41 research outputs found
30th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2017)
Proceedings of COMADEM 201
Feature regularization and learning for human activity recognition.
Doctoral Degree. University of KwaZulu-Natal, Durban.Feature extraction is an essential component in the design of human activity
recognition model. However, relying on extracted features alone for learning often makes the model a suboptimal model. Therefore, this research
work seeks to address such potential problem by investigating feature regularization. Feature regularization is used for encapsulating discriminative
patterns that are needed for better and efficient model learning. Firstly, a
within-class subspace regularization approach is proposed for eigenfeatures
extraction and regularization in human activity recognition. In this ap-
proach, the within-class subspace is modelled using more eigenvalues from
the reliable subspace to obtain a four-parameter modelling scheme. This
model enables a better and true estimation of the eigenvalues that are distorted by the small sample size effect. This regularization is done in one
piece, thereby avoiding undue complexity of modelling eigenspectrum differently. The whole eigenspace is used for performance evaluation because
feature extraction and dimensionality reduction are done at a later stage
of the evaluation process. Results show that the proposed approach has
better discriminative capacity than several other subspace approaches for
human activity recognition. Secondly, with the use of likelihood prior probability, a new regularization scheme that improves the loss function of deep
convolutional neural network is proposed. The results obtained from this
work demonstrate that a well regularized feature yields better class discrimination in human activity recognition. The major contribution of the
thesis is the development of feature extraction strategies for determining
discriminative patterns needed for efficient model learning
P5 eHealth: An Agenda for the Health Technologies of the Future
This open access volume focuses on the development of a P5 eHealth, or better, a methodological resource for developing the health technologies of the future, based on patients’ personal characteristics and needs as the fundamental guidelines for design. It provides practical guidelines and evidence based examples on how to design, implement, use and elevate new technologies for healthcare to support the management of incurable, chronic conditions. The volume further discusses the criticalities of eHealth, why it is difficult to employ eHealth from an organizational point of view or why patients do not always accept the technology, and how eHealth interventions can be improved in the future. By dealing with the state-of-the-art in eHealth technologies, this volume is of great interest to researchers in the field of physical and mental healthcare, psychologists, stakeholders and policymakers as well as technology developers working in the healthcare sector
WSN based sensing model for smart crowd movement with identification: a conceptual model
With the advancement of IT and increase in world population rate, Crowd Management (CM) has become a subject undergoing intense study among researchers. Technology provides fast and easily available means of transport and, up-to-date information access to the people that causes crowd at public places. This imposes a big challenge for crowd safety and security at public places such as airports, railway stations and check points. For example, the crowd of pilgrims during Hajj and Ummrah while crossing the borders of Makkah, Kingdom of Saudi Arabia. To minimize the risk of such crowd safety and security identification and verification of people is necessary which causes unwanted increment in processing time. It is observed that managing crowd during specific time period (Hajj and Ummrah) with identification and verification is a challenge. At present, many advanced technologies such as Internet of Things (IoT) are being used to solve the crowed management problem with minimal processing time. In this paper, we have presented a Wireless Sensor Network (WSN) based conceptual model for smart crowd movement with minimal processing time for people identification. This handles the crowd by forming groups and provides proactive support to handle them in organized manner. As a result, crowd can be managed to move safely from one place to another with group identification. The group identification minimizes the processing time and move the crowd in smart way
Social impact retrieval: measuring author influence on information retrieval
The increased presence of technologies collectively referred to as Web 2.0 mean the entire process of new media production and dissemination has moved away from an
authorcentric approach. Casual web users and browsers are increasingly able to play a more active role in the information creation process. This means that the traditional ways in which information sources may be validated and scored must adapt accordingly.
In this thesis we propose a new way in which to look at a user's contributions to the network in which they are present, using these interactions to provide a measure of
authority and centrality to the user. This measure is then used to attribute an query-independent interest score to each of the contributions the author makes, enabling us
to provide other users with relevant information which has been of greatest interest to a community of like-minded users. This is done through the development of two
algorithms; AuthorRank and MessageRank.
