The automotive industry plays key role in global gas emission, contributing to the greenhouse effect. This paper explores the importance of SCADA (Supervisory Control and Data Acquisition) in optimizing industrial processes within automotive manufacturing and engine management. By real-time monitoring, optimization, control of industrial processes and data collection, SCADA contribute to reduce energy consumption and emissions of harmful pollutants such as carbon dioxide and nitrogen oxides. This paper analyzes technical architecture, specific applications in diesel engine control, and environmental benefits that are supported by relevant case studies and empirical data. SCADA systems may offer considerable advantages, but there are also challenges such as cybersecurity vulnerabilities, integration complexity and implementation costs that are also discussed.

Climate change represents one of the serious challenges of modern times, with profound consequences for ecosystems, the economy and everyday life. In this context, Artificial Intelligence (AI) is increasingly recognized as a powerful tool used to recognize and manage complex climate processes. This paper explores concrete applications of AI in the fight against climate change, analyzing how these systems are used in energy, agriculture, risk management. Special attention is paid to ethical challenges such as bias, transparency and energy consumption, which accompany the application and development of AI technologies.

The Goal of this paper is to review software quality in agile environments as well as software quality monitoring in agile working environments. An overview of ISO standards for different quality aspects has also been reviewed, as it proposes the international standardization scope for quality evaluation. Besides functional and non-functional aspects of software quality during the software development lifecycle, psychological factors were also considered.

The growth of the Internet of Things (IoT) devices has introduced significant security challenges due to energy efficiency and limited hardware resources. This research paper presents a preliminary review of security techniques applied in IoT systems, focusing on mechanisms for authentication, encryption, and intrusion detection as well as lightweight cryptographic approaches, and device-level security capabilities like Secure Boot (SB) and Trusted Platform Module (TPM). This review highlights current trends and common vulnerabilities, aiming to provide an improved understanding of IoT security strategies and challenges.

Onboarding in companies is an important process in the integration of new employees, especially in the aspect of Information Technology (IT) sector. This paper uses analytic autoethnography with the aim of presenting the experience of the first author during his onboarding process in the position of Integration Specialist. Autoethnography allows researchers to combine personal reflection and theory-based analysis to gain a deeper understanding of the emotional and cognitive challenges experienced by new hires. Using paper notes, digital notes, internal communication, and mentor communications, we construct narrative episodes that trace emotional and cognitive transitions. The contribution of this paper is reflected in the fact that an authentic approach to informal learning processes and identity formation on the businesspath is presented. Also, this paper indicates practical guidelines for improving the onboarding model in companies that want to develop a structured and empathetic approachto the integration of new employees during the process.

In this paper, we identify security threats in a microservice-based application using the STRIDE framework. The study addresses the question of how the architecture of STRIDE procedure, which is aligned with Data Flow Diagram (DFD) trust boundaries, can support early threat identification in microservice architecture. STRIDE methodology is used for categorizing security threats based on six criteria: identity spoofing, data falsification, denial of action or responsibility, information disclosure, denial of service, and privilege escalation. In addition, STRIDE enables assessment of the severity and status of the identified threats. The research relies on the creation of microservice architectural model created in draw.io and DFD of application that was constructed with Microsoft Threat Modeling Tool. Applied to the case study system, the procedure identified 52 threats that were dominated by Spoofing (29%) and Denial of Service (25%), followed by Elevation of Privilege (21%), Repudiation (17%), and Information Disclosure and Tampering (4% each). The paper presents a simple STRIDE procedure that can be reused for other microservice applications. It includes four steps: prepare an architectural diagram, create a DFD with trust boundaries, run STRIDE analysis in a certain tool, and summarize results in a matrix of threats per microservice to support prioritization of mitigation measures.