14,926 research outputs found

    Diffusion Schr\"odinger Bridge Matching

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    Solving transport problems, i.e. finding a map transporting one given distribution to another, has numerous applications in machine learning. Novel mass transport methods motivated by generative modeling have recently been proposed, e.g. Denoising Diffusion Models (DDMs) and Flow Matching Models (FMMs) implement such a transport through a Stochastic Differential Equation (SDE) or an Ordinary Differential Equation (ODE). However, while it is desirable in many applications to approximate the deterministic dynamic Optimal Transport (OT) map which admits attractive properties, DDMs and FMMs are not guaranteed to provide transports close to the OT map. In contrast, Schr\"odinger bridges (SBs) compute stochastic dynamic mappings which recover entropy-regularized versions of OT. Unfortunately, existing numerical methods approximating SBs either scale poorly with dimension or accumulate errors across iterations. In this work, we introduce Iterative Markovian Fitting, a new methodology for solving SB problems, and Diffusion Schr\"odinger Bridge Matching (DSBM), a novel numerical algorithm for computing IMF iterates. DSBM significantly improves over previous SB numerics and recovers as special/limiting cases various recent transport methods. We demonstrate the performance of DSBM on a variety of problems

    Strategies for Early Learners

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    Welcome to learning about how to effectively plan curriculum for young children. This textbook will address: • Developing curriculum through the planning cycle • Theories that inform what we know about how children learn and the best ways for teachers to support learning • The three components of developmentally appropriate practice • Importance and value of play and intentional teaching • Different models of curriculum • Process of lesson planning (documenting planned experiences for children) • Physical, temporal, and social environments that set the stage for children’s learning • Appropriate guidance techniques to support children’s behaviors as the self-regulation abilities mature. • Planning for preschool-aged children in specific domains including o Physical development o Language and literacy o Math o Science o Creative (the visual and performing arts) o Diversity (social science and history) o Health and safety • Making children’s learning visible through documentation and assessmenthttps://scholar.utc.edu/open-textbooks/1001/thumbnail.jp

    Image classification over unknown and anomalous domains

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    A longstanding goal in computer vision research is to develop methods that are simultaneously applicable to a broad range of prediction problems. In contrast to this, models often perform best when they are specialized to some task or data type. This thesis investigates the challenges of learning models that generalize well over multiple unknown or anomalous modes and domains in data, and presents new solutions for learning robustly in this setting. Initial investigations focus on normalization for distributions that contain multiple sources (e.g. images in different styles like cartoons or photos). Experiments demonstrate the extent to which existing modules, batch normalization in particular, struggle with such heterogeneous data, and a new solution is proposed that can better handle data from multiple visual modes, using differing sample statistics for each. While ideas to counter the overspecialization of models have been formulated in sub-disciplines of transfer learning, e.g. multi-domain and multi-task learning, these usually rely on the existence of meta information, such as task or domain labels. Relaxing this assumption gives rise to a new transfer learning setting, called latent domain learning in this thesis, in which training and inference are carried out over data from multiple visual domains, without domain-level annotations. Customized solutions are required for this, as the performance of standard models degrades: a new data augmentation technique that interpolates between latent domains in an unsupervised way is presented, alongside a dedicated module that sparsely accounts for hidden domains in data, without requiring domain labels to do so. In addition, the thesis studies the problem of classifying previously unseen or anomalous modes in data, a fundamental problem in one-class learning, and anomaly detection in particular. While recent ideas have been focused on developing self-supervised solutions for the one-class setting, in this thesis new methods based on transfer learning are formulated. Extensive experimental evidence demonstrates that a transfer-based perspective benefits new problems that have recently been proposed in anomaly detection literature, in particular challenging semantic detection tasks

    An investigation of the relationship between perioperative characteristics and perioperative anaesthesia on the postoperative systemic inflammatory response and clinical outcome in patients undergoing surgery for colorectal cancer

