This paper presents generate tool path and getting G-codes for complex shapes depending on mathematical equations without using the package programs that using linear interpolation. Circular interpolation (G02, G03) was used to generate tool path and this need to define the tool radius and radius of curvature in addition to define the cutting direction if it is clockwise or counter clockwise. In addition many other factors had been considered in the machining process of the proposed surface to find the best tool path and G-code. Side step, feed rate and diameter had been studied as machining factors affecting tool path generation process. The impact of the machining parameters on the Material Removal Rate was determined by the use of analysis of variance (ANOVA) that detect more influence for side step (75%).From this study, it has been learned that less side step (0.6) mm and feed speed (2000) mm/min and high value for diameter (12) mm is better tool path to be used in machining operations to give high Material Removal Rate. This study would help engineer and machinist to select the best tool path for their product.

1,2,4 Department of Botany, Maulana Azad College of Arts, Science and Commerce, P.O. Box No-27, Aurangabad (MS), India. 3 Yeshwant Mahavidyalaya, Nanded (MS), India. Key words : Fungal Endophytes, Indian Laburnum, Bioactive compounds.

1 Zhytomyr Polytechnic State University, 103 Chudnivsyka Str., Zhytomyr, 10005, Ukraine 2 Institute for Digitalisation of Education of the NAES of Ukraine, 9 M. Berlynskoho Str., Kyiv, 04060, Ukraine 3 Kryvyi Rih State Pedagogical University, 54 Gagarin Ave., Kryvyi Rih, 50086, Ukraine

The exponential expansion of national digital ecosystems and government-wide cloud adoption has introduced unprecedented attack surfaces vulnerable to advanced, persistent, and state-sponsored cyber threats. Traditional signature-based and heuristic security approaches fall short in addressing the complexity, scalability, and zero-day risks associated with national-scale cloud networks. This study presents a multi-layered, AI-enhanced threat detection framework designed for sovereign cloud environments that span critical infrastructure sectors, including healthcare, defense, and public administration. The proposed architecture combines federated anomaly detection, distributed behavioral analytics, and hybrid threat intelligence fusion. At its core, it leverages transformer-based deep learning models and graph-based unsupervised learning to detect polymorphic malware, lateral movement, and privilege escalation across dynamic, containerized environments. The system incorporates edge-AI agents for decentralized inference, enabling real-time detection with minimal latency, while central orchestrators aggregate alerts for high-confidence triage. The framework also addresses adversarial machine learning risks and integrates continuous learning loops for evolving threat landscapes. This paper synthesizes empirical insights from three national deployments: a zero-trust e-governance platform in Estonia, a secure cloud migration strategy for national defense systems in South Africa, and a pandemic-era scalable health cloud infrastructure in Brazil. These case studies demonstrate AI’s effectiveness in reducing mean time to detect (MTTD) and mean time to respond (MTTR) while enhancing situational awareness across federated public clouds. Key challenges discussed include model interpretability, regulatory fragmentation across jurisdictions, and the ethical implications of algorithmic surveillance. The paper concludes with policy recommendations for harmonizing national AI security standards, investing in explainable AI, and fostering public-private cloud security alliances.

. Wireless Touch Networks (WTN) have become increasingly important with the emergence of the Internet of Things (IoT) and are regarded as a class of self-organizing networks. This article presents an overview of the construction principles, routing protocols, quality of service parameters, traffic models, and characteristics of WTN. The article also explores the application of dynamic routing protocols for constructing a self-organizing network of autonomous IoT systems. Known dynamic routing protocols for mobile radio networks are reviewed and the advantages and disadvantages of proactive and reactive approaches are discussed.

2 Information Technology University, Arfa Software Technology Park, Ferozepur Road, Lahore, Pakistan Abstract. Edge computing is an extension of cloud computing where physical servers are deployed closer to the users in order to reduce latency. Edge data centers face the challenge of serving a continuously increasing number of applications with a reduced capacity compared to traditional data center. This paper introduces ImpalaE, an agent based on Deep Reinforcement Learning that aims at optimizing the resource usage in edge data centers. First, it proposes modeling the problem as a Markov Decision Process, with two optimization objectives: reducing the number of physical servers used and maximize number of applications placed in the data center. Second, it introduces an agent based on Proximal Policy Optimization, for finding the optimal consolidation policy, and an asynchronous architecture with multiple workers-shared learner that enables for faster convergence, even with reduced amount of data. We show the potential in a simulated edge data center scenario with different VM sizes based on Microsoft Azure real traces, considering CPU, memory, disk and network requirements. Experiments show that ImpalaE effectively increases the number of VMs that can be placed per episode and that it quickly converges to an optimal policy. 1. Keywords: edge computing, policy gradient, reinforcement learning, efficient resource management

2 S.P. Korolev Zhytomyr Military Institute, 22 Mira Ave., Zhytomyr, 10004, Ukraine 3 University of Bielsko-Biala, Willowa 2, 43-300 Bielsko-Biała, Poland Abstract. This article presents a detailed analysis of the Internet of Things (IoT) systems and the methods used to protect them. The article highlights the potential of edge computing to minimize traffic transmission and the decentralization of decision-making systems to enhance security. The analysis examines attacks on IoT system components and provides protection recommendations. Furthermore, the article explores the prospects of information protection in IoT systems.

2 G.E. Pukhov Institute for Modelling in Energy Engineering of NAS of Ukraine, 15 General Naumova Str., Kyiv, 03164, Ukraine Abstract. This paper presents a new approach for solving the problem of dispatching task flows with known complexity in GRID systems that have inalienable resources with determined performance. The proposed method is simple to implement and is compared with the commonly used FCFS method. An example of a practical problem that can be solved using this method is provided. Keywords: GRID systems, dispatching task flows, inalienable resources, performance, complexity, FCFS method, practical problem, task scheduling