Olives and Olive Oil in Health and Disease Prevention

Author: Victor R. Preedy,Ronald Ross Watson

Publisher: Academic Press

ISBN: 9780080922201

Category: Technology & Engineering

Page: 1520

View: 3029

Long used in sacred ceremonies and associated with good health, the nutritional and health promoting benefits of olives and olive oils have been proven by an ever-increasing body of science. From cardiovascular benefits to anti-microbial, anti-cancer, antioxidant activity and effects on macrophages and aptoptosis to cellular and pathophysiollogical process, olives and olive oils are proving important in many healthful ways. For example, reactive components in olive oils or olive oil by-products have now been isolated and identified. These include tyrosol, hydroxytyrosol, 3,4-dihydroxyphenyl acetic acid elenolic acid and oleuropein. Oleic acid is the main monosaturated fatty acid of olive oil. These have putative protective effects and modulate the biochemistry of a variety of cell types including those of the vascular system. Some but not all components have been characterised by their putative pharmacological properties. It is possible that usage of these aforementioned products may have beneficial application in other disease. However, in order for this cross-fertilization to take place, a comprehensive understanding of olives and olive oils is required. Finding this knowledge in a single volume provides a key resource for scientists in a variety of food an nutritional roles. Key Features: * Explores olives and olive oil from their general aspects to the detailed level of important micro-and micronutrients * Includes coverage of various methodologies for analysis to help scientists and chemists determine the most appropriate option for their own studies, including those of olive-related compounds in other foods * Relates, in a single volume resource, information for food and nutritional chemists, pharmaceutical scientists, nutritionists and dieticians * Presents information in three key categories: General aspects of olives an olive oils; Nutritional, pharmacological and metabolic properties of olives and olive oil; Specific components of olive oil and their effects on tissue and body systems

Progress in Pattern Recognition 1

Author: L.N. Kanal,A. Rosenfeld

Publisher: Elsevier

ISBN: 1483295893

Category: Computers

Page: 395

View: 4944

Progress in Pattern Recognition 1

Advances in Pattern Recognition - ICAPR 2001

Second International Conference Rio de Janeiro, Brazil, March 11-14, 2001 Proceedings

Author: Sameer Singh,Nabeel Murshed,Walter Kropatsch

Publisher: Springer

ISBN: 3540447326

Category: Computers

Page: 482

View: 6258

The paper is organized as follows: In section 2, we describe the no- orientation-discontinuity interfering model based on a Gaussian stochastic model in analyzing the properties of the interfering strokes. In section 3, we describe the improved canny edge detector with an ed- orientation constraint to detect the edges and recover the weak ones of the foreground words and characters; In section 4, we illustrate, discuss and evaluate the experimental results of the proposed method, demonstrating that our algorithm significantly improves the segmentation quality; Section 5 concludes this paper. 2. The norm-orientation-discontinuity interfering stroke model Figure 2 shows three typical samples of original image segments from the original documents and their magnitude of the detected edges respectively. The magnitude of the gradient is converted into the gray level value. The darker the edge is, the larger is the gradient magnitude. It is obvious that the topmost strong edges correspond to foreground edges. It should be noted that, while usually, the foreground writing appears darker than the background image, as shown in sample image Figure 2(a), there are cases where the foreground and background have similar intensities as shown in Figure 2(b), or worst still, the background is more prominent than the foreground as in Figure 2(c). So using only the intensity value is not enough to differentiate the foreground from the background. (a) (b) (c) (d) (e) (f)

