Bøker av Lizhen Wang

The book involves the basic principles, methods, anatomy and other knowledge for modelling and simulation of the musculoskeletal system. In addition, abundant examples are presented in detail to help readers easily learn the principles and methods of modelling and simulation. These examples include the impact injury and clinical application of the modelling of bone and muscle. In terms of impact injury, the book introduces the biomechanical simulation of impact injury in head, spine, ankle, knee, eyeball and many other parts. With regard to clinical application, it explores the optimization of orthopaedic surgery and design of orthopaedic implants. Readers will find this is a highly informative and carefully presented book, introducing not only the biomechanical principles in the musculoskeletal system, but also the application abilities of modelling and simulation on the musculoskeletal system.

This book summarizes the recent advancements for biomechanics of injury and prevention in mechanism, application and developing frontiers. Biomechanics plays an important role in achieving safety, health, comfort, and a high quality of life by revealing injury mechanism and providing prevention methods. The book covers injury and prevention to the entire human body, from head to toe, including injury and prevention in sports, traffic, accident, clinic and so on. In addition, bionics prevention method inspired by woodpecker is also introduced. The book provides the reader with not only the mechanism of injury but also the advanced injury diagnosis, treatment, and prevention devices based on biomechanics.

The development of information technology has made it possible to collect large amounts of spatial data on a daily basis. It is of enormous significance when it comes to discovering implicit, non-trivial and potentially valuable information from this spatial data. Spatial co-location patterns reveal the distribution rules of spatial features, which can be valuable for application users. This book provides commercial software developers with proven and effective algorithms for detecting and filtering these implicit patterns, and includes easily implemented pseudocode for all the algorithms. Furthermore, it offers a basis for further research in this promising field.Preference-based co-location pattern mining refers to mining constrained or condensed co-location patterns instead of mining all prevalent co-location patterns. Based on the authors¿ recent research, the book highlights techniques for solving a range of problems in this context, including maximal co-location pattern mining, closed co-location pattern mining, top-k co-location pattern mining, non-redundant co-location pattern mining, dominant co-location pattern mining, high utility co-location pattern mining, user-preferred co-location pattern mining, and similarity measures between spatial co-location patterns.Presenting a systematic, mathematical study of preference-based spatial co-location pattern mining, this book can be used both as a textbook for those new to the topic and as a reference resource for experienced professionals.