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Biopharmaceutics applications in drug development
This book introduces fundamental concepts, methods, and advances in the areas of dissolution, absorption, and permeability and their key applications in dosage form performance. Case studies are used to discuss the applications of biopharmaceutic strategies in the development of successful drugs, with a specific focus on the applications of biopharmaceutic strategies in the development of successful drugs. The book presents an integrated view in linking pharmaceutic to the biological consequences of drug products and leverages those for decision making in drug development.
Benign anorectal diseases : Diagnosis with endoanal and endorectal ultrasound and new treatment options
New three-dimensional endoanal and endorectal ultrasonographic and magnetic resonance imaging techniques have given better insight into the complex anatomy of the pelvic floor and its pathologic modification in benign anorectal diseases. Obstetrical events leading to fecal incontinence in females, the relationship between fistulous tracks and the sphincter complex, and mechanisms of obstructed defecation syndrome can now be accurately evaluated, which is of fundamental importance for decision making.
Machine Learning and Probabilistic Graphical Models for Decision Support Systems
Presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.
Machine Ethics : From Machine Morals to the Machinery of Morality
Offers the first systematic guide to machine ethics, bridging between computer science, social sciences and philosophy. Based on a dialogue between an AI scientist and a novelist philosopher, the book discusses important findings on which moral values machines can be taught and how. In turn, it investigates what kind of artificial intelligence (AI) people do actually want.
Law and the Semantic Web : Legal Ontologies, Methodologies, Legal Information Retrieval, and Applications
As part of this objective, ICT (information and communication technologies) services should become available for every citizen, and for all schools, homes and businesses. The book you have in front of you is about Semantic Web technology and law. Law is something omnipresent; all citizens — at some points in their lives — have to deal with it. In addition, law involves a large group of professionals, and is a mul- billion business world wide. Information technology is important because it that can improve citizens’ interaction with law, as well as improve legal professionals’ work environment. Legal professionals dedicate a significant amount of their time to finding, reading, analyzing and synthesizing information in order to take decisions, and prepare advice and trials, among other tasks. As part of the “Semantic-Based Knowledge and Content Systems” Strategic Objective, the European Commission is funding projects to construct technology to make the Semantic Web vision come true. 1 The articles in this book are related to two current foci of the Strategic Objective : • Knowledge acquisition and modelling, capturing knowledge from raw information and multimedia content in webs and other distributed repositories to turn poorly structured information into machi- processable knowledge.
Knowledge Processing with Interval and Soft Computing
In particular, these chapters cover computing techniques for interval linear systems of equations, interval matrix singular-value decomposition, interval function approximation, and decision making with statistical and graph-based data processing. To enable these applications, the book presents a standards-based object-oriented interval computing environment in C++.
Big Data : An Art of Decision Making
Manipulating and processing masses of digital data is never a purely technical activity. It requires an interpretative and exploratory outlook - already well known in the social sciences and the humanities - to convey intelligible results from data analysis algorithms and create new knowledge. Big Data is based on an inquiry of several years within Proxem, a software publisher specializing in big data processing. The book examines how data scientists explore, interpret and visualize our digital traces to make sense of them, and to produce new knowledge. Grounded in epistemology and science and technology studies, Big Data offers a reflection on data in general, and on how they help us to better understand reality and decide on our daily actions.
Beginning Excel What-If Data Analysis tools : Getting started with goal seek, data tables, scenarios, and solver
Excels what-if data analysis tools let you experiment with your data to project future results. In turn, these predictions will lead to better decision making and unlock the mystery of many business analysis scenarios. For example, what-if data analysis tools will enable you to forecast how lowering the price per unitwhile increasing projected unit salesmight affect your profit margins. Beginning Excel What-If Data Analysis Tools explores the use of Goal Seek, Data Tables, Scenarios, and Solver to help you get insight on your data. This book is focused and to the point, and it provides tutorial treatment of what-if tools in a practical, hands-on manner.
Bayesian Networks and Decision Graphs
Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. As modeling languages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algorithms for automatic construction and query answering. This includes belief updating, finding the most probable explanation for the observed evidence, detecting conflicts in the evidence entered into the network, determining optimal strategies, analyzing for relevance, and performing sensitivity analysis. The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams.It contians two parts. The first part focuses on probabilistic graphical models. Compared with the previous book, the new edition also includes a thorough description of recent extensions to the Bayesian network modeling language, advances in exact and approximate belief updating algorithms, and methods for learning both the structure and the parameters of a Bayesian network. The second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision processes and partially ordered decision problems.
Applied mathematics and machine learning
The simultaneous availability of large datasets and high-performance computing capability in recent years has enabled the rapid development of powerful machine learning algorithms. On the one hand, state-of-the-art machine learning techniques have transformed many areas of science and engineering; on the other hand, theoretical discoveries in mathematical algorithms, differential equations, and statistical inferences, to name a few, have provided the foundation for the exploration of new multidisciplinary models for solving practical problems. This Special Issue endeavors to continue the journey that started in our previous Special Issue (Applied Mathematics and Computational Physics) by providing a platform for researchers from both academia and industry, as well as government, to present their new computational methods that have engineering and physics applications.
Algorithms for Decision Making
A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them.
Active Conceptual Modeling of Learning : Next Generation Learning-Base System Development
This volume contains a collection of the papers presented during the 1st International ACM-L Workshop, which was held on November 8, 2006 during the 25th International Conference on Conceptual Modeling, ER 2006, held November 6–9,2006, in Tucson, Arizona, plus several invited papers.These papers plus the invited papers represent the current thinking in conceptual modeling research, The active model can only be realized through technology integration (e.g., AI, software engineering, information technology,cognitive science, art and sciences, philosophy, etc.)
