In this paper, we propose taking into account the architectural features of the processor at the stage of constructing the numerical method itself. This idea is illustrated by the example of the synthesis of a new dif...
In this paper, we propose taking into account the architectural features of the processor at the stage of constructing the numerical method itself. This idea is illustrated by the example of the synthesis of a new difference scheme for the heat conduction equation, which has traditionally been the object of testing innovations in the theory of difference schemes. The architectural feature hierarchical structure of the computer memory chosen led to considerable communication costs even when a single hardware computational flow was used for organising the calculations. This feature is accounted for in computational linear algebra by using block algorithms, and in the theory of difference schemes, by using the technique of programming 'tiling'. However, for the two-layer difference schemes of block algorithms for solving grid equations, prior to the proposed work, it was not known because of the impossibility of organising block calculations by using the existing schemes. Here, we propose a new method of constructing two-layer difference schemes and a mixed scheme with a shift as an example of the application of this method. In the course of the experiments, a five-fold acceleration of calculations according to this scheme was demonstrated relative to the traditional explicit model, with the same computational complexity.
Since Web 2.0 be announced, social media services become popular in these years. Due to multiple relationships existing simultaneously among the members of the community in real world, to detect all overlapping commun...
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ISBN:
(纸本)9781509040179
Since Web 2.0 be announced, social media services become popular in these years. Due to multiple relationships existing simultaneously among the members of the community in real world, to detect all overlapping communities from complex networks is becoming an important issue. The paper proposed a novel overlapping community detection method by seed set expansion with local cluster coefficient (LCC). In addition, the detection result will be evaluated by measuring the cohesion quality of communities.
This paper introduces a new way of interaction in JFCS Software where users can view and navigate easily between different combinations of fuzzy colors and pixels in images. Fuzzy colors allow introducing semantics in...
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ISBN:
(纸本)9781509060344
This paper introduces a new way of interaction in JFCS Software where users can view and navigate easily between different combinations of fuzzy colors and pixels in images. Fuzzy colors allow introducing semantics in the description of color by using linguistic labels, filling the semantic gap between the color representation in computers and the subjective human perception. JFCS (Java Fuzzy Color Space) Software, an open source (GPLv3) software with a user-friendly interface, provides an easy framework to design and automatically obtain customized fuzzy color spaces on the basis of an approach proposed by the authors in previous work. This new functionality in JFCS endows it with a very useful tool to visually analyze correspondences between pixels and fuzzy colors in images. Users can obtain combined mapped images where regions, corresponding to a combination of color concepts, are highlighted. In addition, users can describe and interact, in a simple and visual way, with colors present on a given image in terms of fuzzy colors.
The evolution of the video surveillance systems generates questions concerning protection of individual privacy. In this paper, we design ASePPI, an Adaptive Scrambling enabling Privacy Protection and Intelligibility ...
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ISBN:
(纸本)9781538607336
The evolution of the video surveillance systems generates questions concerning protection of individual privacy. In this paper, we design ASePPI, an Adaptive Scrambling enabling Privacy Protection and Intelligibility method operating in the H.264/AVC stream with the aim to be robust against de-anonymization attacks targeting the restoration of the original image and the re-identification of people. The proposed approach automatically adapts the level of protection according to the resolution of the region of interest. Compared to existing methods, our framework provides a better trade-off between the privacy protection and the visibility of the scene with robustness against de-anonymization attacks. Moreover, the impact on the source coding stream is negligible.
The proceedings contain 43 papers. The topics discussed include: compressive sensing based interference cancellation for ultra dense network;performance analysis of computer virus detection from binary code using ense...
ISBN:
(纸本)9781450353847
The proceedings contain 43 papers. The topics discussed include: compressive sensing based interference cancellation for ultra dense network;performance analysis of computer virus detection from binary code using ensemble classifier;balance between performance and security in IPI-based key schemes using heartbeats;research for building high performance communication service based on Netty protocol in smart health;hybrid scheme to solve finite precision in digital chaotic random number generator;maximum likelihood indoor localization of a WiFi radio transmitter with structural knowledge;SAAP: a state-aware adaptive prediction strategy for CPU load of desktops;deep Q-learning to preserve connectivity in multi-robot systems;nature as a source for inspiring new optimization algorithms;structural damage detection of a concrete based on the autoregressive all-pole model parameters and artificial intelligence techniques;fire boundary detection method using a unique structure from motion for non-rigid bodies algorithm (SFM-NRBA);brightness preserving satellite image contrast enhancement using bacterial foraging algorithm;generalized multi-Bernoulli filters for track-before-detect of objects from image observations;amalgamation of video description and multiple object localization using single deep learning model;and time-domain processing for exact background clutter extraction and reduction in RCS measurement.
Real-time computing system attracts more and more attention in both academic researches and industrial applications. One of the real-time computing systems, Apache Storm, because of its characteristics of stream proce...
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ISBN:
(纸本)9781538629345
Real-time computing system attracts more and more attention in both academic researches and industrial applications. One of the real-time computing systems, Apache Storm, because of its characteristics of stream processing and high fault tolerance, is widely used for machine learning and distributed remote process call (RPC), etc. However, the existing approaches to decompose topology for Storm cannot ensure an optimized performance. In this paper, we propose an adaptive topology decomposition algorithm for Storm where topology decomposition based on cluster status and components of topology can be performed at run time. We have evaluated the processing performance and the load balancing of the algorithm. The evaluation results indicate that the proposed algorithm has better performances on task processing and load-balancing than the existing algorithms.
