Parameter determination of support vector machine and feature selection using simulated annealing approach

Support vector machine (SVM) is a novel pattern classification method that is valuable in many applications. Kernel parameter setting in the SVM training process, along with the feature selection, significantly affects classification accuracy. The objective of this study is to obtain the better parameter values while also finding a subset of features that does not degrade the SVM classification accuracy. This study develops a simulated annealing (SA) approach for parameter determination and feature selection in the SVM, termed SA-SVM.To measure the proposed SA-SVM approach, several datasets in UCI machine learning repository are adopted to calculate the classification accuracy rate. The proposed approach was compared with grid search which is a conventional method of performing parameter setting, and various other methods. Experimental results indicate that the classification accuracy rates of the proposed approach exceed those of grid search and other approaches. The SA-SVM is thus useful for parameter determination and feature selection in the SVM.     

逻辑内建自测试高故障覆盖率设计

基于扫描的可测性设计技术需要大量空间存储测试矢量,并且难以实现全速测试,随着芯片规模越来越大,频率越来越高,其测试成本也将越来越高,逻辑内建自测试(Logic Built-In-Self-Test,LBIST)技术以其简单的硬件实现和较小的设计开销开始被业界广泛使用,但该技术也存在覆盖率较低的问题,主要原因在于:一是线性反馈移位寄存器(Linear Feedback Shift Register,LFSR)产生的伪随机矢量的空间相关性;二是电路结构上对伪随机矢量的抵抗性;针对这两种原因给出了一些改善的方法,从而达到提高故障覆盖率的目的,为实际设计提供借鉴。     

基于矢量方法的图像预处理及其应用

图像预处理是图像处理中量之间的内在联系,具有保边缘、细节和抑制颜色偏差的优点,而且计算量小、算法简单、易于实现.将该方法应用于眼底图像中,取得了令人满意的效果,为眼底图像的后续处理奠定基础.     

基于ASP．NET的高校群体竞赛管理系统

论述了基于ASP.NET,C#,ADO.NET和Microsoft Access 2003相结合的高校群体竞赛管理系统的设计原理、总体结构及功能实现.该系统对加强和落实高校群体竞赛的网络化管理,提高高校群体竞赛管理工作的科学水平,提高工作效率具有现实意义.     

西门子S7系列PLC在成都地铁BAS系统中的应用

本系统以西门子S7-414H冗余控制器为主站,多台S7—200PLC和S7—300PLC为从站,通过光纤链路模块OLM组成冗余光纤环网,实现地铁设备监控系统的完美控制。文章重点介绍了控制工艺背景、主／从网络组成构架、硬件配置及软件编程．要点、系统中包含的PROFIBUS-DP、MODBUS、网络读写等通讯协议出现的问题及解决方法、调试后达到的效果及应用体会。     

Secretome analysis of novel IgE-binding proteins from Penicillium citrinum

The Penicillium genus of fungi is a frequently reported cause of allergic reactions. However, only a limited number of allergens have been reported. In Penicillium spp., many allergens show higher IgE-binding activity in culture filtrate extracts than in cellular extracts. In order to investigate the IgE-reactive profile of mold-sensitized patients, secreted IgE-reactive proteins from Penicillium citrinum were identified by 2-DE, serum immunoblotting, and nanoLC-MS/MS. Among the IgE-reactive spots, one known allergen, Pen c 13, and four novel allergens were identified. The cDNAs coding for Pen c 32 and Pen c 30 were cloned using designed primers based on nanoLC-MS/MS analysis. The amino acid sequences of Pen c 32 and Pen c 30 were, respectively, found to have extensive similarity with those of pectate lyases and catalases from various fungi. Native Pen c 30 was shown to have catalase activity and to bind to serum IgE from 48% of mold-allergic patients and induced immediate type skin reactions in a sensitized patient. Here, we present a proteome approach which resulted in the identification of four novel secreted allergens. These novel allergens might be useful in allergy diagnosis and in the treatment of mold-allergic disorders.     

