Traitor tracing is one kind of piracy deterrent schemes that helps trace the source of leaks when sensitive or proprietary data is made available to a large set of *** their natural properties,error correcting codes c...
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ISBN:
(纸本)0780397371
Traitor tracing is one kind of piracy deterrent schemes that helps trace the source of leaks when sensitive or proprietary data is made available to a large set of *** their natural properties,error correcting codes can be applied as traceability codes in such *** this paper,we present ReedSolomon codes as a kind of traceability codes and use list decoding algorithm to efficiently trace the traitors. We emphasize the conditions under which list decoding algorithm can be applied successfully for Reed-Solomon codes and the maximum numbers of users and traceable traitors for particular codes.
The principle and development of bio-inspired computer Immune System are surveyed, A computer network immune system model intending to remove the three hidden perils of computer security (Intrusion, Virus, Abnormity) ...
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A two-dimensional （2D） optimized nanotaper mode converter is presented and analyzed using the finite- difference time-domain （FDTD） method. It can convert the mode size in a silicon pillar waveguide （PWG） from 4...
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A two-dimensional （2D） optimized nanotaper mode converter is presented and analyzed using the finite- difference time-domain （FDTD） method. It can convert the mode size in a silicon pillar waveguide （PWG） from 4 μm to 1 μm over a length of 7 μm and achieve a transmission efficiency of 83.6% at a wavelength of 1.55 μm. The dual directional mode conversion of the nanotaper and its ability to perform mode compression and expansion are also demonstrated. The broadband with high transmittance is satisfied in this structure. Using this silicon-based nanotaper, mode conversion between integrated photonic devices can be more compact and efficient.
Medical data tampering has become one of the main challenges in the field of secure-aware medical data *** of normal patients’medical data to present them as COVID-19 patients is an illegitimate action that has been ...
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Medical data tampering has become one of the main challenges in the field of secure-aware medical data *** of normal patients’medical data to present them as COVID-19 patients is an illegitimate action that has been carried out in different ways ***,the integrity of these data can be *** detection is a method of detecting an anomaly in manipulated forged *** appropriate number of features are needed to identify an anomaly as either forged or non-forged data in order to find distortion or tampering in the original *** neural networks(CNNs)have contributed a major breakthrough in this type of *** has been much interest from both the clinicians and the AI community in the possibility of widespread usage of artificial neural networks for quick diagnosis using medical data for early COVID-19 patient *** purpose of this paper is to detect forgery in COVID-19 medical data by using CNN in the error level analysis(ELA)by verifying the noise pattern in the *** proposed improved ELA method is evaluated using a type of data splicing forgery and sigmoid and ReLU phenomenon *** proposed method is verified by manipulating COVID-19 data using different types of forgeries and then applying the proposed CNN model to the data to detect the data *** results show that the accuracy of the proposed CNN model on the test COVID-19 data is approximately 92%.
Nowadays,the COVID-19 virus disease is spreading *** are some testing tools and kits available for diagnosing the virus,but it is in a lim-ited *** diagnose the presence of disease from radiological images,auto-mated ...
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Nowadays,the COVID-19 virus disease is spreading *** are some testing tools and kits available for diagnosing the virus,but it is in a lim-ited *** diagnose the presence of disease from radiological images,auto-mated COVID-19 diagnosis techniques are *** enhancement of AI(Artificial Intelligence)has been focused in previous research,which uses X-ray images for detecting *** most common symptoms of COVID-19 are fever,dry cough and sore *** symptoms may lead to an increase in the rigorous type of pneumonia with a severe *** medical imaging is not suggested recently in Canada for critical COVID-19 diagnosis,computer-aided systems are implemented for the early identification of COVID-19,which aids in noticing the disease progression and thus decreases the death ***,a deep learning-based automated method for the extraction of features and classi-fication is enhanced for the detection of COVID-19 from the images of computer tomography(CT).The suggested method functions on the basis of three main pro-cesses:data preprocessing,the extraction of features and *** approach integrates the union of deep features with the help of Inception 14 and VGG-16 *** last,a classifier of Multi-scale Improved ResNet(MSI-ResNet)is developed to detect and classify the CT images into unique labels of *** the support of available open-source COVID-CT datasets that consists of 760 CT pictures,the investigational validation of the suggested method is *** experimental results reveal that the proposed approach offers greater performance with high specificity,accuracy and sensitivity.
