Base, Pulse, and Trace File Reference Guide

Size: px
Start display at page:

Download "Base, Pulse, and Trace File Reference Guide"

Transcription

1 Base, Pulse, and Trace File Reference Guide Introduction This document describes the contents of the three main files generated by the Pacific Biosciences primary analysis pipeline: bas.h5 (Base File, includes Circular Consensus Sequencing Basecalls created by the Base2Circular Consensus pipeline step.) trc.h5 (Trace file) pls.h5 (Pulse File) Trace (.trc.h5) Pulse (.pls.h5) Base (.bas.h5) File Format: HDF5 HDF5 HDF5 Generated by: Movie2Trace Trace2Pulse Pulse2Base Approximate Size (2 x 45 Minute Movies): > 75 GB ~ 20 GB ~ 2 GB Contains: Real time trace data processed from image frames from selected ZMWs. Pulse characteristics from trace data: Pulse height, width, inter-pulse distance, and so on. Raw base calls from each defined pulse along with quality metrics. You can easily browse HDF5 files using HDFView, a free utility. See For information about the HDF5 format, see API Software Pacific Biosciences provides Java and R APIs to read three types of HDF5 files (Base, Trace, and Pulse) produced by the primary analysis pipeline. The APIs allows you to query for details in the HDF5 files for post-processing analysis. Note that you can use any programming language that can access HDF5 files to work with the Base, Trace, and Pulse files. Note: There are objects in the Base, Pulse and Trace files that cannot be accessed using Pacific Biosciences API software. The latest version of the API software and documentation are available from the PacBio Developer s Network at Page 1

2 Base File (bas.h5) The bas.h5 file is created by the Pulse2Base primary analysis pipeline step. The file is processed by the SMRT Pipe secondary analysis pipeline to generate mapping, alignment, consensus, and variants information. If you need to archive primary analysis results, we recommend that you keep only the bas.h5 file as it is the only file needed for reprocessing secondary analysis results. bas.h5 is a proper subset of the pls.h5 file, but lacks the majority of pulse features. Both bas.h5 and pls.h5 files contain raw base calls generated from the pulse metrics, but bas.h5 contains only minimal pulse data for kinetic analysis purposes. Because of this, the bas.h5 file can be recreated from the pls.h5 file, but not vice versa. The following table describes the contents of the bas.h5 file, including Circular Consensus Sequencing Basecalls created by the Base2Circular Consensus pipeline step: Base File HDF5 Object Root (/) /PulseData /PulseData/BaseCalls BaseCall PulseIndex QualityValue DeletionQV DeletionTag InsertionQv PreBaseFrames SubstitutionQV SubstitutionTag Top-level container. Container for the BaseCalls and ConsensusBaseCalls groups. Contains base metrics produced by the PulseToBase pipeline stage. Each child data is a 1-dimensional array of length numbases, where numbases is the total number of basecalls in the file (that is, the sum of ZMW/NumEvent). An ASCII representation of the called base for a The index into the pulse stream corresponding to the pulse that was called as this base. The Phred-style quality values of the bases. A Phred-style quality value indicating the total probability of a deleted base before the current base. The ASCII code of the most likely base to have been deleted before the current base. A Phred-style quality value indicating the probability that the current base is an insertion. The number of frames between the start of the base and the end of the previous base. A Phred-style quality value indicating the total probability that the current base call is a substitution error. The ASCII code of the most likely alternative base call at this position for a Page 2

3 Base File HDF5 Object WidthInFrames ZMW ZMW/ HoleNumber ZMW/ HoleStatus ZMW/HoleXY ZMW/ NumEvent ZMWMetrics ZMWMetrics/BaseFraction ZMWMetrics/BaseRate ZMWMetrics/BaseWidth ZMWMetrics/BaseIpd ZMWMetrics/CmBasQv ZMWMetrics/Productivity ZMWMetrics/ReadScore ZMWMetrics/RmBasQv ZMWMetrics/CmDelQv ZMWMetrics/CmInsQv ZMWMetrics/CmSubQv ZMWMetrics/HQRegionSNR ZMWMetrics/LocalBaseRate ZMWMetrics/RmDelQv The width of the pulse that generated this base, in frames. ZMW identifiers. The hole numbers of the ZMWs. Indicates how to decode the HoleStatus field. Only ZMWs with a HoleStatus == 0 can generate a sequence. The X, Y coordinates of a The number of bases per Pulse metrics, per The fraction of the bases called by channel within a The average (global) pulse rate (in pulses/second) of called bases within the high quality region for a The mean pulse width of called bases within the high quality region in the ZMW, in seconds. The robust mean pulse IPD (interpulse distance) for called bases within a high quality region for a The mean Phred-style quality values by base channel over the read for a A classification corresponding to hole productivity for a The values are: 0 = Empty, 1 = Sequencing (Good), and 2 = Other (Bad, Multiple occupation). A score corresponding to the predicted accuracy of the read within a The mean Phred-style quality value over all bases in the read for a The mean deletion quality values by base channel over the read for a The mean insertion quality values by base channel over the read for a The mean substitution quality values by base channel over the read for a The signal-to-noise ratio (SNR) of the pulses inside the HQRegion, where the HQRegion is a trimmed region predicted to be the high quality subset of the basecalls in the trace. An estimate of the local pulse rate for called bases, excluding polymerase, and pauses within a high quality region, for a The mean deletion quality value over all bases in the read for a Page 3

4 Base File HDF5 Object ZMWMetrics/RmInsQv ZMWMetrics/RmSubQv ZMWMetrics/HQRegionStartTime ZMWMetrics/HQRegionEndTime ZMWMetrics/DarkBaseRate /PulseData/Regions /PulseData/ConsensusBaseCalls BaseCall QualityValue DeletionQV DeletionTag InsertionQv SubstitutionQV SubstitutionTag Passes Passes/AdapterHitAfter Passes/AdapterHitBefore Passes/NumPasses The mean insertion quality value over all bases in the read for a The mean substitution quality value over all bases in the read for a The start time of the HQRegion from the beginning of the movie. The end time of the HQRegion from the beginning of the movie. The predicted local base rate when the chip is not illuminated (1/sec). This is a robust estimate of the local polymerization rate in this ZMW when the lasers are off. Single molecule consensus region objects information for a Each row in this table applies an annotation to a region of basecalls in one trace. These regions are used by downstream secondary analysis algorithms. Column 0: The HoleNumber of the ZMW that the annotation is being applied to. Column 1: The RegionType index. This value is an index into the 'RegionType' attribute of the Regions dataset. Column 2: The start base of the region. Column 3: The end base of the region. Column 4: The score applied to the region. Information on Single Molecule Consensus reads produced by the Single Molecule Consensus pipeline stage. An ASCII representation of the base calls for every read. The Phred-style quality values of the bases. A Phred-style quality value indicating the total probability of a deleted base before the current base. The likely identity of deleted base (if they exist) in a A Phred-style quality value indicating the probability that the current base is an insertion. The Phred-style quality value indicating the total probability that the current base call is a substitution error for bases in a The ASCII code of the most likely alternative base call at this position for a Information from Single Molecule Consensus processing of the raw read. For each pass, 1 if the pass ended with an adapter hit; 0 if it didn't. For each pass, 1 if the pass began with an adapter hit; 0 if it didn't. The number of passes detected in a Page 4

