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Nowadays, agricultural-food system has been experiencing major changes which are driven mainly by recent developments in consumer preferences and attitudes, technological improvements, food safety issues and related regulations. The advanced agro-food sec
This textbook addresses the main economic principles required by agricultural economists involved in rural development. The principles of 'micro-economics' or 'price-theory' are of relevance to economists everywhere, but this book reinforces the message of their relevance for rural development by explaining the theory in the specific context of the agricultural and food sectors of developing countries. Hypothetical and actual empirical illustrations drawn almost exclusively from such countries distinguish this book from other economic principles texts that draw their examples almost invariably from industrialised countries, and also from books more oriented to the issue of rural development. The first half of the book deals with the underlying principles of production, supply and demand. These are essential tools for the study and management of the agricultural sector and food markets. In the second half, supply and demand are bought together into a chapter of equilibrium and exchange. This is followed by chapters on trade and the theory of economic welfare. In the final chapter it is shown that much of the material in the earlier chapters can be combined by agricultural economists into a system for analysing and comparing the effects of alternative agricultural policies. The ability of agricultural economics to provide a consistent framework for the analysis of policy problems thus enables it to make a key contribution to rural development.
This book covers the basic theory of how, what and when firms should produce to maximise profits. Based on the neoclassical theory of the firm presented in most general microeconomic textbooks, it extends the general treatment and focuses on the application of the theory to specific problems that the firm faces when making production decisions to maximise profits. Increasing level of government regulation and the use of specialised and often very expensive equipment in modern production motivates the following focus areas: 1) How to optimise production under restrictions., 2) Treatment of fixed inputs and the process of input fixation, 3) Optimisation of production over time, 4) Linear and Mixed Integer Programming as tools for optimisation in practice. This updated second edition includes a more comprehensive introduction to the theory of decision making under risk and uncertainty as well as a new chapter on how to use linear programming to generate the supply function of the firm.
Recently Geometric Programming has been applied to study a variety of problems in the analysis and design of communication systems from information theory and queuing theory to signal processing and network protocols. Geometric Programming for Communication Systems begins its comprehensive treatment of the subject by providing an in-depth tutorial on the theory, algorithms, and modeling methods of Geometric Programming. It then gives a systematic survey of the applications of Geometric Programming to the study of communication systems. It collects in one place various published results in this area, which are currently scattered in several books and many research papers, as well as to date unpublished results. Geometric Programming for Communication Systems is intended for researchers and students who wish to have a comprehensive starting point for understanding the theory and applications of geometric programming in communication systems.
This book is about resource allocation matters with the aim to further development thoughts and models on resource allocation applied to livestock production. It contains 18 chapters divided into 4 parts which discuss resources and resource allocation patterns, trade-offs, metabolic constraints to resource allocation and the process of homeorhesis with a special emphasis to homeorhesis during heat stress; the relationship between food intake and resources allocated to body maintenance, growth, reproduction and the immune response; the consequences of high production efficiency in pigs, poultry and dairy cattle and the consequences of improved production by means of biological engineering and options to include resource allocation matters in the breeding objective, animal welfare and in resource allocation modelling.
Summary Software Development Metrics is a handbook for anyone who needs to track and guide software development and delivery at the team level, such as project managers and team leads. New development practices, including "agile" methodologies like Scrum, have redefined which measurements are most meaningful and under what conditions you can benefit from them. This practical book identifies key characteristics of organizational structure, process models, and development methods so that you can select the appropriate metrics for your team. It describes the uses, mechanics, and common abuses of a number of metrics that are useful for steering and for monitoring process improvement. The insights and techniques in this book are based entirely on field experience. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book When driving a car, you are less likely to speed, run out of gas, or suffer engine failure because of the measurements the car reports to you about its condition. Development teams, too, are less likely to fail if they are measuring the parameters that matter to the success of their projects. This book shows you how. Software Development Metrics teaches you how to gather, analyze, and effectively use the metrics that define your organizational structure, process models, and development methods. The insights and examples in this book are based entirely on field experience. You'll learn practical techniques like building tools to track key metrics and developing data-based early warning systems. Along the way, you'll learn which metrics align with different development practices, including traditional and adaptive methods. No formal experience with developing or applying metrics is assumed. What's Inside Identify the most valuable metrics for your team and process Differentiate "improvement" from "change" Learn to interpret and apply the data you gather Common pitfalls and anti-patterns About the Author Dave Nicolette is an organizational transformation consultant, team coach, and trainer. Dave is active in the agile and lean software communities. Table of Contents Making metrics useful Metrics for steering Metrics for improvement Putting the metrics to work Planning predictability Reporting outward and upward
An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.