Browsing
     by title


0-9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

or enter first few letters:   
OK
Full Text
Peer Reviewed
See detailMachine Learning to Support the Presentation of Complex Pathway Graphs.
Nielsen, Sune Steinbjorn UL; Ostaszewski, Marek UL; McGee, Fintan et al

in IEEE/ACM transactions on computational biology and bioinformatics (2019)

Visualization of biological mechanisms by means of pathway graphs is necessary to better understand the often complex underlying system. Manual layout of such pathways or maps of knowledge is a difficult ... [more ▼]

Visualization of biological mechanisms by means of pathway graphs is necessary to better understand the often complex underlying system. Manual layout of such pathways or maps of knowledge is a difficult and time consuming process. Node duplication is a technique that makes layouts with improved readability possible by reducing edge crossings and shortening edge lengths in drawn diagrams. In this article we propose an approach using Machine Learning (ML) to facilitate parts of this task by training a Support Vector Machine (SVM) with actions taken during manual biocuration. Our training input is a series of incremental snapshots of a diagram describing mechanisms of a disease, progressively curated by a human expert employing node duplication in the process. As a test of the trained SVM models, they are applied to a single large instance and 25 medium-sized instances of hand-curated biological pathways. Finally, in a user validation study, we compare the model predictions to the outcome of a node duplication questionnaire answered by users of biological pathways with varying experience. We successfully predicted nodes for duplication and emulated human choices, demonstrating that our approach can effectively learn human-like node duplication preferences to support curation of pathway diagrams in various contexts. [less ▲]

Detailed reference viewed: 70 (3 UL)
Full Text
Peer Reviewed
See detailMachine learning-assisted neurotoxicity prediction in human midbrain organoids
Monzel, Anna Sophia UL; Hemmer, K; Smits, Lisa UL et al

in Parkinsonism and Related Disorders (2020)

Detailed reference viewed: 38 (3 UL)
Full Text
Peer Reviewed
See detailA Machine Learning-Based Approach for Demarcating Requirements in Textual Specifications
Abualhaija, Sallam UL; Arora, Chetan UL; Sabetzadeh, Mehrdad UL et al

in 27th IEEE International Requirements Engineering Conference (RE'19) (2019)

A simple but important task during the analysis of a textual requirements specification is to determine which statements in the specification represent requirements. In principle, by following suitable ... [more ▼]

A simple but important task during the analysis of a textual requirements specification is to determine which statements in the specification represent requirements. In principle, by following suitable writing and markup conventions, one can provide an immediate and unequivocal demarcation of requirements at the time a specification is being developed. However, neither the presence nor a fully accurate enforcement of such conventions is guaranteed. The result is that, in many practical situations, analysts end up resorting to after-the-fact reviews for sifting requirements from other material in a requirements specification. This is both tedious and time-consuming. We propose an automated approach for demarcating requirements in free-form requirements specifications. The approach, which is based on machine learning, can be applied to a wide variety of specifications in different domains and with different writing styles. We train and evaluate our approach over an independently labeled dataset comprised of 30 industrial requirements specifications. Over this dataset, our approach yields an average precision of 81.2% and an average recall of 95.7%. Compared to simple baselines that demarcate requirements based on the presence of modal verbs and identifiers, our approach leads to an average gain of 16.4% in precision and 25.5% in recall. [less ▲]

Detailed reference viewed: 508 (48 UL)
Full Text
See detailMachine Learning-Based Malware Detection for Android Applications: History Matters!
Allix, Kevin UL; Bissyande, Tegawendé François D Assise UL; Klein, Jacques UL et al

Report (2014)

Machine Learning-based malware detection is a promis- ing scalable method for identifying suspicious applica- tions. In particular, in today’s mobile computing realm where thousands of applications are ... [more ▼]

Machine Learning-based malware detection is a promis- ing scalable method for identifying suspicious applica- tions. In particular, in today’s mobile computing realm where thousands of applications are daily poured into markets, such a technique could be valuable to guaran- tee a strong filtering of malicious apps. The success of machine-learning approaches however is highly de- pendent on (1) the quality of the datasets that are used for training and of (2) the appropriateness of the tested datasets with regards to the built classifiers. Unfortu- nately, there is scarce mention of these aspects in the evaluation of existing state-of-the-art approaches in the literature. In this paper, we consider the relevance of history in the construction of datasets, to highlight its impact on the performance of the malware detection scheme. Typ- ically, we show that simply picking a random set of known malware to train a malware detector, as it is done in most assessment scenarios from the literature, yields significantly biased results. In the process of assessing the extent of this impact through various experiments, we were also able to confirm a number of intuitive assump- tions about Android malware. For instance, we discuss the existence of Android malware lineages and how they could impact the performance of malware detection in the wild. [less ▲]

