Context-aware Security for Vehicles and Fleets: A Survey

Vehicles are becoming increasingly intelligent and connected. Interfaces for communication with the vehicle, such as WiFi and 5G, enable seamless integration into the user’s life, but also cyber attacks on the vehicle. Therefore, research is working on in-vehicle countermeasures such as authentication, access controls, or intrusion detection. Recently, legal regulations have also become effective that require automobile manufacturers to set up a monitoring system for fleet-wide security analysis. The growing amount of software, networking, and the automation of driving create new challenges for security. Context-awareness, situational understanding, adaptive security, and threat intelligence are necessary to cope with these ever-increasing risks. In-vehicle security should be adaptive to secure the car in an infinite number of (driving) situations. For fleet-wide analysis and alert triage, knowledge and understanding of the circumstances are required. Context-awareness, nonetheless, has been sparsely considered in the field of vehicle security. This work aims to be a precursor to context-aware, adaptive and intelligent security for vehicles and fleets. To this end, we provide a comprehensive literature review that analyzes the vehicular as well as related domains. Our survey is mainly characterized by the detailed analysis of the context information that is relevant for vehicle security in the future

Using Machine Learning to Optimize Energy Consumption of HVAC Systems in Vehicles

The detachment and calculation of functionalities from a vehicle into a cloud creates new chances. By linking different data sources with the in-vehicle data in the cloud, an optimization of these functionalities in terms of en-ergy efficiency can be applied. For example, the Heating, Ventilation and Air Conditioning (HVAC) consumes up to 30% of total energy in a vehicle. Electric vehicles in particular lead to these high values because they are not able to re-cover the waste heat from combustion engines for interior heating. Therefore, the optimization of energy efficient strategies with respect to the vehicle energy management system becomes more relevant. Forecasts of the interior vehicle temperature are directly related to the HVAC energy consumption. This work focuses on the implementation and accuracy evaluation of Recurrent Neural Networks (RNN) for interior vehicle temperature forecasting

Applied Machine Learning: Reconstruction of Spectral Data for the Classification of Oil-Quality Levels

In modern complex systems and machines - e.g., automobiles or construction vehicles - different versions of a "Condition Based Service" (CBS) are deployed for maintenance and supervision. According to the current state of the art, CBS is focusing on monitoring of static factors and rules. In the area of agricultural machines, these are for example operating hours, kilometers driven or the number of engine starts. The decision to substitute hydraulic oil is determined on the basis of the factors listed. A data-driven procedure is proposed instead to leverage the decision-making process. Thus, this paper presents a method to support continuous oil monitoring with the emphasis on artificial intelligence using real-world spectral oil-data. The reconstruction of the spectral data is essential, as a complete spectral analysis for the ultraviolet and visible range is not available. Instead, a possibility of reconstruction by sparse supporting wavelengths through neural networks is proposed and benchmarked by standard interpolation methods. Furthermore, a classification via a feed-forward neural network with the conjunction of Dynamic Time Warping (DTW) algorithm for the production of labeled data was developed. Conclusively, the extent to which changes in hyper-parameters (number of hidden layers, number of neurons, weight initialization) affect the accuracy of the classification results have been investigated

QUA³CK - A Machine Learning Development Process

Machine learning and data processing are trending topics at the moment. However, there is still alack of a standard process to support a fast, simple, and effective development of machine learningmodels for academia and industry combined. Processes such as KDD or CRISP-DM are highlyspecialized in data mining and business cases. Therefore, engineers often refer to individualapproaches to solve a machine learning problem. Especially in teaching, the lack of a standardprocess is a challenge. Students typically get a better understanding if a systematic approach tosolve problems is given to them. A challenge when formulating a machine learning developmentprocess is to provide standard actions that work on different use-cases. At the same time, it has tobe simple. Complex processes often lead to the wrong approach.The QUA³CK process was created at the Karlsruhe Institute of Technology to fill the gap inresearch and industry for a machine learning development process. However, the main focus wasto reach engineering students with an easy-to-remember, didactic way to solve machine learningproblems. This five-stage process starts with a machine learning question (Q), a problem thathas to be solved. Understanding the data (U) comes next. Then, the loop between selecting anAlgorithm (A), Adapting the features (A), and Adjusting the hyperparameters (A) is executeduntil the system is ready for Conclude and compare (C). At last, the Knowledge transfer (K) ofthe given solution can be realized as deployment in hardware or as a documentation.This paper describes the process and all individual steps in detail. Besides, we present severaluse-cases of QUA³CK in academia and research projects

A Viral Discovery Methodology for Clinical Biopsy Samples Utilising Massively Parallel Next Generation Sequencing

Here we describe a virus discovery protocol for a range of different virus genera, that can be applied to biopsy-sized tissue samples. Our viral enrichment procedure, validated using canine and human liver samples, significantly improves viral read copy number and increases the length of viral contigs that can be generated by de novo assembly. This in turn enables the Illumina next generation sequencing (NGS) platform to be used as an effective tool for viral discovery from tissue samples

Comparison of participants and non-participants to the ORISCAV-LUX population-based study on cardiovascular risk factors in Luxembourg