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    In UK, colorectal cancer (CRC) is the fourth most common cancer and the second most common cause of cancer death. Until now, surgical resection remains the cornerstone for the management of CRC in all stages, however, stress response elicit from surgery may cause different changes through multiple systems in human body including neural, endocrine, metabolic, inflammatory, and immunological changes. In addition, other perioperative factors such as volatile anaesthetic and opioids may induce the immunosuppression. There is a proportional correlation between the stress response and the magnitude of the inflammatory immune response, invasiveness, and duration of surgery. The pre-operative and post-operative status of patients are important when considering the prognosis. The systemic inflammatory response (SIR) has been recognised to correlate with tumour progression and the prognosis of CRC. An exaggerated postoperative SIR is associated with postoperative infective complications and poor survival. Several predictive markers of the SIR have been used, such as the neutrophil to lymphocyte ratio (NLR), serum C-reactive protein (CRP) level, and Glasgow prognostic score (GPS). Some evidence reported that general anaesthesia (GA) combined with regional anaesthesia (RA) are better than the single use of general anaesthesia in reducing the post-operative immuno-suppression in some degrees. Furthermore, the peri-operative inflammatory process may be affected by the choice of anaesthetic technique, with propofol reported to have anti-inflammatory effect by targeting neutrophil activity. Up to now, there is insufficient evidence to recommend any specific anaesthetic or analgesic technique for patients undergoing surgery for tumour resection based on inflammatory response, recurrence, and metastasis. The work presented in this thesis further examines the relationship between the perioperative characteristics, perioperative anaesthesia, and the postoperative systemic inflammatory response following surgery for colorectal cancer. Several preoperative medications along with anaesthesia might influence the postoperative systemic inflammatory response but the question is whether the post-operative systemic inflammatory response affected by the administration of different types of anaesthesia or not following surgery for colorectal cancer. Chapter 1 discusses the epidemiology, aetiology, carcinogenesis, risk factors of colorectal cancer, pro-carcinogenic factors, anti-carcinogenic agents, inflammation and cancer, the post-operative systemic inflammatory response, tumour staging, screening, and diagnosis of colorectal cancer. Chapter 2 discusses the treatment of colorectal cancer. Chapter 3 discusses different anaesthetic techniques and agents. Chapter 4 provides summary and aims of the thesis. Chapter 5 represents findings from a systematic review and meta-analysis about the effect of anaesthesia on the postoperative systemic inflammatory response in patients undergoing surgery. The results conclude that there was some evidence that anaesthetic regimens may reduce the magnitude of the post-operative SIR. However, the studies identified in this systematic review were heterogeneous and generally of low quality. Chapter 6 represents a retrospective cohort study about the relationship between anaesthetic technique, clinicopathological characteristics and the magnitude of the postoperative systemic inflammatory response in patients undergoing elective surgery for colon cancer. The results show that the type of anaesthesia varied over time and appears to influence the magnitude of the postoperative SIR on post-operative day 2 for those patients who underwent for open surgery but not laparoscopic surgery. Chapter 7 represents a prospective cohort study about the effect of anaesthesia on the magnitude of the postoperative systemic inflammatory response in patients undergoing elective surgery for colorectal cancer in the context of an enhanced recovery pathway. The results show that there was a modest but an independent association between regional anaesthesia (RA) and a lower magnitude of the postoperative SIR. Chapter 8 represents the relationship between pre-operative medications, the type of anaesthesia and post-operative sequelae in patients undergoing surgery for colorectal cancer. The results show that there was no association between the preoperative administration of aspirin, statins and ACE inhibitors and anaesthesia. Chapter 9 represents the relationship between nutritional status, anaesthetic approach, and peri-operative characteristics of patients undergoing surgery for colorectal cancer. The results show that there was no significant association between measures of nutritional status and anaesthetic approach. Chapter 10 represents the relationship between opioid administration, type of anaesthesia and clinicopathological characteristics in patients undergoing surgery for colorectal cancer. The results show that opioid administration was independently associated with both anaesthetic and operative factors. Chapter 11 represents the main findings of the thesis and some recommendation for a future work

    Annals [...].

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    Pedometrics: innovation in tropics; Legacy data: how turn it useful?; Advances in soil sensing; Pedometric guidelines to systematic soil surveys.Evento online. Coordenado por: Waldir de Carvalho Junior, Helena Saraiva Koenow Pinheiro, Ricardo SimĂŁo Diniz Dalmolin

    Causal and Semantic Relations in L2 Text Processing: An Eye-Tracking Study

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    This study is an extension of Nahatame’s (2018) research that demonstrated the effects of causal and semantic relations between sentences on second language (L2) text processing. Employing eye tracking, this study aimed to examine whether these effects appear during more natural, uninterrupted reading processes and to identify the time course of the effects. In the experiment, Japanese learners of English read two-sentence texts that varied in their causal and semantic relatedness, as evaluated by crowdsourced human judgments and via a computational approach (latent semantic analysis), respectively. Two eye-movement measures were collected and analyzed: first-pass reading times for the second sentence and lookbacks from the second to the first sentence. The results indicated that causal relatedness had a robust impact on both reading times and lookbacks. However, semantic relatedness impacted only reading times, and its effects were modulated by causal relatedness. Theoretical, pedagogical, and methodological implications of this finding were discussed

