Energy efficiency has been a hot research topic for many years and routing algorithms have proposed to improve energy prolong lifetime wireless sensor networks (WSNs). Since nodes close the sink usually need consume more forward data of its neighbours sink, they will exhaust quickly. These are called spot we call this phenomenon problem. In paper, an Enhanced Power Efficient Gathering in Sensor Information Systems (EPEGASIS) algorithm is alleviate spots problem from four aspects. Firstly,...

Brain-computer interfaces (BCIs) are used to translate brain activity signals into control for external devices. Currently, it is difficult BCI systems provide the multiple independent necessary multi-degree continuous of a wheelchair. In this paper, we address challenge by introducing hybrid that uses motor imagery-based mu rhythm and P300 potential brain-actuated simulated or real The objective greater number commands with increased accuracy user. Our paradigm allows user direction (left...

With the rapid growth of Internet technology, security concerns have risen, particularly with prevalence Deepfakes, a popular visual forgery technique. Therefore, there is necessary to research more powerful methods detect Deepfakes. However, many Convolutional Neural Networks-based detection struggle cross-database performance, often overfitting specific color textures. We observe that image noises can weaken influence textures and expose traces in noise domain. This because tampering...

Electrocardiographic (ECG) signal is essential to diagnose and analyse cardiac disease. However, ECG signals are susceptible be contaminated with various noises, which affect the application value of signals. In this paper, we propose an de-noising method using wavelet energy a sub-band smoothing filter. Unlike traditional threshold method, carries out processing for all coefficients, coefficients that require selected according other remain unchanged in proposed method. Moreover, The filter...

The electrocardiogram (ECG) signal can easily be affected by various types of noises while being recorded, which decreases the accuracy subsequent diagnosis. Therefore, efficient denoising ECG signals has become an important research topic. In paper, we proposed approach based on empirical mode decomposition (EMD), sample entropy, and improved threshold function. This method better remove noise provide diagnosis service for computer-based automatic medical system. work includes three stages...

The electroencephalogram (EEG) signal in the brain–computer interface (BCI) has suffered great cross-subject variability. BCI system needs to be retrained before each time it is used, which a waste of resources and time. Thus, difficult generalize fixed classification method for all subjects. Therefore, transfer learning proposed this article, combines XDAWN spatial filter Riemannian Geometry classifier (RGC), can achieve offline P300-speller paradigm. used enhanced P300 components raw as...

Advanced unsupervised learning techniques are an emerging challenge in the big data era due to increasing requirements of extracting knowledge from a large amount unlabeled heterogeneous data. Recently, many efforts have been done effectively capture information However, most them with huge time consumption, which obstructs their further application analytics scenarios, where enormous provided but real-time strongly demanded. In this paper, we address problem by proposing fast algorithm,...

In addition to helping develop products that aid the disabled, brain–computer interface (BCI) technology can also become a modality of entertainment for all people. However, most BCI games cannot be widely promoted due poor control performance or because they easily cause fatigue. this paper, we propose P300 brain–computer-interface game (MindGomoku) explore feasible and natural way play by using electroencephalogram (EEG) signals in practical environment. The novelty research is reflected...

Seam carving has been widely used in image resizing due to its superior performance avoiding distortion and deformation, which can maliciously be on purpose, such as tampering contents of an image. As a result, seam-carving detection is becoming crucially important recognize the authenticity. However, existing methods do not perform well accuracy especially when scaling ratio low. In this paper, we propose forensic approach based cooccurrence adjacent local binary patterns (LBPs), employs...

Automatic and precise polyp segmentation in colonoscopy images is highly valuable for diagnosis at an early stage surgery of colorectal cancer. Nevertheless, it still posed a major challenge due to variations the size intricate morphological characteristics polyps coupled with indistinct demarcation between mucosas. To alleviate these challenges, we proposed improved dual-aggregation network, dubbed Dua-PSNet, automatic accurate full-size prediction by combining both transformer branch fully...

The coma recovery scale-revised (CRS-R) behavioral scale is commonly used for the clinical evaluation of patients with disorders consciousness (DOC). However, since DOC generally cannot supply stable and efficient responses to external stimulation, results based on scales are not sufficiently accurate. In this paper, we proposed a novel brain-computer interface (BCI) 3D stereo audiovisual stimuli supplement object recognition in CRS-R. During experiment, subjects needed follow instructions...

Serving as a key step for applications of image processing, superpixel generation has been attracting increasing attention. RGB-D images are used pervasively in scenes reconstruction and representation, benefiting from their contained depth data. In this paper, we present novel framework generating superpixels focus on indoor scenes, based weighted geodesic driven metric that combines both color geometric information. particular, taking into account the unique structures scenarios, first...

A decision model of knowledge transfer is presented on the basis characteristics in a big data environment. This can determine weight transferred from another enterprise or provider. Numerous simulation experiments are implemented to test efficiency optimization model. Simulation experiment results show that when increasing provider, total discount expectation profits will increase, and cost be reduced. The calculated accordance with actual economic situation. provide useful support for enterprises

With the rapid development of mobile networks, there are more and application scenarios that require group communication. For example, in edge computing, communication can be used to transmit messages all members with minimal resources. The key directly affects security Most existing agreement protocols often flawed performance, scalability, forward or backward secrecy, single node failure. Therefore, this paper proposes a blockchain-based authentication dynamic protocol. our protocol, each...

Recent image inpainting methods have achieved remarkable improvements by using generative adversarial networks (GAN). Most of them been designed to produce plausible results from high-level semantic features only high-resolution (HR) supervision. However, because abundant details are lost in large holes, it is difficult simultaneously synthesize while preserving structural coherence HR space. Besides, the correlations between inside and outside missing region play a critical role...

Ultra-short-term electrical load forecasting is an important guarantee for the safety and efficiency of energy system operation. Temperature also factor affecting changes in electric load. However, different cases, impact temperature on will vary greatly, sometimes even lead to decrease accuracy. This often brings great difficulties researchers’ work. In order make more scientific use ultra-short-term forecasting, especially avoid negative influence this paper we propose method based weight...

Video frame interpolation (VFI) is of great importance for many video applications, yet it still challenging even in the era deep learning. Some existing VFI models directly exploit lightweight network frameworks, thus making synthesized in-between frames blurry and creating artifacts due to imprecise motion representation. The other typically depend on heavy model architectures with a large number parameters, preventing them from being deployed small terminals. To address these issues, we...

Sparse unmixing separates the pixel of hyperspectral images into a collection pure spectral signatures and associated fractional coefficients with complete library as priori, avoiding drawback inaccurate extraction endmember information from original image. As state-of-the-art sparse method, fast multiscale spatial regularization algorithm (MUA) consists two procedures, concerning on approximation image domain domain, respectively. However, it ignores inter-superpixel correlation that each...