In recent years, a chaotic system is considered as an important pseudo-random source to number generators (PRNGs). This paper proposes PRNG based on modified logistic system. with fixed parameters convergent and its behavior analyzed proved. order improve the complexity randomness of PRNGs, parameter denoted by floating point numbers generated confused rearranged increase key space reduce possibility exhaustive attack. It hard speculate because there no statistical characteristics infer...

Multi-modal entity alignment (MMEA) aims to identify equivalent entities between two multi-modal knowledge graphs for integration. Unfortunately, prior arts have attempted improve the interaction and fusion of information, which overlooked influence modal-specific noise usage labeled unlabeled data in semi-supervised settings. In this work, we introduce a Pseudo-label Calibration Entity Alignment (PCMEA) way. Specifically, order generate holistic representations, first devise various...

In high-speed mobile scenarios characteristic of the Fifth Generation Mobile Networks (5G) environment, user video experience may be compromised due to concurrent access by numerous users and frequent base station transitions. Addressing this issue, study introduces a cross-layer resource allocation model that integrates environmental awareness is tailored for exigencies networks. The paper delves into challenges engendered rapid mobility extensive within 5G environment critiques constraints...

With the rapid development of remote sensing (RS) observation technology over recent years, high-level semantic association-based cross-modal retrieval RS images has drawn some attention. However, few existing studies on have addressed issue mutual interference between features caused by “multi-scene semantics”. Therefore, we proposed a novel cross-attention (CA) model, called CABIR, based regional-level for text-image retrieval. This technique utilizes CA mechanism to implement information...

This paper proposes an Agile Aggregating Multi-Level feaTure framework (Agile Amulet) for salient object detection. The Amulet builds on previous works to predict saliency maps using multi-level convolutional features. Compared works, employs some key innovations improve training and testing speed while also increase prediction accuracy. More specifically, we first introduce a contextual attention module that can rapidly highlight most objects or regions with pyramids. Thus, it effectively...

Face identification is an important research topic in artificial intelligence and it has wide application civilian law enforcement scenarios that require reliable biometric identification. However, the deployment of face systems raised serious privacy concerns about abuse users' images. In this paper, we propose efficient privacy-preserving protocol based on fully homomorphic encryption garbled circuit. Our work first guarantees images such server cannot learn any information images, access...

Compared with traditional anomaly analysis, intelligent connected vehicle (ICV) data validity analysis is faced a variety of anomalies, including sensor driving behavior malicious tampering, and so on, which eventually leads to anomalies in the data. How integrate moving characteristics, style, traffic flow conditions provide an effective detection method has become new problem field networked vehicles. Based on ICV data, particle swarm optimization algorithm (TE-PSO-SVM) was proposed by...

As High-speed rail becomes a popular way to travel, users have high demand for streaming services. In scenarios, move fast and base stations handover frequently. Most of the existing network bandwidth prediction algorithms bitrate selection are proposed based on low-speed scenarios. These difficult adapt high-speed mobile To solve this problem, paper proposes an adaptive media transmission method using edge computing, status cross-layer information (EHCI) in 5G environment. Firstly, QoE...

In recent years, there has been a growing interest in remote sensing image-text cross-modal retrieval due to the rapid development of space information technology and significant increase image data volume. One approach that shown promising results natural images is multimodal fusion encoding method. However, have unique characteristics make task challenging. Firstly, semantic features are fine-grained, meaning they can be divided into multiple basic units expression. Additionally, these...

The Additive Increase and Multiplicative Decrease (AIMD) congestion control algorithm of TCP protocol deployed in the end systems Random Early Detection (RED) queue management scheme intermediate contribute to Internet stability integrity. Previous research based on fluid-flow model analysis indicated that an AIMD/RED system may not be asymptotically stable when feedback delays or link capacity becomes large [3]. However, as long operates near its desired equilibrium, small oscillations are...

In this paper, a method for distance measurement only using single target image without any internal camera parameters is developed. The mapping relation between row pixel values and the actual distances established by detecting locating corners on reference image. information extracted in real time combining moving detection based Gaussian mixture model (GMM) shadow elimination Hue-Saturation-Intensity (HSI) color space. has simple calibration procedure with image, which suitable practical...

Abstract Fine-Grained Visual Categorization (FGVC) aims to distinguish between extremely similar subordinate-level categories within the same basic-level category. Existing research has proven great importance of discriminative features in FGVC but ignored contributions for correct classification from other features, and extracted always contain more information about obvious regions less subtle regions. In this paper, firstly, a novel module named forcing is proposed force network extract...

Flight control systems (FCSs) are safety-critical systems, which require high reliability requirements. Probabilistic model checking techniques use mathematical reasoning to check quantitative properties and generate accurate value. This paper combines the probabilistic analysis for FCSs, so that it is possible make full of verification solving The FCS described as Continuous-Time Markov Chains (CTMCs), a commonly used model, using PRISM language. Each software component device with behavior...

Liver segmentation is a basic and indispensable function in systems of computer aided liver surgery for volume calculation, operation designing risk evaluation. Traditional manual very time consuming because the complicated contours big amount images. For increasing efficiency clinical work, this paper, fully-automatic method was proposed to segment from multi-phase contrast-enhanced computed tomography (CT) As an advanced region growing method, we applied various pre- post-processing get...

In recent years, there has been a growing interest in remote sensing image–text cross-modal retrieval due to the rapid development of space information technology and significant increase volume image data. Remote images have unique characteristics that make task challenging. Firstly, semantics are fine-grained, meaning they can be divided into multiple basic units semantic expression. Different combinations expression generate diverse text descriptions. Additionally, these exhibit...

Due to the swift growth in scale of remote sensing imagery, scholars have progressively directed their attention towards achieving efficient and adaptable cross-modal retrieval for images. They also steadily tackled distinctive challenge posed by multi-scale attributes these However, existing studies primarily concentrate on characterization features, neglecting comprehensive investigation complex relationship between targets semantic alignment with text. To address this issue, study...

Liver tumor, one of the most wide-spread diseases, has a very high mortality in China. To improve success rates liver surgeries and life qualities such patients, we implement an interactive surgery planning system based on contrastenhanced CT images. The consists five modules: pre-processing, segmentation, modeling, quantitative analysis simulation. Graph Cuts method is utilized to automatically segment anatomical prior knowledge that biggest organ almost homogeneous gray value. supports...

Multi-modal entity alignment (MMEA) aims to identify equivalent entities between two multi-modal knowledge graphs for integration. Unfortunately, prior arts have attempted improve the interaction and fusion of information, which overlooked influence modal-specific noise usage labeled unlabeled data in semi-supervised settings. In this work, we introduce a Pseudo-label Calibration Entity Alignment (PCMEA) way. Specifically, order generate holistic representations, first devise various...

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In this study, the ill-conditioning of iterative method for nonlinear models is discussed. Due to effectiveness ridge estimation ill-conditioned problems and lack a combination H-K formula with method, improvement LM algorithm studied in paper. Considering least squares, an improved based on proposed image distortion correction using self-calibration. Three finite difference methods are used approximate Jacobian matrix, calculate damping factor each iteration. The Brown model, quadratic...

In general, remote sensing images depict intricate scenes. cross-modal retrieval tasks involving images, the accompanying text includes numerus information with an emphasis on mainly large objects due to higher attention, and features from small targets are often omitted naturally. While conventional vision transformer (ViT) method adeptly captures regarding global targets, its capability extract of is limited. This limitation stems constrained receptive field in ViT’s self-attention layer,...