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Statistical Inference from High Dimensional Data
• Real-world problems can be high-dimensional, complex, and noisy • More data does not imply more information • Different approaches deal with the so-called curse of dimensionality to reduce irrelevant information • A process with multidimensional information is not necessarily easy to interpret nor process • In some real-world applications, the number of elements of a class is clearly lower than the other. The models tend to assume that the importance of the analysis belongs to the majority class and this is not usually the truth • The analysis of complex diseases such as cancer are focused on more-than-one dimensional omic data • The increasing amount of data thanks to the reduction of cost of the high-throughput experiments opens up a new era for integrative data-driven approaches • Entropy-based approaches are of interest to reduce the dimensionality of high-dimensional data
Wildlife Habitat Connectivity Across European Highways
The Federal Highway Administration (FHWA), American Association of State Highway and Transportation Officials (AASHTO), and the National Cooperative Highway Research Program (NCHRP) sponsored an international technology scan to learn what actions are being taken in Europe to address habitat and wildlife issues. A delegation of federal, State, and conservation group representatives visited Slovenia, Switzerland, Germany, France, and the Netherlands to observe and document efforts in Europe. As a result of the trip, the team formed conclusions and recommendations for U.S. applications in the areas of policy, communications, guidance manuals, and research.
The New Records
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The Border Dispute Between Croatia and Slovenia
This book re-constructs the evolution of the border conflict between Croatia and Slovenia. The aim is to reveal the processes at work, the historical and contemporary circumstances, and the strategies and motives of the actors involved. The book highlights the roles of the European Union and of judicial third parties in the management of the conflict. Further, it considers the precedent-setting value of the Slovenian-Croatian conflict, the attempts at its resolution, and what they mean for the ongoing and prospective EU enlargement in South East Europe. Internal documents and interviews are at the heart of this process-tracing analysis, which discusses the third-party roles of the European Commission and the EU Council Presidency in 2008/2009 as a mediator-facilitator in the drafting stages of the arbitration agreement, and the judicial work of the arbitration tribunal and the EU Court of Justice. Lastly, the book offers policy recommendations on how to strengthen dispute resolution and solve current bilateral issues in the EU accession process.
The Opera Directory
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Gramophone
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Memristor and Memristive Neural Networks
This book covers a range of models, circuits and systems built with memristor devices and networks in applications to neural networks. It is divided into three parts: (1) Devices, (2) Models and (3) Applications. The resistive switching property is an important aspect of the memristors, and there are several designs of this discussed in this book, such as in metal oxide/organic semiconductor nonvolatile memories, nanoscale switching and degradation of resistive random access memory and graphene oxide-based memristor. The modelling of the memristors is required to ensure that the devices can be put to use and improve emerging application. In this book, various memristor models are discussed, from a mathematical framework to implementations in SPICE and verilog, that will be useful for the practitioners and researchers to get a grounding on the topic. The applications of the memristor models in various neuromorphic networks are discussed covering various neural network models, implementations in A/D converter and hierarchical temporal memories.
Artificial Neural Networks
Artificial neural networks may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications. The purpose of this book is to provide recent advances of artificial neural networks in industrial and control engineering applications. The book begins with a review of applications of artificial neural networks in textile industries. Particular applications in textile industries follow. Parts continue with applications in materials science and industry such as material identification, and estimation of material property and state, food industry such as meat, electric and power industry such as batteries and power systems, mechanical engineering such as engines and machines, and control and robotic engineering such as system control and identification, fault diagnosis systems, and robot manipulation. Thus, this book will be a fundamental source of recent advances and applications of artificial neural networks in industrial and control engineering areas. The target audience includes professors and students in engineering schools, and researchers and engineers in industries.
Artificial Neural Networks for Engineering Applications
Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications.
