DOCSLIB.ORG

DARPA and Data: a Portfolio Overview

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
DARPA and Data: a Portfolio Overview DARPA and Data: A Portfolio Overview William C. Regli Special Assistant to the Director Defense Advanced Research Projects Agency Brian Pierce Director Information Innovation Office Defense Advanced Research Projects Agency Fall 2017 Distribution Statement “A” (Approved for Public Release, Distribution Unlimited) 1 DARPA Dreams of Data • Investments over the past decade span multiple DARPA Offices and PMs • Information Innovation (I2O): Software Systems, AI, Data Analytics • Defense Sciences (DSO): Domain-driven problems (chemistry, social science, materials science, engineering design) • Microsystems Technology (MTO): New hardware to support these processes (neuromorphic processor, graph processor, learning systems) • Products include DARPA Program testbeds, data and software • The DARPA Open Catalog • Testbeds include those in big data, cyber-defense, engineering design, synthetic bio, machine reading, among others • Multiple layers and qualities of data are important • Important for reproducibility; important as fuel for future DARPA programs • Beyond public data to include “raw” data, process/workflow data • Data does not need to be organized to be useful or valuable • Software tools are getting better eXponentially, ”raw” data can be processed • Changing the economics (Forensic Data Curation) • Its about optimizing allocation of attention in human-machine teams Distribution Statement “A” (Approved for Public Release, Distribution Unlimited) 2 Working toward Wisdom Wisdom: sound judgment - governance Abstraction Wisdom (also Understanding: explanation – why “value”) Understanding Knowledge: correlation and composition – how Knowledge Information: facts - what, who, where, when data: representing signals or stimuli Information data Sapience (or processing/cognitive ‘load’) EXample of the Data-Wisdom process for model evolution and application: data Information Knowledge Understanding Wisdom IRAQ COUNTER-INSURGENCY DYNAMICS IRAQ COUNTER-INSURGENCY DYNAMICS COALITION Coalition Instit’l COIN Recent COIN Fear of Under- Related Mistake standing & Experience Coalition GOVERNMENTGovt Capability Qual/Avail Perceived Support Govt COIN of COIN COALITION Coalition Instit’l COIN Recent COIN Conflict for Conflict Appropriate COINTrai ni n g COIN Fear of Under- Related Appr Indigenous Forces Mistake Experience Costs Public Actions Specialist Insurge nt standing & Skills Coalition GOVERNMENTGovt Capability Qual/Avail Support Adequacy Ability to Support of COIN Media Emp hasis for Conflict Elapsed Govt COIN COIN Appr Perceived Govt COIN Tool s Instit’l Provoke Conflict for Conflict Appropriate COINTrai ni n g COIN on Negativ e & Ti me of Under- MILITARY – Inform al Excessive Appr Public COIN COIN Costs Public Actions Specialist Insurge nt Sensational UnderstaCOALITION nding Conflict standing & Military to Learni ng COIN Response Support Adequacy Skills Ability to Expect- Govt Comms Learni ng Media Emp hasis for Conflict Elapsed Govt COIN COIN Appr MEDIA and Expectati ons STR / OP & Adjust Unit Duratio n Tool s Instit’l Provoke Media ations Quality Bureaucr acy & & Adjust Military on Negativ e & Ti me of Under- MILITARY – Inform al Excessive Susceptibility Media PUBLIC Manpow er Organizati onal in Area Sensational Public COIN standing & Military to COIN COIN Sensation- Depth & Quality Fundi n g ApprUse Media Coverage UnderstaCOALITION nding Conflict Learni ng Response & RIP/TOA to Insur gent Delays and Expectati ons Expect- Govt Comms STR / OP & Adjust Learni ng alism Bias of Media Equip Dev Fundi ng of Forc e Media MEDIA Bureaucr acy & Unit Duratio n Message Quality Media PUBLIC ations Manpow er Quality & Adjust in Area Military Quality & Availability Coverag e Adequacy