Research on the Legal Framework of Content Regulations for Network Platforms

In the era of the Internet,various network platforms have evolved into new hubs for information dissemination.Currently,China has established a platform-centered content regulation framework,wherein platforms proactively enforce content regulations in accordance with legal censorship obligations.Additionally,platform policies and user agreements augment their authority in content regulation.The platforms can achieve cost-effective and highly efficient content regulation by leveraging their strategic advantages enabled by their own technical capabilities and extensive coverage.The platform self-regulation model,however,still faces challenges.First,accurately evaluating content remains a formidable task;second,ensuring effective platform publicity through self-regulation poses difficulties;third,users may potentially face disadvantages due to the platform’s right of self-regulation;and fourth,digital copyright owners face challenges when defending digital copyright disputes under the safe harbor rule.Therefore,it is imperative to establish,review,and revise the legal framework for content regulation of network platforms in order to enhance the efficiency of their governance systems.The formulation of the legal framework for content regulation of network platforms may encompass the following aspects:rationalizing obligations pertaining to platform content regulations,enhancing supervision over platform self-regulation,and establishing a dual-track responsibility system for digital copyright content regulation.This will ensure a harmonious balance among public interests,users’personal rights and interests,and commercial benefits through regulating the content on network platforms.

Research on Network Security Level Protection Measurement Strategy in the Context of Cloud Platforms

Platforms facilitate information exchange,streamline resources,and reduce production and management costs for companies.However,some viral information may invade and steal company resources,or lead to information leakage.For this reason,this paper discusses the standards for cybersecurity protection,examines the current state of cybersecurity management and the risks faced by cloud platforms,expands the time and space for training on cloud platforms,and provides recommendations for measuring the level of cybersecurity protection within cloud platforms in order to build a solid foundation for them.

基于OneNET云平台的智慧消防远程监控系统的设计

针对传统消防监控系统存在开发成本高、误警率高、实时监控不便的问题,提出一种基于物联网云平台的智慧消防远程监控系统。采用STM32单片机作为中枢控制芯片,经多传感器采集温度、湿度、烟雾、火焰等环境数据,通过窄带物联网(NB-IoT,Narrow Band Internet of Things)上传至OneNET云平台。经数据分析后以可视化方式呈现,对异常数据触发报警实时响应。通过手机APP实现数据实时监测及一键处置。经测试,监控系统报警准确率高于97.2%,数据延迟低于50 ms,表明该系统能够实现消防火警的无线远程监控,并做出快速反应,满足中小微企业和普通家庭用户的消防监控需要。

结合改进ShuffleNet-V2和注意力机制的无人机图像自主分类预警框架

为实现灾难事件的无人机(Unmanned Aerial Vehicle,UAV)自主监测和预警,提出了结合逐通道注意力机制和高效卷积神经网络的新架构。考虑到嵌入式平台的资源限制条件,使用轻量级ShuffleNet-V2作为骨干网络,能够对更多信息进行高效编码并尽可能降低网络复杂度。为进一步提高灾难场景分类的准确度,在ShuffleNet-V2网络中结合了挤压-激发(Squeeze-Excitation,SE)模块以实现逐通道注意力机制,显著增强分类网络对重要特征的关注度。通过数据采集和增强技术获得包括12876张图像的UAV航拍灾难事件数据集,对所提方法进行性能评估,并比较所提方法与其他先进模型的性能。结果表明,所提方法取得了99.01%的平均准确度,模型大小仅为5.6 MB,且在UAV机载平台上的处理速度超过10 FPS,能够满足UAV平台自主灾情监测任务的现实需求。

Experiment Verification of Damage Detection for Offshore Platforms by Neural Networks

In the present work, damage detection for offshore platforms is divided into three steps. Firstly, the located direction of the damaged member is detemfined by the pmbabilistic neural network with input of the change rate of normalized medal frequency. Secondly, the profile and layer of the damaged member is also determined by the pmbabilistic neural network with input of the normalized damage-signal index. Finally, the damage extent is determined by the back propagation neural networks with input of the squared change rate of modal frequency. So the size of the network and the training time can be reduced greatly. All these networks are trained with simulated data obtained from the finite element model of an experiment model. Then these trained neural networks are examined with data obtained from impulse tests on the experiment model. The experiment results show that the trained neural networks are able to detect the damaged member with reasonable accuracy.

