Journal of Computers, Mechanical and Management

Editorial Comments

2025-09-22T17:21:10+03:00

Advancing Sustainable Transportation

2025-03-25T17:07:15+03:00

Electric vehicles (EVs) have emerged as a central pathway for decarbonizing transport, yet sustained adoption depends on coordinated progress in technology, infrastructure, and policy. This mini-review synthesizes recent evidence on environmental performance, market growth, and enabling systems for large-scale electrification. First, it consolidates technical and life-cycle findings that indicate lower greenhouse gas emissions and higher energy-conversion efficiency for EVs relative to internal combustion engine vehicles, with advantages strengthening as grids decarbonize. Second, it examines charging infrastructure typologies and deployment patterns, highlighting the complementary roles of Level 2 and DC fast charging and the need for reliability, interoperability, and grid-aware siting. Third, it analyzes policy instruments—financial incentives, regulatory mandates, and planning frameworks—and compares national approaches to illustrate how instrument mixes shape outcomes. Persistent challenges include upfront affordability, uneven access to charging, grid integration under peak demand, and battery material sustainability. The review identifies future directions in managed and bidirectional charging, data-driven planning, AI-enabled operations, and circular economy practices for batteries, alongside equity-focused governance. Collectively, these insights outline a coherent agenda for scaling EV adoption while aligning climate mitigation with resilient and inclusive mobility.

The Role of Edge Computing in Enhancing the Performance of Smart City Applications

2025-03-25T13:31:51+03:00

The rapid proliferation of smart city initiatives has generated vast amounts of data from heterogeneous sources, including sensors, Internet of Things (IoT) devices, and mobile applications. Traditional cloud infrastructures face high latency, bandwidth constraints, and scalability issues in handling such massive real-time data streams. Edge computing addresses these limitations by decentralizing data processing and bringing computation closer to the data source. This paradigm enables faster response, lower latency, optimized bandwidth use, and improved resilience. For applications such as traffic management, public safety, energy optimization, and environmental monitoring, edge computing significantly enhances efficiency and scalability. This paper investigates the role of edge computing in smart city applications, discusses benefits and challenges, and presents performance models focusing on latency reduction, bandwidth optimization, and energy efficiency. The study highlights how edge computing can be integrated into sustainable smart city frameworks to enhance urban living standards.

A Blockchain-Based Framework for Secure Communication in Smart IoT Systems

2025-03-26T16:06:55+03:00

Blockchain technology has emerged as a promising paradigm for addressing the inherent vulnerabilities of Internet of Things (IoT) networks. Conventional IoT systems rely on centralized architectures that are prone to single points of failure, data breaches, and unauthorized access. This paper presents a blockchain-enabled secure communication framework for smart IoT systems that integrates symmetric encryption, distributed ledger validation, and smart-contract–driven access control. The proposed model is formalized through mathematical definitions of encryption, hashing, and contract execution, and validated using simulation tools such as NS-3 and Ethereum-based test environments. Comparative results demonstrate that the framework significantly improves communication security, data integrity, and resistance to cyberattacks while reducing latency and energy consumption relative to traditional models. The findings suggest that blockchain integration provides a scalable, resilient, and efficient foundation for trustworthy IoT communication in smart environments.

Secure AR-enabled Smart Manufacturing Framework Integrating Machine Learning and Blockchain

2025-03-26T15:54:13+03:00

Augmented reality (AR) is increasingly adopted in Industry~4.0 to enhance operational efficiency and workplace safety. Yet, most implementations examine productivity and safety in isolation and seldom integrate AR with complementary technologies. This study proposes a secure AR-enabled framework for smart manufacturing that incorporates machine learning for predictive optimization and blockchain for tamper-proof data integrity. The framework is formalized through an algorithmic workflow, a six-layer system architecture, and mathematical models quantifying productivity, safety, economic viability, and user engagement. A simulation-based evaluation with 50 participants across five representative manufacturing tasks indicated measurable improvements: 25% faster task completion, 15% error reduction, 30% downtime reduction, 40% safety improvement, and 35% shorter training duration. While these results provide quantitative evidence of AR’s dual role in enhancing efficiency and safety, the findings are limited to controlled simulations and do not fully capture the variability of industrial environments. Future validation in live manufacturing contexts is therefore necessary to establish practical applicability.

Activation Energy and Dielectric Properties of Epoxy Nanocomposites with Carbon Nanotubes and Carbon Black

2025-09-21T16:40:32+03:00

This study presents a comparative analysis of multiwall carbon nanotube–epoxy (MWCNT–EP) and carbon black–epoxy (CB–EP) nanocomposites to evaluate the influence of filler concentration and frequency on activation energy and dielectric properties. Activation energy was obtained from the slopes of Arrhenius plots (ln sigma vs. 1/T) at 0.5, 5, and 10 kHz. Both composites showed higher activation energy at 0.5 kHz due to long-range charge-carrier hopping, whereas higher frequencies promoted localized transport between adjacent defect sites. Increasing filler concentration further reduced activation energy, reflecting saturation of dangling bonds, lower density of states, and reduced domain boundary potential. Dielectric analysis revealed that CB–EP composites consistently possessed higher dielectric constants than MWCNT–EP composites at equivalent filler loadings, owing to CB's smaller particle size and greater surface area. For both composites, the dielectric constant decreased with increasing frequency, consistent with interfacial polarization effects. These findings clarify how carbonaceous fillers influence the electrical and dielectric behavior of epoxy nanocomposites.