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Alberta Government Services ______Corporate Registry ______
Alberta Government Services ____________________ Corporate Registry ____________________ Registrar’s Periodical REGISTRAR’S PERIODICAL, SEPTEMBER 15, 2006 ALBERTA GOVERNMENT SERVICES Corporate Registrations, Incorporations, and Continuations (Business Corporations Act, Cemetery Companies Act, Companies Act, Cooperatives Act, Credit Union Act, Loan and Trust Corporations Act, Religious Societies’ Land Act, Rural Utilities Act, Societies Act, Partnership Act) 0751152 B.C. LTD. Other Prov/Territory Corps 1256866 ALBERTA LTD. Numbered Alberta Registered 2006 AUG 11 Registered Address: 600, Corporation Incorporated 2006 AUG 14 Registered 12220 STONY PLAIN ROAD, EDMONTON Address: 314 CARMICHAEL WYND, EDMONTON ALBERTA, T5N 3Y4. No: 2112610379. ALBERTA, T6R 2K6. No: 2012568669. 101026957 SASKATCHEWAN LTD. Other 1256869 ALBERTA LTD. Numbered Alberta Prov/Territory Corps Registered 2006 AUG 15 Corporation Incorporated 2006 AUG 03 Registered Registered Address: SUITE 300, 255 - 17 AVE SW, Address: BOX #8, 125 8170 50 ST NW, EDMONTON CALGARY ALBERTA, T2S 2T8. No: 2112616210. ALBERTA, T6B 1E6. No: 2012568693. 101075855 SASKATCHEWAN LTD. Other 1257443 ALBERTA LTD. Numbered Alberta Prov/Territory Corps Registered 2006 AUG 15 Corporation Incorporated 2006 AUG 15 Registered Registered Address: 5105 - 49 STREET, Address: 1314 RIVERDALE AVENUE SW, LLOYDMINSTER ALBERTA, T9V 0K3. No: CALGARY ALBERTA, T2S 0Y8. No: 2012574436. 2112617788. 1258360 ALBERTA LTD. Numbered Alberta 101086914 SASKATCHEWAN LTD. Other Corporation Incorporated 2006 AUG 01 Registered Prov/Territory Corps Registered 2006 AUG 10 Address: 303-9811 34 AVE, EDMONTON ALBERTA, Registered Address: 176 STRATTEN WAY SE, T6E 5X9. No: 2012583601. MEDICINE HAT ALBERTA, T1B 3R3. No: 2112605619. 1258478 ALBERTA LTD. Numbered Alberta Corporation Incorporated 2006 AUG 01 Registered 10K CONSULTING LTD. Named Alberta Corporation Address: 282 TUSCANY VALLEY VIEW NW, Incorporated 2006 AUG 04 Registered Address: 2529-7 CALGARY ALBERTA, T3L 2K8. -
VMD User's Guide
VMD User’s Guide Version 1.9.4a48 October 13, 2020 NIH Biomedical Research Center for Macromolecular Modeling and Bioinformatics Theoretical and Computational Biophysics Group1 Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign 405 N. Mathews Urbana, IL 61801 http://www.ks.uiuc.edu/Research/vmd/ Description The VMD User’s Guide describes how to run and use the molecular visualization and analysis program VMD. This guide documents the user interfaces displaying and grapically manipulating molecules, and describes how to use the scripting interfaces for analysis and to customize the behavior of VMD. VMD development is supported by the National Institutes of Health grant numbers NIH P41- GM104601. 1http://www.ks.uiuc.edu/ Contents 1 Introduction 11 1.1 Contactingtheauthors. ....... 12 1.2 RegisteringVMD.................................. 12 1.3 CitationReference ............................... ...... 12 1.4 Acknowledgments................................. ..... 13 1.5 Copyright and Disclaimer Notices . .......... 13 1.6 For information on our other software . .......... 15 2 Hardware and Software Requirements 17 2.1 Basic Hardware and Software Requirements . ........... 17 2.2 Multi-core CPUs and GPU Acceleration . ......... 17 2.3 Parallel Computing on Clusters and Supercomputers . .............. 18 3 Tutorials 19 3.1 RapidIntroductiontoVMD. ...... 19 3.2 Viewing a molecule: Myoglobin . ........ 19 3.3 RenderinganImage ................................ 21 3.4 AQuickAnimation................................. 21 3.5 An Introduction to Atom Selection . ......... 22 3.6 ComparingTwoStructures . ...... 22 3.7 SomeNiceRepresenations . ....... 23 3.8 Savingyourwork.................................. 24 3.9 Tracking Script Command Versions of the GUI Actions . ............ 24 4 Loading A Molecule 26 4.1 Notes on common molecular file formats . ......... 26 4.2 Whathappenswhenafileisloaded? . ....... 27 4.3 Babelinterface ................................. -
