3,833 research outputs found
Monitoring and detection of agitation in dementia: towards real-time and big-data solutions
The changing demographic profile of the population has potentially challenging social, geopolitical, and financial consequences for individuals, families, the wider society, and governments globally. The demographic change will result in a rapidly growing elderly population with healthcare implications which importantly include Alzheimer type conditions (a leading cause of dementia). Dementia requires long term care to manage the negative behavioral symptoms which are primarily exhibited in terms of agitation and aggression as the condition develops. This paper considers the nature of dementia along with the issues and challenges implicit in its management. The Behavioral and Psychological Symptoms of Dementia (BPSD) are introduced with factors (precursors) to the onset of agitation and aggression. Independent living is considered, health monitoring and implementation in context-aware decision-support systems is discussed with consideration of data analytics. Implicit in health monitoring are technical and ethical constraints, we briefly consider these constraints with the ability to generalize to a range of medical conditions. We postulate that health monitoring offers exciting potential opportunities however the challenges lie in the effective realization of independent assisted living while meeting the ethical challenges, achieving this remains an open research question remains.Peer ReviewedPostprint (author's final draft
Smart Geographic object: Toward a new understanding of GIS Technology in Ubiquitous Computing
One of the fundamental aspects of ubiquitous computing is the instrumentation
of the real world by smart devices. This instrumentation constitutes an
opportunity to rethink the interactions between human beings and their
environment on the one hand, and between the components of this environment on
the other. In this paper we discuss what this understanding of ubiquitous
computing can bring to geographic science and particularly to GIS technology.
Our main idea is the instrumentation of the geographic environment through the
instrumentation of geographic objects composing it. And then investigate how
this instrumentation can meet the current limitations of GIS technology, and
offers a new stage of rapprochement between the earth and its abstraction. As
result, the current research work proposes a new concept we named Smart
Geographic Object SGO. The latter is a convergence point between the smart
objects and geographic objects, two concepts appertaining respectively to
A Deep Search Architecture for Capturing Product Ontologies
This thesis describes a method to populate very large product ontologies quickly. We discuss a deep search architecture to text-mine online e-commerce market places and build a taxonomy of products and their corresponding descriptions and parent categories. The goal is to automatically construct an open database of products, which are aggregated from different online retailers. The database contains extensive metadata on each object, which can be queried and analyzed. Such a public database currently does not exist; instead the information currently resides siloed within various organizations. In this thesis, we describe the tools, data structures and software architectures that allowed aggregating, structuring, storing and searching through several gigabytes of product ontologies and their associated metadata. We also describe solutions to some computational puzzles in trying to mine data on large scale. We implemented the product capture architecture and, using this implementation, we built product ontologies corresponding to two major retailers: Wal-Mart and Target. The ontology data is analyzed to explore structural complexity and similarities and differences between the retailers. A broad product ontology has several uses, from comparison shopping applications that already exist to situation aware computing of tomorrow where computers are aware of the objects in their surroundings and these objects interact together to help humans in everyday tasks
Ontology-based Activity Recognition Framework and Services
This paper introduces an ontology-based integrated framework for activity modeling, activity recognition and activity model evolution. Central to the framework is ontological activity modeling and semantic-based activity recognition, which is supported by an iterative process that incrementally improves the completeness and accuracy of activity models. In addition, the paper presents a service-oriented architecture for the realization of the proposed framework which can provide activity context-aware services in a scalable distributed manner. The paper further describes and discusses the implementation and testing experience of the framework and services in the context of smart home based assistive living
CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap
After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in
multimedia search engines, we have identified and analyzed gaps within European research effort during our second year.
In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio-
economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown
of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on
requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the
community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our
Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as
National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core
technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research
challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal
challenges
Propelling the Potential of Enterprise Linked Data in Austria. Roadmap and Report
In times of digital transformation and considering the potential of the data-driven
economy, it is crucial that data is not only made available, data sources can be trusted,
but also data integrity can be guaranteed, necessary privacy and security mechanisms
are in place, and data and access comply with policies and legislation. In many cases,
complex and interdisciplinary questions cannot be answered by a single dataset and
thus it is necessary to combine data from multiple disparate sources. However, because
most data today is locked up in isolated silos, data cannot be used to its fullest
potential.
