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Detective 11.0 October 2018
OXYGEN FORENSIC® DETECTIVE 11.0 OCTOBER 2018 USE NEW WHATSAPP EXTRACTION METHOD AQCUIRE IOT DEVICES WhatsApp is without doubt the most popular messenger Digital assistants are already a part of everyday life and in the world with over 1.5 billion users globally. Thus, have been successfully used to solve several crimes. extracting complete WhatsApp content from all possible Oxygen Forensic® Detective v.11 brings support for the sources is essential for any investigation. two most popular digital assistants – Amazon Alexa and Google Home. Commonly used methods of WhatsApp data acquisition involve extracting data from mobile devices and their You can access Amazon Alexa cloud using a username cloud backups. Oxygen Forensic® Detective v.11 and password or token. A token can be found on the introduces an industry-first alternative method of device’s associated computer with Oxygen Forensic® WhatsApp data extraction. KeyScout and used in Cloud Extractor. The software acquires a complete evidence set from Amazon Alexa, In the new software version, you can access complete including account and device details, contacts, messages, WhatsApp data by scanning a QR code from a mobile calendars, notifications, lists, activities, skills, etc. app or using the WhatsApp token from a PC. This token can be extracted by our KeyScout utility from the Google Home data can be extracted via Google WhatsApp desktop app or from desktop Web browsers. username/password or a master token found in mobile devices. Extracted Google Home data includes account Once data is extracted, you will be able to download and device details, voice commands, and information WhatsApp communications from the subject’s account about users.Google Home data can also be acquired from any time later when an investigation requires by using a the Google Home mobile app on Apple iOS and Android specially generated WhatsApp QR token available in the devices. -
URBAN MOBILITY - WALLY CLICK ICON for Size: 106 X 62 X 8 Mm Logo Size: 90 X 45 Mm PRODUCT VIDEO
URBAN MOBILITY - WALLY CLICK ICON FOR Size: 106 x 62 x 8 mm Logo Size: 90 X 45 mm PRODUCT VIDEO Up to 6 cards RFID Blocking Hold cards sized 85 x 55 mm: Keeps your cards protected from smart entry cards, public transport RF readers or mobile apps capable How to brand? cards, bank card, ID cards etc. of electronic theft Your logo engraved on aluminum surface with high precision laser. Card slider trigger Simply pull the trigger and your cards will eject for an easy acces. Craft paper packaging Wally Carta is a secured (credit) card holder for the minimalists. It offers room for up to 6 cards and has integrated RFID protection technology to keep your cards and personal information safe. No more bending and breaking. Wally Carta’s aluminium foundation protects your cards while remaining small enough to fit in any pocket. ue8premium DESIGNED FOR BRAND ADDITION URBAN MOBILITY - WALLY CARTA CLICK ICON FOR Size: 106 x 62 x 15 mm Logo Size: 90 X 45 mm PRODUCT VIDEO RFID Blocking Keeps your cards protected from RF readers or mobile apps capable of electronic theft Genuine leather How to brand? Your logo embossed on leather. Craft paper packaging Wally Carta is a card and cash carrier for the minimalists. It is modern in its styling and combining natural materials as leather and aluminium it offers something that not many others on the market Card slider trigger Up to 7 cards Cash strap offer: RFID blocking and a luxurious feel at the same time. Simply pull the trigger and Hold cards sized Cash Strap is the slimmest This sleek wallet can hold up to 7 cards without stretching out and your cards will eject for an 85 x 55 mm: smart entry solution to secure easy acces. -
