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A harmonisation approach to traditional Chinese medicine registration in Asian countries

Journal of Traditional Chinese Medical Sciences 2024年第2期11卷 143-147页

作者： Vivian S.W.Chan Fung Independent Scholar 2 Woodward PlaceSt IvesNSW 2075Australia

The traditional Chinese medicine(TCM)industry is critical to not only for public health but also for economic *** to the European Union(EU)directives,under the EU framework for(traditional)herbal medicinal products,herbal medicines with long history of use can be registered in ***,there is a condition in this directive in which only those that have at least 10e15 years in the EU market are accepted for registration and/or marketing *** author opinion,the condition of 10-15 years of use in EU countries set within the EU regulatory framework is with consideration of the genetic differences which can result in variation in adverse drug responses among different world *** this concept in mind,it is reasonable to project the principal of the EU directive to the Asian countries where TCM is *** like China,Singapore,Japan and South Korea that have well established drug registration framework are in best position in executing the best practice and facilitate harmonization of registration for TCM within the ***,the registration process itself allows more safety and efficacy data to be collected systemically before and after product registration/marketing *** are valuable information for future drug *** therapeutic value of TCM is limitless,it has been left out in the EU regulatory framework,and the opportunity for it to be expanded and carried forward in modern medicines is shadowed by the limited number of TCM that are qualified to be registered under the EU regulatory *** early establishment of a harmonized risk-based registration process for TCM in Asian countries is *** will strengthen the database to substantiate the history of safe use and further preserving and expanding the therapeutic values of TCM within and beyond the Asian region.

关键词： Traditional Chinese medicines Population genetic Harmonization registration Asian countries

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registration algorithm for sensor alignment based on stochastic fuzzy neural network

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Journal of Systems Engineering and Electronics 2005年第1期16卷 134-139页

作者： LiJiao JingZhongliang HeJiaona WangAn DepartmentofAutomaticControl NorthwesternPolytechnicalUniversityXi'an710072P.R.China InstitureofAerospaceInformationandControl SchoolofElectroniceandInformationTechnologyShanghaiJiaotongUniversityShanghai200030P.R.China DepartmentofAutomaticControl NorthwesternPolytechnicalUniversityXi'an710072P.R.China

Multiple sensor registration is an important link in multi-sensors data fusion. The existed algorithm is all based on the assumption that system errors come from a fixed deviation set. But there are many other factors, which can result system errors. So traditional registration algorithms have limitation. This paper presents a registration algorithm for sensor alignment based on stochastic fuzzy neural network (SNFF), and utilized fuzzy clustering algorithm obtaining the number of fuzzy rules. Finally, the simulative result illuminate that this way could gain a satisfing result.

关键词： multi-sensors registration fuzzy clustering stochastic fuzzy neural network.

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A fast registration algorithm of rock point cloud based on spherical projection and feature extraction

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Frontiers of Computer Science 2019年第1期13卷 170-182页

作者： Yaru XIAN Jun XIAO Ying WANG School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China

Point cloud registration is an essential step in the process of 3D *** this paper,a fast registration algorithm of rock mass point cloud is proposed based on the improved iterative closest point (ICP)*** our proposed algorithm,the point cloud data of single station scanner is transformed into digital images by spherical polar coordinates,then image features are extracted and edge points are removed,the features used in this algorithm is scale-invariant feature transform (SIFT).By analyzing the corresponding relationship between digital images and 3D points,the 3D feature points are extracted,from which we can search for the two-way correspondence as candidates. After the false matches are eliminated by the exhaustive search method based on random sampling,the transformation is computed via the Levenberg-Marquardt-Iterative Closest Point (LM-ICP)*** on real data of rock mass show that the proposed algorithm has the similar accuracy and better registration efficiency compared with the ICP algorithm and other algorithms.

关键词： rock point cloud registration LM-ICP spherical projection feature extraction

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A Correntropy-based Affine Iterative Closest Point Algorithm for Robust Point Set registration

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IEEE/CAA Journal of Automatica Sinica 2019年第4期6卷 981-991页

作者： Hongchen Chen Xie Zhang Shaoyi Du Zongze Wu Nanning Zheng the School of Electronic and Information Engineering South China University of TechnologyGuangzhou 510640China the School of Electric Power South China University of TechnologyGuangzhou 510640China the Institute of Artificial Intelligence and Robotics Xi’an Jiaotong UniversityXi’an 710049China the School of Automation Guangdong University of TechnologyGuangzhou 510006China IEEE

The iterative closest point(ICP)algorithm has the advantages of high accuracy and fast speed for point set registration,but it performs poorly when the point set has a large number of noisy *** solve this problem,we propose a new affine registration algorithm based on correntropy which works well in the affine registration of point sets with ***,we substitute the traditional measure of least squares with a maximum correntropy criterion to build a new registration model,which can avoid the influence of *** maximize the objective function,we then propose a robust affine ICP *** each iteration of this new algorithm,we set up the index mapping of two point sets according to the known transformation,and then compute the closed-form solution of the new transformation according to the known index *** to the traditional ICP algorithm,our algorithm converges to a local maximum monotonously for any given initial ***,the robustness and high efficiency of affine ICP algorithm based on correntropy are demonstrated by 2D and 3D point set registration experiments.

