As deepfake becomes more sophisticated, the demand for fake facial image detection is increasing. Although great progress has been made in detection, performance of most existing methods degrade significantly when these are applied to detect low-quality images disappearance key clues during compression process. In this work, we mine frequency domain and RGB information specifically improve comp...

Theconvolution neural network (CNN) has recently shown the good performance in hyperspectral image (HSI) classification tasks. Many CNN-based methods crop patches from original HSI as inputs. However, input cubes usually contain background and many pixels with different land-cover labels. Therefore, spatial context information on objects of same category is diverse cubes, which will weaken disc...

Abstract Stimulus-frequency otoacoustic emissions (SFOAEs) could be a useful tool for assessing hearing capabilities. Training and testing data were collected from 1084 ears of 725 subjects. Based on SFOAEs, this study applied Deep Residual Shrinkage Network to screen status. Results 10-fold cross-validation show that the model performed better than other recent literature in range 0.5 8 kHz, o...

Network residual resilience is a reliability parameter of the network after some nodes or edges of the network have been randomly eliminated from the network as a result of random attack . We consider networks which are monotone binary systems and demonstrate how the residual resilience can be calculated by means of cumulative signature (D-spectra), for three types of random attacks on network ...

clustering is an effective approach for managing nodes in wireless sensor network (wsn). a new method of clustering mechanism with using binary gravitational search algorithm (bgsa) in wsn, is proposed in this paper to improve the energy consumption of the sensor nodes.reducing the energy consumption of sensors in wsnsis the objective of this paper that is through selecting thesub optimum senso...

One of the parameters responsible for decreased water quality in a distribution system is temperature changes. This study was conducted to examine the effect of temperature on pH, turbidity, and residual chlorine in Sanandaj, Iran, Water Distribution System. The required water samples were taken from 85 stations during April to October 2014. Sampling was carried out over 6 months and twice per ...

This paper presents an energy-efficient loadbalancing algorithm for Wireless Sensor Networks. The algorithm specifies that only the nodes which have residual energy above a threshold can take part in routing, and that residual energy is to be updated at the highest opportunistic rate supported by the network. The algorithm was tested on and showed improvements to hierarchical data aggregation a...

state estimation is the foundation of any control and decision making in power networks. the first requirement for a secure network is a precise and safe state estimator in order to make decisions based on accurate knowledge of the network status. this paper introduces a new estimator which is able to detect bad data with few calculations without need for repetitions and estimation residual cal...

3D shape models that directly classify objects from 3D information have become more widely implementable. Current state of the art models rely on deep convolutional and inception models that are resource intensive. Residual neural networks have been demonstrated to be easier to optimize and do not suffer from vanishing/exploding gradients observed in deep networks. Here we implement a residual ...

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...