Detailed reference viewed: 624 (37 UL)
Full Text
See detailMachine Learning-based Methods for Driver Identification and Behavior Assessment: Applications for CAN and Floating Car Data
Jafarnejad, Sasan UL

Doctoral thesis (2020)

The exponential growth of car generated data, the increased connectivity, and the advances in artificial intelligence (AI), enable novel mobility applications. This dissertation focuses on two use-cases ... [more ▼]

The exponential growth of car generated data, the increased connectivity, and the advances in artificial intelligence (AI), enable novel mobility applications. This dissertation focuses on two use-cases of driving data, namely distraction detection and driver identification (ID). Low and medium-income countries account for 93% of traffic deaths; moreover, a major contributing factor to road crashes is distracted driving. Motivated by this, the first part of this thesis explores the possibility of an easy-to-deploy solution to distracted driving detection. Most of the related work uses sophisticated sensors or cameras, which raises privacy concerns and increases the cost. Therefore a machine learning (ML) approach is proposed that only uses signals from the CAN-bus and the inertial measurement unit (IMU). It is then evaluated against a hand-annotated dataset of 13 drivers and delivers reasonable accuracy. This approach is limited in detecting short-term distractions but demonstrates that a viable solution is possible. In the second part, the focus is on the effective identification of drivers using their driving behavior. The aim is to address the shortcomings of the state-of-the-art methods. First, a driver ID mechanism based on discriminative classifiers is used to find a set of suitable signals and features. It uses five signals from the CAN-bus, with hand-engineered features, which is an improvement from current state-of-the-art that mainly focused on external sensors. The second approach is based on Gaussian mixture models (GMMs), although it uses two signals and fewer features, it shows improved accuracy. In this system, the enrollment of a new driver does not require retraining of the models, which was a limitation in the previous approach. In order to reduce the amount of training data a Triplet network is used to train a deep neural network (DNN) that learns to discriminate drivers. The training of the DNN does not require any driving data from the target set of drivers. The DNN encodes pieces of driving data to an embedding space so that in this space examples of the same driver will appear closer to each other and far from examples of other drivers. This technique reduces the amount of data needed for accurate prediction to under a minute of driving data. These three solutions are validated against a real-world dataset of 57 drivers. Lastly, the possibility of a driver ID system is explored that only uses floating car data (FCD), in particular, GPS data from smartphones. A DNN architecture is then designed that encodes the routes, origin, and destination coordinates as well as various other features computed based on contextual information. The proposed model is then evaluated against a dataset of 678 drivers and shows high accuracy. In a nutshell, this work demonstrates that proper driver ID is achievable. The constraints imposed by the use-case and data availability negatively affect the performance; in such cases, the efficient use of the available data is crucial. [less ▲]

Detailed reference viewed: 84 (1 UL)
Full Text
Peer Reviewed
See detailA Machine Learning-Driven Evolutionary Approach for Testing Web Application Firewalls
Appelt, Dennis UL; Nguyen, Duy Cu UL; Panichella, Annibale UL et al

in IEEE Transactions on Reliability (2018), 67(3), 733-757

Web application firewalls (WAF) are an essential protection mechanism for online software systems. Because of the relentless flow of new kinds of attacks as well as their increased sophistication, WAFs ... [more ▼]

Web application firewalls (WAF) are an essential protection mechanism for online software systems. Because of the relentless flow of new kinds of attacks as well as their increased sophistication, WAFs have to be updated and tested regularly to prevent attackers from easily circumventing them. In this paper, we focus on testing WAFs for SQL injection attacks, but the general principles and strategy we propose can be adapted to other contexts. We present ML-Driven, an approach based on machine learning and an evolutionary algorithm to automatically detect holes in WAFs that let SQL injection attacks bypass them. Initially, ML-Driven automatically generates a diverse set of attacks and submit them to the system being protected by the target WAF. Then, ML-Driven selects attacks that exhibit patterns (substrings) associated with bypassing the WAF and evolve them to generate new successful bypassing attacks. Machine learning is used to incrementally learn attack patterns from previously generated attacks according to their testing results, i.e., if they are blocked or bypass the WAF. We implemented ML-Driven in a tool and evaluated it on ModSecurity, a widely used open-source WAF, and a proprietary WAF protecting a financial institution. Our empirical results indicate that ML-Driven is effective and efficient at generating SQL injection attacks bypassing WAFs and identifying attack patterns. [less ▲]

