الصفحة 20
الصفحة 20
Diagnosis of Process Nonlinearities and Valve Stiction : Data Driven Approaches
In this book, Higher Order Statistical (HOS) theory is used to develop indices for detecting and quantifying signal non-Gaussianity and nonlinearity. These indices, together with specific patterns in the mapping of process output and controller output are used to diagnose the causes of poor control loop performance.
Diagnosis and Fault-Tolerant Control
The book presents effective model-based analysis and design methods for fault diagnosis and fault-tolerant control. Architectural and structural models are used to analyse the propagation of the fault throughout the process, to test the fault detectability and to find the redundancies in the process that can be used to ensure fault tolerance. Design methods for diagnostic systems and fault-tolerant controllers are presented for processes that are described by analytical models, by discrete-event models or that can be dealt with as quantised systems. Five case studies on pilot processes show the applicability of the presented methods. The theoretical results are illustrated by two running examples used throughout the book.
Device Applications of Nonlinear Dynamics
This edited book is devoted specifically to the applications of complex nonlinear dynamic phenomena to real systems and device applications. While in the past decades there has been significant progress in the theory of nonlinear phenomena under an assortment of system boundary conditions and preparations, there exist comparatively few devices that actually take this rich behavior into account. "Device Applications of Nonlinear Dynamics" applies and exploits this knowledge to make devices which operate more efficiently and cheaply, while affording the promise of much better performance. Given the current explosion of ideas in areas as diverse as molecular motors, nonlinear filtering theory, noise-enhanced propagation, stochastic resonance and networked systems, the time is right to integrate the progress of complex systems research into real devices.
Developing Statistical Software in Fortran 95
"This book gives statisticians, biostatisticians and methodologically-oriented researchers the tools they need to develop high-quality statistical software. This book is for those who want to learn how to create statistical applications quickly and effectively. Prior experience with a programming language such as Basic, Fortran or C is helpful but not required. More experienced programmers will learn new strategies to harness the power of modern Fortran and the object-oriented paradigm. This may serve as a supplementary text for a graduate course on statistical computing."
Deterministic Numerical Modeling of Soil Structure Interaction
In order to describe soil–structure interaction in various situations (nonlinear, static, dynamic, hydro-mechanical couplings), this book gives an overview of the main modeling methods developed in geotechnical engineering. The chapters are centered around: the finite element method (FEM), the finite difference method (FDM), and the discrete element method (DEM). Deterministic Numerical Modeling of Soil–Structure Interaction allows the reader to explore the classical and well-known FEM and FDM, using interface and contact elements available for coupled hydro-mechanical problems.
Determinants of audit fees : Evidence from Syria
Examines different factors that determine the value of audit fees in Syria. We test the impact of many factors related to audit firm as (audit report type, auditor type, audit firm market share and audit firm rotation) and factors related to client of audit firm (type, size, age and profitability) on the amounts of audit fees. To achieve that goal, the study depends on a practical study ; by extracting an actual data of the 24 companies listed at Damascus Securities Exchange (DSE) for the years 2016-2022. The extracted data were then analyzed by SPSS using descriptive statistics, simple linear regression test, and ANOVA test to examine the research hypothesis.
Designing Organizations : 21st Century Approaches
The design of organizations has been an ongoing concern of management theory and practice over the past several decades. Over this time, there has been little change in the fundamental theory, principles and concepts of Organization Design (OD). Recently organizational life has changed dramatically with the advent of: new communication systems, adaptive mechanisms, information technology, knowledge management systems, innovation processes and more. This book systemically examines these developments and their impact on OD with contributions from leading scholars in the area. Also featured in the book are the practical issues with implementing OD in organizations. The individual chapters are organized into five sections: (1) Putting Contingency Theory in its Place, (2) Focus on Individuals Who Make up the Organization, (3) Innovation Processes and Organization Design, (4) Adaptation and Technology, and (5) Design for Performance. Each chapter examines aspects of the book’s threefold theme: (1) core issues in organization design, (2) emerging theoretical perspectives in OD, and (3) new developments and directions in OD. A special feature of each chapter is: 1) implications for theory, and 2) implications for practice.