Manpow er Adequacy Proactive COIN Local Susceptibility Sensation- Depth & Quality Fundi n g Organizati onal ApprUse per to Insur gent Delays & RIP/TOA of COIN Messa ge Logistics Ops & Timeliness ApprMen tality Knowledge alism Bias of Media Equip Dev Fundi ng Quality of Forc e Perceived Inform ation Population Coalition Population Message Quality & Availability Coverag e Adequacy Manpow er Adequacy Proactive COIN Local Qual/Avail of Effectiveness & Focus Ops of COIN Messa ge per Knowledge Military Adequacy Inform ation Logistics Ops & Timeliness ApprMen tality Use of Fo rce Insurge nt Iraqi Cent ral Effectiveness Data Perceived Qual/Avail of Population Effectiveness & Focus Perceived Intel Military Ops Adequacy Message Govern ment Expected Insurge nt Effectiveness Political Satisfaction Analysis Situational Use of Fo rce Iraqi Cent ral Perceived Intel Effectiveness Benefits COIN Effective MILITARY - Stress Message Govern ment Political Expected Situational Fairness with Infrastr uctur e & Ops Satisfaction Analysis and Cre dibility to Daily Life Econ Dev Ops Resource Effectiveness Fairness Benefits with Infrastr uctur e & COIN Effective MILITARY - Ops Stress Daily Life Effective- and Cre dibility to Daily Life Resource Effectiveness Allocation Daily Life Econ Dev Ops Effective- Perceived Hope for ness Hope for Effectiveness Allocation ness Relative Self & Ops Focus TACTICAL Relative Perceived & Ops Focus Effectiveness Religious & Avg COIN Insurgent Sympathizers Religious & Self TACTICAL Governe d Effectiveness Avg COIN Ideological Appropriate Quality & Governe d Appropriate of Insur gent IRAQI Futur e Emphasis Capability of Insur gent IRAQI Ideological Capability Quality & Compatibility Inter- Volume of Compatibility Futur e Emphasis Inter- Volume of Message on per S oldie r Message on on Civilian per S oldie r on Civilian person al Actionable CiviliansGOVERNMENT LOCAL person al Actionable CiviliansGOVERNMENTLocal Govt/ LOCAL Interacti on Perceptions Civilian Local Govt/ Interacti on Perceptions Behavior Intel Civilian Behavior Intel Police/Military Relative Opport unity/ & Relationships Police/Military Relative Opport unity/ & Relationships Participation Consistency Military to Participation Military to in Central Dev Ops Attractive- Civilian in Central Dev Ops Attractive- Consistency Civilian Govt Events EffectivenessCIVILIANS ness of Qual/Avail Trust Govt Events EffectivenessCIVILIANS ness of Trust Qual/Avail Empower- Ability to Vet Visible Benefits Insurge nt of Local I nfo Ability to Vet of Local I nfo Relig/Trib/ Path Collected Empower- Visible Benefits Insurge nt ment of to Daily Life Civilian Positive Local Relig/Trib/ Path Collected Progressive Polit/Milit Civilian Presence Targ eted ment of to Daily Life Civilian Positive Local Leade rs Willingness Insurge nt Civilian Military Polit/Milit Civilian Targ eted (signals) Local Le aders Ops Offensive Ops Progressive Presence to Inter act Interacti ons Civilian Leade rs Willingness Insurge nt Civilian Military Symp- Fractio n Effectiveness Ability to Effectiveness Offensive Ops athizer Contacts Local Le aders to Inter act Interacti ons Ops Civilian Local Govt Survive Symp- Effectiveness Ability to Effectiveness Fractio n Insurge nt Civilian Fractio n Contacts Coalition Forces Developme nt Prox- athizer Survive Attack & Local Govt Fractio n Civilian Credibility & Consistency Ability to ID imity Insurge nt Effectiveness Effective Use Perception of Military Retaliate Developme nt Prox- Indigenous Government of Existing ISF IP of Coalition Insurge nts & Attack & Credibility & Consistency Govt/Police/ Manpow er Security & Intentions & Activity/ Military Prevent Effective Use Ability to ID imity Personality Attacks Effectiveness Perception of Military Retaliate Milit Capab Effectiveness Perceived Commitment Guardin g Exposure to of Existing