5 Base File HDF5 Object Passes/PassDirection Passes/PassNumBases Passes/PassStartBase ZMW ZMW/HoleNumber ZMW/HoleStatus /PulseData/ConsensusBaseCalls / ZMW/HoleXY PulseData/ConsensusBaseCalls/ ZMW/NumPasses /ScanData /ScanData/AcqParams /ScanData/ChipArray /ScanData/ChipArray/ChipMask DataSet /ScanData/DyeSet /ScanData/DyeSet/Analog[0] /ScanData/DyeSet/Analog[0]/ /ScanData/DyeSet/Analog[1] /ScanData/DyeSet/Analog[1]/ /ScanData/DyeSet/Analog[2] /ScanData/DyeSet/Analog[2]/ /ScanData/DyeSet/Analog[3] /ScanData/DyeSet/Analog[3]/ /ScanData/Experiment /ScanData/RunInfo The pass direction per hole. 0 for a forward pass, 1 for a reverse pass. The number of bases in a circular consensus pass. The index of the first base in a circular consensus pass. ZMW identifiers. The hole numbers of the ZMWs. The hole status per The X, Y coordinates of a The number of SMCs passes detected in each Container for instrument and acquisition metadata. Acquisition-related information, such as number of lasers, laser intensity, number of frames acquired, and so on. Chip-related information, such as chip identifier, chip layout, number of non-sequencing dark holes, and so on. The binary matrix of a chip indicating which ZMWs have been masked. The dye set name. Experiment-related information. Run-related information, such as platform name, run ID, instrument ID, and so on. Page 5

6 Pulse File (pls.h5) The Pulse file is created by the Trace2Pulse primary analysis pipeline step. The following table describes the contents of the pls.h5 file: Pulse File HDF5 Object Root (/) /PulseData /PulseData/PulseCalls Channel Chi2 ClassifierQV IsPulse MaxSignal MeanSignal MidSignal WidthInFrames StartFrame ZMW ZMW/ BaselineLevel ZMW/ BaselineSigma ZMW/ HoleNumber ZMW/ HoleStatus ZMW/ HoleXY ZMW/ NumEvent ZMWMetrics ZMWMetrics/PulseRate Top-level container. Container for the PulseCalls, Basecalls, and ConsensusBasecalls groups. Container for pulsecalls data. The classified channel index (0-based), corresponding to the channel order in the input trace file. The chi-squared values, Chi2/DOF per dye, integrated over pulse signals for a The quality values of a pulse as determined by the CRF in the trace to pulse portion of the primary analysis pipeline for a The pulse CRF trace to pulse valid pulse classification as true, false or otherwise for a The maximum signal levels over the pulse frames for a The mean signal levels over the pulse frames for a The mean signal levels over the mid-pulse frames, excluding the leading and trailing frame. The duration of a pulse in frames for a The acquisition frame when the pulse began for a ZMW identifiers. The mean bias of the baseline signal as estimated by the trace signal processing algorithm for a The standard deviation of the baseline signal for a ZMW; for example, the average noise level. The hole numbers of the ZMWs. A number specifying the status of a The X, Y coordinates of a The number of pulses per Container for pulse metrics. The global pulse rate (in pulses per second) in the Page 6

7 Pulse File HDF5 Object ZMWMetrics/PulseWidth ZMWMetrics/Snr /ScanData /ScanData/AcqParams /ScanData/ChipArray /ScanData/ChipArray/ChipMask DataSet /ScanData/DyeSet /ScanData/DyeSet/Analog[0] /ScanData/DyeSet/Analog[0]/ /ScanData/DyeSet/Analog[1] /ScanData/DyeSet/Analog[1]/ /ScanData/DyeSet/Analog[2] /ScanData/DyeSet/Analog[2]/ /ScanData/DyeSet/Analog[3] /ScanData/DyeSet/Analog[3]/ /ScanData/Experiment /ScanData/RunInfo The mean pulse width (in pulses per second) for a The signal-to-noise ratio (SNR) for a Container for instrument and acquisition metadata. Acquisition-related information, such as number of lasers, laser intensity, number of frames acquired, and so on. Chip-related information, such as chip identifier, chip layout, number of non-sequencing dark holes, and so on. The binary matrix of a chip indicating which ZMWs have been masked. The dye set name. Experiment-related information. Run-related information, such as platform name, run ID, instrument ID, and so on. Page 7

8 Trace File (trc.h5) The Trace file is created by the Movie2Trace primary analysis pipeline step.the following table describes the contents of the trc.h5 file: Trace File HDF5 Object Root (/) /TraceData /TraceData HoleNumber /TraceData HoleStatus /TraceData HoleXY /TraceData ReadVariance /TraceData Spectra /TraceData Traces /TraceData Variances /TraceData HolePhase /TraceData/Codec /TraceData/Codec/Decode /ScanData /ScanData/AcqParams /ScanData/ChipArray /ScanData/ChipArray/ChipMask DataSet /ScanData/DyeSet /ScanData/DyeSet/Analog[0] /ScanData/DyeSet/Analog[0]/ /ScanData/DyeSet/Analog[1] /ScanData/DyeSet/Analog[1]/ /ScanData/DyeSet/Analog[2] /ScanData/DyeSet/Analog[2]/ Top-level container. Container for the trace data. The ZMW hole number. The ZMW hole status. The X,Y coordinates for a ZMW location. The variance estimates corresponding to camera read noise contribution for trace. The spectral distribution for a 8-bit trace data in a ZMW for all frames. Channel variance estimates (post-spatial reduction) that were used to construct the weights for the dye-weighted sum (spectral) reduction, by block increments. The units correspond to decoded trace units. The time delay, as a fraction of the frame interval, of each ZMW for each camera where 0 <= HolePhase <= 1. Container for encoding method and attributes. Codec look-up table. Container for instrument and acquisition metadata. Acquisition-related information, such as number of lasers, laser intensity, number of frames acquired, and so on. Chip-related information, such as chip identifier, chip layout, number of non-sequencing dark holes, and so on. The binary matrix of a chip indicating which ZMWs have been masked. The dye set name. Page 8