Motorola One Zoom Iii
Benutzerhandbuch © 2019 Motorola Mobility LLC. Alle Rechte vorbehalten. MOTOROLA, das Logo mit dem stilisierten M, MOTO und die MOTO-Markenfamilie sind Marken oder eingetragene Marken von Motorola Trademark Holdings, LLC. LENOVO ist eine Marke von Lenovo. Google, Android, Google Play und andere Marken sind Marken von Google LLC. Das microSD-Logo ist eine Marke von SD-3C, LLC. Alle anderen Produkt- und Dienstleistungsnamen sind Eigentum ihrer jeweiligen Inhaber. Bestimmte Funktionen, Dienste und Anwendungen sind netzwerkabhängig und u. U. nicht in allen Regionen verfügbar. Es können zusätzliche Bedingungen, Bestimmungen und/oder Änderungen gelten. Weitere Informationen erhalten Sie von Ihrem Dienstanbieter. Alle Funktionen, Funktionalitäten und andere Produktspezifikationen sowie die in dieser Hilfe enthaltenen Informationen basieren auf den neuesten verfügbaren Informationen, die zum Zeitpunkt der Veröffentlichung für korrekt befunden wurden. Motorola behält sich das Recht vor, Informationen oder Spezifikationen ohne Ankündigung oder Verpflichtungen zu ändern. Die Bilder in dieser Hilfe sind lediglich Beispiele. Sie können die Hilfe auch unter Einstellungen > Hilfe auf Ihrem Telefon anzeigen. motorola one zoom iii Inhalt Telefon einrichten 1 Hardwarediagramm 1 SIM-und SD-Karten einfügen und entfernen 2 Dual-SIMs verwalten 4 Konten hinzufügen oder entfernen 5 Mailbox einrichten 6 E-Mail einrichten 7 Passen Sie Ihr Telefon nach Ihren Vorlieben an 8 Einstellungen für Bedienungshilfen 10 Visuelle Unterstützung 10 Hörhilfen 12 Fingerfertigkeitshilfe -
(Step) Green Paper
10 April 2013 Solving the E-Waste Problem (StEP) Green Paper E-waste Country Study Ethiopia Andreas Manhart, Öko-Institut e.V. Tadesse Amera, PAN Ethiopia Mehari Belay, PAN Ethiopia ISSN: 2219-6579 (Online) ISSN: 2219-6560 (In-Print) Solving the E-Waste Problem (StEP) Initiative Green Paper 0 E-waste Country Study Ethiopia United Nations University/StEP Initiative 2013 This work is licensed under the Creative Commons by-nc-nd License. To view a copy of this license, please visit http://creativecommons.org/licenses/by-nc-nd/3.0/ This publication may thus be reproduced in whole or in part and in any form for educational or non-profit purposes without special permission from the copyright holder, provided acknowledgement of the source is made. No use of this publication may be made for resale or for any other commercial purpose whatsoever without prior permission in writing from the StEP Initiative/United Nations University. The StEP Initiative/United Nations University would appreciate receiving a copy of any pub- lication that uses this publication as a source. Disclaimer StEP Green Paper Series The StEP Green Paper Series is a publication tool for research findings which meet the core principles of StEP and contribute to its objectives towards solving the e-waste prob- lem. StEP members agreed on this support of the author(s) work, but do not necessarily endorse the conclusions made. Hence, StEP Green Papers are not necessarily reflecting a common StEP standpoint. The StEP Green Paper series is published complimentary to the StEP White Paper Series for publication of findings generated within StEP which have been endorsed by its mem- bers. -