关键词： Affine iterative closest point(ICP)algorithm correntropy-based robust point set registration

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Natural forest ALS-TLS point cloud data registration without control points

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Journal of Forestry Research 2023年第3期34卷 809-820页

作者： Jianpeng Zhang Jinliang Wang Feng Cheng Weifeng Ma Qianwei Liu Guangjie Liu Faculty of Geography Yunnan Normal UniversityKunming 650500People’s Republic of China Key Laboratory of Resources and Environmental Remote Sensing for Universities in Yunnan Kunming 650500People’s Republic of China Center for Geospatial Information Engineering and Technology of Yunnan Province Kunming 650500People’s Republic of China College of Resources and Environment Yunnan Agriculture UniversityKunming 650201People’s Republic of China

Airborne laser scanning(ALS)and terrestrial laser scanning(TLS)has attracted attention due to their forest parameter investigation and research *** is limited to obtaining fi ne structure information below the forest canopy due to the occlusion of trees in natural *** contrast,TLS is unable to gather fi ne structure information about the upper *** address the problem of incomplete acquisition of natural forest point cloud data by ALS and TLS on a single platform,this study proposes data registration without control *** ALS and TLS original data were cropped according to sample plot size,and the ALS point cloud data was converted into relative coordinates with the center of the cropped data as the *** same feature point pairs of the ALS and TLS point cloud data were then selected to register the point cloud *** initial registered point cloud data was fi nely and optimally registered via the iterative closest point(ICP)*** results show that the proposed method achieved highprecision registration of ALS and TLS point cloud data from two natural forest plots of Pinus yunnanensis *** Picea asperata *** included diff erent species and *** average registration accuracy of 0.06 m and 0.09 m were obtained for *** and ***,respectively.

关键词： Airborne laser scanning(ALS) Terrestrial laser scanning(TLS) registration Natural forest Iterative closest point(ICP)algorithm

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Non-rigid registration of mural images and laser scanning data based on the optimization of the edges of interest

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Science China(Information Sciences) 2013年第6期56卷 181-190页

作者： ZHANG Fan HUANG XianFeng FANG Wei LI DeRen State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan University

The orientation and correction of mural images by registering them with laser scanning data is critical for the digital protection of ancient *** paper proposes a method for the non-rigid registration of mural images and laser scanning data based on the optimization of the edge of interest by using laser echo intensity information as an ***,the intensity image was generated from the laser echo intensity information,and registered with the mural image using a rigid transformation ***,the edges of interest in the mural image and the gradient field of the intensity images were processed as registration ***,every edge of interest was registered with the optimization base used in the rigid registration of the mural image and intensity ***,the registration was completed after a non-rigid transformation model between these two images was constructed using the control points on the optimized *** experimental results show that the proposed method can obtain high registration accuracy for different data sets.

关键词： laser scanning point cloud image registration non-rigid

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Tracking registration Algorithm for Augmented Reality Based on Template Tracking

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International Journal of Automation and computing 2020年第2期17卷 257-266页

作者： Peng-Xia Cao Wen-Xin Li Wei-Ping Ma Lanzhou Institute of Physics China Academy of Space TechnologyLanzhou 730000China

Tracking registration is a key issue in augmented reality applications,particularly where there are no artificial identifier placed *** this paper,an efficient markerless tracking registration algorithm which combines the detector and the tracker is presented for the augmented reality *** capture the target images in real scenes as template images,use the random ferns classifier for target detection and solve the problem of reinitialization after tracking registration failures due to changes in ambient lighting or occlusion of *** the target has been successfully detected,the pyramid Lucas-Kanade(LK)optical flow tracker is used to track the detected target in real time to solve the problem of slow *** least median of squares(LMedS)method is used to adaptively calculate the homography matrix,and then the three-dimensional pose is estimated and the virtual object is rendered and *** results demonstrate that the algorithm is more accurate,faster and more robust.