Pattern Recognition

A Quality of Data Perspective

Author: Wladyslaw Homenda,Witold Pedrycz

Publisher: John Wiley & Sons

ISBN: 111930282X

Category: Computers

Page: 352

View: 8580

A new approach to the issue of data quality in pattern recognition Detailing foundational concepts before introducing more complex methodologies and algorithms, this book is a self-contained manual for advanced data analysis and data mining. Top-down organization presents detailed applications only after methodological issues have been mastered, and step-by-step instructions help ensure successful implementation of new processes. By positioning data quality as a factor to be dealt with rather than overcome, the framework provided serves as a valuable, versatile tool in the analysis arsenal. For decades, practical need has inspired intense theoretical and applied research into pattern recognition for numerous and diverse applications. Throughout, the limiting factor and perpetual problem has been data—its sheer diversity, abundance, and variable quality presents the central challenge to pattern recognition innovation. Pattern Recognition: A Quality of Data Perspective repositions that challenge from a hurdle to a given, and presents a new framework for comprehensive data analysis that is designed specifically to accommodate problem data. Designed as both a practical manual and a discussion about the most useful elements of pattern recognition innovation, this book: Details fundamental pattern recognition concepts, including feature space construction, classifiers, rejection, and evaluation Provides a systematic examination of the concepts, design methodology, and algorithms involved in pattern recognition Includes numerous experiments, detailed schemes, and more advanced problems that reinforce complex concepts Acts as a self-contained primer toward advanced solutions, with detailed background and step-by-step processes Introduces the concept of granules and provides a framework for granular computing Pattern recognition plays a pivotal role in data analysis and data mining, fields which are themselves being applied in an expanding sphere of utility. By facing the data quality issue head-on, this book provides students, practitioners, and researchers with a clear way forward amidst the ever-expanding data supply.

Research in adaptive pattern recognition

final report. Contract No. Nonr 4752(00), NR-348-010. Period of performance: 4/1/65-3/31/70

Author: Infoton, Inc

Publisher: N.A

ISBN: N.A

Category: Computers

Page: N.A

View: 5571

Hybrid Methods in Pattern Recognition

Author: Horst Bunke,Abraham Kandel

Publisher: World Scientific

ISBN: 9810248326

Category: Technology & Engineering

Page: 324

View: 2636

The field of pattern recognition has seen enormous progress since its beginnings almost 50 years ago. A large number of different approaches have been proposed. Hybrid methods aim at combining the advantages of different paradigms within a single system. Hybrid Methods in Pattern Recognition is a collection of articles describing recent progress in this emerging field. It covers topics such as the combination of neural nets with fuzzy systems or hidden Markov models, neural networks for the processing of symbolic data structures, hybrid methods in data mining, the combination of symbolic and subsymbolic learning, and so on. Also included is recent work on multiple classifier systems. Furthermore, the book deals with applications in on-line and off-line handwriting recognition, remotely sensed image interpretation, fingerprint identification, and automatic text categorization.

Soft Computing Approach to Pattern Classification and Object Recognition

A Unified Concept

Author: Kumar S. Ray

Publisher: Springer Science & Business Media

ISBN: 1461453488

Category: Computers

Page: 176

View: 454

Soft Computing Approach to Pattern Classification and Object Recognition establishes an innovative, unified approach to supervised pattern classification and model-based occluded object recognition. The book also surveys various soft computing tools, fuzzy relational calculus (FRC), genetic algorithm (GA) and multilayer perceptron (MLP) to provide a strong foundation for the reader. The supervised approach to pattern classification and model-based approach to occluded object recognition are treated in one framework , one based on either a conventional interpretation or a new interpretation of multidimensional fuzzy implication (MFI) and a novel notion of fuzzy pattern vector (FPV). By combining practice and theory, a completely independent design methodology was developed in conjunction with this supervised approach on a unified framework, and then tested thoroughly against both synthetic and real-life data. In the field of soft computing, such an application-oriented design study is unique in nature. The monograph essentially mimics the cognitive process of human decision making, and carries a message of perceptual integrity in representational diversity. Soft Computing Approach to Pattern Classification and Object Recognition is intended for researchers in the area of pattern classification and computer vision. Other academics and practitioners will also find the book valuable.

Machine Learning and Data Mining in Pattern Recognition

14th International Conference, MLDM 2018, New York, NY, USA, July 15-19, 2018, Proceedings

Author: Petra Perner

Publisher: Springer

ISBN: 3319961330

Category: Computers

Page: 485

View: 8780

This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.

Pattern Recognition

Third Mexican Conference, MCPR 2011, Cancun, Mexico, June 29 - July 2, 2011. Proceedings

Author: José Francisco Martínez-Trinidad,Jesús Ariel Carrasco-Ochoa,Cherif Ben-Youssef Brants,Edwin Robert Hancock

Publisher: Springer

ISBN: 3642215874

Category: Computers

Page: 352

View: 9958

This book constitutes the refereed proceedings of the Third Mexican Conference on Pattern Recognition, MCPR 2011, held in Cancun, Mexico, in June/July 2011. The 37 revised full papers were carefully reviewed and selected from 69 submissions and are organized in topical sections on pattern recognition and data mining; computer vision and robotics; image processing; neural networks and signal processing; and natural language and document processing.

