Hand gesture recognition is a burgeoning area of study with wide-ranging applications, including human–computer interaction, sign language translation, and virtual reality control. In this work, we introduce an innov...
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With the development of communication systems, modulation methods are becoming more and more diverse. Among them, quadrature spatial modulation(QSM) is considered as one method with less capacity and high efficiency. ...
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With the development of communication systems, modulation methods are becoming more and more diverse. Among them, quadrature spatial modulation(QSM) is considered as one method with less capacity and high efficiency. In QSM, the traditional signal detection methods sometimes are unable to meet the actual requirement of low complexity of the system. Therefore, this paper proposes a signal detection scheme for QSM systems using deep learning to solve the complexity problem. Results from the simulations show that the bit error rate performance of the proposed deep learning-based detector is better than that of the zero-forcing(ZF) and minimum mean square error(MMSE) detectors, and similar to the maximum likelihood(ML) detector. Moreover, the proposed method requires less processing time than ZF, MMSE,and ML.
The Internet of Things (IoT) and edge-assisted networking infrastructures are capable of bringing data processing and accessibility services locally at the respective edge rather than at a centralized module. These in...
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The Internet of Things (IoT) and edge-assisted networking infrastructures are capable of bringing data processing and accessibility services locally at the respective edge rather than at a centralized module. These infrastructures are very effective in providing a fast response to the respective queries of the requesting modules, but their distributed nature has introduced other problems such as security and privacy. To address these problems, various security-assisted communication mechanisms have been developed to safeguard every active module, i.e., devices and edges, from every possible vulnerability in the IoT. However, these methodologies have neglected one of the critical issues, which is the prediction of fraudulent devices, i.e., adversaries, preferably as early as possible in the IoT. In this paper, a hybrid communication mechanism is presented where the Hidden Markov Model (HMM) predicts the legitimacy of the requesting device (both source and destination), and the Advanced Encryption Standard (AES) safeguards the reliability of the transmitted data over a shared communication medium, preferably through a secret shared key, i.e., , and timestamp information. A device becomes trusted if it has passed both evaluation levels, i.e., HMM and message decryption, within a stipulated time interval. The proposed hybrid, along with existing state-of-the-art approaches, has been simulated in the realistic environment of the IoT to verify the security measures. These evaluations were carried out in the presence of intruders capable of launching various attacks simultaneously, such as man-in-the-middle, device impersonations, and masquerading attacks. Moreover, the proposed approach has been proven to be more effective than existing state-of-the-art approaches due to its exceptional performance in communication, processing, and storage overheads, i.e., 13%, 19%, and 16%, respectively. Finally, the proposed hybrid approach is pruned against well-known security attacks
Cloud computing is a new super computing paradigm, which has greatly changed the way users store and process data. Meanwhile, with the prosperity of cloud computing, there are many hidden dangers in data privacy and s...
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The management of plastic waste in our ecosystem represents a significant environmental issue, necessitating effective sorting and categorization to facilitate efficient recycling practices. This study introduces a me...
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Prostate cancer comes under SDG 3—Good Health and Well-Being is a global health concern affecting millions of men, demanding precise analysis for early detection and effective treatment. This project pioneers, innova...
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This paper presents our system for generating counter-speech (CN) in response to hate speech (HS), developed for the COLING 2025 shared task. We employ lightweight transformer-based models, DistilBART and T5-small, op...
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In today’s world, epileptic seizures which is a chronic neurological disorder causes rapid disruptions to a person’s lifestyle. It is very common and the number of cases that involve patients that remain uncurable e...
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The process of modifying digital images has been made significantly easier by the availability of several image editing software. However, in a variety of contexts, including journalism, judicial processes, and histor...
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Credit card fraud has become a major problem in the financial industry, causing huge financial losses for financial institutions and cardholders. Because internet banking and e-commerce are being used more often there...
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