Dissertationen zum Thema „Addressing Machines“
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Munnich, Nicolas. „Operational and categorical models of PCF : addressing machines and distributing semirings“. Electronic Thesis or Diss., Paris 13, 2024. http://www.theses.fr/2024PA131015.
Der volle Inhalt der QuelleDespite being introduced over 60 years ago, PCF remains of interest. Though the quest for a satisfactory fully abstract model of PCF was resolved around the turn of the millennium, new models of PCF still frequently appear in the literature, investigating unexplored avenues or using PCF as a lens or tool to investigate some other mathematical construct. In this thesis, we build upon our knowledge of models of PCF in two distinct ways: Constructing a brand new model, and building upon existing models. Addressing Machines are a relatively new type of abstract machine taking inspiration from Turing Machines. These machines have been previously shown to model the full untyped ?- calculus. We build upon these machines to construct Extended Addressing Machines (EAMs) and endow them with a type system. We then show that these machines can be used to obtain a new and distinct fully abstract model of PCF: We show that the machines faithfully simulatePCF in such a way that a PCF term terminates in a numeral exactly when the corresponding Extended Addressing Machine terminates in the same numeral. Likewise, we show that every typed Extended Addressing Machine can be transformed into a PCF program with the same observational behaviour. From these two results, it follows that the model of PCF obtained by quotienting typable EAMs by a suitable logical relation is fully abstract. There exist a plethora of sound categorical models of PCF, due to its close relationship with the ?-calculus. We consider two similar models (which are also models of Linear Logic) that are based on semirings: Weighted models, using semirings to quantify some internal value, and Multiplicity models, using semirings to linearly model functions (model the exponential !). We investigate the intersection between these two models by investigating the conditions under which two monads derived from specific semirings distribute. We discover that whether or not a semiring has an idempotent sum makes a large difference in its ability to distribute. Our investigation leads us to discover the notion of an unnatural distribution, which forms a monad on a Kleislicategory. Finally, we present precise conditions under which a particular distribution can form between two semirings
RICCI, FRANCESCO. „Effective Product Lifecycle Management: the role of uncertainties in addressing design, manufacturing and verification processes“. Doctoral thesis, Politecnico di Torino, 2012. http://hdl.handle.net/11583/2501694.
Der volle Inhalt der QuelleWang, Fulton. „Addressing two issues in machine learning : interpretability and dataset shift“. Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/122870.
Der volle Inhalt der QuelleCataloged from PDF version of thesis.
Includes bibliographical references (pages 71-77).
In this thesis, I create solutions to two problems. In the first, I address the problem that many machine learning models are not interpretable, by creating a new form of classifier, called the Falling Rule List. This is a decision list classifier where the predicted probabilities are decreasing down the list. Experiments show that the gain in interpretability need not be accompanied by a large sacrifice in accuracy on real world datasets. I then briefly discuss possible extensions that allow one to directly optimize rank statistics over rule lists, and handle ordinal data. In the second, I address a shortcoming of a popular approach to handling covariate shift, in which the training distribution and that for which predictions need to be made have different covariate distributions. In particular, the existing importance weighting approach to handling covariate shift suffers from high variance if the two covariate distributions are very different. I develop a dimension reduction procedure that reduces this variance, at the expense of increased bias. Experiments show that this tradeoff can be worthwhile in some situations.
by Fulton Wang.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
Vendra, Soujanya. „Addressing corner detection issues for machine vision based UAV aerial refueling“. Morgantown, W. Va. : [West Virginia University Libraries], 2006. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4551.
Der volle Inhalt der QuelleTitle from document title page. Document formatted into pages; contains xi, 121 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 90-95).
Heffernan, Rhys. „Addressing One-Dimensional Protein Structure Prediction Problems with Machine Learning Techniques“. Thesis, Griffith University, 2018. http://hdl.handle.net/10072/381401.
