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This book offers up-to-date information on the recording and analysis of respiratory sounds that will assist in clinical routine. The opening sections deliver basic knowledge on aspects such as the physics of sound and sound transmission in the body, a clear understanding of which is key to good clinical practice. Current techniques of breath sound analysis are described, and the diagnostic impact of advances in the processing of lung sound signals is carefully explained. With the aid of audio files that are available online, detailed guidance is then provided on differentiation of normal and abnormal breath sounds and identification of the various sounds, including crackles, wheezes, other lung sounds, cough sounds, and sounds of extrathoracic origin. The book is of high educational value and represents an excellent learning tool at pre- and postgraduate levels. It will also appeal to researchers as it provides comprehensive summaries of knowledge in particular research fields. The editors bring high-level expertise to the subject, including membership of the European Respiratory Society Task Force on the standardization of categories and nomenclature for breath sounds.
Nanomedical Device and Systems Design: Challenges, Possibilities, Visions serves as a preliminary guide toward the inspiration of specific investigative pathways that may lead to meaningful discourse and significant advances in nanomedicine/nanotechnology. This volume considers the potential of future innovations that will involve nanomedical devic
This book is intended for students, instructional designers, professors, instructors, teachers, trainers, software developers, and development team leaders who: • are taking a course on creating computer-based training/educational software applications • are or will be working on a computer-based training/educational software development team • need to expand their skills into the multimedia technology field • are excited about the possibilities of teaching with multimedia • have worked on their own and unsuccessfully tried to do it all • may have created mediocre computer-based training/educational software • want to do it right the first time • need a practical reference • need practical guidelines for creating computer-managed presentations This book focuses on the practical principles of creating computer-based training/educational software applications and computer-managed presentations. In computer-based training/educational software applications, the computer assumes the teaching role. In computer-managed presentations, you maintain the responsibility for teaching the learners and use what is contained in the presentation as a resource. In a sense, computer-managed presentations are a subset of computer-based training/educational software applications. Their differences will be highlighted throughout this book. This book will not make you an expert in designing computer-based training/educational software applications. Expertise comes through years of experience and continual learning. However, this book will provide you with the foundations for creating professional, instructionally-effective products. To gain support for your computer-based training/educational software applications and computer-managed presentations and to silence the critics, it is important to create excellent products. People will notice quality much more than quantity. This is especially true for your first project. This book, with its numerous practical hints, will help you do it right from your first project onward.
Theoretical results suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one may need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae. Searching the parameter space of deep architectures is a difficult task, but learning algorithms such as those for Deep Belief Networks have recently been proposed to tackle this problem with notable success, beating the state-of-the-art in certain areas. This paper discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.
This book is a printed edition of the Special Issue "Spatial Audio" that was published in Applied Sciences