Technology of IT Devices
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SMART MOVEMENT DETECTION for ANDROID PHONES a Degree Thesis Submitted to the Faculty of the Escola Tècnica D'enginyeria De Tele
SMART MOVEMENT DETECTION FOR ANDROID PHONES A Degree Thesis Submitted to the Faculty of the Escola Tècnica d'Enginyeria de Telecomunicació de Barcelona Universitat Politècnica de Catalunya by Pablo Navarro Morales In partial fulfilment of the requirements for the degree in TELECOMMUNICATION ENGINEERING Advisor: Sergio Bermejo Barcelona, October 2016 Abstract This project describes a decision tree based pedometer algorithm and its implementation on Android using machine learning techniques. The pedometer can count steps accurately and It can discard irrelevant motion. The overall classification accuracy is 89.4%. Accelerometer, gyroscope and magnetic field sensors are used in the device. When user puts his smartphone into the pocket, the pedometer can automatically count steps. A filter is used to map the acceleration from mobile phone’s reference frame to the direction of gravity. As a result of this project, an android application has been developed that, using the built-in sensors to measure motion and orientation, implements a decision tree based algorithm for counting steps. 2 Resumen Este proyecto describe un algoritmo para un podómetro basado en un árbol de decisiones y su aplicación en Android utilizando técnicas de aprendizaje automático. El podómetro puede contar los pasos con precisión y se puede descartar el movimiento irrelevante. La precisión de la clasificación general es del 89,4%. Un acelerómetro, un giroscopio y un sensor de campo magnético se utilizan en el dispositivo. Cuando el usuario pone su teléfono en el bolsillo, el podómetro puede contar automáticamente pasos. Un filtro se utiliza para asignar la aceleración del sistema de referencia de teléfono móvil a la dirección de la gravedad. -
Heterogeneous Resource Mobile Sensing: Computational Offloading
Heterogeneous resource mobile sensing: computational offloading, scheduling and algorithm optimisation Petko Georgiev Corpus Christi College University of Cambridge January 2017 This dissertation is submitted for the degree of Doctor of Philosophy Declaration This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except where specifically indicated in the text. This dissertation does not exceed the regulation length of 60 000 words, including tables and footnotes. Heterogeneous resource mobile sensing: computational offloading, scheduling and algorithm optimisation Petko Georgiev Summary Important mobile apps such as digital assistants (Google Now, Apple Siri) rely on sensor data and require low-overhead accurate inferences. Although many sensor types are found in devices, the microphone with its high sampling rates arguably poses one of the greatest sensor-related mobile resource utilisation challenges and has similar generic problems faced by all sensors { e.g., efficient background operation, or obtaining accurate inferences in real time. Resource-heavy inference algorithms often employed by audio sensing apps, and the growing number of simultaneously running on-device audio background services, result in app deployments that routinely struggle to reach a day worth of operation alongside other existing services with a single battery charge. In this dissertation we address the challenges presented by emerging audio workloads on smartphone and wearable devices { we enable accurate and efficient multi-app microphone sensing by carefully managing the full range of heterogeneous processors available to high-end mobile platforms. We devise three general classes of resource optimisation techniques to empower micro- phone sensing apps with continuous, accurate, and more energy efficient operation. -
Huawei's Mobile Processors
