CSE 325 Modules #7 – Memory Management I #8 – Memory Management II #9 – Virtual Memory #10 — Networks #11 – Case Study: Linux #12 – Computer Security Readings Silberschatz, 9.1-9.8 Silberschatz, 10.1-10.6 Silberschatz, 19.1-19.3 Silberschatz, 20.1-20.11 Silberschatz, 16.1-16.6 Sample Exam Spring 2021 The subsequent pages contain 30 sample questions (the answer key is […]
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School of Computing, Edinburgh Napier University Assessment Brief Pro Forma 1. Module number SET07109 2. Module title Programming Fundamentals 3. Module leader Simon Powers 4. Tutor with responsibility for this Assessment Student¡¯s first point of contact Simon Powers S.Powers@napier.ac.uk 5. Assessment Practical Skills Assessment 1 6. Weighting 24% of module assessment 7. Size and/or time
ACS6124 Multisensor and Decision Systems Part I: Multisensor Systems Lecture1: Introduction George Konstantopoulos g.konstantopoulos@sheffield.ac.uk Automatic Control and Systems Engineering The University of Sheffield (lecture notes produced by Dr. Inaki Esnaola and Prof. Visakan Kadirkamanathan) G. Konstantopoulos ACS6124 Multisensor and Decision Systems Module plan and Assessment Time Table Lectures: 16 hours (pre-recorded lectures + synchronous lectures)
Announcements Project Notes (for next week’s deliverable) • Add your proposed Android App to the CourseLink Discussion board: “CIS 3760 Projects – Project selections will be on a first-come- first served basis” – Include your Section # & Group # • Only 1 group member needs to upload the team contract to CourseLink • Only
Reminders and Clarifications • Each sprint must be documented in the GitLab wiki – Sprint Milestones are not accurate historical documents, since unfinished stories may be moved to the next Sprint Milestone, or put back in the Product Backlog due to new priorities – Wiki should document your sprint goals, progress, evidence of completed tasks
Announcements/Reminders • IAR #1 due Friday! – Submit to your CourseLink dropbox AND to your team’s GitLab site • Sprint 1 code changes, documentation, Redmine updates, etc. must be finalized by the BEGINNING of your lab next week! (1st week after Break) – EXCEPT for your Sprint 1 retrospective (and related documentation), which you will
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Announcements • You should be able to see the correct answers/feedback in your Midterm on CourseLink now • Exemplar answers are now posted under Midterm Prep & Results folder CIS 3760 Software Engineering 1 Some QA Humour…from Steph Beach, QA Geek • https://www.youtube.com/watch?v=o2Qxf07kggM • https://www.youtube.com/watch?v=imrp-xFOx_I CIS 3760 Software Engineering 2 CIS 3760: Software Engineering Software
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CS 593: Knowledge Discovery in Databases Stevens Institute of Technology Khasha Dehnad kdehnad@stevens.edu Khasha.dehnad@aimsinfo.com Spring 2013 1 Course Requirements Recommended Prerequisites: Familiarity with the principals of statistics and probabilities and Data Mining; for example, completion of MGT 502 (no credit). Optional Hardware and Software: Lap top with internet access and ability to install
Homework 5: STA465/ STA2016 Homework 5 is due on Friday, April 9th at 11:00 a.m. EST. The homework assignment is worth 20 points in total. Question 1: Sloths in Costa Rica (6 pts) We will fit a spatial point process model to the sloth occurrence data set. The data is available in the Hwk5Files folder
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IDA Case Study 你是虚构的汽车制造商 “OEM1 “的员工。 介绍： 近期，各家TÜV机构关于乘用车法定尾气检测不规范的报道越来越多。根据初步调查，使用特殊软件版本的发动机控制单元会出现CO排放量增加的情况。联邦汽车运输局已经向该公司管理层通报了这些违规行为。他们正代表管理层调查此案，并已向受影响的发动机制造商索取2008-2016年生产的发动机的零部件清单。2009年4月31日至2014年11月31日期间，所有受影响的控制单元 “T2 “均安装在装有汽油发动机的车辆上，由控制单元制造商 “202 “在 “2022 “工厂生产。根据厂家 “201 “的信息，受影响的还有生产编号为 “2-2011-1250 “至 “2-2011-19500 “的机组。查明所有受影响的车辆的品牌和登记的城市。 “T2 “控制单元安装在所有 “OEM1 “品牌发动机上。这些发动机可由客户选择作为 “11型 “或 “12型 “车辆类型的设备特征。您应该确定受影响的车辆，并从现有数据中分离出在车辆上安装受影响部件的零部件、组件和汽车制造商。 所有的信息，包括车辆是在哪个工厂生产的，车辆是否有缺陷，都可以在集团的生产数据中找到。如果安装的单个零件、安装的部件或整车被标记为缺陷，则车辆始终被认为是缺陷。这种逻辑也相应地适用于含有单个部件缺陷的部件。 你可以进入该集团自己的数据库，必须自己决定需要哪些数据进行分析。此外，联邦汽车运输局（KBA）还向您发送了登记数据和地理数据，这些数据也储存在数据库中。数据记录的类别如下： • 单个部件 • 组成部分 • 车辆 • 地理数据 • 审批 • 后勤延误 建议在开始分析之前，先仔细观察一下各表的结构。 对于供应链的所有情况，即单个零件、部件和车辆，都有包含ID号、制造商、制造厂、生产日期和缺陷条目等信息的生产数据。ID号由零件名称、制造商、工厂和顺序号组成。例：1-201-2011-3，部件T1，制造商 “201 “在 “2011 “工厂生产，该系列的第3个部件。 对于零部件和车辆，也有零部件清单可供选择，这些清单由命名惯例Components_Name_Abbreviation声明。它们包含了每种情况下安装的所有部件或组件的信息。 基本目标是开发一个应用程序来分析你的问题。应该可以交互式地操作某些设置，这些设置在分析过程中会被自动考虑在内。为了评估结果，重要的是你要用R Markdown文件来记录你的方法。 1.从提供的tubcloud文件夹中导入相关数据集。首先，在文档中列出你要导入的文件 2.利用整齐数据的原则准备与你的任务相关的数据，并将它们合并成一个数据集。 3.开发一款符合以下标准的闪亮应用。 *
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