Why Peer Evaluation? ccountability Accountability Accountabilit Accountability Accountability Accountabilit Accountability Accountability Accountabil Accountability Accountability Accountabil Accountability Accountability Accountabil Accountability Accountability Accountability Accountability Accountability Accountability Accountability Accountability
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Industry Speaker Series June 4, 2003 Texas Instruments: E&PS Supply Chain Apr. 10, 2003 Retail Demand and Supply Chain Management – continued Apr. 17, 2003 Softgoods Demand and Supply Chain Management Apr. 7, 2003 Consumer Electronics Supply Chain Management and Case Study – continued Mar. 24, 2003 Consumer Electronics Supply Chain Management and Case Study – continued Feb. 28, 2003 Wireless Data Management and the Supply Chai n Feb. 20, 2003 Retail Demand and Supply Chain Management Feb. 17, 2003 Consumer Electronics Supply Chain Management and Case Study – continued Jan. 31, 2003 Air Cargo Supply Chain Management and Challe nges Unlock the Value in Your Supply Chain Jan. 28, 2003 Lean Design: Using Blitz QFD to Deliver Maximu m for Minimum Contract Manufacturing in China Jan. 27, 2003 Consumer Electronics Supply Chain Management and Case Study June 23, 2004 Supply Chain Management at BlockBuster June 17, 2004 CEO Forum & Agile Seminar Feb. 16, 2004 Inventory Management Nov. 3, 2003 Logistics Planning with i2 Oct. 3, 2003 Trends in Wholesale Inventory Management Sept. 26, 2003 The Art and Science of Consulting Sept. 12, 2003 The Outsourced Supply Chain July 28, 2003 Supply Chain Management with Oracle July 21, 2003 Supply Chain Management with SAP APO July 21, 2003 Filling a Niche in the Consumer Goods Demand Chain July 18, 2003 Dell Site Visit, Austin Texas July 14, 2003 June 23, 2003 Slide 14
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The Matrix Structure Cross-Functional Coordination Clear Accountability Dual Chain of Command Allocation of Specialists
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Acronyms • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • MTS – Message Transceiver Service NCW – Network Centric • FRP – Full Rate Production 3CE – Cross-Command Collaborative Effort Warfare • FSE – FCS Simulation Environment ACS – Aerial Common Sensor • NEC2 – Networked Effects Command & Control AKO – Army Knowledge On-Line • HLA - RTI – High Level Architecture – Run Time Interface • NVIG – Night Vision Image Generator ALCES - Aggregate Level Communications Effects Service • HC-NEBC – Human Centric – Network Enabled Battle Command • OCS – Organic Communications Service AMS – Aviation Mobility Service • OneSAF – One Semi-Automated Forces • HPM – Human Performance Model AMSWG – (OSD) Acquisition Modeling & Simulation • OOS – OneSAF Objective System • IDE – Integrated Development Environment Working Group • OTB – OneSAF Testbed Baseline • IOC – Initial Operational Capability ARMS – Armaments Service • OTC – Operational Test Command • IOT&E – Initial Operational Test and Evaluation ATC – Automated Test Capability • PEO – Program Executive Office ATEC – Army Test and Evaluation Command • IER – Information Exchange Requirement • PM – Product, or Program or Project Manager ATIN – ATEC Test Integration Network • R2S – Relative Roles Server • IP03 – Integrated Process 03, Networked Fires AUTL – Army Universal Task List • RDECOM – Research, Development, & Engineering Command • IPT – Integrated Process Team BCT – Brigade Combat Team • RDEC – Research, Development & Engineering Center • IWARS/DI – Infantry Warrior Simulation/Dismounted Infantry • S3E – Systems Engineering, Experimentation, and Enterprise BLCSE – Battle Lab Collaborative Simulation Environment • JCAS – Joint Close Air Support • SANDS – Situational Awareness Normalization & Dissemination C3HPM – Command, Control, & Communications Human Service Performance Model • JCIDS – Joint Combat