Behavioral Analysis of Embedded Linux Device Drivers on Beaglebone Black
PSYCHOLOGY AND EDUCATION (2021) 58(1): 5917-5921 ISSN: 00333077 Behavioral Analysis of Embedded Linux Device Drivers on BeagleBone Black Jignesh J. Patoliya1, Sagar B. Patel 2 , Miral M. Desai 3, Ninad Desai4 1,3 Assistant Professor, 2,4 Student 1,2,3,4 Electronics and Communication Department, C. S. Patel Institute of Technology, Charotar University of Science and Technology, Anand, Gujarat, India [email protected] ABSTRACT In the contemporary era, the Embedded Linux technology is in tremendous demand for various high-end applications like Internet of Things, Industrial Robotics, Smart Devices, Supercomputers. There is use of kernel device drivers in lowest level of Android and iOS which is emerging for more development in terms of the efficiency and robustness. The speed for communicating between the devices in all the technologies is the vital part, hence, the use of appropriate Embedded Linux Device Driver is needed out of IOCTL (Input Output Control), Procfs, Sysfs. The proposed paper relates to the behavioral analysis of the different types of device drivers on the ARM (Advanced RISC Machine) based platform BeagleBone Black Board. The implementation of these drivers is depicted in the proposed paper by cross-compiling the device driver from x86 platform to BeagleBone Black platform. The OS running on the BeagleBone Black is Linux kernel based Debian. The device driver is basic interface between the software and hardware for specific functionality. Keywords Embedded Linux, Device Driver, BeagleBone Black Board, Cross-Compilation, Input Output Control (IOCTL) Article Received: 10 August 2020, Revised: 25 October 2020, Accepted: 18 November 2020 Introduction routing, session management, packet handling for Wi-Fi and Ethernet [13]. -
Getting Started Guide
GETTING STARTED Onion Omega2S Development Kit Getting Started Guide Version 1.0 Omega2 IoT Computer Onion Omega2S Development Kit 1 Revision History Revision Date Description 1.0 March 17, 2018 Initial release Onion Omega2S Development Kit 2 Table of Contents 1. Introduction 4 2. Hardware Overview 5 2.1 Omega2S Hardware Overview 5 2.1.1 Differences from the Omega2 6 2.2 SD Card Development Board Overview 7 2.3 eMMC Development Board Overview 8 3. Hardware Setup 9 4. First Time Setup 13 5. Using the Development Kit 13 5.1 Common Usage 13 5.1.1 Using GPIOs 13 5.1.2 Using USB Storage 13 5.1.3 Using an SD card 14 5.1.4 Rebooting the Omega2S 15 5.1.5 Factory Reset 15 5.2 Removing Omega2S from the Dev Board 16 6. Additional Resources 17 6.1 Hardware Setup Video 17 6.2 Omega2S Datasheet 17 6.3 Schematics 17 6.3.1 Development Board Schematics 17 6.3.2 Omega2S Reference Design Schematics 17 Onion Omega2S Development Kit 3 1. Introduction The Omega2S Development Kit consists of the Omega2S, Onion’s surface-mount Linux WiFi module, and the Development Board, meant to showcase the functionality of the Omega2S module and serve as a test-bed for initial product development. The Omega2S is a highly integrated WiFi enabled, Linux module designed by Onion Corporation. It utilizes the Mediatek MT7688AN System on a Chip (SoC) which is based on the MIPs 24K CPU processor core. The SoC includes 802.11b/g/n Wi-Fi, making the Omega2S ideal for Internet of Things (IoT) applications and projects. -
Using Pareto Optimum to Choose Module's Computing
