Communication Modulation Signal Recognition Algorithm Based on Entropy Cloud Characteristics

Yibing Li,Jie Chen,Dandan Liu,Jingchao Li 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.5

Communication modulation signal recognition, as an emerging technology, has been widely used in the field of communication reconnaissance. It is generally known that the characteristics of communication modulation signals under low SNR environment is difficult to extract. To solve this problem, a novel modulation signal feature extraction algorithm based on entropy cloud characteristics is put forward in three steps by this paper. Firstly, it extracts entropy characteristics of the modification signal, which introduce the exponential entropy to construct two-dimensional feature entropy with shannon and exponential entropy for a better signal recognition performance. Then, it extracts cloud digital characteristics of information entropy to build three-dimensional feature, which can depict the modulation type characteristics of the signal. Finally, it uses grey correlation classifier for signal identification. By means of simulation, it can be seen that the new algorithm has overcome the defection that signal characteristics are unstable and difficult to extract under low SNR environment in the traditional method. So the new algorithm is available and effective for the signal identification under low SNR environment, thus achieves the goal of the signal classification.

An Efficient Combination Method of Conflict Evidences

Yibing Li,Jie Chen,Yun Lin 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.12

Evidence theory is an effective method for uncertainty reasoning, which is widely used in areas like expert system, artificial intelligence, pattern recognition and system decision. But traditional DS combination rule will produce the result contrary to intuition on the condition of high confliction. To solve the problem, this paper proposes a modified method based on the option of distance function and correction of support degree. Firstly, it introduces the Minkowsky distance as distance function of evidences and finds the support degree of each evidence in system, then corrects the support degree on the basic of its distribution, finally, it gets the weighted average of evidence by the normalized evidence credibility, and uses the DS combination rule to synthesis evidences. The simulation results demonstrate the effectiveness and reliability of modified method.

Prediction of Thermophysical Properties of Helium Using Linear Prediction and Artificial Neural Networks

Dazuo Yang,Hao Li,Yibing Zhou 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.11

Thermophysical properties of helium are significant in practical applications. However, the values of properties vary under different circumstances, which may have bad impacts on practical productions and applications. In our study, computational models like Linear Prediction and Artificial Neural Networks (ANNs) are applied to predict the thermophysical properties of the chemical substances. By analyzing 50 data groups using Linear Prediction, General Regression Neural Network (GRNN) and Multilayer Feedforward Neural Network (MLFN) methods, 9 models were successfully established to predict the thermophysical properties of helium, including density, energy, enthalpy, entropy, isochoric heat capacity, isobaric heat capacity, viscosity, thermal conductivity and dielectric constant. Within permissible error range (30% tolerance), our models were proved to be robust and accurate which indicates that ANN models can be used to predict the thermophysical properties of helium.

Accumulated Nitrogen Recovery and its Application in Wheat-Maize Cropping Systems

Yibing Ma,Jie Liu,Jumei Li 한국토양비료학회 2014 한국토양비료학회 학술발표회 초록집 Vol.2014 No.6

Soil Olsen-P Accumulation Models and Prediction Estimation of Soil Olsen-P Accumulation by Models in China

Jumei Li,Yibing Ma,Bin Wang 한국토양비료학회 2014 한국토양비료학회 학술발표회 초록집 Vol.2014 No.6

The impact of TNFSF14 on prognosis and immune microenvironment in clear cell renal cell carcinoma

Fangshi Xu,Yibing Guan,Peng Zhang,Li Xue,Xiaojie Yang,Ke Gao,Tie Chong 한국유전학회 2020 Genes & Genomics Vol.42 No.9

Background TNFSF14 has been proven to play an important role in various types of tumors. However, its function in renal cell carcinoma (RCC) has not yet been fully elucidated. Objective In order to explore molecular mechanism of RCC, we evaluated the efect of TNFSF14 on RCC progression, prognosis and immune microenvironment. Methods Using TCGA database, the diferential expression of TNFSF14 and its relationships between clinicopathological features and prognosis were determined. Cox univariate and multivariate analyses were successively performed to identify whether TNFSF14 was an independent prognostic factor. The discriminating ability of TNFSF14 in RCC prognosis analysis was validated under the same clinical subgroups. Tumor mutational burden (TMB) of each RCC samples was calculated and the diferential expression of TNFSF14 between high- and low-TMB groups was analyzed. The immune abundances of 22 leukocyte subtypes in each RCC samples were presented through the CIBERSORT algorithm. TIMER database was used to explore the relationships between copy number of TNFSF14 and the infltration levels of 6 immune cells. Results Overexpression of TNFSF14 implied adverse clinicopathological features and poor prognosis. Meanwhile, TNFSF14 was identifed as an independent prognostic factor (HR=1.047, P=0.028) and possessed prevalent applicability in RCC prognostic analysis. TNFSF14 was upregulated in high-TMB group than that in low-TMB group (Log2FC=0.722). Moreover, overexpression of TNFSF14 brought alteration of immune abundance of 8 leukocyte subtypes. Besides, somatic copy number alteration (SCNA) of TNFSF14 was associated with infltration levels of 6 immune cells. Conclusions TNFSF14 has crucial impact on progression, prognosis and immune microenvironment in RCC. Besides, TNFSF14 may be a potential biomarker for predicting the efcacy and response rate of RCC immunotherapy.