We present two real-world user experiments which focussed around multimedia annotation and browsing systems that we built; these systems were novel in themselves, bringing together video and text browsing, as well as free-text annotation. Using these systems as examples of real-world applications for our approaches, we then look at a
larger-scale experiment based on the author and citation networks of a ten year period of the ACM SIGIR conference on information retrieval between 1997-2007. We use the
citation context of SIGIR publications as a proxy for annotations, constructing large social networks between authors. Against these networks we show the effectiveness of
incorporating user generated content, or annotations, to improve information retrieval
Contextual Social Networking
The thesis centers around the multi-faceted research question of how contexts may
be detected and derived that can be used for new context aware Social Networking
services and for improving the usefulness of existing Social Networking services, giving
rise to the notion of Contextual Social Networking. In a first foundational part,
we characterize the closely related fields of Contextual-, Mobile-, and Decentralized
Social Networking using different methods and focusing on different detailed
aspects. A second part focuses on the question of how short-term and long-term
social contexts as especially interesting forms of context for Social Networking may
be derived. We focus on NLP based methods for the characterization of social relations
as a typical form of long-term social contexts and on Mobile Social Signal
Processing methods for deriving short-term social contexts on the basis of geometry
of interaction and audio. We furthermore investigate, how personal social agents
may combine such social context elements on various levels of abstraction. The third
part discusses new and improved context aware Social Networking service concepts.
We investigate special forms of awareness services, new forms of social information
retrieval, social recommender systems, context aware privacy concepts and services
and platforms supporting Open Innovation and creative processes.
This version of the thesis does not contain the included publications because of
copyrights of the journals etc. Contact in terms of the version with all included
publications: Georg Groh, [email protected] zentrale Gegenstand der vorliegenden Arbeit ist die vielschichtige Frage, wie Kontexte detektiert und abgeleitet werden können, die dazu dienen können, neuartige kontextbewusste Social Networking Dienste zu schaffen und bestehende Dienste in ihrem Nutzwert zu verbessern. Die (noch nicht abgeschlossene) erfolgreiche Umsetzung dieses Programmes führt auf ein Konzept, das man als Contextual Social Networking bezeichnen kann. In einem grundlegenden ersten Teil werden die eng zusammenhängenden Gebiete Contextual Social Networking, Mobile Social Networking und Decentralized Social Networking mit verschiedenen Methoden und unter Fokussierung auf verschiedene Detail-Aspekte näher beleuchtet und in Zusammenhang gesetzt. Ein zweiter Teil behandelt die Frage, wie soziale Kurzzeit- und Langzeit-Kontexte als für das Social Networking besonders interessante Formen von Kontext gemessen und abgeleitet werden können. Ein Fokus liegt hierbei auf NLP Methoden zur Charakterisierung sozialer Beziehungen als einer typischen Form von sozialem Langzeit-Kontext. Ein weiterer Schwerpunkt liegt auf Methoden aus dem Mobile Social Signal Processing zur Ableitung sinnvoller sozialer Kurzzeit-Kontexte auf der Basis von Interaktionsgeometrien und Audio-Daten. Es wird ferner untersucht, wie persönliche soziale Agenten Kontext-Elemente verschiedener Abstraktionsgrade miteinander kombinieren können. Der dritte Teil behandelt neuartige und verbesserte Konzepte für kontextbewusste Social Networking Dienste. Es werden spezielle Formen von Awareness Diensten, neue Formen von sozialem Information Retrieval, Konzepte für kontextbewusstes Privacy Management und Dienste und Plattformen zur Unterstützung von Open Innovation und Kreativität untersucht und vorgestellt. Diese Version der Habilitationsschrift enthält die inkludierten Publikationen zurVermeidung von Copyright-Verletzungen auf Seiten der Journals u.a. nicht. Kontakt in Bezug auf die Version mit allen inkludierten Publikationen: Georg Groh, [email protected]
Appropriate Wisdom, Technology, and Management toward Environmental Sustainability for Development
The protection and maintenance of environmental resources for future generations require responsible interaction between humans and the environment in order to avoid wasting natural resources. According to an ancient Native American proverb, “We do not inherit the Earth from our ancestors; we borrow it from our children.” This indigenous wisdom has the potential to play a significant role in defining environmental sustainability. Recent technological advances could sustain humankind and allow for comfortable living. However, not all of these advancements have the potential to protect the environment for future generations. Developing societies and maintaining the sustainability of the ecosystem require appropriate wisdom, technology, and management collaboration. This book is a collection of 19 important articles (15 research articles, 3 review papers, and 1 editorial) that were published in the Special Issue of the journal Sustainability entitled “Appropriate Wisdom, Technology, and Management toward Environmental Sustainability for Development” during 2021-2022.addresses the policymakers and decision-makers who are willing to develop societies that practice environmental sustainability, by collecting the most recent contributions on the appropriate wisdom, technology, and management regarding the different aspects of a community that can retain environmental sustainability