Yazar "Hamood, M.A." seçeneğine göre listele

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    Emotion Recognition of Humans using modern technology of AI: A Survey
    (Institute of Electrical and Electronics Engineers Inc., 2023) Alheeti, A.A.M.; Salih, M.M.M.; Mohammed, A.H.; Hamood, M.A.; Khudhair, N.R.; Shakir, A.T.
    This comprehensive investigation and evaluation of the subject matter of emotion recognition is presented, focusing on the broader implications for society at large. The study utilizes a thorough analysis of scholarly literature and practical observations to establish a theoretical framework that facilitates comprehension of the topic under investigation. The findings have considerable implications for future investigations and pragmatic applications. Emotion recognition holds immense importance in diverse domains such as human-computer interaction and healthcare. The analysis of techniques used for emotional recognition includes facial expression assessment, speech patterns analysis, physiological signal interpretation, music perception, and written expression evaluation. The study presents a comprehensive overview of research methodologies commonly used in emotion recognition, discussing datasets, feature extraction techniques, and classification algorithms. The analysis of challenges and limitations pertaining to emotion recognition systems, including privacy concerns, is also discussed. Performance evaluation is analyzed through various methods, including machine assessment and self-report. The significance of continued investigation within the domains encompassing data integration across diverse modalities, the creation of robust classification algorithms, and the exploration of the intricate connection between the brain and affective states is underscored. © 2023 IEEE.
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    On the Performance of mm-Wave Massive MIMO Multi-Carrier Modulation Technique for Vehicle-to-Vehicle Communication
    (Institute of Electrical and Electronics Engineers Inc., 2022) Al-Heety, A.T.; Mohammed, A.H.; Hamood, M.A.; Abdullah, S.N.; Khalaf, Q.M.; Alkhateeb, I.I.
    It is expected that the 5G network will cover more eventualities than what present mobile communications systems can handle. One of the primary anticipated future services is vehicle-to-vehicle (V2V) communications, which have demanding requirements at millimeter wave band frequencies. Waveforms that are spectrally confined and scalable are required to make the greatest use of the frequency resources which are currently available without interfering with nearby nodes. A common method used to reduce out-ofband emission is the filtering of OFDM. The use of OFDM results in a high Out of Band and a high Peak to Average Power Ratio (PAPR). This boosts the chances of hiring additional multicarrier waveform varieties to improve the Orthogonal frequency-division multiplexing responses. A collection of data can be transmitted simultaneously over several narrow-band subcarriers using Multi-Carrier Modulation (MCM) methods. MCM was used in this investigation in four different ways to start examining the performance of a single-user preceded mm-Wave massive MIMO wireless advancement systems: orthogonal frequency-division multiplexing, simplified frequency division multiplexing, filter bank multicarrier, and universal filtered multicarrier. These multicarrier modulation techniques rely on symbol and subcarrier filtering to reduce the effect of cyclic prefixes on the bit error rate (BER) and throughput of OFDM. Additionally, the impacts of phase noise are tested, and it is demonstrated that QAM-FBMC is phase noise resilient. © 2022 IEEE.