Object-oriented DBMS requirements

The requirements on an object-oriented DBMS for management of information in a large, complex enterprise are presented. These requirements aid in the achievement of an environment characterized by data sharing, open architectures, application and data portability, and assurance of data integrity. They were defined from the point of view of a user of the DBMS; therefore they describe the expected functionality of the DBMS and do not specify the method of implementation to achieve this functionality. They encompass requirements on the data model, query and data manipulation languages, the system architecure, interfaces to the system, change management, and transaction management.     

Reliability and stability of executive functioning in older adults.

A number of methodological questions have been raised about the reliability and validity of measuring executive functioning (EF) across multiple time points. In this study, correlational and latent-variable analyses were used to examine test-retest reliability of 5 common measures of EF and the stability of a latent EF construct. One hundred eighteen nondemented older adults were tested twice over a 4- to 8-week period. Findings demonstrated modest reliability of individual EF measures but very high stability of a latent EF construct. Relative contributions of each measure to the latent EF factor did not change across measurement trials. In addition, age-related effects on EF were similar at the 2 time points and were within the expected range. Implications for future studies of EF are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Empirically derived subtypes of adolescent depression: Latent profile analysis of co-occurring symptoms in the Treatment for Adolescents with Depression Study (TADS).

A latent profile analysis was conducted on the co-occurring symptoms of 423 adolescents diagnosed with major depressive disorder as part of the Treatment for Adolescents with Depression Study (TADS), a multisite, randomized treatment trial. The participants had a mean (SD) age of 14.6 (1.5) years; of the sample, 45.6% was male and 73.8% was white. Scores on the primary subscales of Conners' Parent Rating Scale-Revised were used as indicators in the analysis. Five classes of symptoms best described the clinical presentation of adolescents enrolled in the TADS. Of the adolescents in the sample, 80% were assigned to classes with clinically significant elevations on 1 or more subscales of the Children's Depression Rating Scale-Revised. The 5 classes met empirical criteria for distinctiveness and were validated against clinical diagnoses, child-rated symptoms, and clinician-rated functional impairment. The findings are consistent with prior studies that showed a high rate of co-occurring symptoms among depressed adolescents. The discussion focuses on understanding subtypes and comorbidity in adolescent depression as well as the implications for treatment and for prevention. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

High‐error approximate dictionary search using estimate hash comparisons

A method for finding all matches in a pre‐processed dictionary for a query string q and with at most k differences is presented. A very fast constant‐time estimate using hashes is presented. A tree structure is used to minimize the number of estimates made. Practical tests are performed, showing that the estimate can filter out 99% of the full comparisons for 40% error rates and dictionaries of up to four million words. The tree is found to be efficient up to a 50% error rate. Copyright © 2006 John Wiley & Sons, Ltd.     

灵活运用数据库设计理论

简介了关系模型、键、完整性规则、E-R模型、函数依赖、模式分解和关系模式的范式等数据库技术基础和规范化设计理论，从键和完整性规则的实现、数据冗余的特殊情况和字典设计等方面论述了在实际设计工作中如何灵活运用关系数据库设计理论。     

Robust pose invariant face recognition using coupled latent space discriminant analysis

We propose a novel pose-invariant face recognition approach which we call Discriminant Multiple Coupled Latent Subspace framework. It finds the sets of projection directions for different poses such that the projected images of the same subject in different poses are maximally correlated in the latent space. Discriminant analysis with artificially simulated pose errors in the latent space makes it robust to small pose errors caused due to a subject’s incorrect pose estimation. We do a comparative analysis of three popular latent space learning approaches: Partial Least Squares (PLSs), Bilinear Model (BLM) and Canonical Correlational Analysis (CCA) in the proposed coupled latent subspace framework. We experimentally demonstrate that using more than two poses simultaneously with CCA results in better performance. We report state-of-the-art results for pose-invariant face recognition on CMU PIE and FERET and comparable results on MultiPIE when using only four fiducial points for alignment and intensity features.     

Unseen users, unknown systems: Computer design for a scholar's dictionary

The Dictionary of Old English computing systems have provided access since the 1970s to a database of approximately three million running words. These systems, designed for a variety of machines and written in a variety of languages, have until recently been planned with computing center billing algorithms in mind. With personal workstations emphasis has shifted to building more elegant user interfaces and to providing the entire DOE database to editors around the world. While the shift from sequential files to random access files and the provision of extensive development tools have changed some of the design process, error checking and protection of the database against accidental intrusion have remained as central issues.Richard L. Venezky is Unidel Professor of Educational Studies and professor of Computer and Information Sciences at the University of Delaware. He was formerly professor and chair of Computer Sciences at the University of Wisconsin. His research interests include writing systems, literacy, knowledge representation, and computer-assisted instruction. Among his recent publications are The Subtle Danger: Reflections on the Literacy Abilities of America's Young Adults (Princeton, NJ: ETS, 1987), and Steps Towards a Modern History of American Reading Instruction (Review of Research in Education, 1986, vol. 13, 129–70).     

面向工业平稳/非平稳复杂系统的在线故障监测技术

针对复杂系统中关键性能指标（KPI）相关故障检测方法检测精度低的问题,提出基于双层改进潜结构投影（DL-IPLS）的KPI相关故障检测方法. 利用协整分析和主元分析建立底层模型,对非平稳和平稳变量进行特征提取. 将提取的信息进行融合,建立改进潜结构投影的上层模型,根据融合信息对KPI的贡献进行空间分解. 在2个正交子空间中设计统计量,实现KPI相关故障的在线监测. 田纳西-伊斯曼过程和青霉素发酵过程的仿真结果表明,在面向工业平稳和非平稳复杂工业系统检测时,所提方法有效提高了KPI相关故障的检测率,降低了KPI无关故障的误报率.     

无理数字典码的测试数据压缩方案

提出了一种无理数字典码的测试数据压缩方案,能有效地压缩芯片测试数据。方案利用无理数序列建立字典,编码时只需进行相容性检查,无需填充无关位,简化了操作步骤;同时,选择局部压缩率最大的一组数据作为最终编码结果,保证压缩效果可以达到局部最优。对ISCAS 89标准电路Mintest集的实验结果显示,该方案的压缩效果优于传统压缩方法,如Golomb码、FDR码、混合定变长码等。     

稀疏卷积非负矩阵分解的语音增强算法

非平稳噪声和低信噪比条件下提高增强语音质量一直以来都是语音增强研究的难题。近年来,卷积非负矩阵分解在语音增强算法中成功应用,本文进一步考虑语音信号在时频域的稀疏性,提出了稀疏卷积非负矩阵分解(Sparse Convolutive Nonnegative Matrix Factorization, SCNMF)的语音增强算法。该算法包括训练和增强两个阶段。训练阶段通过SCNMF算法分别对纯净语音和噪声的频谱进行训练,得到纯净语音和噪声字典,并将其作为增强阶段的先验信息。增强阶段首先通过SCNMF算法对带噪语音的频谱进行分解,然后利用纯净语音和噪声联合字典对语音编码矩阵进行估计,重构增强语音。本文通过实验仿真分析了稀疏因子对增强语音质量的影响。实验结果表明,在非平稳噪声和低信噪比条件下,本文算法增强效果均优于多带谱减、非负矩阵分解、卷积非负矩阵分解等传统的算法。