This study investigates the impulsive stabilization problem of positive systems with time-varying delays. A new time-varying weighted copositive Lyapunov function is constructed. Sufficient stabilization conditions on...
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ISBN:
(纸本)9781538626795
This study investigates the impulsive stabilization problem of positive systems with time-varying delays. A new time-varying weighted copositive Lyapunov function is constructed. Sufficient stabilization conditions on the upper and lower bounds of impulsive intervals are established using the convex combination technique. Under the proposed conditions, the positivity and exponential stability of the corresponding closed-loop system can be guaranteed. Based on the linear programming (LP) technique, a systematic design procedure is presented for the impulsive controller. Finally, a numerical example is provided to demonstrate the effectiveness of the theoretical result.
With the integration of face recognition technology into important identity applications, it is imperative that the effects of facial aging on face recognition performance are thoroughly understood. As face recognitio...
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ISBN:
(纸本)9781538607336
With the integration of face recognition technology into important identity applications, it is imperative that the effects of facial aging on face recognition performance are thoroughly understood. As face recognition systems evolve and improve, they should be periodically re-evaluated on large-scale longitudinal face datasets. In our study, we evaluate the performance of two state-of-the-art commercial off the shelf (COTS) face recognition systems on two large-scale longitudinal datasets of mugshots of repeat offenders. The largest of these two datasets has 147,784 images of 18,007 subjects with an average of 8 images per subject over an average time span of 8.5 years. We fit multi-level statistical models to genuine comparison scores (similarity between images of the same face) from the two COTS face matchers. This allows us to analyze the degradation in recognition performance due to elapsed time between a probe (query) and its enrollment (gallery) image. We account for face image quality to obtain a better estimate of trends due to aging, and analyze whether longitudinal trends in genuine scores differ by subject gender and race. Based on the results of our statistical model, we infer that the state-of-the-art COTS matchers can verify 99% of the subjects at a false accept rate (FAR) of 0.01% for up to 10.5 and 8.5 years of elapsed time. Beyond this time lapse of 8.5 years, there is a significant loss in face recognition accuracy. This study extends and confirms the findings of earlier longitudinal studies on face recognition.
The 3D reconstruction can facilitate the diagnosis of liver disease by making the target easier to identify and revealing the volume and shape much better than 2D imaging. In this paper, in order to realize 3D reconst...
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ISBN:
(纸本)9783319700939;9783319700922
The 3D reconstruction can facilitate the diagnosis of liver disease by making the target easier to identify and revealing the volume and shape much better than 2D imaging. In this paper, in order to realize 3D reconstruction of liver parenchyma, a series of pretreatments are carried out, including windowing conversion, filtering and liver parenchyma extraction. Furthermore, three kinds of modeling methods were researched to reconstruct the liver parenchyma containing surface rending, volume rendering and point rendering. The MC (marching cubes) algorithm based on 3D region growth is proposed to overcome the existence of a large number of voids and long modeling time for the contours of traditional MC algorithms. Simulation results of the three modeling methods show different advantages and disadvantages. The surface rendering can intuitively image on the liver surface modeling, but it cannot reflect the inside information of the liver. The volume rendering can reflect the internal information of the liver, but it requires a higher computer performance. The point rendering modeling speed is quickly compared to the surface rendering and the volume rendering, whereas the modeling effect is rough. Therefore, we can draw a conclusion that different modeling methods should be selected for different requirements.
Unmanned aerial vehicles (UAVs)-based environmental studies are gaining space in recent years due to their advantages of minimal cost, flexibility, and very high spatial resolution. Researchers can acquire imagery acc...
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Unmanned aerial vehicles (UAVs)-based environmental studies are gaining space in recent years due to their advantages of minimal cost, flexibility, and very high spatial resolution. Researchers can acquire imagery according to their schedule and convenience with the option of alternating the sensors working in visible, infrared, and microwave wavelengths. The recent developments in UAVs and in the associated image-processing techniques extend the fields of UAVs application. Inherent geometric deformation of UAVs images inevitably leads to burgeoning interest in exploring the geographical registration techniques of UAVs images preprocessing. However, atmospheric correction had been generally neglected due to the low altitudes of UAVs platforms. The path radiance of low-latitude atmosphere misleads the reflectance of target objects. Thus, a valid atmospheric correction is essential in the cases where vegetation indices (VIs) are adopted in vegetation monitoring. The off-the-shelf atmospheric correction algorithms adopted in satellite-based remote sensing are typically ill-suited for UAVs-based images due to the distinctly different altitudes and radiation transfer modes. This article identified the effect of atmospheric attenuation for spectral data collected by UAVs sensors of different altitudes and developed a physical-based atmospheric correction algorithm of UAVs images. Field-measured reflectance spectrum was essential in modelling. A sunny and dry day and a flat terrain were the two prerequisites to ensure the general application of the developed algorithm. A case study was subsequently carried out to verify the utility of the developed algorithm, and the results showed that VIs based on the UAVs images of different altitudes had a similar ability in vegetation assessment as groundbased recordings. However, the assessment accuracy could be clearly improved by using the developed atmospheric correction algorithm.
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