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| 1 | Deer Body Adaptive Threshold Segmentation Algorithm Based on Color Space显示文摘In large-scale deer farming image analysis,K-means or maximum between-class variance(Otsu)algorithms can be used to distinguish the deer from the background.However,in an actual breeding environment,the barbed wire or chain-link fencing has a certain isolating effect on the deer which greatly interferes with the identification of the individual deer.Also,when the target and background grey values are similar,the multiple background targets cannot be completely separated.To better identify the posture and behaviour of deer in a deer shed,we used digital image processing to separate the deer from the background.To address the problems mentioned above,this paper proposes an adaptive threshold segmentation algorithm based on color space.First,the original image is pre-processed and optimized.On this basis,the data are enhanced and contrasted.Next,color space is used to extract the several backgrounds through various color channels,then the adaptive space segmentation of the extracted part of the color space is performed.Based on the segmentation effect of the traditional Otsu algorithm,we designed a comparative experiment that divided the four postures of turning,getting up,lying,and standing,and successfully separated multiple target deer from the background.Experimental results show that compared with K-means,Otsu and hue saturation value(HSV)+K-means,this method is better in performance and accuracy for adaptive segmentation of deer in artificial breeding scenes and can be used to separate artificially cultivated deer from their backgrounds.Both the subjective and objective aspects achieved good segmentation results.This article lays a foundation for the effective identification of abnormal behaviour in sika deer. | Yuheng Sun Ye Mu Qin Feng Tianli Hu He Gong Shijun Li Jing Zhou | 2020 | Computers, Materials & Continua2020，，8： | 5 |
| 2 | Numerical Investigation on the Initiation Mechanism of Debris-Flow under Rainfall显示文摘Rainfall is an important factor to trigger the debris flow.Numerical simulation on the responses of slopes and the initiation of debris flow under rainfall was processed by using the software FLAC2D based on the soil parameters in Weijia Gully,Beichuan County,Sichuan Province,China.The effects of the slope angle,rainfall intensity,soil parameters on the developments of the stress and pore pressure and deformation of the slope were studied.It indicates that large displacements of the slope are mainly located near the slope toe.With the increase of the rainfall intensity the stability of the slope decreases and so the debris-flow is easy to occur. | LU Xiaobing YE Tianli CUI Peng HU Kaiheng CHEN Xiaoqing | 2011 | Journal of Mountain Science2011，8，4： | 3 |
| 3 | Late Holocene hydroclimatic variations and possible forcing mechanisms over the eastern Central Asia显示文摘Hydroclimatic variations over the eastern Central Asia are highly sensitive to changes in hemispheric-scale atmospheric circulation systems. To fully understand the long-term variability and relationship between hydroclimate and atmospheric circulation system, we present a high-resolution lascustrine record of late Holocene hydroclimate from Lake Sayram, Central Tianshan Mountains, China, based on the total organic carbon, total nitrogen, and carbonate contents, carbon/nitrogen ratios, and grain size. Our results reveal four periods of substantially increased precipitation at the interval of 4000–3780, 3590–3210, 2800–2160, and 890–280 cal yr BP, and one period of slightly increased precipitation from 1700–1370 cal yr BP. These wetter periods broadly coincide with those identified in other records from the mid-latitude Westerlies-dominated eastern Central Asia, including the northern Tibetan Plateau. As such, a similar hydroclimatic pattern existed over this entire region during the late Holocene. Based on a close similarity of our record with reconstruction of North Atlantic Oscillation indices and solar irradiance, we propose that decreased solar irradiance and southern migration of the entire circum-North Atlantic circulation system, particularly the main pathway of the mid-latitude Westerlies, significantly influenced hydroclimate in eastern Central Asia during the late Holocene. Finally, the inferred precipitation at Lake Sayram has increased markedly over the past 100 years, although this potential future changes in hydroclimate in Central Asia need for further investigation. | Jianghu LAN Hai XU Keke YU Enguo SHENG Kangen ZHOU Tianli WANG YuANDa YE Dongna YAN Huixian WU Peng CHENG Waili ABULIEZI Liangcheng TAN | 2019 | Science China Earth Sciences2019，62，8： | 3 |
| 4 | A Novel Hybrid Tag Identification Protocol for Large-Scale RFID Systems显示文摘Radio frequency identification technology is one of the main technologies of Internet of Things(IoT).Through the transmission and reflection of wireless radio frequency signals,non-contact identification is realized,and multiple objects identification can be realized.However,when multiple tags communicate with a singleton reader simultaneously,collision will occur between the signals,which hinders the successful transmissions.To effectively avoid the tag collision problem and improve the reading performance of RFID systems,two advanced tag identification algorithms namely Adaptive M-ary tree slotted Aloha(AMTS)based on the characteristics of Aloha-based and Query tree-based algorithms are proposed.In AMTS,the reader firstly uses the framed slotted Aloha protocol to map the tag set to different time slots,and then identify the collided tags using binary search method based on collision factor or mapping table.Both performance analysis and extensive experimental results indicate that our proposed algorithms significantly outperforms most existing anti-collision approaches in tag dense RFID systems. | Ye Mu Ruiwen Ni Yuheng Sun Tong Zhang Ji Li Tianli Hu He Gong Shijun Li Thobela Louis Tyasi | 2021 | Computers, Materials & Continua2021，，8： | 1 |
