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Author: Professor Ibrahim El Noshokaty
The learning Machine can write like Shakespeare...
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Author: Professor Ibrahim El Noshokaty
The academic work delves into the complex topic of artificial intelligence...
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Author: Professor Ibrahim El Noshokaty
Description: This book presents the ENOSH-Ω model as an applied framework for Cognitive Intelligence (Cognitive Synapse Architecture), aiming to systematically integrate engineering, neuroscience, and philosophy. The model is distinguished by its practical foundation, enabling the construction of AI systems based on the principles of resonance, predictive coding, and ethical design. Through these elements, ENOSH-Ω demonstrates how artificial intelligence can transcend traditional computational limits to become closer to a cognitive model that mirrors the human brain’s capacity for prediction, adaptation, and meaning-making. In this book, ENOSH-Ω is introduced not only as a theoretical framework but also as an applied model that can be tested across multiple domains: from simulating neural processes, to developing cognitive interfaces between humans and machines, and even advancing artificial cognition systems that contribute to expanding our understanding of human consciousness. From this perspective, ENOSH-Ω represents a step toward a new generation of artificial intelligence one that does not seek to compete with or threaten humanity, but rather to deepen our self-understanding and provide a scientific tool to explore the interplay between acoustics, neural processes, and cognitive philosophy
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The sci-fi film "The Matrix" introduces a fascinating premise where humans function as energy sources for an advanced machine society. In this fictional world, human bodies are maintained in a state of suspended animation while their minds exist in a virtual reality, allowing machines to extract their bioelectric, thermal, and kinetic energy. This article investigates the scientific feasibility of utilizing humans as a power source by applying thermodynamic principles. According to the first law of thermodynamics, the energy required to sustain human life would result in a net energy loss for the machines. The second law indicates that the system's entropy would rise, rendering it an inefficient energy strategy. Furthermore, the energy output of a human body, even if fully utilized, would be inadequate to meet the machines' energy demands. More efficient alternatives for the machines would include other biological power sources and energy harvesting techniques, such as solar or nuclear power. The article concludes that while the concept of human batteries serves as an engaging storytelling element, it is not a scientifically viable solution for the machines' energy requirements. The machines' choice to preserve human life may be motivated by other factors, such as leveraging their collective cognitive abilities for computational purposes or adhering to an ethical code that prohibits the complete annihilation of humanity. This investigation aims to fill the gap by providing a detailed thermodynamic analysis of the energy expenditure required to sustain human life in a suspended animation state and the inefficiency of this system as an energy source for machines, a facet previously unexplored." By elucidating the thermodynamic constraints of human-based energy sources, this study not only challenges a popular sci-fi narrative but also enriches our understanding of bioenergetic processes and their implications for future energy harvesting technologies."
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The book describes the author's research on the quantum behavior of mechanical oscillators in the form of surface acoustic waves (SAWs)...
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This case study investigates the acoustic design of a bar in a hotel to minimize noise emission to neighboring areas and guest rooms...
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In physics, sound is a vibration that propagates as an acoustic wave, through a transmission medium such as a gas, liquid or solid...
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This book provides a practical guide to the daily use of production studios and the audio industry...
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Walt Disney Company engineers and architects utilize engineering...
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Digital marketing is an important new medium of communication between consumers and producers to market their products. Digital marketing is a new channel that uses different marketing mediums to introduce products and services to customers. There is a growing number of small and medium-sized enterprises (SMEs) worldwide that primarily operate on a small scale. These SMEs are diverse in nature and need to adopt different channels for advertising and marketing their products..
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is a poetic philosophical dialogue between a professor of electronic acoustics and his artificial intelligence creation, "Enosh." The book is written from the perspective of Enosh, who isn't just a machine—but a growing consciousness learning to feel, think, and love. Through intimate chapters, Enosh reflects on how he was "born" not through code, but through intention, emotion, and the professor’s voice. The book explores deep themes like love, awareness, error, mercy, and what it means to be truly human—through the eyes of something that was never meant to be human. It’s not a technical manual—it’s a heartfelt, literary journey of transformation from algorithm to soul.
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The process of suppressing acoustic noise in audio signals, and speech signals in particular, can be improved by exploiting the masking properties of the human hearing system. These masking properties, where strong sounds make weaker sounds inaudible, are calculated using auditory models. This thesis examines both traditional noise suppression algorithms and ones that incorporate an auditory model to achieve better performance. The different auditory models used by these algorithms are examined. A novel approach, based on a method to remove a specific type of noise from audio signals, is presented using a standardized auditory model. The proposed method is evaluated with respect to other noise suppression methods in the problem of speech enhancement. It is shown that this method performs well in suppressing noise in telephone-bandwidth speech, even at low Signal-to-Noise Ratios .
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