The main goal of this study is to design and develop a half-bridge inverter architecture specifically for high-voltage power supply applications. An effective, small, and affordable system that converts direct current (DC) to alternating current(AC) can be built, thanks to the IR2151 chip’s dependable characteristics and performance. To get the desired output voltage, the transformer first increases the voltage and then the voltage is increased with a voltage-doubling rectifier (VDR) circuit. The study emphasizes how crucial it is to choose components carefully and simulate the circuit design and implementation process to guarantee dependable performance. The experimental results validate... More >

In recent years, vehicular ad hoc networks (VANETs) have faced growing security concerns, particularly from Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks. These attacks flood the network with malicious traffic, disrupting services and compromising resource availability. While various techniques have been proposed to address these threats, this study presents an optimized framework leveraging advanced deep-learning models for improved detection accuracy. The proposed Intrusion Detection System (IDS) employs Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and Deep Belief Networks (DBN) alongside robust feature selection techniques, Random Projecti... More >

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 >