ISF IP of Coalition Insurge nts & Stability Coalition Activity/ & Credibility Insurge nt Ability Ops Insurge nt Casualties Govt/Police/ Manpow er Security & Intentions & Military Prevent to Oper ate Attack Personality Insurge nt Effective- Milit Capab Effectiveness Perceived Commitment Exposure to Attacks Infrastr uctur e in Area ness Guardin g Coalition Economy IRAQI POLICE/ Recruiting & Credibility Stability Insurge nt Ability Insurge nt & Retention Civilian Ops Casualties Tri bal & Employment to Oper ate Attack Religious MILITARY Hard Core Insurge nt Insurge nt Casualties Insurge nt Effective- & Damages Infrastr uctur e in Area Tension Contracto r Insurge nt Insurge nts Learni ng Material Insurge nt IRAQI POLICE/ Recruiting ness Adequacy Fear of Manpow er & Support Attacks Economy in Area Employment & Retention Civilian Insurge nt Leade rship on Military Tri bal & Casualties Repercussio n Religious MILITARY Hard Core Insurge nt Insurge nt from Insurge nt & Damages Insurge nt Contracto r Insurge nt Insurge nts Learni ng Material Insurge nt Targ eted Capability Tension Adequacy Thre ats & Fear of Manpow er & in Area Support Attacks Local Civilians Insurge nt on Military Attacks on Leade rship Repercussio n Iraqis INSURGENTS Insurge nt Insurge nt Insurge nt Casualties Targ eted Capability and Capt ures Thre ats & Attacks on Iraqis INSURGENTS Insurgent Forces Infrastructure Insurge nt WORKING HYPOTHESIS Casualties and Capt ures multiple © PA Knowledge Limite d 200 6. All rights reserv ed. – 10/1 8/200 6 WORKING HYPOTHESIS sources International Diplomacy © PA Knowledge Limite d 200 6. All rights reserv ed. – 10/1 8/200 6 Descriptive model Correlative/predictive model EXplanatory model Judgement, value, (symbols, syntaX) (rules, processes, (abstractions, insight, instinct, semantics) theories, etc) principles, etc Distribution Statement “A” (Approved for Public Release, Distribution Unlimited) 3 EXamples of Data-to-Wisdom Information Knowledge Understanding Wisdom Task Determine facts
Load more

Recommended publications
  • Declarative Languages for Big Streaming Data a Database Perspective
    Tutorial Declarative Languages for Big Streaming Data A database Perspective Riccardo Tommasini Sherif Sakr University of Tartu Unversity of Tartu [email protected] [email protected] Emanuele Della Valle Hojjat Jafarpour Politecnico di Milano Confluent Inc. [email protected] [email protected] ABSTRACT sources and are pushed asynchronously to servers which are The Big Data movement proposes data streaming systems to responsible for processing them [13]. tame velocity and to enable reactive decision making. However, To facilitate the adoption, initially, most of the big stream approaching such systems is still too complex due to the paradigm processing systems provided their users with a set of API for shift they require, i.e., moving from scalable batch processing to implementing their applications. However, recently, the need for continuous data analysis and pattern detection. declarative stream processing languages has emerged to simplify Recently, declarative Languages are playing a crucial role in common coding tasks; making code more readable and main- fostering the adoption of Stream Processing solutions. In partic- tainable, and fostering the development of more complex appli- ular, several key players introduce SQL extensions for stream cations. Thus, Big Data frameworks (e.g., Flink [9], Spark [3], 1 processing. These new languages are currently playing a cen- Kafka Streams , and Storm [19]) are starting to develop their 2 3 4 tral role in fostering the stream processing paradigm shift. In own SQL-like approaches (e.g., Flink SQL , Beam SQL , KSQL ) this tutorial, we give an overview of the various languages for to declaratively tame data velocity. declarative querying interfaces big streaming data.
