Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection

Unsupervised image Anomaly Detection (UAD) aims to learn robust and discriminative representations of normal samples. While separate solutions per class endow expensive computation and limited generalizability, this paper focuses on building a unified framework for multiple classes. Under such a challenging setting, popular reconstruction-based networks with continuous latent representation assumption always suffer from the "identical shortcut" issue, where both normal and abnormal samples can be well recovered and difficult to distinguish. To address this pivotal issue, we propose a hierarchical vector quantized prototype-oriented Transformer under a probabilistic framework. First, instead of learning the continuous representations, we preserve the typical normal patterns as discrete iconic prototypes, and confirm the importance of Vector Quantization in preventing the model from falling into the shortcut. The vector quantized iconic prototype is integrated into the Transformer for reconstruction, such that the abnormal data point is flipped to a normal data point.Second, we investigate an exquisite hierarchical framework to relieve the codebook collapse issue and replenish frail normal patterns. Third, a prototype-oriented optimal transport method is proposed to better regulate the prototypes and hierarchically evaluate the abnormal score. By evaluating on MVTec-AD and VisA datasets, our model surpasses the state-of-the-art alternatives and possesses good interpretability. The code is available at https://github.com/RuiyingLu/HVQ-Trans

An investigation into pilot and system response to critical in-flight events. Volume 1: Executive summary

Critical in-flight events (CIFE) that threaten the aircraft were studied. The scope of the CIFE was described and defined with emphasis on characterizing event development, detection and assessment; pilot information requirements, sources, acquisition, and interpretation, pilot response options, decision processed, and decision implementation and event outcome. Detailed scenarios were developed for use in simulators and paper and pencil testing for developing relationships between pilot performance and background information as well as for an analysis of pilot reaction decision and feedback processes. Statistical relationships among pilot characteristics and observed responses to CIFE's were developed

The Use of Exemplars in Audio-Based Media to Increase Behavioral Intent in Adopting Preventive Skin-Cancer Behaviors

Skin cancer is a growing concern in the young-adult population due to the popularity of indoor ultraviolet (UV) tanning and the acceptance of numerous myths that skin cancer is not a major health concern. This thesis aims to look at the use of media exemplar perceived to be similar and credible to the target population in order to persuade the target population to adopt preventative skin-cancer behaviors. College students of both genders and various ethnicities (N = 170) were surveyed after listening to different radio exemplars on skin cancer. Results indicated that similarity and credibility play a key role in increasing the likelihood to change behaviors, but similarity played a larger role than credibility. Results also indicated that college-aged women were more likely to be persuaded by a similar source. However, the target audience was not transported by the exemplar. Overall, results indicated that similarity and credibility play an important role in persuading individuals to change their health behaviors; however, although similar, those roles are distinct

Ambient-aware continuous care through semantic context dissemination

Background: The ultimate ambient-intelligent care room contains numerous sensors and devices to monitor the patient, sense and adjust the environment and support the staff. This sensor-based approach results in a large amount of data, which can be processed by current and future applications, e. g., task management and alerting systems. Today, nurses are responsible for coordinating all these applications and supplied information, which reduces the added value and slows down the adoption rate. The aim of the presented research is the design of a pervasive and scalable framework that is able to optimize continuous care processes by intelligently reasoning on the large amount of heterogeneous care data. Methods: The developed Ontology-based Care Platform (OCarePlatform) consists of modular components that perform a specific reasoning task. Consequently, they can easily be replicated and distributed. Complex reasoning is achieved by combining the results of different components. To ensure that the components only receive information, which is of interest to them at that time, they are able to dynamically generate and register filter rules with a Semantic Communication Bus (SCB). This SCB semantically filters all the heterogeneous care data according to the registered rules by using a continuous care ontology. The SCB can be distributed and a cache can be employed to ensure scalability. Results: A prototype implementation is presented consisting of a new-generation nurse call system supported by a localization and a home automation component. The amount of data that is filtered and the performance of the SCB are evaluated by testing the prototype in a living lab. The delay introduced by processing the filter rules is negligible when 10 or fewer rules are registered. Conclusions: The OCarePlatform allows disseminating relevant care data for the different applications and additionally supports composing complex applications from a set of smaller independent components. This way, the platform significantly reduces the amount of information that needs to be processed by the nurses. The delay resulting from processing the filter rules is linear in the amount of rules. Distributed deployment of the SCB and using a cache allows further improvement of these performance results

