Oracle Critical Patch Update for July 2015

Oracle于2015年7月14日发布了关键补丁更新,强烈建议尽快应用补丁。此更新包含受影响产品的列表、获取补丁的方法、各产品套件的安全漏洞概述及重要文件链接。
July 14, 2015
Oracle Critical Patch Update for July 2015


The Critical Patch Update for July 2015 was released on July 14th, 2015. Oracle strongly recommends applying the patches as soon as possible.

The Critical Patch Update Advisory is the starting point for relevant information. It includes the list of products affected, pointers to obtain the patches, a summary of the security vulnerabilities for each product suite, and links to other important documents. Supported products that are not listed in the "Affected Products and Components" section of the advisory do not require new patches to be applied.

Also, it is essential to review the Critical Patch Update supporting documentation referenced in the Advisory before applying patches, as this is where you can find important pertinent information. Critical Patch Update Advisories are available at the following location:

Oracle Technology Network: [url]http://www.oracle.com/technetwork/topics/security/alerts-086861.html[/url]

The Critical Patch Update Advisory for July 2015 is available at the following location:

Oracle Technology Network: [url]http://www.oracle.com/technetwork/topics/security/cpujul2015-2367936.html[/url]

Important information can also be found at: https://blogs.oracle.com/security/

The next four dates for Critical Patch Updates are:
• October 20, 2015
• January 19, 2016
• April 19, 2016
• July 19, 2016

Customer Support of Oracle Corporation
【无人机】基于改进粒子群算法的无人机路径规划研究[和遗传算法、粒子群算法进行比较](Matlab代码实现)内容概要:本文围绕基于改进粒子群算法的无人机路径规划展开研究,重点探讨了在复杂环境中利用改进粒子群算法(PSO)实现无人机三维路径规划的方法,并将其与遗传算法(GA)、标准粒子群算法等传统优化算法进行对比分析。研究内容涵盖路径规划的多目标优化、避障策略、航路点约束以及算法收敛性和寻优能力的评估,所有实验均通过Matlab代码实现,提供了完整的仿真验证流程。文章还提到了多种智能优化算法在无人机路径规划中的应用比较,突出了改进PSO在收敛速度和全局寻优方面的优势。; 适合人群:具备一定Matlab编程基础和优化算法知识的研究生、科研人员及从事无人机路径规划、智能优化算法研究的相关技术人员。; 使用场景及目标:①用于无人机在复杂地形或动态环境下的三维路径规划仿真研究;②比较不同智能优化算法(如PSO、GA、蚁群算法、RRT等)在路径规划中的性能差异;③为多目标优化问题提供算法选型和改进思路。; 阅读建议:建议读者结合文中提供的Matlab代码进行实践操作,重点关注算法的参数设置、适应度函数设计及路径约束处理方式,同时可参考文中提到的多种算法对比思路,拓展到其他智能优化算法的研究与改进中。
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