Huawei's mobile processors Dezső Sima Vers. 2.1 November 2018 Sima Dezső, 2018 Huawei's mobile processors • 1. Overview • 2. Examples: The Kirin 950 • 2.1 The Kirin 950 • 2.2 The Kirin 960 • 2.3 The Kirin 970 • 2.4 The Kirin 980 • 3. References 1. Overview 1. Overview (1) Huawei [1] • Huawei Technologies Co. Ltd. is a Chinese multinational networking and telecommunications equipment and services company headquartered in Shenzhen China. • It was founded in 1987 and became the world's largest telecom equipment manufacturer. • The name Huawei (华为) means Chinese achievement. • Recently it has about 180 000 employees. Figure: Huawei's logo [1] Figure: Huawei's headquarter in Shenzen [1] 1. Overview (2) HiSilicon [2] • HiSilicon, a global fabless semiconductor and IC design company, headquartered in Shenzhen, China. • It was founded in 2004 as a subsidiary of Huawei. • It has offices and research centers worldwide, the number of the employees is about 7000. • HiSilicon purchases licenses mainly from ARM and designs in the first line application processors for mobiles. It filed over 5,000 patents. 1. Overview (3) 1. Overview Worldwide smartphone shipments by vendors Q4/2009 to Q4/2016 (million units) [3] 1. Overview (4) Worldwide market share of application processors in 2015 used in smartphones (based on revenue) [4] Market Processor lines Vendor Cores ISA share (examples) Qualcomm Snapdragon Qualcomm designed Krait cores ARMv7 42 % (USA) 200-800 ARM Cortex A line ARMv7/v8 Apple Apple A7-A9 Apple designed Cyclone core 21 % ARMv8 (USA) Apple A10 2xbig./4x LITTLE cores 8xARM Cortex A53 ARMv7 MediaTek Helio x10 (ARM big.LITTLE) 19 % (Taiwan) Helio X20 2xARM Cortex A72/8x A53 ARMv8 (ARM big.LITTLE) Samsung Exynos ARM Cortex A line ARMv7 (S. -
July, 2015 P.Gargini ITRS/RC
July, 2015 ITRS/RC P.Gargini ITRS Past, Present and Future PaoloPaolo GarginiGargini ChairmanChairman ITRSITRS FellowFellow IEEE,IEEE, FellowFellow II--JSAPJSAP July, 2015 ITRS/RC P.Gargini 2 AgendaAgenda InIn thethe beginningbeginning GeometricalGeometrical ScalingScaling ITRSITRS 1.01.0 EquivalentEquivalent ScalingScaling PostPost CMOSCMOS ITRSITRS 2.02.0 3D3D PowerPower ScalingScaling HeterogeneousHeterogeneous IntegrationIntegration July, 2015 ITRS/RC P.Gargini 3 MooreMoore’’ss LawLaw -- 19651965 2X/Year ~65,000 July, 2015 ITRS/RC P.Gargini 4 The Semiconductor Business in the 70s System Designer Product Proprietary Definition Product Definition Open Semiconductor Market Company Custom Standard Components Components System Integration July, 2015 ITRS/RC P.Gargini 5 The SX-70 The story of the struggle between Fairchild Instruments and Texas Instruments for the contract to supply the integrated circuitry for Polaroid's SX-70 camera, introduced in 1972, is related. Research and development work by both companies is described. The problems caused by Polaroid's secrecy regarding the overall camera design are highlighted IEEE Spectrum archive Volume 26 Issue 5, May 1989 July, 2015 ITRS/RC P.Gargini 6 Phase 1 First Age of Scaling (Self-aligned Silicon Gate) July, 2015 ITRS/RC P.Gargini 7 MOSMOS TransistorTransistor ScalingScaling (1972) Scaled Constant Parameter Voltage Voltage S < 1 Supply Voltage (Vdd) S 1 Channel Length (Lg, Le) S S Channel Width (W) S S Gate Oxide Thickness (Tox) S S Substrate Doping (N) 1/s 1/s Drive Current (Id) S 1/s * Gate Capacitance (Cg) S S Gate Delay S S 2 Active Power S 3 S * Does Not Include Carrier Velocity Saturation R. -
2017 Annual Report
