Integrating intermediate inputs from partially classified images within a hybrid classification framework: An impervious surface estimation example

With the constant proliferation of computational power, our ability to develop hybrid classifiers has improved. Hybrid classifiers integrate results from multiple algorithms and often improve classification accuracy. In this paper, a hybrid classification framework was used to evaluate two research hypotheses: i) can manipulated results from prior classifiers (“intermediate inputs” (IIs)) improve classification accuracy in subsequent classification steps. and ii) is there an optimal dataset proportion for creation and usage of intermediate inputs. These additional intermediate inputs were based on spatial and texture statistics calculated on a partially classified image. The implementation of intermediate inputs on an impervious surface classification task using a 2001 Landsat ETM+ image from central New York was demonstrated. The results suggested that there was an average accuracy improvement of 3.6% (maximum 6.6%) by using intermediate inputs. These improvements were proved statistically significant by a Z-test and tended to increase as classification difficulty increased. The experiments in this paper also showed that there was an optimal point that balanced the number of pixels and pixel classification accuracy from prior steps used to produce intermediate inputs. Additionally, some traditional problems such as separation of impervious surfaces and soil were successfully tackled through intermediate inputs. The concept of the intermediate inputs may easily apply to other sensors and/or ground features.     

A leakage-aware L2 cache management technique for producer-consumer sharing in low-power chip multiprocessors

This paper proposes a novel leakage management technique for applications with producer-consumer sharing patterns. Although previous research has proposed leakage management techniques by turning off inactive cache blocks, these techniques can be further improved by exploiting the various run-time characteristics of target applications in CMPs. By exploiting particular access sequences observed in producer-consumer sharing patterns and the spatial locality of shared buffers, our technique enables a more aggressive turn-off of L2 cache blocks of these buffers. Experimental results using a CMP simulator show that our proposed technique reduces the energy consumption of on-chip L2 caches, a shared bus, and off-chip memory by up to 31.3% over the existing cache leakage power management techniques with no significant performance loss.     

State estimation for fuzzy cellular neural networks with time delay in the leakage term, discrete and unbounded distributed delays

This paper deals with the problem of state estimation for fuzzy cellular neural networks (FCNNs) with time delay in the leakage term, discrete and unbounded distributed delays. In this paper, leakage delay in the leakage term is used to unstable the neuron states. It is challenging to develop a delay dependent condition to estimate the unstable neuron states through available output measurements such that the error-state system is globally asymptotically stable. By constructing the Lyapunov-Krasovskii functional which contains a triple-integral term, an improved delay-dependent stability criterion is derived in terms of linear matrix inequalities (LMIs). However, by using the free-weighting matrices method, a simple and efficient criterion is derived in terms of LMIs for estimation. The restriction such as the time-varying delay which was required to be differentiable or even its time-derivative which was assumed to be smaller than one, are removed. Instead, the time-varying delay is only assumed to be bounded. Finally, numerical examples and its simulations are given to demonstrate the effectiveness of the derived results.     

Large-area assessment of impervious surface based on integrated analysis of single-date Landsat-7 images and geospatial vector data

Driven by a constantly accelerating increase of urban population in recent decades urban sprawl has become one of the most dynamic processes in the context of global land use transformations. The expansion of urban agglomerations is closely associated with a substantial increase of impervious surface. In Europe, methods for an accurate, fast and cost-effective mapping and assessment of impervious surface on a state-wide or national scale have not been established so far. This study presents an approach for estimating the impervious surface based on a combined analysis of single-date Landsat images and road network and railway vector data using Support Vector Machines and functionalities of geographic information processing. The modeling aims at the provision of data on the impervious surface for the total of residential, industrial and transportation-related areas. The derived information is provided for the administrative units of communities. The output of the procedure is a vector data file providing the ‘percent impervious surface of built-up areas’ (PIS_B) and the ‘percent impervious surface of the total of built-up and transportation-related areas’ (PIS_BT) for the administrative units of communities. The developed method is tested for a study area covering almost one third of the German territory. The results prove the suitability of the approach for a widely automated and area-wide mapping of impervious surfaces. Using reference data sets of three cities (Leipzig, Ludwigshafen, Passau) we realized a mean absolute error of 19.8% and an average error of 6.4% for the percent impervious surface modeled on the basis of the Landsat images. The final product resulting from a combination of the imperviousness raster derived from the satellite images with the transportation-related vector information showed a mean difference of 1% to 4% compared to corresponding reference data and results of previous studies. For the year 2000 our research shows that 45.3% of the area occupied by settlements and transport infrastructure in the German federal state of Bavaria, 44.6% in the state of Baden-Württemberg and 42.6% in the state of Saxony was covered by impervious surface.     

单层平面索网玻璃幕墙数值风洞风载荷分析

针对现行幕墙设计规范没有明确规定单层平面索网幕墙体系的风载荷计算的问题,以某大厦裙房幕墙为研究对象,用ADINA分析考虑流固耦合作用的玻璃 索网体系风振响应分析,并与通常采用的等效静风载荷方法得到的结构风效应比较.分析表明,对于非线性的索网玻璃幕墙结构,现行载荷规范采用的等效静风载荷方法会导致偏于不安全的设计计算结果.     

中厚板水幕分组冷却的最优前馈控制算法

针对中厚板水幕分组冷却系统的最优前馈控制算法进行了研究。由该算法确定水幕的开幕数、流量及水幕的排列方式 ,从而对水幕入口温度的波动进行补偿。     

特种粘土固化浆液在军山水库除险加固中的应用

本文介绍江西省于都县军山水库大坝坝体防渗所采用的特种粘土固化浆液灌浆技术的施工工艺和技术要求.     

玻璃幕墙传热系数计算方法及工程应用

在研究玻璃幕墙热传递特点的基础上,基于一维稳态热传导理论,以中空玻璃为例建立了玻璃系统传热系数计算模型;基于二维稳态热传导理论和有限单元法,采用三节点三角形单元对二维温度场进行了离散,推导了单元热传导矩阵和温度载荷列阵,并推导了热对流、热流密度、辐射以及各种边界条件耦合作用下对单元热传导矩阵和温度载荷列阵的修正公式,建立了玻璃幕墙框及附加线传热系数计算模型。利用Visual C++和ObjectARX对AutoCAD进行了二次开发,研发了玻璃幕墙传热系数计算软件TJCW,并通过算例与LBNL系列软件计算结果进行比较,验证了所编软件的正确性和有效性。最后对某工程实例中玻璃幕墙传热系数进行了节能验算。研究结果表明:建立的传热系数计算模型能够正确的计算玻璃幕墙传热系数,基于该计算模型开发出的软件能够应用于实际工程的节能分析和计算中。     

大型地下石洞油气库人工水幕技术

人工水幕技术,是建造储存石油和天然气的不衬砌石洞地下库的关键。一座总库容为300万m3、9条20 m×30 m×(484~717)m的中国首座大型地下水封洞库建成,标志我国"国家战略石油地下储备库"的梦想成真。给出了人工水幕技术原理、具体实施关键技术以及水封效果。理论分析与初步实践结果表明,在年均降水量736mm的花岗片麻岩内建造储存原油洞库,是切实可行的。首座大型地下水封石洞储库的施工建设技术,对我国后续的国家战略油气地下储库规划实施,起到了示范启迪与借鉴作用。     

观音岩水电站右岸大坝首次基础固结灌浆生产性试验成果分析及建议

观音岩水电站右岸混凝土坝段坝基地质条件复杂,通过固结灌浆生产性试验,确定合理的施工参数和施工工艺措施,验证设计指标的合理性。本文对此加以介绍。