    [Show full text]
  • Snap Creator Framework 4.3.3 Administration Guide
    Snap Creator® Framework 4.3.3 Administration Guide February 2021 | 215-14105_C0 [email protected] Snap Creator 4.3.3 Administration Guide ii Contents Contents What Snap Creator Framework does............................................................................ 6 Benefits of using Snap Creator....................................................................................................................................... 6 Snap Creator architecture...............................................................................................8 Snap Creator Server overview........................................................................................................................................ 8 Snap Creator Agent overview.......................................................................................................................................10 Plug-ins for application integration.............................................................................................................................. 11 Managing Snap Creator Server....................................................................................13 Starting, verifying, and stopping Snap Creator Server on Windows............................................................................ 13 Starting, verifying, and stopping Snap Creator Server on UNIX................................................................................. 13 Changing the Snap Creator Server port after installation.............................................................................................14
    [Show full text]
  • The Snap Framework: a Web Toolkit for Haskell
    The Functional Web The Snap Framework A Web Toolkit for Haskell Gregory Collins • Google Switzerland Doug Beardsley • Karamaan Group askell is an advanced functional pro- the same inputs, always produce the same out- gramming language. The product of more put. This property means that you almost always H than 20 years of research, it enables rapid decompose a Haskell program into smaller con- development of robust, concise, and fast soft- stituent parts that you can test independently. ware. Haskell supports integration with other Haskell’s ecosystem also includes many power- languages and has loads of built-in concurrency, ful testing and code-coverage tools. parallelism primitives, and rich libraries. With Haskell also comes out of the box with a set its state-of-the-art testing tools and an active of easy-to-use primitives for parallel and con- community, Haskell makes it easier to produce current programming and for performance pro- flexible, maintainable, high-quality software. filing and tuning. Applications built with GHC The most popular Haskell implementation is enjoy solid multicore performance and can han- the Glasgow Haskell Compiler (GHC), a high- dle hundreds of thousands of concurrent net- performance optimizing native-code compiler. work connections. We’ve been delighted to find Here, we look at Snap, a Web-development that Haskell really shines for Web programming. framework for Haskell. Snap combines many other Web-development environments’ best fea- What’s Snap? tures: writing Web code in an expressive high- Snap offers programmers a simple, expressive level language, a rapid development cycle, fast Web programming interface at roughly the same performance for native code, and easy deploy- level of abstraction as Java servlets.
    [Show full text]
  • Kodai: a Software Architecture and Implementation for Segmentation
    University of Rhode Island DigitalCommons@URI Open Access Master's Theses 2017 Kodai: A Software Architecture and Implementation for Segmentation Rick Rejeleene University of Rhode Island, [email protected] Follow this and additional works at: https://digitalcommons.uri.edu/theses Recommended Citation Rejeleene, Rick, "Kodai: A Software Architecture and Implementation for Segmentation" (2017). Open Access Master's Theses. Paper 1107. https://digitalcommons.uri.edu/theses/1107 This Thesis is brought to you for free and open access by DigitalCommons@URI. It has been accepted for inclusion in Open Access Master's Theses by an authorized administrator of DigitalCommons@URI. For more information, please contact [email protected]. KODAI: A SOFTWARE ARCHITECTURE AND IMPLEMENTATION FOR SEGMENTATION BY RICK REJELEENE A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS OF MASTER OF SCIENCE IN COMPUTER SCIENCE UNIVERSITY OF RHODE ISLAND 2017 MASTER OF SCIENCE THESIS OF RICK REJELEENE APPROVED: Thesis Committee: Major Professor: Joan Peckham Lisa DiPippo Ruby Dholakia Nasser H Zawia DEAN OF GRADUATE COMMITTEE UNIVERSITY OF RHODE ISLAND 2017 ABSTRACT The purpose of this thesis is to design and implement a software architecture for segmen- tation models to improve revenues for a supermarket. This tool supports analysis of su- permarket products and generates results to interpret consumer behavior, to give busi- nesses deeper insights into targeted consumer markets. The software design developed is named as Kodai. Kodai is horizontally reusable and can be adapted across various indus- tries. This software framework allows testing a hypothesis to address the problem of in- creasing revenues in supermarkets. Kodai has several advantages, such as analyzing and visualizing data, and as a result, businesses can make better decisions.
