University of Waterloo
Education•Waterloo, Ontario, Canada•
About: University of Waterloo is a(n) education organization based out in Waterloo, Ontario, Canada. It is known for research contribution in the topic(s): Population & Poison control. The organization has 36093 authors who have published 93906 publication(s) receiving 2948139 citation(s). The organization is also known as: UW & uwaterloo.
Papers published on a yearly basis
•01 Jan 1996
TL;DR: A valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography, this book provides easy and rapid access of information and includes more than 200 algorithms and protocols.
Abstract: From the Publisher: A valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography, this book provides easy and rapid access of information and includes more than 200 algorithms and protocols; more than 200 tables and figures; more than 1,000 numbered definitions, facts, examples, notes, and remarks; and over 1,250 significant references, including brief comments on each paper.
•01 May 1990
TL;DR: The Fourth Edition of Biomechanics as an Interdiscipline: A Review of the Fourth Edition focuses on biomechanical Electromyography, with a focus on the relationship between Electromyogram and Biomechinical Variables.
Abstract: Preface to the Fourth Edition. 1 Biomechanics as an Interdiscipline. 1.0 Introduction. 1.1 Measurement, Description, Analysis, and Assessment. 1.2 Biomechanics and its Relationship with Physiology and Anatomy. 1.3 Scope of the Textbook. 1.4 References. 2 Signal Processing. 2.0 Introduction. 2.1 Auto- and Cross-Correlation Analyses. 2.2 Frequency Analysis. 2.3 Ensemble Averaging of Repetitive Waveforms. 2.4 References. 3 Kinematics. 3.0 Historical Development and Complexity of Problem. 3.1 Kinematic Conventions. 3.2 Direct Measurement Techniques. 3.3 Imaging Measurement Techniques. 3.4 Processing of Raw Kinematic Data. 3.5 Calculation of Other Kinematic Variables. 3.6 Problems Based on Kinematic Data. 3.7 References. 4 Anthropometry. 4.0 Scope of Anthropometry in Movement Biomechanics. 4.1 Density, Mass, and Inertial Properties. 4.2 Direct Experimental Measures. 4.3 Muscle Anthropometry. 4.4 Problems Based on Anthropometric Data. 4.5 References. 5 Kinetics: Forces and Moments of Force. 5.0 Biomechanical Models. 5.1 Basic Link-Segment Equations-the Free-Body Diagram. 5.2 Force Transducers and Force Plates. 5.3 Bone-on-Bone Forces During Dynamic Conditions. 5.4 Problems Based on Kinetic and Kinematic Data. 5.5 References. 6 Mechanical Work, Energy, and Power. 6.0 Introduction. 6.1 Efficiency. 6.2 Forms of Energy Storage. 6.3 Calculation of Internal and External Work. 6.4 Power Balances at Joints and Within Segments. 6.5 Problems Based on Kinetic and Kinematic Data. 6.6 References. 7 Three-Dimensional Kinematics and Kinetics. 7.0 Introduction. 7.1 Axes Systems. 7.2 Marker and Anatomical Axes Systems. 7.3 Determination of Segment Angular Velocities and Accelerations. 7.4 Kinetic Analysis of Reaction Forces and Moments. 7.5 Suggested Further Reading. 7.6 References. 8 Synthesis of Human Movement-Forward Solutions. 8.0 Introduction. 8.1 Review of Forward Solution Models. 8.2 Mathematical Formulation. 8.3 System Energy. 8.4 External Forces and Torques. 8.5 Designation of Joints. 8.6 Illustrative Example. 8.7 Conclusions. 8.8 References. 9 Muscle Mechanics. 9.0 Introduction. 9.1 Force-Length Characteristics of Muscles. 9.2 Force-Velocity Characteristics. 9.3 Muscle Modeling. 9.4 References. 10 Kinesiological Electromyography. 10.0 Introduction. 10.1 Electrophysiology of Muscle Contraction. 10.2 Recording of the Electromyogram. 10.3 Processing of the Electromyogram,. 10.4 Relationship between Electromyogram and Biomechanical Variables. 10.5 References. 11 Biomechanical Movement Synergies. 11.0 Introduction. 11.1 The Support Moment Synergy. 11.2 Medial/Lateral and Anterior/Posterior Balance in Standing. 11.3 Dynamic Balance during Walking. 11.4 References. APPENDICES. A. Kinematic, Kinetic, and Energy Data. Figure A.1 Walking Trial-Marker Locations and Mass and Frame Rate Information. Table A.1 Raw Coordinate Data (cm). Table A.2( a ) Filtered Marker Kinematics-Rib Cage and Greater Trochanter (Hip). Table A.2( b ) Filtered Marker Kinematics-Femoral Lateral Epicondyle (Knee) and Head of Fibula. Table A.2( c ) Filtered Marker Kinematics-Lateral Malleolus (Ankle) and Heel. Table A.2( d ) Filtered Marker Kinematics-Fifth Metatarsal and Toe. Table A.3( a ) Linear and Angular Kinematics-Foot. Table A.3( b ) Linear and Angular Kinematics-Leg. Table A.3( c ) Linear and Angular Kinematics-Thigh. Table A.3( d ) Linear and Angular Kinematics-1/2 HAT. Table A.4 Relative Joint Angular Kinematics-Ankle, Knee, and Hip. Table A.5( a ) Reaction Forces and Moments of Force-Ankle and Knee. Table A.5( b ) Reaction Forces and Moments of Force-Hip. Table A.6 Segment Potential, Kinetic, and Total Energies-Foot, Leg, Thigh, and1/2 HAT. Table A.7 Power Generation/Absorption and Transfer-Ankle, Knee, and Hip. B. Units and Definitions Related to Biomechanical and Electromyographical Measurements. Table B.1 Base SI Units. Table B.2 Derived SI Units. Index.
