In today’s world, there are many people suffering from mentalhealth problems such as depression and anxiety. If these conditions are notidentified and treated early, they can get worse quickly and have far-reachingne...In today’s world, there are many people suffering from mentalhealth problems such as depression and anxiety. If these conditions are notidentified and treated early, they can get worse quickly and have far-reachingnegative effects. Unfortunately, many people suffering from these conditions,especially depression and hypertension, are unaware of their existence until theconditions become chronic. Thus, this paper proposes a novel approach usingBi-directional Long Short-Term Memory (Bi-LSTM) algorithm and GlobalVector (GloVe) algorithm for the prediction and treatment of these conditions.Smartwatches and fitness bands can be equipped with these algorithms whichcan share data with a variety of IoT devices and smart systems to betterunderstand and analyze the user’s condition. We compared the accuracy andloss of the training dataset and the validation dataset of the two modelsnamely, Bi-LSTM without a global vector layer and with a global vector layer.It was observed that the model of Bi-LSTM without a global vector layer hadan accuracy of 83%,while Bi-LSTMwith a global vector layer had an accuracyof 86% with a precision of 86.4%, and an F1 score of 0.861. In addition toproviding basic therapies for the treatment of identified cases, our model alsohelps prevent the deterioration of associated conditions, making our methoda real-world solution.展开更多
The paper uses a global vector autoregressive model to examine provincial output spillover effects in China. We find that there are effective output spillovers from Guangdong, Liaoning and Zhejiang to other provinces ...The paper uses a global vector autoregressive model to examine provincial output spillover effects in China. We find that there are effective output spillovers from Guangdong, Liaoning and Zhejiang to other provinces in China, but trivial effects from Shanghai, Shandong, Sichuan and Xinfiang, and negative effects from Beijing. Foreign direct investment （FDI） in Guangdong and Liaoning is the main channel for creating provincial output spillovers, compared with domestic investment and exports. However, FDl spillovers tend to decrease, with spillovers from exports and domestic investment rising over time, so that the spillover effects in Guangdong and Liaoning are non-persistent and highly volatile. Other channels of output spillover, such as domestic investment, should be enhanced. Impacts of shock from government expenditure on GDP vary significantly across time and provinces; inland and western provinces are most negatively affected. The heterogeneous spillover structure shows that regional policies might achieve better results than nationwide policies in reducing regional disparity.展开更多
This research paper proposes a filter to remove Random Valued Impulse Noise (RVIN) based on Global Threshold Vector Outlyingness Ratio (GTVOR) that is applicable for real time image processing. This filter works with ...This research paper proposes a filter to remove Random Valued Impulse Noise (RVIN) based on Global Threshold Vector Outlyingness Ratio (GTVOR) that is applicable for real time image processing. This filter works with the algorithm that breaks the images into various decomposition levels using Discrete Wavelet Transform (DWT) and searches for the noisy pixels using the outlyingness of the pixel. This algorithm has the capability of differentiating high frequency pixels and the “noisy pixel” using the threshold as well as window adjustments. The damage and the loss of information are prevented by means of interior mining. This global threshold based algorithm uses different thresholds for different quadrants of DWT and thus helps in recovery of noisy image even if it is 90% affected. Experimental results exhibit that this method outperforms other existing methods for accurate noise detection and removal, at the same time chain of connectivity is not lost.展开更多
针对Open Street Map(OSM)数据不能全要素转换为所需的地理信息要素数据库数据的逻辑关系、数据要素不能高效处理和快速质检的问题,本文基于GIS技术,建立了一套核心矢量快速生产系统。该系统包含对千万级、亿级节点的OSM数据的快速读写...针对Open Street Map(OSM)数据不能全要素转换为所需的地理信息要素数据库数据的逻辑关系、数据要素不能高效处理和快速质检的问题,本文基于GIS技术,建立了一套核心矢量快速生产系统。该系统包含对千万级、亿级节点的OSM数据的快速读写,可实现OSM数据到地理信息要素数据的高效转化,完成地理要素数据的快速质检,该项成果已经在国家重大测绘工程项目生产中应用。基于GIS技术实现的核心矢量数据快速生产系统的生产实践表明,该系统通过一系列高效自动的批量处理和质检技术,提高了数据的几何和属性辨识能力,对国家地理信息资源建设起到了良好支撑作用。展开更多
The seven co-located sites of the Crustal Movement Observation Network of China（CMONOC） in Shanghai, Wuhan, Kunming, Beijing, Xi＇an, Changchun, and Urumqi are equipped with Global Navigation Satellite System（GNSS...The seven co-located sites of the Crustal Movement Observation Network of China（CMONOC） in Shanghai, Wuhan, Kunming, Beijing, Xi＇an, Changchun, and Urumqi are equipped with Global Navigation Satellite System（GNSS）, very long baseline interferometry（VLBI）, and satellite laser ranging（SLR） equipment. Co-location surveying of these sites was performed in 2012 and the accuracies of the solved tie vectors are approximately 5 mm.This paper proposes a mathematical model that handles the least squares adjustment of the 3D control network and calculates the tie vectors in one step, using all the available constraints in the adjustment. Using the new mathematical model, local tie vectors can be more precisely determined and their covariance more reasonably estimated.展开更多
In this paper,the global and local linear independence of any compactly supported distributions by using time domain spaces,and of refinable vectors by invariant linear spaces are investigated.
