DRRS-BC:Decentralized Routing Registration System Based on Blockchain

The border gateway protocol(BGP)has become the indispensible infrastructure of the Internet as a typical inter-domain routing protocol.However,it is vulnerable to misconfigurations and malicious attacks since BGP does not provide enough authentication mechanism to the route advertisement.As a result,it has brought about many security incidents with huge economic losses.Exiting solutions to the routing security problem such as S-BGP,So-BGP,Ps-BGP,and RPKI,are based on the Public Key Infrastructure and face a high security risk from the centralized structure.In this paper,we propose the decentralized blockchain-based route registration framework-decentralized route registration system based on blockchain(DRRS-BC).In DRRS-BC,we produce a global transaction ledge by the information of address prefixes and autonomous system numbers between multiple organizations and ASs,which is maintained by all blockchain nodes and further used for authentication.By applying blockchain,DRRS-BC perfectly solves the problems of identity authentication,behavior authentication as well as the promotion and deployment problem rather than depending on the authentication center.Moreover,it resists to prefix and subprefix hijacking attacks and meets the performance and security requirements of route registration.

Selection and Research for Online Registration System’s Database System

Based on the Online Registration System (ORS) characteristics and key technology analysis, this paper points out that that a good performance and high stability of the ORS lies in the choice of the system database. Database clustering technology which has merits such as concurrent processing, easy expansion, and high security is proposed to achieve database subsystem of ORS, and the design of the database cluster system framework is available in this paper. Finally, we also explore the database load balancing of the cluster system, heterogeneous database replication technology.

Design and Implementation of Clinic Appointment Registration System

Clinic Appointment Registration System is an important way to see a doctor, and it’s also a preliminary tool for storage and management of clinic medical records. This new system was developed using Visual Studio 2008 and C#.NET as the development environment and tools and Microsoft Access 2003 as the database to store the medical data based on Browse/Server (B/S) model. The system consists of several data operation functions including appointment registration, data management (e.g. addition, deletion and searching), data backup and recovery, etc., thus, achieve key research ob-jectives.

User and Systems Requirement Framework for Electronic Land Registration Systems Decentralisation in Ghana

Although land registration systems are constantly changing based on entrenched institutional frameworks,they cannot fulfill their technical objectives.Technical designs based on loopholes in the existing land registration system are the common steps in advanced countries.However,the missing link between the implementation of technical designs and their uses and users,affect the prospects of land registration decentralisation in developing countries.User and System requirements are used to integrate and enhance land registration services delivery across land information systems.This study assesses and develops framework for decentralised electronic land registration systems in Ghana.Semi-structured interviews were used to collect user and system requirement data from clients and technical staff of the Lands Commission in Accra.The framework pointed out five main policy outline strategies.These include land registration process modeling(process reduction and turnaround time monitoring),technical function(file tracking),the effect of changes in the registration loupe and absorption of land registration report,land registration workflow improvement,and the use of aerial images.The study recommends a systemic monitoring and evaluation of staff job roles.

Registration system reform and initial public offering ownership preference:Evidence from China

Whether registration system reform(RSR)can curb administrative intervention and create a fair market environment has long been a concern in China.We explore this issue from the perspective of the initial public offering(IPO)preference based on the entropy balancing method,and findings are as follows.First,an IPO ownership preference exists under approval system.That is,state-owned enterprises(SOEs)are more likely than private enterprises to obtain IPO approval.However,RSR significantly changes this preference,especially for non-politically connected private enterprises.Second,the post-IPO market performance of SOEs is inferior to that of private enterprises under approval system,thus excluding the view that approval is prioritized for SOEs because of superior performance.Third,compared with SOEs,private enterprises are more likely to switch the issuance system from approval system to registration system;this change makes it easier for them to obtain IPO approval,indicating that private enterprise owners perceive the registration channel to be fairer.Fourth,the effect of RSR on IPO ownership preference mainly occurs in companies in three major urban agglomerations in China—the Pearl River Delta,the Yangtze River Delta,and the Beijing–Tian jin–Hebei region—and in technology-intensive industries.Collectively,our findings reveal that RSR cultivates a fairer IPO approval process.

Nonlinear Registration of Brain Magnetic Resonance Images with Cross Constraints of Intensity and Structure

Many deep learning-based registration methods rely on a single-stream encoder-decoder network for computing deformation fields between 3D volumes.However,these methods often lack constraint information and overlook semantic consistency,limiting their performance.To address these issues,we present a novel approach for medical image registration called theDual-VoxelMorph,featuring a dual-channel cross-constraint network.This innovative network utilizes both intensity and segmentation images,which share identical semantic information and feature representations.Two encoder-decoder structures calculate deformation fields for intensity and segmentation images,as generated by the dual-channel cross-constraint network.This design facilitates bidirectional communication between grayscale and segmentation information,enabling the model to better learn the corresponding grayscale and segmentation details of the same anatomical structures.To ensure semantic and directional consistency,we introduce constraints and apply the cosine similarity function to enhance semantic consistency.Evaluation on four public datasets demonstrates superior performance compared to the baselinemethod,achieving Dice scores of 79.9%,64.5%,69.9%,and 63.5%for OASIS-1,OASIS-3,LPBA40,and ADNI,respectively.

