Alcuni abstract di articoli che trattano argomenti relativi all'eHealth

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Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory. International Journal of Telemedicine and Applications

Requirement volatility is an issue in software engineering in general, and in Web-based clinical applications in particular, which often originates from an incomplete knowledge of the domain of interest. With advances in the health science, many features and functionalities need to be added to, or removed from, existing software applications in the biomedical domain. At the same time, the increasing complexity of biomedical systems makes them more difficult to understand, and consequently it is more difficult to define their requirements, which contributes considerably to their volatility. In this paper, we present a novel agent-based approach for analyzing and managing volatile and dynamic requirements in an ontology-driven laboratory information management system (LIMS) designed for Web-based case reporting in medical mycology. The proposed framework is empowered with ontologies and formalized using category theory to provide a deep and common understanding of the functional and nonfunctional requirement hierarchies and their interrelations, and to trace the effects of a change on the conceptual framework.Comment: 36 Pages, 16 Figure

Dealing with uncertain entities in ontology alignment using rough sets

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Ontology alignment facilitates exchange of knowledge among heterogeneous data sources. Many approaches to ontology alignment use multiple similarity measures to map entities between ontologies. However, it remains a key challenge in dealing with uncertain entities for which the employed ontology alignment measures produce conflicting results on similarity of the mapped entities. This paper presents OARS, a rough-set based approach to ontology alignment which achieves a high degree of accuracy in situations where uncertainty arises because of the conflicting results generated by different similarity measures. OARS employs a combinational approach and considers both lexical and structural similarity measures. OARS is extensively evaluated with the benchmark ontologies of the ontology alignment evaluation initiative (OAEI) 2010, and performs best in the aspect of recall in comparison with a number of alignment systems while generating a comparable performance in precision

NLP and the Humanities: The Revival of an Old Liaison

This paper presents an overview of some\ud emerging trends in the application of NLP\ud in the domain of the so-called Digital Humanities\ud and discusses the role and nature\ud of metadata, the annotation layer that is so\ud characteristic of documents that play a role\ud in the scholarly practises of the humanities.\ud It is explained how metadata are the\ud key to the added value of techniques such\ud as text and link mining, and an outline is\ud given of what measures could be taken to\ud increase the chances for a bright future for\ud the old ties between NLP and the humanities.\ud There is no data like metadata

Semantic Ontologies for Complex Healthcare Structures: A Scoping Review

The healthcare environment is made up of highly complicated interactions between many technologies, activities, and people. Ensuring a solid communication between them is vital to ease the healthcare management. Semantic ontologies are knowledge representation tools that implement abstractions to fully describe a given topic in terms of subjects and relations. This scoping review aims to identify and analyse available ontologies which can depict all the available use-cases that describe the hospital environment in relation to the European project ODIN and its future expansion. The review has been conducted on the Scopus database on January 13th, 2023 using the PRISMA extensions for scoping reviews. Two reviewers screened 3,225 documents emerged from the database search. Further filtering led to a final set of 32 articles to be analysed for the results. A set of 34 ontologies extracted by the identified articles has been analysed and discussed as well. The results of this study will lead to the implementation of a common integrated ontology which could hold information about healthcare entities as well as their semantic relationships, strengthen data exchange and interconnections among people, devices and applications in an expanded scenario which include Internet of Things, robots and Artificial Intelligence

Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunities

In recent years, ubiquitous semantic Metaverse has been studied to revolutionize immersive cyber-virtual experiences for augmented reality (AR) and virtual reality (VR) users, which leverages advanced semantic understanding and representation to enable seamless, context-aware interactions within mixed-reality environments. This survey focuses on the intelligence and spatio-temporal characteristics of four fundamental system components in ubiquitous semantic Metaverse, i.e., artificial intelligence (AI), spatio-temporal data representation (STDR), semantic Internet of Things (SIoT), and semantic-enhanced digital twin (SDT). We thoroughly survey the representative techniques of the four fundamental system components that enable intelligent, personalized, and context-aware interactions with typical use cases of the ubiquitous semantic Metaverse, such as remote education, work and collaboration, entertainment and socialization, healthcare, and e-commerce marketing. Furthermore, we outline the opportunities for constructing the future ubiquitous semantic Metaverse, including scalability and interoperability, privacy and security, performance measurement and standardization, as well as ethical considerations and responsible AI. Addressing those challenges is important for creating a robust, secure, and ethically sound system environment that offers engaging immersive experiences for the users and AR/VR applications.Comment: 18 pages, 7 figures, 3 table

The Lexical Grid: Lexical Resources in Language Infrastructures

Language Resources are recognized as a central and strategic for the development of any Human Language Technology system and application product. they play a critical role as horizontal technology and have been recognized in many occasions as a priority also by national and spra-national funding a number of initiatives (such as EAGLES, ISLE, ELRA) to establish some sort of coordination of LR activities, and a number of large LR creation projects, both in the written and in the speech areas

