Development of a risk index for cross-border data movement

Cross-border data transmission in the biomedical area is on the rise,which brings potential risks and management challenges to data security,biosafety,and national security.Focusing on cross-border data security assessment and risk management,many countries have successively issued relevant laws,regulations,and assessment guidelines.This study aims to provide an index system model and management application reference for the risk assessment of the cross-border data movement.From the perspective of a single organization,the relevant risk assessment standards of several countries are integrated to guide the identification and determination of risk factors.Then,the risk assessment index system of cross-border data flow is constructed.A case study of risk assessment in 358 biomedical organizations is carried out,and the suggestions for data management are offered.This study is condusive to improving security monitoring and the early warning of the cross-border data flow,thereby realizing the safe and orderly global flow of biomedical data.

Digital Development Rights in Developing Countries:Where the Governance Rules for Cross-Border Data Flows

The digital development rights in developing countries are based on establishing a new international economic order and ensuring equal participation in the digital globalization process to achieve people's well-rounded development in the digital society.The relationship between cross-border data flows and the realization of digital development rights in developing countries is quite complex.Currently,developing countries seek to safeguard their existing digital interests through unilateral regulation to protect data sovereignty and multilateral regulation for cross-border data cooperation.However,developing countries still have to face internal conflicts between national digital development rights and individual and corporate digital development rights during the process of realizing digital development rights.They also encounter external contradictions such as developed countries interfering with developing countries'data sovereignty,developed countries squeezing the policy space of developing countries through dominant rules,and developing countries having conflicts between domestic and international rules.This article argues that balancing openness and security on digital trade platforms is the optimal solution for developing countries to realize their digital development rights.The establishment of WTO digital trade rules should inherently reflect the fundamental demands of developing countries in cross-border data flows.At the same time,given China's dual role as a digital powerhouse and a developing country,it should actively promote the realization of digital development rights in developing countries.

Application of Big Data Analysis Technology in Cross-Border E-Commerce

Under the background of national development strategy in the new era,cross-border e-commerce with the help of Internet platfbnn can realize the interconnection between producers and consumers,and gradually expand the influence of international trade.Based on big data technology,this paper builds an industry chain with cross-border e-commerce members'participation,and analyzes the specific application of big data in the product support,internal operation,external marketing,logistics service and service evaluation of cross-border e-commerce industry chain.The purpose is to effectively promote the healthy development of cross-border e-commerce and improve China's trade and economic level.

The development of real time data driving multi-axis linkage and synergic movement control system of 3D variable cross-section roll forming machine

The three dimensional variable cross-section roll forming is a kind of new metal forming technol- ogy which combines large forming force, multi-axis linkage movement and space synergic movement, and the sequential synergic movement of the ganged roller group is used to complete the metal sheet forming according to the shape of the complicated and variable forming part data. The control system should meet the demands of quick response to the test requirements of the product part. A new kind of real time data driving multi-axis linkage and synergic movement control strategy of 3D roll forming is put forward in the paper. In the new control strategy, the forming data are automatically generated according to the shape of the parts, and the multi-axis linkage movement together with cooperative motion among the six stands of the 3D roll forming machine is driven by the real-time information, and the control nodes are also driven by the forming data. The new control strategy is applied to a 48 axis 3D roll forming machine developed by our research center, and the control servo period is less than 10ms. A forming experiment of variable cross section part is carried out, and the forming preci- sion is better than ＋ 0.5mm by the control strategy. The result of the experiment proves that the control strategy has significant potentiality for the development of 3D roll forming production line with large scale, multi-axis ganged and svner^ic movement

The movement age of hidden fault and analysis on width of its effect zone from shallow seismic sounding and drilling data