Biological systems exhibit remarkable adaptation and robustness in the face of widely changing environments. While, current Network Security researches on bioinspired are all limited in the layer of human body - immun...
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Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC...
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Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC） scheme based on multi-user detection for the multiple unicast transmission is *** analysis and simulation results demonstrate that,compared with the conventional cooperation（CC） scheme and network-coded cooperation（NCC） scheme,CFNCC would obtain higher network throughput and consumes less time ***,a further investigation is made for the symbol error probability（SEP） performance of CFNCC scheme,and SEPs of CFNCC scheme are compared with those of NCC scheme in various scenarios for different signal to noise ratio（SNR） values.
This paper proposes an automatic structure overset grid method, which utilizes the hole-surface optimization with one-step searching, wall-surface grid oversetting, and dynamic overset grid approaches to achieve the h...
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This paper proposes an automatic structure overset grid method, which utilizes the hole-surface optimization with one-step searching, wall-surface grid oversetting, and dynamic overset grid approaches to achieve the high adaptability of overset grids for complex multi-body aircrafts. Specifically, based on the automatic structure overset grids, the method first solves the coupling of Navier-Stokes(N-S) unsteady flow equation and 6DOF motion equation, and establishes the multi-body collision model. Then, the numerical simulation of unsteady flow for complex aircrafts' multi-body separation, the simulation of multi-body separating trajectory and the separation safety analysis are accomplished. Thus, the method can properly handle practical engineering problems including the wing/drop tank separation, aircraft/mount separation, and cluster bomb projection. Experiments show that our numerical results match well with experimental results, which demonstrates the effectiveness of our methods in solving the multi-body separation problem for aircrafts with complex shapes.
Dear editor,The theoretical security of the quantum secure communication protocols can be proved with the law of quantum mechanics, when the classical communication protocols’ security can only depend on the computat...
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Dear editor,The theoretical security of the quantum secure communication protocols can be proved with the law of quantum mechanics, when the classical communication protocols’ security can only depend on the computational complexity [1, 2]. Based on the quantum BB84 protocol [3] and the quantum MEQKD protocol [4], we present a QKD (quantum key distribution) protocol based on a singleparticle and an EPR (Einstein-Podolsky-Rosen)entanglement pair, which is called the quantum TEQKD protocol. Compared with MEQKD,
Soil is the major source of infinite lives on Earth and the quality of soil plays significant role on Agriculture practices all ***,the evaluation of soil quality is very important for determining the amount of nutrie...
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Soil is the major source of infinite lives on Earth and the quality of soil plays significant role on Agriculture practices all ***,the evaluation of soil quality is very important for determining the amount of nutrients that the soil require for proper *** present decade,the application of deep learning models in many fields of research has created greater *** increasing soil data availability of soil data there is a greater demand for the remotely avail open source model,leads to the incorporation of deep learning method to predict the soil *** that concern,this paper proposes a novel model called Improved Soil Quality Prediction Model using Deep Learning(ISQP-DL).The work considers the chemical,physical and biological factors of soil in particular area to estimate the soil ***,pH rating of soil samples has been collected from the soil testing laboratory from which the acidic range has been categorized through soil test and the same data has been taken as input to the Deep Neural Network Regression(DNNR)***,soil nutrient data has been given as second input to the DNNR *** utilizing this data set,the DNNR method is used to evaluate the fertility rate by which the soil quality has been *** training and testing,the model uses Deep Neural Network Regression(DNNR),by utilizing the *** results show that the proposed model is effective for SQP(Soil Quality Prediction Model)with efficient good fitting and generality is enhanced with input features with higher rate of classification *** results show that the proposed model achieves 96.7%of accuracy rate compared with existing models.
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