Tools and techniques for product design

For product designers, tools and techniques are essential in driving the design cycle. Nevertheless, their employment usually is implicit, while passing over e.g. the design and project environments empowering their adequate use. This publication presents an overview of approaches in structuring and using tools/techniques, based on the effectuation of creativity and decision-making in the design environment. In elaborating on characteristics of tools/techniques and ensuing ways of selecting them, the designer's portfolio of tools/techniques is characterised. Representative problems of tool/technique usage are depicted and contextualised by illustrating their industrial application. Prospects for future developments are also reviewe

Relative-fuzzy: a novel approach for handling complex ambiguity for software engineering of data mining models

There are two main defined classes of uncertainty namely: fuzziness and ambiguity, where ambiguity is ‘one-to-many’ relationship between syntax and semantic of a proposition. This definition seems that it ignores ‘many-to-many’ relationship ambiguity type of uncertainty. In this thesis, we shall use complex-uncertainty to term many-to-many relationship ambiguity type of uncertainty. This research proposes a new approach for handling the complex ambiguity type of uncertainty that may exist in data, for software engineering of predictive Data Mining (DM) classification models. The proposed approach is based on Relative-Fuzzy Logic (RFL), a novel type of fuzzy logic. RFL defines a new formulation of the problem of ambiguity type of uncertainty in terms of States Of Proposition (SOP). RFL describes its membership (semantic) value by using the new definition of Domain of Proposition (DOP), which is based on the relativity principle as defined by possible-worlds logic. To achieve the goal of proposing RFL, a question is needed to be answered, which is: how these two approaches; i.e. fuzzy logic and possible-world, can be mixed to produce a new membership value set (and later logic) that able to handle fuzziness and multiple viewpoints at the same time? Achieving such goal comes via providing possible world logic the ability to quantifying multiple viewpoints and also model fuzziness in each of these multiple viewpoints and expressing that in a new set of membership value. Furthermore, a new architecture of Hierarchical Neural Network (HNN) called ML/RFL-Based Net has been developed in this research, along with a new learning algorithm and new recalling algorithm. The architecture, learning algorithm and recalling algorithm of ML/RFL-Based Net follow the principles of RFL. This new type of HNN is considered to be a RFL computation machine. The ability of the Relative Fuzzy-based DM prediction model to tackle the problem of complex ambiguity type of uncertainty has been tested. Special-purpose Integrated Development Environment (IDE) software, which generates a DM prediction model for speech recognition, has been developed in this research too, which is called RFL4ASR. This special purpose IDE is an extension of the definition of the traditional IDE. Using multiple sets of TIMIT speech data, the prediction model of type ML/RFL-Based Net has classification accuracy of 69.2308%. This accuracy is higher than the best achievements of WEKA data mining machines given the same speech data

Epilepsy

Epilepsy is the most common neurological disorder globally, affecting approximately 50 million people of all ages. It is one of the oldest diseases described in literature from remote ancient civilizations 2000-3000 years ago. Despite its long history and wide spread, epilepsy is still surrounded by myth and prejudice, which can only be overcome with great difficulty. The term epilepsy is derived from the Greek verb epilambanein, which by itself means to be seized and to be overwhelmed by surprise or attack. Therefore, epilepsy is a condition of getting over, seized, or attacked. The twelve very interesting chapters of this book cover various aspects of epileptology from the history and milestones of epilepsy as a disease entity, to the most recent advances in understanding and diagnosing epilepsy

Species boundaries in bats: a philosophical, morphometric, environmental, and phylogenetic analysis of the genera Anoura, Carollia and Sturnira

Thesis (Ph.D.)--Boston UniversitySpecies are central to evolutionary biology, systematics and taxonomy. However, their precise definition and diagnosis is not straightforward. Species may be purely nominal constructs of the human mind or they may be real entities. Part of the difficulty of defining and diagnosing species lies in the continuous nature of variation from the level of the individual to the population, subspecies and species. It is here where systematics and taxonomy become challenging and exciting tools for understanding life on the planet. For bats, most of the efforts to describe and differentiate species have been qualitative. This may have worked in earlier times, during the first efforts to describe and name species. But, more recently, our perspectives have become sharper and the shortcomings of the qualitative approach have become obvious. This thesis is a collection of published essays, submitted studies, and ongoing research into the boundaries of bat species. In each chapter, I stress that species are not ideas or categories in the mind, but are real entities, based on testable hypotheses about the distribution of character states within multiorganismal entities. Therefore, these hypotheses and distributions of character states should optimally be analyzed through the prism of statistical inference. The dynamics of size and shape in the genus Anoura are discussed in the context of the space occupied by the different species within the genus, with novel insights into the interpretation of the distribution of these species in morphospace. For boundaries in the genus Carollia, I reassess current taxonomical knowledge, analyze morphological variation in relation to the environment, and the statistical uncertainty of species discrimination. In the species-rich genus Sturnira, I analyze a large morphological dataset for several species from Ecuador, describe a new species (S. peria) synonymize an old one (S. luisi), and provide a new perspective on phylogenetic relationships and species boundaries

