基于Transformer实现文本导向的图像编辑

为方便非专业用户修图,提出一种基于Transformer的图像编辑模型TMGAN,使用户可通过自然语言描述自动修改图像属性。TMGAN整体框架采用生成对抗网络,生成器采用Transformer编码器结构提取全局上下文信息,解决生成图像不够真实的问题;判别器包含基于Transformer的多尺度判别器和词级判别器两部分,给生成器细粒度的反馈,生成符合文本描述的目标图像且保留原始图像中与文本描述无关的内容。实验表明,此模型在CUB Bird数据集上,IS（inception score）、FID（Fréchet inception distance）以及MP（manipulation precision）度量指标分别达到了9.07、8.64和0.081。提出的TMGAN模型对比现有模型效果更好,生成图像既满足了给定文本的属性要求又具有高语义性。     

Language learners' digital literacies: Focus on students' information literacy and reading practices online

The widespread use of technology and the Internet have changed many of language learners' everyday practices, including literacies. While there have been many studies with the focus on language learners' digital literacies, few, however, have explored language learners' digital information literacy and online reading practices with the use of social bookmarking tools, especially in a community college setting. We address this gap by investigating community-college language learners' digital literacies when social bookmarking with the focus on digital information and online reading practices from an ecological perspective. In this qualitative multiple-case study, the focal participants were five English learners, students in an English as a Second Language writing course in a community college in the northeastern United States. Data collection included interviews, observations, and researchers' e-journals. Thorough within- and cross-case analysis of data shows that language learners searched for digital texts and evaluated them based on relevance, reliability, interest, language, and importance for them and their learning community in the social bookmarking tool. The participants struggled with the number of results in search engines, keywords, and evaluation of digital texts for relevance and reliability. We show the need for more instruction, support, and guidance of language learners' digital information literacy practices as well as the benefits of providing students with opportunities to read digital texts. Our suggestions for future research include investigating the role of multimodality and other factors that influence language learners' evaluation practices when they look for and read information online.     

Developing and evaluating language courseware

The paper sets out twenty proposals for the development and evaluation of Computer Assisted Language Learning (CALL) programs. These proposals emerge from special characteristics of language instruction and of the use of computers to assist in language instruction. We combine theoretically-based assumptions with empirical findings drawn from investigation of language courseware for Hebrew speakers in Israel. We first list four unique features of language instruction: (1) the object-language-meta-language distinction; (2) computer as written medium vs. language as primary spoken medium; (3) teaching of second language skills vs. linguistics; (4) the computer as an electronic tool vs. the computer as a cognitive entity simulating the speaker. We then show how these unique characteristics of language instruction (mother-tongue and foreign language) impose special proposals on language courseware. These proposals should be observed in the development of language courseware and in the evaluation of such programs. Clearly, these proposals integrate with general courseware proposals. Michal Ephratt (Ph.D., computational linguistics) completed post-doctoral studies at the University of Rochester. She has been on the staff of the Dept. of Hebrew Linguistics, University of Haifa, since 1988. Some of her publications include Root-Pattern Array: The Main Tool of Hebrew Word Formation (Hebrew University, 1985); and What's in a Joke? in Advances in Artificial Intelligence, Natural Language and Knowledge-based Systems (Springer-Verlag, 1990).This paper is based on work the author did as a consultant in the National Courseware Evaluation Department of the Ministry of Education. I wish to thank Esther Diamant, head of the department, for making the study possible.     

Why does language matter to artificial intelligence?

Artificial intelligence, conceived either as an attempt to provide models of human cognition or as the development of programs able to perform intelligent tasks, is primarily interested in theuses of language. It should be concerned, therefore, withpragmatics. But its concern with pragmatics should not be restricted to the narrow, traditional conception of pragmatics as the theory of communication (or of the social uses of language). In addition to that, AI should take into account also the mental uses of language (in reasoning, for example) and the existential dimensions of language as a determiner of the world we (and our computers) live in. In this paper, the relevance of these three branches of pragmatics-sociopragmatics, psychopragmatics, and ontopragmatics-for AI are explored.     

软件工程专业汇编语言课程实践教学模式研究

本文提出了汇编语言课程学习对于软件人才能力培养的重要性,分析了汇编语言课程教学现状,提出了一些实践教学改革措施。     

基于SVM的维吾尔文文本分类研究

文本自动分类技术在提高文本信息利用的有效性和准确性上具有重要的现实意义和广阔的应用前景。随着Internet上维吾尔文信息的迅速发展,维吾尔文文本分类成为处理和组织这些大量文本数据的关键技术。研究维吾尔文文本分类相关技术和方法,针对维吾尔文文本在向量空间模型表示下的高维性,本文采用词干提取和χ2统计量相结合的方法对表示空间进行降维。采用SVM算法构造了维吾尔文文本分类器。针对维吾尔文文本分类语料进行的实验结果表明,SVM分类器的MacroF1值达到了84.6%,明显好于kNN方法。     

访问控制策略描述语言与策略冲突研究

访问控制技术是网络安全防范和保护的主要方法,能保证信息的完整性和机密性。随着计算机、互联网和无线通信技术的高速发展,网络安全问题日益严重,访问控制策略的研究已成为计算机学科的一个热点课题。本文首先介绍了五种主要的访问控制策略描述语言,分析了各自的特点及适用环境;然后总结了访问控制策略冲突产生的原因、类型、冲突检测以及冲突消解方法;最后给出了访问控制策略研究的发展趋势。     

检验标准管理系统的设计与实现

检验标准管理系统从工作实际出发,采用VisualBasic来制作交互介面,MicrosoftAccess作为后台支持的数据库来管理数据信息,从而实现产品质量检验机构的检验标准管理自动化。该系统是从服务客户和检验人员的角度出发,本着为客户提供准确、快捷、方便服务和更好管理本单位检验标准、方便检验人员使用的原则,可使检验机构大量的检验标准信息得以快捷管理,缩短了客户办理检验业务的时间,以及检验人员检验过程中快速查询使用检验标准的相关信息。本管理系统主要完成:对检验标准中数据的增加、数据的删除、数据的查询和数据的浏览。     

一个面向电子政务的信息交换与共享平台的设计与实现*

基于J2EE、XML等技术,设计并实现了一个面向电子政务的信息交换与共享平台.对平台的总体结构、元数据定义与管理、数据交换模式等关键问题进行了论述,最后给出了平台的模块实现.该平台已经应用于北京市信息资源管理中心,实现了遥感信息、区县图层、企业基础信息等资源的交换与共享.     

Desiderata for Languages to be Used in the Defnition of Reference Business Processes

In many modern enterprises, explicit business process de nitions facilitate the pursuit of business goals in such ways as best practice reuse, process analysis, processe ciency improvement, and automation. Most real-world business processes are large and complex. Successfully capturing, analysing, and automating these processes requires process de nition languages that capture a variety of process aspects with a wealth of details. Mostcurrent process modelling languages, such as Business Process Modelling Notation (BPMN),focus on structural control ows among activities while providing inadequate support for other process de nition needs. In this paper, we rst illustrate these inadequacies through our experiences with a collection of real-world reference business processes from the Aus-tralian lending industry. We observe that the most signi cant inadequacies include lack of resource management, exception handling, process variation, and data ow integration.These identi ed shortcomings led us to consider the Little-JIL language as a vehicle forde ning business processes. Little-JIL addresses the afore-mentioned inadequacies with a number of innovative features. Our investigation concludes that these innovative features are e ective in addressing a number of key reference business process de nition needs.