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Master's Thesis Electronic Gatekeeper Using ETHERNET
University of West Bohemia Faculty of Applied Sciences Department of Computer Science and Engineering Master’s thesis Electronic Gatekeeper using ETHERNET Plzeň 2019 Hamza Elghoul Místo této strany bude zadání práce. Declaration I hereby declare that this master’s thesis is completely my own work and that I used only the cited sources. Plzeň, 2 May 2018 Hamza Elghoul Abstract The aim of this thesis is the analysis and the realization of a budget 2-way communication system using ETHERNET connection, more specific- ally a door intercom station (hereinafter ”Bouncer” or "Gatekeeper"), where it is possible to make voice calls between two CLIENTS, a CALLER and a CALLEE with an acceptable to minimal delay. There are many alternative methods available for implementing such sys- tems, this project will try to compare some of these solutions and choose the most convenient platform according to a number of factors, such as band- width, processing power needed and communication protocols in question. Keywords: VoIP, SIP,SDP, server, client, LAN, ethernet, embedded, audio, raspberry pi Contents Page List of Figures7 1 Preface 10 2 Analysis 11 2.1 Objectives and Requirements................. 11 2.2 Hardware............................ 12 2.2.1 Arduino......................... 12 2.2.2 RaspberryPi 3 Model B................ 13 2.2.3 Banana Pi........................ 14 2.2.4 Orange Pi........................ 15 2.2.5 CubieBoard 2...................... 16 2.2.6 Beagle Bone Black................... 16 2.3 Application........................... 18 2.4 Audio capture and digitalisation................ 19 2.4.1 Signaling Protocols................... 20 2.5 Communication Protocol.................... 23 2.5.1 Session Initiation Protocol............... 23 2.5.2 Real Time Protocol.................. -
Test Coverage Guide
TEST COVERAGE GUIDE Test Coverage Guide A Blueprint for Strategic Mobile & Web Testing SUMMER 2021 1 www.perfecto.io TEST COVERAGE GUIDE ‘WHAT SHOULD I BE TESTING RIGHT NOW?’ Our customers often come to Perfecto testing experts with a few crucial questions: What combination of devices, browsers, and operating systems should we be testing against right now? What updates should we be planning for in the future? This guide provides data to help you answer those questions. Because no single data source tells the full story, we’ve combined exclusive Perfecto data and global mobile market usage data to provide a benchmark of devices, web browsers, and user conditions to test on — so you can make strategic decisions about test coverage across mobile and web applications. CONTENTS 3 Putting Coverage Data Into Practice MOBILE RECOMMENDATIONS 6 Market Share by Country 8 Device Index by Country 18 Mobile Release Calendar WEB & OS RECOMMENDATIONS 20 Market Share by Country 21 Browser Index by Desktop OS 22 Web Release Calendar 23 About Perfecto 2 www.perfecto.io TEST COVERAGE GUIDE DATA INTO PRACTICE How can the coverage data be applied to real-world executions? Here are five considerations when assessing size, capacity, and the right platform coverage in a mobile test lab. Optimize Your Lab Configuration Balance Data & Analysis With Risk Combine data in this guide with your own Bundle in test data parameters (like number of tests, analysis and risk assessment to decide whether test duration, and required execution time). These to start testing with the Essential, Enhanced, or parameters provide the actual time a full- cycle or Extended mobile coverage buckets. -
Totalmem),Form Factor,System on Chip,Screen Sizes,Screen Densities,Abis,Android SDK Versions,Opengl ES Versions
Manufacturer,Model Name,Model Code,RAM (TotalMem),Form Factor,System on Chip,Screen Sizes,Screen Densities,ABIs,Android SDK Versions,OpenGL ES Versions 10.or,E,E,2846MB,Phone,Qualcomm MSM8937,1080x1920,480,arm64-v8a 10.or,G,G,3603MB,Phone,Qualcomm MSM8953,1080x1920,480,arm64-v8a 10.or,D,10or_D,2874MB,Phone,Qualcomm MSM8917,720x1280,320,arm64-v8a 4good,A103,4GOOD_Light_A103,907MB,Phone,Mediatek MT6737M,540x960,240,armeabi- v7a 4good,4GOOD Light B100,4GOOD_Light_B100,907MB,Phone,Mediatek MT6737M,540x960,240,armeabi-v7a 7Eleven,IN265,IN265,466MB,Phone,Mediatek MT6572,540x960,240,armeabi-v7a 7mobile,DRENA,DRENA,925MB,Phone,Spreadtrum SC7731C,480x800,240,armeabi-v7a 7mobile,KAMBA,KAMBA,1957MB,Phone,Mediatek MT6580,720x1280,320,armeabi-v7a 7mobile,SWEGUE,SWEGUE,1836MB,Phone,Mediatek MT6737T,1080x1920,480,arm64-v8a A.O.I. ELECTRONICS FACTORY,A.O.I.,TR10CS1_11,965MB,Tablet,Intel Z2520,1280x800,160,x86 Aamra WE,E2,E2,964MB,Phone,Mediatek MT6580,480x854,240,armeabi-v7a Accent,Pearl_A4,Pearl_A4,955MB,Phone,Mediatek MT6580,720x1440,320,armeabi-v7a Accent,FAST7 3G,FAST7_3G,954MB,Tablet,Mediatek MT8321,720x1280,160,armeabi-v7a Accent,Pearl A4 PLUS,PEARL_A4_PLUS,1929MB,Phone,Mediatek MT6737,720x1440,320,armeabi-v7a Accent,SPEED S8,SPEED_S8,894MB,Phone,Mediatek MT6580,720x1280,320,armeabi-v7a Acegame S.A. -
Icaeyeblinkmetrics() Version 3.2