Der volle Inhalt der QuelleThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Eng & Built Env
Science, Environment, Engineering and Technology
Full Text
RAGONESI, RUGGERO. „Addressing Dataset Bias in Deep Neural Networks“. Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1069001.
Der volle Inhalt der QuelleAl-Shahib, Ali Walid. „Addressing the core challenges in predicting protein function from sequence using machine learning“. Thesis, University of Glasgow, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.425167.
Der volle Inhalt der QuelleRendleman, Michael. „Machine learning with the cancer genome atlas head and neck squamous cell carcinoma dataset: improving usability by addressing inconsistency, sparsity, and high-dimensionality“. Thesis, University of Iowa, 2019. https://ir.uiowa.edu/etd/6841.
Der volle Inhalt der QuelleMollen, Anne. „Addressing the ghost in the machine or “Is engagement a sustainable intermediate variable between the website drivers of consumer experience and consumers’ attitudinal and behavioural outputs?”“. Thesis, Cranfield University, 2007. http://hdl.handle.net/1826/2047.
Der volle Inhalt der QuelleKonishcheva, Kseniia. „Novel strategies for identifying and addressing mental health and learning disorders in school-age children“. Electronic Thesis or Diss., Université Paris Cité, 2023. http://www.theses.fr/2023UNIP7083.
Der volle Inhalt der QuelleThe prevalence of mental health and learning disorders in school-age children is a growing concern. Yet, a significant delay exists between the onset of symptoms and referral for intervention, contributing to long-term challenges for affected children. The current mental health system is fragmented, with teachers possessing valuable insights into their students' well-being but limited knowledge of mental health, while clinicians often only encounter more severe cases. Inconsistent implementation of existing screening programs in schools, mainly due to resource constraints, suggests the need for more effective solutions. This thesis presents two novel approaches for improvement of mental health and learning outcomes of children and adolescents. The first approach uses data-driven methods, leveraging the Healthy Brain Network dataset which contains item-level responses from over 50 assessments, consensus diagnoses, and cognitive task scores from thousands of children. Using machine learning techniques, item subsets were identified to predict common mental health and learning disability diagnoses. The approach demonstrated promising performance, offering potential utility for both mental health and learning disability detection. Furthermore, our approach provides an easy-to-use starting point for researchers to apply our method to new datasets. The second approach is a framework aimed at improving the mental health and learning outcomes of children by addressing the challenges faced by teachers in heterogeneous classrooms. This framework enables teachers to create tailored teaching strategies based on identified needs of individual students, and when necessary, suggest referral to clinical care. The first step of the framework is an instrument designed to assess each student's well-being and learning profile. FACETS is a 60-item scale built through partnerships with teachers and clinicians. Teacher acceptance and psychometric properties of FACETS are investigated. Preliminary pilot study demonstrated overall acceptance of FACETS among teachers. In conclusion, this thesis presents a framework to bridge the gap in detection and support of mental health and learning disorders in school-age children. Future studies will further validate and refine our tools, offering more timely and effective interventions to improve the well-being and learning outcomes of children in diverse educational settings
Jiang, Yingwei, und 江盈緯. „A Study on the Addressing Issue in 3GPP Machine Type Communications“. Thesis, 2012. http://ndltd.ncl.edu.tw/handle/48158187681165993681.