The core challenge for most organisations and enterprises in regards to data exchange
and integration is to be able to combine data from internal and external data sources
in a manner that supports both day to day operations and innovation. Linked Data is a
promising data publishing and integration paradigm that builds upon standard web
technologies. It supports the publishing of structured data in a semantically explicit
and interlinked manner such that it can be easily connected, and consequently becomes
more interoperable and useful.
The PROPEL project - Propelling the Potential of Enterprise Linked Data in Austria - surveyed technological challenges, entrepreneurial opportunities, and open research
questions on the use of Linked Data in a business context and developed a roadmap and a set of recommendations for policy makers, industry, and the research community.
Shifting away from a predominantly academic perspective and an exclusive focus on open data, the project looked at Linked Data as an emerging disruptive technology
that enables efficient enterprise data management in the rising data economy. Current market forces provide many opportunities, but also present several data and
information management challenges. Given that Linked Data enables advanced analytics and decision-making, it is particularly suitable for addressing today's data and
information management challenges. In our research, we identified a variety of highly promising use cases for Linked Data in an enterprise context. Examples of promising
application domains include "customization and customer relationship management", "automatic and dynamic content production, adaption and display", "data search, information
retrieval and knowledge discovery", as well as "data and information exchange and integration". The analysis also revealed broad potential across a large spectrum of
industries whose structural and technological characteristics align well with Linked
Data characteristics and principles: energy, retail, finance and insurance, government, health, transport and logistics, telecommunications, media, tourism, engineering, and research and development rank among the most promising industries for the adoption of Linked Data principles.
In addition to approaching the subject from an industry perspective, we also examined the topics and trends emerging from the research community in the field of Linked Data and the Semantic Web. Although our analysis revolved around a vibrant and active community composed of academia and leading companies involved in semantic technologies, we found that industry needs and research discussions are
somewhat misaligned. Whereas some foundation technologies such as knowledge representation and data creation/publishing/sharing, data management and system
engineering are highly represented in scientific papers, specific topics such as recommendations, or cross-topics such as machine learning or privacy and security are marginally
present. Topics such as big/large data and the internet of things are (still) on an
upward trajectory in terms of attention. In contrast, topics that are very relevant for
industry such as application oriented topics or those that relate to security, privacy
and robustness are not attracting much attention. When it comes to standardisation
efforts, we identified a clear need for a more in-depth analysis into the effectiveness of
existing standards, the degree of coverage they provide with respect the foundations
they belong to, and the suitability of alternative standards that do not fall under the
core Semantic Web umbrella.
Taking into consideration market forces, sector analysis of Linked Data potential, demand
side analysis and the current technological status it is clear that Linked Data
has a lot of potential for enterprises and can act as a key driver of technological, organizational,
and economic change. However, in order to ensure a solid foundation
for Enterprise Linked Data include there is a need for: greater awareness surrounding
the potential of Linked Data in enterprises, lowering of entrance barriers via education
and training, better alignment between industry demands and research activities,
greater support for technology transfer from universities to companies.
The PROPEL roadmap recommends concrete measures in order to propel the adoption
of Linked Data in Austrian enterprises. These measures are structured around five
fields of activities: "awareness and education", "technological innovation, research gaps,
standardisation", "policy and legal", and "funding". Key short-term recommendations include the clustering of existing activities in order to raise visibility on an international level, the funding of key topics that are under represented by the community, and the setup of joint projects. In the medium term, we recommend the strengthening
of existing academic and private education efforts via certification and to establish flagship projects that are based on national use cases that can serve as blueprints for transnational initiatives. This requires not only financial support, but also infrastructure support, such as data and services to build solutions on top. In the long term, we
recommend cooperation with international funding schemes to establish and foster a European level agenda, and the setup of centres of excellence
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