Household registration system faces overhaul

The government plans to lift re-strictions on where people work andlive.The move wi1l create a more mo-bile workforce it is hoped.The ministries of public security,construction and agriculture as well asthe State Commission for Restructur-ing the Economy have started surveysas a first step to reforming the systemof household registration in smalltowns and cities.

Accelerating the Reform of the Household Registration System to Ensure the Realization of Registered Population Urbanization Objectives and Tasks

Zhang Gaoli,Member of the Standing Committee of the Political Bureau of the CPC Central Committee and Vice Premier of the State Council,attended a teleconference on promoting the national household registration system reform and made a speech on Jul 7,2017.Zhang said that the CPC Central Committee and the State Council attached great importance to the reform of the household registration system。

Registration Based on ORB and FREAK Features for Augmented Reality Systems

This paper proposes a novel registration method for augmented reality(AR) systems based on Oriented FAST and RotatedBRIEF(ORB) and Fast Retina Keypoint(FREAK) natural features. In the proposed ORBFREAK method, feature extraction is implemented based on the combination of ORB and FREAK, and the feature points are matched using Hamming distance. To get good matching points, cross-checks and least median squares are used to perform outlier filtration, and camera pose is estimated using the matched points. Finally, AR is rendered.Experiments show that the proposed method improves the speed of registration to be in real time; the proposed method can accurately register the target object under the circumstances of partial occlusion of the object; and it also can overcome the effects of rotation, scale change, ambient light and distance.

Global pattern and trends of colorectal cancer survival: a systematic review of population-based registration data

This review will describe the global patterns and trends of colorectal cancer survival,using data from the population-based studies or cancer registration.We performed a systematic search of China National Knowledge Infrastructure(CNKI),Wanfang Data,PubMed,Web of Science,EMBASE,and SEER and collected all population-based survival studies of colorectal cancer(up to June 2020).Estimates of observed and relative survival rates of colorectal cancer by sex,period,and country were extracted from original studies to describe the temporal patterns and trends from the late 1990s to the early 21st century.Globally,5-year observed survival rates were higher in Seoul,Republic of Korea(1993–1997;56.8%and 54.3%for colon and rectum cancers,respectively),Zhejiang province(2005–2010;52.9%for colon cancer),Tianjin(1991–1999;52.5%for colon cancer),Shanghai(2002–2006;50.0%for rectum cancer)of China,and in Japan(1993–1996,59.6%for colorectal cancer).Five-year relative survival rates of colorectal cancer in the Republic of Korea(2010–2014),Queensland,Australia(2005–2012),and the USA(2005–2009)ranked at relatively higher positions compared to other countries.In general,colorectal cancer survival rates are improving over time worldwide.Sex disparities in survival rates were also observed in the colon,rectum,and colorectal cancers in most countries or regions.The poorest age-specific 5-year relative survival rate was observed in patients>75 years of age.In conclusion,over the past 3 decades,colorectal cancer survival has gradually improved.Geographic variations,sex differences,and age gradients were also observed globally in colorectal cancer survival.Further studies are therefore warranted to investigate the prognostic factors of colorectal cancer.

Joint Registration System under the Background of Big Data

With the increasing frequency of human social activity, the amount of data generated daily is also increasing exponentially. The recording medium of information has changed from the oldest carved stone to the current semiconductor carrier, which also pushes forward the progress of society. This also moves society into the big data era （BDE）, in which all things can be data. BD has helped people make many breakthroughs in political decision-making, economic policy, and more, and thus affects the human knowledge system and way of life.[1] The choice is no longer dependent on subjective judgment using imagination, but a large digital network in series consisting of habitual movement, physical movement, consumption, or medical record. In the medical field, many public databases are funded by the government and open to all researchers. BD for use in genomics, oncology, and proteomics provides resources and information that make healthcare and disease prevention more personalized and the digitalization of medicine unstoppable.[2] The convergence of digital and medical is inevitable, and the current changes have appeared to be a good start.

Disordered Multi-view Registration Method Based on the Soft Trimmed Deep Network

Compared with the pair-wise registration of point clouds,multi-view point cloud registration is much less studied.In this dissertation,a disordered multi-view point cloud registration method based on the soft trimmed deep network is proposed.In this method,firstly,the expression ability of feature extraction module is improved and the registration accuracy is increased by enhancing feature extraction network with the point pair feature.Secondly,neighborhood and angle similarities are used to measure the consistency of candidate points to surrounding neighborhoods.By combining distance consistency and high dimensional feature consistency,our network introduces the confidence estimation module of registration,so the point cloud trimmed problem can be converted to candidate for the degree of confidence estimation problem,achieving the pair-wise registration of partially overlapping point clouds.Thirdly,the results from pair-wise registration are fed into the model fusion to achieve the rough registration of multi-view point clouds.Finally,the hierarchical clustering is used to iteratively optimize the clustering center model by gradually increasing the number of clustering categories and performing clustering and registration alternately.This method achieves rough point cloud registration quickly in the early stage,improves the accuracy of multi-view point cloud registration in the later stage,and makes full use of global information to achieve robust and accurate multi-view registration without initial value.