9 Trace File HDF5 Object /ScanData/DyeSet/Analog[3] /ScanData/DyeSet/Analog[3]/ /ScanData/Experiment /ScanData/RunInfo Experiment-related information. Run-related information, such as platform name, run ID, instrument ID, and so on. For Research Use Only. Not for use in diagnostic procedures. Copyright 2011, Pacific Biosciences of California, Inc. All rights reserved. Information in this document is subject to change without notice. Pacific Biosciences assumes no responsibility for any errors or omissions in this document. Certain notices, terms, conditions and/or use restrictions may pertain to your use of Pacific Biosciences products and/or third party products. Please refer to the applicable Pacific Biosciences Terms and Conditions of Sale and to the applicable license terms at Pacific Biosciences, the Pacific Biosciences logo, SMRT and SMRTbell are trademarks of Pacific Biosciences in the United States and/or certain other countries. All other trademarks are the sole property of their respective owners. P/N Page 9

BitWise (V2.1 and later) includes features for determining AP240 settings and measuring the Single Ion Area.

BitWise (V2.1 and later) includes features for determining AP240 settings and measuring the Single Ion Area. BitWise. Instructions for New Features in ToF-AMS DAQ V2.1 Prepared by Joel Kimmel University of Colorado at Boulder & Aerodyne Research Inc. Last Revised 15-Jun-07 BitWise (V2.1 and later) includes features

More information

WHAT MAKES FOR A HIT POP SONG? WHAT MAKES FOR A POP SONG?

WHAT MAKES FOR A HIT POP SONG? WHAT MAKES FOR A POP SONG? WHAT MAKES FOR A HIT POP SONG? WHAT MAKES FOR A POP SONG? NICHOLAS BORG AND GEORGE HOKKANEN Abstract. The possibility of a hit song prediction algorithm is both academically interesting and industry motivated.

More information

PulseCounter Neutron & Gamma Spectrometry Software Manual

PulseCounter Neutron & Gamma Spectrometry Software Manual PulseCounter Neutron & Gamma Spectrometry Software Manual MAXIMUS ENERGY CORPORATION Written by Dr. Max I. Fomitchev-Zamilov Web: maximus.energy TABLE OF CONTENTS 0. GENERAL INFORMATION 1. DEFAULT SCREEN

More information

base calling: PHRED...

base calling: PHRED... sequence quality base by base error probability for base calling programs reflects assay bias (e.g. detection chemistry, algorithms) allows for more efficient sequence editing and assembly allows for poorly

More information

AUDIOVISUAL COMMUNICATION

AUDIOVISUAL COMMUNICATION AUDIOVISUAL COMMUNICATION Laboratory Session: Recommendation ITU-T H.261 Fernando Pereira The objective of this lab session about Recommendation ITU-T H.261 is to get the students familiar with many aspects

More information

CS229 Project Report Polyphonic Piano Transcription

CS229 Project Report Polyphonic Piano Transcription CS229 Project Report Polyphonic Piano Transcription Mohammad Sadegh Ebrahimi Stanford University Jean-Baptiste Boin Stanford University sadegh@stanford.edu jbboin@stanford.edu 1. Introduction In this project

More information

Frame Processing Time Deviations in Video Processors

Frame Processing Time Deviations in Video Processors Tensilica White Paper Frame Processing Time Deviations in Video Processors May, 2008 1 Executive Summary Chips are increasingly made with processor designs licensed as semiconductor IP (intellectual property).

More information

OptoFidelity Video Multimeter User Manual Version 2017Q1.0

OptoFidelity Video Multimeter User Manual Version 2017Q1.0 OptoFidelity Video Multimeter User Manual Version 2017Q1.0 OptoFidelity Oy sales@optofidelity.com www.optofidelity.com OptoFidelity 2017 Microsoft and Excel are either registered trademarks or trademarks

More information

UC San Diego UC San Diego Previously Published Works

UC San Diego UC San Diego Previously Published Works UC San Diego UC San Diego Previously Published Works Title Classification of MPEG-2 Transport Stream Packet Loss Visibility Permalink https://escholarship.org/uc/item/9wk791h Authors Shin, J Cosman, P

More information

VLSI Design: 3) Explain the various MOSFET Capacitances & their significance. 4) Draw a CMOS Inverter. Explain its transfer characteristics

VLSI Design: 3) Explain the various MOSFET Capacitances & their significance. 4) Draw a CMOS Inverter. Explain its transfer characteristics 1) Explain why & how a MOSFET works VLSI Design: 2) Draw Vds-Ids curve for a MOSFET. Now, show how this curve changes (a) with increasing Vgs (b) with increasing transistor width (c) considering Channel

More information

Singer Traits Identification using Deep Neural Network

Singer Traits Identification using Deep Neural Network Singer Traits Identification using Deep Neural Network Zhengshan Shi Center for Computer Research in Music and Acoustics Stanford University kittyshi@stanford.edu Abstract The author investigates automatic

More information

Principles of Video Compression

Principles of Video Compression Principles of Video Compression Topics today Introduction Temporal Redundancy Reduction Coding for Video Conferencing (H.261, H.263) (CSIT 410) 2 Introduction Reduce video bit rates while maintaining an

More information

RECOMMENDATION ITU-R BT.1203 *

RECOMMENDATION ITU-R BT.1203 * Rec. TU-R BT.1203 1 RECOMMENDATON TU-R BT.1203 * User requirements for generic bit-rate reduction coding of digital TV signals (, and ) for an end-to-end television system (1995) The TU Radiocommunication

More information

Module 8 VIDEO CODING STANDARDS. Version 2 ECE IIT, Kharagpur

Module 8 VIDEO CODING STANDARDS. Version 2 ECE IIT, Kharagpur Module 8 VIDEO CODING STANDARDS Lesson 27 H.264 standard Lesson Objectives At the end of this lesson, the students should be able to: 1. State the broad objectives of the H.264 standard. 2. List the improved

More information

Detecting Musical Key with Supervised Learning

Detecting Musical Key with Supervised Learning Detecting Musical Key with Supervised Learning Robert Mahieu Department of Electrical Engineering Stanford University rmahieu@stanford.edu Abstract This paper proposes and tests performance of two different

More information

HD-SDI Express User Training. J.Egri 4/09 1

HD-SDI Express User Training. J.Egri 4/09 1 HD-SDI Express User Training J.Egri 4/09 1 Features SDI interface Supports 720p, 1080i and 1080p formats. Supports SMPTE 292M serial interface operating at 1.485 Gbps. Supports SMPTE 274M and 296M framing.

