Journal of Mobile Computing, Communications & Mobile Networks
Volume 13, Issue 1 (2026)
Table of contents
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Ethical Challenges in Natural Language Processing: A Comparative Study of Solutions Across Multiple Domains
Abstract: This comparative analysis investigates the ethical challenges associated with natural language processing (NLP) by reviewing and synthesizing insights from ten influential and widely cited publications in the field. As NLP technologies are increasingly integrated into domains such as healthcare, finance, education, and governance, ethical concerns related to algorithmic bias, data privacy, fairness, accountability, and system transparency have become more prominent. This paper systematically examines how different researchers conceptualize and address …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 01–07 Read article
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An Investigative Study of Competition-Aware Incentive Mechanisms in Mobile Ad Hoc Networks
Abstract: Mobile ad hoc networks (MANETs) present a unique communication paradigm characterized by their decentralized and dynamic nature, where nodes rely on each other for packet forwarding and network maintenance. However, the inherent selfishness of individual nodes and resource constraints often leads to non-cooperative behaviors, significantly degrading network performance. This investigative study delves into the critical role of competition-aware incentive mechanisms in fostering sustainable cooperation within MANETs. Competition, a portmanteau of …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 08–15 Read article
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An Adaptive and Privacy-Aware Federated Learning Framework for Efficient and Secure Model Training Across Heterogeneous Datasets
Abstract: The problem of efficiency and privacy regarding heterogeneous data in modern distributed machine learning systems is a vital point that should be taken into account. The absence of IID data distribution, client heterogeneity, and privacy invasion during the aggregation model are the bane of conventional federated learning (FL) approaches to learning like FedAvg and FedProx. The paper proposes that the adaptive and privacy-aware FL framework (AFL-P) can be used to …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 16–25 Read article
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A Technical Blueprint for AI-Driven Localization in 6G Mobile Networks
Abstract: The advent of sixth-generation (6G) wireless systems promises unprecedented spatial resolution, ultra-low-latency, and pervasive connectivity, turning mobile localization from a peripheral service into a core enabler of immersive extended reality (XR), autonomous logistics, and digital twins. Yet, the sheer scale of dense terahertz (THz) deployments, the stochastic nature of reconfigurable intelligent surfaces (RIS), and the dynamic interference landscape render traditional model-based positioning techniques inadequate. This work investigates how artificial intelligence …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 26–34 Read article
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Privacy and Security Enhancement in Mobile Ad Hoc Network (MANET) Using Information Hiding Techniques Based on Man-In-The-Middle Attack: A Review
Abstract: The mobile ad hoc network (MANET) is widely spread throughout the entire world for quick communication. MANET is a type of ad hoc network with specific features of independent direct connections between devices. The current MANET network is rapidly used in wireless communication in fast and easy access terms, but MANET has many weaknesses in privacy and security, which makes information leakage in unprotected communication. So, goals are the most …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 35–50 Read article