4,136 research outputs found

    Automatic solar feature detection using image processing and pattern recognition techniques

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    The objective of the research in this dissertation is to develop a software system to automatically detect and characterize solar flares, filaments and Corona Mass Ejections (CMEs), the core of so-called solar activity. These tools will assist us to predict space weather caused by violent solar activity. Image processing and pattern recognition techniques are applied to this system. For automatic flare detection, the advanced pattern recognition techniques such as Multi-Layer Perceptron (MLP), Radial Basis Function (RBF), and Support Vector Machine (SVM) are used. By tracking the entire process of flares, the motion properties of two-ribbon flares are derived automatically. In the applications of the solar filament detection, the Stabilized Inverse Diffusion Equation (SIDE) is used to enhance and sharpen filaments; a new method for automatic threshold selection is proposed to extract filaments from background; an SVM classifier with nine input features is used to differentiate between sunspots and filaments. Once a filament is identified, morphological thinning, pruning, and adaptive edge linking methods are applied to determine filament properties. Furthermore, a filament matching method is proposed to detect filament disappearance. The automatic detection and characterization of flares and filaments have been successfully applied on Hα full-disk images that are continuously obtained at Big Bear Solar Observatory (BBSO). For automatically detecting and classifying CMEs, the image enhancement, segmentation, and pattern recognition techniques are applied to Large Angle Spectrometric Coronagraph (LASCO) C2 and C3 images. The processed LASCO and BBSO images are saved to file archive, and the physical properties of detected solar features such as intensity and speed are recorded in our database. Researchers are able to access the solar feature database and analyze the solar data efficiently and effectively. The detection and characterization system greatly improves the ability to monitor the evolution of solar events and has potential to be used to predict the space weather

    The impact of hot and cold storages on a solar absorption cooling system for an office building

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    A Review of Thermal Analysis on Novel Roofing Systems

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    In this paper, we reviewed three types of novel roofing systems which can reduce building thermal loads: cool roof, green roof, and phase change material (PCM) roof. Cool roofs are designed to keep the roof cool by reflecting the incident solar radiation away from the building and radiating the stored heat away at night. Green roof, also called eco-roof, covered by vegetation, utilizes the thermal insulation provided by the soil and evapo-transpiration to keep the roof cool under the sun. PCM roofs employ phase change material with high latent heat of fusion in the roofs. PCM roofs are able to absorb large amount of heat at demand peak when PCM changes its phase, so that the heat from outdoor is stored in the PCM rather than flows into indoor space. The effort in the paper has compared the key parameters of each of the systems, thermal analysis methodologies, and the energy savings due to each of them with reference cases, in addition, we provide a comprehensive thermal analysis methods applied in novel roof systems and a guide to design proper novel roofing system for a give climate and building types

    LINE: Large-scale Information Network Embedding

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    This paper studies the problem of embedding very large information networks into low-dimensional vector spaces, which is useful in many tasks such as visualization, node classification, and link prediction. Most existing graph embedding methods do not scale for real world information networks which usually contain millions of nodes. In this paper, we propose a novel network embedding method called the "LINE," which is suitable for arbitrary types of information networks: undirected, directed, and/or weighted. The method optimizes a carefully designed objective function that preserves both the local and global network structures. An edge-sampling algorithm is proposed that addresses the limitation of the classical stochastic gradient descent and improves both the effectiveness and the efficiency of the inference. Empirical experiments prove the effectiveness of the LINE on a variety of real-world information networks, including language networks, social networks, and citation networks. The algorithm is very efficient, which is able to learn the embedding of a network with millions of vertices and billions of edges in a few hours on a typical single machine. The source code of the LINE is available online.Comment: WWW 201

    An Attention-based Collaboration Framework for Multi-View Network Representation Learning

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    Learning distributed node representations in networks has been attracting increasing attention recently due to its effectiveness in a variety of applications. Existing approaches usually study networks with a single type of proximity between nodes, which defines a single view of a network. However, in reality there usually exists multiple types of proximities between nodes, yielding networks with multiple views. This paper studies learning node representations for networks with multiple views, which aims to infer robust node representations across different views. We propose a multi-view representation learning approach, which promotes the collaboration of different views and lets them vote for the robust representations. During the voting process, an attention mechanism is introduced, which enables each node to focus on the most informative views. Experimental results on real-world networks show that the proposed approach outperforms existing state-of-the-art approaches for network representation learning with a single view and other competitive approaches with multiple views.Comment: CIKM 201