Neurobiological Foundations for EMDR Practice

Author: Uri Bergmann, PhD

Publisher: Springer Publishing Company

ISBN: 0826109381

Category: Psychology

Page: 248

View: 7608

This volume introduces the most current research about the neural underpinnings of consciousness and EMDR (eye movement desensitization and reprocessing) in regard to attachment, traumatic stress, and dissociation. It is the first book to comprehensively integrate new findings in information processing, consciousness, traumatic disorders of information processing, chronic trauma and autoimmune compromises, and the implications of these data on the Adaptive Information Processing (AIP) model and EMDR treatment The text examines online/wakeful information processing, including sensation, perception, somatosensory integration, cognition, memory, language and motricity, and off-line/sleep information processing, such as slow wave sleep and cognitive memorial processing, as well as REM/dream sleep and its function in emotional memory processing. The volume also addresses disorders of consciousness, including coma, anesthesia, and other neurological disorders, particularly disorders of Type 1 PTSD, complex PTSD/dissociative disorders, and personality disorders. It delves into chronic trauma and autoimmune function, especially in regard to diseases of unknown origin, and examines them from the perspective of autoimmune compromises resulting from the unusual neuroendocrine profile of PTSD sufferers. The final section integrates all material to illustrate the tenets of the AIP model and the implication of this material with respect to current EMDR treatment, as well as techniques to render it more robust Key Features: Provides a neurobiological foundation that informs our understanding of human development, disorders of attachment, and information processing Examines biological underpinnings of EMDR and other psychotherapeutic modalities regarding successful treatment outcomes for attachment, stress, and dissociation Offers the latest research in neurosciences relevant to attachment, traumatic stress, and dissociation Explicates disorders as outcomes of chronically dysregulated, evolutionarily based, biological action systems Illustrates EMDR's sensorial input to the brain as a neural catalyst that can facilitate repair of dysfunctional neural circuitry Includes illustrative neural maps

Proceedings

Author: N.A

Publisher: N.A

ISBN: 9780818686474

Category: Medicine

Page: 913

View: 6109

Signal Processing, Image Processing and Pattern Recognition

International Conferences, SIP 2011, Held as Part of the Future Generation Information Technology Conference, FGIT 2011, in Conjunction with GDC 2011, Jeju Island, Korea, December 8-10, 2011. Proceedings

Author: Tai-hoon Kim,Hojjat Adeli,Carlos Ramos,Byeong-Ho Kang

Publisher: Springer Science & Business Media

ISBN: 3642271820

Category: Computers

Page: 450

View: 8279

This book comprises selected papers of the International Conference on Signal Processing, Image Processing and Pattern Recognition, SIP 2011, held as Part of the Future Generation Information Technology Conference, FGIT 2011, in Conjunction with GDC 2011, in Conjunction with GDC 2011, Jeju Island, Korea, in December 2011. The papers presented were carefully reviewed and selected from numerous submissions and focus on the various aspects of signal processing, image processing and pattern recognition.

Pattern Recognition in Bioinformatics

Third IAPR International Conference, PRIB 2008, Melbourne, Australia, October 15-17, 2008. Proceedings