Neural Network-Based Active Control for Offshore Platforms

A new active control scheme, based on neural network, for the suppression of oscillation in multiple-degree-of-freedom (MDOF) offshore platforms, is studied in this paper. With the main advantages of neural network, i.e. the inherent robustness, fault tolerance, and generalized capability of its parallel massive interconnection structure, the active structural control of offshore platforms under random waves is accomplished by use of the BP neural network model. The neural network is trained offline with the data generated from numerical analysis, and it simulates the process of Classical Linear Quadratic Regular Control for the platform under random waves. After the learning phase, the trained network has learned about the nonlinear dynamic behavior of the active control system, and is capable of predicting the active control forces of the next time steps. The results obtained show that the active control is feasible and effective, and it finally overcomes time delay owing to the robustness, fault tolerance, and generalized capability of artificial neural network.

Semi-Active TLCD Control of Fixed Offshore Platforms Using Artifical Neural Networks

In this paper, the control method for fixed offshore platforms using semi-active tuned liquid column damper (TLCD) is presented. The equation of motion for the platform-TLCD control system is given and the semi-active control strategy is established. A back propagation artificial neural network (ANN) is used to adjust the orifice opening of TLCD because of the nonlinear motion of liquid in TLCD. The effectiveness of the control method is verified by numerical examples.

基于Kubernetes的工业AI项目开发平台

随着人工智能(AI)成为改变世界的前沿技术,企业也迫切需要系统地开发和实现人工智能来升级新一代工业系统的基础。考虑到将人工智能应用开发集成到工业开发中存在开发流程环节多、AI项目开发人员能力背景不一等问题,以企业实际需求为背景设计实现了一个AI项目开发平台。探讨了人工智能项目开发平台的概念和实现,并且基于企业实际需求对其进行定制化。在传统开发流程基础上完善更多开发工作流环节。在企业内部成功进行部署和测试。结果表明:项目开发平台的功能合理、运行正常、管理便捷对AI项目开发效率、体验、规范化有积极影响,提高了计算加速部件利用率。

基于One NET云平台和北斗GPS双模定位的智慧停车系统

本文指出目前智慧停车面临三大技术难题:一是如何实现高精度停车位置定位;二是如何准确实现车位空闲状态检测;三是构建互联互通的停车场停车信息网络系统并对接到云平台,实现整个城市停车信息的大数据共享。为此,本文设计了一款基于OneNET云平台和北斗GPS双模定位的智慧停车系统,从理论上可解决上述3个关键问题。系统经过测试运行正常,数据收发正常,各传感器和北斗GPS定位数据准确,云平台数据更新保持在1~2 s之间。表明该系统具有车位状态监测准确、位置定位可精确到分米级别、数据上传到云平台存储和显示快速及时的特点,能够提高停车场的利用率和周转率,方便车主出行和生活。

Vibration Control of Jacket Platforms with Magnetorheological Damper and Experimental Validation~

Magnetorheological （MR） dampers have been proposed to control the vibration of offshore platforms in this paper. The semi-active control strategy based on fuzzy control algorithm was adopted to determine the optimal output control force based on the responses of jacket platforms. A typical jacket platform in Mexico Gulf was selected as the numerical example to investigate the effectiveness of the proposed control method. Furthermore, a model experiment was performed to validate the results of the numerical simulation. The experimental model of the jacket platform was designed based on dynamical similarity criterion by the scale of 1：50. Both of the numerical and experimental results show that the semi-active control system with the MR damper can reduce vibrations of jacket platforms effectively and at the same time the control effect is stable.

