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Environmental performance measurement in arts and cultural organisations: exploring factors influencing organisational changes
Arts and Cultural Organisations (ACOs) have received significant attention over the last few years regarding their environmental performance. ACOs are often non-profit organisations, relying on government funding to implement various programmes to support societal development. Funding dependence can shift ACOs' focus from creating socio-cultural value to being more commercially driven. This paper explores factors influencing organisational changes in ACOs related to environmental performance measurement. Stakeholders in ACOs based in Nottingham, England, were interviewed and participated in a workshop to validate and collect additional data. Our research uncovered five interrelated factors that influence organisational change: the role of funding bodies; local policies and networks; organisational culture and leadership; lack of resources; and building proprietary-tenant relationships. This paper contributes to understanding ACOs responses to measuring environmental performance and the challenges they face as they move from measuring to implementation. Implications are explored for how funding is allocated and understood in terms of moving beyond merely measuring the carbon footprint of activities. ACOs' funding dependence indicates a focus on carbon measurement , omitting a more holistic approach towards the environment and sustainability
Exploration autonome et efficiente de chantiers miniers souterrains inconnus avec un drone filaire
Abstract: Underground mining stopes are often mapped using a sensor located at the end of a pole that the operator introduces into the stope from a secure area. The sensor emits laser beams that provide the distance to a detected wall, thus creating a 3D map. This produces shadow zones and a low point density on the distant walls. To address these challenges, a research team from the Université de Sherbrooke is designing a tethered drone equipped with a rotating LiDAR for this mission, thus benefiting from several points of view. The wired transmission allows for unlimited flight time, shared computing, and real-time communication. For compatibility with the movement of the drone after tether entanglements, the excess length is integrated into an onboard spool, contributing to the drone payload. During manual piloting, the human factor causes problems in the perception and comprehension of a virtual 3D environment, as well as the execution of an optimal mission. This thesis focuses on autonomous navigation in two aspects: path planning and exploration. The system must compute a trajectory that maps the entire environment, minimizing the mission time and respecting the maximum onboard tether length. Path planning using a Rapidly-exploring Random Tree (RRT) quickly finds a feasible path, but the optimization is computationally expensive and the performance is variable and unpredictable. Exploration by the frontier method is representative of the space to be explored and the path can be optimized by solving a Traveling Salesman Problem (TSP) but existing techniques for a tethered drone only consider the 2D case and do not optimize the global path. To meet these challenges, this thesis presents two new algorithms. The first one, RRT-Rope, produces an equal or shorter path than existing algorithms in a significantly shorter computation time, up to 70% faster than the next best algorithm in a representative environment. A modified version of RRT-connect computes a feasible path, shortened with a deterministic technique that takes advantage of previously added intermediate nodes. The second algorithm, TAPE, is the first 3D cavity exploration method that focuses on minimizing mission time and unwound tether length. On average, the overall path is 4% longer than the method that solves the TSP, but the tether remains under the allowed length in 100% of the simulated cases, compared to 53% with the initial method. The approach uses a 2-level hierarchical architecture: global planning solves a TSP after frontier extraction, and local planning minimizes the path cost and tether length via a decision function. The integration of these two tools in the NetherDrone produces an intelligent system for autonomous exploration, with semi-autonomous features for operator interaction. This work opens the door to new navigation approaches in the field of inspection, mapping, and Search and Rescue missions.La cartographie des chantiers miniers souterrains est souvent réalisée à l’aide d’un capteur situé au bout d’une perche que l’opérateur introduit dans le chantier, depuis une zone sécurisée. Le capteur émet des faisceaux laser qui fournissent la distance à un mur détecté, créant ainsi une carte en 3D. Ceci produit des zones d’ombres et une faible densité de points sur les parois éloignées. Pour relever ces défis, une équipe de recherche de l’Université de Sherbrooke conçoit un drone filaire équipé d’un LiDAR rotatif pour cette mission, bénéficiant ainsi de plusieurs points de vue. La transmission filaire permet un temps de vol illimité, un partage de calcul et une communication en temps réel. Pour une compatibilité avec le mouvement du drone lors des coincements du fil, la longueur excédante est intégrée dans une bobine embarquée, qui contribue à la charge utile du drone. Lors d’un pilotage manuel, le facteur humain entraîne des problèmes de perception et compréhension d’un environnement 3D virtuel, et d’exécution d’une mission optimale. Cette thèse se concentre sur la navigation autonome sous deux aspects : la planification de trajectoire et l’exploration. Le système doit calculer une trajectoire qui cartographie l’environnement complet, en minimisant le temps de mission et en respectant la longueur maximale de fil embarquée. La planification de trajectoire à l’aide d’un Rapidly-exploring Random Tree (RRT) trouve rapidement un chemin réalisable, mais l’optimisation est coûteuse en calcul et la performance est variable et imprévisible. L’exploration