Detailed reference viewed: 617 (104 UL)
See detailMacht Bildung glücklich?
Samuel, Robin UL

Speeches/Talks (2010)

Detailed reference viewed: 75 (9 UL)
Full Text
Peer Reviewed
See detailDie Macht der Verhältnisse: Fiktion und Beobachtung im Schulroman
Priem, Karin UL

in Zeitschrift für Qualitative Forschung (2007), 8(1), 51-59

Detailed reference viewed: 67 (1 UL)
Peer Reviewed
See detailDie Macht des Diskurses. Pestalozzis politische Sozialisation im radikalen Republikanismus Zürichs
Tröhler, Daniel UL

in Tröhler, Daniel; Horlacher, Rebekka (Eds.) Die Lebenswelten Pestalozzis im Spiegel seiner Korrespondenz 1760-1810, 1/2010 (2010)

Detailed reference viewed: 25 (1 UL)
See detailDie Macht des Stimmzettels : die Einführung des Frauenwahlrechts in Luxemburg.
Wagener, Renée UL

in Bab, Bettina (Ed.) Mit Macht zur Wahl: 100 Jahre Frauenwahlrecht in Europa. Band 1 - Historischer Teil (2006)

Detailed reference viewed: 94 (3 UL)
Full Text
Peer Reviewed
See detailMacht die Bekanntmachung zum Beihilfebegriff Steuerbeihilfen transparenter?
Haslehner, Werner UL; Schwarz, Paloma

in Jaeger, Thomas; Haslinger, Birgit (Eds.) Jahrbuch Beihilferecht 18 (2018)

The Commission's 2016 Notice on the Notion of Aid extensively covers the issue of tax measures constituting aid. This is a welcome development as it gives vital guidance to tax practice, which had been ... [more ▼]

The Commission's 2016 Notice on the Notion of Aid extensively covers the issue of tax measures constituting aid. This is a welcome development as it gives vital guidance to tax practice, which had been subject to increasing uncertainty in recent years in the area of tax aid. Due to the one-sided binding value of the notice, protected legitimate expectations are created for taxpayers to the extent that the Notice provides clear delimiting statements. Nevertheless, many of the interpretations of the Commission in the Notice are not based on case law, but rather the Commission's own views, which requires a critical examination of the positions taken by the Commission and their backing by the Court of Justice. [less ▲]

Detailed reference viewed: 74 (1 UL)
Full Text
See detailMacht Junk Food abhängig?
Matschke, Xenia; Tripathi, Gautam UL

Article for general public (2013)

Detailed reference viewed: 86 (8 UL)
Full Text
See detailMacht klassische Musik schlau? Warum Mozart hören allein nicht reicht.
Baudson, Tanja Gabriele UL

Article for general public (2013)

Detailed reference viewed: 81 (3 UL)
Full Text
See detailMacht mehr falsch! Warum uns Fehler weiterbringen.
Baudson, Tanja Gabriele UL

Article for general public (2013)

Detailed reference viewed: 38 (0 UL)
See detailMacht und Missbrauch in Institutionen: Interdisziplinäre Perspektiven auf institutionelle Kontexte und Strategien der Prävention
Willems, Helmut UL; Ferring, Dieter UL

Book published by Springer VS Verlag für Sozialwissenschaften (2014)

Während sich die öffentliche Debatte über sexuellen Missbrauch weitgehend auf die Frage nach möglichen Entschädigungen für die Opfer konzentriert, bleiben für die wissenschaftliche Diskussion doch eine ... [more ▼]