基于OneNET平台的语音控制室内环境监测系统设计

互联网越来越发达,人们对智能化设备的要求越来越高。基于OneNET平台对室内环境监测系统进行设计,系统包括环境参数采集模块、语音控制模块、显示模块、报警模块和继电器模块,可根据环境采集参数控制窗帘和灯光、空调、加湿器、窗户、排风扇,同时在OLED屏和云平台上显示环境采集参数。系统有手动、自动、语音和远程4种控制模式,实现对以上设备开启或关闭控制。实物的研制成功,不仅对室内污染防患于未然,而且可以实时了解家居环境情况和安全情况,提升居住的安全感和幸福感。

Application of GNSS-PPP on Dynamic Deformation Monitoring of Offshore Platforms

The real-time dynamic deformation monitoring of offshore platforms under environmental excitation is crucial to their safe operation.Although Global Navigation Satellite System-Precise Point Positioning(GNSS-PPP)has been considered for this purpose,its monitoring accuracy is relatively low.Moreover,the influence of background noise on the dynamic monitoring accuracy of GNSS-PPP remains unclear.Hence,it is imperative to further validate the feasibility of GNSS-PPP for deformation monitoring of offshore platforms.To address these concerns,vibration table tests with different amplitudes and frequencies are conducted.The results demonstrate that GNSS-PPP can effectively monitor horizontal vibration displacement as low as±30 mm,which is consistent with GNSS-RTK.Furthermore,the spectral characteristic of background noise in GNSS-PPP is similar to that of GNSS-RTK(Real Time Kinematic).Building on this observation,an improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)has been proposed to de-noise the data and enhance the dynamic monitoring accuracy of GNSS-PPP.Field monitoring application research is also undertaken,successfully extracting and analyzing the dynamic deformation of an offshore platform structure under environmental excitation using GNSS-PPP monitoring in conjunction with improved CEEMDAN de-noising.By comparing the de-noised dynamic deformation trajectories of the offshore platform during different periods,it is observed that the platform exhibits reversible alternating vibration responses under environmental excitation,with more pronounced displacement deformation in the direction of load action.The research results confirm the feasibility and potential of GNSS-PPP for dynamic deformation monitoring of offshore platforms.

Design and Implementation of a Network Performance Analysis System for Space Network Emulation Platforms

Emulation platforms are critical for evaluation and verification in the research of networking technologies and protocols for space networks(SN).High fidelity emulating technologies have been extensively studied for SN in earlier work,while little emphasis has been placed on the performance evaluation part.In this paper,the design of a network performance analysis architecture is presented,with which high-speed network traffic can be captured and indexed,and the performance of the emulated SN can be well analyzed and evaluated.This architecture comprises three components,namely capture layer,storage layer and analysis layer.Analytic Hierarchy Process(AHP)and several analysis methods are adopted to evaluate the network performance comprehensively.In the implementation of the proposed architecture,configuration optimization and parallel processing are applied to handle large amount of high-speed network traffic.Finally,experiment results through the analysis system exhibits the effectiveness of the proposed architecture.

Characteristics of Patients Sponsored by the Internet Platforms of Medical Mutual Aid

The morbidity and mortality of life-threatening diseases such as cancers are increasing year by year in China. Although the national medical insurance has been improved a lot, it still falls short of expecting “universal medical insurance”. To help the families of patients with cancer and other serious diseases to resolve the unaffordable medical cost, several internet platforms of “Peer to Peer Medical Mutual Aid” have gradually emerged recently. In the form of low threshold insurance combined with public support, these platforms provide subsidies to families of patients suffering from serious financial burden and then partly compensate them for the limit of national medical insurance. This article summarized the characteristics of declared patients sponsored by several medical mutual aid internet platforms. The results showed that the sponsored patients were mostly cancer patients (90.1%), aged 21 - 60 (88.4%), and the average amounts of financial support had a trend to decrease with the increase of age. In particular, the reported cases of thyroid cancer were increased dramatically recently, however, with a lowest average mutual aid fund. Given these data, it is urgent to list out a detailed rule for the use of national medical insurance on the treatment of cancer, to heighten the healthcare system for the occupational population, age from 21 to 60, and to establish the credit system for Medicare and Medicaid services.