par la méthode des frontières est représentative de l’espace à explorer et le chemin peut être optimisé en résolvant un Traveling Salesman Problem (TSP), mais les techniques existantes pour un drone filaire ne considèrent que le cas 2D et n’optimisent pas le chemin global. Pour relever ces défis, cette thèse présente deux nouveaux algorithmes. Le premier, RRT-Rope, produit un chemin égal ou plus court que les algorithmes existants en un temps de calcul jusqu’à 70% plus court que le deuxième meilleur algorithme dans un environnement représentatif. Une version modifiée de RRT-connect calcule un chemin réalisable, raccourci avec une technique déterministe qui tire profit des noeuds intermédiaires préalablement ajoutés. Le deuxième algorithme, TAPE, est la première méthode d’exploration de cavités en 3D qui minimise le temps de mission et la longueur du fil déroulé. En moyenne, le trajet global est 4% plus long que la méthode qui résout le TSP, mais le fil reste sous la longueur autorisée dans 100% des cas simulés, contre 53% avec la méthode initiale. L’approche utilise une architecture hiérarchique à 2 niveaux : la planification globale résout un TSP après extraction des frontières, et la planification locale minimise le coût du chemin et la longueur de fil via une fonction de décision. L’intégration de ces deux outils dans le NetherDrone produit un système intelligent pour l’exploration autonome, doté de fonctionnalités semi-autonomes pour une interaction avec l’opérateur. Les travaux réalisés ouvrent la porte à de nouvelles approches de navigation dans le domaine des missions d’inspection, de cartographie et de recherche et sauvetage
Fairness-Aware Graph Neural Networks: A Survey
Graph Neural Networks (GNNs) have become increasingly important due to their
representational power and state-of-the-art predictive performance on many
fundamental learning tasks. Despite this success, GNNs suffer from fairness
issues that arise as a result of the underlying graph data and the fundamental
aggregation mechanism that lies at the heart of the large class of GNN models.
In this article, we examine and categorize fairness techniques for improving
the fairness of GNNs. Previous work on fair GNN models and techniques are
discussed in terms of whether they focus on improving fairness during a
preprocessing step, during training, or in a post-processing phase.
Furthermore, we discuss how such techniques can be used together whenever
appropriate, and highlight the advantages and intuition as well. We also
introduce an intuitive taxonomy for fairness evaluation metrics including
graph-level fairness, neighborhood-level fairness, embedding-level fairness,
and prediction-level fairness metrics. In addition, graph datasets that are
useful for benchmarking the fairness of GNN models are summarized succinctly.
Finally, we highlight key open problems and challenges that remain to be
addressed
Topic Modeling based text classification regarding Islamophobia using Word Embedding and Transformers Techniques
Islamophobia is a rising area of concern in the current era where Muslims face discrimination and receive negative perspectives towards their religion, Islam. Islamophobia is a type of racism that is being practiced by individuals, groups, and organizations worldwide. Moreover, the ease of access to social media platforms and their augmented usage has also contributed to spreading hate speech, false information, and negative opinions about Islam. In this research study, we focused to detect Islamophobic textual content shared on various social media platforms. We explored the state-of-the-art techniques being followed in text data mining and Natural Language Processing (NLP). Topic modelling algorithm Latent Dirichlet Allocation is used to find top topics. Then, word embedding approaches such as Word2Vec and Global Vectors for word representation (GloVe) are used as feature extraction techniques. For text classification, we utilized modern text analysis techniques of transformers-based Deep Learning algorithms named Bidirectional Encoders Representation from Transformers (BERT) and Generative Pre-Trained Transformer (GPT). For results comparison, we conducted an extensive empirical analysis of Machine Learning algorithms and Deep Learning using conventional textual features such as the Term Frequency-Inverse Document Frequency, N-gram, and Bag of words (BoW). The empirical based results evaluated using standard performance evaluation measures show that the proposed approach effectively detects the textual content related to Islamophobia. In the corpus of the study under Machine Learning models Support Vector Machine (SVM) performed best with an F1 score of 91%. The Transformer based core NLP models and the Deep Learning model Convolutional Neural Network (CNN) when combined with GloVe performed best among all the techniques except SVM with BoW. GPT, SVM when combined with BoW and BERT yielded the best F1 score of 92%, 92% and 91.9% respectively, while CNN performed slightly poor with an F1 score of 91%
The origins and early development of Copenhagen International School, 1962-1973
This thesis critically examines the origins and early development of Copenhagen International School (CIS, Denmark), which evolved from an American outpost secondary school, attached to the American embassy, to one of the first International Baccalaureate (IB) trial schools, in 1968. The case study places the school’s history in the Danish context of the mid-1960s and early 1970s, and in the wider international and geopolitical configurations of the same period. Using an insider approach, as a full member of the school, I apply a participative method which includes the role of school’s informants particularly in the preservation and the access to the data. By drawing on cross-analysis of the school unexplored records, donated materials, unofficial written histories and oral testimonies from alumni and staff members, the research addresses three questions:
1 What does the school’s early history reveal about the inception of international schooling in the mid-1960s and early 1970s?
