Runway Sign Classifier: A DAL C Certifiable Machine Learning System

In recent years, the remarkable progress of Machine Learning (ML) technologies within the domain of Artificial Intelligence (AI) systems has presented unprecedented opportunities for the aviation industry, paving the way for further advancements in automation, including the potential for single pilot or fully autonomous operation of large commercial airplanes. However, ML technology faces major incompatibilities with existing airborne certification standards, such as ML model traceability and explainability issues or the inadequacy of traditional coverage metrics. Certification of ML-based airborne systems using current standards is problematic due to these challenges. This paper presents a case study of an airborne system utilizing a Deep Neural Network (DNN) for airport sign detection and classification. Building upon our previous work, which demonstrates compliance with Design Assurance Level (DAL) D, we upgrade the system to meet the more stringent requirements of Design Assurance Level C. To achieve DAL C, we employ an established architectural mitigation technique involving two redundant and dissimilar Deep Neural Networks. The application of novel ML-specific data management techniques further enhances this approach. This work is intended to illustrate how the certification challenges of ML-based systems can be addressed for medium criticality airborne applications

Wieso Achtsamkeitsmeditation vor Depressionen schützen kann: Erkenntnisse aus der Hirnforschung

Depressionen stellen eines der häufigsten psychiatrischen Störungsbilder dar. In den vergangenen Jahren hat sich die Perspektive der klinischen Psychologie auf dieses weit verbreitete Phänomen stark gewandelt. Früher gingen Forscher und Therapeuten häufig davon aus, dass eine Therapie nach dem Abklingen depressiver Symptome beigelegt werden kann. Unterdessen ist jedoch bekannt, dass Depressionen eine hartnäckige Krankheit darstellen, und dass negative Verstimmungen häufig auch nach einer erfolgreich beendeten Therapie wiederkehren können. Aufgrund dessen liegt bei modernen Behandlungsansätzen ein besonderer Fokus auf sogenannten "Erhaltungstherapien". Dabei handelt es sich um Maßnahmen, die Betroffenen helfen sollen, sich vor dem erneuten Auftreten depressiver Symptome zu schützen. Die "Achtsamkeitsbasierte kognitive Therapie der Depression" (Englisch: Mindfulness-Based Cognitive Therapy, MBCT; Segal et al., 2002) stellt eine solche Maßnahme dar. Betroffene können im Rahmen dieses kompakten 8-wöchigen Kurses wirksame Techniken zum Schutz vor Depressionen erlernen, die auf Achtsamkeitsmeditation basieren. Dass MBCT wirksam zur Vorbeugung gegen Depressionen ist, wurde bereits in verschiedenen Studien belegt. Es wurde auch wiederholt gezeigt, dass sich Achtsamkeitsmeditation positiv auf relevante Risikofaktoren auswirken kann. Dennoch werden die zugrundeliegenden Mechanismen auf Ebene der Hirnfunktion bis heute noch nicht ganz verstanden. An der Universität Tübingen haben wir uns in einem von der Deutschen Forschungsgemeinschaft geförderten Projekt (DFG Projekt: #KO1753/8-1, #HA1399/16-1) mit der Wirkung von Achtsamkeitsmeditation bei Patienten mit wiederkehrenden Depressionen beschäftigt. Der folgende Text soll sowohl allgemein interessierten Lesern, als auch Menschen, die von Depressionen betroffen sind, einen verständlichen Einblick in die Erkenntnisse dieser Arbeit geben. Ferner soll der akademische Leser zusammenfassend über unsere Ergebnisse informiert werden. Neben der angeführten, grundlegenden Literatur, bezieht sich die Zusammenfassung unserer Ergebnisse dabei auf folgende Veröffentlichungen: Bostanov, V., Keune, P.M., Kotchoubey, B., Hautzinger, M., 2012. Event-related brain potentials reflect increased concentration ability after mindfulness-based cognitive therapy for depression: a randomized clinical trial. Psychiatry research 199, 174-180. Keune, P.M., Bostanov, V., Hautzinger, M., Kotchoubey, B., 2011. Mindfulness-based cognitive therapy (MBCT), cognitive style, and the temporal dynamics of frontal EEG alpha asymmetry in recurrently depressed patients. Biological psychology 88, 243-252. Keune, P.M., Bostanov, V., Hautzinger, M., Kotchoubey, B., 2013. Approaching dysphoric mood: State-effects of mindfulness meditation on frontal brain asymmetry. Biological psychology 93, 105-113

Effectiveness of mobile learning languages of object-oriented programming

Nowadays, in the process of learning object-oriented programming traditional forms of learning are mainly used, but in today's world where information technologies are rapidly developing every day, there is a need to introduce additional methods and forms of learningt. This emerging form of learning is mobile learning. The article considers the main directions and possibilities of mobile learning languages of object-oriented programmingНа сегодняшний день, в процессе обучения объектно-ориентированному программированию преимущественно используются традиционные формы обучения, но в современном мире, когда информационные технологии каждый день стремительно развиваются, есть необходимость внедрения дополнительных методов и форм обучения. И этой новой развивающейся формой обучения является мобильное обучение. В статье рассмотрены основные направления и возможности мобильного обучения языкам объектно-ориентированного программировани