HTC spokesman Name Peter Shen Title Chief Financial Ocer Acting spokesman Not Available Tel +886 3 3753252 Email [email protected] corporate headquarters Address No. 23, Xinghua Road, Taoyuan District, Taoyuan City, Taiwan, R.O.C. Tel +886 3 3753252 taipei oce Address No. 88, Section 3, Zhongxing Road, Xindian District, New Taipei City 231, Taiwan, R.O.C. Tel +886 2 89124138 Address 1F, No. 6-3, Baoqiang Road, Xindian District, New Taipei City, Taiwan, R.O.C. Tel +886 2 89124138 stock transfer agent The Transfer Agency Department of CTBC Bank Co., Ltd Address 5F, 83 Chung-Ching S. Rd. Sec 1, Taipei, Taiwan, R.O.C tel +886 2 66365566 web https://www.ctbcbank.com auditors Deloitte & Touche Auditors Wen-Ya Hsu and Casey Lai Address 12th Floor, Hung Tai Financial Plaza, 156 Min Sheng East Road. Sec 3, Taipei, Taiwan, R.O.C. Tel +886 2 25459988 Web www.deloitte.com.tw overseas stock transfer information Trading luxembourg stock exchange Web www.bourse.lu HTC website Web www.htc.com 2 Table of contents TABLE OF CONTENTS 1 Letter to HTC Shareholders p. 4 5 Capital and shares p. 120 Financial status, operating results 2 Company profile p. 12 6 and risk management p. 140 Affiliate information and 3 Business operations p. 32 7 other special notes p. 154 8 Financial information p. 178 4 Corporate governance p. 62 Table of contents 3 LETTER TO HTC SHAREHOLDERS 6 Letter to HTC shareholders LETTER TO HTC SHAREHOLDERS Dear Shareholders, In the year that HTC celebrated its 20th anniversary, we want to express our deep appreciation towards our shareholders for your dedicated support and commitment to our pursuit of HTC VISION: VIVE Reality brilliance. -
Semiconductor Times, August 2020 (P. 8)
SEMICONDUCTOR TIMES AUGUST 2020 / 1 ® AUGUST 2020 FOCUSED ON EMERGING SEMICONDUCTOR COMPANIES VOL 25, ISSUE 8 Trex processor is the first in the industry recognition streams simultaneously Startup Profiles focused on latency optimization ground- while consuming only 45W. This perfor- up, according to the company. mance demonstrates 13x performance DinoPlusAI improvement and 1/6x energy consump- DinoplusAI was founded in October The DinoplusAI processor platform tion reduction compared to Nvidia’s 2017 to develop latency-optimized AI is highly consistent and predictable, Tesla V100, according to the company. processors to enable future’s real-time and has achieved the industry’s lowest and ultra-low latency applications. The latency at low batch size, according to The DinoplusAI processor platform company has raised $6.5M. the company, which is critical in AI ap- combines the SiFive RISC-V E34 plications. DinoPlusAI has verified Trex Management Core with a proprietary VR headset users will experience nausea chipset performance against a large set AI engine from DinoplusAI. In addition, when the latency between users moving of deep learning models, ranging from SiFive’s Custom SoC Division will their eye position to video showing up is popular CNN models to LSTM models provide RTL-to-physical design. SiFive over 20 ms. Ideally, VR latency should for speech recognition. The DinoplusAI will integrate DinoplusAI AI IP blocks be no more than 7 ms, if not zero. Ul- processor, with superior DeepBench into its 16nm FinFET design platform tra-low latency, ideally at single-digit LSTM performance, enables more than based on the SiFive RISC-V E34 man- ms, also significantly benefits manufac- 4,000 real-time audio streams with a agement core to deliver a complete turing, remote operation and medicine. -
ITRS Past, Present and Future Paolopaolo Garginigargini Chairmanchairman ITRSITRS Fellowfellow IEEE,IEEE, Fellowfellow II--JSAPJSAP
ITRS Past, Present and Future PaoloPaolo GarginiGargini ChairmanChairman ITRSITRS FellowFellow IEEE,IEEE, FellowFellow II--JSAPJSAP May, 2015 ConFab P.Gargini 1 AgendaAgenda InIn thethe beginningbeginning GeometricalGeometrical ScalingScaling ITRSITRS 1.01.0 EquivalentEquivalent ScalingScaling PostPost CMOSCMOS ITRSITRS 2.02.0 3D3D PowerPower ScalingScaling HeterogeneousHeterogeneous IntegrationIntegration May, 2015 ConFab P.Gargini 2 TheThe FirstFirst PlanarPlanar IntegratedIntegrated CircuitCircuit ~1961~1961 May, 2015 ConFab P.Gargini 3 Integrated Circuits Economics Gordon Moore at Fairchild Semiconductors May, 2015 ConFab P.Gargini 4 MooreMoore’’ss LawLaw -- 19651965 2X/Year ~65,000 May, 2015 ConFab P.Gargini 5 Question April 19, 