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Lecture Notes In Public Budgeting And Financial Management

This lecture notes provides an overview of budgeting and financial management in the public and non-profit sectors. Fundamental concepts and practices of budgeting, financial management and public finance are introduced, with special emphasis on state and local government budgeting and financial management in the United States. The objectives of courses in Public Budgeting and this title are to teach the basic concepts and nomenclature of public finance, to develop an understanding of budget processes as well as the sources and uses of public revenues, and to make relatively simple, but useful computations in an intelligent way. Key course learning outcomes include the abilities to: There are no indispensable pre-requisites by the reader, and it has been designed for students from a wide variety of backgrounds and undergraduate majors. Although this works well as an introductory text to a broader public administration curriculum, it also can make sense for students to take after some more basic courses in economics, policy analysis, and public organizations. Issues of tax incidence and the effect of taxes on economic efficiency can be covered in greater depth.

Although this works well as an introductory text to a broader public administration curriculum, it also can make sense for students to take after some more basic courses in economics, policy analysis, and public organizations.

Managing Customer Value

One Stage at a Time

This book is written for students - as well as employees of organizations - who have some previous exposure to principles of marketing. Its main objectives are to introduce the key marketing principles that govern the interactions between consumers and the goods and services being offered to them, to show how these principles can be used to gain a deeper understanding of the consumer's decision-making cycle, and to apply this knowledge in developing micro-marketing tactics. In doing so, the book offers an alternative perspective to the general practice of marketing products to consumers. Instead of applying the principles of mass marketing to a general group of consumers with similar characteristics, it aims to capture the right consumer at the right time. This is achieved by gaining a deep understanding of consumers' purchasing behavior as they progress through different stages of affiliation with the product or service. These stages are simply a set of thoughts, experiences and feelings that consumers encounter when faced with a purchase decision. Therefore, the major unifying theme between all the observable consumer behaviors and marketing tactics is micro-marketing.

This book is written for students - as well as employees of organizations - who have some previous exposure to principles of marketing.

Changes and Disturbance in Tropical Rainforest in South-East Asia

Views on the dynamics of tropical forests are changing rapidly with the recognition that their environment is variable on the decadal to century scale. Fluctuating climatic conditions partly determine tropical forest structure, species composition and dynamics. Tropical communities are also highly contingent in space and time with respect to site and historical factors. Tropical forests have experienced to some degree this disturbance regime in the past, but climatologists are now predicting increasingly frequent extreme events in the new century. The combination of increasing deforestation and land-use conversion by man plus an increasingly variable environment means a situation that could be very difficult to manage.

Fluctuating climatic conditions partly determine tropical forest structure, species composition and dynamics. Tropical communities are also highly contingent in space and time with respect to site and historical factors.

Advances in Data Mining and Modeling

Data mining and data modeling are hot topics and are under fast development. Because of their wide applications and rich research contents, many practitioners and academics are attracted to work in these areas. With a view to promoting communication and collaboration among the practitioners and researchers in Hong Kong, a workshop on data mining and modeling was held in June 2002. Prof Ngaiming Mok, Director of the Institute of Mathematical Research, The University of Hong Kong, and Prof Tze Leung Lai (Stanford University), C V Starr Professor of the University of Hong Kong, initiated the workshop. This book contains selected papers presented at the workshop. The papers fall into two main categories: data mining and data modeling. Data mining papers deal with pattern discovery, clustering algorithms, classification and practical applications in the stock market. Data modeling papers treat neural network models, time series models, statistical models and practical applications. Contents:Data Mining:Algorithms for Mining Frequent Sequences (B Kao & M-H Zhang)Cluster Analysis Using Unidimensional Scaling (P-L Leung et al.)From Associated Implication Networks to Intermarket Analysis (P C-W Tse & J-M Liu)Automating Technical Analysis (P L-H Yu et al.)Data Modeling:Learning Sunspot Series Dynamics by Recurrent Neural Networks (L-K Li)Bond Risk and Return in the SSE (L-Z Fan)Mining Loyal Customers: A Practical Use of the Repeat Buying Theory (H-P Lo et al.)and other papers Readership: Graduate students, researchers and practitioners in data mining, data modeling, engineering and computer science. Keywords:Data Mining;Data Modeling;Classification;Clustering;Time Series;Markov Model;Neural Networks;Stock Applications

This book contains selected papers presented at the workshop. The papers fall into two main categories: data mining and data modeling.

