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"This book presents indepth research that builds a link between natural and life sciences with informatics and computer science for investigating cognitive mechanisms and the human information processes"--
This book thoroughly investigates the underlying theoretical basis of membrane computing models, and reveals their latest applications. In addition, to date there have been no illustrative case studies or complex real-life applications that capitalize on the full potential of the sophisticated membrane systems computational apparatus; gaps that this book remedies. By studying various complex applications – including engineering optimization, power systems fault diagnosis, mobile robot controller design, and complex biological systems involving data modeling and process interactions – the book also extends the capabilities of membrane systems models with features such as formal verification techniques, evolutionary approaches, and fuzzy reasoning methods. As such, the book offers a comprehensive and up-to-date guide for all researchers, PhDs and undergraduate students in the fields of computer science, engineering and the bio-sciences who are interested in the applications of natural computing models.
This book collates past and current research on one of the most promising emerging modalities for breast cancer detection. Readers will discover how, as a standalone technology or in conjunction with another modality, microwave imaging has the potential to provide reliable, safe and comfortable breast exams at low cost. Current breast imaging modalities include X- ray, Ultrasound, Magnetic Resonance Imaging, and Positron Emission Tomography. Each of these methods suffers from limitations, including poor sensitivity or specificity, high cost, patient discomfort, and exposure to potentially harmful ionising radiation. Microwave breast imaging is based on a contrast in the dielectric properties of breast tissue that exists at microwave frequencies. The book begins by considering the anatomy and dielectric properties of the breast, contrasting historical and recent studies. Next, radar-based breast imaging algorithms are discussed, encompassing both early-stage artefact removal, and data independent and adaptive beamforming algorithms. In a similar fashion, microwave tomographic reconstruction algorithms are reviewed in the following chapter, introducing the reader to both the fundamental and more advanced algorithms. Apart from imaging, the book also reviews research efforts in extracting clinically useful information from the Radar Target Signature of breast tumours, which is used to classify tumours as either benign or malignant. Finally, the book concludes by describing the current state of the art in terms of prototype microwave breast imaging systems, with a particular emphasis on those which have progressed to the clinical evaluation stage. This work is motivated by the fact that breast cancer is one of the leading causes of death amongst women in Europe and the US, and the second most common cancer in the world today. Such an important area of research will appeal to many scholars and practitioners.p>
The three-volume set LNCS 13623, 13624, and 13625 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22–26, 2022. The 146 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.