Field experimental seismic sounding permitted us to obtain optimal shallow seismic reflection sounding parameters.In process of data processing,we obtained a high-qualitative shallow seismic reflection sounding profile by using the techniques such as filtering,edition surgical blanking,prediction deconvolution,fitting static correlation of first arrival time,and velocity analysis.Comprehensive analysis on the information of reflection wave groups along the seismic sounding profile and the stratigraphic and neogeochronological data obtained from many drills near the sounding line reveals that the upper termination of the detected fault zone is located at depth of 75~80 m,in the Middle Pleistocene deposits dated to be about 220 ka BP.The continuity,discontinuity,increasing and decreasing amount of reflection wave groups and change of their configurations,in combination with geological columns of drills,permitted us to know that the width of upper termination of the fault zone is 100 m.It can be inferred from the variation of number of reflection wave groups along the profile that the scarp of hidden fault is 200 m wide and the fault is a synsedimentary active fault in the Early Pleistocene and the early stage of Middle Pleistocene.No tectonic movement,which offset the covering deposits,had occurred since the late stage of Middle Pleistocene.

Prediction of landslide block movement based on Kalman filtering data assimilation method

Compared with the study of single point motion of landslides,studying landslide block movement based on data from multiple monitoring points is of great significance for improving the accurate identification of landslide deformation.Based on the study of landslide block,this paper regarded the landslide block as a rigid body in particle swarm optimization algorithm.The monitoring data were organized to achieve the optimal state of landslide block,and the 6-degree of freedom pose of the landslide block was calculated after the regularization.Based on the characteristics of data from multiple monitoring points of landslide blocks,a prediction equation for the motion state of landslide blocks was established.By using Kalman filtering data assimilation method,the parameters of prediction equation for landslide block motion state were adjusted to achieve the optimal prediction.This paper took the Baishuihe landslide in the Three Gorges reservoir area as the research object.Based on the block segmentation of the landslide,the monitoring data of the Baishuihe landslide block were organized,6-degree of freedom pose of block B was calculated,and the Kalman filtering data assimilation method was used to predict the landslide block movement.The research results showed that the proposed prediction method of the landslide movement state has good prediction accuracy and meets the expected goal.This paper provides a new research method and thinking angle to study the motion state of landslide block.

Assessment of International GNSS Service Global Ionosphere Map products over China region based on measurements from the Crustal Movement Observation Network of China

The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of GIM products in data-sparse regions is of paramount importance.In this study,measurements from the Crustal Movement Observation Network of China(CMONOC)are leveraged to evaluate the suitability of IGS-GIM products over China region in 2013-2014.The indices of mean error(ME),root mean square error(RMSE),and normalized RMSE(NRMSE)are then utilized to quantify the accuracy of IGS-GIM products.Results revealed distinct local time and latitudinal dependencies in IGS-GIM errors,with substantially high errors at nighttime(NRMSE:39%)and above 40°latitude(NRMSE:49%).Seasonal differences also emerged,with larger equinoctial deviations(NRMSE:33.5%)compared with summer(20%).A preliminary analysis implied that the irregular assimilation of sparse IGS observations,compounded by China’s distinct geomagnetic topology,may manifest as error variations.These results suggest that modeling based solely on IGS-GIM observations engenders inadequate representations across China and that a thorough examination would proffer the necessary foundation for advancing regional total electron content(TEC)constructions.

Obtaining 2D Soil Resistance Profiles from the Integration of Electrical Resistivity Data and Standard Penetration Test (SPT) and Light Dynamic Penetrometer (DPL) Resistance Tests—Applications in Mass Movements Studies

In Brazil and various regions globally, the initiation of landslides is frequently associated with rainfall;yet the spatial arrangement of geological structures and stratification considerably influences landslide occurrences. The multifaceted nature of these influences makes the surveillance of mass movements a highly intricate task, requiring an understanding of numerous interdependent variables. Recent years have seen an emergence in scholarly research aimed at integrating geophysical and geotechnical methodologies. The conjoint examination of geophysical and geotechnical data offers an enhanced perspective into subsurface structures. Within this work, a methodology is proposed for the synchronous analysis of electrical resistivity geophysical data and geotechnical data, specifically those extracted from the Light Dynamic Penetrometer (DPL) and Standard Penetration Test (SPT). This study involved a linear fitting process to correlate resistivity with N10/SPT N-values from DPL/SPT soundings, culminating in a 2D profile of N10/SPT N-values predicated on electrical profiles. The findings of this research furnish invaluable insights into slope stability by allowing for a two-dimensional representation of penetration resistance properties. Through the synthesis of geophysical and geotechnical data, this project aims to augment the comprehension of subsurface conditions, with potential implications for refining landslide risk evaluations. This endeavor offers insight into the formulation of more effective and precise slope management protocols and disaster prevention strategies.

