Current Issue [Vol. 11, No. 09] [September 2025]

This article examines the role of mechanization in the construction industry and its impact on reducing labor costs. The application of mechanization in high-tech countries is studied, including the integration of digital technologies such as Building Information Modeling (BIM), robotics, and 3D printing, as well as its adaptation in the context of developing countries. The influence of mechanization on productivity, quality, and safety in construction processes is analyzed. Examples of successful mechanization applications are provided, including the use of construction robots and autonomous equipment in the U.S., Japan, India, and other countries.
Keywords: Mechanization, construction, labor cost reduction, high-tech countries, developing countries, robotics, 3D printing, Building Information Modeling (BIM)

The article presents an analysis of architectural, network, and algorithmic factors that determine the quality of experience in hybrid cloud–edge video delivery systems, with a focus on their impact on delivery stability and QoE parameters. The study is conducted within an interdisciplinary paradigm combining distributed computing theory, network engineering, multimedia processing, and resource management in wireless networks. The methodological basis is a content analysis of peer-reviewed publications on low-latency bitrate adaptation, software-defined intercloud backbones with points of presence, GPU-accelerated encoding, and SDN control using the "Lyapunov drift-plus-penalty" function. Three interrelated groups of optimization mechanisms are identified and systematized: transport and routing (PoP-Overlay, jitter reduction, latency predictability), computational (multi-level caching, serverless GPU processing), and algorithmic (CMAF with chunked transfer, low-latency ABR strategies, content-aware scheduling). Three analytical tables are presented, including an intercontinental backbone comparison, HEVC accelerated encoding metrics, and comparative results of adaptive streaming algorithms. It is shown that the coordinated integration of transport, computational, and algorithmic solutions forms a predictable delivery loop that minimizes playback stalls and abrupt quality switches. The findings substantiate the need to design cloud–edge video systems based on QoE-oriented management models. The article will be of interest to researchers in multimedia networking, cloud and edge platform engineers, adaptive video streaming developers, and specialists in distributed architecture optimization.
Keywords: hybrid cloud–edge architecture, video content delivery, quality of experience, QoE-oriented management, low-latency bitrate adaptation, software-defined networking, points of presence, CMAF, edge caching, GPU-accelerated encoding.

The article presents an analysis of the applicability of system identification methods in cost estimation for renewable energy projects. The study is based on an interdisciplinary approach that combines engineering sciences, reliability theory, and applied energy economics. Particular attention is given to the comparison of Bayesian reliability models for wind turbines, predictive monitoring architectures, evolutionary algorithms for parametric identification in photovoltaics, and optimization strategies for the operation of energy storage systems. Modern methods are considered that enable the integration of technical data into financial and economic calculations, including forecasting of operating expenses, capital costs, and key investment metrics. The study identifies key interdependencies between the accuracy of engineering models and the reliability of investment forecasts, which is especially relevant under conditions of high market volatility. A comparative analysis has shown that the application of advanced algorithms reduces uncertainty in cost estimation and increases the reliability of payback calculations. Special attention is paid to the problems of data scarcity for certain technologies, the sensitivity of metaheuristic methods to noise, and the necessity of institutional support for the implementation of identification procedures in energy planning practices. The article proposes an original classification of applied models and substantiates the need for a comprehensive approach that combines engineering and economic data. This work will be useful for researchers in the field of renewable energy, cost estimation experts, design engineers, and investors focused on the development of sustainable energy strategies.
Keywords: system identification, cost estimating, renewable energy, wind power, photovoltaics, battery storage, Bayesian modeling, investment analysis.

This paper examines the role of digitalization as a key driver of territorial attractiveness through a comparative benchmarking analysis between the Casablanca-Settat region in Morocco and the Provence-Alpes-Côte d’Azur (PACA) region in France. The study highlights the initiatives, achievements, challenges, and future perspectives of both regions in their pursuit of digital transformation. Findings reveal that while Casablanca-Settat has made significant progress in fostering digital entrepreneurship, PACA demonstrates a more advanced digital ecosystem with stronger infrastructures, higher foreign investment attraction, and robust innovation policies. The paper provides recommendations to strengthen Casablanca-Settat’s digital competitiveness by leveraging best practices from PACA and addressing structural, regulatory, and technological barriers.
Keywords: Digitalization; Territorial Attractiveness; Casablanca-Settat; Provence-Alpes-Côte d’Azur; Benchmarking; Regional Competitiveness

