Formerly out of print and unavailable for almost 20 years, this book has remained the foundational text on sandplay psychotherapeutic theory. The theoretical mechanics of how sandplay, an effective nonverbal therapy, works to heal and transform the psyche are articulated and applied to a complete sandplay case. This updated edition includes a clarification of the function of Jung's personality theory in the sandplay therapy method and an examination of the process of growth and development undergone in sandplay therapy. The material provides the clinician and student the theoretical foundation necessary to develop the clinical tools for the practice of sandplay therapy.
Core images are the central images of our lives that put us in touch with our deepest levels of personality and the meaning of our lives. Taken from a variety of sources--songs, cartoons, stories, the scenes that constitute our earliest memories--the core images the author presents here illustrate how we can gain access to our own core images for self-knowledge and healing.
Jung was fascinated by the problem of unity in the personality. If the personality is made up of multiple voices or affective-imaginal states, as he believed it was, then how does an individual achieve a core self? Jung concluded that a coherent and continuous self is the hard won achievement of consciousness, the product of a mature personality in the second half of life. His theory of the integration of multiple subjectivities into an individuating self' anticipates current trends in constructivism and developmental psychology. Jung did not systematize his own work, nor attempt to make accessible many of his most complex ideas about the self. This volume explores his self psychology, its meaning and its application within the context of other contemporary theories of subjectivity. To describe Jung's self psychology more fully in the light of contemporary theories, the authors introduce twelve other self theories in a comparative analysis of the clinical case of a midlife man in psychotherapy. From Kohut and Piaget to Lichtenberg and Loevinger, the authors compare Jung's theories with other clinical and developmental approaches. The book's final chapter offers cogent suggestions for future use of Jung's self psychology. Unique in its treatment and understanding of Jung's theories, this volume illuminates and simplifies many of his central ideas about the self. For Jungians, it provides a contemporary context in which to read and systematize his work. For professionals in the larger therapeutic and educational communities, it offers an up-to-date introduction to a provocative and imaginative body of work that is a central chapter of modern theories of subjectivity.
A “Woman’s Insecurities” is an empowering motivational guide book that addresses a woman’s secured self-image and self-worth. The book focuses on concerns regarding a woman understanding of her own self-image which usually is acknowledged through many forms of experiences involving certain levels of confidence and self-doubt that leads to a type of insecurity through a gradual process. To acknowledge any issues and/or concerns for a woman’s insecurities, the guide book first provides an insecurity quiz to help measure what level your own self-image and self-worth lies. A 7-day ‘Daily Mirror Check’ is also included to see whether you hold a positive or negative self-worth and self-doubt. Insecurity is known to be one of life major challenges, especially among women. However, humanly there is an understanding that everyone experiences some form of insecurity. Insecurity in women can also affect their sexual desires and psychological makeup clouding their judgments and decision-making skills and quality of choices.
“Not many books have a single project that lives and evolves through the entire narrative. The reason not many books do this is because it is difficult to do well. Important toolkit features get shoehorned in weird places because the author didn’t do enough up-front design time. This book, though, takes you from design, to a prototype, to the Real Deal. And then it goes further.” —Mark Dalrymple, cofounder of CocoaHeads, the international Mac and iPhone programmer community; author of Advanced Mac OS X Programming: The Big Nerd Ranch Guide Learning iPad Programming, Second Edition, will help you master all facets of iPad programming with Apple’s newest tools. Its in-depth, hands-on coverage fully addresses the entire development process, from installing the iOS SDK through coding, debugging, submitting apps for Apple’s review, and deployment. Extensively updated for Apple’s newest iOS features and Xcode 4.x updates, this book teaches iPad programming through a series of exercises centered on building PhotoWheel, a powerful personal photo library app. As you build PhotoWheel, you’ll gain experience and real-world insights that will help you succeed with any iPad development project. Leading iOS developers Kirby Turner and Tom Harrington introduce the essentials of iOS development, focusing on features that are specific to iPad. You’ll find expert coverage of key topics many iOS development books ignore, from app design to Core Data. You’ll also learn to make the most of crucial iOS and Xcode features, such as Storyboarding and Automatic Reference Counting (ARC), and extend your app with web services and the latest iCloud synching techniques. Learn how to Build a fully functional app that uses Core Data and iCloud synching Use Storyboarding to quickly prototype a functional UI and then extend it with code Create powerful visual effects with Core Animation and Core Image Support AirPrint printing and AirPlay slideshows Build collection views and custom views, and use custom segues to perform custom view transitions Download the free version of PhotoWheel from the App Store today! Import, manage, and share your photos as you learn how to build this powerful app.