EDGAR: An Autonomous Driving Research Platform -- From Feature Development to Real-World Application

While current research and development of autonomous driving primarily focuses on developing new features and algorithms, the transfer from isolated software components into an entire software stack has been covered sparsely. Besides that, due to the complexity of autonomous software stacks and public road traffic, the optimal validation of entire stacks is an open research problem. Our paper targets these two aspects. We present our autonomous research vehicle EDGAR and its digital twin, a detailed virtual duplication of the vehicle. While the vehicle's setup is closely related to the state of the art, its virtual duplication is a valuable contribution as it is crucial for a consistent validation process from simulation to real-world tests. In addition, different development teams can work with the same model, making integration and testing of the software stacks much easier, significantly accelerating the development process. The real and virtual vehicles are embedded in a comprehensive development environment, which is also introduced. All parameters of the digital twin are provided open-source at https://github.com/TUMFTM/edgar_digital_twin

A mixed method review and quality criteria analysis : towards improving decision aids and informing care models in prenatal testing

Introduction: Les incertitudes des pronostics cliniques et les dilemmes moraux associés aux technologies des tests prénataux affectent les expériences et les processus décisionnels des femmes et des couples. D’une part, la validité des normes relatives au ‘consentement autonome’ et au conseil ‘non directif’ est remise en question. D’autre part, les aides à la décision sont prônées pour rehausser la prise de décision éclairée. L’objectif de ce mémoire est de construire un modèle de l’expérience des femmes et des couples qui font face aux tests prénataux afin d’identifier les facteurs qui amélioreraient les expériences, la prise de décision et le rôle des aides à la décision et informeraient le modèle de soin. Méthodologie: La modélisation et l’analyse des expériences des femmes et des couples qui affrontent les tests prénataux reposent sur une méta-ethnographie des études qualitatives et sur une analyse narrative thématique des études quantitatives. La critique d’un outil (PT) en matière de tests prénataux est également effectuée en ayant recours aux critères de qualité de l’International Patient Decision Aid Standards (IPDAS). Résultats: Un cadre conceptuel décrivant les expériences vécues est construit et l’analyse thématique le complète en soulignant que la prise de décision n’est que rarement éclairée. Les normes d’une ‘décision autonome’ et d’un ‘conseil non directif’ sont problématiques pour les femmes. Les aides à la décision amélioraient les scores de connaissances, sans pour autant modifier la perception du risque, ni les niveaux d'anxiété. L’outil PT favorise une prise de décision basée sur les préférences, mais les critères IPDAS sont difficilement applicables et leur rôle dans une décision de qualité est incertain. Discussion et conclusion: Les résultats éclairent les facteurs macro, méso et micro pouvant améliorer les expériences vécues des femmes et des couples et affecter la prise de décision et l’utilisation des aides à la décision. Un changement de paradigme préconisant le concept d’autonomie relationnelle dans le modèle de soins est suggéré. Dans le contexte des avancées en matière de test prénataux, une réévaluation des normes de pratique et de modèles de soin est requise. Le rôle des aides à la décision devra être élucidé.Introduction: The clinical prognostic uncertainties and moral dilemmas associated with technological advances of prenatal testing impact the experiences and decision-making of women and couples. While the validity of the norms of ‘autonomous consent’ and ‘non-directive’ counseling is being questioned, decision aids are promoted to enhance informed decision-making. The goals of this thesis are to develop a model of the experiences of women and couples in prenatal testing so as to identify factors that may improve experiences, decision-making, the role of decision aids and inform the care model. Methods: A model of the experiences of prenatal testing is developed through a meta-ethnography of qualitative studies and a narrative synthesis of the themes explored in quantitative studies. A prenatal testing (PT) decision tool is critically assessed using the International Patient Decision Aids Standards (IPDAS) quality criteria for decision aids. Results: A conceptual framework of the experiences of women and couples in prenatal diagnosis is constructed and complemented by a narrative thematic analysis showing that decision-making is rarely informed and that the norms of an ‘autonomous decision’ and a ‘non-directive’ counselling are problematic for women. Decision aids improve knowledge scores, but do no modify risk perception or anxiety levels. A PT tool increases preference based informed decision-making, but quality criteria are not always applicable and their role in quality decision-making is unclear. Discussion and conclusion: The results highlight macro, meso and micro-level factors that may improve the experiences of women and couples and inform decision-making processes as well as the use of decision aids. A paradigm shift towards the concept of relational autonomy in the prenatal diagnosis model of care is suggested. Advances in prenatal testing require a re-evaluation of the norms of practice and care model. The role of decision aids requires further elucidation