Integrated Defense System • SE – Systems Engineering • JROC – Joint Requirements Oversight Council C3GRID – Command & Control, Computer GRID • Sim Init – Simulation Initialization CES – Communications Effects Server • JSBE – Joint Service Battlespace Environment • SNE – Synthetic Natural Environment CMS – Countermine Server • KPP – Key Performance Parameters • SoS – System of System CMS2 – Comprehensive Munitions & Sensor Server • LSI – Lead Systems Integrator (FCS) • SoSE – System of System Engineering CSAT – C4ISR Static Analysis Tool • SOSCOE – System of Systems Common Operating Environment • LVC – Live Virtual Constructive C4ISR – Command & Control, Communications, • STEM – Science and Technology Enterprise Management • LVCI - Live Virtual Constructive Interoperability Computers, Intelligence, Surveillance and Reconnaissance • S&T – Science and Technology DCARS – Data Collection, Analysis & Reporting System• LVS – Lethality/Vulnerability Service • TENA – Test & Training Enabling Architecture DCA – Data Collection & Analysis • MATREX – Modeling Architecture for Technology, Research, & • TIE – Technical Integration Event DCAT – Data Collection & Analysis Tool EXperimentation • TRADOC – Training & Doctrine Command DES – Damage Effects Server • MC2 – Mobile Command & Control • UAV – Unmanned Aerial Vehicle DOTMLPF – Doctrine, Organization, Training, Materiel,• MDA – Model Driven Architecture • UC – Universal Controller Leadership, Personnel & Facilities • UJTL – Universal Joint Task List • MMIC – MATREX Middleware Independence Capability DOS – Dynamic Organization Service • USAF – United States Air Force • MOE – Measures of Effectiveness DTC – Developmental Test Command • USMC – United States Marine Corps • MOP – Measures of Performance DTE – Distributed Test Event • VDMS – Vehicle Dynamics & Mobility Service DT&E – Developmental Test and Evaluation • M&S – Modeling and Simulation • V&V – Verification and Validation DVL – Distributed Virtual Laboratory • VV&A – Verification, Validation & Accreditation • MSDE – Military Scenario Development Environment • WECM – Warfighter Electronic Collection and Mapping EE – Effects Engine • MSDL – Military Scenario Definition Language • WI – Warfighter Interface FCS – Future Combat Systems • MSLS – Missile Service FOC – Full Operational Capability • MSO – PM FCS (BCT) Modeling & Simulation Office FOM – Federation Object Model
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Array Lesson 2 Outline 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. Array Lesson 2 Outline Reading Array Values Using for Loop 19. #1 20. Reading Array Values Using for Loop 21. #2 22. for Loop: Like Many Statements #1 23. for Loop: Like Many Statements #2 24. for Loop: Like Many Statements #3 25. Reading Array on One Line of Input #1 Reading Array on One Line of Input #2 26. Reading Array on One Line of Input #3 27. Aside: Why Named Constants Are Good 28. Named Constants as Loop Bounds #1 29. Named Constants as Loop Bounds #2 30. Computing with Arrays #1 31. Computing with Arrays #2 32. Computing with Arrays #3 33. Computing with Arrays #4 34. Computing with Arrays #5 35. Static Memory Allocation Static Memory Allocation Example #1 Static Memory Allocation Example #2 Static Sometimes Not Good Enough #1 Static Sometimes Not Good Enough #2 Static Sometimes Not Good Enough #3 Static Sometimes Not Good Enough #4 Static Memory Allocation Can Be Wasteful Dynamic Memory Allocation #1 Dynamic Memory Allocation #2 Dynamic Memory Allocation #3 Dynamic Memory Allocation #4 Dynamic Memory Deallocation Dynamic Memory Allocation Example #1 Dynamic Memory Allocation Example #2 Dynamic Memory Allocation Example #3 Exercise: mean #1 Exercise: mean #2 Array Lesson 2 CS1313 Spring 2019 1