Qikink Product & Price List
PHONE CASE LIST - SUBLIMATION ONEPLUS APPLE OPPO REALME NOKIA HUAWEI ONEPLUS 3 IPHONE SE OPPO F3 REALME C1 NOKIA 730 HONOR 6X ONEPLUS 3T IPHONE 6 OPPO F5 REALME C2 NOKIA 640 HONOR 9 LITE ONEPLUS 5 IPHONE 6 PLUS OPPO FIND X REALME 3 NOKIA 540 HONOR Y9 ONEPLUS 5T IPHONE 6S OPPO REALME X REALME 3i NOKIA 7 PLUS HONOR 10 LITE ONEPLUS 6 IPHONE 7 OPPO F11 PRO REALME 5i NOKIA 8 HONOR 8C ONEPLUS 6T IPHONE 7 PLUS OPPO F15 REALME 5S NOKIA 6 HONOR 8X ONEPLUS 7 IPHONE 8 PLUS OPPO RENO 2F REALME 2 PRO NOKIA 3.1 HONOR 10 ONEPLUS 7T IPHONE X OPPO F11 REALME 3 NOKIA 2.1 HONOR 7C ONEPLUS 7PRO IPHONE XR OPPOF13 REALME 3 PRO NOKIA 7.1 HONOR 5C ONEPLUS 7T PRO IPHONE XS OPPO F1 REALME C3 NOKIA 3.1 PLUS HONOR P20 ONEPLUS NORD IPHONE XS MAX OPPO F7 REALME 6 NOKIA 5.1 HONOR 6PLUS ONEPLUS X IPHONE 11 OPPO A57 REALME 6 PRO NOKIA 7.2 HONOR PLAY 8A ONEPLUS 2 IPHONE 11 PRO OPPO F1 PLUS REALME X2 NOKIA 7.1 PLUS HONOR NOVA 3i ONEPLUS 1 IPHONE 11 PRO MAX OPPO F9 REALME X2 PRO NOKIA 6.1 PLUS HONOR PLAY IPHONE 12 OPPO A7 REALME 5 NOKIA 6.1 HONOR 8X IPHONE 12 MINI OPPO R17 PRO REALME 5 PRO NOKIA 8.1 HONOR 8X MAX IPHONE 12 PRO OPPO K1 REALME XT NOKIA 2 HONOR 20i IPHONE 12 PRO MAX OPPO F9 REALME 1 NOKIA 3 HONOR V20 IPHONE X LOGO OPPO F3 REALME X NOKIA 5 HONOR 6 PLAY IPHONE 7 LOGO OPPO A3 REALME 7 PRO NOKIA 6 (2018) HONOR 7X IPHONE 6 LOGO OPPO A5 REALME 5S NOKIA 8 HONOR 5X IPHONE XS MAX LOGO OPPO A9 REALME 5i NOKIA 2.1 PLUS HONOR 8 LITE IPHONE 8 LOGO OPPO R98 HONOR 8 IPHONE 5S OPPO F1 S HONOR 9N IPHONE 4 OPPO F3 PLUS HONOR 10 LITE IPHONE 5 OPPO A83 (2018) HONOR 7S IPHONE 8 -
NASA Process for Limiting Orbital Debris
NASA-HANDBOOK NASA HANDBOOK 8719.14 National Aeronautics and Space Administration Approved: 2008-07-30 Washington, DC 20546 Expiration Date: 2013-07-30 HANDBOOK FOR LIMITING ORBITAL DEBRIS Measurement System Identification: Metric APPROVED FOR PUBLIC RELEASE – DISTRIBUTION IS UNLIMITED NASA-Handbook 8719.14 This page intentionally left blank. Page 2 of 174 NASA-Handbook 8719.14 DOCUMENT HISTORY LOG Status Document Approval Date Description Revision Baseline 2008-07-30 Initial Release Page 3 of 174 NASA-Handbook 8719.14 This page intentionally left blank. Page 4 of 174 NASA-Handbook 8719.14 This page intentionally left blank. Page 6 of 174 NASA-Handbook 8719.14 TABLE OF CONTENTS 1 SCOPE...........................................................................................................................13 1.1 Purpose................................................................................................................................ 13 1.2 Applicability ....................................................................................................................... 13 2 APPLICABLE AND REFERENCE DOCUMENTS................................................14 3 ACRONYMS AND DEFINITIONS ...........................................................................15 3.1 Acronyms............................................................................................................................ 15 3.2 Definitions ......................................................................................................................... -
Lecture 26: Domain Specific Architectures Chapter 07, CAQA 6Th Edition
