194 publications from this institution
By using integral operator, some oscillation criteria for second order elliptic differential equation$$ \sum^d _{i,j=1} D_i[A_{ij}(x)D_jy]+ q(x)f(y)=0, \;x \in \Omega\qquad \eqno{(E)} $$are established. The results obtained here can be regarded as the extension of the well-known Kamenev theorem to Eq.$(E)$.
As computer networks keep growing at a high rate, achieving confidentiality, integrity, and availability of the information system is essential. Intrusion detection systems (IDSs) have been widely used to monitor and secure networks. The two major limitations facing existing intrusion detection systems are high rates of false-positive alerts and low detection rates on zero-day attacks. To overcome these problems, we need intrusion detection techniques that can learn and effectively detect intrusions. Hybrid methods based on machine learning techniques have been proposed by different researchers. These methods take advantage of the single detection methods and leverage their weakness. Therefore, this paper reviews 111 related studies in the period between 2012 and 2022 focusing on hybrid detection systems. The review points out the existing gaps in the development of hybrid intrusion detection systems and the need for further research in this area.
In order to obtain the position of thunderstorm cloud in real time and make it possible to track the thunderstorm cloud motion, a method is proposed for tracking the moving path of thunderstorm cloud, with the aid of the three‐dimensional atmospheric electric field apparatus (AEFA). According to the method of images, we establish a spatial model for tracking the moving path. Based on the model, we define the dynamic parameters of thunderstorm cloud position. Subsequently, to realize the moving path tracking of thunderstorm cloud, its coordinates are associated with the time points. Besides, we use the relationship between electric field component measurement error, horizontal angle, elevation angle, and the tracking accuracy to analyze the tracking performance. Finally, a fusion system combining an electric field measurement unit, electric field calibration unit, and permittivity measurement unit is designed to meet the actual needs. The results show that the method can accurately track the thunderstorm cloud moving path and has a better effect. In addition, the method can also be combined with a radar map, thus better predicting the development of the thunderstorm cloud.
For the serious problems of lighting waste in current universities and other public places,this paper designed an intelligent lighting control system.Taking AT89S52 microcontroller integrated circuit as master control,it used light intensity measurement module,sound intensity measurement module,stepping motor rotationpyroelectric infrared sensor modules to constitute a multi-way detection system.The innovative use of multi-sensor complementary probes,complemented by stepper motor rotation realization pyroelectric infrared sensor dynamic detection.After debugged,it certifies that the programme is possible,and it has high practical value.
A combination of the sample entropy and the artificial intelligence (AI) would hopefully bring progress to the smart thunderstorm detection. In this article, we establish an entropy-based thunderstorm point charge imaging system with data clustering, in which data are ultrareliable and have low-latency 3-D atmospheric electric field (3DAEF) values. In particular, a high-resolution 3DAEF sensor with the single-axis rotary vane is developed to measure the time sequence signal of the 3DAEF. The signal is first denoised and then decomposed into multiple groups of branch data with the same number of samples. In order to break through the limitations of existing clustering rules, we propose a 3DAEF signal reconstruction method based on entropy intervals. By reconstructing the branch data, multiple time-scale data are formed. Finally, the curve fitting of the data is performed to realize the imaging after clustering the data. Experimental results suggest that the imaging error after the clustering is reduced by about 2.33%. Comparisons with radar charts show that the proposed system can effectively image the point charge moving paths.
Swing-type device and generating system is a new type of energy converting system. It converts water flow energy into electricity by the blade's swinging in the flowing water. The device is composed of supporting system,blade,blade motion organ,collision and return organ,transition system and electricity generating system. The hydrodynamic model of blade is established based on the stream tube!method. The dynamic model of system is established according to the institutional characteristics of the system. The dynamic characteristics of the system are analyzed by simultaneously solving the coupled hydrodynamic model and kinetic equations. The comparison between numerical results and experimental results proves the effectiveness of the model. The research results are of importance to the design of swing-type flow energy generation system.
Glioblastoma contains a hierarchy of stem-like cancer cells, but how this hierarchy is established is unclear. Here, we show that asymmetric Numb localization specifies glioblastoma stem-like cell (GSC) fate in a manner that does not require Notch inhibition. Numb is asymmetrically localized to CD133-hi GSCs. The predominant Numb isoform, Numb4, decreases Notch and promotes a CD133-hi, radial glial-like phenotype. However, upregulation of a novel Numb isoform, Numb4 delta 7 (Numb4d7), increases Notch and AKT activation while nevertheless maintaining CD133-hi fate specification. Numb knockdown increases Notch and promotes growth while favoring a CD133-lo, glial progenitor-like phenotype. We report the novel finding that Numb4 (but not Numb4d7) promotes SCF(Fbw7) ubiquitin ligase assembly and activation to increase Notch degradation. However, both Numb isoforms decrease epidermal growth factor receptor (EGFR) expression, thereby regulating GSC fate. Small molecule inhibition of EGFR activity phenocopies the effect of Numb on CD133 and Pax6. Clinically, homozygous NUMB deletions and low Numb mRNA expression occur primarily in a subgroup of proneural glioblastomas. Higher Numb expression is found in classical and mesenchymal glioblastomas and correlates with decreased survival. Thus, decreased Numb promotes glioblastoma growth, but the remaining Numb establishes a phenotypically diverse stem-like cell hierarchy that increases tumor aggressiveness and therapeutic resistance.