29TH DAAAM INTERNATIONAL SYMPOSIUM ON INTELLIGENT MANUFACTURING AND AUTOMATION DOI: 10.2507/29th.daaam.proceedings.081 USING PARETO OPTIMUM TO CHOOSE MODULE’S COMPUTING PLATFORMS OF MOBILE ROBOT WITH MODULAR ARCHITECTURE Victor Andreev, Valerii Kim & Pavel Pletenev This Publication has to be referred as: Andreev, V[iktor]; Kim, V[alerii] & Pletenev, P[avel] (2018). Using Pareto Optimum to Choose Module’s Computing Platforms of Mobile Robot with Modular Architecture, Proceedings of the 29th DAAAM International Symposium, pp.0559-0565, B. Katalinic (Ed.), Published by DAAAM International, ISBN 978-3-902734-20-4, ISSN 1726-9679, Vienna, Austria DOI: 10.2507/29th.daaam.proceedings.081 Abstract This paper tries to address a sufficiently complex task – choice of module’s computing platform for implementation of information-measuring and control system (IMCS) of full-functional modules of mobile robot with modular architecture. The full functionality of a mechatronic device is the ability to perform its goal function using only its own facilities for executing instructions from an external control system. This condition sets for robot’s IMCS some specific requirements on selection of corresponding computational platform, which one could separate into objective, subjective and computative-objective criteria. This paper proposes use of discrete optimization with Pareto-optimum to select viable alternatives from computing platforms which can be both off-the-shelf and perspective products. One of the main criteria – such embedded computing platforms must have suitable computational power, low weight and sizes. The paper provides descriptions of different computing platforms, as well as the rationale for main quality criteria of them. An example of Pareto optimization for a specific IMCS solution for some types of mobile robot modules with modular architecture is provided. -
Jan 2021 LG SBC Catalog
Comparison of 150 Open Spec, Hacker Friendly Single Board Computers -- Jan. 2021 Click on the product names to get more product information. In most cases these links go to LinuxGizmos.com articles with detailed product descriptions plus market analysis. MCU or AI Camera USB Price ($) Vendor Processor Cores 3D GPU chip RAM eMMC/flash Other storage LAN Wireless HDMI or DP output ports Expansion OSes opt. 8GB or A20-OLinuXino-Lime2 49 to 73 Olimex Allwinner A20 2x A7 @ 1GHz Mali-400 no 1GB 16GB eMMC SATA GbE no yes no 3 other Linux, Android opt. 8GB or A20-OLinuXino-Micro 50 to 76 Olimex Allwinner A20 2x A7 @ 1GHz Mali-400 no 1GB 16GB eMMC SATA Fast no yes no 3 other Linux, Android A33-OLinuXino 37 or 49 Olimex Allwinner A33 4x A7 @ 1.2GHz Mali-400 no 1GB opt. 8GB NAND no no no no yes 1 dual 40-pin Linux, Android 1GB or opt. opt. 4GB or A64-OLinuXino 44 to 86 Olimex Allwinner A64 4x A53 @ 1.2GHz Mali-400 MP2 no 2GB 16GB eMMC no GbE WiFi, BT yes via GPIO 1 40-pin custom Linux Qualcomm Atheros Atmega32 Arduino Yun Rev 2 56 Arduino AR9331 1x MIPS @ 400MHz no U4 64MB 16MB no Fast WiFi no no 2 Arduino Linux SAM9X60 128MB or Banana Pi BPI-F2P NEW 63 SinoVoip SunPlus SP7021 4x A7 @ 1GHz no and 8051 512MB 8GB eMMC no 2x Fast no yes yes 3 40-pin Linux SAM9X60 128MB or 40-pin and FPGA Banana Pi BPI-F2S 58 SinoVoip SunPlus SP7021 4x A7 @ 1GHz no and 8051 512MB 8GB eMMC no 2x Fast no yes yes 3 I/O Linux Banana Pi BPI-M2 Berry 36 SinoVoip Allwinner V40 4x A7 Mali-400 MP2 no 1GB no SATA GbE WiFi, BT yes yes 4 Pi 40 Linux, Android 8GB to 64GB Banana Pi -
Gpu-Accelerated Applications Gpu‑Accelerated Applications