    [Show full text]
  • What I Wish I Knew When Learning Haskell
    What I Wish I Knew When Learning Haskell Stephen Diehl 2 Version This is the fifth major draft of this document since 2009. All versions of this text are freely available onmywebsite: 1. HTML Version ­ http://dev.stephendiehl.com/hask/index.html 2. PDF Version ­ http://dev.stephendiehl.com/hask/tutorial.pdf 3. EPUB Version ­ http://dev.stephendiehl.com/hask/tutorial.epub 4. Kindle Version ­ http://dev.stephendiehl.com/hask/tutorial.mobi Pull requests are always accepted for fixes and additional content. The only way this document will stayupto date and accurate through the kindness of readers like you and community patches and pull requests on Github. https://github.com/sdiehl/wiwinwlh Publish Date: March 3, 2020 Git Commit: 77482103ff953a8f189a050c4271919846a56612 Author This text is authored by Stephen Diehl. 1. Web: www.stephendiehl.com 2. Twitter: https://twitter.com/smdiehl 3. Github: https://github.com/sdiehl Special thanks to Erik Aker for copyediting assistance. Copyright © 2009­2020 Stephen Diehl This code included in the text is dedicated to the public domain. You can copy, modify, distribute and perform thecode, even for commercial purposes, all without asking permission. You may distribute this text in its full form freely, but may not reauthor or sublicense this work. Any reproductions of major portions of the text must include attribution. The software is provided ”as is”, without warranty of any kind, express or implied, including But not limitedtothe warranties of merchantability, fitness for a particular purpose and noninfringement. In no event shall the authorsor copyright holders be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, Arising from, out of or in connection with the software or the use or other dealings in the software.
    [Show full text]
  • Carnivorous Plant Newsletter V44 N4 December 2015
    Technical Refereed Contribution Several pygmy Sundew species possess catapult-flypaper traps with repetitive function, indicating a possible evolutionary change into aquatic snap traps similar to Aldrovanda Siegfried R. H. Hartmeyer and Irmgard Hartmeyer • Weil am Rhein • Germany • s.hartmeyer@ t-online.de • www.hartmeyer.de Keywords: Drosera, pygmy Sundew, Aldrovanda, Dionaea, Droseraceae, Collembola, carnivorous plant, catapult-flypaper trap, snap trap, snap-tentacle, functional morphology, phylogeny. Abstract: Approximately 50 species of pygmy Sundews (genus Drosera, section Bryastrum) occur in the South of Australia and one each in New Zealand (D. pygmaea) and Venezuela (D. meristo- caulis). They grow mainly as small stemless rosettes possessing minute trapping leaves of 1-2 mm diameter with prominent marginal tentacles, or have elongated erect stems. The caulescent species possess only mucus-producing tentacles that are most effective in capturing small flying insects. The acaulescent species in contrast are specialized on crawling prey (Verbeek & Boasson 1993) and have developed mucus-free snap-tentacles (Fig. 1), able to bend surprisingly rapidly towards the leaf center. They lift prey like, e.g. springtails (Collembola) from the ground and carry it with a 180°-movement from the periphery of the plant onto the sticky leaf. Our examinations brought to light that several small species of section Bryastrum are able to catapult small animals even within fractions of a second. If the whole leaf is touched, several or even all marginal tentacles perform such bending movements simultaneously. We documented this behavior on video, featured on our film “Catapults in Pygmyland” on YouTube (www.youtube.com/watch?v=5k7GYGibdjM). Our results prove that more than only one species in the genus Drosera possess rapidly moving catapult-flypaper traps and that the examined pygmy catapults show a further specialization and function repeatedly (in contrast to the one-shot snap tentacles of D.