1965 With unit cost falling as the number of components per circuit rises, by 1975 economics may dictate squeezing as many as 65,000 components on a single silicon chip What could you do with 65,000 components? Gordon Moore May, 2015 ConFab P.Gargini 6 May, 2015 ConFab P.Gargini 7 ENIAC (Electronic Numerical Integrator and Computer) ENIAC weighted 30 tons and occupied 1500 squared feet of space. May, 2015 ConFab P.Gargini 8 The Semiconductor Business in the 70s System Designer Product Proprietary Definition Product Definition Open Semiconductor Market Company Custom Standard Components Components System Integration May, 2015 ConFab P.Gargini 9 The SX-70 The story of the struggle between Fairchild Instruments and Texas Instruments for the contract to supply the integrated circuitry for Polaroid's SX-70 -
Fastboot Oem Vuln: Android Bootloader Vulnerabilities in Vendor Customizations
fastboot oem vuln: Android Bootloader Vulnerabilities in Vendor Customizations Roee Hay Aleph Research, HCL Technologies Abstract dition to the main SoC, devices also have ad-hoc ICs (e.g. device sensors), each of which may contain its own We discuss the fastboot interface of the Android boot- firmware, oftentimes updatable over-the-air. loader, an area of fragmentation in Android devices. We Much room for fragmentation (and bugs), we decided then present a variety of vulnerabilities we have found to focus our research on one area, the fastboot inter- across multiple Android devices. Most notable ones in- face. clude Secure Boot & Device Locking bypasses in the Motorola and OnePlus 3/3T bootloaders. Another crit- ical flaw in OnePlus 3/3T enables easy attacks by ma- 2 Secure Boot & ABOOT licious chargers – the only prerequisite is a powered- off device to be connected. An unexpected attack vec- Android devices implement Secure Boot through a tor in Nexus 9 is also shown – malicious headphones. chain-of-trust, with a root certificate stored in hardware. Other discovered weaknesses allow for data exfiltration The first bootloader (PBL) verifies the authenticity of the (including a memory dumping of a Nexus 5X device), next one. The next bootloader verifies the one after and enablement of hidden functionality such as access to the so forth, until executions reaches ABOOT. Code flows device’s modem diagnostics and AT interfaces , and at- to ABOOT which verifies the authenticity of the boot tacks against internal System-on-Chips (SoCs) found on or recovery partitions (possibly with another key-pair), the Nexus 9 board. -
ITRS 2.0: Toward a Re-Framing of the Semiconductor Technology Roadmap
ITRS 2.0: Toward a Re-Framing of the Semiconductor Technology Roadmap Juan-Antonio Carballo3, Wei-Ting Jonas Chan1, Paolo A. Gargini4, Andrew B. Kahng1,2 and Siddhartha Nath2 1ECE and 2CSE Departments, UC San Diego, La Jolla, CA 92093 3Broadcom Corporation, San Jose, CA 95134 4Stanford University, Stanford, CA 94305 [email protected], [email protected], [email protected], [email protected], [email protected] Abstract—The International Technology Roadmap for Semiconduc- requirements. Applications had to be designed based on these tors (ITRS) has roadmapped technology requirements of the semiconductor components. However, in the past ten years, fabless design houses industry over the past two decades. The roadmap identifies major challenges have changed the industry landscape. Design teams have been in advanced technology and leads the investment of research in a cost- effective way. Traditionally, the ITRS identifies major semiconductor building customized system-on-chip (SOC) and system-in-package IC products as drivers; these set requirements for the state-of-the- (SIP) products to address specific application requirements instead art semiconductor technologies. High-performance microprocessor unit of building standard components. As applications evolve, they (MPU-HP) for servers and consumer portable system-on-chip (SOC-CP) drive further requirements for heterogeneous integration, outside for smartphones are two examples. Throughout the history of the ITRS, Moore’s Law has been the main impetus for these drivers, continuously system connectivity, etc. Up to the current 2013 edition, the ITRS pushing the transistor density to scale at a rate of 2× per technology roadmapping process (e.g., as seen in the System Drivers Chapter generation (aka “node”). -