A Study on Forecasting System of Patent Registration Based on Bayesian Network

Recently the importance of intellectual property has been increased. There has been various ways of research on analy- sis of companies, forecast of technology and so on through patents and many investments of money and time. Unlike traditional method of patent analysis such as company analysis, forecasting technologies, this research is to suggest the ways to forecast registration and rejection of patents which help minimize the efforts to register patents. To do so, in- formation such as inventors, applicants, application date, and IPC codes were extracted to be used as input variables for analyzing Bayesian network. Especially, among various forms of Bayesian network, we used Tree Augmented NBN (TAN) to forecast registration and rejection of patent. This is because, TAN was assumed to have dependence between variables. As a result of this Bayesian network, it was shown that there are nearly more than 80% of accuracy to fore- cast registration and rejection of patents. Therefore, we expect the minimization of time and cost of registration by forecasting registration and rejection of R&D patent through this research.

Research on the System of Preliminary Registration in the Property Right Law of China

In property transactions,there are many reasons for the debt agreement and the property registration that cause some timeinterval,which can easily lead to acts of infringing upon the interests of creditors,for example, a thing sold to different people at the sametime.Because in a number of transactions,the effectiveness of each contract is independent of each other, and this can lead to the occurrenceof credit,and each claim has the function of mutual tolerance and equality.Then set up multiple claims on the same item,the ownership of theproperty is difficult to determine because there is no priority.In order to ensure the realization of coming property rights,it is particularly importantto apply for preliminary registration to the registration authority.

Real-time continuous image guidance for endoscopic retrograde cholangiopancreatography based on 3D/2D registration and respiratory compensation

BACKGROUND It has been confirmed that three-dimensional(3D)imaging allows easier identification of bile duct anatomy and intraoperative guidance of endoscopic retrograde cholangiopancreatography(ERCP),which reduces the radiation dose and procedure time with improved safety.However,current 3D biliary imaging does not have good real-time fusion with intraoperative imaging,a process meant to overcome the influence of intraoperative respiratory motion and guide navigation.The present study explored the feasibility of real-time continuous image-guided ERCP.AIM To explore the feasibility of real-time continuous image-guided ERCP.METHODS We selected 23D-printed abdominal biliary tract models with different structures to simulate different patients.The ERCP environment was simulated for the biliary phantom experiment to create a navigation system,which was further tested in patients.In addition,based on the estimation of the patient’s respiratory motion,preoperative 3D biliary imaging from computed tomography of 18 patients with cholelithiasis was registered and fused in real-time with 2D fluoroscopic sequence generated by the C-arm unit during ERCP.RESULTS Continuous image-guided ERCP was applied in the biliary phantom with a registration error of 0.46 mm±0.13 mm and a tracking error of 0.64 mm±0.24mm.After estimating the respiratory motion,3D/2D registration accurately transformed preoperative 3D biliary images to each image in the X-ray image sequence in real-time in 18 patients,with an average fusion rate of 88%.CONCLUSION Continuous image-guided ERCP may be an effective approach to assist the operator and reduce the use of X-ray and contrast agents.

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

Airborne laser scanning(ALS)and terrestrial laser scanning(TLS)has attracted attention due to their forest parameter investigation and research applications.ALS is limited to obtaining fi ne structure information below the forest canopy due to the occlusion of trees in natural forests.In contrast,TLS is unable to gather fi ne structure information about the upper canopy.To 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 points.The 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 origin.The same feature point pairs of the ALS and TLS point cloud data were then selected to register the point cloud data.The initial registered point cloud data was fi nely and optimally registered via the iterative closest point(ICP)algorithm.The results show that the proposed method achieved highprecision registration of ALS and TLS point cloud data from two natural forest plots of Pinus yunnanensis Franch.and Picea asperata Mast.which included diff erent species and environments.An average registration accuracy of 0.06 m and 0.09 m were obtained for P.yunnanensis and P.asperata,respectively.

Automatic Extraction of the Sparse Prior Correspondences for Non-Rigid Point Cloud Registration

Non-rigid registration of point clouds is still far from stable,especially for the largely deformed one.Sparse initial correspondences are often adopted to facilitate the process.However,there are few studies on how to build them automatically.Therefore,in this paper,we propose a robust method to compute such priors automatically,where a global and local combined strategy is adopted.These priors in different degrees of deformation are obtained by the locally geometrical-consistent point matches from the globally structural-consistent region correspondences.To further utilize the matches,this paper also proposes a novel registration method based on the Coherent Point Drift framework.This method takes both the spatial proximity and local structural consistency of the priors as supervision of the registration process and thus obtains a robust alignment for clouds with significantly different deformations.Qualitative and quantitative experiments demonstrate the advantages of the proposed method.