Lecture 26: Domain Specific Architectures Chapter 07, CAQA 6th Edition CSCE 513 Computer Architecture Department of Computer Science and Engineering Yonghong Yan [email protected] https://passlab.github.io/CSCE513 Copyright and Acknowledgements § Copyright © 2019, Elsevier Inc. All rights Reserved – Textbook slides § Machine Learning for Science” in 2018 and A Superfacility Model for Science” in 2017 By Kathy Yelic – https://people.eecs.berkeley.edu/~yelick/talks.html 2 CSE 564 Class Contents § Introduction to Computer Architecture (CA) § Quantitative Analysis, Trend and Performance of CA – Chapter 1 § Instruction Set Principles and Examples – Appendix A § Pipelining and Implementation, RISC-V ISA and Implementation – Appendix C, RISC-V (riscv.org) and UCB RISC-V impl § Memory System (Technology, Cache Organization and Optimization, Virtual Memory) – Appendix B and Chapter 2 – Midterm covered till Memory Tech and Cache Organization § Instruction Level Parallelism (Dynamic Scheduling, Branch Prediction, Hardware Speculation, Superscalar, VLIW and SMT) – Chapter 3 § Data Level Parallelism (Vector, SIMD, and GPU) – Chapter 4 § Thread Level Parallelism – Chapter 5 § Domain-Specific Architecture – Chapter 7 3 The Moore’s Law TrendSuperscalar/Vector/Parallel GPUs 1 PFlop/s (1015) IBM Parallel BG/L ASCI White ASCI Red 1 TFlop/s Pacific 12 (10 ) 2X Transistors/Chip TMC CM-5 Cray T3D Every 1.5 Years Vector TMC CM-2 1 GFlop/s Cray 2 Cray X-MP (109) Super Scalar Cray 1 1941 1 (Floating Point operations / second, Flop/s) 1945 100 CDC 7600 IBM 360/195 -
Comparative Visualization of Protein Sequences
Masaryk University Faculty of Informatics Comparative Visualization of Protein Sequences Master’s Thesis Pavol Ulbrich Brno, Spring 2018 Masaryk University Faculty of Informatics Comparative Visualization of Protein Sequences Master’s Thesis Pavol Ulbrich Brno, Spring 2018 This is where a copy of the official signed thesis assignment and a copy ofthe Statement of an Author is located in the printed version of the document. Declaration Hereby I declare that this paper is my original authorial work, which I have worked out on my own. All sources, references, and literature used or excerpted during elaboration of this work are properly cited and listed in complete reference to the due source. Pavol Ulbrich Advisor: doc. RNDr. Barbora Kozlíková, Ph.D. i Acknowledgements I would like to thank my supervisor, Bára Kozlíková, for an excellent mentoring and guidance through the last stages of my master studies. Then my thanks go to two of my colleagues, Víťa Matela and Vojta Frodl, for countless nights in sixth floor of the faculty building. Writing our theses. iii Abstract To better understand the constitution and spatial arrangement of protein sequences, L. Kocincová et al. [1] proposed a novel method of comparative visualization, which combines traditionally used 1D and 3D representations. Its main contribution is the ability to observe the spatial differences between the proteins without any occlusion problems, commonly present in 3D view. However, the practical im- plementation of the innovative method has remained unfinished. This thesis aims to create a web application for comparative visualization of protein secondary structures, which will benefit from the qualities of the method proposed by Kocincová et al. -
Lexical Innovation on the Internet - Neologisms in Blogs