List of Type Approved Equipment by Aiti
LIST OF TYPE APPROVED EQUIPMENT BY AITI No. Brand Model 1 360 FV-3603 (1.4MM) 2 3COM 3CRWE454G75 3 3COM 3CRWEASYA73 4 3COM 3CRWER200-75 5 3COM 3CRWER300-73 6 3COM ACCESS POINT 3150 (3CRWX315075A) 7 3COM AP2750 8 3COM AP3750 (3CRWX375075A) 9 3COM AP9552 10 3COM ROUTER 3040 (3C13640) 11 3COM WIRELESS 7760 12 3COM WIRELESS 8760 13 3COM WL-524 14 3COM WL-603 15 3COM WX2200 (3CRWX220095A) 16 3ONEDATA 1100-SS/20 17 4D-60 CHIP (TRK-AT60) 18 4K WIFI SPORTS ULTRA HD 19 4K WIDE HD A3 (ALLWINNER V3) 20 4RF APRISA SR+ 21 7 LAYERS VBTHF.GEN3.1 22 A.D.C SYSTEMS GmbH ARS100 23 A-10 TECHNOLOGY RT-760 24 A4 BT630 25 A4 TECH G10-660L 26 A4 TECH G3100 XFAR 27 A4 TECH G3-280 28 A4 TECH G7630 29 A4 TECH G9-310 30 A4 TECH G7-300 31 AASTRA BS330 32 AASTRA DIALOG 4222 33 AASTRA DT390 34 AASTRA DT690 35 ABB M-III 36 ACEMAX AMLOGIC M8S 37 ACER AM02LG 38 ACER AS4253 NOTEBOOK Page 1 of 177 LIST OF TYPE APPROVED EQUIPMENT BY AITI 39 ACER AS4830TG NOTEBOOK 40 ACER AS5750G NOTEBOOK 41 ACER ASPIRE (E5-411-C4TN) 42 ACER ASPIRE A0725-C75KK 43 ACER ASPIRE E1-410-29204G5OMN 44 ACER ASPIRE E1421-21802G50 45 ACER ASPIRE E1-422-12502G50 46 ACER ASPIRE E1-432-29552G50 47 ACER ASPIRE E1-432-29554G50 48 ACER ASPIRE E1-432-29574G50 49 ACER ASPIRE E1-432G-29552G50 50 ACER ASPIRE E1-442G-45002G75 51 ACER ASPIRE E1-470-33214G50 52 ACER ASPIRE E1-472G-54204G1T 53 ACER ASPIRE E1-472G-54204G75 54 ACER ASPIRE E1-522-65204G1TM 55 ACER ASPIRE E1-522-65204G50 56 ACER ASPIRE E1-522-65204G75 57 ACER ASPIRE E1-572G-34014G1TM 58 ACER ASPIRE E1-572G-54204G1TM 59 ACER ASPIRE E1-572G-74508G1TM -
UCLA Electronic Theses and Dissertations
UCLA UCLA Electronic Theses and Dissertations Title A Framework for Pervasive Context Awareness Permalink https://escholarship.org/uc/item/7bj942gr Author Shen, Chenguang Publication Date 2016 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California University of California Los Angeles A Framework for Pervasive Context Awareness A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science by Chenguang Shen 2016 c Copyright by Chenguang Shen 2016 Abstract of the Dissertation A Framework for Pervasive Context Awareness by Chenguang Shen Doctor of Philosophy in Computer Science University of California, Los Angeles, 2016 Professor Mani B. Srivastava, Chair The proliferation of pervasive computing devices with unprecedented sensing, communica- tion, and computation capabilities has enabled continuous and ubiquitous monitoring of users and their surrounding environments. While smartphones have evolved from only communi- cation devices into powerful personal computing platforms, connected devices such as smart- watches, cameras, motions sensors, thermostats, and energy meters, collectively dubbed as the Internet of Things, are also rapidly permeating our living spaces. The continuous stream of richly annotated, real-time data made available by tapping into the spectrum of sensors available on these devices has led to the emergence of a sprawling ecosystem of context-aware apps. These apps use sensors such as GPS, microphone, accelerometer, and gyroscope to make diverse inferences about user activities and contexts. Typical context-aware apps employ a suite of machine learning algorithms to extract semantically meaningful inferences from sensor data. However, today's connected devices and mobile operating systems are not designed to support sensing and inference workloads.