Design of Reinforced Concrete Buildings for Seismic Performance : Practical Deterministic and Probabilistic Approaches
Presents an elegant, simple and theoretically coherent design framework. Required strength is determined on the basis of an estimated yield displacement and desired limits of system ductility and drift demands. A simple deterministic approach is presented along with its elaboration into a probabilistic treatment that allows for design to limit annual probabilities of failure. The design method allows the seismic force resisting system to be designed on the basis of elastic analysis results, while nonlinear analysis is used for performance verification. Detailing requirements of ACI 318 and Eurocode 8 are presented. Students will benefit from the coverage of seismology, structural dynamics, reinforced concrete, and capacity design approaches, which allows the book to be used as a foundation text in earthquake engineering.
Design of advanced manufacturing systems : Models for capacity planning in advanced manufacturing systems
The aim of this book is to provide a framework and speci?c methods and tools for the selection and con?guration of capacity of Advanced Manufacturing Systems (AMS). In particular this book de?nes an - chitecture where the multidisciplinary aspects of the designofAMSare properly organized and addressed. The tool will support the decisi- maker in the de?nition of the con?guration of the system which is best suited for the particular competitive context where the ?rm operates or wants tooperate. Thisbookisofinterest for academic researchers in the ?eldofind- trial engineering and particularly indicated in the areas of operations and manufacturing strategy.
Design of adaptive finite Element software : The finite element toolbox ALBERTA
During the last years, scientific computing has become an important research branch located between applied mathematics and applied sciences and engineering. Highly efficient numerical methods are based on adaptive methods, higher order discretizations, fast linear and non-linear iterative solvers, multi-level algorithms, etc. Such methods are integrated in the adaptive finite element software ALBERTA. It is a toolbox for the fast and flexible implementation of efficient software for real life applications, based on modern algorithms. ALBERTA also serves as an environment for improving existent, or developing new numerical methods in an interplay with mathematical analysis and it allows the direct integration of such new or improved methods in existing simulation software.
Design and Analysis of Simulation Experiments
This is an advanced expository book on statistical methods for the Design and Analysis of Simulation Experiments (DASE). Though the book focuses on DASE for discrete-event simulation (such as queuing and inventory simulations), it also discusses DASE for deterministic simulation (such as engineering and physics simulations). The text presents both classic and modern statistical designs. Classic designs (e.g., fractional factorials) assume only a few factors with a few values per factor. The resulting input/output data of the simulation experiment are analyzed through low-order polynomials, which are linear regression (meta)models. Modern designs allow many more factors, possible with many values per factor. These designs include group screening (e.g., Sequential Bifurcation, SB) and space filling designs (e.g., Latin Hypercube Sampling, LHS). The data resulting from these modern designs may be analyzed through low-order polynomials for group screening and various metamodel types (e.g., Kriging) for LHS.
Dependence in Probability and Statistics
This book gives a detailed account of some recent developments in the field of probability and statistics for dependent data. The book covers a wide range of topics from Markov chain theory and weak dependence with an emphasis on some recent developments on dynamical systems, to strong dependence in times series and random fields. A special section is devoted to statistical estimation problems and specific applications. The book is written as a succession of papers by some specialists of the field, alternating general surveys, mostly at a level accessible to graduate students in probability and statistics, and more general research papers mainly suitable to researchers in the field. The first part of the book considers some recent developments on weak dependent time series, including some new results for Markov chains as well as some developments on new notions of weak dependence. This part also intends to fill a gap between the probability and statistical literature and the dynamical system literature. The second part presents some new results on strong dependence with a special emphasis on non-linear processes and random fields currently encountered in applications. Finally, in the last part, some general estimation problems are investigated, ranging from rate of convergence of maximum likelihood estimators to efficient estimation in parametric or non-parametric time series models, with an emphasis on applications with non-stationary data.
Delay Differential Equations and Applications ; Proceedings of the NATO Advanced Study Institute held in Marrakech, Morocco, 9-21 September 2002
This Edition includes detailed discussion and analysis on: General Results and Linear Theory of Delay Equations in Finite Dimensional Spaces; Hopf Bifurcation, Centre Manifolds and Normal Forms for Delay Differential Equations; Functional Differential Equations in Infinite Dimensional Spaces; and Delay Differential Equations and Applications.
