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1دورية أكاديمية
المؤلفون: Jie Lian, Mingyu Zhang, Na Jiang, Wei Bi, Xiaoqiu Dong
الوصف: The kidney tissue image is affected by other interferences in the tissue, which makes it difficult to extract the kidney tissue image features, and it is difficult to judge the lesion characteristics and types by intelligent feature recognition. In order to improve the efficiency and accuracy of feature extraction of kidney tissue images, refer to the ultrasonic heart image for analysis and then apply it to the feature extraction of kidney tissue. This paper proposes a feature extraction method based on ultrasound image segmentation. Moreover, this study combines the optical flow method and the speckle tracking algorithm to select the best image tracking method and optimizes the algorithm speed through the full search method and the two-dimensional log search method. In addition, this study verifies the performance of the method proposed in this paper through comparative experimental research, and this study combines statistical analysis methods to perform data analysis. The research results show that the algorithm proposed in this paper has a certain effect.
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2دورية أكاديمية
المؤلفون: Qiong Yang, Yi Zhang, Chengkai Tang, Jie Lian
الوصف: The Global Positioning System (GPS), with its accurate positioning and timing information, has become a commonly used navigation instrument for many applications. However, it is susceptible to intentional interference such as jamming and spoofing. The conventional antijamming GPS receiver fails to work in a combined jamming and spoofing attack scenario. To solve the problem, a combined antijamming and antispoofing algorithm for a GPS receiver based on an antenna array is proposed. In this method, the jamming is eliminated by subspace projection, and then a compressed sensing framework is adopted to obtain the direction of arrival (DOA) of the despreading satellite navigation signal and detect the spoofing signal. According to the DOA of the authentic and spoofing signals, the receiver uses adaptive multibeamforming to concurrently achieve the undistorted reception of the authentic satellite signal and the suppression of the spoofing. We analyse three aspects of algorithmic performance: the antenna array direction diagram, the spoofing detection and the acquisition results. The simulation results and their analysis preliminarily show that the proposed method can detect and suppress GPS jamming and spoofing effectively.
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3دورية أكاديمية
المؤلفون: Lei Liu, Song Yue, Jingyang Wu, Jiahua Zhang, Jie Lian, Desheng Huang, Weiping Teng, Lei Chen
الوصف: The aim of this research was to identify the prevalence and distribution of vitreoretinal interface abnormalities (VIAs) among urban community population in Shenyang, China. According to the WHO criteria, a cross-sectional study was carried out among 304 Type 2 diabetes (T2D) patients and 304 people without diabetes as control over 45 years old. The presence of VIAs was determined by standardized grading of macular optical coherence tomography (Optovue OCT; Optovue, Inc., Fremont, CA) scans and two-field fundus photographs in at least one eye. For both men and women, high prevalence of VIAs (70.79%) was observed among over 65-years-old T2D patients. Prevalence of VIAs was observed to be high among T2D patients in all age groups compared to normal subjects. Prevalence of VIAs increased with age in all subjects. Prevalence of components of VIAs was epiretinal membrane (ERM) 11.43%, posterior vitreous detachment (PVD) 17.76%, vitreomacular traction syndrome (VMT) 5.67%, macular cysts/macular edema (MC/ME) 4.61%, full-thickness macular hole (FTMH) 0.82%, and partial thickness macular hole (PTMH) 0.74% in any eye, respectively. ERM and MC/ME were more prevalent in T2D in both males and females. The results highlight the need for early detection using OCT and approaches for the prevention of VIAs of diabetes in urban community.
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4دورية أكاديمية
المؤلفون: Yun Liu, Jie Lian, Michael R. Bartolacci, Qing-An Zeng
الوصف: The support vector machine (SVM) is one of the most widely used approaches for data classification and regression. SVM achieves the largest distance between the positive and negative support vectors, which neglects the remote instances away from the SVM interface. In order to avoid a position change of the SVM interface as the result of an error system outlier, C-SVM was implemented to decrease the influences of the system’s outliers. Traditional C-SVM holds a uniform parameter C for both positive and negative instances; however, according to the different number proportions and the data distribution, positive and negative instances should be set with different weights for the penalty parameter of the error terms. Therefore, in this paper, we propose density-based penalty parameter optimization of C-SVM. The experiential results indicated that our proposed algorithm has outstanding performance with respect to both precision and recall.
