Distributed reflective architectures for anomaly detection and autonomous recovery

  • 191 Pages
  • 1.11 MB
  • English
University of Birmingham , Birmingham
Statementby Catriona Mairi Kennedy.
The Physical Object
Paginationviii, 191 p. ;
ID Numbers
Open LibraryOL21688665M

Details Distributed reflective architectures for anomaly detection and autonomous recovery FB2

Autonomous recovery from hostile code insertion using distributed reflection. Action editor: Ron Sun replanning and reconfiguration can also be incorporated in a real autonomous system based on a distributed reflective architecture. so that normal patterns of anomaly-detection and recovery can be included in the model.

The model of a Cited by: In this paper, we explore reflective architectures which enable an autonomous system to build a model of its own operation and use this model for the purpose of survival (including anomaly.

Distributed Reflective Architectures for Anomaly Detection and Autonomous Recovery In a hostile environment, an autonomous system requires a reflective capability to detect problems in its own. Title: Distributed Reflective Architectures for Anomaly Detection and Autonomous Recovery PhD thesis, University of Birmingham, Author: Catriona M.

Kennedy Date installed: 16. Distributed anomaly-detection techniques that concurrently process multiple streams of data to detect outliers have been well-studied in the literature. A comprehensive survey of data-mining research in IoT has been conducted by Tsai et al. [51] and includes details about various classifications, clustering, knowledge discovery in databases Cited by: Concurrency control and recovery in database systems Helary J, Raynal M and Singhal M () Deadlock Models and a General Algorithm for Distributed Deadlock Detection, Journal of Parallel and or Guaranteeing Serializability in a Heterogeneous Environment of Multiple Autonomous Resource Mangers Using Atomic Commitment Proceedings of the.

Partitioning is a widespread technique that enables the execution of mixed-criticality applications in the same hardware platform. New challenges for the next generation of partitioned systems include the use of multiprocessor architectures and distribution standards in order to open up this technique to a heterogeneous set of emerging scenarios (e.g., cyber-physical systems).

1. Introduction. Wearable Health Devices (WHDs) are an emerging technology that enables continuous ambulatory monitoring of human vital signs during daily life (during work, at home, during sport activities, etc.) or in a clinical environment, with the advantage of minimizing discomfort and interference with normal human activities [].WHDs are part of personal health systems, a concept Cited by: Certificateless Distributed reflective architectures for anomaly detection and autonomous recovery book verification scheme with privacy-preserving and message recovery for dynamic group.

Anomaly detection in agri warehouse construction: Andrew McCarren, Suzanne McCarthy Chris Date published a book about the view update problem in the context of the Relational Model.

He presented several detailed examples of Cited by: 7. Machine Learning (ML) has been enjoying an unprecedented surge in applications that solve problems and enable automation in diverse domains. Primarily, this is due to the explosion in the availability of data, significant improvements in ML techniques, and advancement in computing capabilities.

Undoubtedly, ML has been applied to various mundane and complex problems arising in Cited by: This volume originated from the International Parallel and Distributed Processing Symposium, and examines distributed computing and real-time systems.

It is intended for researchers, professors, practitioners and students. in Proc. of the 14th Intl. Workshop on Nature Inspired Distributed Computing (NIDISC ), part of the 25th IEEE/ACM Intl.

Parallel and Distributed Processing Symposium (IPDPS ) () Sparse Antenna Array Optimization with the Cross-Entropy Method. Allspaw is the former CTO of Etsy. He applies concepts from resilience engineering to the tech industry. He is one of the founders Adaptive Capacity Labs, a resilience engineering consultancy.

Allspaw tweets as @allspaw. Selected publications. STELLA: Report from the SNAFUcatchers Workshop on Coping with Complexity. Established in OctoberUSI's Faculty of Informatics is dedicated to high quality teaching and research.

The mission of the Faculty is to conduct research and produce results in the field of informatics and to equip students with creative problem-solving skills that enable them to address. () Hyperspectral Anomaly Detection via Global and Local Joint Modeling of Background.

