4,375 research outputs found

    UMSL Bulletin 2023-2024

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    The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp

    2023-2024 Boise State University Undergraduate Catalog

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    This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State

    Assessment of the accuracy in the alignment of the extremity and positioning of implants in total knee arthroplasties

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    Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2022-2023. Tutor/Director: Segur Vilalta, Josep Maria ; Martínez Pastor, Juan Carlos, Balaguer Castro, MarianoOsteoarthritis is the most frequent diagnosis of arthritis that requires for a Total Knee Replacement (TKA). This disease is characterised by a slowly degeneration of the cartilage within a joint causing pain, stiffness and swelling. TKA surgery consists of the resection of the affected joint surfaces, so they can be replaced by metal and polyethylene biomaterials (which reproduce the knee anatomy and function). Due to the variety of results between surgeries, an interest in assistive robotic technologies to standardize the procedure and more accurately place and align the implant with the limb has increased. This thesis explains the realisation of an unicentric prospective cohort study that examines the accuracy of ROSA Knee System (Robotic Surgical Assistant) a surgical robot to assist and support surgeons during TKA achieved by Hospital Clinic recently. To study this feature, certain variables have been recorded intraoperatively by ROSA and compared with the same variables but extracted from Computed Tomography (CT) or X-Ray (XR) postoperative images. All the phases to conduct, from scratch, the clinical study are explained in detail in this project. This project has been carried out under the supervision of the Knee Department of the Clinic hospital, which has allowed the use of data from their patients and their inclusion as participants in the study. This thesis will be attached to an extensive study conducted by the Knee Department regarding the ROSA robot that tries to answer the question: is the robotic assistance an improvement in TKAs surgeries

    Development of linguistic linked open data resources for collaborative data-intensive research in the language sciences

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    Making diverse data in linguistics and the language sciences open, distributed, and accessible: perspectives from language/language acquistiion researchers and technical LOD (linked open data) researchers. This volume examines the challenges inherent in making diverse data in linguistics and the language sciences open, distributed, integrated, and accessible, thus fostering wide data sharing and collaboration. It is unique in integrating the perspectives of language researchers and technical LOD (linked open data) researchers. Reporting on both active research needs in the field of language acquisition and technical advances in the development of data interoperability, the book demonstrates the advantages of an international infrastructure for scholarship in the field of language sciences. With contributions by researchers who produce complex data content and scholars involved in both the technology and the conceptual foundations of LLOD (linguistics linked open data), the book focuses on the area of language acquisition because it involves complex and diverse data sets, cross-linguistic analyses, and urgent collaborative research. The contributors discuss a variety of research methods, resources, and infrastructures. Contributors Isabelle Barrière, Nan Bernstein Ratner, Steven Bird, Maria Blume, Ted Caldwell, Christian Chiarcos, Cristina Dye, Suzanne Flynn, Claire Foley, Nancy Ide, Carissa Kang, D. Terence Langendoen, Barbara Lust, Brian MacWhinney, Jonathan Masci, Steven Moran, Antonio Pareja-Lora, Jim Reidy, Oya Y. Rieger, Gary F. Simons, Thorsten Trippel, Kara Warburton, Sue Ellen Wright, Claus Zin

    DCNFIS: Deep Convolutional Neuro-Fuzzy Inference System

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    A key challenge in eXplainable Artificial Intelligence is the well-known tradeoff between the transparency of an algorithm (i.e., how easily a human can directly understand the algorithm, as opposed to receiving a post-hoc explanation), and its accuracy. We report on the design of a new deep network that achieves improved transparency without sacrificing accuracy. We design a deep convolutional neuro-fuzzy inference system (DCNFIS) by hybridizing fuzzy logic and deep learning models and show that DCNFIS performs as accurately as three existing convolutional neural networks on four well-known datasets. We furthermore that DCNFIS outperforms state-of-the-art deep fuzzy systems. We then exploit the transparency of fuzzy logic by deriving explanations, in the form of saliency maps, from the fuzzy rules encoded in DCNFIS. We investigate the properties of these explanations in greater depth using the Fashion-MNIST dataset

    MethOds and tools for comprehensive impact Assessment of the CCAM solutions for passengers and goods. D1.1: CCAM solutions review and gaps

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    Review of the state-of-the-art on Cooperative, Connected and Automated mobility use cases, scenarios, business models, Key Performance Indicators, impact evaluation methods, technologies, and user needs (for organisations & citizens)

    LIPIcs, Volume 274, ESA 2023, Complete Volume

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    LIPIcs, Volume 274, ESA 2023, Complete Volum

