共查询到20条相似文献，搜索用时 187 毫秒
1.
逆编译在支持可执行代码的分析和软件维护方面起着十分关键的作用.本文针对逆编译的发展现状,概述了逆编译的作用并总结了其实现方法. 相似文献
2.
逆编译在支持可执行代码的分析和软件维护方面起着十分关键的作用。本文针对逆编译的发展现状,概述了逆编译的作用并总结了其实现方法。 相似文献
3.
Web应用中经常需要使用Excel存储数据批量添加或者更新到数据库中,各种此类功能之间存在大量的重复代码.本文使用工厂方法模式对该问题进行了解决,实现了一个抽象类.通过本文提供的设计方案,在添加新的类似功能的时候只需要是继承该抽象类,并实现具体处理功能即可,有效的减少了重复代码. 相似文献
4.
DM6446在一个芯片上集合了ARM内核和DSP内核,为了良好的进行双核交互,可以运用Codec Engine（编解码引擎）软件模块。Codec Engine软件模块可以隐藏复杂的DSP配置和硬件细节,不必修改应用代码就可以实现编解码器的转换,并可以使用第三方提供的Codec,缩短了应用开发的周期。 相似文献
5.
首先分析了MARC数据的结构和一些特殊字符在此结构中的功能。其次确定什么形式的数据用户易于理解。对MARC数据的转换和提取方法进行分析,提出MARC数据的转换提取方案和流程,给出JSP下的代码实现。最后就代码实现中遇到的特殊字符的ASCII码和中文字符占位问题提出了解决办法。 相似文献
6.
存储过程的调用在管理系统开发中会经常用到,因为传统的调用方法不仅速度慢,而且代码会随着系统功能的增多不断膨胀,难以维护。而通过存储过程更新数据不但容易维护,还可以提高系统的执行效率。采用具体实例就如何通过存储过程更新数据库的技术提出了实现方法。 相似文献
7.
在云存储服务中,为使用户可以随时验证存储在云存储服务器上数据的完整性,需要对云计算数据进行移动学习,在移动学习过程中,产生大量的重复数据。需要设计云计算静态重删系统,对重复数据有效及时删除。传统方法采用虚拟化云平台分类层次重删模型,需要修改内核代码或者以模块的形式动态植入内核代码,重删效果不好。本文提出一种基于奇异值分解移动学习的云计算静态重删系统设计方案,进行云计算存储系统设计与重删数据特征分析,对云计算静态重复数据的尺度伸缩分解,把重复数据宽带互模糊度函数映射为一个检测统计量特征分解问题,构建一个参数未知多重假设检验,对云计算静态重复数据进行奇异值尺度伸缩分解,对分解后的奇异值特征进行状态空间重组和移动学习,得到重删系统模型改进。仿真结果表明,该算法对云计算静态重复数据检测性能较高,重删性能优越,抗干扰能力强,具有较好的应用前景。 相似文献
8.
通过研究构建系统模型和模型转换规则而自动生成可执行代码的开发流程,探讨了基于J2EE平台实现图书馆综合服务系统的MDA开发方式。 相似文献
9.
10.
11.
《Information processing & management》2022,59(3):102919
Similarity search with hashing has become one of the fundamental research topics in computer vision and multimedia. The current researches on semantic-preserving hashing mainly focus on exploring the semantic similarities between pointwise or pairwise samples in the visual space to generate discriminative hash codes. However, such learning schemes fail to explore the intrinsic latent features embedded in the high-dimensional feature space and they are difficult to capture the underlying topological structure of data, yielding low-quality hash codes for image retrieval. In this paper, we propose an ordinal-preserving latent graph hashing (OLGH) method, which derives the objective hash codes from the latent space and preserves the high-order locally topological structure of data into the learned hash codes. Specifically, we conceive a triplet constrained topology-preserving loss to uncover the ordinal-inferred local features in binary representation learning. By virtue of this, the learning system can implicitly capture the high-order similarities among samples during the feature learning process. Moreover, the well-designed latent subspace learning is built to acquire the noise-free latent features based on the sparse constrained supervised learning. As such, the latent under-explored characteristics of data are fully employed in subspace construction. Furthermore, the latent ordinal graph hashing is formulated by jointly exploiting latent space construction and ordinal graph learning. An efficient optimization algorithm is developed to solve the resulting problem to achieve the optimal solution. Extensive experiments conducted on diverse datasets show the effectiveness and superiority of the proposed method when compared to some advanced learning to hash algorithms for fast image retrieval. The source codes of this paper are available at https://github.com/DarrenZZhang/OLGH . 相似文献
12.
可执行程序自删除广泛用于卸载程序。一般来说,程序在运行时无法删除自己,但可以用一些巧妙的方法来实现程序的自删除。这里阐述了三种可执行程序自删除的方法,并在VC中实现。这三种方法是:调用批处理文件实现程序自删除,基于CLONE--用复制品启动另一个进程删除原来的可执行文件和释放程序文件在内存中的映射,再调用文件操作删除程序. 相似文献
13.
14.