Decomposition Methodology for Knowledge Discovery and Data Mining

Theory and Applications

Data Mining is the science and technology of exploring data in order to discover previously unknown patterns. It is a part of the overall process of Knowledge Discovery in Databases (KDD). The accessibility and abundance of information today makes data mining a matter of considerable importance and necessity. This book provides an introduction to the field with an emphasis on advanced decomposition methods in general data mining tasks and for classification tasks in particular. The book presents a complete methodology for decomposing classification problems into smaller and more manageable sub-problems that are solvable by using existing tools. The various elements are then joined together to solve the initial problem.The benefits of decomposition methodology in data mining include: increased performance (classification accuracy); conceptual simplification of the problem; enhanced feasibility for huge databases; clearer and more comprehensible results; reduced runtime by solving smaller problems and by using parallel/distributed computation; and the opportunity of using different techniques for individual sub-problems.

This book provides an introduction to the field with an emphasis on advanced decomposition methods in general data mining tasks and for classification tasks in particular.

Data Mining with Decision Trees

Theory and Applications

This is the first comprehensive book dedicated entirely to the field of decision trees in data mining and covers all aspects of this important technique.Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining, the science and technology of exploring large and complex bodies of data in order to discover useful patterns. The area is of great importance because it enables modeling and knowledge extraction from the abundance of data available. Both theoreticians and practitioners are continually seeking techniques to make the process more efficient, cost-effective and accurate. Decision trees, originally implemented in decision theory and statistics, are highly effective tools in other areas such as data mining, text mining, information extraction, machine learning, and pattern recognition. This book invites readers to explore the many benefits in data mining that decision trees offer: Self-explanatory and easy to follow when compacted Able to handle a variety of input data: nominal, numeric and textual Able to process datasets that may have errors or missing values High predictive performance for a relatively small computational effort Available in many data mining packages over a variety of platforms Useful for various tasks, such as classification, regression, clustering and feature selection

This is the first comprehensive book dedicated entirely to the field of decision trees in data mining and covers all aspects of this important technique.Decision trees have become one of the most powerful and popular approaches in knowledge ...

Data Mining in Time Series Databases

Adding the time dimension to real-world databases produces Time Series Databases (TSDB) and introduces new aspects and difficulties to data mining and knowledge discovery. This book covers the state-of-the-art methodology for mining time series databases. The novel data mining methods presented in the book include techniques for efficient segmentation, indexing, and classification of noisy and dynamic time series. A graph-based method for anomaly detection in time series is described and the book also studies the implications of a novel and potentially useful representation of time series as strings. The problem of detecting changes in data mining models that are induced from temporal databases is additionally discussed. Contents: A Survey of Recent Methods for Efficient Retrieval of Similar Time Sequences (H M Lie); Indexing of Compressed Time Series (E Fink & K Pratt); Boosting Interval-Based Literal: Variable Length and Early Classification (J J Rodriguez Diez); Segmenting Time Series: A Survey and Novel Approach (E Keogh et al.); Indexing Similar Time Series under Conditions of Noise (M Vlachos et al.); Classification of Events in Time Series of Graphs (H Bunke & M Kraetzl); Median Strings--A Review (X Jiang et al.); Change Detection in Classfication Models of Data Mining (G Zeira et al.). Readership: Graduate students, reseachers and practitioners in the fields of data mining, machine learning, databases and statistics.

This book covers the state-of-the-art methodology for mining time series databases.