    Sociological analysis of state capacity in the South African social security agency’s special CoVID-19 social relief of distress grant

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    Dissertation (MSocSci)--University of Pretoria, 2023.South Africa’s national response to the advent of the CoVID-19 pandemic included government’s announcement of the “extraordinary coronavirus budget” of R500 billion that was aimed at cushioning society and the economy from the socio-economic hardships that accompanied the pandemic. Part of this national response included the implementation of the CoVID-19 Social Relief of Distress (SRD) grant by the South African Social Security Agency (SASSA) for beneficiaries who were unemployed and did not receive any other form of income. Given SASSA’s previous administration of the SRD programme for citizens or permanent residents who have insufficient means of livelihood, the responsibility to implement this grant rested with this agency. However, what remains unknown is how, in the context of intense, condensed and temporal shocks such as CoVID-19, the State decisively mobilised the capacity to implement the CoVID-19 SRD grant. In order to establish this, the research delved into the “opacity of the State social world” to demonstrate how the productive processes that arise from concrete and ongoing systems of social relations contested and influenced the meanings, configurations, choices and performance of State capacity under conditions of a covariate shock. An understanding of the social construction of State capacity is relevant to the National Development Plan’s aspiration of developing and implementing critical interventions that are required to build a State that is capable of realising the vision for 2030. Theoretically, the study is important for understanding how State institution-based social processes shape a State’s capacity to implement policy decisions. The study is an invitation to theorise the State during shocks. It draws on Granovetter’s (1985) concept of embeddedness and Migdal’s (2004) State-in-society framework. Methodologically, the question of how the State capacity to implement the CoVID-19 SRD grant was approached as a case for the period May 2020 to April 2021. Within case study, process tracing and abductive inference were applied alongside the insider researcher approach. Process tracing was applied to trace institutional processes through which the State’s capacity to implement the CoVID-19 SRD grant was developed. Data were collected with two qualitative research methods: document review and key informant interviews. The former entailed a systematic review of key informant-provided documents with the view to interpret and elicit their meanings and understandings of the study phenomena. On the other hand, key informant interviews were conducted with six officials that were assigned the role of key informant by their respective institutions owing to their in-depth knowledge and understanding of the research subject matter. Consequently, empirical knowledge on how the State capacity for the implementation of the CoVID-19 SRD grant was mobilised was developed. The collected data were analysed by applying abductive inference. The objective of applying abductive inference was to identify data that were beyond the study’s conceptual framework. This enabled the development and emergence of theoretically surprising explanations from within the CoVID-19 SRD grant as a case. The study’s key findings are that, firstly, the advent of CoVID-19 found a SASSA that was in the process of self-reconfiguration with the view to improve its institutional capabilities and effectiveness. Owing to this institutional confidence, SASSA withstood and rejected all the suggestions that the private sector should perform what this agency considered to be its core functions: the implementation of a cash transfer programme. Second, SASSA’s resistance of corporate creep in the implementation of the CoVID-19 SRD grant disrupted the interests of those State actors who sought to increase the role of the private sector in this grant. Ultimately, this activated the formation of typical as well as unlikely institutional relations and coalitions in support of SASSA’s overall leadership of the CoVID-19 SRD grant. Third, the State capacity for the implementation of the CoVID-19 SRD grant would not have decisively been mobilised outside of the intense, condensed and temporal shock that is the advent of CoVID-19. Fourth, it is doubtful if the State verifiably knows its capacity to implement its responses to covariate shocks. This was evident in the absence of knowing SASSA’s implementation capacity. Therefore, the extent to which practical efforts are being taken to measure, innovate and translate Cabinet’s priority that a State that has the necessary capacity, capabilities and institutions that can meet the needs of South Africans should be developed comes to question. Based on the study’s findings the following three recommendations are made: Firstly, policy needs to be mobilised to define and regulate the State-wide data environment for it to be useful in the eventuality of covariate shocks. Secondly, noting that into the foreseeable future every South African will experience one form of covariate shock or other practitioners in, for instance, disaster management and social protection need to innovate responses to covariate shocks. Lastly, further research can be conducted on diverse factors that relate to the implementation of the CoVID-19 SRD grant over the four iterations of its implementation: 2020—2024. Similar prospects are available for quantitative analyses of the extensive data that the CoVID-19 SRD grant collected on millions of applicants. Another prospective research area is conducting research on the State during times of shock. Lastly, this research opened opportunities for methodologists to conduct research on the experiences of State-based insider researchers as well as the factors that enable and constrain them.Department of Social DevelopmentSociologyMSocSciUnrestricte
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