《Information processing & management》2022,59(1):102743
Multi-modal hashing can encode the large-scale social geo-media multimedia data from multiple sources into a common discrete hash space, in which the heterogeneous correlations from multiple modalities could be well explored and preserved into the objective semantic-consistent hash codes. The current researches on multi-modal hashing mainly focus on performing common data reconstruction, but they fail to effectively distill the intrinsic and consensus structures of multi-modal data and fully exploit the inherent semantic knowledge to capture semantic-consistent information across multiple modalities, leading to unsatisfactory retrieval performance. To facilitate this problem and develop an efficient multi-modal geographical retrieval method, in this article, we propose a discriminative multi-modal hashing framework named Cognitive Multi-modal Consistent Hashing (CMCH), which can progressively pursue the structure consensus over heterogeneous multi-modal data and simultaneously explore the informative transformed semantics. Specifically, we construct a parameter-free collaborative multi-modal fusion module to incorporate and excavate the underlying common components from multi-source data. Particularly, our formulation seeks for a joint multi-modal compatibility among multiple modalities under a self-adaptive weighting manner, which can take full advantages of their complementary properties. Moreover, a cognitive self-paced learning policy is further leveraged to conduct progressive feature aggregation, which can coalesce multi-modal data onto the established common latent space in a curriculum learning mode. Furthermore, deep semantic transform learning is elaborated to generate flexible semantics for interactively guiding collaborative hash codes learning. An efficient discrete learning algorithm is devised to address the resulting optimization problem, which obtains stable solutions when dealing with large-scale multi-modal retrieval tasks. Sufficient experiments performed on four large-scale multi-modal datasets demonstrate the encouraging performance of the proposed CMCH method in comparison with the state-of-the-arts over multi-modal information retrieval and computational efficiency. The source codes of this work could be available at https://github.com/JunfengAn1998a/CMCH . 相似文献
15.
In this paper we present an executable approach to model interactions between agents that involve sensitive, privacy-related
information. The approach is formal and based on deontic, epistemic and action logic. It is conceptually related to the Belief-Desire-Intention
model of Bratman. Our approach uses the concept of sphere as developed by Waltzer to capture the notion that information is
provided mostly with restrictions regarding its application. We use software agent technology to create an executable approach.
Our agents hold beliefs about the world, have goals and commitment to the goals. They have the capacity to reason about different
courses of action, and communicate with one another. The main new ingredient of our approach is the idea to model information
itself as an intentional agent whose main goal it is to preserve the integrity of the information and regulate its dissemination.
We demonstrate our approach by applying it to an important process in the insurance industry: applying for a life insurance.
In this paper we will: (1) describe the challenge organizational complexity poses in moral reasoning about informational relationships;
(2) propose an executable approach, using software agents with reasoning capacities grounded in modal logic, in which moral
constraints on informational relatio nships can be modeled and investigated; (3) describe the details of our approach, in
which information itself is modeled as an intentional agent in its own right; (4) test and validate it by applying it to a
concrete ‘hard case’ from the insurance industry; and (5) conclude that our approach upholds and offers potential for both
research and practical application. 相似文献
16.
如何与产业融合是人工智能技术发展的关键。鉴于“万物皆媒”的未来场景,对智能媒体技术的发展趋势、技术集群演变和国际竞争态势研究对媒体行业及其相关行业的发展,国家核心竞争力的提高都至关重要。本文对2008年至2020年间的专利数据进行检索,鉴别出75 051条德温特专利数据作为分析基础。采取关键词、专利代码及学科领域相结合的方法确定了智能媒体技术涉及的专利范围;结合时间变迁和聚类分析将智能媒体技术的发展分为平稳、迅速、平缓和迅猛发展四个阶段;利用共词分析建立了不同专利代码之间的共现关系,利用社会化网络分析将共现关系可视化,识别出不同阶段的主要技术集群;结合企业专利拥有量及所属国家分析了智能媒体技术的国际竞争态势。基于以上定量分析从媒体业务与智能技术融合视角提出了媒体机构的智能化战略建议,从智能媒体技术研发、行业应用、国际竞争力提升视角提出了智能媒体产业发展政策建议。本文基于专利测度从发展趋势、技术集群演变和国际竞争态势三方面分析了智能媒体技术发展规律,为从专利视角对人工智能技术与产业融合的研究提供了方法体系。 相似文献
17.
文章对比了利用VisualFoxpro系统制作各类含图片资料的报表打印中的几种常用方法,分析了各类方法的利弊以及实现难易程度;最后引用实例阐明在实际工作中笔者所推荐的最优方案及此方案所涉及的应予以注意的关键程序代码。 相似文献
18.
Quickly and accurately summarizing representative opinions is a key step for assessing microblog sentiments. The Ortony-Clore-Collins (OCC) model of emotion can offer a rule-based emotion export mechanism. In this paper, we propose an OCC model and a Convolutional Neural Network (CNN) based opinion summarization method for Chinese microblogging systems. We test the proposed method using real world microblog data. We then compare the accuracy of manual sentiment annotation to the accuracy using our OCC-based sentiment classification rule library. Experimental results from analyzing three real-world microblog datasets demonstrate the efficacy of our proposed method. Our study highlights the potential of combining emotion cognition with deep learning in sentiment analysis of social media data. 相似文献
19.
图像曼形技术是指将一幅图像平滑地变换到另一幅图像的方法,它是一种有用的图像处理方法。介绍一种简单的图像变形技术——Morphing技术的原理和算法,并给出了用MA3、LAB实现的代码。 相似文献
20.
基于共词分析的技术机会分析 总被引：1，自引：0，他引：1
技术机会是未来可能发生并且可资利用的"技术变化",是企业进行技术创新的关键。本文借鉴技术预测和知识发现的相关理论,建立了关键技术、技术前沿和技术趋势三个视角的分析框架。提出以科技期刊文献为数据源,以共词分析及其可视化技术相结合的技术机会分析方法。最后以铝电解领域为例进行了案例研究,介绍如何运用技术机会分析方法为企业技术创新活动提供决策信息。 相似文献