Author: Madhu Chetty,Alioune Ngom,Shandar Ahmad

Publisher: Springer

ISBN: 354088436X

Category: Science

Page: 472

View: 675

In the post-genomic era, a holistic understanding of biological systems and p- cesses,inalltheircomplexity,is criticalincomprehendingnature’schoreography of life. As a result, bioinformatics involving its two main disciplines, namely, the life sciences and the computational sciences, is fast becoming a very promising multidisciplinary research ?eld. With the ever-increasing application of lar- scalehigh-throughputtechnologies,suchasgeneorproteinmicroarraysandmass spectrometry methods, the enormous body of information is growing rapidly. Bioinformaticians are posed with a large number of di?cult problems to solve, arising not only due to the complexities in acquiring the molecular infor- tion but also due to the size and nature of the generated data sets and/or the limitations of the algorithms required for analyzing these data. Although the ?eld of bioinformatics is still in its embryonic stage, the recent advancements in computational and information-theoretic techniques are enabling us to c- ductvariousinsilicotestingandscreeningofmanylab-basedexperimentsbefore these are actually performed in vitro or in vivo. These in silico investigations are providing new insights for interpretation and establishing a new direction for a deeper understanding. Among the various advanced computational methods currently being applied to such studies, the pattern recognition techniques are mostly found to be at the core of the whole discovery process for apprehending the underlying biological knowledge. Thus, we can safely surmise that the - going bioinformatics revolution may, in future, inevitably play a major role in many aspects of medical practice and/or the discipline of life sciences.

Computational Intelligence in Multi-Feature Visual Pattern Recognition

Hand Posture and Face Recognition using Biologically Inspired Approaches

Author: Pramod Kumar Pisharady,Prahlad Vadakkepat,Loh Ai Poh

Publisher: Springer

ISBN: 9812870563

Category: Computers

Page: 138

View: 7861

This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good inter class discrimination. A Bayesian model of visual attention is described which is effective in handling complex background problem in hand posture recognition. The book provides qualitative and quantitative performance comparisons for the algorithms outlined, with other standard methods in machine learning and computer vision. The book is self-contained with several figures, charts, tables and equations helping the reader to understand the material presented without instruction.

Pattern Recognition and Image Analysis

4th Iberian Conference, IbPRIA 2009 Póvoa de Varzim, Portugal, June 10-12, 2009 Proceedings

Author: Hélder J. Araújo,Ana Maria Mendonça,Armando J. Pinho

Publisher: Springer Science & Business Media

ISBN: 3642021719

Category: Computers

Page: 514

View: 7831

IbPRIA 2009 (Iberian Conference on Pattern Recognition and Image Analysis) was the fourth edition of a series of conferences jointly organized by APRP (- socia, c ao Portuguesa de Reconhecimento de Padroes) and AERFAI (Asociaci on Espano la de Reconocimiento de Formas y An alisis de Im agenes). This year, IbPRIA was held in Pov oade Varzim, Portugal, June 10 12,2009, and was a - caljointorganizationofISR(Instituto deSistemaseRobot ica), INEB(Instituto de Engenharia Biom edica) and IEETA (Instituto de Engenharia Electron ica e Telem atica de Aveiro). It followed the three successful previous editions hosted by the Universitat de les Illes Balears (2003), Instituto de Sistemas e Robot ica and Centro de Geo-Sistemas of Instituto Superior T ecnico (2005), and the - stitute of Informatics and Applications of the University of Girona (2007). A total of 106 manuscripts, from 18 countries, were received. Each of these submissions was reviewed in a blind process by at least two reviewers, resulting in 62 accepted papers, 33 for oral presentation and 29 for poster presentation. We were very honored to have as invited speakers such internationally r- ognized researchers as Samy Bengio from Google Inc., USA, Joachim Weickert from Saarland University, Germany, and Nando de Freitas from the University of British Columbia, Canada. We would like to thank all the authors for submitting their papers and thus making these proceedings possible."

Structural, Syntactic, and Statistical Pattern Recognition

Joint IAPR International Workshop, SSPR & SPR 2008, Orlando, USA, December 4-6, 2008. Proceedings

Author: Niels da Vitoria Lobo,Takis Kasparis,Michael Georgiopoulos,Fabio Roli,James Kwok,Georgios C. Anagnostopoulos,Marco Loog

Publisher: Springer Science & Business Media

ISBN: 3540896880

Category: Computers

Page: 1011

View: 6528

This book constitutes the refereed proceedings of the 12th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2008 and the 7th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2008, held jointly in Orlando, FL, USA, in December 2008 as a satellite event of the 19th International Conference of Pattern Recognition, ICPR 2008. The 56 revised full papers and 42 revised poster papers presented together with the abstracts of 4 invited papers were carefully reviewed and selected from 175 submissions. The papers are organized in topical sections on graph-based methods, probabilistic and stochastic structural models for PR, image and video analysis, shape analysis, kernel methods, recognition and classification, applications, ensemble methods, feature selection, density estimation and clustering, computer vision and biometrics, pattern recognition and applications, pattern recognition, as well as feature selection and clustering.

