Victor A. Skormin – författare

Overview This book introduces immunocomputing (Ie) as a new computing approach that replicates the principles of information processing by proteins and immune networks. It establishes a rigorous mathematical basis for IC, consistent with recent findings in immunology, and it presents various applications of IC to specific computationally intensive real-life problems. The hardware implementation aspects of the IC concept in an immunocomputer as a new kind of computing medium and its potential connections with modem biological microchips (biochips) and future biomolecular computers (biocomputers) are also discussed. All biological systems at the cellular and biomolecular levels are sophisticated mechanisms honed to perfection by millions of years of evolution, and their exploration provides inspiration for various novel concepts in science and engineering. Of these systems, however, only two types, the neural system and the immune system of the vertebrates, possess the extraordinary capabilities of "intellectual" information processing, which include memory, the ability to learn, to recognize, and to make decisions with respect to unknown situations. The potential of the natural neural system as a biological prototype of a computing scheme has already been utilized intensively in computer science through the mathematical and software models of artificial neural networks (ANN) and their hardware implementation in neural computers (see, e.g., Haykin, 1999; Wasserman, 1990).

This book is an attempt to introduce immunocomputing (IC) as a new computing approach replicating the principles of information processing by proteins and immune networks. A rigorous mathematical basis of the IC, consistent with the recent findings of immunology, is established. Various applications of IC to specific computationally- intensive real-life problems are presented. The hardware implementation aspects of the IC concept in an immunocomputer as a new kind of computing media and its potential connections with modern biological microchips (biochips) and future biomolecular computers (biocomputers) are discussed. The book is intended for experts in computer science, artificial intelligence and biomolecular computing interested in adopting the principles of computing, honed to perfection by million-year evolution, immunologists seeking to further quantify their field of research, multidisciplinary researchers interested in mutual enhancement of computer science and immunology, and university students exploring their individual "entry points" to the world of science.

Overview This book introduces immunocomputing (Ie) as a new computing approach that replicates the principles of information processing by proteins and immune networks. It establishes a rigorous mathematical basis for IC, consistent with recent findings in immunology, and it presents various applications of IC to specific computationally intensive real-life problems. The hardware implementation aspects of the IC concept in an immunocomputer as a new kind of computing medium and its potential connections with modem biological microchips (biochips) and future biomolecular computers (biocomputers) are also discussed. All biological systems at the cellular and biomolecular levels are sophisticated mechanisms honed to perfection by millions of years of evolution, and their exploration provides inspiration for various novel concepts in science and engineering. Of these systems, however, only two types, the neural system and the immune system of the vertebrates, possess the extraordinary capabilities of "intellectual" information processing, which include memory, the ability to learn, to recognize, and to make decisions with respect to unknown situations. The potential of the natural neural system as a biological prototype of a computing scheme has already been utilized intensively in computer science through the mathematical and software models of artificial neural networks (ANN) and their hardware implementation in neural computers (see, e.g., Haykin, 1999; Wasserman, 1990).

This textbook is intended for an introductory graduate level on process control, taught in most engineering curricula. It focuses on the statistical techniques and methods of control and system optimization needed for the mathematical modeling, analysis, simulation, control and optimization of multivariable manufacturing processes. In four sections, it covers:Relevant mathematical methods, including random events, variables and processes, and their characteristics; estimation and confidence intervals; Bayes applications; correlation and regression analysis; statistical cluster analysis; and singular value decomposition for classification applications.Mathematical description of manufacturing processes, including static and dynamic models; model validation; confidence intervals for model parameters; principal component analysis; conventional and recursive least squares procedures; nonlinear least squares; and continuous-time, discrete-time, s-domain and Z-domain models.Control of manufacturing processes, including transfer function/transfer matrix models; state-variable models; methods of discrete-time classical control; state variable discrete-time control; state observers/estimators in control systems; methods of decoupling control; and methods of adaptive control.Methods and applications of system optimization, including unconstrained and constrained optimization; analytical and numerical optimization procedures; use of penalty functions; methods of linear programming; gradient methods; direct search methods; genetic optimization; methods and applications of dynamic programming; and applications to estimation, design, control, and planning.Each section of the book will include end-of-chapter exercises, and the book will be suitable for any systems, electrical, chemical, or industrial engineering program, as it focuses on the processes themselves, and not on the product being manufactured.  Students will be able to obtain a mathematical model of any manufacturing process, to design a computer-based control system for a particular continuous manufacturing process, and be able to formulate an engineering problem in terms of optimization, as well as the ability to choose and apply the appropriate optimization technique.

This textbook is intended for an introductory graduate level on process control, taught in most engineering curricula. It focuses on the statistical techniques and methods of control and system optimization needed for the mathematical modeling, analysis, simulation, control and optimization of multivariable manufacturing processes. In four sections, it covers:

 Relevant mathematical methods, including random events, variables and processes, and their characteristics; estimation and confidence intervals; Bayes applications; correlation and regression analysis; statistical cluster analysis; and singular value decomposition for classification applications. Mathematical description of manufacturing processes, including static and dynamic models; model validation; confidence intervals for model parameters; principal component analysis; conventional and recursive least squares procedures; nonlinear least squares; and continuous-time, discrete-time, s-domain and Z-domain models. Control of manufacturing processes, including transfer function/transfer matrix models; state-variable models; methods of discrete-time classical control; state variable discrete-time control; state observers/estimators in control systems; methods of decoupling control; and methods of adaptive control. Methods and applications of system optimization, including unconstrained and constrained optimization; analytical and numerical optimization procedures; use of penalty functions; methods of linear programming; gradient methods; direct search methods; genetic optimization; methods and applications of dynamic programming; and applications to estimation, design, control, and planning.