GPU-ACCELERATED APPLICATIONS GPU-ACCELERATED APPLICATIONS Accelerated computing has revolutionized a broad range of industries with over five hundred applications optimized for GPUs to help you accelerate your work. CONTENTS 1 Computational Finance 2 Climate, Weather and Ocean Modeling 2 Data Science & Analytics 4 Deep Learning and Machine Learning 8 Defense and Intelligence 9 Manufacturing/AEC: CAD and CAE COMPUTATIONAL FLUID DYNAMICS COMPUTATIONAL STRUCTURAL MECHANICS DESIGN AND VISUALIZATION ELECTRONIC DESIGN AUTOMATION 17 Media & Entertainment ANIMATION, MODELING AND RENDERING COLOR CORRECTION AND GRAIN MANAGEMENT COMPOSITING, FINISHING AND EFFECTS EDITING ENCODING AND DIGITAL DISTRIBUTION ON-AIR GRAPHICS ON-SET, REVIEW AND STEREO TOOLS WEATHER GRAPHICS 24 Medical Imaging 27 Oil and Gas 28 Research: Higher Education and Supercomputing COMPUTATIONAL CHEMISTRY AND BIOLOGY NUMERICAL ANALYTICS PHYSICS SCIENTIFIC VISUALIZATION 39 Safety and Security 42 Tools and Management Computational Finance APPLICATION NAME COMPANY/DEVELOPER PRODUCT DESCRIPTION SUPPORTED FEATURES GPU SCALING Accelerated Elsen Secure, accessible, and accelerated back- • Web-like API with Native bindings for Multi-GPU Computing Engine testing, scenario analysis, risk analytics Python, R, Scala, C Single Node and real-time trading designed for easy • Custom models and data streams are integration and rapid development. easy to add Adaptiv Analytics SunGard A flexible and extensible engine for fast • Existing models code in C# supported Multi-GPU calculations of a wide variety of pricing transparently, with minimal code Single Node and risk measures on a broad range of changes asset classes and derivatives. • Supports multiple backends including CUDA and OpenCL • Switches transparently between multiple GPUs and CPUS depending on the deal support and load factors. -
Gpu-Accelerated Applications Gpu‑Accelerated Applications
GPU-ACCELERATED APPLICATIONS GPU-ACCELERATED APPLICATIONS Accelerated computing has revolutionized a broad range of industries with over five hundred applications optimized for GPUs to help you accelerate your work. CONTENTS 1 Computational Finance 2 Climate, Weather and Ocean Modeling 2 Data Science and Analytics 4 Artificial Intelligence DEEP LEARNING AND MACHINE LEARNING 8 Federal, Defense and Intelligence 10 Design for Manufacturing/Construction: CAD/CAE/CAM COMPUTATIONAL FLUID DYNAMICS COMPUTATIONAL STRUCTURAL MECHANICS DESIGN AND VISUALIZATION ELECTRONIC DESIGN AUTOMATION INDUSTRIAL INSPECTION 19 Media & Entertainment ANIMATION, MODELING AND RENDERING COLOR CORRECTION AND GRAIN MANAGEMENT Test Drive the COMPOSITING, FINISHING AND EFFECTS World’s Fastest EDITING ENCODING AND DIGITAL DISTRIBUTION Accelerator – Free! ON-AIR GRAPHICS ON-SET, REVIEW AND STEREO TOOLS Take the GPU Test Drive, a free and WEATHER GRAPHICS easy way to experience accelerated computing on GPUs. You can run 29 Medical Imaging your own application or try one of the preloaded ones, all running on a 30 Oil and Gas remote cluster. Try it today. 31 Research: Higher Education and Supercomputing www.nvidia.com/gputestdrive COMPUTATIONAL CHEMISTRY AND BIOLOGY NUMERICAL ANALYTICS PHYSICS SCIENTIFIC VISUALIZATION 47 Safety and Security 49 Tools and Management Computational Finance APPLICATION NAME COMPANY/DEVELOPER PRODUCT DESCRIPTION SUPPORTED FEATURES GPU SCALING Accelerated Elsen Secure, accessible, and accelerated back- • Web-like API with Native bindings for Multi-GPU Computing Engine testing, scenario analysis, risk analytics Python, R, Scala, C Single Node and real-time trading designed for easy • Custom models and data streams are integration and rapid development. easy to add Adaptiv Analytics SunGard A flexible and extensible engine for fast • Existing models code in C# supported Multi-GPU calculations of a wide variety of pricing transparently, with minimal code Single Node and risk measures on a broad range of changes asset classes and derivatives. -
Image Fx 1.5 Plus!
