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。

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。

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。

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.

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.

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.

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.

Research on the Audio Publishing of Classical Books Based on the Theory of Business Model Canvas: Taking Romance of the Three Kingdoms in Digital Audio Platforms as an Example

Visual media have dominated sensory communications for decades,and the resulting“visual hegemony”leads to the call for the“auditory return”in order to achieve a holistic balance in cultural acceptance.Romance of the Three Kingdoms,a classic literary work in China,has received significant attention and promotion from leading audio platforms.However,the commercialization of digital audio publishing faces unprecedented challenges due to the mismatch between the dissemination of long-form content on digital audio platforms and the current trend of short and fast information reception.Drawing on the Business Model Canvas Theory and taking Romance of the Three Kingdoms as the main focus of analysis,this paper argues that the construction of a business model for the audio publishing of classical books should start from three aspects:the user evaluation of digital audio platforms,the establishment of value propositions based on the“creative transformation and innovative development”principle,and the improvement of the audio publishing infrastructure to ensure the healthy operation and development of the digital audio platforms and consequently improve their current state of development and expand the boundaries of cultural heritage.

Transforming Digital Experiences: The Evolution of Digital Experience Platforms (DXPs) from Monoliths to Microservices: A Practical Guide

The research aims to explore the transition from monolithic Digital Experience Platforms (DXPs) to Microservices-based DXPs, addressing scalability challenges. The study systematically decomposes monolithic structures into Microservices, emphasizing business capability and subdomain decomposition. Concrete insights, challenges, and solutions encountered during this transformation process are presented. The research contributes valuable insights into the challenges and benefits of adopting Microservices in DXPs. Results highlight the importance of architectural patterns and strategic scaling dimensions for improved performance and scalability. The case study on Backbase’s Engagement Banking Platform showcases successful implementation, providing flexibility, integration, and efficient development in the evolving DXP landscape.

基于.NET的番茄果园视觉特征管理系统

介绍了一种基于.NET平台的番茄果园视觉特征管理系统,旨在提高番茄果实的检测和识别效率,促进农业生产的智能化发展。随着信息技术的发展与普及,越来越多的农业生产活动开始向数字化、智能化的方向转变。同时,随着人口增长和城市化进程的加速,人们对蔬菜和水果的需求越来越大,对水果品质的要求也越来越高。而作为现代农业中重要的经济作物之一,番茄的种植和管理对于果农们来说至关重要。为了提高番茄种植的生产效率和品质,帮助果农实现对番茄种植全过程的管理。以位于辽宁省大连市旅顺口区某番茄果园为例,对系统框架的搭建,包括系统的数据结果和框架,同时对传感器数据和图像数据进行处理和数据分析,实现对果园内番茄的生长状态和品质的实时监测和管理,提高番茄果园的生产效率和品质,增加果农的生产效益和经济效益。

Application Analysis of Doctor-Nurse Cooperation Follow-up Model Based on the Internet Platform in Continuation Care of Patients after Urooncology Surgery

Objective:To explore the application effect of a doctor-nurse cooperation follow-up model based on an Internet platform in the continuation of care for patients after uro-oncology surgery.Methods:A convenient sampling method was used to select patients with urinary system tumors who underwent surgery in the Department of Urology in Grade III A general hospital in Shanghai from May to August 2022.Patients who underwent surgery from May to June 2022 were assigned to the control group,and those who underwent surgery from July to August 2022 were assigned to the experimental group.The control group received routine post-discharge nursing health education and telephone follow-up.On the basis of routine discharge guidance,the experimental group implemented the intervention method based on the Internet platform in continuation care.The levels of self-management efficacy,satisfaction,and incidence of unplanned readmission were compared one month after discharge between the two groups.Results:One month after discharge,the self-management efficacy of the experimental group(90.15±7.92)was significantly higher than that of the control group(79.10±7.84),and the patient satisfaction score(97.83±2.32)was significantly higher than that of the control group(90.23±2.58),with statistical significance(P<0.05).Additionally,the incidence of unplanned readmissions within one month after discharge in the experimental group(1.59%)was slightly lower than that in the control group(4.84%).Conclusion:The doctor-nurse cooperation follow-up model based on the Internet platform in continuation care can significantly improve the self-management efficiency of patients after discharge and enhance patient satisfaction,providing a new approach for discharge follow-up of urological tumor patients after surgery.

