1,753 research outputs found
Alʔilbīrī’s Book of the rational conclusions. Introduction, Critical Edition of the Arabic Text and Materials for the History of the Ḫawāṣṣic Genre in Early Andalus
[eng] The Book of the rational conclusions, written perhaps somewhen in the 10th c. by a physician from Ilbīrah (Andalus), is a multi-section medical pandect. The author brings together, from a diversity of sources, materials dealing with matters related to drug-handling, natural philosophy, therapeutics, medical applications of the specific properties of things, a regimen, and a dispensatory. This dissertation includes three different parts. First the transmission of the text, its contents, and its possible context are discussed. Then a critical edition of the Arabic text is offered. Last, but certainly not least, the subject of the specific properties is approached from several points of view. The analysis of Section III of the original book leads to an exploration of the early Andalusī assimilation of this epistemic tradition and to the establishment of a well-defined textual family in which our text must be inscribed. On the other hand, the concept itself of ‘specific property’ is often misconstrued and it is usually made synonymous to magic and superstition. Upon closer inspection, however, the alleged irrationality of the knowledge of these properties appears to be largely the result of anachronistic interpretation. As a complement of this particular research and as an illustration of the genre, a sample from an ongoing integral commentary on this section of the book is presented.[cat] El Llibre de les conclusions racionals d’un desconegut metge d’Ilbīrah (l’Àndalus) va ser compilat probablement durant la segona meitat del s. X. Es tracta d’un rudimentari però notablement complet kunnaix (un gènere epistèmic que és definit sovint com a ‘enciclopèdia mèdica’) en què l’autor aplega materials manllevats (sovint de manera literal i no-explícita) de diversos gèneres. El llibre obre amb una secció sobre apoteconomia (una mena de manual d’apotecaris) però se centra després en les diferents branques de la medicina. A continuació d’uns prolegòmens filosòfics l’autor copia, amb mínima adaptació lingüística, un tractat sencer de terapèutica, després un altre sobre les aplicacions mèdiques de les propietats específiques de les coses, una sèrie de fragments relacionats amb la dietètica (un règim en termes tradicionals) i, finalment, una col·lecció de receptes mèdiques. Cadascuna d’aquestes seccions mostren evidents lligams d’intertextualitat que apunten cap a una intensa activitat sintetitzadora de diverses tradicions aliades a la medicina a l’Àndalus califal. El text és, de fet, un magnífic objecte sobre el qual aplicar la metodologia de la crítica textual i de fonts. L’edició crítica del text incorpora la dimensió cronològica dins l’aparat, que esdevé així un element contextualitzador. Quant l’estudi de les fonts, si tot al llarg de la primera part d’aquesta tesi és només secundari, aquesta disciplina pren un protagonisme gairebé absolut en la tercera part, especialment en el capítol dedicat a l’anàlisi individual de cada passatge recollit en la secció sobre les propietats específiques de les coses
Hidden in the Cloud : Advanced Cryptographic Techniques for Untrusted Cloud Environments
In the contemporary digital age, the ability to search and perform operations on encrypted data has become increasingly important. This significance is primarily due to the exponential growth of data, often referred to as the "new oil," and the corresponding rise in data privacy concerns. As more and more data is stored in the cloud, the need for robust security measures to protect this data from unauthorized access and misuse has become paramount.
One of the key challenges in this context is the ability to perform meaningful operations on the data while it remains encrypted. Traditional encryption techniques, while providing a high level of security, render the data unusable for any practical purpose other than storage. This is where advanced cryptographic protocols like Symmetric Searchable Encryption (SSE), Functional Encryption (FE), Homomorphic Encryption (HE), and Hybrid Homomorphic Encryption (HHE) come into play. These protocols not only ensure the confidentiality of data but also allow computations on encrypted data, thereby offering a higher level of security and privacy.
