Artificial intelligence (AI) is not a new term;its beginnings go back to the beginnings of the fifth decade in the year 1955. Since the emergence of artificial intelligence, it has been in the process of continuous de...
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Data centers are essential components of the modern digital world. They provide the necessary resources and infrastructure to enable access to online services and applications, enabling individuals and organizations t...
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Cloud Computing (CC) offers a diverse range of services along with huge data storage across a network. CC has collaborated with varied emerging technologies like IoT because of its numerous advantages. Despite CC'...
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Voice Assistants software agents to comprehend spoken language and respond with synthesized voices, voice assistants have revolutionized human-computer interaction. An application programming interface (API) called Bu...
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Detection of DeepFakes presents formidable challenges primarily due to adversarial attacks that can dramatically reduce model accuracy. Current detection models are reasonably effective in real scenarios;however, thes...
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Non-orthogonal multiple access (NOMA), multiple-input multiple-output (MIMO) and mobile edge computing (MEC) are prominent technologies to meet high data rate demand in the sixth generation (6G) communication networks...
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Non-orthogonal multiple access (NOMA), multiple-input multiple-output (MIMO) and mobile edge computing (MEC) are prominent technologies to meet high data rate demand in the sixth generation (6G) communication networks. In this paper, we aim to minimize the transmission delay in the MIMO-MEC in order to improve the spectral efficiency, energy efficiency, and data rate of MEC offloading. Dinkelbach transform and generalized singular value decomposition (GSVD) method are used to solve the delay minimization problem. Analytical results are provided to evaluate the performance of the proposed Hybrid-NOMA-MIMO-MEC system. Simulation results reveal that the H-NOMA-MIMO-MEC system can achieve better delay performance and lower energy consumption compared to OMA.
Edge detection plays an important role in various fields by identifying object boundaries and supporting advanced image analysis, such as segmentation, recognition, and tracking. Many edge detection algorithms, such a...
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Electroencephalography (EEG) signals are often utilized to study cognitive processes and brain diseases. The non-stationary and non-linear nature of EEG signals makes their analysis difficult. A deep learning framewor...
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The use of complex fuzzy systems to predict human thinking is an area of active research. These systems are based on fuzzy logic, which is an approach to computing based on approximation and imprecision. Fuzzy logic h...
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With each passing generation, the human language is getting rich vocabulary usually effected by regional, domain specific and emotional dialects. Natural Language Processing (NLP) deals with training machines the huma...
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