic jam has a bad impact on drivers and road users due to the time delay it causes for road users to reach their destinations. This delay can cause a life threat in case of emergency vehicles, such as ambulance vehicles and police cars. One key solution to solve traffic jam on intersections is the dynamic traffic lights, where traffic light operation adapts based on the intersection traffic conditions. Since few of researches projects in the literature interested in solving traffic jam problem for emergency vehicles, the contribution of this paper is to introduces a novel approach to operate traffic light system. The new approach consists of two algorithms which are pure operation mode and hybrid operation mode. These operation modes aim to reduce the waiting time of emergency vehicles on traffic intersections. They assume that there is a smart infrastructure system uses Internet of Things (IoT) that can detect emergency vehicles arrival to an intersection. The smart infrastructure system switches traffic light operation from fixed cycle mode to dynamic mode. The dynamic mode manages traffic lights at intersections to reduce the waiting time of emergency vehicles. The paper presents a simulation of the proposed algorithms, highlights their advantages. In order to evaluate the efficiency of the new technique, we compared our approach with Wen algorithm in the literature and the Traditional traffic light system. Our evaluation study indicated that the proposed algorithms outperformed Wen technique and the Traditional system under different traffic scenarios

Code readability and software complexity are considered essential components of software quality. They significantly impact software metrics, such as reusability and maintenance. The maintainability process consumes a high percentage of the software lifecycle cost, which is considered a very costly phase and should be given more focus and attention. For this reason, the importance of code readability and software complexity is addressed by considering the most time-consuming component in all software maintenance activities. This paper empirically studies the relationship between code readability and software complexity using various readability and complexity metrics and machine learning algorithms. The results are derived from an analysis dataset containing roughly 12,180 Java files, 25 readability features, and several complexity metric variables. Our study empirically shows how these two attributes affect each other. The code readability affects software complexity with 90.15% effectiveness using a decision tree classifier. In addition, the impact of software complexity on the readability of code using the decision tree classifier has a 90.01% prediction accuracy.

The swift evolution of information technology and growing connectivity in critical applications have elevated cybersecurity, protecting and certifying software and designs against rising cyber threats. For example, software and hardware have become highly susceptible to various threats, like reverse engineering, cloning, tampering, and IP piracy. While various techniques exist to enhance software and hardware security, including encryption, native code, and secure server-side execution, obfuscation emerges as a preeminent and cost-efficient solution to address these challenges. Obfuscation purposely converts software and hardware to improve complexity for probable adversaries, targeting obscure realization operations while preserving safety and functionality. Former research has commonly engaged features of obfuscation, deobfuscation, and obfuscation detection approaches. A novel departure from conventional research methodologies, this revolutionary comprehensive article reviews these approaches in depth. It explicates the correlations and dynamics among them. Furthermore, it conducts a meticulous comparative analysis, evaluating obfuscation techniques across parameters such as the methodology, testing procedures, efficacy, associated drawbacks, market applicability, and prospects for future enhancement. This review aims to assist organizations in wisely electing obfuscation techniques for firm protection against threats and enhances the strategic choice of deobfuscation and obfuscation detection techniques to recognize vulnerabilities in software and hardware products. This empowerment permits organizations to proficiently treat security risks, guaranteeing secure software and hardware solutions, and improving user satisfaction for maximized profitability.