1,151 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
2023-2024 Catalog
The 2023-2024 Governors State University Undergraduate and Graduate Catalog is a comprehensive listing of current information regarding:Degree RequirementsCourse OfferingsUndergraduate and Graduate Rules and Regulation
Image-based Decision Support Systems: Technical Concepts, Design Knowledge, and Applications for Sustainability
Unstructured data accounts for 80-90% of all data generated, with image data contributing its largest portion. In recent years, the field of computer vision, fueled by deep learning techniques, has made significant advances in exploiting this data to generate value. However, often computer vision models are not sufficient for value creation. In these cases, image-based decision support systems (IB-DSSs), i.e., decision support systems that rely on images and computer vision, can be used to create value by combining human and artificial intelligence. Despite its potential, there is only little work on IB-DSSs so far.
In this thesis, we develop technical foundations and design knowledge for IBDSSs and demonstrate the possible positive effect of IB-DSSs on environmental sustainability. The theoretical contributions of this work are based on and evaluated in a series of artifacts in practical use cases: First, we use technical experiments to demonstrate the feasibility of innovative approaches to exploit images for IBDSSs.
We show the feasibility of deep-learning-based computer vision and identify future research opportunities based on one of our practical use cases. Building on this, we develop and evaluate a novel approach for combining human and artificial intelligence for value creation from image data. Second, we develop design knowledge that can serve as a blueprint for future IB-DSSs. We perform two design science research studies to formulate generalizable principles for purposeful design — one for IB-DSSs and one for the subclass of image-mining-based decision support systems (IM-DSSs). While IB-DSSs can provide decision support based on single images, IM-DSSs are suitable when large amounts of image data are available and required for decision-making. Third, we demonstrate the viability of applying IBDSSs to enhance environmental sustainability by performing life cycle assessments for two practical use cases — one in which the IB-DSS enables a prolonged product lifetime and one in which the IB-DSS facilitates an improvement of manufacturing processes.
We hope this thesis will contribute to expand the use and effectiveness of imagebased decision support systems in practice and will provide directions for future research
Tradition and Innovation in Construction Project Management
This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings
Towards an integrated vulnerability-based approach for evaluating, managing and mitigating earthquake risk in urban areas
Tese de doutoramento em Civil EngineeringSismos de grande intensidade, como aqueles que ocorreram na Turquía-Síria (2023) ou México (2017)
deviam chamar a atenção para o projeto e implementação de ações proativas que conduzam à identificação
de bens vulneráveis. A presente tese propõe um fluxo de trabalho relativamente simples para
efetuar avaliações da vulnerabilidade sísmica à escala urbana mediante ferramentas digitais. Um modelo
de vulnerabilidade baseado em parâmetros é adotado devido à afinidade que possui com o Catálogo Nacional
de Monumentos Históricos mexicano. Uma primeira implementação do método (a grande escala)
foi efetuada na cidade histórica de Atlixco (Puebla, México), demonstrando a sua aplicabilidade e algumas
limitações, o que permitiu o desenvolvimento de uma estratégia para quantificar e considerar as incertezas
epistémicas encontradas nos processos de aquisição de dados. Devido ao volume de dados tratado, foi
preciso desenvolver meios robustos para obter, armazenar e gerir informações. O uso de Sistemas de
Informação Geográfica, com programas à medida baseados em linguagem Python e a distribuição de
ficheiros na ”nuvem”, facilitou a criação de bases de dados de escala urbana para facilitar a aquisição de
dados em campo, os cálculos de vulnerabilidade e dano e, finalmente, a representação dos resultados.