The ability to search and perform operations on encrypted data has several practical implications. For instance, it enables efficient Boolean queries on encrypted databases, which is crucial for many "big data" applications. It also allows for the execution of phrase searches, which are important for many machine learning applications, such as intelligent medical data analytics. Moreover, these capabilities are particularly relevant in the context of sensitive data, such as health records or financial information, where the privacy and security of user data are of utmost importance.
Furthermore, these capabilities can help build trust in digital systems. Trust is a critical factor in the adoption and use of digital services. By ensuring the confidentiality, integrity, and availability of data, these protocols can help build user trust in cloud services. This trust, in turn, can drive the wider adoption of digital services, leading to a more inclusive digital society.
However, it is important to note that while these capabilities offer significant advantages, they also present certain challenges. For instance, the computational overhead of these protocols can be substantial, making them less suitable for scenarios where efficiency is a critical requirement. Moreover, these protocols often require sophisticated key management mechanisms, which can be challenging to implement in practice. Therefore, there is a need for ongoing research to address these challenges and make these protocols more efficient and practical for real-world applications.
The research publications included in this thesis offer a deep dive into the intricacies and advancements in the realm of cryptographic protocols, particularly in the context of the challenges and needs highlighted above.
Publication I presents a novel approach to hybrid encryption, combining the strengths of ABE and SSE. This fusion aims to overcome the inherent limitations of both techniques, offering a more secure and efficient solution for key sharing and access control in cloud-based systems. Publication II further expands on SSE, showcasing a dynamic scheme that emphasizes forward and backward privacy, crucial for ensuring data integrity and confidentiality. Publication III and Publication IV delve into the potential of MIFE, demonstrating its applicability in real-world scenarios, such as designing encrypted private databases and additive reputation systems. These publications highlight the transformative potential of MIFE in bridging the gap between theoretical cryptographic concepts and practical applications. Lastly, Publication V underscores the significance of HE and HHE as a foundational element for secure protocols, emphasizing its potential in devices with limited computational capabilities.
In essence, these publications not only validate the importance of searching and performing operations on encrypted data but also provide innovative solutions to the challenges mentioned. They collectively underscore the transformative potential of advanced cryptographic protocols in enhancing data security and privacy, paving the way for a more secure digital future
Planetary Hinterlands:Extraction, Abandonment and Care
This open access book considers the concept of the hinterland as a crucial tool for understanding the global and planetary present as a time defined by the lasting legacies of colonialism, increasing labor precarity under late capitalist regimes, and looming climate disasters. Traditionally seen to serve a (colonial) port or market town, the hinterland here becomes a lens to attend to the times and spaces shaped and experienced across the received categories of the urban, rural, wilderness or nature. In straddling these categories, the concept of the hinterland foregrounds the human and more-than-human lively processes and forms of care that go on even in sites defined by capitalist extraction and political abandonment. Bringing together scholars from the humanities and social sciences, the book rethinks hinterland materialities, affectivities, and ecologies across places and cultural imaginations, Global North and South, urban and rural, and land and water
Complex systems methods characterizing nonlinear processes in the near-Earth electromagnetic environment: recent advances and open challenges
Learning from successful applications of methods originating in statistical mechanics, complex systems science, or information theory in one scientific field (e.g., atmospheric physics or climatology) can provide important insights or conceptual ideas for other areas (e.g., space sciences) or even stimulate new research questions and approaches. For instance, quantification and attribution of dynamical complexity in output time series of nonlinear dynamical systems is a key challenge across scientific disciplines. Especially in the field of space physics, an early and accurate detection of characteristic dissimilarity between normal and abnormal states (e.g., pre-storm activity vs. magnetic storms) has the potential to vastly improve space weather diagnosis and, consequently, the mitigation of space weather hazards.
