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In the recent years, virtual machine introspection (VMI) has become a valuable technique for developing security applications for virtualized environments. With the increasing popularity of the ARM architecture, and the recent addition of hardware virtualization extensions, there is a growing need for porting existing VMI tools. Porting these applications requires proper hypervisor support, which we have been implementing for the upcoming release of the Xen hypervisor.

山中 卓 (大阪大学 大学院理学研究科 物理学専攻)先生が作成された科研費LaTeXを、坂東 慶太 (名古屋学院大学) が了承を得てテンプレート登録しています。 詳細はこちら↓をご確認ください。 http://osksn2.hep.sci.osaka-u.ac.jp/~taku/kakenhiLaTeX/

This template was designed for my students to utilize when completing their Reflection on Growth Mindset and Productive Failure Videos assignment.

Template para o relatório de drawback.

This template mainly refer to: HPI – PhD Thesis Template Tesi UniTN ULBreport Template Unofficial La Trobe University Template

Graduation project report for computer sciences/software engineering studies in French

重庆大学计算组成原理系列实验报告模板

The Observatory of Public Spending (or ODP, in Portuguese) is a special unit of Brazil's Ministry of Transparency, Monitoring and Office of the Comptroller-General (or CGU, in Portuguese) responsible for monitoring public spending and gathering managerial and audit information to support the work of CGU internal auditors. One of the most important themes monitored by this unit is Public Procurements and Government Suppliers which have won these procurement processes. Image analysis of many of these suppliers headquarters revealed suspicious landscapes, such as rural areas, isolated places or slums. These landscapes could be an indication of fake suppliers with poor capacity of delivering public goods and services. However, checking thousands of landscapes in order to find these fake suppliers would be a very expensive task. Our objective then is to discover what are the possible groups of scenes involving government suppliers, given that these images were not previously labeled, as automatically as possible. For that reason, we used Places CNN, a pretrained convolutional neural network for scene recognition presented by Zhou et al., which was trained on 205 scene categories with 2.5 million images, for scene recognition on Brazilian Government Suppliers.

Report for laboratory sessions and assignments based on Bachelor's & Master's Thesis Template copyleft by Artur M. Brodzki & Piotr Woźniak Faculty of Electronics and Information Technology, all credits to them