Research progress of 24-hour movement behaviors in chronic non-communicable disease

Chronic non-communicable diseases(NCDs)represent a significant impediment to improve life expectancy and remain a focal point in global public health and disease prevention efforts.24-hour movement behaviors,which include sleep,sedentary behavior(SED),and physical activity,underscore the inherent connections between different daily activities and the comprehensive impact of overall movement patterns on health.Evidence suggested that modifying patterns of 24-hour movement behaviors can aid in preventing and attenuating the progression of NCDs.This study systematically delineated the concept,evolution,analytical methods,and intrinsic associations of 24-hour movement behaviors,emphasizing their pivotal role in the prevention and management of NCDs such as obesity,mental disorders,cardiovascular diseases,diabetes,and renal diseases.Future research endeavors should focus on refining methodologies,broadening study populations,developing research tools,and exploring precise intervention strategies and interdisciplinary approaches to comprehensively enhance the effectiveness of NCDs prevention and management from a temporal perspective.Such efforts are poised to provide substantive guidance and support for public health practices.

Data synchronization in IMU/GPS integrated measurement system of vehicle motion parameters

To realize the data synchronization between the inertial measurement unit （IMU） and the global positioning system （GPS）, the synchronization technology in the IMU/GPS integrated measurement system of vehicle motion parameters is studied. According to the characteristics of the output signals of the IMU and the GPS, without the IMU synchronization signal, the synchronization circuit based on CPLD is designed and developed, which need not alter the configurations of the IMU and GPS. Experiments of measuring vehicle motion parameters, which rely on the synchronization circuit to realize IMU/GPS data synchronization, are made. The driving routes in experiments comprise a curve and a straight line. Experimental results show that the designed circuit can accurately measure the synchronization time difference and the IMU period, and can effectively solve the data synchronization in IMU/GPS integration. Furthermore, the IMU/GPS integrated measurement system based on the synchronization circuit can measure and calculate many vehicle motion parameters in high frequency mode.

Mass movements in small canyons in the northeast of Baiyun deepwater area, north of the South China Sea

The process of mass movements and their consequent turbidity currents in large submarine canyons has been widely reported, however, little attention was paid to that in small canyons. In this paper, we document mass movements in small submarine canyons in the northeast of Baiyun deepwater area, north of the South China Sea （SCS）, and their strong effects on the evolution of the canyons based on geophysical data. Submarine canyons in the study area arrange closely below the shelf break zone which was at the depth of -500 m. Within submarine canyons, seabed surface was covered with amounts of failure scars resulted from past small-sized landslides. A complex process of mass transportation in the canyons is indicated by three directions of mass movements. Recent mass movement deposits in the canyons exhibit translucent reflections or parallel reflections which represent the brittle deformation and the plastic deformation, respectively. The area of most landslides in the canyons is less than 3 km2. The trigger mechanisms for mass movements in the study area are gravitational overloading, slope angle and weak properties of soil. Geophysical data indicate that the genesis of submarine canyons is the erosion of mass movements and consequent turbidity currents. The significant effects of mass movements on canyon are incision and sediment transportation at the erosion phases and fillings supply at the fill phases. This research will be helpful for the geological risk assessments and understanding the sediment transportation in the northern margin of the SCS.

Sea surface temperature data from coastal observation stations:quality control and semidiurnal characteristics

Sea surface temperature(SST)data obtained from coastal stations in Jiangsu,China during 20102014 are quality controlled before analysis of their characteristic semidiurnal and seasonal cycles,including the correlation with the variation of the tide.Quality control of data includes the validation of extreme values and checking of hourly values based on temporally adjacent data points,with 0.15℃/h considered a suitable threshold for detecting abnormal values.The diurnal variation amplitude of the SST data is greater in spring and summer than in autumn and winter.The diurnal variation of SST has bimodal structure on most days,i.e.,SST has a significant semidiurnal cycle.Moreover,the semidiurnal cycle of SST is negatively correlated with the tidal data from March to August,but positively correlated with the tidal data from October to January.Little correlation is detected in the remaining months because of the weak coastal offshore SST gradients.The quality control and understanding of coastal SST data are particularly relevant with regard to the validation of indirect measurements such as satellite-derived data.