BACKGROUND: Poor response is a major concern in public health surveys. In a population-based ORISCAV-LUX study carried out in Grand-Duchy of Luxembourg to assess the cardiovascular risk factors, the non-response rate was not negligible. The aims of the present work were: 1) to investigate the representativeness of study sample to the general population, and 2) to compare the known demographic and cardiovascular health-related profiles of participants and non-participants. METHODS: For sample representativeness, the participants were compared to the source population according to stratification criteria (age, sex and district of residence). Based on complementary information from the "medical administrative database", further analysis was carried out to assess whether the health status affected the response rate. Several demographic and morbidity indicators were used in the univariate comparison between participants and non-participants. RESULTS: Among the 4452 potentially eligible subjects contacted for the study, there were finally 1432 (32.2%) participants. Compared to the source population, no differences were found for gender and district distribution. By contrast, the youngest age group was under-represented while adults and elderly were over-represented in the sample, for both genders. Globally, the investigated clinical profile of the non-participants was similar to that of participants. Hospital admission and cardiovascular health-related medical measures were comparable in both groups even after controlling for age. The participation rate was lower in Portuguese residents as compared to Luxembourgish (OR = 0.58, 95% CI: 0.48-0.69). It was also significantly associated with the professional status (P < 0.0001). Subjects from the working class were less receptive to the study than those from other professional categories. CONCLUSION: The 32.2% participation rate obtained in the ORISCAV-LUX survey represents the realistic achievable rate for this type of multiple-stage, nationwide, population-based surveys. It corresponds to the expected rate upon which the sample size was calculated. Given the absence of discriminating health profiles between participants and non-participants, it can be concluded that the response rate does not invalidate the results and allows generalizing the findings for the population

Variability of the chronic obstructive pulmonary disease key epidemiological data in Europe: systematic review

<p>Abstract</p> <p>Background</p> <p>Chronic obstructive pulmonary disease (COPD) is predicted to become a major cause of death worldwide. Studies on the variability in the estimates of key epidemiological parameters of COPD may contribute to better assessment of the burden of this disease and to helpful guidance for future research and public policies. In the present study, we examined differences in the main epidemiological characteristics of COPD derived from studies across countries of the European Union, focusing on prevalence, severity, frequency of exacerbations and mortality, as well as on differences between the studies' methods.</p> <p>Methods</p> <p>This systematic review was based on a search for the relevant literature in the Science Citation Index database via the Web of Science and on COPD mortality rates issued from national statistics. Analysis was finally based on 65 articles and Eurostat COPD mortality data for 21 European countries.</p> <p>Results</p> <p>Epidemiological characteristics of COPD varied widely from country to country. For example, prevalence estimates ranged between 2.1% and 26.1%, depending on the country, the age group and the methods used. Likewise, COPD mortality rates ranged from 7.2 to 36.1 per 10⁵inhabitants. The methods used to estimate these epidemiological parameters were highly variable in terms of the definition of COPD, severity scales, methods of investigation and target populations. Nevertheless, to a large extent, several recent international guidelines or research initiatives, such as GOLD, BOLD or PLATINO, have boosted a substantial standardization of methodology in data collection and have resulted in the availability of more comparable epidemiological estimates across countries. On the basis of such standardization, severity estimates as well as prevalence estimates present much less variation across countries. The contribution of these recent guidelines and initiatives is outlined, as are the problems remaining in arriving at more accurate COPD epidemiological estimates across European countries.</p> <p>Conclusions</p> <p>The accuracy of COPD epidemiological parameters is important for guiding decision making with regard to preventive measures, interventions and patient management in various health care systems. Therefore, the recent initiatives for standardizing data collection should be enhanced to result in COPD epidemiological estimates of improved quality. Moreover, establishing international guidelines for reporting research on COPD may also constitute a major contribution.</p

Mechanical Bonds and Topological Effects in Radical Dimer Stabilization

While mechanical bonding stabilizes tetrathiafulvalene (TTF) radical dimers, the question arises: what role does topology play in catenanes containing TTF units? Here, we report how topology, together with mechanical bonding, in isomeric [3]- and doubly interlocked [2]catenanes controls the formation of TTF radical dimers within their structural frameworks, including a ring-in-ring complex (formed between an organoplatinum square and a {2+2} macrocyclic polyether containing two 1,5-dioxynaphthalene (DNP) and two TTF units) that is topologically isomeric with the doubly interlocked [2]catenane. The separate TTF units in the two {1+1} macrocycles (each containing also one DNP unit) of the isomeric [3]catenane exhibit slightly different redox properties compared with those in the {2+2} macrocycle present in the [2]catenane, while comparison with its topological isomer reveals substantially different redox behavior. Although the stabilities of the mixed-valence (TTF2)^(•+) dimers are similar in the two catenanes, the radical cationic (TTF^(•+))_2 dimer in the [2]catenane occurs only fleetingly compared with its prominent existence in the [3]catenane, while both dimers are absent altogether in the ring-in-ring complex. The electrochemical behavior of these three radically configurable isomers demonstrates that a fundamental relationship exists between topology and redox properties

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Integrative and comparative genomic analyses identify clinically relevant pulmonary carcinoid groups and unveil the supra-carcinoids

International audienceThe worldwide incidence of pulmonary carcinoids is increasing, but little is known about their molecular characteristics. Through machine learning and multi-omics factor analysis, we compare and contrast the genomic profiles of 116 pulmonary carcinoids (including 35 atypical), 75 large-cell neuroendocrine carcinomas (LCNEC), and 66 small-cell lung cancers. Here we report that the integrative analyses on 257 lung neuroendocrine neoplasms stratify atypical carcinoids into two prognostic groups with a 10-year overall survival of 88% and 27%, respectively. We identify therapeutically relevant molecular groups of pulmonary car-cinoids, suggesting DLL3 and the immune system as candidate therapeutic targets; we confirm the value of OTP expression levels for the prognosis and diagnosis of these diseases, and we unveil the group of supra-carcinoids. This group comprises samples with carcinoid-like morphology yet the molecular and clinical features of the deadly LCNEC, further supporting the previously proposed molecular link between the low-and high-grade lung neuroendocrine neoplasms