Search results for " decision support system"

A multi-methodology and sustainability-supporting framework for implementation and assessment of a holistic building renovation

La ristrutturazione degli edifici in futuro dovrà essere condotta secondo una prospettiva più olistica legata alla sostenibilità vista in una più ampia gamma di obiettivi/criteri e facilitata dagli scenari di ristrutturazione possibili. La ristrutturazione degli edifici dovrebbe servire a migliorarne le performance al fine di soddisfare le esigenze degli utenti, rendendo questi ultimi meno vulnerabili in relazione ai futuri costi energetici. Vi è un grande potenziale per ridurre il consumo di energia negli edifici esistenti. Tuttavia, ciò non deve comprometterè i valori architettonici e di qualità che rendono particolari. Pertanto, non possono essere semplicemente rinnovati, ma devono subir…

eHealth Initiatives for The Promotion of Healthy Lifestyle and Allied Implementation Difficulties

2019

Research in eHealth has opened a new dimension to improve personal healthcare with the help of information and communication technologies (ICT). eHealth is an ‘umbrella term’ for the use of ICT for health. Remote care-giving technologies (mHealth, Telehealth, Telemedicine) are an extended branch of eHealth initiatives. The concept of health e- Coaching is another promising initiative of eHealth research for real-time personalized lifestyle support. The focus of eHealth initiatives is to deliver high quality, evidence-based, secure, cost- effective, timely care to support people for sustaining a healthy lifestyle. However, the practical implementation of different eHealth initiatives has oft…

HCI for biomedical decision-making: From diagnosis to therapy.

2020

Abstract Human-Computer Interaction (HCI) plays a fundamental role in the design of software oriented towards clinical decision-making tasks. Currently, physicians have to deal with an ensemble of systems and software tools in the clinical environment, such as clinical Decision Support Systems (CDSSs), Electronic Health Records (EHRs), Picture Archiving and Communication Systems (PACSs). Moreover, additional platforms aim at collaborative work particularly in telemedicine, where rehabilitation technologies and conversational agents can support the healthcare professionals.

An ontological-based knowledge organization for bioinformatics workflow management system

2012

Motivation and Objectives In the field of Computer Science, ontologies represent formal structures to define and organize knowledge of a specific application domain (Chandrasekaran et al., 1999). An ontology is composed of entities, called classes, and relationships among them. Classes are characterized by features, called attributes, and they can be arranged into a hierarchical organization. Ontologies are a fundamental instrument in Artificial Intelligence for the development of Knowledge-Based Systems (KBS). With its formal and well defined structure, in fact, an ontology provides a machine-understandable language that allows automatic reasoning for problems resolution. Typical KBS are E…

Demonstration of Semantic Web-based Medical Ontologies and Clinical Decision Support Systems

2016

Master's thesis in Information- and communication technology IKT590 - University of Agder 2016 Konfidensiell til / confidential until 01.01.2022

Ontology-based clinical decision support system applied on diabetes

2017

Master's thesis Information- and communication technology IKT590 - University of Agder 2017 Medical diagnosis is a multi-step process which is complex as it requires the consideration of many factors. Additionally, the accuracy of diagnosis varies depending on the skill and knowledge a physician has in the medical field. Using ICT solution, the physicians can be assisted so that they can make an accurate decision. Many applications have been developed to enhance physician performance and improve the patient outcome, however, the quality of these applications varies depending on knowledge representation methodology and reasoning approach adopted. Nowadays, ontology is being used in many clin…

Designing Ethical AI in the Shadow of Hume’s Guillotine

2020

Artificially intelligent systems can collect knowledge regarding epistemic information, but can they be used to derive new values? Epistemic information concerns facts, including how things are in the world, and ethical values concern how actions should be taken. The operation of artificial intelligence (AI) is based on facts, but it require values. A critical question here regards Hume’s Guillotine, which claims that one cannot derive values from facts. Hume’s Guillotine appears to divide AI systems into two ethical categories: weak and strong. Ethically weak AI systems can be applied only within given value rules, but ethically strong AI systems may be able to generate new values from fac…

A planning support system for assessing strategies of local urban planning agencies

2008

Here we present our research project, which aims to develop a new kind of planning support system (PSS). The PSS aims to analyse the urban planning process. An important part of the construction of the PSS is the development of a multi-agent simulation model of the urban planning process; the model will be based on the comparison of the planning systems of France, England and the Netherlands.

Big Data Metadata Management in Smart Grids

2014

Smart home, smart grids, smart museum, smart cities, etc. are making the vision for living in smart environments come true. These smart environments are built based upon the Internet of Things paradigm where many devices and applications are involved. In these environments, data are collected from various sources in diverse formats. The data are then processed by different intelligent systems with the purpose of providing efficient system planning, power delivery, and customer operations. Even though there are known technologies for most of these smart environments, putting them together to make intelligent and context-aware systems is not an easy task. The reason is that there are semantic…

Deep Learning for Resource-Limited Devices

2020

In recent years, deep neural networks have revolutionized the development of intelligent systems and applications in many areas. Despite their numerous advantages and potentials, these intelligent models still suffer from several issues. Among them, the fact that they became very complex with millions of parameters. That is, requiring more resources and time, and being unsuitable for small restricted devices. To contribute in this direction, this paper presents (1) some state-of-the-art lightweight architectures that were specifically designed for small-sized devices, and (2) some recent solutions that have been proposed to optimize/compress classical deep neural networks to allow their dep…