Während sich die öffentliche Debatte über sexuellen Missbrauch weitgehend auf die Frage nach möglichen Entschädigungen für die Opfer konzentriert, bleiben für die wissenschaftliche Diskussion doch eine Reihe offener Fragen. Dies betrifft die Suche nach den Ursachen und organisatorischen Risikofaktoren für das Auftreten solcher Missbrauchsfälle ebenso wie die Identifikation geeigneter Maßnahmen zur Vermeidung und Prävention. Der Sammelband thematisiert nicht nur den Missbrauch von Kindern und Jugendlichen, sondern in einem weiteren Fokus auch die Frage von Macht und Machtmissbrauch in unterschiedlichen institutionalen Kontexten (wie etwa in Pflegebeziehungen, in Altenheimen, in Gefängnissen etc.). [less ▲]

Detailed reference viewed: 167 (11 UL)
See detailMacht und Missbrauch in Institutionen: Konzeption, Begriffsbestimmung und theoretische Perspektiven
Willems, Helmut UL; Ferring, Dieter UL

in Willems, Helmut; Ferring, Dieter (Eds.) Macht und Missbrauch in Institutionen: Interdisziplinäre Perspektiven auf institutionelle Kontexte und Strategien der Prävention (2014)

Detailed reference viewed: 122 (11 UL)
Full Text
Peer Reviewed
See detailMachtindex und Drittelmitbestimmung: Differenzierter Arbeitnehmereinfluss und dessen Konsequenzen
Balsmeier, Benjamin UL; Dilger, Alexander; Geyer, Hannah

in Schmollers Jahrbuch = Journal of Applied Social Science Studies (2011), 131

Detailed reference viewed: 63 (0 UL)
See detailMachtressourcentheorie und Korporatismusansatz
Ebbinghaus, Bernhard UL

in Wenzelburger, Georg; Zohlnhöfer, Reimut (Eds.) Handbuch Policy-Forschung (2015)

Detailed reference viewed: 146 (1 UL)
Full Text
Peer Reviewed
See detailMacro- and Microrheological Properties of Mucus Surrogates in Comparison to Native Intestinal and Pulmonary Mucus
Huck, Benedikt C.; Hartwig, Olga; Biehl, Alexander et al

in BIOMACROMOLECULES (2019), 20(9), 3504-3512

Mucus is a complex hydrogel that acts as a protective barrier in various parts of the human body. Both composition and structural properties play a crucial role in maintaining barrier properties while ... [more ▼]

Mucus is a complex hydrogel that acts as a protective barrier in various parts of the human body. Both composition and structural properties play a crucial role in maintaining barrier properties while dictating diffusion of molecules and (nano)materials. In this study, we compare previously described mucus surrogates with the native human airway and pig intestinal mucus. Oscillatory shear rheology was applied to characterize mucus on the bulk macrorheological level, revealing that the artificial airway surrogate deviates from the elastic-dominant behavior of native mucus samples. We circumvented this limitation through the addition of a cross-linking polymer to the surrogate adjusting the rheological properties closer to those of native mucus. Applying particle tracking microrheology, we further demonstrated that the mechanical properties at the microscale differ significantly between artificial and native mucus. We conclude that proper characterization of mucus and its surrogates is vital for a reliable investigation of nanoparticle-based mucosal drug delivery. [less ▲]

Detailed reference viewed: 22 (0 UL)
Full Text
Peer Reviewed
See detailMacroeconomic Conditionalities: Using the Controversial Link between EU Cohesion Policy and Economic Governance
Sacher, Martin UL

in Journal of Contemporary European Research (2019), 15(2), 179-193

The reform of EU economic governance since the outbreak of the euro area crisis has not stopped at the borders of Economic and Monetary Union. With the introduction of macroeconomic conditionalities in ... [more ▼]

The reform of EU economic governance since the outbreak of the euro area crisis has not stopped at the borders of Economic and Monetary Union. With the introduction of macroeconomic conditionalities in all European Structural and Investment Funds (ESIF), EU cohesion policy is now closely linked to the Stability and Growth Pact. The European Commission is expected to propose the suspension of ESIF funding in case of non-compliance with the Excessive Deficit Procedure. This article focuses on Portugal and Spain, which were nearly sanctioned under the macroeconomic conditionalities in 2016. It will address the question of why the application of this sanctioning procedure was softened compared to the hardness of its legal provisions. Drawing on the ‘usage of Europe’ approach and on the concepts of hard and soft law, this article argues that the usage actors make of a procedure has an influence on its legal character at the enforcement stage. This article finds that the hard law character of the procedure was softened by the European Commission’s flexible application of the provisions and by the European Parliament’s strategic usage of the rules. [less ▲]

Detailed reference viewed: 49 (3 UL)