IMAGE FX We show you how to manipulate scan s and Hi Quality Version Available on AMIGALAND.COMclip art like this! All the software you need on this months coverdisksl UTILITY DISK AH Araigas with 2Mb IMAGE FX 1.5 PLUS! The best image processing program lor the Amiga! RAM speed test: AMIGA S S S L , 110 Blinara 1230 III Siren Apollo - 4 * BOctaM I E 0 6 I L; ' / P Test your skills \ \ , / < with this superb renewed > > * ■ d cup challenge ^ ‘*en10 *,om x J Impressions f i' I e long wait is over - see page 20 antes: 977096300903706 I Primal Rage i Sensible Golf » High Seas Trader i Pizza Tycoon 9 ( fU V O D UUYUJI I Ultimate Soccer June 1995 f 3 99 USSJ.95 ■ CAS9 95 ■ 0M2D ■ PIA1.150 ■ II 3.600 Manager ■ ASCHWO An (nap Piblitdtan LEISURE SUIT LARRY 1 ................. LEMMINGS 2 .................................... HOP * w ill not work on 4500 Phn, LOROS OF THE REALM 2149 4600 or 41200 A-TRAIN - CONSTRUCTION SET .......... 1049 MICRO MACHINES (512K) ................. 12 99 ACID BLITZ COMPILER VERSION 2. 17 BIT COLLECTION 2 CD S. MASSIVE 2 CO I MONOPOLY (5I2K) ......................... 13 99 THE LATEST UPOATE TO THE POPULAR SET OF GAMES. DEMOS. EDUCATION. MUSIC HOI2; w ill not work on 41200 A.T.R ITEAM 17) ..................................1649 A10 TANK KILLER............................... 1299 MORTAL KOMBAT ........................ 11 99 BLITZ BASIC IWHICH WAS USED TO MAKE ANO GRAPHICS 31JB j 5124 = will work onSOkn ALIEN BREED • TOWER ASSAUIJ (512K) 1349 MORTAL KOMBAT 2 19 49 SKIDMARKS AND GUARDIAN) WITH 1 CO S OF 17 Bn CONTINUATION. -
Rhorix: an Interface Between Quantum Chemical Topology and the 3D Graphics Program Blender
Lawrence Berkeley National Laboratory Recent Work Title Rhorix: An interface between quantum chemical topology and the 3D graphics program blender. Permalink https://escholarship.org/uc/item/18n454gq Journal Journal of computational chemistry, 38(29) ISSN 0192-8651 Authors Mills, Matthew JL Sale, Kenneth L Simmons, Blake A et al. Publication Date 2017-11-01 DOI 10.1002/jcc.25054 Peer reviewed eScholarship.org Powered by the California Digital Library University of California SOFTWARE NEWS AND UPDATES WWW.C-CHEM.ORG Rhorix: An Interface between Quantum Chemical Topology and the 3D Graphics Program Blender Matthew J. L. Mills ,[a,b] Kenneth L. Sale,[a,b] Blake A. Simmons,[a,c] and Paul L. A. Popelier [d] Chemical research is assisted by the creation of visual repre- topological objects and their 3D representations. Possible sentations that map concepts (such as atoms and bonds) to mappings are discussed and a canonical example is suggested, 3D objects. These concepts are rooted in chemical theory that which has been implemented as a Python “Add-On” named predates routine solution of the Schrodinger€ equation for sys- Rhorix for the state-of-the-art 3D modeling program Blender. tems of interesting size. The method of Quantum Chemical This allows chemists to use modern drawing tools and artists Topology (QCT) provides an alternative, parameter-free means to access QCT data in a familiar context. A number of exam- to understand chemical phenomena directly from quantum ples are discussed. VC 2017 The Authors. Journal of Computa- mechanical principles. Representation of the topological ele- tional Chemistry Published by Wiley Periodicals, Inc. -
Load Monitor 2