Zurich Open Repository and Archive University of Zurich Main Library Strickhofstrasse 39 CH-8057 Zurich www.zora.uzh.ch Year: 2009 Lexical innovation on the internet - neologisms in blogs Smyk-Bhattacharjee, Dorota Abstract: Studien im Bereich des Sprachwandels beschreiben traditionellerweise diachronische Verän- derungen in den Kernsubsystemen der Sprache und versuchen, diese zu erklären. Obwohl ein Grossteil der Sprachwissenschaftler sich darüber einig ist, dass die aktuellen Entwicklungen in einer Sprache am klarsten im Wortschatz reflektiert werden, lassen die lexikographischen und morphologischen Zugänge zur Beobachtung des lexikalischen Wandels wichtige Fragen offen. So beschäftigen sich letztere typischer- weise mit Veränderungen, die schon stattgefunden haben, statt sich dem sich zum aktuellen Zeitpunkt vollziehenden Wandel zu widmen. Die vorliegende Dissertation bietet eine innovative Lösung zur Un- tersuchung des sich vollziehenden lexikalischen Wandels sowohl in Bezug auf die Datenquelle als auch bzgl. der verwendeten Methodologie. In den vergangenen 20 Jahren hat das Internet unsere Art zu leben, zu arbeiten und zu kommunizieren drastisch beeinflusst. Das Internet bietet aber auch eine Masse an frei zugänglichen Sprachdaten und damit neue Möglichkeiten für die Sprachforschung. Die in dieser Arbeit verwendeten Daten stammen aus einem Korpus englischsprachiger Blogs, eine Art Computer gestützte Kommunikation (computer-mediated communication, CMC). Blogs bieten eine neue, beispiel- lose Möglichkeit, Wörtern nachzuspüren zum Zeitpunkt, in der sie Eingang in die Sprache finden. Um die Untersuchung des Korpus zu vereinfachen, wurde eine Software mit dem Namen Indiana entwickelt. Dieses Instrument verbindet den Korpus basierten Zugang mit einer lexikographischen Analyse. Indiana verwendet eine Kombination von HTML-to-text converter, eine kumulative Datenbank und verschiede Filter, um potentielle Neologismen im Korpus identifizieren zu können. -
P1360R0: Towards Machine Learning for C++: Study Group 19
P1360R0: Towards Machine Learning for C++: Study Group 19 Date: 2018-11-26(Post-SAN mailing): 10 AM ET Project: ISO JTC1/SC22/WG21: Programming Language C++ Audience SG19, WG21 Authors : Michael Wong (Codeplay), Vincent Reverdy (University of Illinois at Urbana-Champaign, Paris Observatory), Robert Douglas (Epsilon), Emad Barsoum (Microsoft), Sarthak Pati (University of Pennsylvania) Peter Goldsborough (Facebook) Franke Seide (MS) Contributors Emails: [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] Reply to: [email protected] Introduction 2 Motivation 2 Scope 5 Meeting frequency and means 6 Outreach to ML/AI/Data Science community 7 Liaison with other groups 7 Future meetings 7 Conclusion 8 Acknowledgements 8 References 8 Introduction This paper proposes a WG21 SG for Machine Learning with the goal of: ● Making Machine Learning a first-class citizen in ISO C++ It is the collaboration of a number of key industry, academic, and research groups, through several connections in CPPCON BoF[reference], LLVM 2018 discussions, and C++ San Diego meeting. The intention is to support such an SG, and describe the scope of such an SG. This is in terms of potential work resulting in papers submitted for future C++ Standards, or collaboration with other SGs. We will also propose ongoing teleconferences, meeting frequency and locations, as well as outreach to ML data scientists, conferences, and liaison with other Machine Learning groups such as at Khronos, and ISO. As of the SAN meeting, this group has been officially created as SG19, and we will begin teleconferences immediately, after the US thanksgiving, and after NIPS. -