Mirror Mapping of Laser Interferometer Measurement System on Ultra-precise Movement Stage

The accuracy and repeatability of the laser interferometer measurement system （LIMS） are often limited by the mirror surface error that comes from the mirror surface shape and distortion. This paper describes a new method to calibrate mirror map on ultraprecise movement stage （UPMS） with nanopositioning and to make a real-time compensation for the mirror surface error by using mirror map data tables with the software algorithm. Based on the mirror map test model, the factors affecting mirror map are analyzed through geometric method on the UPMS with six digrees of freedom. Dam processing methods including spline interpolation and spline offsets are used to process the raw sampling data to build mirror map tables. The linear interpolation as compensation method to make a real-time correction on the stage mirror unflatness is adopted and the correction formulas are illuminated. In this way, the measurement accuracy of the system is obviously improved from 40 nm to 5 nm.

Radarsat observations and forecasting of oil slick trajectory movements

RADARSAT data have a potential role for coastal pollution monitoring. This study presents a new approach to detect and forecast oil slick trajectory movements. The oil slick trajectory movements is based on the tidal current effects and Fay's algorithm for oil slick spreading mechanisms. The oil spill trajectory model contains the integration between Doppler frequency shift model and Lagrangian model. Doppler frequency shift model implemented to simulate tidal current pattern from RADARSAT data while the Lagrangian model used to predict oil spill spreading pattern. The classical Fay's algorithm was implemented with the two models to simulate the oil spill trajectory movements.The study shows that the slick lengths are effected by tidal current V component with maximum velocity of 1.4 m/s. This indicates that oil slick trajectory path is moved towards the north direction. The oil slick parcels are accumulated along the coastline after 48 h. The analysis indicated that tidal current V components were the dominant forcing for oil slick spreading.

Vertical deformation analysis based on combined adjustment for GNSS and leveling data

A method is proposed to fuse the velocity data of the global navigation satellite system(GNSS) and leveling height via combined adjustment with constraints. First, stable GNSS-leveling points are uniformly selected, and the constraints of the geodetic height change velocity and normal height change velocity are given. Then, the GNSS vertical velocities and leveling height difference are used as observations of combined adjustment, and robust least-squares estimation are used to estimate the velocities of the unknown points. Finally, a vertical movement model is established with the GNSS vertical velocities and leveling vertical velocities obtained via combined adjustment. Data from the second-order leveling network and GNSS control points in Shandong Province are taken as test data, and eight calculation schemes are used for discussion. One of the schemes, the bifactor robust combined adjustment method based on variance component estimation with two kinds of vertical velocity constraints achieves the optimal results. The method applied in the scheme can be recommended for data fusion of GNSS and leveling, further improving the reliability of vertical crustal movement in Shandong Province.

Exploiting Data Science for Measuring the Performance of Technology Stocks

The rise or fall of the stock markets directly affects investors’interest and loyalty.Therefore,it is necessary to measure the performance of stocks in the market in advance to prevent our assets from suffering significant losses.In our proposed study,six supervised machine learning(ML)strategies and deep learning(DL)models with long short-term memory(LSTM)of data science was deployed for thorough analysis and measurement of the performance of the technology stocks.Under discussion are Apple Inc.(AAPL),Microsoft Corporation(MSFT),Broadcom Inc.,Taiwan Semiconductor Manufacturing Company Limited(TSM),NVIDIA Corporation(NVDA),and Avigilon Corporation(AVGO).The datasets were taken from the Yahoo Finance API from 06-05-2005 to 06-05-2022(seventeen years)with 4280 samples.As already noted,multiple studies have been performed to resolve this problem using linear regression,support vectormachines,deep long short-termmemory(LSTM),and many other models.In this research,the Hidden Markov Model(HMM)outperformed other employed machine learning ensembles,tree-based models,the ARIMA(Auto Regressive IntegratedMoving Average)model,and long short-term memory with a robust mean accuracy score of 99.98.Other statistical analyses and measurements for machine learning ensemble algorithms,the Long Short-TermModel,and ARIMA were also carried out for further investigation of the performance of advanced models for forecasting time series data.Thus,the proposed research found the best model to be HMM,and LSTM was the second-best model that performed well in all aspects.A developedmodel will be highly recommended and helpful for early measurement of technology stock performance for investment or withdrawal based on the future stock rise or fall for creating smart environments.

