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One major goal of green-field factory planning is to decide on space requirements in the plant. In this phase, detailed information about the supply chain network (e.g. which suppliers deliver which parts) is often unavailable. Nevertheless, typical decisions in supply chain management, like the definition of replenishment processes and quantities or make-or-buy decisions, impact space requirements in the factory and should therefore be considered in the factory planning. This research article proposes a simulation approach for a factory simulation in which raw material replenishment is integrated to evaluate the space requirements for raw materials.
We present two methods that combine image reconstruction and edge detection in computed tomography (CT) scans. Our first method is as an extension of the prominent filtered backprojection algorithm. In our second method we employ ℓ1-regularization for stable calculation of the gradient. As opposed to the first method, we show that this approach is able to compensate for undersampled CT data.
Background:
Brain lesions in language-related cortical areas remain a challenge in the clinical routine. In recent years the resting-state fMRI (rs-fMRI) was shown to be a feasible method for preoperative language assessment. The aim of this study was to examine whether language-related resting-state components, which have been obtained using a data-driven independent-component-based identification algorithm, can be supportive in determining language dominance in the left or right hemisphere.
Methods:
Twenty patients suffering from brain lesions close to supposed language relevant cortical areas were included. Rs-fMRI and task-based (tb-fMRI) were performed for the purpose of preoperative language assessment. Tb-fMRI included a verb generation task with an appropriate control condition (a syllable switching task) to decompose language critical and language supportive processes. Subsequently, the best fitting ICA component for the resting-state language network (RSLN) referential to general linear models (GLMs) of the tb-fMRI (including models with and without linguistic control conditions) was identified using an algorithm based on the Dice-index.
Results:
The RSLNs associated with GLMs using a linguistic control condition led to significantly higher laterality indices than GLM baseline contrasts. LIs derived from GLM contrasts with and without control conditions alone did not differ significantly.
Conclusion:
In general, the results suggest that determining language dominance in the human brain is feasible both with tb-fMRI and rs-fMRI, and in particular, the combination of both approaches yields a higher specificity in preoperative language assessment. Moreover, we can conclude that the choice of the language mapping paradigm is crucial for the mentioned benefits.
To investigate the role of heuristics in the domain of software engineering, an eye tracking study was conducted in which experts and novices were compared. The study focused on one of the most challenging parts in this domain: the generation of an object model for a software product based on a requirements specification. During their training, software engineers are taught different techniques to solve this task. One of these techniques is the noun/verb analysis.
However, it is still unclear to what extent novice and expert programmers are making use of it. Ideally, the noun/verb analysis works as a heuristic and helps programmers to make fast and accurate decisions. Participants in the study were 40 software programmers at four levels of expertise (novices, intermediates, experienced rogrammers, experts). They were presented with ten decision tasks. In each task, participants read a requirement specification and then had to choose one out of three presented class diagrams that they considered the best solution. During the task, their eye movements were recorded. Results show that all participants used the noun/verb analysis as a heuristic. Programmers with higher levels of expertise, however, outperformed programmers with lower levels of expertise. Interestingly, the more experienced programmers were not following the noun/verb analysis in a blindfolded way. They realised that the noun/verb analysis would produce diagrams, but a skilled software architect would not model them in this way. Instead they created their models in a way that they perceived as more logical and realistic
The partitioning hypervisor Jaihouse allows us to run safety critical and uncritical applications in parallel on a single SoC. We present our experiences when porting a safety and real-time critical existing application as a Jailhouse guest. It shows a novel and promising approach for implementing mixed-criticality applications with real-time requirement while not loosing the benefits of Linux. This is done by static partitioning of hardware resources; guests do not interfere. We will present a multicopter platform running the real-time critical flight stack in an isolated Jailhouse guest. This proves the practicability of Jailhouse as well as the suitability for real-time safety critical systems by porting an existing application to a Jailhouse cell. We stress its concept and show up current hardware limitations, like undesired behaviour and present possible workarounds and solutions.
Embedded Linux drives an every-increasing number of appliances in many domains and applications, some even real-time and/or safety critical. Traditional quality assurance of such systems is based on testing and formal verification, but the huge amount of code and the rapid dynamics of the Linux ecosystem, as well as fundamental limitations of formal methods make these approaches unsatisfactory.
Statistical quality assurance for reliability, error rates, maximal latencies etc. is needed. We will discuss current best practises, how to design and run automated statistical tests that capture relevant information, and how to properly evaluate the resulting data. Practical real-world examples and recipes are played through using the open source R language. Most importantly, we identify common mistakes in (over-)interpreting statistical results and predictions that may eventually harm people.
IOT Backdoors in Cars
(2019)
Connecting cheap IoT devices to the safety-critical network of a car can be an extremely bad idea, but at least it allows us to hack together our own automotive gadget. This talk explains the complete procedure involved in transforming a cheap OBD GSM dongle designed for fleet management into a open source automotive hacking tool. First, the hardware reverse engineering is demonstrated, showing how each component is interconnected and working together. With this knowledge, it was possible to capture the communication of the GSM module and understand the OTA protocol used by this dongle, which can be used to extract the firmware. A quick reverse engineering of the software will show that no cryptographic authentication is used for the OTA updates, and therefore a pirate GSM BTS can be used to obtain remote code execution. After that, a new open source firmware is written for the device, which can easily be extended and controlled remotely with the LUA scripting language. Examples on how hacking this dongle remotely can affect the safety of the driver will be also given.
This talk will provide a general overview on how Scapy can be used for automotive penetration testing. All present features of Scapy for automotive penetration will be introduced and explained. Also an overview of higher level automotive protocols will be given.
As automotive penetration testing becomes more important, the lack of free tools for automotive network penetration testing led us to integrate new features in Scapy. Scapy is a well established framework for packet manipulation. The flexibility of Scapy allowed us to implement automotive interfaces (CAN) and automotive protocols (ISOTP, GMLAN, UDS, DoIP, OBD-II).
This talk explains the basics of these automotive protocols, the workflow with Scapy for automotive network penetration testing. A live demonstration with some embedded hardware will be given.