Fuzzy transfer learning in human activity recognition.

Assisted living environments are incorporated with different technological solutions to improve the quality of life and well-being. In recent years, there has been a growing interest in the research community on how to develop evolving solutions to aid assisted living. Different techniques have been studied to address the need for technological systems which are intelligent enough to evolve their knowledge to solve tasks which have not been previously encountered. One such approach is Transfer Learning (TL), for example, between humans and robots. Humans excel at dealing with everyday activities, learning and adapting to different activities. This comprises different complex techniques which enable the lifelong learning process from observation of our environment. To obtain similar learning in assistive agents, TL is needed. The aim of the research reported in this thesis is to address the challenge associated with learning and reuse of knowledge by assistive agents in an Ambient Assisted Living (AAL) environment. In this thesis, a novel approach to transfer learning of human activities through the combination of three methods; TL, Fuzzy Systems (FS) and Human Activity Recognition (HAR) is presented. Through the incorporation of FS into the proposed approach, uncertainty that is evident in the dynamic nature of human activities are embedded into the learning model. This research is focused on applications in assistive robotics. This is with a purpose of enabling assistive robots in AAL environments to acquire knowledge of such activities as are performed by humans. To achieve this, an extensive investigation into existing learning methods applied in human activities is conducted. The investigation encompasses current state-of-the-art of TL approaches employed in skill transfer across different but contextually related activities. To address the research questions identified in the thesis, the contributions of the methodology employed are in three main categories; 1) Firstly, a novel framework for human activity learning from information observed. Experiments are conducted on selected human activities to acquire enough information for building the framework. From the acquired information, relevant features extracted are used in a learning model to recognise different activities. 2) Secondly, the sequence of occurrence(s) of tasks in an activity needs to be considered in the learning process. Therefore, in this research, a novel technique for adaptive learning of activity sequences from acquired information is developed. 3) Finally, from the sequence obtained, a novel technique for transfer of human activity across heterogeneous feature space existing between a human and an assistive robot is developed. These categories form the basis of the TL framework modelled in this research. The framework proposed is applied to TL of human activity from data generated experimentally and benchmark datasets of various classes of human activities. The results presented in this thesis show that exploring the process of human activity learning is an important aspect in the TL framework. The features extracted sufficiently distinguish relevant patterns for each activity. Also, the results demonstrate the ability of the methodology to learn and predict human actions with a high degree of certainty. This encourages the use of TL in assisted living environments and other applications. This and many more applications of TL in technology would be a potential driver of the next revolution in artificial intelligence

Proceedings of the First NASA Formal Methods Symposium

Topics covered include: Model Checking - My 27-Year Quest to Overcome the State Explosion Problem; Applying Formal Methods to NASA Projects: Transition from Research to Practice; TLA+: Whence, Wherefore, and Whither; Formal Methods Applications in Air Transportation; Theorem Proving in Intel Hardware Design; Building a Formal Model of a Human-Interactive System: Insights into the Integration of Formal Methods and Human Factors Engineering; Model Checking for Autonomic Systems Specified with ASSL; A Game-Theoretic Approach to Branching Time Abstract-Check-Refine Process; Software Model Checking Without Source Code; Generalized Abstract Symbolic Summaries; A Comparative Study of Randomized Constraint Solvers for Random-Symbolic Testing; Component-Oriented Behavior Extraction for Autonomic System Design; Automated Verification of Design Patterns with LePUS3; A Module Language for Typing by Contracts; From Goal-Oriented Requirements to Event-B Specifications; Introduction of Virtualization Technology to Multi-Process Model Checking; Comparing Techniques for Certified Static Analysis; Towards a Framework for Generating Tests to Satisfy Complex Code Coverage in Java Pathfinder; jFuzz: A Concolic Whitebox Fuzzer for Java; Machine-Checkable Timed CSP; Stochastic Formal Correctness of Numerical Algorithms; Deductive Verification of Cryptographic Software; Coloured Petri Net Refinement Specification and Correctness Proof with Coq; Modeling Guidelines for Code Generation in the Railway Signaling Context; Tactical Synthesis Of Efficient Global Search Algorithms; Towards Co-Engineering Communicating Autonomous Cyber-Physical Systems; and Formal Methods for Automated Diagnosis of Autosub 6000

Intensional Cyberforensics

This work focuses on the application of intensional logic to cyberforensic analysis and its benefits and difficulties are compared with the finite-state-automata approach. This work extends the use of the intensional programming paradigm to the modeling and implementation of a cyberforensics investigation process with backtracing of event reconstruction, in which evidence is modeled by multidimensional hierarchical contexts, and proofs or disproofs of claims are undertaken in an eductive manner of evaluation. This approach is a practical, context-aware improvement over the finite state automata (FSA) approach we have seen in previous work. As a base implementation language model, we use in this approach a new dialect of the Lucid programming language, called Forensic Lucid, and we focus on defining hierarchical contexts based on intensional logic for the distributed evaluation of cyberforensic expressions. We also augment the work with credibility factors surrounding digital evidence and witness accounts, which have not been previously modeled. The Forensic Lucid programming language, used for this intensional cyberforensic analysis, formally presented through its syntax and operational semantics. In large part, the language is based on its predecessor and codecessor Lucid dialects, such as GIPL, Indexical Lucid, Lucx, Objective Lucid, and JOOIP bound by the underlying intensional programming paradigm.Comment: 412 pages, 94 figures, 18 tables, 19 algorithms and listings; PhD thesis; v2 corrects some typos and refs; also available on Spectrum at http://spectrum.library.concordia.ca/977460