This book presents state-of-the-art optimization algorithms followed by Internet of Things (IoT) fundamentals. The applications of machine learning and IoT are explored, with topics including optimization, algorithms and machine learning in image processing and IoT. Applications of Optimization and Machine Learning in Image Processing and IoT is a complete reference source, providing the latest research findings and solutions for optimization and machine learning algorithms. The chapters examine and discuss the fields of machine learning, IoT and image processing. KEY FEATURES: • Includes fundamental concepts towards advanced applications in machine learning and IoT. • Discusses potential and challenges of machine learning for IoT and optimization • Reviews recent advancements in diverse researches on computer vision, networking and optimization field. • Presents latest technologies such as machine learning in image processing and IoT This book has been written for readers in academia, engineering, IT specialists, researchers, industrial professionals and students, and is a great reference for those just starting out in the field as well as those at an advanced level.
This book provides a practical explanation of the backpropagation neural networks algorithm and how it can be implemented for image classification. The discussion in this book is presented in step by step so that it will help readers understand the fundamental of the backpropagation neural networks and its steps. This book is very suitable for students, researchers, and anyone who want to learn and implement the backpropagation neural networks for image classification using PYTHON GUI. The discussion in this book will provide readers deep understanding about the backpropagation neural networks architecture and its parameters. The readers will be guided to understand the steps of the backpropagation neural networks for image classification through case example. The readers will be guided to create their own neural networks class and build their complete applications for data image classification. The final objective of this book is that the readers are able to realize each step of the multilayer perceptron neural networks for image classification. In Addition, the readers also are able to create the neural networks applications which consists of two types of applications which are command window based application and GUI based application. Here are the material that you will learn in this book. CHAPTER 1: This chapter will guide you in preparing what software are needed to realize the backpropagation neural networks using Python GUI. The discussion in this chapter will start from installing Python and the libraries that will be used, installing Qt Designer, understanding and using Qt Designer to design the application UI, and the last is about how to create a GUI program using Python and Qt Designer. CHAPTER 2: This chapter discusses the important parts in the backpropagation neural networks algorithm which includes the architecture of the backpropagation neural networks, the parameters contained in the backpropagation neural networks, the steps of the backpropagation neural networks algorithm, and the mathematical calculations of the backpropagation neural networks. CHAPTER 3: This chapter discusses in detail the mathematical calculations of fruit quality classification using the backpropagation neural networks which includes the feature extraction process of fruit images, data normalization, the training process, and the classification process. The feature extraction method used in this case is GLCM (Gray Level Co-occurrence Matrix). The image features that will be used in this case are energy, contrast, entropy, and homogeneity. CHAPTER 4: This chapter discusses how to implement the backpropagation neural networks algorithm for fruit quality classification using Python. This chapter will present the steps to create your backpropagation neural networks class and to define the functions that represent each process of the backpropagation neural networks. This chapter will also present the steps to create a class for image processing. And in final discussion you will be guided to create your backpropagation neural networks application from scratch to classify the quality of fruit. CHAPTER 5: This chapter will discuss how to create a GUI based application for fruit quality classification using the backpropagation neural networks algorithm. This chapter will discuss in detail the steps for designing the application UI by using Qt Designer, the steps for creating a class for the backpropagation neural networks GUI based application, and how to run the GUI based application to classify the fruit data.