More information

Bar Codes to the Rescue!

Bar Codes to the Rescue! Fighting Computer Illiteracy or How Can We Teach Machines to Read Spring 2013 ITS102.23 - C 1 Bar Codes to the Rescue! If it is hard to teach computers how to read ordinary alphabets, create a writing

More information

The reduction in the number of flip-flops in a sequential circuit is referred to as the state-reduction problem.

The reduction in the number of flip-flops in a sequential circuit is referred to as the state-reduction problem. State Reduction The reduction in the number of flip-flops in a sequential circuit is referred to as the state-reduction problem. State-reduction algorithms are concerned with procedures for reducing the

More information

PYROPTIX TM IMAGE PROCESSING SOFTWARE

PYROPTIX TM IMAGE PROCESSING SOFTWARE Innovative Technologies for Maximum Efficiency PYROPTIX TM IMAGE PROCESSING SOFTWARE V1.0 SOFTWARE GUIDE 2017 Enertechnix Inc. PyrOptix Image Processing Software v1.0 Section Index 1. Software Overview...

More information

Enabling editors through machine learning

Enabling editors through machine learning Meta Follow Meta is an AI company that provides academics & innovation-driven companies with powerful views of t Dec 9, 2016 9 min read Enabling editors through machine learning Examining the data science

More information

Precision testing methods of Event Timer A032-ET

Precision testing methods of Event Timer A032-ET Precision testing methods of Event Timer A032-ET Event Timer A032-ET provides extreme precision. Therefore exact determination of its characteristics in commonly accepted way is impossible or, at least,

More information

TechNote: MuraTool CA: 1 2/9/00. Figure 1: High contrast fringe ring mura on a microdisplay

TechNote: MuraTool CA: 1 2/9/00. Figure 1: High contrast fringe ring mura on a microdisplay Mura: The Japanese word for blemish has been widely adopted by the display industry to describe almost all irregular luminosity variation defects in liquid crystal displays. Mura defects are caused by

More information

Department of Electrical & Electronic Engineering Imperial College of Science, Technology and Medicine. Project: Real-Time Speech Enhancement

Department of Electrical & Electronic Engineering Imperial College of Science, Technology and Medicine. Project: Real-Time Speech Enhancement Department of Electrical & Electronic Engineering Imperial College of Science, Technology and Medicine Project: Real-Time Speech Enhancement Introduction Telephones are increasingly being used in noisy

More information

Reconstruction of Ca 2+ dynamics from low frame rate Ca 2+ imaging data CS229 final project. Submitted by: Limor Bursztyn

Reconstruction of Ca 2+ dynamics from low frame rate Ca 2+ imaging data CS229 final project. Submitted by: Limor Bursztyn Reconstruction of Ca 2+ dynamics from low frame rate Ca 2+ imaging data CS229 final project. Submitted by: Limor Bursztyn Introduction Active neurons communicate by action potential firing (spikes), accompanied

More information

Restoration of Hyperspectral Push-Broom Scanner Data

Restoration of Hyperspectral Push-Broom Scanner Data Restoration of Hyperspectral Push-Broom Scanner Data Rasmus Larsen, Allan Aasbjerg Nielsen & Knut Conradsen Department of Mathematical Modelling, Technical University of Denmark ABSTRACT: Several effects

More information

Scout 2.0 Software. Introductory Training

Scout 2.0 Software. Introductory Training Scout 2.0 Software Introductory Training Welcome! In this training we will cover: How to analyze scwest chip images in Scout Opening images Detecting peaks Eliminating noise peaks Labeling your peaks of

More information

Normalization Methods for Two-Color Microarray Data

Normalization Methods for Two-Color Microarray Data Normalization Methods for Two-Color Microarray Data 1/13/2009 Copyright 2009 Dan Nettleton What is Normalization? Normalization describes the process of removing (or minimizing) non-biological variation

More information

Smart Coding Technology

Smart Coding Technology WHITE PAPER Smart Coding Technology Panasonic Video surveillance systems Vol.2 Table of contents 1. Introduction... 1 2. Panasonic s Smart Coding Technology... 2 3. Technology to assign data only to subjects

More information

Skip Length and Inter-Starvation Distance as a Combined Metric to Assess the Quality of Transmitted Video

Skip Length and Inter-Starvation Distance as a Combined Metric to Assess the Quality of Transmitted Video Skip Length and Inter-Starvation Distance as a Combined Metric to Assess the Quality of Transmitted Video Mohamed Hassan, Taha Landolsi, Husameldin Mukhtar, and Tamer Shanableh College of Engineering American

More information

Brain-Computer Interface (BCI)

Brain-Computer Interface (BCI) Brain-Computer Interface (BCI) Christoph Guger, Günter Edlinger, g.tec Guger Technologies OEG Herbersteinstr. 60, 8020 Graz, Austria, guger@gtec.at This tutorial shows HOW-TO find and extract proper signal

More information

Understanding Compression Technologies for HD and Megapixel Surveillance

Understanding Compression Technologies for HD and Megapixel Surveillance When the security industry began the transition from using VHS tapes to hard disks for video surveillance storage, the question of how to compress and store video became a top consideration for video surveillance

More information

VISSIM Tutorial. Starting VISSIM and Opening a File CE 474 8/31/06

VISSIM Tutorial. Starting VISSIM and Opening a File CE 474 8/31/06 VISSIM Tutorial Starting VISSIM and Opening a File Click on the Windows START button, go to the All Programs menu and find the PTV_Vision directory. Start VISSIM by selecting the executable file. The following

More information

Supplementary Note. Supplementary Table 1. Coverage in patent families with a granted. all patent. Nature Biotechnology: doi: /nbt.