| 5 | A Lightweight Model of VGG-U-Net for Remote Sensing Image Classification显示文摘Remote sensing image analysis is a basic and practical research hotspot in remote sensing science.Remote sensing images contain abundant ground object information and it can be used in urban planning,agricultural monitoring,ecological services,geological exploration and other aspects.In this paper,we propose a lightweight model combining vgg-16 and u-net network.By combining two convolutional neural networks,we classify scenes of remote sensing images.While ensuring the accuracy of the model,try to reduce the memory of themodel.According to the experimental results of this paper,we have improved the accuracy of the model to 98%.The memory size of the model is 3.4 MB.At the same time,The classification and convergence speed of the model are greatly improved.We simultaneously take the remote sensing scene image of 64×64 as input into the designed model.As the accuracy of the model is 97%,it is proved that the model designed in this paper is also suitable for remote sensing images with few target feature points and low accuracy.Therefore,the model has a good application prospect in the classification of remote sensing images with few target feature points and low pixels. | Mu Ye Li Ji Luo Tianye Li Sihan Zhang Tong Feng Ruilong Hu Tianli Gong He Guo Ying Sun Yu Thobela Louis Tyasi Li Shijun | 2022 | Computers, Materials & Continua2022，，12： | 1 |
| 6 | Segmentation of Remote Sensing Images Based on U-Net Multi-Task Learning显示文摘In order to accurately segment architectural features in highresolution remote sensing images,a semantic segmentation method based on U-net network multi-task learning is proposed.First,a boundary distance map was generated based on the remote sensing image of the ground truth map of the building.The remote sensing image and its truth map were used as the input in the U-net network,followed by the addition of the building ground prediction layer at the end of the U-net network.Based on the ResNet network,a multi-task network with the boundary distance prediction layer was built.Experiments involving the ISPRS aerial remote sensing image building and feature annotation data set show that compared with the full convolutional network combined with the multi-layer perceptron method,the intersection ratio of VGG16 network,VGG16+boundary prediction,ResNet50 and the method in this paper were increased by 5.15%,6.946%,6.41%and 7.86%.The accuracy of the networks was increased to 94.71%,95.39%,95.30%and 96.10%respectively,which resulted in high-precision extraction of building features. | Ni Ruiwen Mu Ye Li Ji Zhang Tong Luo Tianye Feng Ruilong Gong He Hu Tianli Sun Yu Guo Ying Li Shijun Thobela Louis Tyasi | 2022 | Computers, Materials & Continua2022，，11： | 0 |
| 7 | Adenosine cyclic phosphate with ultrasonic-assisted pectinase extraction alleviated allergic reactions in RBL-2H3 through inhibiting the influx of intracellular Ca^(2+)显示文摘Jujube contains abundant cyclic adenosine monophosphate(cAMP)and the ultrasonic-assisted pectinase extraction(UAPE)conditions for obtaining the maximum cAMP yield from jujube were optimized.Orthogonal array design was applied to evaluate the effects of 4 variables by UAPE on cAMP yield.The results showed that the optimal cAMP yield(783.0μg/g)was derived at ratio of liquid to solid 5 mL/g,ratio of pectinase to raw material 1.5%,time 60 min and temperature 40℃.Moreover,the effect of cAMP on the anti-allergic function of action induced by immunoglobulin E(IgE)and its meschanism was investigated through establishing the sensitized cell model in rat basophilic leukemia(RBL-2 H3)cells using dinitrophenylated(DNP)-bovine serum albumin(BSA)-IgE.The results showed that cAMP interfered with sensitized cells,effectively inhibited the occurrence of basophil degranulation in dose dependence,and significantly reduced the activity ofβ-hexosamindase(β-hex),at the optimal concentration of 50μg/mL.The level of anti-inflammatory factor interleukin-10(IL-10)was promoted and the content of pro-inflammatory factor tumor necrosis factor-α(TNF-α)was suppressed by cAMP.In addition,influx of intracellular Ca^(2+) was repressed effectively.Our results demonstrate that jujube cAMP regulated the cytokine balance in the allergy pathway through blocking the influx of extracellular Ca^(2+),with the prevention of allergy symptoms. | Qiao Bai Xiaoping Feng Yu Wang Chunyu Wu Ye Liu Jiao Sun Tianli Yue Fangyu Long | 2023 | Food Science and Human Wellness2023，12，3： | 0 |