Indian Textile Industry is the burgeoning sector, it contribute major portion to the nation economic progress, offer employment opportunity and total production. Moreover the corporate sector performances influenced by the Government policies and amendments like GST implementation and norms related to CSR activities. Besides, business environment of the each corporate sector growth depends on the stakeholders’ performance. It induces the researchers to analyze the Textile Industry sector CSR strategies to stakeholders before and after GST. The present study highlighted the CSR practices towards Shareholders, Employees and Consumers. Data were collected from 113 respondents, other available web sources and analyzed using the Weighted Average Method.
Keywords: Corporate Social Responsibility, Stakeholders, Textile Industry and Goods and Services Tax.

The article presents an analytical study of contemporary, including innovative, approaches to data recovery after formatting and deletion. The relevance is determined by changing volumes of digital information and the increasing complexity of storage architectures, which requires more efficient and universal methods for data regeneration. The scientific novelty lies in proposing a hybrid model that combines the use of file system metadata with signature-based content analysis, as well as adapting algorithms to complex configurations such as RAID arrays and SSDs with an active TRIM function. The study highlights key challenges — file fragmentation and the specifics of solid-state drives. Special attention is given to methods for automatic determination of RAID array parameters and algorithms for deep scanning (deep scan). The aim of the study is to systematize advanced practices and propose an integrated approach to recovery in cases of partial or complete loss of metadata. The methodological basis includes comparative analysis, systematization, and generalization; up-to-date scientific publications and the author’s practical experience were also used. The conclusion demonstrates the effectiveness of the proposed hybrid model. The material is intended for IT specialists, digital forensics experts, and software developers.
Keywords: Data recovery, disk formatting, file deletion, signature analysis, file carving, RAID arrays, SSD, TRIM, file systems, digital forensics.

This study explores the opportunities, challenges, and enabling conditions for adopting Artificial Intelligence (AI) tools in manufacturing engineering project management. Positioned within the Industry 4.0 context, AI applications offer transformative potential for enhancing operational efficiency, risk forecasting, and decision-making. Yet, adoption remains uneven due to technical, organizational, and ethical constraints. Drawing upon the Technology Acceptance Model (TAM), Technology–Organization–Environment (TOE) framework, and Unified Theory of Acceptance and Use of Technology (UTAUT), this research adopts a qualitative, exploratory design using semi-structured interviews with project managers, engineers, and IT specialists. The findings reveal significant opportunities for process automation, real-time data analytics, and quality improvement, while highlighting challenges related to legacy system integration, workforce resistance, financial constraints, and cyber security concerns. Enablers such as leadership commitment, technological readiness, employee training, and regulatory frameworks emerge as critical for successful AI integration. The study contributes to theory by offering a holistic socio-technical perspective on AI adoption and to practice by providing actionable guidance for managers and policymakers aiming to leverage AI for competitive advantage. Future research directions include cross-sectoral comparisons and quantitative modeling to examine causal relationships between adoption enablers, barriers, and performance outcomes.
Keywords: Project Management, Artificial Intelligence, Manufacturing Engineering, Technology Adoption, Industry 4.0

This paper presents the conceptualization and realization of a multifunctional intelligent electric wheelchair nursing bed, designed to address the limitations of existing products on the market, such as excessive size, single functionality, poor mobility, lack of toilet assistance, and insufficient leg rehabilitation training. The system integrates core functions including electric mobility, stepless adjustment of standing-sitting-lying postures, toilet assistance, and passive leg training, adopting a modular mechanical structure and intelligent control technologies (incorporating voice interaction and remote APP control). This design not only significantly improves users' life autonomy and comfort but also reduces the overall volume and manufacturing costs of the device, making it suitable for scenarios such as hospitals, nursing homes, and families. Ultimately, this work contributes to optimizing the elderly care support system and promoting the development of intelligent aging-friendly products.
Keywords: Intelligent Nursing Bed; Electric Wheelchair; Posture Stepless Adjustment; Toilet Assistance; Passive Leg Training