ASUS A002 2 Asus Zenfone AR ASUS A002 1 Asus Zenfone AR (ZS571KL) ASUS A002
FAQ for Toyota AR MY (iOS and Android) Q1. What types of devices are required to operate Toyota AR MY? A1. Toyota AR MY requires the latest high-end Apple and Android mobile devices with ARKit and ARcore to operate smoothly. Q2. What types of Apple devices can support Toyota AR MY? A2. The Apple iPhone (iPhone 6S and above), iPhone SE, iPad Pro (2nd Generation and above) and iPad (5th Generation and above). Q3. What types of Android mobile devices support Toyota AR MY? A3. Android devices such as AndroidOS 8 and above support the AR core framework. Other supporting Android devices are listed as below: Manufacturer Model Name Model Code Asus ROG Phone ASUS_Z01QD_1 Asus ZenFone Ares (ZS572KL) ASUS_A002_2 Asus ZenFone AR ASUS_A002_1 Asus ZenFone AR (ZS571KL) ASUS_A002 Manufacturer Model Name Model Code Google Pixel 3 blueline Google Pixel sailfish Google Pixel 2 walleye Google Pixel XL marlin Google Pixel 3 XL crosshatch Google Pixel 2 XL taimen Manufacturer Model Name Model Code Huawei Honor 8X HWJSN-H Huawei Honor 8X Max HWJSN-HM Huawei P20 Pro HWCLT Huawei P20 Pro HW-01K Huawei Honor 10 HWCOL Huawei P20 lite HWANE Huawei Nexus 6P angler Huawei Mate 20 X HWEVR Huawei Mate 20 Pro HWLYA Huawei nova 3 HWPAR Huawei Honor Magic 2 HWTNY Huawei HUAWEI Y9 2019 HWJKM-H Huawei Mate 20 HWHMA Huawei Mate 20 lite HWSNE Huawei nova 3i HWINE Manufacturer Model Name Model Code LG Electronics Q8 anna LG Electronics Q8 cv7an LG Electronics G7 One phoenix_sprout LG Electronics LG G6 lucye LG Electronics JOJO L-02K LG Electronics LG G7 ThinQ judyln LG Electronics -
SIMD in Different Processors
SIMD Introduction Application, Hardware & Software Champ Yen (嚴梓鴻) [email protected] http://champyen.blogspot.tw Agenda ● What & Why SIMD ● SIMD in different Processors ● SIMD for Software Optimization ● What are important in SIMD? ● Q & A Link of This Slides https://goo.gl/Rc8xPE 2 What is SIMD (Single Instruction Multiple Data) one lane for(y = 0; y < height; y++){ for(x = 0; x < width; x+=8){ //process 8 point simutaneously for(y = 0; y < height; y++){ uin16x8_t va, vb, vout; for(x = 0; x < width; x++){ va = vld1q_u16(a+x); //process 1 point vb = vld1q_u16(b+x); out[x] = a[x]+b[x]; vout = vaddq_u16(va, vb); } vst1q_u16(out, vout); a+=width; b+=width; out+=width; } a+=width; b+=width; out+=width; } } 3 Why do we need to use SIMD? 4 Why & How do we use SIMD? Image Processing Gaming Scientific Computing Deep Neural Network 5 SIMD in different Processor - CPU ● x86 − MMX − SSE − AVX − AVX-512 ● ARM - Application − v5 DSP Extension − v6 SIMD − v7 NEON − v8 Advanced SIMD (NEON) − SVE https://software.intel.com/sites/landingpage/IntrinsicsGuide/ http://infocenter.arm.com/help/topic/com.arm.doc.ihi0073a/IHI0073A_arm_neon_intrinsics_ref.pdf6 SIMD in different Processor - GPU ● SIMD − AMD GCN − ARM Mali ● WaveFront − Nvidia − Imagination PowerVR Rogue 7 SIMD in different Processor - DSP ● Qualcomm Hexagon 600 HVX ● Cadence IVP P5 ● Synopsys EV6x ● CEVA XM4 8 SIMD Optimization SIMD SIMD Framework / Software Hardware Programming Design Model 9 SIMD Optimization ● Auto/Semi-Auto Method ● Compiler Intrinsics ● Specific Framework/Infrastructure