Structural Design Study of Air-Dropped Unmanned Maritime Mobile Search and Rescue Platforms

In order to improve the efficiency and safety of search and rescue(SAR)at sea,this paper proposes a kind of emergency rapid rescue unmanned craft(air-dropped unmanned maritime motorized search and rescue platform)that can be delivered by a large transport aircraft.This paper studies the structural design scheme of the platform,and the main scale of the platform,the choice of power system and the impact resistance performance are considered in the design process to ensure its rapid response and effective rescue capability under complex sea conditions.Simulation results show that the platform can withstand the impact of air injection into the water and the shipboard equipment can operate normally under the impact load,thus verifying the feasibility and safety of the design.This study serves to improve the maritime search and rescue system and enhance the oceanic emergency response capability.

面向深度学习Kubernetes负载饱和调度算法设计与实现

构建深度学习云平台的基础技术Kubernetes在调度过程中使用负载均衡策略,易产生资源碎片,增加任务等待时间。Kubernetes没有考虑对GPU等外部拓展资源的评分,不能很好适应深度学习云平台的业务场景。针对以上问题提出一种负载饱和调度策略,对Kubernetes调度过程进行改进,减少资源碎片,提高资源利用率。该策略支持对用户指定的外部拓展资源进行评分,能更好适应深度学习云平台业务场景。实验结果表明,负载饱和调度策略能够减少23.40%的任务等待时间,并能将GPU利用率提升14.15%,GPU显存利用率提升6.85%。

基于MobileNet-CBAM模型的轻量级鸟类识别方法

对于鸟类识别任务,当前一些深度学习网络模型的效果并不理想,针对现有模型的痛点,提出了一种在识别精度、计算性能、资源消耗和实用性上更具优势的轻量级鸟类识别方法。该方法基于轻量级MobileNet模型,融合了卷积注意力机制(Convolutional Block Attention Module,CBAM),在减少模型复杂度的同时增强了局部特征的提取能力,与主流模型的对比实验验证了该模型的有效性。此外,该模型能够应用于机器人、便携式手机等硬件平台,扩展了应用场景,并添加数据库来进行辅助计算,减少额外开销,兼具便携性和实用性。

基于PointNet优化网络的铁路站台语义分割

铁路站台点云语义分割是对铁路侵界现象进行检测的关键环节。文中以新型激光扫描测量系统采集的具有三维空间信息的点云数据为基础,在获取初步分割结果的基础上,设计PointNet网络整体结构提取点云数据全局特征,采用多层次金字塔结构对网络进行局部特征提取优化,实现铁路站台点云数据语义分割。研究表明,所提方法对实验点云数据的分割准确率达到84.5%,在铁路工程应用中的点云总体分割精度达到75.34%,在铁路检测中实现了大范围多尺度点云数据的可靠语义分割,满足铁路侵界现象检测分析需求。

基于ONENET云平台的家居环境多参数监测系统

针对目前监测系统对智能设备远程控制编程复杂,服务器成本较高的问题,文章设计了基于ONENET云平台的家居环境多参数监测系统的方案。该方案基于Lora低功耗无线通信技术,以STM32为主控芯片,选用多种传感器共同采集环境数据,采用Lora和WIFI无线通信模块,将采集到的数据传输到ONENET云平台上,用户可以登录云平台账号完成对家里环境的远程监控。实验结果表明,该系统性能可靠性高且成本低,具有较好的可实施性,可应用于普通家庭。

基于One NET云平台的肺结节数据集的设计与实现

肺癌的早期表现为肺CT图像中的微小结节,及早发现与治疗对于提高肺癌患者的生存率至关重要。近年来,目标检测技术逐渐被应用于医学图像处理领域,成为肺癌筛查的智能辅助手段。目标检测需要以大量数据为基础进行特征提取,其目标定位的精准性受训练数据集的直接影响,但现阶段我国没有可以直接进行目标检测的干净肺结节数据集。为此,该系统分别将预处理后的肺CT图像和目标检测后的肺CT图像上传至云平台实现数据共享,搭建了适用于我国的肺结节检测数据集,为计算机辅助诊断方法的研究提供了数据基础。

基于.NET平台的高校竞赛管理系统设计

高校竞赛管理系统是高校教育教学工作中的重要信息化工具,主要用于组织、监督和评估各类校内校外竞赛。系统通常包括复杂的数据处理、多用户协作和严格的安全性要求。.NET平台因其跨语言互操作性、高效的内存管理、稳健的安全机制等优势在构建平台性应用程序时展现出极大价值。基于此,文章将分析基于.NET平台的高校竞赛管理系统需求,将其划分为竞赛管理、服务需求和用户权限需求,设计竞赛管理系统的系统架构,实现平台功能、竞赛开启功能、竞赛报名功能、成绩查询功能,旨在为构建高效、稳定且安全的竞赛管理平台提供实践参考。