Supplementary Note. Supplementary Table 1. Coverage in patent families with a granted. all patent. Nature Biotechnology: doi: /nbt. Supplementary Note Of the 100 million patent documents residing in The Lens, there are 7.6 million patent documents that contain non patent literature citations as strings of free text. These strings have

More information

Multi-Frame Matrix Capture Common File Format (MFMC- CFF) Requirements Capture

Multi-Frame Matrix Capture Common File Format (MFMC- CFF) Requirements Capture University of Bristol NDT Laboratory Multi-Frame Matrix Capture Common File Format (MFMC- CFF) Requirements Capture Martin Mienczakowski, September 2014 OVERVIEW A project has been launched at the University

More information

Outline for ContigExpress workshop

Outline for ContigExpress workshop Outline for ContigExpress workshop Importing fragments Individual editing Group editing Algorithm Generate contigs and editing contigs 1203 G G T C G A C C C A C G C G T C C G G A A C T T A C T A A A A

More information

Creating a Feature Vector to Identify Similarity between MIDI Files

Creating a Feature Vector to Identify Similarity between MIDI Files Creating a Feature Vector to Identify Similarity between MIDI Files Joseph Stroud 2017 Honors Thesis Advised by Sergio Alvarez Computer Science Department, Boston College 1 Abstract Today there are many

More information

FPA (Focal Plane Array) Characterization set up (CamIRa) Standard Operating Procedure

FPA (Focal Plane Array) Characterization set up (CamIRa) Standard Operating Procedure FPA (Focal Plane Array) Characterization set up (CamIRa) Standard Operating Procedure FACULTY IN-CHARGE Prof. Subhananda Chakrabarti (IITB) SYSTEM OWNER Hemant Ghadi (ghadihemant16@gmail.com) 05 July 2013

More information

Dual Link DVI Receiver Implementation

Dual Link DVI Receiver Implementation Dual Link DVI Receiver Implementation This application note describes some features of single link receivers that must be considered when using 2 devices for a dual link application. Specific characteristics

More information

Using Extra Loudspeakers and Sound Reinforcement

Using Extra Loudspeakers and Sound Reinforcement 1 SX80, Codec Pro A guide to providing a better auditory experience Produced: December 2018 for CE9.6 2 Contents What s in this guide Contents Introduction...3 Codec SX80: Use with Extra Loudspeakers (I)...4

More information

Story Tracking in Video News Broadcasts. Ph.D. Dissertation Jedrzej Miadowicz June 4, 2004

Story Tracking in Video News Broadcasts. Ph.D. Dissertation Jedrzej Miadowicz June 4, 2004 Story Tracking in Video News Broadcasts Ph.D. Dissertation Jedrzej Miadowicz June 4, 2004 Acknowledgements Motivation Modern world is awash in information Coming from multiple sources Around the clock

More information

How to Manage Video Frame- Processing Time Deviations in ASIC and SOC Video Processors

How to Manage Video Frame- Processing Time Deviations in ASIC and SOC Video Processors WHITE PAPER How to Manage Video Frame- Processing Time Deviations in ASIC and SOC Video Processors Some video frames take longer to process than others because of the nature of digital video compression.

More information

Auditory Illusions. Diana Deutsch. The sounds we perceive do not always correspond to those that are

Auditory Illusions. Diana Deutsch. The sounds we perceive do not always correspond to those that are In: E. Bruce Goldstein (Ed) Encyclopedia of Perception, Volume 1, Sage, 2009, pp 160-164. Auditory Illusions Diana Deutsch The sounds we perceive do not always correspond to those that are presented. When

More information

Contents. xv xxi xxiii xxiv. 1 Introduction 1 References 4

Contents. xv xxi xxiii xxiv. 1 Introduction 1 References 4 Contents List of figures List of tables Preface Acknowledgements xv xxi xxiii xxiv 1 Introduction 1 References 4 2 Digital video 5 2.1 Introduction 5 2.2 Analogue television 5 2.3 Interlace 7 2.4 Picture

More information

Intelligent Monitoring Software IMZ-RS300. Series IMZ-RS301 IMZ-RS304 IMZ-RS309 IMZ-RS316 IMZ-RS332 IMZ-RS300C

Intelligent Monitoring Software IMZ-RS300. Series IMZ-RS301 IMZ-RS304 IMZ-RS309 IMZ-RS316 IMZ-RS332 IMZ-RS300C Intelligent Monitoring Software IMZ-RS300 Series IMZ-RS301 IMZ-RS304 IMZ-RS309 IMZ-RS316 IMZ-RS332 IMZ-RS300C Flexible IP Video Monitoring With the Added Functionality of Intelligent Motion Detection With

More information

PSC300 Operation Manual

PSC300 Operation Manual PSC300 Operation Manual Version 9.10 General information Prior to any attempt to operate this Columbia PSC 300, operator should read and understand the complete operation of the cubing system. It is very

More information

GLog Users Manual.

GLog Users Manual. GLog Users Manual GLog is copyright 2000 Scott Technical Instruments It may be copied freely provided that it remains unmodified, and this manual is distributed with it. www.scottech.net Introduction GLog

More information

Design Project: Designing a Viterbi Decoder (PART I)

Design Project: Designing a Viterbi Decoder (PART I) Digital Integrated Circuits A Design Perspective 2/e Jan M. Rabaey, Anantha Chandrakasan, Borivoje Nikolić Chapters 6 and 11 Design Project: Designing a Viterbi Decoder (PART I) 1. Designing a Viterbi

More information

Cycle-7 MAMA Pulse height distribution stability: Fold Analysis Measurement

Cycle-7 MAMA Pulse height distribution stability: Fold Analysis Measurement STIS Instrument Science Report, STIS 98-02R Cycle-7 MAMA Pulse height distribution stability: Fold Analysis Measurement Harry Ferguson, Mark Clampin and Vic Argabright October 26, 1998 ABSTRACT We describe

More information

PAPER Wireless Multi-view Video Streaming with Subcarrier Allocation

PAPER Wireless Multi-view Video Streaming with Subcarrier Allocation IEICE TRANS. COMMUN., VOL.Exx??, NO.xx XXXX 200x 1 AER Wireless Multi-view Video Streaming with Subcarrier Allocation Takuya FUJIHASHI a), Shiho KODERA b), Nonmembers, Shunsuke SARUWATARI c), and Takashi

