基于SSLVPN的数字校园网络应用研究

为了更好的解决校内电子资源远程访问和管理的问题,文章通过SSL VPN原理和关键技术的分析,结合南京财经大学校园网的实际应用方案阐述了SSL VPN在远程访问数据的优势。     

本体映射的进化研究

本体映射的进化是本体研究中待研究的课题之一。本文首先给出本体和本体映射形式化定义,在此基础上讨论本体变化后的映射进化方法。将本体变化类型分为删除、增加、修改,针对不同的类型提出本体删除后的映射进化算法、本体增加后的映射进化算法和本体修改后的映射进化算法。实验结果表明该方法能基本解决本体映射的进化问题。最后指出算法中存在的挑战,并给出进一步研究的方向。     

利用数据库通信在Authorware中实现问卷统计

在众多的多媒体开发工具中,Authorware是其中的佼佼者,很多人在进行多媒体开发的时候都会以它为首选。随着数据库技术的发展,在Authorware制作过程中,可以通过ODBC接口实现在Authorware中调用数据库。利用Authorware与数据库的通信可以轻松实现问卷统计功能,从而使多媒体程序更加的完美。     

数据挖掘技术在钢材仓储管理中的应用研究

提出了数据挖掘技术在钢材仓储管理中的实施方案,并以钢材仓储管理中实时库存的统计分析为例介绍了该方案的实施过程。仓库管理者能够找到有关影响钢材库存损耗的因素,从而改进仓储钢材的利用方法,必然对仓库的效益起到积极的作用。     

Accurately estimating reflectance parameters for color and gloss reproduction

A new method is described to estimate diffuse and specular reflectance parameters using spectral images, which overcomes the dynamic range limitation of imaging devices. After eliminating the influences of illumination and camera on spectral images, reflection values are initially assumed as diffuse-only reflection components, and subjected to the least squares method to estimate diffuse reflectance parameters at each wavelength on each single surface particle. Based on the dichromatic reflection model, specular reflection components are obtained, and then subjected to the least squares method to estimate specular reflectance parameters for gloss intensity and surface roughness. Experiments were carried out using both simulation data and measured spectral images. Our results demonstrate that this method is capable of estimating diffuse and specular reflectance parameters precisely for color and gloss reproduction, without requiring preprocesses such as image segmentation and synthesis of high dynamic range images.     

“AI+智能”赋能高校智慧教学生态体系构建研究

随着人工智能技术的快速发展,深化“AI+智能”应用以推进高校教学生态体系的优化与升级,已成为教育领域发展的一种重要趋势。为顺应这一趋势,加速构建智慧教学生态体系,更好地利用“AI+智能”技术推动教学质效升级,成为当前高校教学创新发展的重要举措。基于“AI+智能”的高校智慧教学生态体系主要通过综合应用多种智能技术,实现教学内容的多元化,为学生提供个性化的学习体验。文中从智慧教学生态体系的基础理论入手,在精准把握“AI+智能”技术在高等教育中的应用优势的基础上,进一步提出了“AI+智能”赋能高校智慧教学生态体系构建的实践策略,以期为推动高校实现智慧化教学提供有益的路径参考。     

基于绿电流分析的用户侧消纳责任分配研究

双碳目标的提出促进了我国绿色电力的发展,也对绿色电力消纳提出了新要求。当前阶段,对于用户侧绿电消纳责任分配问题尚未形成统一政策,围绕这一问题,探讨了绿电流分析的必要性,概述了潮流分析、碳流分析、绿电流分析3者的侧重点和对应关系。结合电力系统潮流计算,提出了电力系统绿电流分析理论的基本概念和重要结论,初步形成了绿电流分析的计算方法。通过IEEE 14节点母线系统对所提方法进行验证,分析了不同情况下系统各节点绿电流的分布特点。最后对绿电消纳责任划分、单一机组的绿电流向追踪等应用方向进行了展望。     

基于纯电动船舶应用实践的综合效益分析与推广

电动船舶是船舶行业发展最有前景的技术方向之一,是实现水上交通领域双碳目标的重要举措。聚焦近年来电动船舶推广现状,以江苏电动船舶的应用实践为例,通过试验数据分析了电动船舶的建设成本高、运营成本低、环境减排效益显著等特点。基于主要特征进一步研究了电动船舶推广机制,阐述了江苏实践的相关举措与成效,通过建设电动船舶配套充换电设施、降低电动船舶使用成本等方法,为现阶段电动船舶的规模化推广提供参考。     

Unsupervised model-driven neural network based image denoising for transmission line monitoring

With the expansion of smart grid and Internet of things (IoT) technology, edge computing has a wide variety of applications in these domains. The criteria for real-time monitoring and accuracy are particularly high in the field of online real-time monitoring of electricity lines. Based on edge technology, high-quality real-time monitoring can be performed for transmission lines using image processing techniques. Therefore, we propose an image denoising method, which can learn clean images using a stream-based generative model. The stream model uses a two-stage approach in the network to handle the different training periods of denoising separately. Experimental results show that the proposed method has good denoising performance.     

Jointly beam stealing attackers detection and localization without training: an image processing viewpoint

Recently revealed beam stealing attacks could greatly threaten the security and privacy of IEEE 802.11ad communications. The premise to restore normal network service is detecting and locating beam stealing attackers without their cooperation. Current consistency-based methods are only valid for one single attacker and are parameter-sensitive. From the viewpoint of image processing, this paper proposes an algorithm to jointly detect and locate multiple beam stealing attackers based on RSSI (Received Signal Strength Indicator) map without the training process involved in deep learning-based solutions. Firstly, an RSSI map is constructed based on interpolating the raw RSSI data for enabling high-resolution localization while reducing monitoring cost. Secondly, three image processing steps, including edge detection and segmentation, are conducted on the constructed RSSI map to detect and locate multiple attackers without any prior knowledge about the attackers. To evaluate our proposal’s performance, a series of experiments are conducted based on the collected data. Experimental results have shown that in typical parameter settings, our algorithm’s positioning error does not exceed 0.41 m with a detection rate no less than 91%.