Modern software cybernetics: new trends

Software cybernetics research is to apply a variety of techniques from cybernetics research to software engineering research. For more than fifteen years since 2001, there has been a dramatic increase in work relating to software cybernetics. From cybernetics viewpoint, the work is mainly on the first-order level, namely, the software under observation and control. Beyond the first-order cybernetics, the software, developers/users, and running environments influence each other and thus create feedback to form more complicated systems. We classify software cybernetics as Software Cybernetics I based on the first-order cybernetics, and as Software Cybernetics II based on the higher order cybernetics. This paper provides a review of the literature on software cybernetics, particularly focusing on the transition from Software Cybernetics I to Software Cybernetics II. The results of the survey indicate that some new research areas such as Internet of Things, big data, cloud computing, cyber-physical systems, and even creative computing are related to Software Cybernetics II. The paper identifies the relationships between the techniques of Software Cybernetics II applied and the new research areas to which they have been applied, formulates research problems and challenges of software cybernetics with the application of principles of Phase II of software cybernetics; identifies and highlights new research trends of software cybernetic for further research

Modern software cybernetics: New trends

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Software cybernetics research is to apply a variety of techniques from cybernetics research to software engineering research. For more than fifteen years since 2001, there has been a dramatic increase in work relating to software cybernetics. From cybernetics viewpoint, the work is mainly on the first-order level, namely, the software under observation and control. Beyond the first-order cybernetics, the software, developers/users, and running environments influence each other and thus create feedback to form more complicated systems. We classify software cybernetics as Software Cybernetics I based on the first-order cybernetics, and as Software Cybernetics II based on the higher order cybernetics. This paper provides a review of the literature on software cybernetics, particularly focusing on the transition from Software Cybernetics I to Software Cybernetics II. The results of the survey indicate that some new research areas such as Internet of Things, big data, cloud computing, cyber-physical systems, and even creative computing are related to Software Cybernetics II. The paper identifies the relationships between the techniques of Software Cybernetics II applied and the new research areas to which they have been applied, formulates research problems and challenges of software cybernetics with the application of principles of Phase II of software cybernetics; identifies and highlights new research trends of software cybernetic for further research

PECoP: Parameter Efficient Continual Pretraining for Action Quality Assessment

The limited availability of labelled data in Action Quality Assessment (AQA), has forced previous works to fine-tune their models pretrained on large-scale domain-general datasets. This common approach results in weak generalisation, particularly when there is a significant domain shift. We propose a novel, parameter efficient, continual pretraining framework, PECoP, to reduce such domain shift via an additional pretraining stage. In PECoP, we introduce 3D-Adapters, inserted into the pretrained model, to learn spatiotemporal, in-domain information via self-supervised learning where only the adapter modules' parameters are updated. We demonstrate PECoP's ability to enhance the performance of recent state-of-the-art methods (MUSDL, CoRe, and TSA) applied to AQA, leading to considerable improvements on benchmark datasets, JIGSAWS ($\uparrow6.0\%$), MTL-AQA ($\uparrow0.99\%$), and FineDiving ($\uparrow2.54\%$). We also present a new Parkinson's Disease dataset, PD4T, of real patients performing four various actions, where we surpass ($\uparrow3.56\%$) the state-of-the-art in comparison. Our code, pretrained models, and the PD4T dataset are available at https://github.com/Plrbear/PECoP.Comment: Accepted to WACV 2024 (preprint

Intensional Cyberforensics

This work focuses on the application of intensional logic to cyberforensic analysis and its benefits and difficulties are compared with the finite-state-automata approach. This work extends the use of the intensional programming paradigm to the modeling and implementation of a cyberforensics investigation process with backtracing of event reconstruction, in which evidence is modeled by multidimensional hierarchical contexts, and proofs or disproofs of claims are undertaken in an eductive manner of evaluation. This approach is a practical, context-aware improvement over the finite state automata (FSA) approach we have seen in previous work. As a base implementation language model, we use in this approach a new dialect of the Lucid programming language, called Forensic Lucid, and we focus on defining hierarchical contexts based on intensional logic for the distributed evaluation of cyberforensic expressions. We also augment the work with credibility factors surrounding digital evidence and witness accounts, which have not been previously modeled. The Forensic Lucid programming language, used for this intensional cyberforensic analysis, formally presented through its syntax and operational semantics. In large part, the language is based on its predecessor and codecessor Lucid dialects, such as GIPL, Indexical Lucid, Lucx, Objective Lucid, MARFL, and JOOIP bound by the underlying intensional programming paradigm

Scientific and Technical Publishing at Goddard Space Flight Center in Fiscal Year 1994

This publication is a compilation of scientific and technical material that was researched, written, prepared, and disseminated by the Center's scientists and engineers during FY94. It is presented in numerical order of the GSFC author's sponsoring technical directorate; i.e., Code 300 is the Office of Flight Assurance, Code 400 is the Flight Projects Directorate, Code 500 is the Mission Operations and Data Systems Directorate, Code 600 is the Space Sciences Directorate, Code 700 is the Engineering Directorate, Code 800 is the Suborbital Projects and Operations Directorate, and Code 900 is the Earth Sciences Directorate. The publication database contains publication or presentation title, author(s), document type, sponsor, and organizational code. This is the second annual compilation for the Center