Surge detection methods using empirical mode decomposition and continuous wavelet transform for a centrifugal compressor

Xin Wu,Yibing Liu,Rui Liu,Li Zhao 대한기계학회 2016 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.30 No.4

The occurrence of surge in a centrifugal compressor results in large oscillations in pressure and flow. To avoid damaging the compressor because of surge, we develop several surge detection methods in this study. Considering the incipient surge phenomenon, the Empirical mode decomposition (EMD) and the Morlet Continuous wavelet transform (CWT) methods are selected. Both methods are validated through experimental data collected from surge tests conducted on the three-stage Ingersoll-Rand Centac centrifugal compressor at Toyota Motor Manufacturing in Kentucky, USA. For incipient surge detection, the EMD-based method can determine the threshold 1 sec earlier than the Morlet CWT-based method. Therefore, the EMD method can be used to implement the incipient surge detection scheme on the tested centrifugal compressor for safety considerations.

Energy absorption ability of buckyball C ₇₂₀ at low impact speed: a numerical study based on molecular dynamics

Xu, Jun,Li, Yibing,Xiang, Yong,Chen, Xi Springer 2013 Nanoscale research letters Vol.8 No.1

<P>The dynamic impact response of giant buckyball C<SUB>720</SUB> is investigated by using molecular dynamics simulations. The non-recoverable deformation of C<SUB>720</SUB> makes it an ideal candidate for high-performance energy absorption. Firstly, mechanical behaviors under dynamic impact and low-speed crushing are simulated and modeled, which clarifies the buckling-related energy absorption mechanism. One-dimensional C<SUB>720</SUB> arrays (both vertical and horizontal alignments) are studied at various impact speeds, which show that the energy absorption ability is dominated by the impact energy per buckyball and less sensitive to the number and arrangement direction of buckyballs. Three-dimensional stacking of buckyballs in simple cubic, body-centered cubic, hexagonal, and face-centered cubic forms are investigated. Stacking form with higher occupation density yields higher energy absorption. The present study may shed lights on employing C<SUB>720</SUB> assembly as an advanced energy absorption system against low-speed impacts.</P>

An A²CL Algorithm based on Information Optimization Strategy for MMRS

( Qianhui Dong ),( Yibing Li ),( Qian Sun ),( Yuan Tian ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.4

Multiple Mobile Robots System (MMRS) has shown many attractive features in lots of real-world applications that motivate their rapid and wide diffusion. In MMRS, the Cooperative Localization (CL) is the basis and premise of its high-performance task. However, the statistical characteristics of the system noise should be already known in traditional CL algorithms, which is difficult to satisfy in actual MMRS because of the numerous of disturbances form the complex external environment. So the CL accuracy will be reduced. To solve this problem, an improved Adaptive Active Cooperative Localization (A²CL) algorithm based on information optimization strategy for MMRS is proposed in this manuscript. In this manuscript, an adaptive information fusion algorithm based on the variance component estimation under Extended Kalman filter (VCEKF) method for MMRS is introduced firstly to enhance the robustness and accuracy of information fusion by estimating the covariance matrix of the system noise or observation noise in real time. Besides, to decrease the effect of observation uncertainty on CL accuracy further, an observation optimization strategy based on information theory, the Model Predictive Control (MPC) strategy, is used here to maximize the information amount from observations. And semi-physical simulation experiments were carried out to verity the A²CL algorithm’s performance finally. Results proved that the presented A²CL algorithm based on information optimization strategy for MMRS cannot only enhance the CL accuracy effectively but also have good robustness.

A New DS Combination Method for Dealing with Conflict Evidence Effectively

Jinfeng Pang,Yun Lin,Yibing Li,Xiaochun Xu,Bin Li 보안공학연구지원센터(IJSIP) 2013 International Journal of Signal Processing, Image Vol.6 No.5