… required probes under network coding is significantly … network tomography stems from the
observation that, usually in typical networks, only a limited number of links exhibit large delays …

… loss and delay for selected flows on certain links, thus complementing the typical E2E
tomography model. This technique can potentially be applied in cloud and vehicular networks, as …

… event of network congestion. … Network (VANET) nodes. This paper proposes a new approach,
VANETomo, which uses statistical Network Tomography (NT) to infer transmission delays …

… , network performance tomography, abbreviated as network tomography in the sequel,
provides timely and accurate knowledge of the internal state of network elements (eg, delay/loss/…

… a network from binary measurements taken along selected paths. We consider the problem
of Boolean network tomography in … (eg, delays) of non-failed links under failures. For robust …

… delay inputs can be recovered from outputs [70]. Since the input and output of our framework
are density matrices, we define the d-delay … limited to quantum spin networks, but is more …

… Core tip: We developed and evaluated a deep learning-based convolutional neural network
(CNN) to classify focal liver lesions (FLLs) on multiphase computed tomography. The most …

… Using the link layer, we perform full state tomography of the generated states and achieve
… The communication delays between the quantum network controller and quantum device …

… We present the first demonstration of hydraulic tomography (HT) … (HRFS), including the
fracture network and connectivity through it. … reveal a 3D fracture network within the estimated K …

… Network Tomography is a general inference technique based on end-to-… network
characteristics such as link delays and link loss rates but also defective items. Network Tomography …