Dynamics and Mission Design Near Libration Points

Fundamentals - The Case of Triangular Libration Points

This book studies several problems related to the analysis of planned or possible spacecraft missions. It is divided into four chapters. The first chapter is devoted to the computation of quasiperiodic solutions for the motion of a spacecraft near the equilateral points of the Earth-Moon system. The second chapter gives a complete description of the orbits near the collinear point, L 1, between the Earth and the Sun in the restricted three-body problem (RTBP) model. In the third chapter, methods are developed to compute the nominal orbit and to design and test the control strategy for the qua

The periods found are equal to the period of revolution of the Sun in the Earth-
Moon synodical system and to three times this period. The period must be a
multiple of the period of revolution. The bicircular problem is far from the real one.

Input-output Economics

Theory and Applications : Featuring Asian Economies

Thijs ten Raa, author of the acclaimed text The Economics of InputOCoOutput Analysis, now takes the reader to the forefront of the field. This volume collects and unifies his and his co-authors'' research papers on national accounting, InputOCoOutput coefficients, economic theory, dynamic models, stochastic analysis, and performance analysis. The research is driven by the task to analyze national economies. The final part of the book scrutinizes the emerging Asian economies in the light of international competition. Sample Chapter(s). Introduction (45 KB). Chapter 1: National Accounts, Planning and Prices (108 KB). Contents: National Accounts: National Accounts, Planning and Prices; Commodity and Sector Classifications in Linked Systems of National Accounts; Accounting or Technical Coefficients: The Choice of Model in the Construction of InputOCoOutput Coefficients Matrices; The Extraction of Technical Coefficients from Input and Output Data; Neoclassical and Classical Connections: On the Methodology of InputOCoOutput Analysis; The Substitution Theorem; Dynamic InputOCoOutput Analysis: Dynamic InputOCoOutput Analysis with Distributed Activities; Applied Dynamic InputOCoOutput with Distributed Activities; Stochastic InputOCoOutput Analysis: Primary Versus Secondary Production Techniques in US Manufacturing; Stochastic Analysis of InputOCoOutput Multipliers on the Basis of Use and Make Tables; Performance Analysis: A Neoclassical Analysis of TFP Using InputOCoOutput Prices; Competition and Performance: The Different Roles of Capital and Labor; The Canadian Economy: A General Equilibrium Analysis of the Evolution of Canadian Service Productivity; The Location of Comparative Advantages on the Basis of Fundamentals Only; Asian Economies: Competitive Pressures on China: Income Inequality and Migration; Competitive Pressure on the Indian Households: A General Equilibrium Approach; and other papers. Readership: Economists at research institutes and universities, national accountants, graduate students in economics, and trade policy analysts."

This volume collects and unifies his and his co-authors'' research papers on national accounting, InputOCoOutput coefficients, economic theory, dynamic models, stochastic analysis, and performance analysis.

Steps Towards a Unified Basis for Scientific Models and Methods

Culture, in fact, also plays an important role in science which is, per se, a multitude of different cultures. The book attempts to build a bridge across three cultures: mathematical statistics, quantum theory and chemometrical methods. Of course, these three domains should not be taken as equals in any sense. But the book holds the important claim that it is possible to develop a common language which, at least to a certain extent, can create direct links and build bridges. From this point of departure, the book will be of interest to the following three types of scientists OCo statisticians, quantum physicists and chemometricians OCo and in particular, statisticians and physicists who are interested in interdisciplinary research. Written at a level that is accessible to general readers, not only the academics, the book will appeal to graduate students and mathematically educated persons of all disciplines as well as philosophers, pure and applied mathematicians, and the general public. Sample Chapter(s). Chapter 1: The Basic Elements (1,433 KB). Contents: The Basic Elements; Statistical Theory and Practice; Statistical Inference Under Symmetry; The Transition from Statistics to Quantum Theory; Quantum Mechanics from a Statistical Basis; Further Development of Quantum Mechanics; Decisions in Statistics; Multivariate Data Analysis and Statistics; Quantum Mechanics and the Diversity of Concepts. Readership: Graduate students and researchers in the field of statistics and mathematical physics."

8.1 Introduction In recent years there has been a large scientific activity
connected to the development of data-analytic methods which at first sight seem
to have little or no connection to traditional statistics. Some of these methods
have been ...