GatherTweet: A Python Package for Collecting Social Media Data on Online Events

Social media plays a crucial role in the organization of massive social movements. However, the sheer quantity of data generated by the events as well as the data collection restrictions that researchers encounter, leads to a series of challenges for researchers who want to analyze dynamic public discourse and opinion in response to and in the creation of world events. In this paper we present gatherTweet, a Python package that helps researchers efficiently collect social media data for events that are composed of many decentralized actions (across both space and time). The package is useful for studies that require analysis of the organizational or baseline messaging before an action, the action itself, and the effects of the action on subsequent public discourse. By capturing these aspects of world events gatherTweet enables the study of events and actions like protests, natural disasters, and elections.

Trace Interpolation Algorithm Based on Intersection Vehicle Movement Modeling

Real vehicle tracking data play an important role in the research of routing in vehicle sensor networks. Most of the vehicle tracking data, however, were collected periodically and could not meet the requirements of real-time by many applications. Most of the existing trace interpolation algorithms use uniform interpolation methods and have low accuracy problem. From our observation, intersection vehicle status is critical to the vehicle movement. In this paper, we proposed a novel trace interpolation algorithm. Our algorithm used intersection vehicle movement modeling (IVMM) and velocity data mining (VDM) to assist the interpolation process. The algorithm is evaluated with real vehicle GPS data. Results show that our algorithm has much higher accuracy than traditional trace interpolation algorithms.

GPS DATA INVERSION OF KINEMATIC MODEL OF MAIN FAULTS IN YUNNAN

On the basis of GPS observations in Yunnan from 1999 to 2001, we adopt the robust Bayesian least square estimation and multi fault dislocation model to analyze the quantitative kinematics models of the main faults in Yunnan. The geodetic inversion suggests that: (1) The horizontal movement of crust in Yunnan is affected distinctly by fault activity whose characters are consistent with geological results; (2) The activity of the north segment of the Red River fault zone is maximum, in the middle segment is moderate, and in the south segment is minimum; (3)Among others, the Xiaojiang fault zone has the strongest activity, the secondary are the Lancang fault zone and the north segment of Nujiang fault zone, the Qujiang fault zone shows the characteristic of hinge fault; (4)Each fault could produce an earthquake of M s=6 more or less per year; (5) The larger value of maximum shear strain are mostly located along the main active fault zones and their intersections; earthquakes did not occur at the place of maximum shear strain, and mostly take place at the higher gradient zones, especially at its corner.

欧盟金融数据治理:框架、重点与启示

加强金融数据治理,促进金融数据顺畅流动和高效使用,是经济高质量发展的内在要求。经过多年发展,欧盟积累了较为丰富的数据治理经验,并逐步建立起较为完善的数据治理体系。前期,欧盟强调个人数据保护;但在过去的3~4年,数字经济立法更加强调消除数据流动障碍,促进数据共享。目前,欧盟在数据权利界定、权利保护、跨境流动等方面已建立了较为完善的法律体系,并形成了从欧盟到成员国再到金融业最后到单一金融机构的统一性、垂直性和专业化的金融数据治理体系。我国可学习欧盟经验,加强对国家数字经济和数字金融发展的顶层设计,以法制建设为核心完善金融数据治理的长效机制,强化金融数据跨境安全流动机制,加强数据流动应用和价值挖掘,高质量发展数字市场和数字服务,提升数字金融的国际竞争力,推进金融强国建设。