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ARFF Feature List  The datasets contain network transactions captured over a serial line  Network information   Payload information   System control and state information Label   Time stamp, Station address, CRC, etc. Binary / Category / Specific mode identifier Deep packet inspection provides system state information  Pressure measurements, pump state, solenoid state, etc. Feature Type address Network function Command Payload length Network setpoint Command Payload gain Command Payload reset rate Command Payload deadband Command Payload cycle time Command Payload rate Command Payload system mode Command Payload control scheme Command Payload pump Command Payload solenoid Command Payload pressure measurement crc rate Response Payload Network command response Network time Network binary attack Label categorized attack Label specific attack Label 
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CROSS PRODUCT APPLICATION: POLYGON CONVEXITY A POLYGON IS CONVEX THE SEGMENT BETWEEN ANY TWO POINTS ON ITS BOUNDARY IS COMPLETELY CONTAINED WITHIN THE POLYGON. SOME GRAPHICAL ALGORITHMS DEPEND ON POLYGONS BEING CONVEX. TO DETERMINE WHETHER A POLYGON IS CONVEX, TAKE THE CROSS PRODUCT OF EACH PAIR OF VECTORS BETWEEN CONSECUTIVE VERTEX TRIPLES. IF ALL OF THESE CROSS PRODUCTS HAVE THE SAME SIGN, THEN THE POLYGON IS CONVEX. POSITIVE CROSS PRODUCT POSITIVE CROSS PRODUCT POSITIVE CROSS PRODUCT CS 482 – Fall 2017 POSITIVE CROSS PRODUCT POSITIVE CROSS PRODUCT POSITIVE CROSS PRODUCT POSITIVE CROSS PRODUCT NEGATIVE CROSS PRODUCT POSITIVE CROSS PRODUCT CHAPTER 7: VECTORS AND MATRICES POSITIVE CROSS PRODUCT PAGE 7
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//////////////////////////////////////////// // Class implementation file: Matrix.cpp // // The implementation of the copy and // // initializing constructors, the setEle- // // ment, determinant, and minor member // // functions, and the output operator. // //////////////////////////////////////////// #include #include #include #include #include #include "Matrix.h" using namespace std; // Copy constructor: Copies existing mat.// matrix::matrix(const matrix &m) { size = m.size; for (int row = 0; row < m.size; row++) for (int col = 0; col < m.size; col++) table[row][col] = m.table[row][col]; } // Initializing constructor: Sets *this // // up as a sz x sz matrix of zeros. // matrix::matrix(int sz) { size = sz; for (int row = 0; row < sz; row++) for (int col = 0; col < sz; col++) table[row][col] = 0; } CS 240 // SetElement Member Function: Sets the // // (i,j) element of the matrix to item. // void matrix::setElement(int i, int j, elementType e) { assert ((0<=i) && (i
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Probability of Treatment Modality for Orthopedic Specialists Compared to Primary Care Specialists • Orthopedic specialists were -11.6 percentage points less likely to prescribe an opioid than primary care specialists. • Orthopedic specialists were +15.4 percentage points more likely to order physical therapy than primary care specialists. • There was no difference between specialty for the likelihood of prescribing non-opioid analgesics. +15.4 percentage points No difference -11.6 percentage points
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Using the Select Commands Using Pipes – The pipe operator (|) redirects the output of one command to the input of another command. The character used to represent the pipe is the \ immediately above the right key (It looks like a : ). – An example would be to redirect the output of the ls command to the more command • ls | more – The pipe operator can connect several commands on the same command line • First_command | second command | third command • The output of the first command goes into the second command as input, and the output of the second command goes into the third command as input. • For example: cat products | cut –f2 –d: | sort – Will cat the products file, cut out the description field and sort by the desciption field. 7
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