Measuring Mindfulness: A Psychophysiological Approach

Mindfulness-based interventions have proved effective in reducing various clinical symptoms and in improving general mental health and well-being. The investigation of the mechanisms of therapeutic change needs methods for assessment of mindfulness. Existing self-report measures have, however, been strongly criticized on various grounds, including distortion of the original concept, response bias, and other. We propose a psychophysiological method for the assessment of the mindfulness learned through time-limited mindfulness-based therapy by people who undergo meditation training for the first time. We use the individual pre-post-therapy changes (dERPi) in the event-related brain potentials (ERPs) recorded in a passive meditation task as a measure of increased mindfulness. dERPi is computed through multivariate assessment of individual participant's ERPs. We tested the proposed method in a group of about 70 recurrently depressed participants, randomly assigned in 1.7:1 ratio to mindfulness-based cognitive therapy (MBCT) or cognitive therapy (CT). The therapy outcome was measured by the long-term change (dDS) relative to baseline in the depression symptoms (DS) assessed weekly, for 60 weeks, by an online self-report questionnaire. We found a strong, highly significant, negative correlation (r = −0.55) between dERPi (mean = 0.4) and dDS (mean = −0.7) in the MBCT group. Compared to this result, the relationship between dDS and the other (self-report) measures of mindfulness we used was substantially weaker and not significant. So was also the relationship between dERPi and dDS in the CT group. The interpretation of dERPi as a measure of increased mindfulness was further supported by positive correlations between dERPi and the other measures of mindfulness. In this study, we also replicated a previous result, namely, the increase (dLCNV) of the late contingent negative variation (LCNV) of the ERP in the MBCT group, but not in the control group (in this case, CT). We interpreted dLCNV as a measure of increased meditative concentration. The relationship between dLCNV and dDS was, however, very week, which suggests that concentration might be relatively unimportant for the therapeutic effect of mindfulness. The proposed psychophysiological method could become an important component of a “mindfulness test battery” together with self-report questionnaires and other newly developed instruments

FEATURES OF METHODOLOGICAL AND SUBJECT TRAINING OF FUTURE TEACHERS OF COMPUTER SCIENCE

В статье рассматриваются дидактический потенциал сетевых сервисов на основе облачных технологий для использования в обучении, а также в профессионально-педагогической деятельности будущих учителей информатикиThe article discusses the didactic potential of network services based on cloud technologies for use in training, as well as in the professional and pedagogical activities of future computer science teacher

Atypical neural responses to vocal anger in attention-deficit/hyperactivity disorder

Background Deficits in facial emotion processing, reported in attention-deficit/hyperactivity disorder (ADHD), have been linked to both early perceptual and later attentional components of event-related potentials (ERPs). However, the neural underpinnings of vocal emotion processing deficits in ADHD have yet to be characterised. Here, we report the first ERP study of vocal affective prosody processing in ADHD. Methods Event-related potentials of 6–11-year-old children with ADHD (n = 25) and typically developing controls (n = 25) were recorded as they completed a task measuring recognition of vocal prosodic stimuli (angry, happy and neutral). Audiometric assessments were conducted to screen for hearing impairments. Results Children with ADHD were less accurate than controls at recognising vocal anger. Relative to controls, they displayed enhanced N100 and attenuated P300 components to vocal anger. The P300 effect was reduced, but remained significant, after controlling for N100 effects by rebaselining. Only the N100 effect was significant when children with ADHD and comorbid conduct disorder (n = 10) were excluded. Conclusion This study provides the first evidence linking ADHD to atypical neural activity during the early perceptual stages of vocal anger processing. These effects may reflect preattentive hyper-vigilance to vocal anger in ADHD

Event-Related Potentials and Emotion Processing in Child Psychopathology

In recent years there has been increasing interest in the neural mechanisms underlying altered emotional processes in children and adolescents with psychopathology. This review provides a brief overview of the most up-to-date findings in the field of Event-Related Potentials (ERPs) to facial and vocal emotional expressions in the most common child psychopathological conditions. In regards to externalising behaviour (i.e. ADHD, CD), ERP studies show enhanced early components to anger, reflecting enhanced sensory processing, followed by reductions in later components to anger, reflecting reduced cognitive-evaluative processing. In regards to internalising behaviour, research supports models of increased processing of threat stimuli especially at later more elaborate and effortful stages. Finally, in autism spectrum disorders abnormalities have been observed at early visual-perceptual stages of processing. An affective neuroscience framework for understanding child psychopathology can be valuable in elucidating underlying mechanisms and inform preventive intervention

The Neurocognition of Prosody

Prosody is one of the most undervalued components of language, despite its fulfillment of manifold purposes. It can, for instance, help assign the correct meaning to compounds such as “white house” (linguistic function), or help a listener understand how a speaker feels (emotional function). However, brain-based models that take into account the role prosody plays in dynamic speech comprehension are still rare. This is probably due to the fact that it has proven difficult to fully denote the neurocognitive architecture underlying prosody. This review discusses clinical and neuroscientific evidence regarding both linguistic and emotional prosody. It will become obvious that prosody processing is a multistage operation and that its temporally and functionally distinct processing steps are anchored in a functionally differentiated brain network