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关键词： Java   开发工具   Ultra   Edit   JDK  

摘要： Java技术具有卓越的通用性、高效性、平台移植性和安全性,广泛应用于个人PC、数据中心、游戏控制台、科学超级计算机、移动电话和互联网,同时拥有全球最大的开发者专业社群.因此,同时关注Java程序设计语言工具的厂商如此众多,有如此多的开发工具,对于学习Java的初学者,甚至是对Java程序设计有基础的人员来说都很难做出选择.本文向热爱Java程序设计的开发者介绍一些Java开发工具,并进行分析和点评.

关键词： 传感网   标识符   字符串匹配   传感节点编码  

摘要： 随着无线传感网应用规模的日益扩大,统一的传感网传感节点标识符能够保证各异构网络的互联互通,从而对不同系统的感知信息进行共享和管理;文中结合我国传感网标准工作组PG5标识项目组制定的传感节点标识符编码规范,设计了传感节点标识符编码测试系统,提出了一个改进的字符串匹配算法,从而提高了系统的测试效率,保证了传感节点编码的正确性和唯一性。

关键词： 数字信息   中华医学会   标注   杂志   object   出版物   国际标准   条形码  

摘要： 数字对象唯一标识符（digital object identifier，DOI）是对包括互联网信息在内的数字信息进行标识的一种工具。在传统的出版物中，书刊、磁带、光盘都有国际标准编号（ISBN、ISSN、ISCN）及其条形码，作为出版物的唯一标识。这些标识使出版物得到有效的管理，便于读者查找和利用。而网上的文档一旦变更了网址便无从追索。数字信息标注DOI如同出版物的条形码，是一个永久和唯一的标识号。

关键词： IMS   ISIM   标识符   应用接入  

摘要： 通过对ISIM现有标准情况的梳理和规范概括,以及对ISIM文件架构及标识符参数的归纳分析,得出ISIM标识符参数特征,并对ISIM/USIM在IMS网络中当前和将来的应用情况做总结。

关键词： 抽象语法树   标识符   面向对象   Java   对象行为   相似度比对  

摘要： 程序相似度及其比对方法一直是近年来防止程序抄袭和剽窃的热门话题,该研究对检查学生的原创性非常有利。基于抽象语法树,研究面向对象的程序设计语言中的对象行为,提出一种基于对象行为的相似度比对方法。该方法以抽象语法树高度展现程序结构的优点作为基础,比对程序中的对象及其行为特征,能够较为详实地展现对象及其行为的相似度度量。

关键词： attention-deficit hyperactivity disorder   borderline personality features   diathesis-stress   trajectory analysis  

摘要： Objective: To examine trajectories of adolescent borderline personality (BP) features in a normative-risk cohort (n = 566) of Canadian children assessed at ages 13, 14, 15, and 16 and childhood predictors of trajectory group membership assessed at ages 8, 10, 11, and 12. Method: Data were drawn from the McMaster Teen Study, an on-going study examining relations among bullying, mental health, and academic achievement. Participants and their parents completed a battery of mental health and peer relations questionnaires at each wave of the study. Academic competence was assessed at age 8 (Grade 3). Latent class growth analysis, analysis of variance, and logistic regression were used to analyze the data. Results: Three distinct BP features trajectory groups were identified: elevated or rising, intermediate or stable, and low or stable. Parent-and child-reported mental health symptoms, peer relations risk factors, and intra-individual risk factors were significant predictors of elevated or rising and intermediate or stable trajectory groups. Child-reported attention-deficit hyperactivity disorder (ADHD) and somatization symptoms uniquely predicted elevated or rising trajectory group membership, whereas parent-reported anxiety and child-reported ADHD symptoms uniquely predicted intermediate or stable trajectory group membership. Child-reported somatization symptoms was the only predictor to differentiate the intermediate or stable and elevated or rising trajectory groups (OR 1.15, 95% CI 1.04 to 1.28). Associations between child-reported reactive temperament and elevated BP features trajectory group membership were 10.23 times higher among children who were bullied, supporting a diathesis-stress pathway in the development of BP features for these youth. Conclusions: Findings demonstrate the heterogeneous course of BP features in early adolescence and shed light on the potential prodromal course of later borderline personality disorder.

关键词： Product heterogeneity   Clustering   Online transaction data   E-commerce  

摘要： Investigations of online transaction data often face the problem that entries for identical products cannot be identified as such. There is, for example, typically no unique product identifier in online auctions;retailers make their offers at price comparison sites hardly comparable and online stores often use different identifiers for virtually equal products. Existing studies typically use data sets that are restricted to one or only a few products in order to avoid product heterogeneity if a unique product identifier is not available. We propose the Ambiguous Identifier Clustering Technique (AICT) that identifies online transaction data that refer to virtually the same product. Based on a data set of eBay auctions, we demonstrate that AICT clusters online transactions for identical products with high accuracy. We further show how researchers benefit from AICT and the reduced product heterogeneity when analyzing data with econometric models.

关键词： Continuous neural networks   Switched systems   Up-flow anaerobic sludge blanket   Trichloroethylene   Adaptive identifier  

摘要： Sequential processes appear naturally in all types of industries. Biotechnology is a good example of such schemes. Wastewater treatment using microbiological activity is a particular case having all the characteristics of sequential methods. Sulfate reduction as pre-treatment followed by the decomposition of sulfated compounds using adapted microorganisms is the sequential nonlinear process with state constrains analyzed in this paper. Modeling this procedure is still a difficult task because the number of elements involved in the reaction. This paper presents an adaptive algorithm to obtain a suitable model of this process using continuous neural networks. The adaptive model preserves the sequential nature of the process as well as the bounded nature of all states. The neural network is proposed as a system identifier in terms of the hybrid systems theory. The Lyapunov stability method is used to demonstrate the convergence of the identifier states to the real concentrations of the microbiological system. Experimental results and their corresponding simulation using the adaptive model based on neural networks confirm the theoretical results described in this paper. (C) 2015 Elsevier Inc. All rights reserved.

关键词： NGS   flow cytometry   glycosylphosphatidylinositol (GPI) anchor   cell sorting  

摘要： Identification of mutations induced by xenotoxins is a common task in the field of genetic toxicology. Mutations are often detected by clonally expanding potential mutant cells and genotyping each viable clone by Sanger sequencing. Such a clone-by-clone approach requires significant time and effort, and sometimes is even impossible to implement. Alternative techniques for efficient mutation identification would greatly benefit both basic and regulatory genetic toxicology research. Here, we report the development of Mutation Analysis with Random DNA Identifiers (MARDI), a novel high-fidelity Next Generation Sequencing (NGS) approach that circumvents clonal expansion and directly catalogs mutations in pools of mutant cells. MARDI uses oligonucleotides carrying Random DNA Identifiers (RDIs) to tag progenitor DNA molecules before PCR amplification, enabling clustering of descendant DNA molecules and eliminating NGS- and PCR-induced sequencing artifacts. When applied to the Pig-a cDNA analysis of heterogeneous pools of CD48-deficient T cells derived from DMBA-treated rats, MARDI detected nearly all Pig-a mutations that were previously identified by conventional clone-by-clone analysis and discovered many additional ones consistent with DMBA exposure: mostly A to T transversions, with the mutated A located on the non-transcribed DNA strand. Environ. Mol. Mutagen. 57:114-124, 2016. (c) 2015 Wiley Periodicals, Inc.