关键词： Tracking registration augmented reality markerless random ferns Lucas-Kanade(LK)optical flow

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Who Will Come: Predicting Freshman registration Based on Decision Tree

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Computers, Materials & Continua 2020年第11期65卷 1825-1836页

作者： Lei Yang Li Feng Liwei Tian Hongning Dai Macao University of Science and Technology Macao

The registration rate of freshmen has been a great concern at many colleges and universities,particularly private ***,there are two inquiry methods:telephone and ***,the former is not only time-consuming but also suffers from the fact that many students tend to keep their choices *** the other hand,the latter is not always feasible because only few students are willing to pay their university tuition fees in *** is often believed that it is impossible to predict incoming freshmen’s choice of university due to the large amount of ***,if we look at the two major considerations a potential freshman contemplates in making a choice,such as the geographical location of the university in relation to his/her home town,and testimonies about of that college life experience by previous graduates,we believe it is possible to predict future enrollment *** paper is the first to find a way to solve the problem of predicting the choice of university a freshman will *** contributions include the following:*** present a dataset on freshman registration;*** propose a decision-tree-based approach for freshman registration *** results show that freshman registration is predictable.

关键词： Decision tree prediction registration

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Multi-source Remote Sensing Image registration Based on Contourlet Transform and Multiple Feature Fusion

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International Journal of Automation and computing 2019年第5期16卷 575-588页

作者： Huan Liu Gen-Fu Xiao Yun-Lan Tan Chun-Juan Ouyang College of Electronic and Information Engineering Jinggangshan UniversityJi′an 343009China Key Laboratory of Watershed Ecology and Geographical Environment Monitoring National Administration of SurveyingMapping and Geoinformation(NASG)Ji′an 343009China College of Mechanical and Electronic Jinggangshan UniversityJi′an 343009China

Image registration is an indispensable component in multi-source remote sensing image processing. In this paper, we put forward a remote sensing image registration method by including an improved multi-scale and multi-direction Harris algorithm and a novel compound feature. Multi-scale circle Gaussian combined invariant moments and multi-direction gray level co-occurrence matrix are extracted as features for image matching. The proposed algorithm is evaluated on numerous multi-source remote sensor images with noise and illumination changes. Extensive experimental studies prove that our proposed method is capable of receiving stable and even distribution of key points as well as obtaining robust and accurate correspondence matches. It is a promising scheme in multi-source remote sensing image registration.

关键词： Feature fusion multi-scale circle Gaussian combined invariant moment multi-direction gray level co-occurrence matrix multi-source remote sensing image registration contourlet transform

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Automated registration of wide-baseline point clouds in forests using discrete overlap search

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Forest Ecosystems 2022年第6期9卷 852-877页

作者： Onni Pohjavirta Xinlian Liang Yunsheng Wang Antero Kukko Jiri Pyorala Eric Hyyppa Xiaowei Yu Harri Kaartinen Juha Hyyppa Department of Remote Sensing and Photogrammetry Finnish Geospatial Research InstituteVuorimiehentie 5Espoo02150Finland The State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhan430070China Department of Forest Sciences University of HelsinkiHelsinkiFI-00014Finland Department of Geography and Geology University of TurkuTurkuFI-20500Finland

Forest is one of the most challenging environments to be recorded in a three-dimensional(3D)digitized geometrical representation,because of the size and the complexity of the environment and the data-acquisition constraints brought by on-site *** studies have indicated that the data-acquisition pattern can have more influence on the registration results than other *** practice,the ideal short-baseline observations,i.e.,the dense collection mode,is rarely feasible,considering the low accessibility in forest environments and the commonly limited labor and time *** wide-baseline observations that cover a forest site using a few folds less observations than short-baseline observations,are therefore more preferable and commonly ***,the wide-baseline approach is more challenging for data registration since it typically lacks the required sufficient overlaps between *** now,a robust automated registration solution that is independent of special hardware requirements has still been *** is,the registration accuracy is still far from the required level,and the information extractable from the merged point cloud using automated registration could not match that from the merged point cloud using manual *** paper proposes a discrete overlap search(DOS)method to find correspondences in the point clouds to solve the low-overlap problem in the wide-baseline point *** proposed automatic method uses potential correspondences from both original data and selected feature points to reconstruct rough observation geometries without external knowledge and to retrieve precise registration parameters at *** extensive experiment was carried out with 24 forest datasets of different conditions categorized in three difficulty *** performance of the proposed method was evaluated using various accuracy criteria,as well as based on data acquired from different hardware,platforms,viewing persp

关键词： Close-range sensing Forest registration Point cloud Wide-baseline Terrestrial laser scanning Unmanned aerial vehicle Drone In situ Discrete overlap search

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