Sedimentary build-ups of pre-salt isolated carbonate platforms and formation of deep-water giant oil fields in Santos Basin,Brazil

In response to the problems of unclear distribution of deep-water pre-salt carbonate reservoirs and formation conditions of large oil fields in the Santos passive continental margin basin,based on comprehensive utilization of geological,seismic,and core data,and reconstruction of Early Cretaceous prototype basin and lithofacies paleogeography,it is proposed for the first time that the construction of pre-salt carbonate build-ups was controlled by two types of isolated platforms:inter-depression fault-uplift and intra-depression fault-high.The inter-depression fault-uplift isolated platforms are distributed on the present-day pre-salt uplifted zones between depressions,and are built on half-and fault-horst blocks that were inherited and developed in the early intra-continental and inter-continental rift stages.The late intra-continental rift coquinas of the ITP Formation and the early inter-continental rift microbial limestones of the BVE Formation are continuously constructed;intra-depression fault-high isolated platforms are distributed in the current pre-salt depression zones,built on the uplifted zones formed by volcanic rock build-ups in the early prototype stage of intra-continental rifts,and only the BVE microbial limestones are developed.Both types of limestones formed into mound-shoal bodies,that have the characteristics of large reservoir thickness and good physical properties.Based on the dissection of large pre-salt oil fields discovered in the Santos Basin,it has been found that both types of platforms could form large-scale combined structural-stratigraphic traps,surrounded by high-quality lacustrine and lagoon source rocks at the periphery,and efficiently sealed by thick high-quality evaporite rocks above,forming the optimal combination of source,reservoir and cap in the form of“lower generation,middle storage,and upper cap”,with a high degree of oil and gas enrichment.It has been found that the large oil fields are all bottom water massive oil fields with a unified pressure system,and they are all filled to the spill-point.The future exploration is recommended to focus on the inter-depression fault-uplift isolated platforms in the western uplift zone and the southern section of eastern uplift zones,as well as intra-depression fault-high isolated platforms in the central depression zone.The result not only provides an important basis for the advanced selection of potential play fairways,bidding of new blocks,and deployment of awarded exploration blocks in the Santos Basin,but also provides a reference for the global selection of deep-water exploration blocks in passive continental margin basins.

A Framework for Cybersecurity Alert Distribution and Response Network (ADRIAN)

Security Information and Event Management (SIEM) platforms are critical for organizations to monitor and manage their security operations centers. However, organizations using SIEM platforms have several challenges such as inefficiency of alert management and integration with real-time communication tools. These challenges cause delays and cost penalties for organizations in their efforts to resolve the alerts and potential security breaches. This paper introduces a cybersecurity Alert Distribution and Response Network (Adrian) system. Adrian introduces a novel enhancement to SIEM platforms by integrating SIEM functionalities with real-time collaboration platforms. Adrian leverages the uniquity of mobile applications of collaboration platforms to provide real-time alerts, enabling a two-way communication channel that facilitates immediate response to security incidents and efficient SIEM platform management. To demonstrate Adrian’s capabilities, we have introduced a case-study that integrates Wazuh, a SIEM platform, to Slack, a collaboration platform. The case study demonstrates all the functionalities of Adrian including the real-time alert distribution, alert customization, alert categorization, and enablement of management activities, thereby increasing the responsiveness and efficiency of Adrian’s capabilities. The study concludes with a discussion on the potential expansion of Adrian’s capabilities including the incorporation of artificial intelligence (AI) for enhanced alert prioritization and response automation.

