In engineering applications, high-precision tracking control is crucial for robotic manipulators to successfully complete complex operational tasks. To achieve this goal, this study proposes an adaptive tunable predefined-time backstepping control strategy for uncertain robotic manipulators with external disturbances and model uncertainties. By establishing a novel practical predefined-time stability criterion, a tunable predefined-time backstepping controller is systematically presented, allowing the upper bound of tracking error settling time to be precisely determined by adjusting only one control parameter. To accurately address lumped uncertainty, two updating laws are designed: a fuzz... More >

Smart Environment is rapidly growing with the inclusion of Artificial Intelligence of Things (AIoT) when it connects to future communication and social media networks. Security and privacy are significant challenges, including data integrity, account hijacking, cybersecurity, and cyberbullying. To mitigate these challenges, Social Media 3.0 is utilized with advanced emerging technologies such as Blockchain, Federated Learning (FL), and others and offers solutions in existing research. This article comprehensively reviews and proposes Next-Generation Technologies for Secure Future Communication Service Scenario for Smart Environment and Social-Media 3.0. We discuss existing attacks with their... More >

Humanoid robots play a significant role in numerous fields, where efficient and intuitive control inputs are essential, particularly in applications requiring remote operation. In this paper, we investigate the potential advantages of inertial sensors as a key component for generating command signals in humanoid robot control systems. The objective is to accurately detect user motion through inertial sensing, thereby enabling precise control commands. Finger gestures are first captured as signals from the inertial sensor, and movement commands are extracted through filtering and recognition processes. These commands are then translated into corresponding robot actions based on the sensor’s... More >

Collective motion has been a pivotal area of research, especially due to its substantial importance in Unmanned Aerial Vehicle (UAV) systems for several purposes, including path planning, formation control, and trajectory tracking. UAVs significantly enhance coordination, flexibility, and operational efficiency in practical applications such as search-and-rescue operations, environmental monitoring, and smart city construction. Notwithstanding the progress in UAV technology, significant problems persist, especially in attaining dependable and effective coordination in intricate, dynamic, and unexpected settings. This study offers a comprehensive examination of the fundamental principles, mod... More >

The efficient extraction and fusion of video features to accurately identify complex and similar actions has consistently remained a significant research endeavor in the field of video action recognition. While adept at feature extraction, prevailing methodologies for video action recognition frequently exhibit suboptimal performance in the context of complex scenes and similar actions. This shortcoming arises primarily from their reliance on uni-dimensional feature extraction, thereby overlooking the interrelations among features and the significance of multi-dimensional fusion. To address this issue, this paper introduces an innovative framework predicated upon a soft correlation strategy... More >

As we know, the world is rapidly moving towards 5G and B5G technology to achieve high data rates, massive communication capacity, connectivity, and low latency. 5G offers a latency of less than 1 ms and extremely high data volume compared to previous technologies. The main challenge is the complex nature of 5G network deployment, especially at high frequencies (3–300 GHz) on a university campus with varied building structures. In this paper, we will discuss a scenario for deploying 5G at the Mirpur University of Science and Technology (MUST) in Mirpur, Pakistan so that telecom operators and vendors who wish to deploy a 5G network on the campus in the future can draw on our research finding... More >

The proliferation of Recommender Systems (RecSys), driven by their expanding application domains, explosive data growth, and exponential advancements in computing capabilities, has cultivated a dynamic and evolving research landscape. This paper comprehensively reviews the foundational concepts, methodologies, and challenges associated with RecSys from technological and social scientific lenses. Initially, it categorizes personalized RecSys technical solutions into five paradigms: collaborative filtering, scenario-aware, knowledge & data co-driven approaches, large language models, and hybrid models integrating diverse data sources. Subsequently, the paper analyses the key challenges and fut... More >

This review paper offers a thorough assessment of three-dimensional object recognition methods, an essential element in the perception frameworks of autonomous systems. This analysis emphasises the integration of LiDAR and camera sensors, providing a distinctive contrast with more economical alternatives like camera-only or camera-Radar combinations. This study objectively evaluates performance and practical implementation issues, such as cost and operational efficiency, thereby elucidating the limitations of existing systems and proposing avenues for further research. The insights provided render it a significant asset for enhancing 3D object recognition and autonomy in intelligent systems. More >