196 research outputs found

    Investigation of a Radiantly Heated and Cooled Office with an Integrated Desiccant Ventilation Unit

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    Radiant heating and cooling has a reputation of increasing the comfort level and reducing the energy consumption of buildings. The main advantages of radiant heating and cooling are low operational noise and reduced fan power cost. Radiant heating and cooling has been supplied in several forms, including floor heating, ceiling heating and cooling, radiant panels and façade heating and cooling. Among them, façade heating and cooling is the most recently developed system. This dissertation provides a comprehensive study of several technical issues relative to radiant heating and cooling systems that have received little attention in previous research. The following aspects are covered in this dissertation: First, a heat transfer model of mullion radiators, one type of façade heating and cooling, is developed and verified by measured performance data. The simulation demonstrates that the heating or cooling capacity of mullion radiators is a semi-linear function of supply water temperature and is affected by the thermal conductive resistance of mullion tubes, the room air temperature, the supply water flow rate, and the outside air temperature. Second, the impact of the positions of radiators on energy consumption and thermal comfort is studied. This dissertation compares the heating load and comfort level as measured by uniformity of operative temperature for two different layouts of radiators in the same geometric space. The air exchange rate has been identified as an important factor which affects energy saving benefits of the radiant heating systems. Third, the infiltration and the interaction of infiltration and mechanical ventilation air to produce moisture condensation in a radiantly cooled office are examined. The infiltration of the studied office is also explored by on-site blower door measurement, by analyzing measured CO2 concentration data, and through modeling. This investigation shows the infiltration level of the studied office to range between 0.46 and 1.03 air changes per hour (ACH). Fourth, the integrated sensible heating and cooling system is simulated and compared with a single duct variable air volume (VAV) system. The results show that, at the current infiltration level, the studied sensible heating and cooling system with an integrated active desiccant ventilation unit consumes 5.6% more primary energy than a single duct VAV system; it would consumes 11.4% less primary energy when the system is integrated with a presumed passive desiccant ventilation unit

    An Intelligent Framework for Oversubscription Management in CPU-GPU Unified Memory

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    This paper proposes a novel intelligent framework for oversubscription management in CPU-GPU UVM. We analyze the current rule-based methods of GPU memory oversubscription with unified memory, and the current learning-based methods for other computer architectural components. We then identify the performance gap between the existing rule-based methods and the theoretical upper bound. We also identify the advantages of applying machine intelligence and the limitations of the existing learning-based methods. This paper proposes a novel intelligent framework for oversubscription management in CPU-GPU UVM. It consists of an access pattern classifier followed by a pattern-specific Transformer-based model using a novel loss function aiming for reducing page thrashing. A policy engine is designed to leverage the model's result to perform accurate page prefetching and pre-eviction. We evaluate our intelligent framework on a set of 11 memory-intensive benchmarks from popular benchmark suites. Our solution outperforms the state-of-the-art (SOTA) methods for oversubscription management, reducing the number of pages thrashed by 64.4\% under 125\% memory oversubscription compared to the baseline, while the SOTA method reduces the number of pages thrashed by 17.3\%. Our solution achieves an average IPC improvement of 1.52X under 125\% memory oversubscription, and our solution achieves an average IPC improvement of 3.66X under 150\% memory oversubscription. Our solution outperforms the existing learning-based methods for page address prediction, improving top-1 accuracy by 6.45\% (up to 41.2\%) on average for a single GPGPU workload, improving top-1 accuracy by 10.2\% (up to 30.2\%) on average for multiple concurrent GPGPU workloads.Comment: arXiv admin note: text overlap with arXiv:2203.1267

    The stability and design of nonlinear neural networks

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    AbstractBased on the techniques of singular value decomposition and generalized inverse, two new methods for designing associative memories are presented. The two methods not only guarantee that each given vector is an equilibrium point of the network, but also guarantee the asymptotic stability of the equilibrium points. Examples show the effectiveness of the new methods

    Artificial Intelligence in the Differential Diagnosis of Cardiomyopathy Phenotypes

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    Artificial intelligence (AI) is rapidly being applied to the medical field, especially in the cardiovascular domain. AI approaches have demonstrated their applicability in the detection, diagnosis, and management of several cardiovascular diseases, enhancing disease stratification and typing. Cardiomyopathies are a leading cause of heart failure and life-threatening ventricular arrhythmias. Identifying the etiologies is fundamental for the management and diagnostic pathway of these heart muscle diseases, requiring the integration of various data, including personal and family history, clinical examination, electrocardiography, and laboratory investigations, as well as multimodality imaging, making the clinical diagnosis challenging. In this scenario, AI has demonstrated its capability to capture subtle connections from a multitude of multiparametric datasets, enabling the discovery of hidden relationships in data and handling more complex tasks than traditional methods. This review aims to present a comprehensive overview of the main concepts related to AI and its subset. Additionally, we review the existing literature on AI-based models in the differential diagnosis of cardiomyopathy phenotypes, and we finally examine the advantages and limitations of these AI approaches

    A Survey on Breaking Technique of Text-Based CAPTCHA

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    The CAPTCHA has become an important issue in multimedia security. Aimed at a commonly used text-based CAPTCHA, this paper outlines some typical methods and summarizes the technological progress in text-based CAPTCHA breaking. First, the paper presents a comprehensive review of recent developments in the text-based CAPTCHA breaking field. Second, a framework of text-based CAPTCHA breaking technique is proposed. And the framework mainly consists of preprocessing, segmentation, combination, recognition, postprocessing, and other modules. Third, the research progress of the technique involved in each module is introduced, and some typical methods of segmentation and recognition are compared and analyzed. Lastly, the paper discusses some problems worth further research

    Predicting progression of white matter hyperintensity using coronary artery calcium score based on coronary CT angiography—feasibility and accuracy

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    ObjectiveCoronary artery disease (CAD) usually coexists with subclinical cerebrovascular diseases given the systematic nature of atherosclerosis. In this study, our objective was to predict the progression of white matter hyperintensity (WMH) and find its risk factors in CAD patients using the coronary artery calcium (CAC) score. We also investigated the relationship between the CAC score and the WMH volume in different brain regions.MethodsWe evaluated 137 CAD patients with WMH who underwent coronary computed tomography angiography (CCTA) and two magnetic resonance imaging (MRI) scans from March 2018 to February 2023. Patients were categorized into progressive (n = 66) and nonprogressive groups (n = 71) by the change in WMH volume from the first to the second MRI. We collected demographic, clinical, and imaging data for analysis. Independent risk factors for WMH progression were identified using logistic regression. Three models predicting WMH progression were developed and assessed. Finally, patients were divided into groups based on their total CAC score (0 to <100, 100 to 400, and > 400) to compare their WMH changes in nine brain regions.ResultsAlcohol abuse, maximum pericoronary fat attenuation index (pFAI), CT-fractional flow reserve (CT-FFR), and CAC risk grade independently predicted WMH progression (p < 0.05). The logistic regression model with all four variables performed best (training: AUC = 0.878, 95% CI: 0.790, 0.938; validation: AUC = 0.845, 95% CI: 0.734, 0.953). An increased CAC risk grade came with significantly higher WMH volume in the total brain, corpus callosum, and frontal, parietal and occipital lobes (p < 0.05).ConclusionThis study demonstrated the application of the CCTA-derived CAC score to predict WMH progression in elderly people (≥60 years) with CAD
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