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This new monograph provides a comprehensive overview of the state of the art of the automation of laboratory processes in analytical chemistry. The topics have been chosen according to such criteria as the degree of consolidation, scope of application and most promising trends. The first part of the book begins with the basic principles behind the automation of laboratory processes, then describes automatic systems for sampling and sample treatment. In the second part the principal types of analysers are discussed: continuous, batch and robotic. The third part is devoted to the automation of analytical instrumentation: spectroscopic, electroanalytical and chromatographic techniques and titrators. The last part presents some examples of the application of automation to clinical chemistry, environmental pollution monitoring and industrial process control. The text is supplemented by 290 figures and 800 literature references. It is written primarily for scientists directly involved in laboratory work and those responsible for industrial planning and control, research centres, etc. It will also be of interest to analytical chemists wishing to update their knowledge in this area, and will be of especial interest to scientists directly related to environmental sciences or clinical chemistry.
This book presents a collection of automated methods that are useful for different aspects of fault analysis in cryptography. The first part focuses on automated analysis of symmetric cipher design specifications, software implementations, and hardware circuits. The second part provides automated deployment of countermeasures. The third part provides automated evaluation of countermeasures against fault attacks. Finally, the fourth part focuses on automating fault attack experiments. The presented methods enable software developers, circuit designers, and cryptographers to test and harden their products.
Written with practical experience of many of the systems it describes, this book provides coverage of all aspects of automation, from sample preparation, right through to data processing. The book also includes Coverage Of Robotics Computer Applications And Process Control, And The scope and limitations of each development are discussed. Three prac
A new approach to the analysis of satellite imagery is presented. The central part of this approach is an algorithm which compresses information stored in the ordinary six or eight bits per picture element into only one bit. The quality of this compression is demonstrated by examples of its application to high resolution visual imagery. Both visual inspection and rms difference criterion are used for this evaluation. There are four objectives of this report which are: to review the status of processing techniques which remove redundant information, to show the need for redundance reduction in the processing of satellite images, to present the development of an algorithm for reducing it, and to show results obtained by application of the algorithm to visual imagery. Also, comments are made on needed developments of the technique and its potential application to problems of analysis of satellite imagery data. (Author).
This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.
Spectral analysis requires subjective decisions which influence the final estimate and mean that different analysts can obtain different results from the same stationary stochastic observations. Statistical signal processing can overcome this difficulty, producing a unique solution for any set of observations but that is only acceptable if it is close to the best attainable accuracy for most types of stationary data. This book describes a method which fulfils the above near-optimal-solution criterion, taking advantage of greater computing power and robust algorithms to produce enough candidate models to be sure of providing a suitable candidate for given data.
A survey of the stability analysis techniques for automatically controlled aircraft is presented. The survey is limited to techniques commonly applied to linear, continuous-control systems wherein the difference between the output and input quantities is measured continuously and is used in the operation of the system (a closed-loop system). An evaluation of the techniques, based on the kind and amount of information derivable, is included. An illustrative example is also presented to demonstrate the calculations involved for a typical aircraft-autopilot combination.