A method is introduced for determination of a vector network analyzer’s calibration residual errors for measurement of the reflection coefficient. The method utilizes unscented Kalman filtering and spline interpolation time domain techniques. All three residual errors are calculated by processing the measured reflection coefficient of a single verification device, such as an air line terminated...

Road extraction from aerial images has been a hot research topic in the field of remote sensing image analysis. In this letter, a semantic segmentation neural network which combines the strengths of residual learning and U-Net is proposed for road area extraction. The network is built with residual units and has similar architecture to that of U-Net. The benefits of this model is two-fold: firs...

In this paper we present a new ensemble method, called Boosted Residual Networks, which builds an ensemble of Residual Networks by growing the member network at each round of boosting. The proposed approach combines recent developements in Residual Networks a method for creating very deep networks by including a shortcut layer between different groups of layers with the Deep Incremental Boostin...

In this paper, a new hybrid routing protocol is presented for low power Wireless Sensor Networks (WSNs). The new system uses an integrated piezoelectric energy harvester to increase the network lifetime. Power dissipation is one of the most important factors affecting lifetime of a WSN. An innovative cluster head selection technique using Cuckoo optimization algorithm has been used in the desig...

In this project, we tackle the problem of depth estimation from single image. The mapping between a single image and the depth map is inherently ambiguous, and requires both global and local information. We employ a fully convolutional architecture, which first extracts image feature by pretrained ResNet-50 network. We do transfer learning by replacing the fully connected layer of ResNet-50 wit...

A test system for water distribution was used to evaluate the stability and effectiveness of three residual disinfectants--free chlorine, combined chlorine, and chlorine dioxide--when challenged with a sewage contaminant. The test distribution system consisted of the street main and internal plumbing for two barracks at Fort George G. Meade, MD. To the existing pipe network, 152 m (500 ft) of 1...

Toxoplasma gondii proliferates and organizes within a parasitophorous vacuole in rosettes around a residual body and is surrounded by a membranous nanotubular network whose function remains unclear. Here, we characterized structure and function of the residual body in intracellular tachyzoites of the RH strain. Our data showed the residual body as a body limited by a membrane formed during prol...

in this paper, the role of molecular diffusion in mobilization of waterflood residual oil is examined. a moving mesh method is applied to solve the moving interface problem of residual oil blobs swelling by co2 diffusion through a blocking water phase. the results of this modeling are compared with experimental results of a 2d glass micromodel experiment. although, the solution method is applie...

Deep learning (DL) based semantic segmentation methods have been providing state-of-the-art performance in the last few years. More specifically, these techniques have been successfully applied to medical image classification, segmentation, and detection tasks. One deep learning technique, U-Net, has become one of the most popular for these applications. In this paper, we propose a Recurrent Co...

Most traditional algorithms for compressive sensing image reconstruction suffer from the intensive computation. Recently, deep learning-based reconstruction algorithms have been reported, which dramatically reduce the time complexity than iterative reconstruction algorithms. In this paper, we propose a novel Deep Residual Reconstruction Network (DRNet) to reconstruct the image from its Compress...