IEEE Transactions on Signal Processing() Efficient dynamic simulations of charged dielectric colloids through a novel hybrid by: Search the leading research in optics and photonics applied research from SPIE journals, conference proceedings and presentations, and eBooks.

“Anomaly Detection in IoMT-Enabled Data Mashup Service for Urban Environmental Monitoring”. In 13th International Conference on Multimedia Information Technology and Applications, Cyberjaya, Malaysia., July () Sparse representation and overcomplete dictionary learning for anomaly detection in electrocardiograms.

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How it works. This project is about the description of ontologies for anomaly detection in computer systems. The special case of the anomaly detection system in Cfengine is used as a case study.

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Soft real-time requirements are often related to communication in distributed systems. Therefore it is interesting to understand how UML sequence diagrams can be. Sure. Here's a selection from The ACM Computing Classification System General and reference Document types Surveys and overviews.

Cloud Computing for Enterprise Architectures: Concepts, Principles and Approaches Zaigham Mahmood Abstract Cloud Computing is the latest paradigm that involves delivering hosted services over the Internet, based on a pay-as-you-go approach.

In the security field, deep learning has shown good experimental results in malware/anomaly detection, APT protection, spam/phishing detection, and traffic identification.

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This DEF CON session will guide the audience through the theory and motivations behind deep learning systems. Anomaly Detection has become an invaluable tool for forensic analysis and intrusion detection.

Unfortunately, the detection accuracy of all learning-based ADs depends heavily on the quality of the training data, which is often poor, severely degrading their reliability as a.

Abstract Book 6 Improving Application Software by Integrating Master Scheduling with Material Requirements Planning in Supply Chain Management Harish Bahl 44 Developing and Implementing Instrumentation for Digital High School Curricula: A Regional Study of a Rubric for Instructional Quality Savilla Bannister & Rachel Reinhart 45 Classification of outputs submitted to Sub-panel Computer Sciences and Informatics.

This REF specialism classification is taken from the Association of Computing Machinery (ACM) Computing Classification System March Revision, hence the use of American spelling. Content Posted in PDF. Annual Report of the Graduate School of Engineering and Management, Air Force Institute of Technology, Office of Research and Sponsored Programs, Graduate School of Engineering and Management, AFIT.

PDF. Annual Report of the Graduate School of Engineering and Management, Air Force Institute of Technology, Office of Research and Sponsored. This purpose of this project is to develop a spray drying prototype to for the recovery and recycle of water from concentrated waste water recovery system brine.

Spray drying is a one step, continuous process where a solution, slurry, sludge or paste is transformed into a dry solid and clean water.

Long-range detection on the ground is a key step on the path to detection from low Earth orbit or geosynchronous (GEO) orbit [8], and one of the limitations is the lack of an appropriately sensitive advanced sensor capable of high dynamic range that can tolerate field conditions, sense light very precisely (ideally at or near the photon shot.

Implementation of Regional-CNN and SSD Machine Learning Object Detection Architectures for the Real Time Analysis of Blood Borne Pathogens in Dark Field Microscopy Daniel Fleury, Angelica Fleury Subject: Mathematics & Computer Science, Artificial Intelligence & Robotics Keywords: Convolutional Neural Network,Single Shot Detector, Regional.

/ - DISTRIBUTED NETWORK ANOMALY DETECTION: 1: Yang Ma: US: Irvine: / - Ultrasound Assisted Heavy Metal Recovery: 1: An Ma: CN: Beijing: / - Selective Hydrogenation Catalyst for Unsaturated Compound: 1: Yantao Ma: US: Bosie: / - MULTI-PHASE SIGNAL.The book does not attempt to compare, analyse or propose improvements to existing processes or process design methodologies.

Its main concern is with the core technologies and basic concepts underpinning software process modelling and software process automation, with a special emphasis on the mechanisms that support software process evolution. Autonomicity (or self-management) -based architectures for the entirety, or parts, of airspace operations.

Autonomous systems to produce any of the following system capabilities: Prognostics, data mining, and data discovery to identify opportunities for improvement in airspace operations. Weather-integrated flight planning, rerouting, and.