A Coordinate-Free Approach to the Design of Generalized Griffis-Duffy Platforms

Architectural singularity belongs to the Type II singularity,in which a parallel manipulator(PM)gains one or more degrees of freedom and becomes uncontrollable.PMs remaining permanently in a singularity are beneficial for linearto-rotary motion conversion.Griffis-Duffy(GD)platform is a mobile structure admitting a Bricard motion.In this paper,we present a coordinate-free approach to the design of generalized GD platforms,which consists in determining the shape and attachment of both the moving platform and the fixed base.The generalized GD platform is treated as a combination of six coaxial single-loop mechanisms under the same constraints.Owing to the inversion,hidden in the geometric structure of these single-loop mechanisms,the mapping from a line to a circle establishes the geometric transformation between the fixed base and the moving platform based on the center of inversion,and describes the shape and attachment of the generalized GD platform.Moreover,the center of inversion not only identifies the location of rotation axis,but also affects the shape of the platform mechanism.A graphical construction of generalized GD platforms using inversion,proposed in the paper,provides geometrically feasible solutions of the manipulator design for the requirement of the location of rotation axis.

Performance of composite foundations with different load transfer platforms and substratum stiffness over silty clay

The semi-rigid pile-supported composite foundation is widely used in highway projects due to its effectiveness in increasing the bearing capacity and stability of foundations.It is crucial to understand the stress distribution across the embankment width and the behaviour of unreinforced foundations.Thus,five centrifuge tests were conducted to examine the bearing and deformation behaviours of NPRS(Non-Connected Piled Raft Systems)and GRPS(GeosyntheticReinforced Pile-Supported systems)with varying substratum stiffness,then a comparative analysis was conducted on embankment settlement,pressures underneath the embankments,and axial forces along the piles.The results indicated that greater substratum stiffness correlates with reduced settlement and deformation at various depths.Deformation occurring 5 meters from the embankment toe includes settlement in NPRS and upward movement in GRPS.The potential sliding surface is primarily located within the embankment in NPRS,whereas it may extend through both the embankment and foundation in GRPS.The pile-soil stress ratio and efficiency in NPRS are higher than in GRPS across the embankment.The axial force borne by end-bearing piles is significantly greater than that by floating piles.As the buried depth increases,the axial force in GRPS initially rises then declines,whereas in NPRS,it remains relatively constant within a certain range before decreasing.This study aids in assessing the applicability of composite foundations in complex railway environments and provides a reference for procedural measures under similar conditions.

Robotic complete mesocolic excision for right colon cancer:Learning curve,training,techniques,approach,platforms,and future perspectives

Colon cancer has the fifth highest incidence worldwide and has the sixth highest mortality.Compared with rectal cancer,colon cancer currently has the worst 5-year overall survival for patients with stage Ⅱ and Ⅲ disease.Complete mesocolic excision has been developed as a standardized and optimized surgical technique for the excision of colon cancers.This technique has traditionally been performed through an open approach since laparoscopy is generally considered technically challenging.The robotic approach has been slowly implemented for colon cancer,but the newest robotic platforms allow for a safer and optimized approach for right colon cancer.Several robotic approaches have been developed and explored.The expansion of the current robotic platform ecosystem is gradually providing new outputs in the application of the robotic approach to complete mesocolic excision.This review gains an oversight of existing literature on robotic complete mesocolic excision for right colon cancer(learning curve,training,techniques,approach,platforms,and future perspectives).

Predicting Purchasing Behavior on E-Commerce Platforms: A Regression Model Approach for Understanding User Features that Lead to Purchasing

This research introduces a novel approach to improve and optimize the predictive capacity of consumer purchase behaviors on e-commerce platforms. This study presented an introduction to the fundamental concepts of the logistic regression algorithm. In addition, it analyzed user data obtained from an e-commerce platform. The original data were preprocessed, and a consumer purchase prediction model was developed for the e-commerce platform using the logistic regression method. The comparison study used the classic random forest approach, further enhanced by including the K-fold cross-validation method. Evaluation of the accuracy of the model’s classification was conducted using performance indicators that included the accuracy rate, the precision rate, the recall rate, and the F1 score. A visual examination determined the significance of the findings. The findings suggest that employing the logistic regression algorithm to forecast customer purchase behaviors on e-commerce platforms can improve the efficacy of the approach and yield more accurate predictions. This study serves as a valuable resource for improving the precision of forecasting customers’ purchase behaviors on e-commerce platforms. It has significant practical implications for optimizing the operational efficiency of e-commerce platforms.