Each section of the book will include end-of-chapter exercises, and the book will be suitable for any systems, electrical, chemical, or industrial engineering program, as it focuses on the processes themselves, and not on the product being manufactured.  Students will be able to obtain a mathematical model of any manufacturing process, to design a computer-based control system for a particular continuous manufacturing process, and be able to formulate an engineering problem in terms of optimization, as well as the ability to choose and apply the appropriate optimization technique.

This textbook is intended for an introductory graduate level on process control, taught in most engineering curricula. It focuses on the statistical techniques and methods of control and system optimization needed for the mathematical modeling, analysis, simulation, control and optimization of multivariable manufacturing processes. In four sections, it covers:Relevant mathematical methods, including random events, variables and processes, and their characteristics; estimation and confidence intervals; Bayes applications; correlation and regression analysis; statistical cluster analysis; and singular value decomposition for classification applications.Mathematical description of manufacturing processes, including static and dynamic models; model validation; confidence intervals for model parameters; principal component analysis; conventional and recursive least squares procedures; nonlinear least squares; and continuous-time, discrete-time, s-domain and Z-domain models.Control of manufacturing processes, including transfer function/transfer matrix models; state-variable models; methods of discrete-time classical control; state variable discrete-time control; state observers/estimators in control systems; methods of decoupling control; and methods of adaptive control.Methods and applications of system optimization, including unconstrained and constrained optimization; analytical and numerical optimization procedures; use of penalty functions; methods of linear programming; gradient methods; direct search methods; genetic optimization; methods and applications of dynamic programming; and applications to estimation, design, control, and planning.Each section of the book will include end-of-chapter exercises, and the book will be suitable for any systems, electrical, chemical, or industrial engineering program, as it focuses on the processes themselves, and not on the product being manufactured.  Students will be able to obtain a mathematical model of any manufacturing process, to design a computer-based control system for a particular continuous manufacturing process, and be able to formulate an engineering problem in terms of optimization, as well as the ability to choose and apply the appropriate optimization technique.

This volume contains the papers presented at the International Workshop "Autonomous Intelligent Systems: Agents and Data Mining" (AIS-ADM 2005) held in St. Petersburg, Russia, during June 6-8, 2005. The workshop was - ganized by the St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS) in cooperation with Binghamton U- versity (SUNY, USA) and the Web Intelligence Consortium. Autonomous Intelligent Systems (AIS) constitute an emerging class of int- ligent information systems integrating recent advances in various technologies of Arti?cial Intelligence. Modern AIS incorporate multi-agent and data mining systemsprovidinganewdimensionforfurtherprogressinintelligentinformation technology. AIS-ADM 2005 provided an international forum to multi-agent and data mining researchers. A total of 29 papers from 15 countries relating to various aspects of both theory and applications of multi-agent systems, data mining and their joint area were submitted to AIS-ADM 2005. Out of them 17 were selected as regular presentations.Three technical sessions were organized, namely: In- gration of Multi-agent and Data Mining Techniques; Ontology Issues and Web Mining; and Applications and Case Studies of the Integrated Technology. The panel discussion was devoted to the mutual enrichment and challenging pr- lems emerging in the joint area of research. The AIS-ADM 2005 program was enriched by six distinguished invited speakers: Nick Jennings, Chengqi Zhang, Mircea Negoita, Pericles Mitkas, Hai Zhuge and Leonid Perlovsky.

This book presents the refereed proceedings of the International Workshop on Mathematical Methods, Models, and Architectures for Network Security Systems, MMM-ACNS 2001, held in St. Petersburg in May 2001.The 24 revised full papers presented together with five invited contributions were carefully reviewed and selected from 36 submissions. The papers are organized in topical sections on network security systems: foundations, models and architectures; intrusion detection: foundations and models; access control, authentication, and authorization; and cryptography and steganography: mathematical basis, protocols, and applied methods.

This book presents the refereed proceedings of the International Workshop on Mathematical Methods, Models, and Architectures for Network Security Systems, MMM-ACNS 2001, held in St. Petersburg in May 2001.The 24 revised full papers presented together with five invited contributions were carefully reviewed and selected from 36 submissions. The papers are organized in topical sections on network security systems: foundations, models and architectures; intrusion detection: foundations and models; access control, authentication, and authorization; and cryptography and steganography: mathematical basis, protocols, and applied methods.

This volume contains papers presented at the Fourth International Workshop on Mathematical Methods, Models and Architectures for Computer Network Security (MMM-ACNS 2007) held in St. Petersburg, Russia, during September 13–15, 2007. The workshop was organized by the St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS) in cooperation with Binghamton University (SUNY, USA). The organizers are proud that the MMM-ACNS workshops hosted by the St. Petersburg Institute for Informatics and Automation in 2001, 2003 and 2005 evolved into a bi-annual series recognized in the professional community. These events not only demonstrated the keen interest of the participating researchers in the subject matter and the opportunity to present and disseminate individual achievements, but also promoted the spirit of cooperation, camaraderie, free exchange of ideas, and intellectually stimulating interaction between colleagues. Again, MMM-ACNS 2007 provided an international forum for sharing or- inal research results among specialists in fundamental and applied problems of computer network security. An important distinction of the conference was its focus on mathematical aspects of information and computer network security addressing the ever-increasing demands for secure computing and highly - pendable computer networks. A total of 56 papers from 18 countries related to signi?cant aspects of both theory and applications ofcomputer networkand informationsecurity weres- mitted to MMM-ACNS 2007. In total, 18 papers were selected for regular p- sentationsand 12 for short presentations(32 % of acceptance for full papers and 53 % for all papers).