Este desenvolvimento foi a base para um segundo conjunto de trabalhos em municípios do estado de
Morelos (México). A caracterização da vulnerabilidade sísmica de mais de 160 construções permitiu a
avaliação da representatividade do método paramétrico pela comparação entre os níveis de dano teórico
e os danos observados depois do terramoto de Puebla-Morelos (2017). Esta comparação foi a base para
efetuar processos de calibração e ajuste assistidos por algoritmos de aprendizagem de máquina (Machine
Learning), fornecendo bases para o desenvolvimento de modelos de vulnerabilidade à medida (mediante
o uso de Inteligência Artificial), apoiados nas evidências de eventos sísmicos prévios.Strong seismic events like the ones of Türkiye-Syria (2023) or Mexico (2017) should guide our attention
to the design and implementation of proactive actions aimed to identify vulnerable assets. This work is
aimed to propose a suitable and easy-to-implement workflow for performing large-scale seismic vulnerability
assessments in historic environments by means of digital tools. A vulnerability-oriented model based
on parameters is adopted given its affinity with the Mexican Catalogue of Historical Monuments. A first
large-scale implementation of this method in the historical city of Atlixco (Puebla, Mexico) demonstrated its
suitability and some limitations, which lead to develop a strategy for quantifying and involving the epistemic
uncertainties found during the data acquisition process. Given the volume of data that these analyses involve,
it was necessary to develop robust data acquisition, storing and management strategies. The use
of Geographical Information System environments together with customised Python-based programs and
cloud-based distribution permitted to assemble urban databases for facilitating field data acquisition, performing
vulnerability and damage calculations, and representing outcomes. This development was the
base for performing a second large-scale assessment in selected municipalities of the state of Morelos
(Mexico). The characterisation of the seismic vulnerability of more than 160 buildings permitted to assess
the representativeness of the parametric vulnerability approach by comparing the theoretical damage estimations against the damages observed after the Puebla-Morelos 2017 Earthquakes. Such comparison is
the base for performing a Machine Learning assisted process of calibration and adjustment, representing
a feasible strategy for calibrating these vulnerability models by using Machine-Learning algorithms and the
empirical evidence of damage in post-seismic scenarios.This work was partly financed by FCT/MCTES through national funds (PIDDAC) under the R&D Unit
Institute for Sustainability and Innovation in Structural Engineering (ISISE), reference UIDB/04029/2020.
This research had financial support provided by the Portuguese Foundation of Science and Technology
(FCT) through the Analysis and Mitigation of Risks in Infrastructures (InfraRisk) program under the PhD
grant PD/BD/150385/2019
Automatic Generation of Personalized Recommendations in eCoaching
Denne avhandlingen omhandler eCoaching for personlig livsstilsstøtte i sanntid ved bruk av informasjons- og kommunikasjonsteknologi. Utfordringen er å designe, utvikle og teknisk evaluere en prototyp av en intelligent eCoach som automatisk genererer personlige og evidensbaserte anbefalinger til en bedre livsstil. Den utviklede løsningen er fokusert på forbedring av fysisk aktivitet. Prototypen bruker bærbare medisinske aktivitetssensorer. De innsamlede data blir semantisk representert og kunstig intelligente algoritmer genererer automatisk meningsfulle, personlige og kontekstbaserte anbefalinger for mindre stillesittende tid. Oppgaven bruker den veletablerte designvitenskapelige forskningsmetodikken for å utvikle teoretiske grunnlag og praktiske implementeringer. Samlet sett fokuserer denne forskningen på teknologisk verifisering snarere enn klinisk evaluering.publishedVersio
Digital agriculture: research, development and innovation in production chains.
Digital transformation in the field towards sustainable and smart agriculture. Digital agriculture: definitions and technologies. Agroenvironmental modeling and the digital transformation of agriculture. Geotechnologies in digital agriculture. Scientific computing in agriculture. Computer vision applied to agriculture. Technologies developed in precision agriculture. Information engineering: contributions to digital agriculture. DIPN: a dictionary of the internal proteins nanoenvironments and their potential for transformation into agricultural assets. Applications of bioinformatics in agriculture. Genomics applied to climate change: biotechnology for digital agriculture. Innovation ecosystem in agriculture: Embrapa?s evolution and contributions. The law related to the digitization of agriculture. Innovating communication in the age of digital agriculture. Driving forces for Brazilian agriculture in the next decade: implications for digital agriculture. Challenges, trends and opportunities in digital agriculture in Brazil
Security and Privacy for Modern Wireless Communication Systems
The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
Machine Learning Algorithm for the Scansion of Old Saxon Poetry
Several scholars designed tools to perform the automatic scansion of poetry in many languages, but none of these tools
deal with Old Saxon or Old English. This project aims to be a first attempt to create a tool for these languages. We
implemented a Bidirectional Long Short-Term Memory (BiLSTM) model to perform the automatic scansion of Old Saxon
and Old English poems. Since this model uses supervised learning, we manually annotated the Heliand manuscript, and
we used the resulting corpus as labeled dataset to train the model. The evaluation of the performance of the algorithm
reached a 97% for the accuracy and a 99% of weighted average for precision, recall and F1 Score. In addition, we tested
the model with some verses from the Old Saxon Genesis and some from The Battle of Brunanburh, and we observed that
the model predicted almost all Old Saxon metrical patterns correctly misclassified the majority of the Old English input
verses
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