More information

Techniques to Reduce Manufacturing Cost-of-Test of Optical Transmitters, Flex DCA Interface

Techniques to Reduce Manufacturing Cost-of-Test of Optical Transmitters, Flex DCA Interface Techniques to Reduce Manufacturing Cost-of-Test of Optical Transmitters, Flex DCA Interface Application Note Introduction Manufacturers of optical transceivers are faced with increasing challenges to their

More information

Table of content. Table of content Introduction Concepts Hardware setup...4

Table of content. Table of content Introduction Concepts Hardware setup...4 Table of content Table of content... 1 Introduction... 2 1. Concepts...3 2. Hardware setup...4 2.1. ArtNet, Nodes and Switches...4 2.2. e:cue butlers...5 2.3. Computer...5 3. Installation...6 4. LED Mapper

More information

A Matlab toolbox for. Characterisation Of Recorded Underwater Sound (CHORUS) USER S GUIDE

A Matlab toolbox for. Characterisation Of Recorded Underwater Sound (CHORUS) USER S GUIDE Centre for Marine Science and Technology A Matlab toolbox for Characterisation Of Recorded Underwater Sound (CHORUS) USER S GUIDE Version 5.0b Prepared for: Centre for Marine Science and Technology Prepared

More information

Python Quick-Look Utilities for Ground WFC3 Images

Python Quick-Look Utilities for Ground WFC3 Images Instrument Science Report WFC3 2008-002 Python Quick-Look Utilities for Ground WFC3 Images A.R. Martel January 25, 2008 ABSTRACT A Python module to process and manipulate ground WFC3 UVIS and IR images

More information

Lecture 2 Video Formation and Representation

Lecture 2 Video Formation and Representation 2013 Spring Term 1 Lecture 2 Video Formation and Representation Wen-Hsiao Peng ( 彭文孝 ) Multimedia Architecture and Processing Lab (MAPL) Department of Computer Science National Chiao Tung University 1

More information

TOMELLERI ENGINEERING MEASURING SYSTEMS. TUBO Version 7.2 Software Manual rev.0

TOMELLERI ENGINEERING MEASURING SYSTEMS. TUBO Version 7.2 Software Manual rev.0 TOMELLERI ENGINEERING MEASURING SYSTEMS TUBO Version 7.2 Software Manual rev.0 Index 1. Overview... 3 2. Basic information... 4 2.1. Main window / Diagnosis... 5 2.2. Settings Window... 6 2.3. Serial transmission

More information

GANZ Bridge Powered by

GANZ Bridge Powered by GANZ Bridge Powered by User Guide Wednesday, July 05, 2017 CBC AMERICAS, Corp. 1 P a g e Table of Contents Chapter 1... 7 Chapter 2... 8 2.1 Fundamentals... 8 2.2 User Credentials... 8 2.3 Advanced Topics...

More information

The Measurement Tools and What They Do

The Measurement Tools and What They Do 2 The Measurement Tools The Measurement Tools and What They Do JITTERWIZARD The JitterWizard is a unique capability of the JitterPro package that performs the requisite scope setup chores while simplifying

More information

DELTA MODULATION AND DPCM CODING OF COLOR SIGNALS

DELTA MODULATION AND DPCM CODING OF COLOR SIGNALS DELTA MODULATION AND DPCM CODING OF COLOR SIGNALS Item Type text; Proceedings Authors Habibi, A. Publisher International Foundation for Telemetering Journal International Telemetering Conference Proceedings

More information

Fig. 1 Add the Aro spotfinding Suite folder to MATLAB's set path.

Fig. 1 Add the Aro spotfinding Suite folder to MATLAB's set path. Aro spotfinding Suite v2.5 User Guide A machine-learning-based automatic MATLAB package to analyze smfish images. By Allison Wu and Scott Rifkin, December 2014 1. Installation 1. Requirements This software

More information

Long and Fast Up/Down Counters Pushpinder Kaur CHOUHAN 6 th Jan, 2003

Long and Fast Up/Down Counters Pushpinder Kaur CHOUHAN 6 th Jan, 2003 1 Introduction Long and Fast Up/Down Counters Pushpinder Kaur CHOUHAN 6 th Jan, 2003 Circuits for counting both forward and backward events are frequently used in computers and other digital systems. Digital

More information

Implementation of Real- Time Spectrum Analysis

Implementation of Real- Time Spectrum Analysis Implementation of Real-Time Spectrum Analysis White Paper Products: R&S FSVR This White Paper describes the implementation of the R&S FSVR s realtime capabilities. It shows fields of application as well

More information

PS User Guide Series Seismic-Data Display

PS User Guide Series Seismic-Data Display PS User Guide Series 2015 Seismic-Data Display Prepared By Choon B. Park, Ph.D. January 2015 Table of Contents Page 1. File 2 2. Data 2 2.1 Resample 3 3. Edit 4 3.1 Export Data 4 3.2 Cut/Append Records

More information

An Overview of Video Coding Algorithms

An Overview of Video Coding Algorithms An Overview of Video Coding Algorithms Prof. Ja-Ling Wu Department of Computer Science and Information Engineering National Taiwan University Video coding can be viewed as image compression with a temporal

More information

Release Notes for LAS AF version 1.8.0

Release Notes for LAS AF version 1.8.0 October 1 st, 2007 Release Notes for LAS AF version 1.8.0 1. General Information A new structure of the online help is being implemented. The focus is on the description of the dialogs of the LAS AF. Configuration

More information

CSE Data Visualization. Graphical Perception. Jeffrey Heer University of Washington

CSE Data Visualization. Graphical Perception. Jeffrey Heer University of Washington CSE 512 - Data Visualization Graphical Perception Jeffrey Heer University of Washington Design Principles [Mackinlay 86] Expressiveness A set of facts is expressible in a visual language if the sentences

More information

Example: compressing black and white images 2 Say we are trying to compress an image of black and white pixels: CSC310 Information Theory.