Documentation for: icaeyeblinkmetrics() Version 3.2 This EEGLAB toolbox is designed for automated/semi-automated selection of ICA components associated with eye- blink artifact using time-domain measures. The toolbox is based on the premises that 1) an ICA component associated with eye blinks should be more related to the recorded eye blink activity than other ICA components, and 2) removal of the ICA component associated with eye blinks should reduce the eye blink artifact present within the EEG following back projection. Other than the EEG input, the only required input for the function is specification of the channel that exhibits the artifact (in most cases the VEOG electrode). This can either be stored within the EEG.data matrix or within EEG.skipchannels. It will then identify eye-blinks within the channel to be used for computation of the metrics listed below. If you are not sure what channel to choose, you can let the function determine the channel where the artifact maximally presents but this does slow the function down. The toolbox does not change the data in any way, it only provides an output stored in ‘EEG.icaquant’ providing: 1. Metrics: a. The correlation between the measured artifact in the artifact channel and each ICA component. (i.e. how similar the ICA component is to the eye blink) b. The adjusted normalized convolution of the ICA component activity with the measured artifact in the artifact channel. (i.e., how well does the ICA component overlap with the eye blink) c. The percent reduction in the artifact present in the EEG for each ICA component if it was removed. -
Polycom Realpresence Trio ™ Hands-On Testing of an All-In-One Audio, Content, and Video Conferencing Device for Small Meeting Rooms
June 2017 Evaluation of Polycom RealPresence Trio ™ Hands-on testing of an all-in-one audio, content, and video conferencing device for small meeting rooms. This evaluation sponsored by: Background Founded in 1990 and headquartered in San Jose, California, Polycom is a privately-held 1 company that develops, manufactures, and markets video, voice, and content collaboration and communication products and services. The company employs approximately ~ 3,000 people and generates more than $1B in annual revenue. Polycom has been in the conference phone business since the early 1990s2, and to date has shipped more than six million analog and digital conference phones – all with the familiar Polycom three-legged “starfish” design (see images below). In October 2015, Polycom announced the RealPresence Trio 8800 – a multi-function conferencing device intended for use in small, medium, and large meeting rooms. Figure 1: Polycom SoundStation IP4000 (L) and Polycom RealPresence Trio 8800 (R) In April 2017, Polycom commissioned members of our South Florida test team to perform a third-party assessment of the RealPresence Trio 8800 solution. This document contains the results of our hands-on testing. Note – For readability and brevity’s sake, throughout this document we will refer to the Polycom RealPresence Trio 8800 as the Trio 8800 or simply Trio. 1 Polycom was acquired by private equity firm Siris Capital in September 2016 2 Source: https://en.wikipedia.org/wiki/Polycom#Polycom_audio_and_voice © 2018 Recon Research | www.reconres.com | Page 2 Understanding -
Client-Side Name Collision Vulnerability in the New Gtld Era: a Systematic Study
Session D5: Network Security CCS’17, October 30-November 3, 2017, Dallas, TX, USA Client-side Name Collision Vulnerability in the New gTLD Era: A Systematic Study Qi Alfred Chen, Matthew Thomas†, Eric Osterweil†, Yulong Cao, Jie You, Z. Morley Mao University of Michigan, †Verisign Labs [email protected],{mthomas,eosterweil}@verisign.com,{yulongc,jieyou,zmao}@umich.edu ABSTRACT was recently annouced (US-CERT alert TA16-144A), which specif- The recent unprecedented delegation of new generic top-level do- ically targets the leaked WPAD (Web Proxy Auto-Discovery) ser- mains (gTLDs) has exacerbated an existing, but fallow, problem vice discovery queries [79, 87]. In this attack, the attacker simply called name collisions. One concrete exploit of such problem was needs to register a domain that already receives vulnerable internal discovered recently, which targets internal namespaces and en- WPAD query leaks. Since WPAD queries are designed for discover- ables Man in the Middle (MitM) attacks against end-user devices ing and automatically conguring web proxy services, exploiting from anywhere on the Internet. Analysis of the underlying prob- these leaks allows the attacker to set up Man in the Middle (MitM) lem shows that it is not specic to any single service protocol, but proxies on end-user devices from anywhere on the Internet. little attention has been paid to understand the vulnerability status The cornerstone of this attack exploits the leaked service dis- and the defense solution space at the service level. In this paper, covery queries from the internal network services using DNS- we perform the rst systematic study of the robustness of internal based service discovery. -
