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Author: Efundem Agboraw Publisher: Springer ISBN: 3319677535 Category : Business & Economics Languages : en Pages : 142
Book Description
With substantial risks arising from resource constraints on global growth, serious questions are being posed about how a scarcity of finite resources may impact global social and political fragility. The research which forms the core of this book focuses on how this scarcity will impact the financial sector, especially through insurance, pension and banking activities. The UK finance sector, which is considered to be amongst the most globalised, is placed under the microscope, and its approaches to food and oil are particularly noteworthy. Interviews with senior financial experts are analysed alongside more traditional quantitative economic analysis to explore potential future impacts, the scope of natural resource constraints and their impact on the economy.
Author: Efundem Agboraw Publisher: Springer ISBN: 3319677535 Category : Business & Economics Languages : en Pages : 142
Book Description
With substantial risks arising from resource constraints on global growth, serious questions are being posed about how a scarcity of finite resources may impact global social and political fragility. The research which forms the core of this book focuses on how this scarcity will impact the financial sector, especially through insurance, pension and banking activities. The UK finance sector, which is considered to be amongst the most globalised, is placed under the microscope, and its approaches to food and oil are particularly noteworthy. Interviews with senior financial experts are analysed alongside more traditional quantitative economic analysis to explore potential future impacts, the scope of natural resource constraints and their impact on the economy.
Author: Katharina Morik Publisher: Walter de Gruyter GmbH & Co KG ISBN: 3110785943 Category : Science Languages : en Pages : 506
Book Description
Machine learning is part of Artificial Intelligence since its beginning. Certainly, not learning would only allow the perfect being to show intelligent behavior. All others, be it humans or machines, need to learn in order to enhance their capabilities. In the eighties of the last century, learning from examples and modeling human learning strategies have been investigated in concert. The formal statistical basis of many learning methods has been put forward later on and is still an integral part of machine learning. Neural networks have always been in the toolbox of methods. Integrating all the pre-processing, exploitation of kernel functions, and transformation steps of a machine learning process into the architecture of a deep neural network increased the performance of this model type considerably. Modern machine learning is challenged on the one hand by the amount of data and on the other hand by the demand of real-time inference. This leads to an interest in computing architectures and modern processors. For a long time, the machine learning research could take the von-Neumann architecture for granted. All algorithms were designed for the classical CPU. Issues of implementation on a particular architecture have been ignored. This is no longer possible. The time for independently investigating machine learning and computational architecture is over. Computing architecture has experienced a similarly rampant development from mainframe or personal computers in the last century to now very large compute clusters on the one hand and ubiquitous computing of embedded systems in the Internet of Things on the other hand. Cyber-physical systems’ sensors produce a huge amount of streaming data which need to be stored and analyzed. Their actuators need to react in real-time. This clearly establishes a close connection with machine learning. Cyber-physical systems and systems in the Internet of Things consist of diverse components, heterogeneous both in hard- and software. Modern multi-core systems, graphic processors, memory technologies and hardware-software codesign offer opportunities for better implementations of machine learning models. Machine learning and embedded systems together now form a field of research which tackles leading edge problems in machine learning, algorithm engineering, and embedded systems. Machine learning today needs to make the resource demands of learning and inference meet the resource constraints of used computer architecture and platforms. A large variety of algorithms for the same learning method and, moreover, diverse implementations of an algorithm for particular computing architectures optimize learning with respect to resource efficiency while keeping some guarantees of accuracy. The trade-off between a decreased energy consumption and an increased error rate, to just give an example, needs to be theoretically shown for training a model and the model inference. Pruning and quantization are ways of reducing the resource requirements by either compressing or approximating the model. In addition to memory and energy consumption, timeliness is an important issue, since many embedded systems are integrated into large products that interact with the physical world. If the results are delivered too late, they may have become useless. As a result, real-time guarantees are needed for such systems. To efficiently utilize the available resources, e.g., processing power, memory, and accelerators, with respect to response time, energy consumption, and power dissipation, different scheduling algorithms and resource management strategies need to be developed. This book series addresses machine learning under resource constraints as well as the application of the described methods in various domains of science and engineering. Turning big data into smart data requires many steps of data analysis: methods for extracting and selecting features, filtering and cleaning the data, joining heterogeneous sources, aggregating the data, and learning predictions need to scale up. The algorithms are challenged on the one hand by high-throughput data, gigantic data sets like in astrophysics, on the other hand by high dimensions like in genetic data. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are applied to program executions in order to save resources. The three books will have the following subtopics: Volume 1: Machine Learning under Resource Constraints - Fundamentals Volume 2: Machine Learning and Physics under Resource Constraints - Discovery Volume 3: Machine Learning under Resource Constraints - Applications Volume 1 establishes the foundations of this new field (Machine Learning under Resource Constraints). It goes through all the steps from data collection, their summary and clustering, to the different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Several machine learning methods are inspected with respect to their resource requirements and how to enhance their scalability on diverse computing architectures ranging from embedded systems to large computing clusters.
Author: Christian Artigues Publisher: John Wiley & Sons ISBN: 1118623703 Category : Technology & Engineering Languages : en Pages : 235
Book Description
This title presents a large variety of models and algorithms dedicated to the resource-constrained project scheduling problem (RCPSP), which aims at scheduling at minimal duration a set of activities subject to precedence constraints and limited resource availabilities. In the first part, the standard variant of RCPSP is presented and analyzed as a combinatorial optimization problem. Constraint programming and integer linear programming formulations are given. Relaxations based on these formulations and also on related scheduling problems are presented. Exact methods and heuristics are surveyed. Computational experiments, aiming at providing an empirical insight on the difficulty of the problem, are provided. The second part of the book focuses on several other variants of the RCPSP and on their solution methods. Each variant takes account of real-life characteristics which are not considered in the standard version, such as possible interruptions of activities, production and consumption of resources, cost-based approaches and uncertainty considerations. The last part presents industrial case studies where the RCPSP plays a central part. Applications are presented in various domains such as assembly shop and rolling ingots production scheduling, project management in information technology companies and instruction scheduling for VLIW processor architectures.