This review provides a systematic overview on existing nonlinear dynamical systems-based methodologies along with key results of their previous applications in a space physics context, which particularly illustrates how complementary modern complex systems approaches have recently shaped our understanding of nonlinear magnetospheric variability. The rising number of corresponding studies demonstrates that the multiplicity of nonlinear time series analysis methods developed during the last decades offers great potentials for uncovering relevant yet complex processes interlinking different geospace subsystems, variables and spatiotemporal scales
2017 GREAT Day Program
SUNY Geneseo’s Eleventh Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1011/thumbnail.jp
The Impact of Participatory Budgeting on Health and Well-Being: A Qualitative Case Study of a Deprived Community in London
Background
Participatory budgeting (PB) is a democratic innovation that enables residents to participate directly and collectively decide how to spend public money in their community. Research demonstrates PB improves social well-being through governance, citizens’ participation, empowerment, and improved democracy. Since 2000, PB has increasingly been used in the UK in community development approaches for improving health and well-being outcomes for people living in deprived communities. Yet little is known about how and why PB may impact health and well-being in deprived communities of the UK. This PhD study sought to explore and explain how the application of PB in the Well London programme impacted the health and well-being of people living in a deprived community in London.
Methods
The study employed a qualitative case study design adopting the constructivist grounded theory (CGT) methodology of Charmaz (2006) to explore critical themes from interviews with stakeholders of the Well London programme in Haringey Borough. Forty-one stakeholders engaged in planning, co-designing, co-commissioning and co-delivering, or benefitted from three interventions commissioned through PB participated in this study between March 2017 and April 2018.
Results
A cross-case analysis revealed six pathways through which PB improved health, particularly for the underserved. PB maximised participation and meaningful engagement; enhanced direct demand and response to the community’s needs; individual and collective ownership; action on the social determinants of health; and creative partnership working. These pathways were moderated by the democratic and flexible approach of the PB ethos, particularly the inclusion of residents’ voices in the planning and delivery of the interventions. Residents were motivated to act as agents to change their lives by building positive relationships based on social inclusion and integration. As a result, residents’ self-esteem, sense of belonging, self-confidence, self-worth, and individual sense of belonging and community spirit increased. Residents gained a new zeal and agency to tackle the social determinants of health as they understood them in their lives.
Conclusion
When done correctly, PB can promote health and well-being and build more robust and resilient communities through community-centred democratic decision-making. Interventions should aim to increase critical consciousness, health literacy, and the capacity in deprived communities to tackle life-course issues that prevent residents from enjoying good health and reduce structural barriers to accessing services or interventions to improve health and reduce inequalities. The outcomes of this study have policy and practice implications for strengthening the design, commissioning, and delivery of health interventions in deprived communities of high-income countries
A review of technical factors to consider when designing neural networks for semantic segmentation of Earth Observation imagery
Semantic segmentation (classification) of Earth Observation imagery is a
crucial task in remote sensing. This paper presents a comprehensive review of
technical factors to consider when designing neural networks for this purpose.
The review focuses on Convolutional Neural Networks (CNNs), Recurrent Neural
Networks (RNNs), Generative Adversarial Networks (GANs), and transformer
models, discussing prominent design patterns for these ANN families and their
implications for semantic segmentation. Common pre-processing techniques for
ensuring optimal data preparation are also covered. These include methods for
image normalization and chipping, as well as strategies for addressing data
imbalance in training samples, and techniques for overcoming limited data,
including augmentation techniques, transfer learning, and domain adaptation. By
encompassing both the technical aspects of neural network design and the
data-related considerations, this review provides researchers and practitioners
with a comprehensive and up-to-date understanding of the factors involved in
designing effective neural networks for semantic segmentation of Earth
Observation imagery.Comment: 145 pages with 32 figure
Perceptions of Selves: Beyond the Skin Bag - Analyzing self-representation and ethos in creative digital artefacts