    [Show full text]
  • Space and Defense Issue
    SPACE and DEFENSE Volume Nine Number One Spring 2016 Attack on the Brain: Neurowars and Neurowarfare Armin Krishnan Volume Five Number One Brazil Space: SGDC Satellite Sum Gills Vilar Lopes mer 2011 Mexico Aerospace: The Querétaro Cluster Mónica Casalet REVIEW: Crowded Orbits Coalitions in Space:Deron Jackson Where Networks are PowerPublisher’s Corner: Space Policy’s SALT Moment Ambassadorby James Roger G. ClayHarrison Moltz The 2010 National Space Policy: Down to Earth? by Joan Johnson-Freese Space & Defense Journal of the United States Air Force Academy Eisenhower Center for Space and Defense Studies Publisher Ambassador Roger Harrison, [email protected] Inaugural Director and Co-founder, Eisenhower Center for Space and Defense Studies Editor Dr. Damon Coletta U.S. Air Force Academy, USA Associate Editors Mr. Deron Jackson Dr. Peter Hays Director, Eisenhower Center George Washington University, USA U.S. Air Force Academy, USA Ms. Jonty Kasku-Jackson National Security Space Institute, USA Dr. Schuyler Foerster U.S. Air Force Academy, USA Thank You to Our Reviewers Andrew Aldrin Joanne Gabrynowicz United Launch Alliance, USA University of Mississippi, USA James Armor Jason Healey ATK, USA Atlantic Council, USA William Barry Theresa Hitchens NASA Headquarters, USA United Nations, Switzerland Daniel Blinder Wade Huntley UNSAM-CONICET, Argentina Independent Researcher, USA Dean Cheng Ram Jakhu Heritage Foundation, USA McGill University, Canada, USA Robert Callahan Dana Johnson NORAD-NORTHCOM, USA Department of State, USA Robert Carriedo Roger Launius U.S. Air Force Academy, USA National Air and Space Museum Frans von der Dunk John Logsdon University of Nebraska, USA George Washington University, USA Paul Eckart Agnieszka Lukaszczyk Boeing, USA Secure World Foundation, Belgium Andrew Erickson Molly Macauley Naval War College, USA Resources for the Future, USA Laura Delgado Lopez Dimitrios Stroikos Secure World Foundation, USA London School of Economics, United Kingdom Adam Lowther Brent Talbot SANDS, Kirtland AFB, USA U.S.
    [Show full text]
  • STORM: Refinement Types for Secure Web Applications
    STORM: Refinement Types for Secure Web Applications Nico Lehmann Rose Kunkel Jordan Brown Jean Yang UC San Diego UC San Diego Independent Akita Software Niki Vazou Nadia Polikarpova Deian Stefan Ranjit Jhala IMDEA Software Institute UC San Diego UC San Diego UC San Diego Abstract Centralizing policy specification is not a new idea. Several We present STORM, a web framework that allows developers web frameworks (e.g., HAILS [4], JACQUELINE [5], and to build MVC applications with compile-time enforcement of LWEB [6]) already do this. These frameworks, however, have centrally specified data-dependent security policies. STORM two shortcomings that have hindered their adoption. First, ensures security using a Security Typed ORM that refines the they enforce policies at run-time, typically using dynamic (type) abstractions of each layer of the MVC API with logical information flow control (IFC). While dynamic enforcement assertions that describe the data produced and consumed by is better than no enforcement, dynamic IFC imposes a high the underlying operation and the users allowed access to that performance overhead, since the system must be modified to data. To evaluate the security guarantees of STORM, we build a track the provenance of data and restrict where it is allowed formally verified reference implementation using the Labeled to flow. More importantly, certain policy violations are only IO (LIO) IFC framework. We present case studies and end-to- discovered once the system is deployed, at which point they end applications that show how STORM lets developers specify may be difficult or expensive to fix, e.g., on applications diverse policies while centralizing the trusted code to under 1% running on IoT devices [7].
    [Show full text]
  • FOSS Philosophy 6 the FOSS Development Method 7
    1 Published by the United Nations Development Programme’s Asia-Pacific Development Information Programme (UNDP-APDIP) Kuala Lumpur, Malaysia www.apdip.net Email: [email protected] © UNDP-APDIP 2004 The material in this book may be reproduced, republished and incorporated into further works provided acknowledgement is given to UNDP-APDIP. For full details on the license governing this publication, please see the relevant Annex. ISBN: 983-3094-00-7 Design, layout and cover illustrations by: Rezonanze www.rezonanze.com PREFACE 6 INTRODUCTION 6 What is Free/Open Source Software? 6 The FOSS philosophy 6 The FOSS development method 7 What is the history of FOSS? 8 A Brief History of Free/Open Source Software Movement 8 WHY FOSS? 10 Is FOSS free? 10 How large are the savings from FOSS? 10 Direct Cost Savings - An Example 11 What are the benefits of using FOSS? 12 Security 13 Reliability/Stability 14 Open standards and vendor independence 14 Reduced reliance on imports 15 Developing local software capacity 15 Piracy, IPR, and the WTO 16 Localization 16 What are the shortcomings of FOSS? 17 Lack of business applications 17 Interoperability with proprietary systems 17 Documentation and “polish” 18 FOSS SUCCESS STORIES 19 What are governments doing with FOSS? 19 Europe 19 Americas 20 Brazil 21 Asia Pacific 22 Other Regions 24 What are some successful FOSS projects? 25 BIND (DNS Server) 25 Apache (Web Server) 25 Sendmail (Email Server) 25 OpenSSH (Secure Network Administration Tool) 26 Open Office (Office Productivity Suite) 26 LINUX 27 What is Linux?