Signal Processing, Image Processing and Pattern Recognition,

International Conference, SIP 2009, Held as Part of the Future Generation Information Technology Conference, FGIT 2009, Jeju Island, Korea, December 10-12, 2009. Proceedings

Author: Dominik Slezak,Sankar Pal,Byeong-Ho Kang,Junzhong Gu,Hideo Kuroda,Tai-hoon Kim

Publisher: Springer Science & Business Media

ISBN: 3642105459

Category: Computers

Page: 330

View: 639

As future generation information technology (FGIT) becomes specialized and fr- mented, it is easy to lose sight that many topics in FGIT have common threads and, because of this, advances in one discipline may be transmitted to others. Presentation of recent results obtained in different disciplines encourages this interchange for the advancement of FGIT as a whole. Of particular interest are hybrid solutions that c- bine ideas taken from multiple disciplines in order to achieve something more signi- cant than the sum of the individual parts. Through such hybrid philosophy, a new principle can be discovered, which has the propensity to propagate throughout mul- faceted disciplines. FGIT 2009 was the first mega-conference that attempted to follow the above idea of hybridization in FGIT in a form of multiple events related to particular disciplines of IT, conducted by separate scientific committees, but coordinated in order to expose the most important contributions. It included the following international conferences: Advanced Software Engineering and Its Applications (ASEA), Bio-Science and Bio-Technology (BSBT), Control and Automation (CA), Database Theory and Application (DTA), D- aster Recovery and Business Continuity (DRBC; published independently), Future G- eration Communication and Networking (FGCN) that was combined with Advanced Communication and Networking (ACN), Grid and Distributed Computing (GDC), M- timedia, Computer Graphics and Broadcasting (MulGraB), Security Technology (SecTech), Signal Processing, Image Processing and Pattern Recognition (SIP), and- and e-Service, Science and Technology (UNESST).

Pattern Recognition

Author: Sergios Theodoridis,Konstantinos Koutroumbas

Publisher: Elsevier

ISBN: 9780080513614

Category: Computers

Page: 856

View: 5469

Pattern recognition is a fast growing area with applications in a widely diverse number of fields such as communications engineering, bioinformatics, data mining, content-based database retrieval, to name but a few. This new edition addresses and keeps pace with the most recent advancements in these and related areas. This new edition: a) covers Data Mining, which was not treated in the previous edition, and is integrated with existing material in the book, b) includes new results on Learning Theory and Support Vector Machines, that are at the forefront of today's research, with a lot of interest both in academia and in applications-oriented communities, c) for the first time treats audio along with image applications since in today's world the most advanced applications are treated in a unified way and d) the subject of classifier combinations is treated, since this is a hot topic currently of interest in the pattern recognition community. * The latest results on support vector machines including v-SVM's and their geometric interpretation * Classifier combinations including the Boosting approach * State-of-the-art material for clustering algorithms tailored for large data sets and/or high dimensional data, as required by applications such as web-mining and bioinformatics * Coverage of diverse applications such as image analysis, optical character recognition, channel equalization, speech recognition and audio classification

Pattern Recognition

An Algorithmic Approach

Author: M. Narasimha Murty,V. Susheela Devi

Publisher: Springer Science & Business Media

ISBN: 9780857294951

Category: Computers

Page: 263

View: 8957

Observing the environment and recognising patterns for the purpose of decision making is fundamental to human nature. This book deals with the scientific discipline that enables similar perception in machines through pattern recognition (PR), which has application in diverse technology areas. This book is an exposition of principal topics in PR using an algorithmic approach. It provides a thorough introduction to the concepts of PR and a systematic account of the major topics in PR besides reviewing the vast progress made in the field in recent times. It includes basic techniques of PR, neural networks, support vector machines and decision trees. While theoretical aspects have been given due coverage, the emphasis is more on the practical. The book is replete with examples and illustrations and includes chapter-end exercises. It is designed to meet the needs of senior undergraduate and postgraduate students of computer science and allied disciplines.