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Survey of the DASH7 Alliance Protocol for 433 MHz Wireless Sensor Communication
TLDR
The DASH7 Alliance Protocol, an active RFID alliance standard for 433 MHz wireless sensor communication based on the ISO/IEC 18000-7, is presented and a software stack implementation named OSS-7 is introduced, which is an open source implementation of the Dash7 alliance protocol used for testing, rapid prototyping, and demonstrations.
TACLeBench: A Benchmark Collection to Support Worst-Case Execution Time Research
TLDR
Open-source programs are collected, adapted to a common coding style, and provided in open-source, with the main features of TACLeBench, which is that all programs are self-contained without any dependencies on standard libraries or an operating system.
DDoS defense system for web services in a cloud environment
TLDR
This paper introduces an attack-generating tool to test and confirm previously reported vulnerabilities, and proposes an intelligent, fast and adaptive system for detecting against XML and HTTP application layer attacks.
Responsiveness and meaningful improvement of mobility measures following MS rehabilitation
TLDR
Responsiveness, clinically meaningful improvement, and real changes of frequently used mobility measures were calculated, showing great heterogeneity, and were dependent on disability level in pwMS.
Taxonomy of Real-Time Hypervisors
TLDR
This paper presents a taxonomy of current hyper visor schedulers which aim to virtualize real-time systems, based on two popular open-source hyper visors: KVM and Xen.
Distributed Uniform Streaming Framework: An Elastic Fog Computing Platform for Event Stream Processing and Platform Transparency
TLDR
This paper describes the Distributed Uniform Stream (DUST) framework, a real-world application that uses the DUST framework for platform transparency, and the distributed DUST Coordinator, which will optimize the resource consumption by moving the application components to a different execution location.
A graph CNN-LSTM neural network for short and long-term traffic forecasting based on trajectory data
TLDR
A deep neural network is proposed that simultaneously extracts the spatial features of traffic, using graph convolution, and its temporal features by means of Long Short Term Memory (LSTM) cells to make both short-term and long-term predictions.
Testing IoT systems using a hybrid simulation based testing approach
TLDR
An extensive overview of the challenges that arise when testing large IoT applications at the system level, synchronization between real-life and simulation environment and the scalability constraints of modern simulation techniques is presented.
Automatic Reverse Engineering of CAN Bus Data Using Machine Learning Techniques
TLDR
It is shown that reverse engineering of CAN bus traffic is at least partially possible by applying machine learning techniques and the performance of the classifiers increases when adding additional features to the analysis.
Modeling Resource Prices in Grid Markets
TLDR
This study investigates the possibility of modeling the price evolution in a computational market with number of techniques (support vector machines, back propagation neural networks and sequence patterns) and adds new modeling approaches for the CPU price evolution.
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