Example: compressing black and white images 2 Say we are trying to compress an image of black and white pixels: CSC310 Information Theory. CSC310 Information Theory Lecture 1: Basics of Information Theory September 11, 2006 Sam Roweis Example: compressing black and white images 2 Say we are trying to compress an image of black and white pixels:

More information

MC9211 Computer Organization

MC9211 Computer Organization MC9211 Computer Organization Unit 2 : Combinational and Sequential Circuits Lesson2 : Sequential Circuits (KSB) (MCA) (2009-12/ODD) (2009-10/1 A&B) Coverage Lesson2 Outlines the formal procedures for the

More information

Patchmaster. Elektronik. The Pulse generator. February 2013

Patchmaster. Elektronik. The Pulse generator. February 2013 Patchmaster The Pulse generator Elektronik Telly Galiatsatos, BS 1987: Graduated at Queens College, NY Computer Science 1987-2007: Instrutech Corporation IT Engineering Support Software Engineer, Sales

More information

EDDY CURRENT IMAGE PROCESSING FOR CRACK SIZE CHARACTERIZATION

EDDY CURRENT IMAGE PROCESSING FOR CRACK SIZE CHARACTERIZATION EDDY CURRENT MAGE PROCESSNG FOR CRACK SZE CHARACTERZATON R.O. McCary General Electric Co., Corporate Research and Development P. 0. Box 8 Schenectady, N. Y. 12309 NTRODUCTON Estimation of crack length

More information

Using Genre Classification to Make Content-based Music Recommendations

Using Genre Classification to Make Content-based Music Recommendations Using Genre Classification to Make Content-based Music Recommendations Robbie Jones (rmjones@stanford.edu) and Karen Lu (karenlu@stanford.edu) CS 221, Autumn 2016 Stanford University I. Introduction Our

More information

Adaptive decoding of convolutional codes

Adaptive decoding of convolutional codes Adv. Radio Sci., 5, 29 214, 27 www.adv-radio-sci.net/5/29/27/ Author(s) 27. This work is licensed under a Creative Commons License. Advances in Radio Science Adaptive decoding of convolutional codes K.

More information

IT T35 Digital system desigm y - ii /s - iii

IT T35 Digital system desigm y - ii /s - iii UNIT - III Sequential Logic I Sequential circuits: latches flip flops analysis of clocked sequential circuits state reduction and assignments Registers and Counters: Registers shift registers ripple counters

More information

Reduction of Device Damage During Dry Etching of Advanced MMIC Devices Using Optical Emission Spectroscopy

Reduction of Device Damage During Dry Etching of Advanced MMIC Devices Using Optical Emission Spectroscopy Reduction of Device Damage During Dry Etching of Advanced MMIC Devices Using Optical Emission Spectroscopy D. Johnson, R. Westerman, M. DeVre, Y. Lee, J. Sasserath Unaxis USA, Inc. 10050 16 th Street North

More information

SVC Uncovered W H I T E P A P E R. A short primer on the basics of Scalable Video Coding and its benefits

SVC Uncovered W H I T E P A P E R. A short primer on the basics of Scalable Video Coding and its benefits A short primer on the basics of Scalable Video Coding and its benefits Stefan Slivinski Video Team Manager LifeSize, a division of Logitech Table of Contents 1 Introduction..................................................

More information

Improving Frame Based Automatic Laughter Detection

Improving Frame Based Automatic Laughter Detection Improving Frame Based Automatic Laughter Detection Mary Knox EE225D Class Project knoxm@eecs.berkeley.edu December 13, 2007 Abstract Laughter recognition is an underexplored area of research. My goal for

More information

Real Time Commercial Detection in Videos

Real Time Commercial Detection in Videos Real Time Commercial Detection in Videos Zheyun Feng Comcast Lab, DC/Michigan State University fengzheyun@gmail.com Jan Neumann Comcast Lab, DC Jan Neumann@cable.comcast.com Abstract In this report, we

More information

Vocoder Reference Test TELECOMMUNICATIONS INDUSTRY ASSOCIATION

Vocoder Reference Test TELECOMMUNICATIONS INDUSTRY ASSOCIATION TIA/EIA STANDARD ANSI/TIA/EIA-102.BABC-1999 Approved: March 16, 1999 TIA/EIA-102.BABC Project 25 Vocoder Reference Test TIA/EIA-102.BABC (Upgrade and Revision of TIA/EIA/IS-102.BABC) APRIL 1999 TELECOMMUNICATIONS

More information

What s New in Raven May 2006 This document briefly summarizes the new features that have been added to Raven since the release of Raven

What s New in Raven May 2006 This document briefly summarizes the new features that have been added to Raven since the release of Raven What s New in Raven 1.3 16 May 2006 This document briefly summarizes the new features that have been added to Raven since the release of Raven 1.2.1. Extensible multi-channel audio input device support

More information

Video Surveillance *

Video Surveillance * OpenStax-CNX module: m24470 1 Video Surveillance * Jacob Fainguelernt This work is produced by OpenStax-CNX and licensed under the Creative Commons Attribution License 2.0 Abstract This module describes

More information

Image Acquisition Technology

Image Acquisition Technology Image Choosing the Right Image Acquisition Technology A Machine Vision White Paper 1 Today, machine vision is used to ensure the quality of everything from tiny computer chips to massive space vehicles.

More information

2. Problem formulation

2. Problem formulation Artificial Neural Networks in the Automatic License Plate Recognition. Ascencio López José Ignacio, Ramírez Martínez José María Facultad de Ciencias Universidad Autónoma de Baja California Km. 103 Carretera

More information

Overview of All Pixel Circuits for Active Matrix Organic Light Emitting Diode (AMOLED)

Overview of All Pixel Circuits for Active Matrix Organic Light Emitting Diode (AMOLED) Chapter 2 Overview of All Pixel Circuits for Active Matrix Organic Light Emitting Diode (AMOLED) ---------------------------------------------------------------------------------------------------------------

More information

The Million Song Dataset

The Million Song Dataset The Million Song Dataset AUDIO FEATURES The Million Song Dataset There is no data like more data Bob Mercer of IBM (1985). T. Bertin-Mahieux, D.P.W. Ellis, B. Whitman, P. Lamere, The Million Song Dataset,

More information

A HIGHLY INTERACTIVE SYSTEM FOR PROCESSING LARGE VOLUMES OF ULTRASONIC TESTING DATA. H. L. Grothues, R. H. Peterson, D. R. Hamlin, K. s.