LOAD MONITOR 2 REPORT 2018:483 Load Monitor 2 Measuring and modeling vibrations and loads on wind turbines Part 2: Concepts for monitoring loads on towers and foundations INGEMAR CARLÉN ISBN 978-91-7673-483-4 | © Energiforsk June 2018 Energiforsk AB | Phone: 08-677 25 30 | E-mail: [email protected] | www.energiforsk.se LOAD MONITOR 2 Förord LoadMonitor – Mätning och modellering av vibrationer och laster på vindkraftverk" är ett projekt finansierat av Energiforsk och Energimyndigheten genom programmet Vindforsk IV. Projektets övergripande mål är att öka kunskapen om hur turbinlaster och turbinprestanda påverkas av svenska klimat-, skogs och terrängförhållanden. Med hjälp av nacellemonterad lidar, SCADA systemet och ett egenutvecklat vibrationsmätningssystem har man dels undersökt kopplingen mellan den ostörda vinden och vibrationer i nacellen (del 1) och dels hur man på ett kostnadseffektivt sätt kan mäta laster i strukturen (del 2). Sist men inte minst har man genom projektet fått möjlighet att validera en strömningsmodell över skog som är av stort värde då en stor del av den svenska vindkraften är placerad i skog. Projektet har utförts av Kjeller Vindteknikk, Uppsala Universitet campus Gotland och Teknikgruppen med stöd av Stena Renewable. Göran Dalén Ordförande, Vindforsk IV 3 LOAD MONITOR 2 Sammanfattning Merparten av alla vindkraftverk som installeras idag är utrustade med olika typer av övervakningssystem vars syfte är att tidigt upptäcka om en del eller en komponent är i behov av service eller måste bytas ut. Om dessa behov identifieras i god tid så kan man effektivare planera underhåll och undvika kostsamma skador. Dessa system är i allmänhet inte fullt utvecklade när det gäller att bedöma risken för framtida skador beroende på särskilda vind- förhållanden på platsen, eller på att vindkraftverkets styrsystem inte är optimalt inställda. -
Vulnerabilities' Assessment and Mitigation Strategies for the Small Linux Server, Onion Omega2
electronics Article Vulnerabilities’ Assessment and Mitigation Strategies for the Small Linux Server, Onion Omega2 Darshana Upadhyay 1 , Srinivas Sampalli 1,* and Bernard Plourde 2 1 Faculty of Computer Science, Dalhousie University, Halifax, NS B3H 4R2, Canada; [email protected] 2 Research & Development Department, Technology Sanstream, Ottawa, ON K2R 1C1, Canada; [email protected] * Correspondence: [email protected] Received: 8 May 2020; Accepted: 5 June 2020; Published: 10 June 2020 Abstract: The merger of SCADA (supervisory control and data acquisition) and IoTs (internet of things) technologies allows end-users to monitor and control industrial components remotely. However, this transformation opens up a new set of attack vectors and unpredicted vulnerabilities in SCADA/IoT field devices. Proper identification, assessment, and verification of each SCADA/IoT component through advanced scanning and penetration testing tools in the early stage is a crucial step in risk assessment. The Omega2, a small Linux server from Onion™, is used to develop various SCADA/IoT systems and is a key component of nano power grid systems. In this paper, we report product level vulnerabilities of Onion Omega2 that we have uncovered using advanced vulnerability scanning tools. Through this research, we would like to assist vendors, asset owners, network administrators, and security professionals by creating an awareness of the vulnerabilities of Onion Omega2 and by suggesting effective mitigations and security best practices. Keywords: SCADA; IoT; embedded devices; vulnerability assessment; webserver; Onion Omega2 1. Introduction There has been a surge in the deployment of internet of things (IoT) with supervisory control and data acquisition (SCADA) systems to control industrial infrastructures across open access networks.