Software Similarity and Classification

Clustering is an important unsupervised classification technique where data points are grouped such that points that are similar in some sense belong to the same cluster. Cluster analysis is a complex

Software similarity and classification is an emerging topic with wide applications. It is applicable to the areas of malware detection, software theft detection, plagiarism detection, and software clo

Similarity and analogy are fundamental in human cognition. They are crucial for recognition and classification, and have been associated with scientific discovery and creativity. Successful learning is generally less dependent on the memorization of isolated facts and abstract rules than it is on the ability to identify relevant bodies of knowledge already stored as the starting point for new learning. Similarity and analogy play an important role in this process - a role that in recent years has received much attention from cognitive scientists. Any adequate understanding of similarity and analogy requires the integration of theory and data from diverse domains. This interdisciplinary volume explores current developments in research and theory from psychological, computational, and educational perspectives, and considers their implications for learning and instruction. Well-known cognitive scientists examine the psychological processes involved in reasoning by similarity and analogy,

The book explains the classification of a set of Walsh functions into distinct self-similar groups and subgroups, where the members of each subgroup possess distinct self-similar structures. The obser

As the first book about software culture, this book discusses software culture from three perspectives including historical perspective, the classification of software and software applications. This

This book focuses on the development, maintenance, and implementation of product-line variability. It features a broad classification of tools and techniques for all stages of the development process

This book discusses machine learning algorithms, such as artificial neural networks of different architectures, statistical learning theory, and Support Vector Machines used for the classification and

Computer Manual to Accompany Pattern Classification and its associated MATLAB software is an excellent companion to Duda: Pattern Classfication, 2nd ed, (DH&S). The code contains all algorithms descri

The thrilling untold story of the cyberweapons market―the most secretive, invisible, government-backed market on earth―and a terrifying first look at a new kind of global warfare.Zero day: a software bug that allows a hacker to break into your devices and move around undetected. One of the most coveted tools in a spy's arsenal, a zero day has the power to silently spy on your iPhone, dismantle the safety controls at a chemical plant, alter an election, and shut down the electric grid (just ask Ukraine).For decades, under cover of classification levels and non-disclosure agreements, the United States government became the world’s dominant hoarder of zero days. U.S. government agents paid top dollar―first thousands, and later millions of dollars― to hackers willing to sell their lock-picking code and their silence. Then the United States lost control of its hoard and the market. Now those zero days are in the hands of hostile nations and mercenaries who do not care if your vote goes miss

This book explores the fundamentals of computer music and functional programming through the Haskell programming language. Functional programming is typically considered difficult to learn. This introduction in the context of creating music will allow students and professionals with a musical inclination to leverage their experience to help understand concepts that might be intimidating in more traditional computer science settings. Conversely, the book opens the door for programmers to interact with music by using a medium that is familiar to them. Readers will learn how to use the Euterpea library for Haskell (http://www.euterpea.com) to represent and create their own music with code, without the need for other music software. The book explores common paradigms used in algorithmic music composition, such as stochastic generation, musical grammars, self-similarity, and real-time interactive systems. Other topics covered include the basics of signal-based systems in Haskell, sound synt

This book introduces in a systematic manner a general nonparametric theory of statistics on manifolds, with emphasis on manifolds of shapes. The theory has important and varied applications in medical diagnostics, image analysis, and machine vision. An early chapter of examples establishes the effectiveness of the new methods and demonstrates how they outperform their parametric counterparts. Inference is developed for both intrinsic and extrinsic Fréchet means of probability distributions on manifolds, then applied to shape spaces defined as orbits of landmarks under a Lie group of transformations - in particular, similarity, reflection similarity, affine and projective transformations. In addition, nonparametric Bayesian theory is adapted and extended to manifolds for the purposes of density estimation, regression and classification. Ideal for statisticians who analyze manifold data and wish to develop their own methodology, this book is also of interest to probabilists, mathematicia