As technological innovations reach new heights, questions regarding how we act, see, and live with machines reveal themselves. What was once viewed as mere tools have become something we perceive as part of our social world. Technological actants now hold the power of persuasion, the power to be perceived as a self. This constitutes new perspectives regarding how we relate to those with self-representational qualities. Relations between actants in social settings boil down to discourse, where this study manifests itself. The point of entry is, paradoxically, taking root in ancient theories of rhetoric. Because self-representation in digital artefacts must necessarily be produced, it becomes a text with the potential for analysis. In its broadest possible meaning, text is a modal manifestation of existence, a textual manifestation of self. The representations are always mediated, and that mediation opens up questions about authenticity, agency, and ethos. The artefacts I propose in this thesis exist in a way that changes shape in the perception of those who perceive it. When artefacts are imbued with some form of life, uniqueness, personality and ethos, approaches and attentions must change. That is dependent on the relations we allow and instil in them. We now have different relations than before, which means that the concept of ethos must be seen anew. This thesis is a philosophical and rhetorical exploration of how ethos and self-representation can be renewed to encompass more ways of being. Through perspectives inspired by Posthumanism and Actor-Network Theory, I explore themes relating to self-representation and ethos to conceptualize an updated framework that, in essence, “de-anthropocentrize” our field of view. This thesis does not aim to be either final or limiting, but a starting point in opening a conversation about the rhetorical impact we encounter every day through humans and otherwise.Mastergradsoppgave i digital kulturDIKULT350MAHF-DIKU
Mobility classification of cattle with micro-Doppler radar
Lameness in dairy cattle is a welfare concern that negatively impacts animal productivity and farmer profitability. Micro-Doppler radar sensing has been previously suggested as a potential system for automating lameness detection in ruminants. This thesis investigates the refinement of the proposed automated system by analysing and enhancing the repeatability and accuracy of the existing scoring method in cattle mobility scoring, used to provide labels in machine learning. The main aims of the thesis were (1) to quantify the performance of the micro-Doppler radar sensing method for the assessment of mobility, (2) to characterise and validate micro-Doppler radar signatures of dairy cattle with varying degrees of gait impairment, and (3) to develop machine learning algorithms that can infer the mobility status of the animals under test from their radar signatures and support automatic contactless classification.
The first study investigated inter-assessor agreement using a 4-level system and modifications to it, as well as the impact of factors such as mobility scoring experience, confidence in scoring decisions, and video characteristics. The results revealed low levels of agreement between assessors' scores, with kappa values ranging from 0.16 to 0.53. However, after transforming and reducing the mobility scoring system levels, an improvement was observed, with kappa values ranging from 0.2 to 0.67. Subsequently, a longitudinal study was conducted using good-agreement scores as ground truth labels in supervised machine-learning models. However, the accuracy of the algorithmic models was found to be insufficient, ranging from 0.57 to 0.63. To address this issue, different labelling systems and data pre-processing techniques were explored in a cross-sectional study. Nonetheless, the inter-assessor agreement remained challenging, with an average kappa value of 0.37 (SD = 0.16), and high-accuracy algorithmic predictions remained elusive, with an average accuracy of 56.1 (SD =16.58). Finally, the algorithms' performance was tested with high-confidence labels, which consisted of only scores 0 and 3 of the AHDB system. This testing resulted in good classification accuracy (0.82), specificity (0.79), and sensitivity (0.85). This led to the proposal of a new approach to producing labels, testing vantage point changes, and improving the performance of machine learning models (average accuracy = 0.7 & SD = 0.17, average sensitivity = 0.68 & SD = 0.27, average specificity = 0.75 & SD = 0.17).
The research identified a challenge in creating high-confidence diagnostic labels for supervised machine learning-based algorithms to automate the detection and classification of lameness in dairy cows. As a result, the original goals were partially overridden, with the focus shifted to creating reliable labels that would perform well with radar data and machine learning. This point was considered necessary for smooth system development and process automation. Nevertheless, we managed to quantify the performance of the micro-Doppler radar system, partially develop the supervised machine learning algorithms, compare levels of agreement among multiple assessors, evaluate the assessment tools, assess the mobility evaluation process and gather a valuable data set which can be used as a foundation for subsequent studies. Finally, the thesis suggests changes in the assessment process to improve the prediction accuracy of algorithms based on supervised machine learning with radar data
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