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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Algorithmic trading using neural network models has gained significant attention in predicting stock and commodity price fluctuations and understanding their dynamics. Deep learning techniques have shown significant r...
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Emotion recognition using biological brain signals needs to be reliable to attain effective signal processing and feature extraction techniques. The impact of emotions in interpretations, conversations, and decision-m...
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Emotion recognition using biological brain signals needs to be reliable to attain effective signal processing and feature extraction techniques. The impact of emotions in interpretations, conversations, and decision-making, has made automatic emotion recognition and examination of a significant feature in the field of psychiatric disease treatment and cure. The problem arises from the limited spatial resolution of EEG recorders. Predetermined quantities of electroencephalography (EEG) channels are used by existing algorithms, which combine several methods to extract significant data. The major intention of this study was to focus on enhancing the efficiency of recognizing emotions using signals from the brain through an experimental, adaptive selective channel selection approach that recognizes that brain function shows distinctive behaviors that vary from one individual to another individual and from one state of emotions to another. We apply a Bernoulli–Laplace-based Bayesian model to map each emotion from the scalp senses to brain sources to resolve this issue of emotion mapping. The standard low-resolution electromagnetic tomography (sLORETA) technique is employed to instantiate the source signals. We employed a progressive graph convolutional neural network (PG-CNN) to identify the sources of the suggested localization model and the emotional EEG as the main graph nodes. In this study, the proposed framework uses a PG-CNN adjacency matrix to express the connectivity between the EEG source signals and the matrix. Research on an EEG dataset of parents of an ASD (autism spectrum disorder) child has been utilized to investigate the ways of parenting of the child's mother and father. We engage with identifying the personality of parental behaviors when regulating the child and supervising his or her daily activities. These recorded datasets incorporated by the proposed method identify five emotions from brain source modeling, which significantly improves the accurac
This study presents a new data stream learning framework for class imbalance data sources that can improve classification. This framework uses a genetic algorithm to select the best features and perform fast resamplin...
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technology helps producers to collect enormous amounts of customer-product interaction (CPI) data. From the collected CPI data, the importance of the customers and the products can be measured. This study focuses on f...
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Bolted connections are integral components in steel structures and often are vulnerable to loosening due to cyclic loading and fatigue. Detecting bolt loosening in early stages is critical to prevent sudden catastroph...
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Influence maximization (IM) is the task of selecting the most influential nodes in the network. IM achieves the goal of spreading information, influencing behaviour, or promoting sales of products. Existing studies in...
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GPT is widely recognized as one of the most versatile and powerful large language models, excelling across diverse domains. However, its significant computational demands often render it economically unfeasible for in...
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Internet of Things (IoT) plays a crucial role in automating systems, offering effectual and reliable services with minimal human intervention. To be precise, IoT-enabled smart agriculture is a vital factor in the mode...
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All wireless communication systems are moving towards higher and higher frequencies day by day which are severely attenuated by rains in outdoor environment. To design a reliable RF system, an accurate prediction meth...
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