| 8 | Sika Deer Facial Recognition Model Based on SE-ResNet显示文摘The scale of deer breeding has gradually increased in recent years and better information management is necessary,which requires the identification of individual deer.In this paper,a deer face dataset is produced using face images obtained from different angles,and an improved residual neural network(ResNet)-based recognition model is proposed to extract the features of deer faces,which have high similarity.The model is based on ResNet-50,which reduces the depth of the model,and the network depth is only 29 layers;the model connects Squeeze-and-Excitation(SE)modules at each of the four layers where the channel changes to improve the quality of features by compressing the feature information extracted through the entire layer.A maximum pooling layer is used in the ResBlock shortcut connection to reduce the information loss caused by messages passing through the ResBlock.The Rectified Linear Unit(ReLU)activation function in the network is replaced by the Exponential Linear Unit(ELU)activation function to reduce information loss during forward propagation of the network.The preprocessed 6864 sika deer face dataset was used to train the recognition model based on SEResnet,which is demonstrated to identify individuals accurately.By setting up comparative experiments under different structures,the model reduces the amount of parameters,ensures the accuracy of the model,and improves the calculation speed of the model.Using the improved method in this paper to compare with the classical model and facial recognition models of different animals,the results show that the recognition effect of this research method is the best,with an average recognition accuracy of 97.48%.The sika deer face recognition model proposed in this study is effective.The results contribute to the practical application of animal facial recognition technology in the breeding of sika deer and other animals with few distinct facial features. | He Gong Lin Chen Haohong Pan Shijun Li Yin Guo Lili Fu Tianli Hu Ye Mu Thobela Louis Tyasi | 2022 | Computers, Materials & Continua2022，，9： | 0 |
| 9 | Sika Deer Behavior Recognition Based on Machine Vision显示文摘With the increasing intensive and large-scale development of the sika deer breeding industry,it is crucial to assess the health status of the sika deer by monitoring their behaviours.A machine vision-based method for the behaviour recognition of sika deer is proposed in this paper.Google Inception Net(GoogLeNet)is used to optimise the model in this paper.First,the number of layers and size of the model were reduced.Then,the 5×5 convolution was changed to two 3×3 convolutions,which reduced the parameters and increased the nonlinearity of the model.A 5×5 convolution kernel was used to replace the original convolution for extracting coarse-grained features and improving the model’s extraction ability.A multi-scale module was added to the model to enhance the multi-faceted feature extraction capability of the model.Simultaneously,the Squeeze-and-Excitation Networks(SE-Net)module was included to increase the channel’s attention and improve the model’s accuracy.The dataset’s images were rotated to reduce overfitting.For image rotation,the angle wasmultiplied by 30°to obtain the dataset enhanced by rotation operations of 30°,60°,90°,120°and 150°.The experimental results showed that the recognition rate of this model in the behaviour of sika deer was 98.92%.Therefore,the model presented in this paper can be applied to the behaviour recognition of sika deer.The results will play an essential role in promoting animal behaviour recognition technology and animal health monitoring management. | He Gong Mingwang Deng Shijun Li Tianli Hu Yu Sun Ye Mu Zilian Wang Chang Zhang Thobela Louis Tyasi | 2022 | Computers, Materials & Continua2022，，12： | 0 |
| 10 | Prognostic nomogram incorporating radiological features for predicting overall survival in patients with AIDS-related non-Hodgkin lymphoma显示文摘Background: Acquired immune deficiency syndrome (AIDS)-related non-Hodgkin lymphoma (AR-NHL) is a high-risk factor for morbidity and mortality in patients with AIDS. This study aimed to determine the prognostic factors associated with overall survival (OS) and to develop a prognostic nomogram incorporating computed tomography imaging features in patients with acquired immune deficiency syndrome-related non-Hodgkin lymphoma (AR-NHL).Methods: A total of 121 AR-NHL patients between July 2012 and November 2019 were retrospectively reviewed. Clinical and radiological independent predictors of OS were confirmed using multivariable Cox analysis. A prognostic nomogram was constructed based on the above clinical and radiological factors and then provided optimum accuracy in predicting OS. The predictive accuracy of the nomogram was determined by Harrell C-statistic. Kaplan-Meier survival analysis was used to determine median OS. The prognostic value of adjuvant therapy was evaluated in different subgroups.Results: In the multivariate Cox regression analysis, involvement of mediastinal or hilar lymph nodes, liver, necrosis in the lesions, the treatment with chemotherapy, and the CD4 ≤100 cells/μL were independent risk factors for poor OS (allP < 0.050). The predictive nomogram based on Cox regression has good discrimination (Harrell C-index = 0.716) and good calibration (Hosmer-Lemeshow test,P = 0.620) in high- and low-risk groups. Only patients in the high-risk group who received adjuvant chemotherapy had a significantly better survival outcome.Conclusion: A survival-predicting nomogram was developed in this study, which was effective in assessing the survival outcomes of patients with AR-NHL. Notably, decision-making of chemotherapy regimens and more frequent follow-up should be considered in the high-risk group determined by this model. | Xueqin Li Ziang Pan Xing Wang Tianli Hu Wen Ye Dongmei Jiang Wen Shen Jinxin Liu Yuxin Shi Shuang Xia Hongjun Li | 2022 | Chinese Medical Journal2022，，1： | 0 |
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