2 Why and how did the foundation years of the school embody and reflect broader aspects and interests at stake in the world order?
3 What does the school’s early history unveil about its institutional identity?
The findings provide insights on the interplay and power games between multiple actors in a small international institution under a strong American influence where many interests were at stake. More specifically, it shows how the concept of internationalism embodied a range of different interpretations and had to be negotiated in the school day-to-day life between the different board members, students, parents, headmasters and teachers. Finally, the findings give evidence on the sensitive role and newly increasing power given to international schooling in the changing world order of the mid-twentieth century
Fairness Testing: A Comprehensive Survey and Analysis of Trends
Unfair behaviors of Machine Learning (ML) software have garnered increasing
attention and concern among software engineers. To tackle this issue, extensive
research has been dedicated to conducting fairness testing of ML software, and
this paper offers a comprehensive survey of existing studies in this field. We
collect 100 papers and organize them based on the testing workflow (i.e., how
to test) and testing components (i.e., what to test). Furthermore, we analyze
the research focus, trends, and promising directions in the realm of fairness
testing. We also identify widely-adopted datasets and open-source tools for
fairness testing
The effectiveness and determinants of effectiveness of antiretroviral therapy for adults in the Western Cape Province of South Africa
Antiretroviral therapy (ART) first became available in the public sector in the Western Cape Province in Khayelitsha in 2001. This thesis describes the effectiveness of ART in Khayelitsha and the Province, following adult patients for up to five years on ART, and examining temporal trends over seven years during which time the availability of ART in the Province increased dramatically. Associations are explored with a range of clinical outcomes, and regimen durability and tolerability are described, together with regimen effectiveness when ART is administered to patients co-infected with tuberculosis. The results chapters of the thesis are presented in the form of published or submitted papers. The first paper corrects for under-ascertainment of mortality through linkages with the death registry. After five years on ART, four out of five patients were still alive. Survival did not deteriorate in more recent years despite the large increase in patient numbers. Patients who remained virologically suppressed experienced on average continued CD4 count recovery throughout follow-up to five years. The second paper describes the tolerability of each commonly used first-line antiretroviral drug in two townships in the Western Cape. Treatment-limiting toxicities were frequent and continued throughout follow-up in patients on stavudine (21% by 3 years on ART). Symptomatic hyperlactataemia or lactic acidosis as well as lipodystrophy were strongly associated with women initiating ART with a high initial body mass. The third paper explores the effectiveness of ART when co-administered with tuberculosis treatment, identifying that co-infected patients initiating nevirapinebased ART may be at a higher risk of virological failure, but that concurrent tuberculosis treatment did not otherwise compromise ART outcomes. The fourth paper, based on a household survey, provides an in-depth description of the Khayelitsha population demonstrating comparability with many of the urban settings in which ART is provided in the region. The final paper demonstrates that outcomes have not been compromised by the wider availability of ART in the Western Cape Province. The thesis concludes that the Khayelitsha and Provincial analyses provide considerable reassurance that the anticipated benefits of ART have not to date been eroded by health system weaknesses or contextual challenges
Next Generation Business Ecosystems: Engineering Decentralized Markets, Self-Sovereign Identities and Tokenization
Digital transformation research increasingly shifts from studying information systems within organizations towards adopting an ecosystem perspective, where multiple actors co-create value. While digital platforms have become a ubiquitous phenomenon in consumer-facing industries, organizations remain cautious about fully embracing the ecosystem concept and sharing data with external partners. Concerns about the market power of platform orchestrators and ongoing discussions on privacy, individual empowerment, and digital sovereignty further complicate the widespread adoption of business ecosystems, particularly in the European Union.
In this context, technological innovations in Web3, including blockchain and other distributed ledger technologies, have emerged as potential catalysts for disrupting centralized gatekeepers and enabling a strategic shift towards user-centric, privacy-oriented next-generation business ecosystems. However, existing research efforts focus on decentralizing interactions through distributed network topologies and open protocols lack theoretical convergence, resulting in a fragmented and complex landscape that inadequately addresses the challenges organizations face when transitioning to an ecosystem strategy that harnesses the potential of disintermediation.