Allworx 9204 Phone Guide
Allworx® Phone Guide 9204 No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopy, recording, or otherwise without the prior written permission of Allworx. © 2009 Allworx, a wholly owned subsidiary of PAETEC. All rights reserved. Allworx is a registered trademark of Allworx Corp. All other names may be trademarks or registered trademarks of their respective owners. Phone Guide – 9204 Table of Contents 1 GETTING STARTED.....................................................................................................................................................1 1.1 WHAT IS IN THE BOX? ...............................................................................................................................................1 1.2 CONNECTING THE PHONE .........................................................................................................................................1 2 ADJUSTING YOUR PHONE.........................................................................................................................................3 2.1 BASE ASSEMBLY AND ADJUSTING THE ANGLE OF THE PHONE.....................................................................................3 2.2 VOLUME...................................................................................................................................................................3 3 INTRODUCTION TO YOUR ALLWORX PHONE ........................................................................................................4 -
A Fully Automated Unsupervised Algorithm for Eye-Blink Detection in EEG Signals
2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton) Allerton Park and Retreat Center Monticello, IL, USA, September 24-27, 2019 Blink: A Fully Automated Unsupervised Algorithm for Eye-Blink Detection in EEG Signals Mohit Agarwal Raghupathy Sivakumar Electrical and Computer Engineering Electrical and Computer Engineering Georgia Institute of Technology Georgia Institute of Technology [email protected] [email protected] Abstract— Eye-blinks are known to substantially contaminate measurements. The presence of eye-blink artefacts in the EEG signals, and thereby severely impact the decoding of EEG EEG signal leads to confused or possibly false EEG inter- signals in various medical and scientific applications. In this pretations. Hence, the detection and removal of eye-blink work, we consider the problem of eye-blink detection that can then be employed to reliably remove eye-blinks from EEG components can be significantly useful in any EEG analysis. signals. We propose a fully automated and unsupervised eye- Several algorithms have been proposed in the literature to blink detection algorithm, Blink that self-learns user-specific identify eye-blinks, but they are characterized by one or brainwave profiles for eye-blinks. Hence, Blink does away more of the following limiting requirements - (i) a partly with any user training or manual inspection requirements. manual inspection for thresholds or template selection, (ii) Blink functions on a single channel EEG, and is capable of estimating the start and end timestamps of eye-blinks in a a user training phase, (iii) a high number of EEG channels, precise manner. We collect four different eye-blink datasets and (iv) Electrooculography (EOG) data requiring additional and annotate 2300+ eye-blinks to evaluate the robustness electrodes above and below the eyes. -
Polycom® UC Software with Skype for Business and Microsoft® Lync® Server
DEPLOYMENT GUIDE UC Software 5.4.2AA | March 2016 | 3725-49078-012A Polycom® UC Software with Skype for Business and Microsoft® Lync® Server For Polycom® RealPresence® Trio™ 8800 and Polycom® RealPresence® Trio™ Visual+ Solution Copyright© 2016, Polycom, Inc. All rights reserved. No part of this document may be reproduced, translated into another language or format, or transmitted in any form or by any means, electronic or mechanical, for any purpose, without the express written permission of Polycom, Inc. 6001 America Center Drive San Jose, CA 95002 USA Trademarks Polycom®, the Polycom logo and the names and marks associated with Polycom products are trademarks and/or service marks of Polycom, Inc. and are registered and/or common law marks in the United States and various other countries. All other trademarks are property of their respective owners. No portion hereof may be reproduced or transmitted in any form or by any means, for any purpose other than the recipient's personal use, without the express written permission of Polycom. Disclaimer While Polycom uses reasonable efforts to include accurate and up-to-date information in this document, Polycom makes no warranties or representations as to its accuracy. Polycom assumes no liability or responsibility for any typographical or other errors or omissions in the content of this document. Limitation of Liability Polycom and/or its respective suppliers make no representations about the suitability of the information contained in this document for any purpose. Information is provided "as is" without warranty of any kind and is subject to change without notice. The entire risk arising out of its use remains with the recipient. -