Soft computing applied to optimization, computer vision and medicine

Artificial intelligence has permeated almost every area of life in modern society, and its significance continues to grow. As a result, in recent years, Soft Computing has emerged as a powerful set of methodologies that propose innovative and robust solutions to a variety of complex problems. Soft Computing methods, because of their broad range of application, have the potential to significantly improve human living conditions. The motivation for the present research emerged from this background and possibility. This research aims to accomplish two main objectives: On the one hand, it endeavors to bridge the gap between Soft Computing techniques and their application to intricate problems. On the other hand, it explores the hypothetical benefits of Soft Computing methodologies as novel effective tools for such problems. This thesis synthesizes the results of extensive research on Soft Computing methods and their applications to optimization, Computer Vision, and medicine. This work is composed of several individual projects, which employ classical and new optimization algorithms. The manuscript presented here intends to provide an overview of the different aspects of Soft Computing methods in order to enable the reader to reach a global understanding of the field. Therefore, this document is assembled as a monograph that summarizes the outcomes of these projects across 12 chapters. The chapters are structured so that they can be read independently. The key focus of this work is the application and design of Soft Computing approaches for solving problems in the following: Block Matching, Pattern Detection, Thresholding, Corner Detection, Template Matching, Circle Detection, Color Segmentation, Leukocyte Detection, and Breast Thermogram Analysis. One of the outcomes presented in this thesis involves the development of two evolutionary approaches for global optimization. These were tested over complex benchmark datasets and showed promising results, thus opening the debate for future applications. Moreover, the applications for Computer Vision and medicine presented in this work have highlighted the utility of different Soft Computing methodologies in the solution of problems in such subjects. A milestone in this area is the translation of the Computer Vision and medical issues into optimization problems. Additionally, this work also strives to provide tools for combating public health issues by expanding the concepts to automated detection and diagnosis aid for pathologies such as Leukemia and breast cancer. The application of Soft Computing techniques in this field has attracted great interest worldwide due to the exponential growth of these diseases. Lastly, the use of Fuzzy Logic, Artificial Neural Networks, and Expert Systems in many everyday domestic appliances, such as washing machines, cookers, and refrigerators is now a reality. Many other industrial and commercial applications of Soft Computing have also been integrated into everyday use, and this is expected to increase within the next decade. Therefore, the research conducted here contributes an important piece for expanding these developments. The applications presented in this work are intended to serve as technological tools that can then be used in the development of new devices

Recent Developments in Smart Healthcare

Medicine is undergoing a sector-wide transformation thanks to the advances in computing and networking technologies. Healthcare is changing from reactive and hospital-centered to preventive and personalized, from disease focused to well-being centered. In essence, the healthcare systems, as well as fundamental medicine research, are becoming smarter. We anticipate significant improvements in areas ranging from molecular genomics and proteomics to decision support for healthcare professionals through big data analytics, to support behavior changes through technology-enabled self-management, and social and motivational support. Furthermore, with smart technologies, healthcare delivery could also be made more efficient, higher quality, and lower cost. In this special issue, we received a total 45 submissions and accepted 19 outstanding papers that roughly span across several interesting topics on smart healthcare, including public health, health information technology (Health IT), and smart medicine

Product Design

Product design is a comprehensive process related to the creation of new products, and the ability to design and develop efficient products are key to success in today’s dynamic global market. Written by experts in the field, this book provides a comprehensive overview of the product design process and its applications in various fields, particularly engineering. Over seven chapters, the authors explore such topics as development of new product design methodologies, implementation of effective methods for integrated products, development of more visualized environments for task-based conceptual design methods, and development of engineering design tools based on 3D photogrammetry, among others