Abstract: The influence of Cu and Zn on soil nematode communities was examined along a pollution gradient with increasing distance from a metallurgical factory. Total and available heavy metal contents were used to study the effects of heavy metals on nematode abundance, trophic groups and ecological indices. The results demonstrated significant correlations between the number of total nematodes, bacterivores, plant-parasites and the total and available heavy metals. Bacterivores and plant-parasites were the dominant trophic groups. Significant differences in different sampling sites were found only in the number of bacterivores (P<0.0l). The Shannon-Weaver diversity index (H'), trophic diversity index (TD), evenness index…(J') and dominance index (λ) were found to be sensitive to soil pH and C/N ratios. Significant correlations were found between the total nematodes (TNEM), some genera (Acrobeloides, A phelenchoides, Cephalobus, Ditylenchus, Mesorhabditis, Tetylenchus and Tylenchus) and distance from the factory.
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Abstract: In order to solve the uncertainty of covariance and the unreasonable setting of expectation threshold in traditional cooperative tracking algorithm, it is easy to cause frequent switching of radar. At the same time, the existing sensor management is carried out under the same tracking accuracy, which does not meet the needs of the actual battlefield environment. Therefore, this paper divides the tracking accuracy of tracking target, defines the cooperative index of covariance and information increment cooperative management, improves the discriminant threshold of sensor switch, saves more sensor resources while solving the above problems, and improves the combat and survivability of…aircraft.
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Keywords: Collaborative tracking, sensor management, system survivability
Abstract: For a fuzzy subset system Z L , the concepts of a Δ Γ L -completion and a Z Γ L -completion of a given fuzzy poset (X , e ) are introduced and their universal properties are investigated. In this paper, we prove that: (1) the Δ Γ L -completion Δ Γ L (X ) is a join-completion with the universal property; (2) the Z Γ L -completion Z Γ L (X ) is the smallest Z L -complete fuzzy subposet of Δ Γ L (X ) in the case that Z L is fuzzy subset-hereditary. The results show…that the Dedekind-MacNeille completion is a special case of the Z Γ L -completion.
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Abstract: With the rapid growth of data scale, the problems of collaborative filtering recommendation algorithm are more and more obvious, such as data sparsity, cold start, scalability, and the change of user interest over time. About the existing problems, we introduce the fuzzy clustering and propose a collaborative filtering algorithm based on fuzzy C-means clustering. The algorithm performs fuzzy clustering on the item attribute information to make items belonging to different categories in different membership degree, increases the data density, effectively reduces the data sparsity, and solves the issue that the inaccuracy of similarity leads to the low recommendation accuracy. Meanwhile,…the algorithm introduces the time weight function. Different evaluation times give different time weight values, and recently evaluated items are more representative of the user current interest, so we give a higher weight value, and early evaluated items have less effect on the user current interest, thus the weight value are relatively lower. The experimental results show that our algorithm can effectively alleviate the data sparsity problem and time migration of users preferences, thus achieve better performance.
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Keywords: Recommender systems, collaborative filtering, data sparsity, interest migration
Abstract: BACKGROUND: P300-spellers are brain-computer interface (BCI)-based character input systems. Support vector machine (SVM) ensembles are trained with large-scale training sets and used as classifiers in these systems. However, the required large-scale training data necessitate a prolonged collection time for each subject, which results in data collected toward the end of the period being contaminated by the subject’s fatigue. OBJECTIVE: This study aimed to develop a method for acquiring more training data based on a collected small training set. METHODS: A new method was developed in which two corresponding training datasets in two sequences are superposed and averaged to extend the…training set. The proposed method was tested offline on a P300-speller with the familiar face paradigm. RESULTS: The SVM ensemble with extended training set achieved 85% classification accuracy for the averaged results of four sequences, and 100% for 11 sequences in the P300-speller. In contrast, the conventional SVM ensemble with non-extended training set achieved only 65% accuracy for four sequences, and 92% for 11 sequences. CONCLUSION: The SVM ensemble with extended training set achieves higher classification accuracies than the conventional SVM ensemble, which verifies that the proposed method effectively improves the classification performance of BCI P300-spellers, thus enhancing their practicality.