Modern astronomical research is beset with a vast range of statistical challenges, ranging from reducing data from megadatasets to characterizing an amazing variety of variable celestial objects or testing astrophysical theory. Linking astronomy to the world of modern statistics, this volume is a unique resource, introducing astronomers to advanced statistics through ready-to-use code in the public domain R statistical software environment. The book presents fundamental results of probability theory and statistical inference, before exploring several fields of applied statistics, such as data smoothing, regression, multivariate analysis and classification, treatment of nondetections, time series analysis, and spatial point processes. It applies the methods discussed to contemporary astronomical research datasets using the R statistical software, making it invaluable for graduate students and researchers facing complex data analysis tasks. A link to the author's website for this book ca

This book introduces in a systematic manner a general nonparametric theory of statistics on manifolds, with emphasis on manifolds of shapes. The theory has important and varied applications in medical diagnostics, image analysis, and machine vision. An early chapter of examples establishes the effectiveness of the new methods and demonstrates how they outperform their parametric counterparts. Inference is developed for both intrinsic and extrinsic Fréchet means of probability distributions on manifolds, then applied to shape spaces defined as orbits of landmarks under a Lie group of transformations - in particular, similarity, reflection similarity, affine and projective transformations. In addition, nonparametric Bayesian theory is adapted and extended to manifolds for the purposes of density estimation, regression and classification. Ideal for statisticians who analyze manifold data and wish to develop their own methodology, this book is also of interest to probabilists, mathematicia

The interdisciplinary nature of bioinformatics presents a research challenge in integrating concepts, methods, software and multiplatform data. Although there have been rapid developments in new technology and an inundation of statistical methods for addressing other types of high-throughput data, such as proteomic profiles that arise from mass spectrometry experiments. This book discusses the development and application of Bayesian methods in the analysis of high-throughput bioinformatics data that arise from medical, in particular, cancer research, as well as molecular and structural biology. The Bayesian approach has the advantage that evidence can be easily and flexibly incorporated into statistical methods. A basic overview of the biological and technical principles behind multi-platform high-throughput experimentation is followed by expert reviews of Bayesian methodology, tools and software for single group inference, group comparisons, classification and clustering, motif discov

Bridge the gap between theoretical education and practical work experience with this hands-on guide to GNSS, which features: • A clear, practical presentation of GNSS theory, with emphasis on GPS and GLONASS • All the essential theory behind software receivers and signal simulators • Key applications in navigation and geophysics, including INS aiding, scintillation monitoring, earthquake studies and more • Physical explanations of various important phenomena, including the similarity of code delay and phase advance of GNSS signals, and negative cross-correlation between scintillation intensity and phase variations. Whether you are a practising engineer, a researcher or a student, you will gain a wealth of insights from the authors' twenty-five years of experience. You can explore numerous practical examples and case studies and get hands-on user experience with a bundled real-time software receiver, signal simulator and a set of signal data, enabling you to create your own GNSS lab fo

Functional magnetic resonance imaging (fMRI) has become the most popular method for imaging brain function. Handbook of Functional MRI Data Analysis provides a comprehensive and practical introduction to the methods used for fMRI data analysis. Using minimal jargon, this book explains the concepts behind processing fMRI data, focusing on the techniques that are most commonly used in the field. This book provides background about the methods employed by common data analysis packages including FSL, SPM and AFNI. Some of the newest cutting-edge techniques, including pattern classification analysis, connectivity modeling and resting state network analysis, are also discussed. Readers of this book, whether newcomers to the field or experienced researchers, will obtain a deep and effective knowledge of how to employ fMRI analysis to ask scientific questions and become more sophisticated users of fMRI analysis software.

First published in 1976, Professor Corner's study is a major work of botanical scholarship and reference. In these two volumes the author shows how important the seed is in classification. Systems of ordinal classification based on the flower are potentially misleading in as much as floral similarity is often the effect of polyphyletic convergence. A different system of classification based on the seed is outlined. The work is the result of more than thirty years' collection and study of seeds, particularly in the tropics. The text in the first volume has five introductory chapters leading up to the arillate seed. There then follows in alphabetical order concise descriptions of the seed in families and certain of their genera. The second volume contains more than 600 original illustrations made by the author. The two volumes are unique sources of teaching and reference material for botanical institutions throughout the world.