The relationship between smart devices and human beings is one of the research hotspots of the Fourth Industrial Revolution (4IR). In this regard, we explored the practical relationship between the 3D electric field components measured by the smart 3D atmospheric electric field apparatus (AEFA) and the thunderstorm activity from the perspective of the observer. Especially, in the application of AEFA, a smart calibration method is proposed to solve the problem of inconvenient thunderstorm data acquisition. Firstly, in order to obtain the thunderstorm charge position from the observation angle of the apparatus, this paper establishes a 3D electric field measurement model. According to the mirror method theory, we further obtain the charge potential distribution at AEFA. Then, the electric field components are derived by using the potential distribution formula with permittivity. In addition, based on the vector relation of the model, the thunderstorm charge azimuth and elevation angles are obtained. Finally, after the establishment of a new coordinate system, the calibration of charge localization is carried out, based on the observation point. Meanwhile, a preliminary solution is given to the problem that the elevation of the apparatus position affects the localization performance. Results show that the method matches the data of radar map and microphone array, which reflects the advantages of the method. Besides, this method can be used not only in sound source localization but also in AI thunderstorm monitoring system to realize a big data net observation.
A new concept of the inclusion measure for intuitionistic fuzzy sets is proposed by the axiomatic definition. Also, the distance measures, similarity measures and information entropy are recalled and summarized. Most of important, some relationships among distance measure, information entropy, and inclusion measure of IFSs are then investigated. Finally, we obtain some important theorems by which the distance measure, information entropy and inclusion measure of IFSs and interval-valued intuitionistic fuzzy set can be deduced based on their corresponding axiomatic definitions. Simultaneously, some new formulae to calculate distance measure, information entropy and inclusion measure of IFSs are presented.
We present a theoretical calculation of the dependence of reflectivity R pp of the improved fully leaky waveguide geometry, which comprises pyramid, matching fluid, and strongly anchored hybrid-aligned nematic liquid crystal (NLC) cell on the internal angle.The calculation is based on the multi-layer optical theory and the elastic theory of liquid crystals.For different sums of flexoelectric coefficients e 11 and e 33 , the curve of R pp moves a distance to the left or the right relative to the case of ignoring the flexoelectric effect and the distance of the movement varies with different flexoelectric coefficients.Consequently, the sum of flexoelectric coefficients can be explored by measuring the distance of the movement.
A crisis of amplitude control can occur when a system is multistable. This paper proposes a new chaotic system with a line of equilibria to demonstrate the threat to amplitude control from multistability. The new symmetric system has two coefficients for amplitude control, one of which is a partial amplitude controller, while the other is a total amplitude controller that simultaneously controls the frequency. The amplitude parameter rescales the basins of attraction and triggers a state switch among different states resulting in a failure of amplitude control to the desired state.
Based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) theory, a new adaptive hybrid algorithm for sea clutter denoising is proposed. The chaotic sea clutter signals are decomposed into several intrinsic modal functions (IMF) which start from high-frequency scales to low-frequency scales by using CEEMDAN. According to the relationship between the pretreatment threshold layer and the maximum cross correlation coefficient of the original signal and each IMF corresponding the layer, the proposed algorithm can independently select the wavelet threshold denoising to pretreat. After the pretreatment of original signals, we continue to decompose the signal by CEEMDAN. And later, according to the relationship between the first local minimum corresponding the layers of two adjacent critical IMFs identified by the cross correlation coefficients of the original signal and each IMF, the proposed algorithm adaptively selects the IMFs which need to be filtered. Finally, the IMFs after filtering are reconstructed into a new signal. Rossler, Lorenz system and the measured sea clutter data were selected as examples to study, the result shows that: under the condition of low noise (SNR ≥ 5dB) and high noise (SNR ≤ 0dB), the proposed algorithm can decrease the root mean square error by at least 57% and 72% compared with wavelet threshold denoising etc, the signal to noise ration increased by 3.18-5.64db and 5.73-7.45db. Moreover, the root mean square error after sea clutter signal denoising can be reduced by one order of magnitude, reaching 0.0006147 while the model before denoising only reach 0.0084, which shows that the proposed algorithm is effective for sea clutter signal denoising.
As an important factor in fine thunderstorm detections, a multi-time scale thunderstorm monitoring, warning and imaging system is proposed in this paper. The first computing phase involves a decomposition, classification, denoising and reconstruction of the atmospheric electric field signals (AEFSs), collected by a self-made three-dimensional AEF apparatus, based on autocorrelation characteristics and Fuzzy <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$C$</tex-math></inline-formula> -Means (FCM). Secondly, FCM classifies the equally divided AEFS components. A scale reconstruction rule is put forward and applied to obtain multi-time scale AEF branch data, according to the component temporal continuity in the same class. A corresponding scale correction strategy is then proposed. Thunderstorm point charge coordinate results are calculated by using branch data, and noise points contained in these results are removed. Finally, the curve fitting of denoised coordinate results is performed to image the point charge moving path. Empirical results confirm that the proposed system effectively warns and images thunderstorms, as well as provides a valid reference for multi-scale thunderstorm monitoring.
When the offset boosting technique is introduced into a chaotic system for attractor shifting, the number of coexisting attractors in the system can be doubled under the application of the employed absolute-value function. Consequently, the offset booster becomes a doubling parameter determining the distance between the two coexisting attractors, and therefore can polymerize these attractors to become a pseudo-multi-scroll attractor. This paper demonstrates that the attractor doubling operation can be applied to any dimension of the system and can also be nested at any time leading to the geometric growth of the coexisting attractors. Furthermore, various regimes of coexistence can be merged and composed together to reproduce an integrated attractor in the system.