A HIGHLY INTERACTIVE SYSTEM FOR PROCESSING LARGE VOLUMES OF ULTRASONIC TESTING DATA. H. L. Grothues, R. H. Peterson, D. R. Hamlin, K. s. A HIGHLY INTERACTIVE SYSTEM FOR PROCESSING LARGE VOLUMES OF ULTRASONIC TESTING DATA H. L. Grothues, R. H. Peterson, D. R. Hamlin, K. s. Pickens Southwest Research Institute San Antonio, Texas INTRODUCTION

More information

Sodern recent development in the design and verification of the passive polarization scramblers for space applications

Sodern recent development in the design and verification of the passive polarization scramblers for space applications Sodern recent development in the design and verification of the passive polarization scramblers for space applications M. Richert, G. Dubroca, D. Genestier, K. Ravel, M. Forget, J. Caron and J.L. Bézy

More information

MUSI-6201 Computational Music Analysis

MUSI-6201 Computational Music Analysis MUSI-6201 Computational Music Analysis Part 9.1: Genre Classification alexander lerch November 4, 2015 temporal analysis overview text book Chapter 8: Musical Genre, Similarity, and Mood (pp. 151 155)

More information

SignalTap Plus System Analyzer

SignalTap Plus System Analyzer SignalTap Plus System Analyzer June 2000, ver. 1 Data Sheet Features Simultaneous internal programmable logic device (PLD) and external (board-level) logic analysis 32-channel external logic analyzer 166

More information

The Bias-Variance Tradeoff

The Bias-Variance Tradeoff CS 2750: Machine Learning The Bias-Variance Tradeoff Prof. Adriana Kovashka University of Pittsburgh January 13, 2016 Plan for Today More Matlab Measuring performance The bias-variance trade-off Matlab

More information

Automatic Piano Music Transcription

Automatic Piano Music Transcription Automatic Piano Music Transcription Jianyu Fan Qiuhan Wang Xin Li Jianyu.Fan.Gr@dartmouth.edu Qiuhan.Wang.Gr@dartmouth.edu Xi.Li.Gr@dartmouth.edu 1. Introduction Writing down the score while listening

More information

JPEG2000: An Introduction Part II

JPEG2000: An Introduction Part II JPEG2000: An Introduction Part II MQ Arithmetic Coding Basic Arithmetic Coding MPS: more probable symbol with probability P e LPS: less probable symbol with probability Q e If M is encoded, current interval

More information

Video coding standards

Video coding standards Video coding standards Video signals represent sequences of images or frames which can be transmitted with a rate from 5 to 60 frames per second (fps), that provides the illusion of motion in the displayed

More information

Homework 2 Key-finding algorithm

Homework 2 Key-finding algorithm Homework 2 Key-finding algorithm Li Su Research Center for IT Innovation, Academia, Taiwan lisu@citi.sinica.edu.tw (You don t need any solid understanding about the musical key before doing this homework,

More information

Chapter 2 Introduction to

Chapter 2 Introduction to Chapter 2 Introduction to H.264/AVC H.264/AVC [1] is the newest video coding standard of the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG). The main improvements

More information

Keysight Technologies Techniques to Reduce Manufacturing Cost-of-Test of Optical Transmitters, Classic DCA. Application Note

Keysight Technologies Techniques to Reduce Manufacturing Cost-of-Test of Optical Transmitters, Classic DCA. Application Note Keysight Technologies Techniques to Reduce Manufacturing Cost-of-Test of Optical Transmitters, Classic DCA Application Note Introduction Manufacturers of optical transceivers are faced with increasing

More information

Extraction Methods of Watermarks from Linearly-Distorted Images to Maximize Signal-to-Noise Ratio. Brandon Migdal. Advisors: Carl Salvaggio

Extraction Methods of Watermarks from Linearly-Distorted Images to Maximize Signal-to-Noise Ratio. Brandon Migdal. Advisors: Carl Salvaggio Extraction Methods of Watermarks from Linearly-Distorted Images to Maximize Signal-to-Noise Ratio By Brandon Migdal Advisors: Carl Salvaggio Chris Honsinger A senior project submitted in partial fulfillment

More information

WHAT'S HOT: LINEAR POPULARITY PREDICTION FROM TV AND SOCIAL USAGE DATA Jan Neumann, Xiaodong Yu, and Mohamad Ali Torkamani Comcast Labs

WHAT'S HOT: LINEAR POPULARITY PREDICTION FROM TV AND SOCIAL USAGE DATA Jan Neumann, Xiaodong Yu, and Mohamad Ali Torkamani Comcast Labs WHAT'S HOT: LINEAR POPULARITY PREDICTION FROM TV AND SOCIAL USAGE DATA Jan Neumann, Xiaodong Yu, and Mohamad Ali Torkamani Comcast Labs Abstract Large numbers of TV channels are available to TV consumers

More information

A low noise multi electrode array system for in vitro electrophysiology. Mobius Tutorial AMPLIFIER TYPE SU-MED640

A low noise multi electrode array system for in vitro electrophysiology. Mobius Tutorial AMPLIFIER TYPE SU-MED640 A low noise multi electrode array system for in vitro electrophysiology Mobius Tutorial AMPLIFIER TYPE SU-MED640 Information in this document is subject to change without notice.no part of this document

More information

Hands-on session on timing analysis

Hands-on session on timing analysis Amsterdam 2010 Hands-on session on timing analysis Introduction During this session, we ll approach some basic tasks in timing analysis of x-ray time series, with particular emphasis on the typical signals

More information

MAGNETIC CARD READER DESIGN KIT TECHNICAL SPECIFICATION

MAGNETIC CARD READER DESIGN KIT TECHNICAL SPECIFICATION MAGNETIC CARD READER DESIGN KIT TECHNICAL SPECIFICATION Part Number: D99821002 Rev 212 MAY 2017 REGISTERED TO ISO 9001:2008 1710 Apollo Court Seal Beach, CA 90740 Phone: (562) 546-6400 FAX: (562) 546-6301

More information

m RSC Chromatographie Integration Methods Second Edition CHROMATOGRAPHY MONOGRAPHS Norman Dyson Dyson Instruments Ltd., UK

m RSC Chromatographie Integration Methods Second Edition CHROMATOGRAPHY MONOGRAPHS Norman Dyson Dyson Instruments Ltd., UK m RSC CHROMATOGRAPHY MONOGRAPHS Chromatographie Integration Methods Second Edition Norman Dyson Dyson Instruments Ltd., UK THE ROYAL SOCIETY OF CHEMISTRY Chapter 1 Measurements and Models The Basic Measurements

More information