First published in 1976, Professor Corner's study is a major work of botanical scholarship and reference. The most unsatisfactory part of the classification of dicotyledons is the arrangement of their families into orders. In these volumes the author shows how important the seed is in classification. Systems of ordinal classification based on the flower are potentially misleading in as much as floral similarity is often the effect of polyphyletic convergence. A different system of classification based on the seed is outlined. The work is the result of more than thirty years' collection and study of seeds, particularly in the tropics. The account is published in two volumes. The text in this first volume has five introductory chapters leading up to the nature of the primitive arillate seed. There then follows in alphabetical order concise descriptions of the seed in families and certain of their genera. The second volume contains more than 600 original illustrations made by the author.

First published in 1976, Professor Corner's study is a major work of botanical scholarship and reference. The most unsatisfactory part of the classification of dicotyledons is the arrangement of their families into orders. In these volumes the author shows how important the seed is in classification. Systems of ordinal classification based on the flower are potentially misleading in as much as floral similarity is often the effect of polyphyletic convergence. A different system of classification based on the seed is outlined. The work is the result of more than thirty years' collection and study of seeds, particularly in the tropics. The account is published in two volumes. The text in the first volume has five introductory chapters leading up to the nature of the primitive arillate seed. There then follows in alphabetical order concise descriptions of the seed in families and certain of their genera. This second volume contains more than 600 original illustrations made by the author.

In order to help people with a mental illness it is important to be able to understand and measure the severity of the experiences that they find distressing and disabling and which can affect their behaviour. SCAN is a form of interview, found acceptable to patients, which provides a detailed and accurate picture of 'mental state'. When analysed by computer it provides a diagnosis that is comparable wherever the system is used. The 9th edition of the Present State Examination (PSE-9) was published in 1974 and served to link the two main approaches to the description and classification of psychological problems. PSE-10/SCAN builds on the experience of extensive tests using PSE-9. It retains the main features of PSE-9 and links together the two international classification systems, ICD-10 and DSM-IV. This reference manual is a companion to the SCAN interview schedule and software. It describes the rationale and development of the system and provides a valuable introduction to its uses.

The interdisciplinary nature of bioinformatics presents a research challenge in integrating concepts, methods, software and multiplatform data. Although there have been rapid developments in new technology and an inundation of statistical methods for addressing other types of high-throughput data, such as proteomic profiles that arise from mass spectrometry experiments. This book discusses the development and application of Bayesian methods in the analysis of high-throughput bioinformatics data that arise from medical, in particular, cancer research, as well as molecular and structural biology. The Bayesian approach has the advantage that evidence can be easily and flexibly incorporated into statistical methods. A basic overview of the biological and technical principles behind multi-platform high-throughput experimentation is followed by expert reviews of Bayesian methodology, tools and software for single group inference, group comparisons, classification and clustering, motif discov

In order to help people with a mental illness it is important to be able to understand and measure the severity of the experiences that they find distressing and disabling and which can affect their behaviour. SCAN is a form of interview, found acceptable to patients, which provides a detailed and accurate picture of 'mental state'. When analysed by computer it provides a diagnosis that is comparable wherever the system is used. The 9th edition of the Present State Examination (PSE-9) was published in 1974 and served to link the two main approaches to the description and classification of psychological problems. PSE-10/SCAN builds on the experience of extensive tests using PSE-9. It retains the main features of PSE-9 and links together the two international classification systems, ICD-10 and DSM-IV. This reference manual is a companion to the SCAN interview schedule and software. It describes the rationale and development of the system and provides a valuable introduction to its uses.

Computer Manual (MATHEMATICA version) to accompany Pattern Classification, Third Edition, and its associated software contains all the MATHEMATICA code for the dynamic figures in the electronic versio

Regression and classification methods based on similarity of the input to stored examples have not been widely used in applications involving very large sets of high-dimensional data. Recent advances