Together with the fast advancement of Internet Things (IoT), smart healthcare applications and systems are equipped increasingly more wearable sensors mobile devices. These used not only to collect data but also, importantly, assist in daily activity tracking analyzing their users. Various human recognition (HAR) approaches enhance such tracking. Most existing HAR methods depend on exploratory case-based shallow feature learning architectures, which struggle correct when put into real-life...

The future emergence of disease-modifying treatments for dementia highlights the urgent need to identify reliable and easily accessible tools diagnosing Alzheimer's disease (AD). Electroencephalography (EEG) is a non-invasive cost-effective technique commonly used in study neurodegenerative disorders. However, specific alterations EEG biomarkers associated with AD remain unclear when using limited number electrodes. We studied pathological characteristics low-density data collected from 26...

With the proliferation of autonomous driving technology, traffic sign recognition is crucial for vehicle safety. However, this component vulnerable to adversarial attacks, highlighting need high-quality samples develop robust defense strategies. Existing methods generating such are often inefficient and not optimized signs. This paper addresses by: (i) analyzing characteristics signs, (ii) proposing a set evaluation metrics, (iii) presenting an scheme efficiently generate by selecting most...

Bone age is an important metric to monitor children’s skeleton development in pediatrics. As the of deep learning DL-based bone prediction methods have achieved great success. However, it also faces issue huge computation overhead features learning. Aiming at this problem, paper proposes a new assessment method based on Tanner-Whitehouse method. This extracts limited and useful regions for feature learning, then utilizes convolution layers learn representative these interesting regions....

This paper presents an enhanced historical document image binarization technique that makes use of background estimation and energy minimization. Given a degraded image, mathematical morphology is first carried out to compensate the with disk-shaped mask, whose size determined by stroke width transform (SWT). The Laplacian based segmentation then performed on image. Finally, post-processing further applied improve results. proposed has been extensively evaluated over recent DIBCO H-DIBCO...

We investigate axially symmetric localized bulging of an incompressible hyperelastic circular solid cylinder or tube that is rotating about its axis symmetry with angular velocity ω.For such a cylinder, the homogeneous primary deformation completely determined by axial stretch λ z , and it shown bifurcation condition simply given dω/dλ = 0 if resultant force F fixed.For shrink-fitted to rigid cylindrical spindle, azimuthal on inner surface specified again although now inhomogeneous.For this...

As an indicator of the optical characteristics perovskite materials, band gap is a crucial parameter that impacts functionality wide range optoelectronic devices. Obtaining material via labor-intensive, time-consuming, and inefficient high-throughput calculation based on first principles possible. However, it does not yield most accurate results. Machine learning techniques emerge as viable effective substitute for conventional approaches in prediction. This paper collected 201 pieces data...

Effective description of the brain function after stroke is key to accurate rehabilitation assessment, and it great significance explore nonlinear complexity characteristics from perspective complex networks. In this study, we investigated functional connectivity alterations by constructing a multilayer network model. Firstly, obtained multichannel EEG signals in different frequency bands (θ, α, β γ) during multi-joint compound movement. Furthermore, introduced weighted phase lag index...

Linear structures are a major source of false positives (FPs) in computer-aided detection clustered microcalcifications (MCs) mammograms. In this work, we investigate whether it is feasible to improve the performance MC by directly exploiting FPs associated with linear structures. We analyze cause and their characteristics an SVM detector, design structure procedure together dual-thresholding scheme separate from other tissue background mammogram. The proposed was demonstrated on set 200...

Intelligent environments enhanced the interactions between human and computers. People can seamlessly communicate with system via some event, such as gesture, voice, motion context. Anomaly event detection in temporal data, which collected sensor network of intelligent environments, is a challenging problem, particularly there have no direct priori knowledge anomaly events prominent patterns are known. In this paper, we propose technique extract data identify efficiently. This method based...

In robot visual servoing system, effective detected the region of interest area (ROI) in target images is first problem should be solved, but detection susceptible to an unstructured environment. this paper, instance segmentation network algorithm based on Mask Region Convolutional Neural Networks (Mask R-CNN) framework proposed for ROI image preprocessing. As technology can distinguish complex environmental information, so with advantage filter out message such as shape or similar image,...

The Internet of Things (IoT) has gained significant attention from industry as well academia during the past decade.The main reason behind this interest is capabilities IoT for seamlessly integrating classical networks and networked objects, hence allowing people to create an intelligent environment based on powerful integration. However, how extract useful information data produced by facilitate standard knowledge sharing among different systems are still open issues be addressed. In paper,...

Mammograms acquired with full-field digital mammography (FFDM) systems are provided in both "for-processing'' and "for-presentation'' image formats. For-presentation images traditionally intended for visual assessment by the radiologists. In this study, we investigate feasibility of using for-presentation computerized analysis diagnosis microcalcification (MC) lesions.We make use a set 188 matched mammogram pairs MC lesions from 95 cases (biopsy proven), which for-processing each lesion. We...

In this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The is representation method designed to support discovering, storing, reusing, improving, sharing among machines computing systems. We examine our classifying malicious vehicle control commands based on learning from valid behavior data simulator.

In this paper, we propose a Neural Knowledge DNA (NK-DNA)-based framework that is capable of learning from the car’s daily operations and reusing such learned knowledge in future tasks. The NK-DNA novel representation reasoning approach designed to support discovering, storing, reusing, improving, sharing among machines computing devices. We examine our for drivers’ classification based on their driving behaviors. experimental data are collected via smartphone sensors. initial results...

Restoration of hyperspectral images (HSI) is a crucial step in many potential applications as preprocessing step. Recently, low-rank tensor ring factorization was applied for HSI reconstruction, which has high-order tensors’ powerful and generalized representation ability. Although TR-based approaches with nuclear norm regularization achieved successful results restoring images, there still room improved approximation. In this article, we propose novel Auto-weighted Tensor Ring Factorization...

Polarimetric scattering information has a potential application for ship classification and identification in SAR image. This paper investigates the polarimetric of several types ships like hospital ship, LPD (Landing Platform Dock), container oil tanker. The characteristics every ship's pixel is got by using decompositions such as Pauli decomposition, SDH (Sphere-Dihedral-Helix) Freeman-Durden Moriyama Yamaguchi decomposition Cameron decomposition. Then are fused voting mechanism. Based on...

Digital watermarking is an efficient method to protect multimedia documents. Robust watermarks, which survive any change or alteration of the protected documents, are typically used for copyright protection. Fragile vulnerable a little alteration, content authentication. In paper, we propose hybrid joining robust and fragile watermark, thus combining protection As result this approach at same time resistant against tampering copy attacks. Our contribution setting up relationship between...