A Review on Requirement of Wireless Sensor Network in Healthcare Applications

An assortment of uses depend on Wireless AdHoc and Sensor Networks (WASN) which has pulled in individuals from a wide number of regions demonstrating its utility extents from protection to farming, climate guaging to pre-fiasco discovery, geography to mineralogy, catastrophe alleviation frameworks to medicinal care, vehicle following to territory checking, and a considerable measure many. In the field of therapeutic sciences the uses of WASN are new however have left an incredible effect on the psyches of the two analysts and specialists. Medicinal determination and test examination like observing the patients, detecting exceptional and basic indications physically and rationally should be possible utilizing sensor systems for the therapeutic care. The potential restorative utilizations of WASN are 'Constant, nonstop patient observing', 'Home checking for interminable and elderly patients', 'Gathering of long haul databases of clinical information'. Alternate applications can be giving therapeutic supervision to individuals in remote zones and for detecting vast mischances, fires, fear based oppressor assaults and remote crucial sign checking facilitating the activity of specialists. In this paper we have attempted to make an overview of all the conceivable utilizations of WASN in the field of therapeutic Sciences

Semantic data integration and knowledge graph creation at scale

Contrary to data, knowledge is often abstract. Concrete knowledge can be achieved through the inclusion of semantics in the data models, highlighting the role of data integration. The massive growing number of data, in recent years, has promoted the demand for scaling up data management techniques; materializing data integration, a.k.a., knowledge graph creation falls in that category. In this thesis, we investigate efficient methods and techniques for materializing data integration. We formalize the process of materializing data integration. We formally define the characteristics of a materialized data integration system that merge the data operators and sources. Owing to this formalism, both layers of data integration, including data and schema-level integration, are formalized in the context of mapping assertions. We explore optimization opportunities for improving the materialization of data integration systems. We recognize three angles including intra/inter-mapping assertions from which the materialization can be improved. Accordingly, we propose source-based, mapping-based, and inter-mapping assertion groups of optimization techniques. We utilize our proposed techniques in three real-world projects. We illustrate how applying these optimization techniques contribute to meeting the objectives of the mentioned projects. Furthermore, we study the parameters impacting the performance of materialization of data integration. Relying on reported parameters and the presumably impacting parameters, we build four groups of testbeds. We empirically study the performances of these different testbeds in the presence and absence of our proposed techniques, in terms of execution time. We observe that the savings can be up to 75%. Lastly, we contribute to facilitating the process of declarative data integration system definition. We propose two data operation function signatures in Function Ontology (FnO). The first set of functions is designed to perform the task of entity alignment by resorting to an entity and relation linking tool. The second library consists of domain-specific functions to align genomic entities by harmonizing their representations. Finally, we introduce a tool equipped with a user interface to facilitate the process of defining declarative mapping rules by allowing users to explore the data sources and unified schema while defining their correspondences.Im Gegensatz zu den Daten ist das Wissen oft abstrakt. Konkretes Wissen kann durch die Einbeziehung von Semantik in die Datenmodelle erreicht werden, was die Rolle der Datenintegration unterstreicht. Die massiv wachsende Zahl von Daten hat in den letzten Jahren die Nachfrage nach einer Ausweitung der Datenverwaltungstechnikengef¨ordert; die materialisierende Datenintegration, auch bekannt als die Erstellung von Wissensgraphen, f¨allt in diese Kategorie. In dieser Arbeit untersuchen wir effiziente Methoden und Techniken zur Materialisierung der Datenintegration. Wir formalisieren den Prozess der Materialisierung der Datenintegration. Wir definieren formal die Eigenschaften eines materialisierten Datenintegrationssystems, so dass die Datenoperatoren und -quellen zusammengef¨uhrt werden. Dank dieses Formalismus werden beide Ebenen der Datenintegration, einschließlich der Integration auf Daten- und Schemaebene, im Kontext von Mapping-Assertions formalisiert. Wir untersuchen die Optimierungsm¨oglichkeiten zur Verbesserung der Materialisierung von Datenintegrationssystemen. Wir erkennen drei Gesichtspunkte, einschließlich Intra-/Inter-Mapping-Assertions, unter denen die Materialisierung verbessert werden kann. Dementsprechend schlagen wir quellenbasierte, mappingbasierte und inter-mapping Assertionsgruppen von Optimierungstechniken vor. Wir setzen die von uns vorgeschlagenen Techniken in drei Forschungsprojekte ein. Wir veranschaulichen, wie die Anwendung dieser Optimierungstechniken dazu beitr¨agt, die Ziele der genannten Projekte zu erreichen. Wir untersuchen die Parameter, die sich auf die Leistung der Materialisierung der Datenintegration auswirken. Auf der Grundlage der gemeldeten Parameter und der vermutlich ausschlaggebenden Parameter erstellen wir vier Gruppen von Testumgebungen. Wir untersuchen empirisch die Leistung dieser verschiedenen Testbeds mit und ohne die von uns vorgeschlagenen Techniken in Bezug auf die Ausf¨uhrungszeit. Wir stellen fest, dass die Einsparungen bis zu 75% betragen k¨onnen. Schließlich tragen wir zur Erleichterung des Prozesses der deklarativen Definition von Datenintegrationssystemen bei, indem wir zwei Funktionssignaturen f¨ur Datenoperationen in der Function Ontology (FnO) vorschlagen. Die erste Gruppe von Funktionen ist f¨ur die Aufgabe des Entit¨atsabgleichs konzipiert, w¨ahrend die zweite Bibliothek aus dom¨anenspezifischen Funktionen zum Abgleich genomischer Entit¨aten durch Harmonisierung ihrer Darstellungen besteht. Schließlich stellen wir ein Tool vor, das mit einer Benutzeroberfl¨ache ausgestattet ist, um den Prozess der Definition deklarativer Mapping-Regeln zu erleichtern, indem es den Benutzern erm¨oglicht, die Datenquellen und das einheitliche Schema zu erkunden