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| 1 | Complex Least Squares Adjustment to Improve Tree Height Inversion Problem in PolInSAR显示文摘At present,the principal data processing methods involving complex observations are based on two strategies according to characteristics of the observation process,i.e.,step-by-step and direct resolution.However,these strategies have some limitations,e.g.they cannot consider statistical observation error information,redundant observations and so on.This paper applies least squares methods to complex data processing to extend surveying adjustment theory from real to complex number space.We compared the two adjustment criteria for a complex domain in a quantitative way.In order to understand the effectiveness of complex least squares,tree height inversion from PolInSAR data is taken as an example.We firstly established both a complex adjustment function model and a stochastic model for PolInSAR tree height inversion,and then applied the complex least squares method to estimate tree height.Results show that the complex least squares approach is reliable and outperforms other classic tree height retrieval methods;the method is simple and easy to implement. | Jianjun ZHU Qinghua XIE Tingying ZUO Changcheng WANG Jian XIE | 2019 | Journal of Geodesy and Geoinformation Science2019，2，1： | 12 |
| 2 | α-calcium sulfate hemihydrate preparation from FGD gypsum in recycling mixed salt solutions显示文摘 | Baohong Guan Li Yang Hailu Fu Bao Kong Tingying Li Liuchun Yang | 2011 | Chemical Engineering Journal2011，，1： | 2 |
| 3 | The effect of polymeric coatings on the static fatigue of tightly jacketed double-coated optical fibers显示文摘 | SHIUE S T SHEN Tingying OUYANG Hao | 2004 | Materials Chemistry and Physics2004，83，23： | 1 |
| 4 | On the Growth Rate of Reef Corals and Its Relation to Seawater Temperature显示文摘 | Ma Tingying | 1937 | Memorial of National Institute of Zoology and Botanics Academia Sinica1937，1，1： | 1 |
| 5 | Unmanned Aerial Vehicle Control of Major Sugarcane Diseases and Pests in Low Latitude Plateau显示文摘This research was aimed at the defects in traditional artificial spraying control method and the problems such as the difficulty in pesticides applying,labor shortage and low operating efficiency in the middle and late stage of sugarcane high stalk crops.The aerial pesticide application technology for sugarcane main diseases and pests was systematically developed and demonstrated from the aspects of aircraft type choice,selection of special pesticides and auxiliaries,integration of pesticides and equipment,field operation,technical specifications,and large-scale application organization mode.The UAV model and flight technical parameters suitable for the sugarcane planting area in low-latitude plateau were analyzed,and the optimal agent formulation combination and application technology of the UAV flight control were screened out,and the UAV flight control was applied to the major sugarcane pests and diseases control in the low-latitude plateau in large scale(UAV flight control was popularized and applied to 15 527 hm 2 in 2018).The research results provided mature whole-process technical support for the normalization of the application of the UVA flight control of major sugarcane pests and diseases.The UAV control technology for major sugarcane pests and diseases had the advantages of ultra-low pesticides applying dosage and high operating efficiency,and could effectively solve the problems such as the difficulty in pesticides applying,labor shortage and low operating efficiency in the middle late growth stage of high stalk crops.This technology successfully opened up a simple,efficient and new way for the effective control of major sugarcane pests and diseases,and practically accelerated the process of integrated control and prevention of sugarcane pests and diseases.In addition,this technology had an extremely significant effect on reducing the loss of sugarcane farmers and enterprises caused by the epidemic and outbreak of sugarcane pests and diseases,increasing sugarcane yield and sugar content.At the same time,this technology played an important role in realizing the whole-process precise control of sugarcane pests and diseases,improving the quality and increasing the efficiency of sugarcane,and guaranteeing the national sugar safety. | Xiaoyan WANG Rongyue ZHANG Hongli SHAN Yuanhong FAN Hong XU Pizhong HUANG Zejuan LI Tingying DUAN Ning KANG Wenfeng LI Yingkun HUANG | 2019 | Agricultural Biotechnology2019，8，4： | 1 |
| 6 | Genital human papillomavirus infection in female university students as determined by a PCR-based methed 显示文摘 | Bauerhm Tingy Manos MM | 1991 | JAMA1991，265，4： | 1 |
| 7 | Lateral di- mension-dependent antibacterial activity of graphene oxide sheets显示文摘 | Liu Shaobin Hu Ming Tingying Helen Zeng | 2012 | Langmuir2012，28，12： | 1 |
| 8 | Mircostructure and mediums evolution of TiO2 precursors prepared by peptization-hydrolysis method using polycarboxylic acid as peptizing agent显示文摘 | Tingying Zeng Yong Qiu Liusheng Chen Xinqi Song | 1998 | Material Chemistry and Physics1998，，56： | 1 |
| 9 | etaL Biomechanical comparison ofunipedicular versus bipedicular kyphoplasty显示文摘 | Steinman J Tingy CT Cruz G | 2005 | Spine (Phila Pa1976)2005，30，2： | 1 |
| 10 | Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer with Deep Learning显示文摘Objective.To develop an artificial intelligence method predicting lymph node metastasis(LNM)for patients with colorectal cancer(CRC).Impact Statement.A novel interpretable multimodal AI-based method to predict LNM for CRC patients by integrating information of pathological images and serum tumor-specific biomarkers.Introduction.Preoperative diagnosis of LNM is essential in treatment planning for CRC patients.Existing radiology imaging and genomic tests approaches are either unreliable or too costly.Methods.A total of 1338 patients were recruited,where 1128 patients from one centre were included as the discovery cohort and 210 patients from other two centres were involved as the external validation cohort.We developed a Multimodal Multiple Instance Learning(MMIL)model to learn latent features from pathological images and then jointly integrated the clinical biomarker features for predicting LNM status.The heatmaps of the obtained MMIL model were generated for model interpretation.Results.The MMIL model outperformed preoperative radiology-imaging diagnosis and yielded high area under the curve(AUCs)of 0.926,0.878,0.809,and 0.857 for patients with stage T1,T2,T3,and T4 CRC,on the discovery cohort.On the external cohort,it obtained AUCs of 0.855,0.832,0.691,and 0.792,respectively(T1-T4),which indicates its prediction accuracy and potential adaptability among multiple centres.Conclusion.The MMIL model showed the potential in the early diagnosis of LNM by referring to pathological images and tumor-specific biomarkers,which is easily accessed in different institutes.We revealed the histomorphologic features determining the LNM prediction indicating the model ability to learn informative latent features. | Hailing Liu Yu Zhao Fan Yang Xiaoying Lou Feng Wu Hang Li Xiaohan Xing Tingying Peng Bjoern Menze Junzhou Huang Shujun Zhang Anjia Han Jianhua Yao Xinjuan Fan | 2022 | Biomedical Engineering Frontiers2022，3，1： | 0 |
| 11 | The Optimizing Model and Its Solution for Making Train Working Graph with Computer on Separative Division of Double-Track Lines显示文摘TheOptimizingModelandItsSolutionforMakingTrainWorkingGraphwithComputeronSeparativeDivisionofDouble-TrackLinesPengQiyuan;JuTin... | Peng Qiyuan Ju Tingying(Department of Transportation Engineering),Soulhudest Jiaolong Universily,Chengdu 610031,China | 1994 | Journal of Modern Transportation1994，11，2： | 0 |
| 12 | A Two-phase Methodology Heuristic Insertion Algorithm for TSP显示文摘 | Jianjun Liu Yuan Li Xinrui Wang Yuan Wen Tingying Zhou | 2013 | 计算机科学与技术汇刊(中英文版)2013，2，4： | 0 |
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