    Innovative Hybrid Approaches for Vehicle Routing Problems

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    This thesis deals with the efficient resolution of Vehicle Routing Problems (VRPs). The first chapter faces the archetype of all VRPs: the Capacitated Vehicle Routing Problem (CVRP). Despite having being introduced more than 60 years ago, it still remains an extremely challenging problem. In this chapter I design a Fast Iterated-Local-Search Localized Optimization algorithm for the CVRP, shortened to FILO. The simplicity of the CVRP definition allowed me to experiment with advanced local search acceleration and pruning techniques that have eventually became the core optimization engine of FILO. FILO experimentally shown to be extremely scalable and able to solve very large scale instances of the CVRP in a fraction of the computing time compared to existing state-of-the-art methods, still obtaining competitive solutions in terms of their quality. The second chapter deals with an extension of the CVRP called the Extended Single Truck and Trailer Vehicle Routing Problem, or simply XSTTRP. The XSTTRP models a broad class of VRPs in which a single vehicle, composed of a truck and a detachable trailer, has to serve a set of customers with accessibility constraints making some of them not reachable by using the entire vehicle. This problem moves towards VRPs including more realistic constraints and it models scenarios such as parcel deliveries in crowded city centers or rural areas, where maneuvering a large vehicle is forbidden or dangerous. The XSTTRP generalizes several well known VRPs such as the Multiple Depot VRP and the Location Routing Problem. For its solution I developed an hybrid metaheuristic which combines a fast heuristic optimization with a polishing phase based on the resolution of a limited set partitioning problem. Finally, the thesis includes a final chapter aimed at guiding the computational evaluation of new approaches to VRPs proposed by the machine learning community

    How to Be a God

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    When it comes to questions concerning the nature of Reality, Philosophers and Theologians have the answers. Philosophers have the answers that can’t be proven right. Theologians have the answers that can’t be proven wrong. Today’s designers of Massively-Multiplayer Online Role-Playing Games create realities for a living. They can’t spend centuries mulling over the issues: they have to face them head-on. Their practical experiences can indicate which theoretical proposals actually work in practice. That’s today’s designers. Tomorrow’s will have a whole new set of questions to answer. The designers of virtual worlds are the literal gods of those realities. Suppose Artificial Intelligence comes through and allows us to create non-player characters as smart as us. What are our responsibilities as gods? How should we, as gods, conduct ourselves? How should we be gods

    Consolidation of Urban Freight Transport – Models and Algorithms

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    Urban freight transport is an indispensable component of economic and social life in cities. Compared to other types of transport, however, it contributes disproportionately to the negative impacts of traffic. As a result, urban freight transport is closely linked to social, environmental, and economic challenges. Managing urban freight transport and addressing these issues poses challenges not only for local city administrations but also for companies, such as logistics service providers (LSPs). Numerous policy measures and company-driven initiatives exist in the area of urban freight transport to overcome these challenges. One central approach is the consolidation of urban freight transport. This dissertation focuses on urban consolidation centers (UCCs) which are a widely studied and applied measure in urban freight transport. The fundamental idea of UCCs is to consolidate freight transport across companies in logistics facilities close to an urban area in order to increase the efficiency of vehicles delivering goods within the urban area. Although the concept has been researched and tested for several decades and it was shown that it can reduce the negative externalities of freight transport in cities, in practice many UCCs struggle with a lack of business participation and financial difficulties. This dissertation is primarily focused on the costs and savings associated with the use of UCCs from the perspective of LSPs. The cost-effectiveness of UCC use, which is also referred to as cost attractiveness, can be seen as a crucial condition for LSPs to be interested in using UCC systems. The overall objective of this dissertation is two-fold. First, it aims to develop models to provide decision support for evaluating the cost-effectiveness of using UCCs. Second, it aims to analyze the impacts of urban freight transport regulations and operational characteristics on the cost attractiveness of using UCCs from the perspective of LSPs. In this context, a distinction is made between UCCs that are jointly operated by a group of LSPs and UCCs that are operated by third parties who offer their urban transport service for a fee. The main body of this dissertation is based on three research papers. The first paper focuses on jointly-operated UCCs that are operated by a group of cooperating LSPs. It presents a simulation model to analyze the financial impacts on LSPs participating in such a scheme. In doing so, a particular focus is placed on urban freight transport regulations. A case study is used to analyze the operation of a jointly-operated UCC for scenarios involving three freight transport regulations. The second and third papers take on a different perspective on UCCs by focusing on third-party operated UCCs. In contrast to the first paper, the second and third papers present an evaluation approach in which the decision to use UCCs is integrated with the vehicle route planning of LSPs. In addition to addressing the basic version of this integrated routing problem, known as the vehicle routing problem with transshipment facilities (VRPTF), the second paper presents problem extensions that incorporate time windows, fleet size and mix decisions, and refined objective functions. To heuristically solve the basic problem and the new problem variants, an adaptive large neighborhood search (ALNS) heuristic with embedded local search heuristic and set partitioning problem (SPP) is presented. Furthermore, various factors influencing the cost attractiveness of UCCs, including time windows and usage fees, are analyzed using a real-world case study. The third paper extends the work of the second paper and incorporates daily and entrance-based city toll schemes and enables multi-trip routing. A mixed-integer linear programming (MILP) formulation of the resulting problem is proposed, as well as an ALNS solution heuristic. Moreover, a real-world case study with three European cities is used to analyze the impact of the two city toll systems in different operational contexts
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