Harvard University1, University of Reims Champagne-Ardenne2, College of William & Mary3, Old Dominion University4, University of Lisbon5, University of Burgundy6, California Institute of Technology7, Centre national de la recherche scientifique8, Université catholique de Louvain9, University of York10, University College London11, National Institute of Standards and Technology12, University of Waterloo13, National Center for Atmospheric Research14, University of Cologne15, Karlsruhe Institute of Technology16, Langley Research Center17
TL;DR: The new HITRAN is greatly extended in terms of accuracy, spectral coverage, additional absorption phenomena, added line-shape formalisms, and validity, and molecules, isotopologues, and perturbing gases have been added that address the issues of atmospheres beyond the Earth.
Abstract: This paper describes the contents of the 2016 edition of the HITRAN molecular spectroscopic compilation. The new edition replaces the previous HITRAN edition of 2012 and its updates during the intervening years. The HITRAN molecular absorption compilation is composed of five major components: the traditional line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, infrared absorption cross-sections for molecules not yet amenable to representation in a line-by-line form, collision-induced absorption data, aerosol indices of refraction, and general tables such as partition sums that apply globally to the data. The new HITRAN is greatly extended in terms of accuracy, spectral coverage, additional absorption phenomena, added line-shape formalisms, and validity. Moreover, molecules, isotopologues, and perturbing gases have been added that address the issues of atmospheres beyond the Earth. Of considerable note, experimental IR cross-sections for almost 300 additional molecules important in different areas of atmospheric science have been added to the database. The compilation can be accessed through www.hitran.org. Most of the HITRAN data have now been cast into an underlying relational database structure that offers many advantages over the long-standing sequential text-based structure. The new structure empowers the user in many ways. It enables the incorporation of an extended set of fundamental parameters per transition, sophisticated line-shape formalisms, easy user-defined output formats, and very convenient searching, filtering, and plotting of data. A powerful application programming interface making use of structured query language (SQL) features for higher-level applications of HITRAN is also provided.
Robert H. Waterston1, Kerstin Lindblad-Toh2, Ewan Birney, Jane Rogers3 +219 more•Institutions (26)
TL;DR: The results of an international collaboration to produce a high-quality draft sequence of the mouse genome are reported and an initial comparative analysis of the Mouse and human genomes is presented, describing some of the insights that can be gleaned from the two sequences.
Abstract: The sequence of the mouse genome is a key informational tool for understanding the contents of the human genome and a key experimental tool for biomedical research. Here, we report the results of an international collaboration to produce a high-quality draft sequence of the mouse genome. We also present an initial comparative analysis of the mouse and human genomes, describing some of the insights that can be gleaned from the two sequences. We discuss topics including the analysis of the evolutionary forces shaping the size, structure and sequence of the genomes; the conservation of large-scale synteny across most of the genomes; the much lower extent of sequence orthology covering less than half of the genomes; the proportions of the genomes under selection; the number of protein-coding genes; the expansion of gene families related to reproduction and immunity; the evolution of proteins; and the identification of intraspecies polymorphism.
TL;DR: This paper introduces the reader to a response surface methodology that is especially good at modeling the nonlinear, multimodal functions that often occur in engineering and shows how these approximating functions can be used to construct an efficient global optimization algorithm with a credible stopping rule.
Abstract: In many engineering optimization problems, the number of function evaluations is severely limited by time or cost. These problems pose a special challenge to the field of global optimization, since existing methods often require more function evaluations than can be comfortably afforded. One way to address this challenge is to fit response surfaces to data collected by evaluating the objective and constraint functions at a few points. These surfaces can then be used for visualization, tradeoff analysis, and optimization. In this paper, we introduce the reader to a response surface methodology that is especially good at modeling the nonlinear, multimodal functions that often occur in engineering. We then show how these approximating functions can be used to construct an efficient global optimization algorithm with a credible stopping rule. The key to using response surfaces for global optimization lies in balancing the need to exploit the approximating surface (by sampling where it is minimized) with the need to improve the approximation (by sampling where prediction error may be high). Striking this balance requires solving certain auxiliary problems which have previously been considered intractable, but we show how these computational obstacles can be overcome.
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|John J.V. McMurray||178||1389||184502|
|David A. Weitz||178||1038||114182|
|Will J. Percival||129||473||87752|
|Mark A. Tarnopolsky||115||644||42501|
|Theodore S. Rappaport||112||490||68853|
|Robert C. Haddon||112||577||52712|
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