基金This research is funded by Vellore Institute of Technology,Chennai,India.
文摘In today’s world, there are many people suffering from mentalhealth problems such as depression and anxiety. If these conditions are notidentified and treated early, they can get worse quickly and have far-reachingnegative effects. Unfortunately, many people suffering from these conditions,especially depression and hypertension, are unaware of their existence until theconditions become chronic. Thus, this paper proposes a novel approach usingBi-directional Long Short-Term Memory (Bi-LSTM) algorithm and GlobalVector (GloVe) algorithm for the prediction and treatment of these conditions.Smartwatches and fitness bands can be equipped with these algorithms whichcan share data with a variety of IoT devices and smart systems to betterunderstand and analyze the user’s condition. We compared the accuracy andloss of the training dataset and the validation dataset of the two modelsnamely, Bi-LSTM without a global vector layer and with a global vector layer.It was observed that the model of Bi-LSTM without a global vector layer hadan accuracy of 83%,while Bi-LSTMwith a global vector layer had an accuracyof 86% with a precision of 86.4%, and an F1 score of 0.861. In addition toproviding basic therapies for the treatment of identified cases, our model alsohelps prevent the deterioration of associated conditions, making our methoda real-world solution.
文摘The paper uses a global vector autoregressive model to examine provincial output spillover effects in China. We find that there are effective output spillovers from Guangdong, Liaoning and Zhejiang to other provinces in China, but trivial effects from Shanghai, Shandong, Sichuan and Xinfiang, and negative effects from Beijing. Foreign direct investment （FDI） in Guangdong and Liaoning is the main channel for creating provincial output spillovers, compared with domestic investment and exports. However, FDl spillovers tend to decrease, with spillovers from exports and domestic investment rising over time, so that the spillover effects in Guangdong and Liaoning are non-persistent and highly volatile. Other channels of output spillover, such as domestic investment, should be enhanced. Impacts of shock from government expenditure on GDP vary significantly across time and provinces; inland and western provinces are most negatively affected. The heterogeneous spillover structure shows that regional policies might achieve better results than nationwide policies in reducing regional disparity.
文摘This research paper proposes a filter to remove Random Valued Impulse Noise (RVIN) based on Global Threshold Vector Outlyingness Ratio (GTVOR) that is applicable for real time image processing. This filter works with the algorithm that breaks the images into various decomposition levels using Discrete Wavelet Transform (DWT) and searches for the noisy pixels using the outlyingness of the pixel. This algorithm has the capability of differentiating high frequency pixels and the “noisy pixel” using the threshold as well as window adjustments. The damage and the loss of information are prevented by means of interior mining. This global threshold based algorithm uses different thresholds for different quadrants of DWT and thus helps in recovery of noisy image even if it is 90% affected. Experimental results exhibit that this method outperforms other existing methods for accurate noise detection and removal, at the same time chain of connectivity is not lost.
文摘针对Open Street Map(OSM)数据不能全要素转换为所需的地理信息要素数据库数据的逻辑关系、数据要素不能高效处理和快速质检的问题,本文基于GIS技术,建立了一套核心矢量快速生产系统。该系统包含对千万级、亿级节点的OSM数据的快速读写,可实现OSM数据到地理信息要素数据的高效转化,完成地理要素数据的快速质检,该项成果已经在国家重大测绘工程项目生产中应用。基于GIS技术实现的核心矢量数据快速生产系统的生产实践表明,该系统通过一系列高效自动的批量处理和质检技术,提高了数据的几何和属性辨识能力,对国家地理信息资源建设起到了良好支撑作用。
基金sponsored by the Crustal Movement Observation Network of China(CMONOC)partially supported by the Natural Science Foundation of China(41274035,41174023)
文摘The seven co-located sites of the Crustal Movement Observation Network of China（CMONOC） in Shanghai, Wuhan, Kunming, Beijing, Xi＇an, Changchun, and Urumqi are equipped with Global Navigation Satellite System（GNSS）, very long baseline interferometry（VLBI）, and satellite laser ranging（SLR） equipment. Co-location surveying of these sites was performed in 2012 and the accuracies of the solved tie vectors are approximately 5 mm.This paper proposes a mathematical model that handles the least squares adjustment of the 3D control network and calculates the tie vectors in one step, using all the available constraints in the adjustment. Using the new mathematical model, local tie vectors can be more precisely determined and their covariance more reasonably estimated.
文摘In this paper,the global and local linear independence of any compactly supported distributions by using time domain spaces,and of refinable vectors by invariant linear spaces are investigated.