Author: Rainer Kolisch Publisher: Springer Science & Business Media ISBN: 3642502962 Category : Business & Economics Languages : en Pages : 221
Book Description
This book introduces the field of resource-constrained project scheduling. State-of-the-art reviews of optimal and heuristic procedures are provided for classical project scheduling models. Furthermore, new models which are relevant for practical problem settings, are introduced. The main emphasis is on newly developed competitive heuristic methods. Contents: Introduction. - Description of the Problems.- Classification of Schedules.- Characterisation and Generation of Instances.- The Single-Mode Project Scheduling Problem.- The Multi-Mode Project Scheduling Problem.- Project Scheduling with Given Deadline.- Project Scheduling with Setup Times.- Applications to Production Management.- Concluding Remarks.- List of Notations.- List of Abbreviations.
Author: Eliyahu M. Goldratt Publisher: Routledge ISBN: 1351982117 Category : Business & Economics Languages : en Pages : 471
Book Description
Alex Rogo is a harried plant manager working ever more desperately to try and improve performance. His factory is rapidly heading for disaster. So is his marriage. He has ninety days to save his plant - or it will be closed by corporate HQ, with hundreds of job losses. It takes a chance meeting with a colleague from student days - Jonah - to help him break out of conventional ways of thinking to see what needs to be done. Described by Fortune as a 'guru to industry' and by Businessweek as a 'genius', Eliyahu M. Goldratt was an internationally recognized leader in the development of new business management concepts and systems. This 20th anniversary edition includes a series of detailed case study interviews by David Whitford, Editor at Large, Fortune Small Business, which explore how organizations around the world have been transformed by Eli Goldratt's ideas. The story of Alex's fight to save his plant contains a serious message for all managers in industry and explains the ideas which underline the Theory of Constraints (TOC) developed by Eli Goldratt. Written in a fast-paced thriller style, The Goal is the gripping novel which is transforming management thinking throughout the Western world. It is a book to recommend to your friends in industry - even to your bosses - but not to your competitors!
Author: Javier Larrosa Publisher: Springer ISBN: 3642194869 Category : Computers Languages : en Pages : 161
Book Description
This book constitutes the thoroughly refereed post-proceedings of the 14th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2009, held in Barcelona, Spain, in June 2009. The 9 revised full papers presented were carefully reviewed and selected for inclusion in this post-proceedings. The papers in this volume present original research results and applications of constraint solving and constraint logic programming in several domains. Among the issues addressed are solving argumentation frameworks, software consistency, modeling languages, static design routing, dynamic constraint satisfaction, and constraint-based modeling.
Author: Alexander Nareyek Publisher: Springer ISBN: 3540457461 Category : Computers Languages : en Pages : 187
Book Description
Autonomous agents have become a vibrant research and development topic in recent years attracting activity and attention from various areas. The basic agent concept incorporates proactive autonomous units with goal-directed-behaviour and communication capabilities. The book focuses on autonomous agents that can act in a goal directed manner under real time constraints and incomplete knowledge, being situated in a dynamic environment where resources may be restricted. To satisfy such complex requirements, the author improves, combines, and applies results from areas like planning, constraint programming, and local search. The formal framework developed is evaluated by application to the field of computer games, which fit the problem context very well since most of them are played in real time and provide a highly interactive environment where environmental situations are changing rapidly.
Author: Swaminathan Natarajan Publisher: Springer ISBN: 0585268703 Category : Computers Languages : en Pages : 193
Book Description
Real-time systems are now used in a wide variety of applications. Conventionally, they were configured at design to perform a given set of tasks and could not readily adapt to dynamic situations. The concept of imprecise and approximate computation has emerged as a promising approach to providing scheduling flexibility and enhanced dependability in dynamic real-time systems. The concept can be utilized in a wide variety of applications, including signal processing, machine vision, databases, networking, etc. For those who wish to build dynamic real-time systems which must deal safely with resource unavailability while continuing to operate, leading to situations where computations may not be carried through to completion, the techniques of imprecise and approximate computation facilitate the generation of partial results that may enable the system to operate safely and avert catastrophe. Audience: Of special interest to researchers. May be used as a supplementary text in courses on real-time systems.
Author: Thorsten Pieper Publisher: Springer ISBN: 3658255064 Category : Business & Economics Languages : en Pages : 288
Book Description
Thorsten Pieper explores the impact of innovation barriers along the user innovation process, in particular whether technological, social, legal and ownership barriers change the properties of user-developed products. This study roots from the “open innovation” research field and reveals insights from innovating users in “collaborative workspaces”. The results prove a hierarchical allocation of innovation barriers regarding their influence on the end-product and moderating influences of user innovators’ personal characteristics. The author discusses these insights and provides practical recommendations for more efficient promotion of user innovations and successful integration in corporate "co-creation" projects.
Author: Efundem Agboraw
Author: Efundem Agboraw
Author: Katharina Morik
Author: Mauro L. Baranzini
Author: Christian Artigues
Author: Rainer Kolisch
Author: Eliyahu M. Goldratt
Author: Javier Larrosa
Author: Alexander Nareyek
Author: Swaminathan Natarajan
Author: Thorsten Pieper