Deep learning architecture and application
As one of the fastest-growing topics in machine learning, deep learning algorithms have achieved unprecedented success in recent years. Novel paradigms (such as contrastive learning and few-shot learning) in deep learning and rising neural network architectures (e.g., transformer and masked autoencoder) are dramatically changing the field of data-driven algorithms. More importantly, deep learning models are redefining the next generation of industrial applications spanning image recognition, speech processing, language translation, healthcare, and other sciences. For example, recent advances in deep representation learning are allowing us to learn about protein 3D structures, which sheds new light on fundamental medicine and biology along with potentially bringing in billions of dollars (e.g., in the pharmaceutical market).
Decoupling Control
Decoupling or non-interactive control has attracted considerable research attention since the 1960s when control engineers started to deal with multivariable systems. The theory and design techniques for decoupling control have now, more or less matured for linear time-invariant systems, yet there is no single book which focuses on such an important topic. The present monograph fills this gap by presenting a fairly comprehensive and detailed treatment of decoupling theory and relevant design methods. Decoupling control under the framework of polynomial transfer function and frequency response settings, is included as well as the disturbance decoupling problem. The emphasis here is on special or relatively new compensation schemes such as (true and virtual) feedforward control and disturbance observers, rather than use of feedback control alone. The results are presented in a self-contained way and only the knowledge of basic linear systems theory is assumed of the reader.
Decomposition Techniques in Mathematical Programming : Engineering and Science Applications
This textbook for students and practitioners presents a practical approach to decomposition techniques in optimization. It provides an appropriate blend of theoretical background and practical applications in engineering and science, which makes the book interesting for practitioners, as well as engineering, operations research and applied economics graduate and postgraduate students. "Decomposition Techniques in Mathematical Programming" is based on clarifying, illustrative and computational examples and applications from electrical, mechanical, energy and civil engineering as well as applied mathematics and economics. It addresses decomposition in linear programming, mixed-integer linear programming, nonlinear programming, and mixed-integer nonlinear programming, and provides rigorous decomposition algorithms as well as heuristic ones.
Decision-Making in Engineering Design : Theory and Practice
We use our brains when we create plans and designs. The resulting plans and designs take physical form, however, what we thought about, the alternatives we tried, and the constraints we recognized while we were making these plans and designs are usually not written anywhere. Therefore, those who only get to see the results, e.g. the final text and drawings, do not learn what led the designer to reach such conclusions and as a consequence never understand the real design. This description of decision processes will provide the means for the development of new manufacturing systems and production activities in the future because it helps us gain a real understanding of the how the mind processes we go through when making decisions affect the decisions that we make.
Decision Support for Forest Management
While earlier books concerning forest planning have tended to focus on linear programming, economic aspects, or specific multi-criteria decision aid tools, this book provides a much broader range of tools to meet a variety of planning situations. The methods themselves cover a range of decision situations – from cases involving single decision makers, through group decision making, to participatory planning. They include traditional decision support tools, from optimization to utility functions, as well as methods that are just gaining ground in forest planning – such as problem structuring methods and social choice theory. Including examples which illustrate the application of each technique to specific management planning problems, the book offers an invaluable resource for both researchers and advanced students specializing in management and planning issues relating to forestry.
Decision Making with the Analytic Network Process: Economic, Political, Social and Technological Applications with Benefits, Opportunities, Costs and Risks
A selection of applications of ANP to economic, social and political decisions, and also to technological design. The chapters comprise contributions of scholars, consultants and people concerned about the outcome of certain important decisions who applied the Analytic Network Process to determine the best outcome for each decision from among several potential outcomes.
Data Mining in Biomedicine
This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes new approaches for the analysis of biomedical data; applications of data mining techniques to real-life problems in medical practice; comprehensive reviews of recent trends in the field. The book addresses incorporation of data mining in fundamental areas of biomedical research: genomics, proteomics, protein characterization, and neuroscience.