Combating Fake News on Social Media: A Framework, Review, and Future Opportunities

Social media platforms facilitate the sharing of a vast magnitude of information in split seconds among users. However, some false information is also widely spread, generally referred to as “fake news”. This can have major negative impacts on individuals and societies. Unfortunately, people are often not able to correctly identify fake news from truth. Therefore, there is an urgent need to find effective mechanisms to fight fake news on social media. To this end, this paper adapts the Straub Model of Security Action Cycle to the context of combating fake news on social media. It uses the adapted framework to classify the vast literature on fake news to action cycle phases (i.e., deterrence, prevention, detection, and mitigation/remedy). Based on a systematic and inter-disciplinary review of the relevant literature, we analyze the status and challenges in each stage of combating fake news, followed by introducing future research directions. These efforts allow the development of a holistic view of the research frontier on fighting fake news online. We conclude that this is a multidisciplinary issue; and as such, a collaborative effort from different fields is needed to effectively address this problem

Determinants of the uptake of prenatal aneuploidy screening among pregnant women at The Aga Khan University Hospital, Nairobi, Kenya

INTRODUCTION: Aneuploidies present with an abnormal copy number of chromosomes. Majority are lethal with only a handful carrying on to term and beyond in pregnancy. Its currently recommended that all pregnant women be offered screening for aneuploidies. This is to facilitate pregnant women make informed choices regarding their pregnancies. At present the current uptake rate of aneuploidy screening in Kenya is unknown. The purpose of this study this study was to determine whether pregnant women are aware of aneuploidy screening, the uptake rate of screening and the determinants of screening at a tertiary private healthcare facility in Nairobi, Kenya. METHODS: A cross-sectional study was conducted between August to December 2021 that involved 325 pregnant women attending their antenatal clinics at the Aga Khan University Hospital, Nairobi, Kenya. A self administered questionnaire was used to collect data on demographics, pregnancy follow up information, knowledge and attitude towards aneuploidy screening and uptake of screening. RESULTS: Three hundred and twenty-five (325) pregnant women were enrolled over a period of 6 months. Of the 325 only 186 were aware of aneuploidy screening. Uptake rate of aneuploidy screening was found to be at 39.2% (95%CI: 32.2% - 46.7%) and the only statistically significant factor associated with increased uptake of aneuploidy screening was a positive attitude towards screening (AOR: 4.36; 95%CI: 1.95-10.81, p=0.001. CONCLUSION: The level of awareness of aneuploidy screening among pregnant women is low. Of those aware of the screening methods, less than half of them underwent screening and the concept of informed choice was lacking in a majority. Increased uptake rate of screening was associated with having a positive attitude towards aneuploidy screenin