Master Dentistry ; Vol.1 : Oral and Maxillofacial Surgery, Radiology, Pathology and Oral Medicine
Provides a comprehensive overview of the oral and maxillofacial subjects in dentistry that students will need in order to pass their final exams. This invaluable adjunct to exam preparation provides a practical synthesis of core information, reflecting real-life case scenarios. Information is structured to enhance understanding and clinical decision making, and a variety of self-assessment methods prepare students for success. Comprehensively updated, the book covers a range of essential topics in the field of contemporary oral and maxillofacial subjects, including surgical flap design, state-of-the-art surgical techniques, zygomatic implants, molecular pathology, current imaging applications and pain management. The text is integrated and evidence based throughout. Covers oral and maxillofacial surgery, radiology, pathology and oral medicine subjects Brand new chapter on facial skin broadens diagnostic ability Range of self-assessment tasks to support learning Aligns to dental school curricula globally Concise and easy to follow Designed to support recall for examination purposes Practical guidance on examination preparation and skills Perfect for BDS exam preparation and candidates taking the MFDS, MJDF, ORE or other post-graduate exams
Apical periodontitis in root-filled teeth : Endodontic retreatment and alternative approaches
A comprehensive guide to apical periodontitis in root-filled teeth that covers not only all aspects of diagnosis and management but also epidemiology, etiology, consequences, clinical decision-making, and prognosis. There is a particular focus on the available surgical and nonsurgical methods of retreatment designed to restore healthy periapical conditions.
3D imaging in endodontics : A new era in diagnosis and treatment
Full understanding of the role of cone beam computed tomography (CBCT) in helping to solve many of the most challenging problems in endodontics. It will shorten the learning curve in application of this exciting imaging technology in a variety of contexts: difficult diagnostic cases, treatment planning, evaluation of internal tooth anatomy prior to root canal therapy, nonsurgical and surgical treatments, early detection and treatment of resorptive defects, and outcomes assessment. The ability to obtain an accurate 3D representation of a tooth and the surrounding structures by means of noninvasive CBCT imaging is changing the approach to clinical decision making in endodontics. Clinicians long accustomed to working in very small, three-dimensional spaces are no longer constrained by the limitations of two-dimensional imaging. The challenges of mastering the new technology can, however, be daunting. The detailed guidance contained in this book will help endodontists to take full advantage of the important benefits offered by CBCT.
Aging, shaking, and cracking of infrastructures : From mechanics to concrete dams and nuclear structures
Focuses on the safety assessment of existing structures subjected to multi-hazard scenarios through advanced numerical methods. Whereas the focus is on concrete dams and nuclear containment structures, the presented methodologies can also be applied to other large-scale ones. This book is composed of seven sections: Fundamentals: theoretical coverage of solid mechnics, plasticity, fracture mechanics, creep, / seismology, dynamic analysis, probability and statistics / Damage: that can affect concrete structures, such as cracking of concrete, AAR, chloride ingress, and rebar corrosion, / Finite Element: formulation for both linear and nonlinear analysis including stress, heat and fracture mechanics, / Engineering Models: for soil/fluid-structure interaction, uncertainty quantification, probablilistic and random finite element analysis, machine learning, performance based earthquake engineering, ground motion intensity measures, seismic hazard analysis, capacity/fragility functions and damage indeces, / Applications to dams through potential failure mode analyses, risk-informed decision making, deterministic and probabilistic examples, / Applications to nuclear structures through modeling issues, aging management programs, critical review of some analyses, / Other applications and case studies: massive RC structures and bridges, detailed assessment of a nuclear containment structure evaluation for license renewal.
Managing public services : Making informed choices
Chapters provide a valuable frame of reference for the 21st-century manager of public services by assessing the renewal of existing practices such as strategic costing, performance management, digitization and procurement and innovations in management practices, including branding, Lean Management, resilience and risk management. The book suggests that, as the management of public services is imbued with financial, social, economic and political uncertainties, management needs to be flexible and responsive to new ideas and practices to fulfil its purpose. This book ultimately supports the reflective manager, those who think about their job and are open to new ideas on how their job can be done better, by revisiting existing practices and examining innovations in public management.
Launching & Building a Brand For Dummies
In Launching & Building a Brand For Dummies, Amy Will—who launched her first business at just 24-years-old and has been the brains behind four strong and buzzworthy brands—covers everything from crafting a powerful brand identity and planning that all-important launch to being prepared to scale up as you begin to take off. She reveals crucial lessons from her personal experience in launching five companies, as well as detailing case studies from some of the strongest brands out there, accompanied by insights and advice from successful founders and branding experts.
Large-scale group decision-making : State-to-the-art clustering and consensus paths
The proposed consensus models focus on the treatment of non-cooperative behaviors in the consensus-reaching process and explores the influence of trust loss on the consensus-reaching process.The logic behind is as follows: firstly, a clustering algorithm is adopted to reduce the dimension of decision-makers, and then, based on the clusters’ opinions obtained, a consensus-reaching process is carried out to obtain a decision result acceptable to the majority of decision-makers.
Complexity and Artificial Markets
In recent years, agent-based simulation has become a widely accepted tool when dealing with complexity in economics and other social sciences. The contributions presented in this book apply agent-based methods to derive results from complex models related to market mechanisms, evolution, decision making, and information economics. In addition, the applicability of agent-based methods to complex problems in economics is discussed from a methodological perspective. The papers presented in this collection combine approaches from economics, finance, computer science, natural sciences, philosophy, and cognitive sciences.