Download from App Store to File Converter Download from App Store to File Converter
download from app store to file converter Download from app store to file converter. Completing the CAPTCHA proves you are a human and gives you temporary access to the web property. What can I do to prevent this in the future? If you are on a personal connection, like at home, you can run an anti-virus scan on your device to make sure it is not infected with malware. If you are at an office or shared network, you can ask the network administrator to run a scan across the network looking for misconfigured or infected devices. Another way to prevent getting this page in the future is to use Privacy Pass. You may need to download version 2.0 now from the Chrome Web Store. Cloudflare Ray ID: 67d50b368e5dc3cf • Your IP : 188.246.226.140 • Performance & security by Cloudflare. Download from app store to file converter. Completing the CAPTCHA proves you are a human and gives you temporary access to the web property. What can I do to prevent this in the future? If you are on a personal connection, like at home, you can run an anti-virus scan on your device to make sure it is not infected with malware. If you are at an office or shared network, you can ask the network administrator to run a scan across the network looking for misconfigured or infected devices. Another way to prevent getting this page in the future is to use Privacy Pass. You may need to download version 2.0 now from the Chrome Web Store. -
Forensic Analysis of Communication Records of Messaging Applications from Physical Memory
ARTICLE IN PRESS JID: COSE [mNS; October 24, 2018;11:47 ] computers & security xxx (xxxx) xxx Available online at www.sciencedirect.com j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o s e Forensic analysis of communication records of messaging applications from physical memory ∗ Diogo Barradas , Tiago Brito, David Duarte, Nuno Santos, Luís Rodrigues INESC-ID, Instituto Superior Técnico, Universidade de Lisboa, Portugal a r t i c l e i n f o a b s t r a c t Article history: Inspection of physical memory allows digital investigators to retrieve evidence otherwise Received 2 May 2018 inaccessible when analyzing other storage media. In this paper, we analyze in-memory com- Accepted 23 August 2018 munication records produced by instant messaging and email applications, both in desktop Available online xxx web-based applications and native applications running in mobile devices. Our results show that, in spite of the heterogeneity of data formats specific to each application, communica- Keywords: tion records can be represented in a common application-independent format. This format Digital forensics can then be used as a common representation to allow for general analysis of digital ar- Instant-messaging tifacts across various applications. Then, we introduce RAMAS, an extensible forensic tool Memory forensics which aims to ease the process of analysing communication records left behind in physical Mobile applications memory by instant-messaging and email clients. Web-applications © 2018 Elsevier Ltd. -
Modeling and Analysis of Next Generation 9-1-1 Emergency Medical Dispatch Protocols
MODELING AND ANALYSIS OF NEXT GENERATION 9-1-1 EMERGENCY MEDICAL DISPATCH PROTOCOLS Neeraj Kant Gupta, BE(EE), MBA, MS(CS) Dissertation Prepared for the Degree of DOCTOR OF PHILOSOPHY UNIVERSITY OF NORTH TEXAS August 2013 APPROVED: Ram Dantu, Major Professor Kathleen Swigger, Committe Member Paul Tarau, Committee Member Sam G Pitroda Committee Member Barrett Bryant, Chair of the Department of Computer Science and Engineering Costas Tsatsoulis, Dean of the College of Engineering Mark Wardell, Dean of the Toulouse Graduate School Gupta, Neeraj Kant. Modeling and Analysis of Next Generation 9-1-1 Emergency Medical Dispatch Protocols. Doctor of Philosophy (Computer Science), August 2013, 192 pp., 12 tables, 72 figures, bibliography, 196 titles. In this thesis I analyze and model the emergency medical dispatch protocols for Next Generation 9-1-1 (NG9-1-1) architecture. I have identified various technical aspects to improve the NG9-1-1 dispatch protocols. The specific contributions in this thesis include developing applications that use smartphone sensors. The CPR application uses the smartphone to help administer effective CPR even if the person is not trained. The application makes the CPR process closed loop, i.e., the person who administers the CPR as well as the 9-1-1 operator receive feedback and prompt from the application about the correctness of the CPR. The breathing application analyzes the quality of breathing of the affected person and automatically sends the information to the 9-1-1 operator. In order to improve the human computer interface at the caller and the operator end, I have analyzed Fitts law and extended it so that it can be used to improve the instructions given to a caller.