To address these gaps and successfully engineer next-generation business ecosystems, a comprehensive approach is needed that encompasses the technical design, economic models, and socio-technical dynamics. This dissertation aims to contribute to this endeavor by exploring the implications of Web3 technologies on digital innovation and transformation paths. Drawing on a combination of qualitative and quantitative research, it makes three overarching contributions:
First, a conceptual perspective on \u27tokenization\u27 in markets clarifies its ambiguity and provides a unified understanding of the role in ecosystems.
This perspective includes frameworks on: (a) technological; (b) economic; and (c) governance aspects of tokenization.
Second, a design perspective on \u27decentralized marketplaces\u27 highlights the need for an integrated understanding of micro-structures, business structures, and IT infrastructures in blockchain-enabled marketplaces. This perspective includes: (a) an explorative literature review on design factors; (b) case studies and insights from practitioners to develop requirements and design principles; and (c) a design science project with an interface design prototype of blockchain-enabled marketplaces.
Third, an economic perspective on \u27self-sovereign identities\u27 (SSI) as micro-structural elements of decentralized markets. This perspective includes: (a) value creation mechanisms and business aspects of strategic alliances governing SSI ecosystems; (b) business model characteristics adopted by organizations leveraging SSI; and (c) business model archetypes and a framework for SSI ecosystem engineering efforts.
The dissertation concludes by discussing limitations as well as outlining potential avenues for future research. These include, amongst others, exploring the challenges of ecosystem bootstrapping in the absence of intermediaries, examining the make-or-join decision in ecosystem emergence, addressing the multidimensional complexity of Web3-enabled ecosystems, investigating incentive mechanisms for inter-organizational collaboration, understanding the role of trust in decentralized environments, and exploring varying degrees of decentralization with potential transition pathways
Lisbon public parks: Development of real-world user scenarios
A população mundial está a aumentar. Até 2030, a população
mundial poderá atingir 8,6 mil milhões de pessoas. Nos dias
que correm, cerca de 53,9% da população mundial reside em
cidades. Até 2050 a previsão é que este número aumente para
68,4%. Ao mesmo tempo, prevĂŞ-se que a percentagem de
pessoas com mais de 60 anos aumente de 12% para 22%, e que
em paĂses este nĂşmero atinja 33%. Diversos estudos referem a
importância que parques públicos e espaços verdes têm na
contribuição para uma maior qualidade de vida e bem-estar.
O principal objetivo desta Tese Ă© compreender que tipo de
problemas existem nos parques pĂşblicos de Lisboa e perceber
como o design pode melhorar a experiĂŞncia do utilizador nos
parques públicos de Lisboa. Esta Tese está dividida em seis
capĂtulos: Introdução, Estado da arte, Metodologia de
investigação, Discussão, Cenários reais de utilizador e
ConclusĂŁo.
Os resultados deste trabalho reforçam a importância da
utilização de metodologias de Design Thinking e Design
participativo na reflexão e/ou reformulação de parques
públicos. Além disso, este trabalho destaca a importância de
entender o verdadeiro utilizador, visto que soluções não são
universais e precisam ser pensadas de acordo com a localização
de cada parque.
Esta Tese pretende inspirar novas ideias de investigação,
através da identificação de lacunas no conhecimento. Questões
abertas e desafiantes sobre novas soluções para parques
pĂşblicos sĂŁo propostas e identificadas para trabalhos futuros,
abrindo espaço para pensar em novas soluções que possam
contribuir para futuros parques públicos “inteligentes”.The global population is growing. By 2030, the world
population will reach 8.6 billion people. Nowadays, about
53.9% of the world's population resides in cities, and by
2050, the percentage is expected to rise to 68.4%. At the
same time, the percentage of people over 60 is expected to
rise from 12% to 22%, and 33% residing in developed
countries. Studies have shown that public parks and green
spaces can contribute to a higher quality of life and well being.
The main purpose of this study is to understand the type of
problems exist in Lisbon public parks and to speculate how
design and technology could improve the user experience at
Lisbon public parks. The thesis is divided into six chapters:
Introduction, State of the Art, Research Methodology,
Discussion, Real-world user scenarios, and Conclusion.
The findings of this study underscore the significance of
incorporating Design Thinking and participatory Design
approaches when conceptualizing or revitalizing public
parks. Additionally, this research underscores the necessity
of comprehending the specific park user demographic, as
solutions cannot be one-size-fits-all and must be tailored to
the park's unique context. The thesis aims to stimulate fresh
avenues of research by pinpointing knowledge gaps. It
presents forward-looking and formidable challenges in the
realm of innovative public park solutions for future
exploration. This paves the way for contemplating novel
approaches that can contribute to the evolution of “smart”
public parks in the future
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