The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
With the development of information technology, software plays an increasingly important role in the process of social development. However, at the same time, the number of software vulnerabilities is growing, posing a threat to national security and social stability. Therefore, some scholars and research institutions are paying their attention to the study of software vulnerability. In this paper,...
The seru system is a new way of assembling products which is widely used in the electronics industry. Unlike the traditional assembly line, several small assembly units are constructed of which each is responsible for assembling an entire product. In this paper, the conversion process of assembly lines to seru systems (line-seru conversion) is studied. A cooperative co-evolution (CC) approach is proposed...
The Lamb wave approach in Structural Health Monitoring (SHM) mainly cares the defects detection. It relies on the analysis of signals for physical propagation. In this paper, a sparse representation approach for modeling the signal scattering in discretized monitoring area is proposed. The overcomplete dictionary can be determined explicitly by the Lamb wave propagation theory with columns reflecting...
Traditional task-based fMRI activation detection methods, such as the general linear model (GLM), assume that the fMRI signals of activated brain regions follow the external stimulus paradigm. Typically, these activated regions are detected independently in a voxel-wise fashion, and the interaction among voxels is nevertheless neglected. Despite the wide use and remarkable success of GLM, the temporal...
In this paper, a MV derivation method based on the idea of frame rate up-conversion (FRUC) is proposed. When a block is signaled as FRUC mode, the motion information of the block is derived without signaling. Moreover, derived MVs are refined at sub-block level for more accurate motion field. In addition, two matching methods, i.e., bilateral matching and template matching are supported to obtain...
Sparse representation has been proven to be a powerful tool for analysis and processing of signals and images. Whereas the most existing sparse representation methods are based on the synthesis model, this paper addresses sparse representation with the so-called analysis model. The ℓ1/2-norm regularizer theory in compressive sensing (CS) shows that the ℓ1/2-norm regularizer can yield stronger sparsity-promoting...
The Discrete Cosine Transform (DCT), and in particular the DCT type II, has been widely used for image and video compression. Although DCT efficiently approximates the optimal Karhunen–Loève transform under first-order Markov conditions with low complexity, the energy packing efficiency is still limited since a fixed transform cannot always capture the highly dynamic statistics of natural video content...
Recently, adaptive in-loop filter (ALF) for image/video coding has attracted increasing attention by its proven capability in improving coding performance. ALF is aiming to minimize the mean square error between original samples and decoded samples by using Wiener-based adaptive filter. Samples in a picture are classified into multiple categories and the samples in each category are then filtered...
As brain imaging data such as fMRI is growing explosively, how to reduce its size but not to lose much information becomes a pressing problem. To address this problem, this work aims to represent resting state fMRI (rs-fMRI) signals of a whole brain via a statistical sampling based sparse representation. Specifically, we improve the online dictionary learning and sparse coding algorithm by adding...
SHVC is the scalable extension of the latest video coding standard High Efficiency Video Coding (HEVC). Color Gamut Scalability (CGS) refers to a scalable use case in which base layer and enhancement layer have different color gamuts. In this case, special inter-layer prediction is needed to improve coding efficiency in SHVC. In this paper, a solution based on asymmetric 3D lookup table is presented...
SHVC is the scalable extension of the latest video coding standard High Efficiency Video Coding (HEVC) and spatial resampling process is inevitable module to support spatial scalability. This paper describes in details the resampling process, including both texture and motion data resampling in SHVC, and using experimental evidence, demonstrate their benefits in terms of coding efficiency.
In this paper, a phase-coded OFDM signal based on chaos theory for joint radar-communication systems is proposed. The signal has high time-frequency product and flexibility in waveform design. A new approach of getting phase codes from chaotic sequences is introduced, and the new codes own good correlation performance. The peak-to-mean envelope power ratio (PMEPR) and the auto-correlation function...
Advanced residual prediction (ARP) is an efficient tool for 3D video coding by exploiting the residual correlation between views. In ARP, the residual predictor could be efficiently produced by aligning the motion information at the current view for motion compensation in the reference view. On the other hand, such on-the-fly residual predictor derivation process increases the complexity significantly...
It is widely believed that working memory process involves large-scale functional interactions among multiple brain networks. However, network-level functional interactions across large-scale brain networks in working memory have been rarely explored yet in the literature. In this paper, we propose a novel framework for modeling network-level functional interactions in working memory based on our...
Cognitive processes, such as working memory, are widely considered as dynamic, and they are believed to involve complex functional information flows in large-scale brain networks. However, traditional voxel-based fMRI time series analysis methods, which essentially assume that the hemodynamic responses of involved brain regions follow the block or event-related paradigms, are limited in recognizing...
Functional brain mapping under naturalistic stimuli such as video watching has been receiving greater interest in recent years. We presented a sparse representation based data-driven strategy to explore consistent functional brain networks during free viewing of continuous video streams. Compared with the traditional independent component analysis (ICA) based method, the novelty of our method is taking...
Scalable extension of HEVC, a.k.a. SHVC, is being standardized by the Joint Collaborative Team on Video Coding (JCT-VC). SHVC employs one of the most important coding tools called interlayer prediction, in which. Reconstructed base layer pictures can be used as reference pictures to predict enhancement layer pictures. Therefore, how to efficiently generate interlayer reference pictures to improve...
Based on the structural connectomes constructed from diffusion tensor imaging (DTI) data, we present a novel framework to discover functional connectomics signatures from resting-state fMRI (R-fMRI) data for the characterization of brain conditions. First, by applying a sliding time window approach, the brain states represented by functional connectomes were automatically divided into temporal quasi-stable...
Physical (PHY) layer security has recently become a hot issue in wireless communication. In this paper, an approach to a generalized anti-eavesdropping space-time network coding (GAE-STNC) for cooperative communications is proposed to achieve the physical layer security and overcome the problem of imperfect synchronization while still guaranteeing full diversity. Based on the assumption of channel...
Seismic imaging can be formulated as a linear inverse problem where a medium perturbation is obtained via minimization of a least-squares misfit functional. The demand for higher resolution images in more geophysically complex areas drives the need to develop techniques that handle problems of tremendous size with limited computational resources. While seismic imaging is amenable to dimensionality...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.