Der volle Inhalt der Quelle國立宜蘭大學
資訊工程研究所碩士班
100
Machine-to-Machine (M2M) communications also known as Machine Type Communications (MTC) are widely discussed in the 3rd Generation Partnership Project (3GPP). One of the key issues for MTC is the IP addressing issue. The Internet Protocol version 6 (IPv6) is preferred to adopt in MTC, however the Internet Protocol version 4 (IPv4) addresses are currently used in Internet environments. Since MTC requires large number of network addresses to identify the trillions of M2M devices, Network Address Translation (NAT) are deployed when IPv4 is used. Thus, the NAT traversal problem should be resolved for MTC in 3GPP. In this thesis we first introduce the call flows of the IPv6 addressing solution and three NAT solutions defined in 3GPP TR 23.888. Three NAT solutions include the NAT Traversal through Tunneling (NATTT) solution, the Managed NAT solution and the Non-managed NAT solution. To improve the performance of the NAT solution, this thesis proposes an Enhanced Port Forwarding (EPF) mechanism. In the EPF mechanism, Packet Data Network Gateway (P-GW) assigns IP address to the MTC device and set up the mapping to NAT simultaneously. Therefore the EPF mechanism reduces the latency of binding setup and signal cost. In the end of this thesis, this thesis compares and evaluates the performance of the IPv6 and NAT solutions in term of the signaling cost and packet delivery
Chaw, Shaw Yi. „Addressing the brittleness of knowledge-based question-answering“. Thesis, 2009. http://hdl.handle.net/2152/ETD-UT-2009-12-580.
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Montgomery, Lloyd Robert Frank. „Escalation prediction using feature engineering: addressing support ticket escalations within IBM’s ecosystem“. Thesis, 2017. https://dspace.library.uvic.ca//handle/1828/8478.
Der volle Inhalt der QuelleGraduate
(9873176), Quang Dao. „Addressing the Recommender System Data Solicitation Problem with Engaging User Interfaces“. Thesis, 2020.
Den vollen Inhalt der Quelle findenWith autonomous systems bringing greater demand for user data, in some
applications, this also brings an opportunity to solicit data from users. To exploit this, a user
interface will need to be designed to coax the user into achieving system
goals, like data solicitation. One approach is to design a system to leverage
an already present tendency for people to socially interact with technology. In this thesis, I argue that such an approach would involve
incorporating interaction concepts that facilitate engagement into the design
of recommender system interfaces that will improve the likelihood of obtaining
data from users. To support this claim, I synthesize past work on
human-computer interaction and recommender systems to derive a framework to
guide scientific investigations into interface design concepts that will
address the data solicitation problem.
Bako, Abdulaziz Tijjani. „The Role of Social Workers in Addressing Patients' Unmet Social Needs in the Primary Care Setting“. Diss., 2021. http://hdl.handle.net/1805/25986.
Der volle Inhalt der QuelleUnmet social needs pose significant risk to both patients and healthcare organizations by increasing morbidity, mortality, utilization, and costs. Health care delivery organizations are increasingly employing social workers to address social needs, given the growing number of policies mandating them to identify and address their patients’ social needs. However, social workers largely document their activities using unstructured or semi-structured textual descriptions, which may not provide information that is useful for modeling, decision-making, and evaluation. Therefore, without the ability to convert these social work documentations into usable information, the utility of these textual descriptions may be limited. While manual reviews are costly, time-consuming, and require technical skills, text mining algorithms such as natural language processing (NLP) and machine learning (ML) offer cheap and scalable solutions to extracting meaningful information from large text data. Moreover, the ability to extract information on social needs and social work interventions from free-text data within electronic health records (EHR) offers the opportunity to comprehensively evaluate the outcomes specific social work interventions. However, the use of text mining tools to convert these text data into usable information has not been well explored. Furthermore, only few studies sought to comprehensively investigate the outcomes of specific social work interventions in a safety-net population. To investigate the role of social workers in addressing patients’ social needs, this dissertation: 1) utilizes NLP, to extract and categorize the social needs that lead to referral to social workers, and market basket analysis (MBA), to investigate the co-occurrence of these social needs; 2) applies NLP, ML, and deep learning techniques to extract and categorize the interventions instituted by social workers to address patients’ social needs; and 3) measures the effects of receiving a specific social work intervention type on healthcare utilization outcomes.
„Addressing the Variable Selection Bias and Local Optimum Limitations of Longitudinal Recursive Partitioning with Time-Efficient Approximations“. Doctoral diss., 2019. http://hdl.handle.net/2286/R.I.54792.
Der volle Inhalt der QuelleDissertation/Thesis
Doctoral Dissertation Psychology 2019