    [Show full text]
  • Broad Agency Announcement Computational Cultural Understanding (CCU) Information Innovation Office HR001121S0024 April 29, 2021 TABLE of CONTENTS
    Broad Agency Announcement Computational Cultural Understanding (CCU) Information Innovation Office HR001121S0024 April 29, 2021 TABLE OF CONTENTS PART II: FULL TEXT OF ANNOUNCEMENT ...........................................................................4 I. Funding Opportunity Description ............................................................................................4 A. Program Overview ............................................................................................................4 B. Program Structure .............................................................................................................6 C. Program Metrics..............................................................................................................10 D. Deliverables ....................................................................................................................12 E. Intellectual Property........................................................................................................13 II. Award Information.................................................................................................................13 A. General Award Information............................................................................................13 B. Fundamental Research ....................................................................................................14 III. Eligibility Information........................................................................................................15
    [Show full text]
  • Multimedia Systems
    MVC Design Pattern Introduction to MVC and compare it with others Gholamhossein Tavasoli @ ZNU Separation of Concerns o All these methods do only one thing “Separation of Concerns” or “Layered Architecture” but in their own way. o All these concepts are pretty old, like idea of MVC was tossed in 1970s. o All these patterns forces a separation of concerns, it means domain model and controller logic are decoupled from user interface (view). As a result maintenance and testing of the application become simpler and easier. MVC Pattern Architecture o MVC stands for Model-View-Controller Explanation of Modules: Model o The Model represents a set of classes that describe the business logic i.e. business model as well as data access operations i.e. data model. o It also defines business rules for data means how the data can be created, sotored, changed and manipulated. Explanation of Modules: View o The View represents the UI components like CSS, jQuery, HTML etc. o It is only responsible for displaying the data that is received from the controller as the result. o This also transforms the model(s) into UI. o Views can be nested Explanation of Modules: Controller o The Controller is responsible to process incoming requests. o It receives input from users via the View, then process the user's data with the help of Model and passing the results back to the View. o Typically, it acts as the coordinator between the View and the Model. o There is One-to-Many relationship between Controller and View, means one controller can handle many views.
    [Show full text]
  • Cherrypy Documentation Release 3.3.0
    CherryPy Documentation Release 3.3.0 CherryPy Team August 05, 2016 Contents 1 What is CherryPy? 1 2 What CherryPy is NOT? 3 3 Contents 5 3.1 Why choose CherryPy?.........................................5 3.2 Installation................................................6 3.3 CherryPy License (BSD).........................................8 4 Tutorial 9 4.1 What is this tutorial about?........................................9 4.2 Start the Tutorial.............................................9 5 Programmer’s Guide 35 5.1 Features.................................................. 35 5.2 HTTP details............................................... 66 6 Deployment Guide 79 6.1 Applications............................................... 79 6.2 Servers.................................................. 79 6.3 Environment............................................... 87 7 Reference Manual 91 7.1 cherrypy._cpchecker ....................................... 91 7.2 cherrypy._cpconfig ........................................ 92 7.3 cherrypy._cpdispatch – Mapping URI’s to handlers...................... 94 7.4 cherrypy._cprequest ....................................... 96 7.5 cherrypy._cpserver ........................................ 101 7.6 cherrypy._cptools ........................................ 103 7.7 cherrypy._cptree ......................................... 105 7.8 cherrypy._cpwsgi ......................................... 107 7.9 cherrypy ................................................ 108 7.10 cherrypy.lib...............................................
    [Show full text]