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Studies on the utilization of eaf slag as coarse aggregate in concrete- A review 炉渣粗骨料在混凝土中的应用研究综述
Pub Date : 2020-01-01 DOI: 10.5958/2454-762x.2020.00012.8
Mehnaz Dhar, Sanjay Sharma
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引用次数: 0
Forecasting of Rainfall Variability Using Stationary Wavelet Transforms 基于平稳小波变换的降雨变率预测
Pub Date : 2020-01-01 DOI: 10.5958/2454-762x.2020.00003.7
Uttam Kumar Rawat, Anil Kumar
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引用次数: 0
Topology Based Routing Protocol in Vehicular Ad-Hoc Network 基于拓扑的车载Ad-Hoc网络路由协议
Pub Date : 2020-01-01 DOI: 10.5958/2454-762X.2020.00019.0
Vibha Oberoi, Praveena Chaturvedi
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引用次数: 0
Design consideration and issues in wireless sensor network deployment 无线传感器网络部署的设计考虑及问题
Pub Date : 2020-01-01 DOI: 10.5958/2454-762x.2020.00010.4
Vipul Narayan, A. Daniel
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引用次数: 7
Study and Analysis of Digital Watermarking for Medical Images 医学图像数字水印的研究与分析
Pub Date : 2020-01-01 DOI: 10.5958/2454-762x.2020.00001.3
M. Singh, Ankur Rai, P. Chaurasia
In the recent years, Internet users are increased tremendously. Hence, it demands a secure communication for different Internet services. Data sharing such as audio, video, image and documents are an integral part, which needs to be secure during transmission. In healthcare applications, the patient's information requires security and integrity during transfer of data from one place to another. The watermarking techniques can improve data protection and content enrichment of medical images. In this article, the literature study is carried out to show the frequency domain techniques are more robust than spatial domain. Apart from this, a brief and comparative analysis of watermarking technique with different image size is presented to show the trade-off between capacity and perceptibility of the image.
近年来,互联网用户急剧增加。因此,它要求对不同的Internet服务进行安全通信。音频、视频、图像和文档等数据共享是一个不可分割的组成部分,在传输过程中需要保证安全。在医疗保健应用程序中,在将数据从一个地方传输到另一个地方期间,患者的信息需要安全性和完整性。水印技术可以提高医学图像的数据保护和内容丰富程度。在本文中,进行了文献研究,表明频域技术比空间域技术更具鲁棒性。此外,本文还对不同图像大小的水印技术进行了简要的对比分析,以说明图像容量和可感知性之间的权衡。
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引用次数: 0
Simulation of Heat Transfer Characteristics of Sensible Heat Storage System 显热蓄热系统传热特性的模拟
Pub Date : 2020-01-01 DOI: 10.5958/2454-762x.2020.00017.7
A. Vedrtnam
The aim of present work includes development of a numerical model for the prediction of heat transfer characteristics of a sensible heat storage system (SHSS) followed by the validation using a small scale experiment. The concrete structures with entrenched steel pipe with definite maximum energy storage capacity was considered for the modelling and in an experimental scheme. The charging-discharging time, temperature profiles were predicted with significant accuracy by the developed model. The dependence of sensible heat storage performance on operating temperature range, thermo-physical properties of sensible heat storage material, and heat transfer fluid is also established. The excellent agreement between experimental and simulation results ensured the applicability of develop ed models for higher temperature full-scale applications.
目前工作的目的包括开发一个数值模型,用于预测显热存储系统(SHSS)的传热特性,然后使用小规模实验进行验证。在模型和试验方案中考虑了具有确定最大储能容量的钢管混凝土结构。该模型能较准确地预测电池的充放电时间和温度分布。建立了显热蓄热性能与工作温度范围、显热蓄热材料的热物理性质和传热流体的关系。实验和仿真结果之间的良好一致性确保了所开发的模型适用于更高温度的全尺寸应用。
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引用次数: 0
Solution of hyperbolic equation with time variable coefficient by rothe's method 用rothe法求解时变系数双曲方程
Pub Date : 2020-01-01 DOI: 10.5958/2454-762x.2020.00006.2
R. Shukla, Dinesh Kumar
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引用次数: 0
Recurrent neural network based image compression 基于递归神经网络的图像压缩
Pub Date : 2020-01-01 DOI: 10.5958/2454-762x.2020.00013.x
Ashwini Kambar
In this presentation we described and implemented Image compression using recurrent neural network, the compression of image method is a type of information compression that will decrease the same amount of image to be transmitted, stored and evaluated, but without losing the information content. Here we are compressing image with one of most type of neural network i.e. Recurrent Neural Network (RNN). The architecture consist of recurrent neural network based encoder, binarizer, and decoder system. Using this reconstructed the image which is having better quality than the original image and along with this here we show the activation function i.e. Sigmoid, ReLU and tanh functions. And also we evaluated PSNR, MSE, CR, BPP and SSIM, MS-SSIM, parameters for comparing original and compressed images. For this we are taken selected images on the Kodak dataset images. And this work is performed by using python 3.6 version tool with some standard packages for AI functions. So this can demonstrates that our Deep learning achieves better generalization
在本演讲中,我们描述并实现了使用递归神经网络的图像压缩,图像压缩方法是一种信息压缩,它将减少相同数量的图像传输,存储和评估,但不会丢失信息内容。这里我们用一种最常见的神经网络,即递归神经网络(RNN)来压缩图像。该结构由基于循环神经网络的编码器、二值化器和解码器系统组成。利用这种方法重建的图像比原始图像质量更好,与此同时,我们展示了激活函数,即Sigmoid, ReLU和tanh函数。并对原始图像和压缩图像的PSNR、MSE、CR、BPP和SSIM、MS-SSIM进行了比较。为此,我们在柯达数据集图像上选取图像。使用python 3.6版本的工具和一些AI功能的标准包来完成这项工作。所以这可以证明我们的深度学习实现了更好的泛化
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引用次数: 1
Psychological pressure and stress on employees during ‘unlock-1’: A case study “解锁1”期间员工的心理压力与压力:个案研究
Pub Date : 2020-01-01 DOI: 10.5958/2454-762x.2020.00005.0
Hanuman Sharma, Smriti Sharma
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引用次数: 1
Green Cargo Cycle 绿色货运循环
Pub Date : 2019-01-01 DOI: 10.5958/2454-762x.2019.00023.4
Vijay Kumar, Ankit Prasad, A. Singh, A. Jaiswal, A. Yadav
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引用次数: 0
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