    Low Dose Theophylline Showed an Inhibitory Effect on the Production of IL-6 and IL-8 in Primary Lung Fibroblast from Patients with COPD

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    Chronic obstructive pulmonary disease (COPD) is characterized by the abnormal and chronic lung inflammation. We hypothesized that lung fibroblasts could contribute to the local inflammation and investigated whether low dose theophylline had a beneficial effect on fibroblasts inflammation. Subjects undergoing lobectomy for bronchial carcinoma were enrolled and divided into COPD and control groups according to spirometry. Primary human lung fibroblasts were cultured from peripheral lung tissue distant to tumor tissue. There was a significant increase in both the mRNA expressions and protein levels for IL-6 and IL-8 in fibroblasts in COPD group, and the values were negatively correlated with lung function (P < 0.05). For COPD fibroblasts, the protein levels of IL-6 and IL-8 decreased from 993.0 ± 738.9 pg/mL to 650.1 ± 421.9 pg/mL (P = 0.014) and from 703.1 ± 278.0 pg/mL to 492.0 ± 214.9 pg/mL (P = 0.001), respectively, with 5 μg/mL theophylline treatment. In addition, theophylline at the dose of 5 μg/mL reduced the increased production of IL-6 and IL-8 induced by 1 μg/mL LPS in primary human lung fibroblasts. Our data suggest that lung fibroblasts participate in the chronic inflammation in COPD by releasing IL-6 and IL-8, and low dose theophylline can alleviate the proinflammatory mediators' production by fibroblasts

    Absorption Simulation ( ABSIM ) Software Development

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    Researchers working on air conditioning systems currently use a software called ABSIM ( Absorption Simulation ) to evaluate current absorption systems or simulate new system designs. ABSIM was developed at Oak Ridge National Labs in the 1980s and the latest platform it is compatible with is Windows XP. ABSIM is not compatible on newer platforms and is not very user friendly. A lot of the actions involved in using ABSIM aren’t very intuitive. The goal is to develop a more user friendly simulation program that is based off of ABSIM and see to it that the program can be deployed across different platforms. Storing and managing the data of the modular system was another issue that needed to be addressed. Putting together a user interface for the new program was achieved by using the application framework ‘Qt Creator’. To learn more about ‘Qt Creator’ and its uses, online research was primarily done on forums popular amongst app developers. A linked list was used to store and manage the data. A simulation program for absorption systems is currently being developed in C++ using ‘Qt Creator’. Using a linked list for storing and organizing data turned out to be the simplest and most efficient way to do so. ‘Qt Creator’ is the right tool used in the development of the simulation program because it allows a program to be deployed on any platform which has the necessary libraries

    Environmental Monitoring in Preparation for the Installation of a Green Roof

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    Green roofs are becoming an increasingly popular way to improve the environmental, economic, and aesthetic performance of both new and existing buildings. Along with the green roofs themselves, it is also common to install sensors to measure various environmental parameters that are affected by or important to the operation of the roof such as precipitation, temperature, and runoff. However, for most of these systems, the sensors are installed at the same time or even after the green roof. Therefore, no before-and-after comparisons can be made for those roofs. To account for this missing data, monitoring equipment was installed on a Purdue University campus building to measure existing conditions for the year prior to the expected construction of a green roof. This equipment currently includes a weather station, along with runoff, heat flux, and temperature sensors, and there are plans to monitor air quality as well. Preliminary findings from values recorded thus far appear to validate the expected behavior of the roof. Stormwater runoff directly correlates to rainfall, and roof temperature is dependent on ambient air temperature and solar radiation. Data from the heat flux sensors, however, is not yet fully explained. This ongoing experiment should see significant changes in the data once the green roof is installed, but until that time, it will continue to serve its role as the control setup for measuring the performance of a standard roof
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