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Keywords: Brain-computer interface, familiar face paradigm, P300 speller, SVM ensemble, training set extension
Abstract: Due to the limited focus range of optical imaging system, and the locations or focus of different objects in the same scene are different, multiple objects cannot be focused at the same time. In order to solve this problem and make the underwater image clearer, we propose a fusion method based on the sparse matrix in this paper. Firstly, we transform the source image into sparse image by sparse transform and get the clearity of the image based on the sparsity. Then, the clearity image will be segmented into focus regions. After that, the focus regions and non-focus regions are fused…respectively based on different fusion algorithms. Finally, the focus regions and non-focus regions are combined to get the enhanced image. The experiments in the end show that the fusion method we proposed in this paper has higher information entropy, correlation entropy, standard deviation, and average gradient, so it can enhance the underwater multi-focus image and can be applied to the underwater object detection.
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Keywords: Sparse matrix, underwater multi-focus image, fusion, region segment
Abstract: The detection of magnetic tile quality is an essential link before the assembly of permanent magnet motor. In order to meet the high standard of magnetic tile surface defect detection and realize the rapid and automatic segmentation of magnetic tile defects, a magnetic tile surface defect segmentation algorithm based on cross self-attention model (CSAM) is proposed. It adopts high-low level semantic feature fusion method to build the dependency relationship between the deep and shallow features. Multiple auxiliary loss functions are used to constrain the network and reduce the noise in the deep features. In addition, an image enhancement method is…also designed to solve the problem of insufficient annotated data. The experimental results show that the network can achieve 79.6% mIoU and 98.5% PA, which can meet the high standard requirements of magnetic tile manufacturing.
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Abstract: OBJECTIVES: To explore the feasibility of contrast-enhanced ultrasound (CEUS) as a new tool for characterizing vascularization of primary peripheral lung cancer. METHODS: 315 consecutive patients with definite primary peripheral lung cancers underwent CEUS examination from November 2016 to March 2022. CEUS parameters including time to enhancement (TE), time to peak (TP), time to wash-out (TW), distribution of vessels (DV), extent of enhancement (EE) and homogeneity of enhancement (HE) were obtained. RESULTS: The lesions were grouped on the basis of TE which reflects tumor vascularization: early enhancement (pulmonary arterial vascularization) (n = 91) and delayed enhancement group (bronchial arterial vascularization) (n = 224).…Overall, lung tumors commonly (71.1%) manifested a delayed enhancement which indicating blood supply originated from bronchial arteries, while an early enhancement was present in less than a third of the cases. Tumors with bronchial vascularization tended to show a delayed, reduced and heterogeneous enhancement. Correspondingly, it is characterized by a shorter TE, marked EE and a relatively infrequent occurrence of necrosis in tumors with pulmonary vascularization. CONCLUSIONS: Providing micro-perfusion information, CEUS is a potentially imaging tool for evaluating blood supply in primary peripheral lung cancer.
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Abstract: The hydropower plays a key role in electricity system owing to its renewability and largest share of clean electricity generation that promotes sustainable development of national economy. Developing a proper forecasting model for the quarterly hydropower generation is crucial for associated energy sectors, which could assist policymakers in adjusting corresponding schemes for facing with sustained demands. For this purpose, this paper presents a fractional nonlinear grey Bernoulli model (abbreviated as FANGBM(1,1)) coupled seasonal factor and Particular Swarm Optimization (PSO) algorithm, namely PSO algorithm-based FASNGBM(1,1) model. In the proposed method, the moving average method that eliminates the seasonal fluctuations is introduced…into FANGBM(1,1), then in which the structure parameters of FASNGBM(1,1) are determined by PSO. Based on hydropower generation of China from the first quarter of 2011 to the final quarter of 2018 (2011Q1-2018Q4), the numerical results show that the proposed model has a better performance than that of other benchmark models. Eventually, the quarterly hydropower generation of China from 2019 to 2020 are forecasted by the proposed model, according to results, the hydropower generation of China will reach 11287.14 × 108 Kwh in 2020.
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