Proteomics integrated with Escherichia coli vector-based vaccines and antigen microarrays reveals the immunogenicity of a surface sialidase-like protein of Propionibacterium acnes

Proteomics is a powerful tool for the identification of proteins, which provides a basis for rational vaccine design. However, it is still a highly technical and time‐consuming task to examine a protein's immunogenicity utilizing traditional approaches. Here, we present a platform for effectively evaluating protein immunogenicity and antibody detection. A tetanus toxin C fragment (Tet‐c) was used as a representative antigen to establish this platform. A cell wall‐anchoring sialidase‐like protein (SLP) of Propionibacterium acnes was utilized to assess the efficacy of this platform. We constructed an Escherichia coli vector‐based vaccine by overexpressing Tet‐c or SLP in E. coli and utilized an intact particle of E. coli itself as a vaccine (E. coli Tet‐c or SLP vector). After ultraviolet (UV) irradiation, the E. coli vector‐based vaccines were administered intranasally into imprinting control region mice without adding exogenous adjuvants. For antibody detection, we fabricated antigen microarrays by printing with purified recombinant proteins including Tet‐c and SLP. Our results demonstrated that detectable antibodies were elicited in mice 6 weeks after intranasal administration of UV‐irradiated E. coli vector‐based vaccines. The antibody production of Tet‐c and SLP was significantly elevated after boosting. Notably, the platform with main benefits of using E. coli itself as a vaccine carrier provides a critical template for applied proteomics aimed at screening novel vaccine targets. In addition, the novel immunogenic SLP potentially serves as an antigen candidate for the development of vaccines targeting P. acnes‐associated diseases.     

Arthemis: annotation software in an integrated capturing and analysis system for colonoscopy

Colonoscopy is an endoscopic technique that allows physicians to inspect the inside of the human colon. During a colonoscopic procedure, a tiny video camera at the tip of the endoscope generates a video signal of the internal mucosa of the colon. In current practice, the entire colonoscopic procedure is not routinely captured. Software tools providing easy access to important contents of videos that are digitally captured during colonoscopy are not available. Hence, it is very time consuming to review an entire video, locate important contents, annotate them, and extract the annotated contents for research, teaching, and training purposes. Arthemis, a software application, was developed to facilitate this process. For convenient data sharing, Arthemis allows annotation according to the European Gastrointestinal Society for Endoscopy (ESGE) Minimal Standard Terminology (MST), an internationally accepted standard for digestive endoscopy. Arthemis is part of our integrated capturing and content analysis system for colonoscopy called Endoscopic Multimedia Information System (EMIS). This paper presents Arthemis as a component of EMIS, the design and implementation of Arthemis, and key lessons learned from the development process.     

LSS: an S-Plus/R program for the accelerated failure time model to right censored data based on least-squares principle

Due to lack of proper inference procedure and software, the ordinary linear regression model is seldom used in practice for the analysis of right censored data. This paper presents an S-Plus/R program that implements a recently developed inference procedure [Z. Jin, D.Y. Lin, Z. Ying, On least-squares regression with censored data, Biometrika 93 (2006) 147-161] for the accelerated failure time model based on the least-squares principle. The program is user-friendly and yields outputs similar to S-Plus/R function 1m.     

Batch RNAi selector: a standalone program to predict specific siRNA candidates in batches with enhanced sensitivity

RNA interference (RNAi) is a popular and effective method for silencing gene expression. siRNAs should be gene-specific and effective to achieve specific and potent gene silencing. However, most currently available siRNA design programs are web-based programs that either require each sequence be submitted individually, making large-batch analyses difficult to conduct, or only provide limited options for searching off-target candidates (e.g. NCBI-BLAST). We have developed a stand-alone, enhanced RNAi design program that overcomes these shortcomings. We have implemented WU-BLAST, FASTA and SSEARCH homology searches for siRNA candidates to improve gene specific siRNA selection and to identity siRNA candidates that could lead to off-target gene silencing. We also included many new features such as siRNA score calculation and calculation of siRNA internal stability to help select highly potent siRNAs. This program is freely available for academic and commercial use (), and can be installed and run on any Linux machine. Our program automates the search for siRNAs and the resulting data files including a list of siRNA primers with scores and database search results for each siRNA candidate are stored locally for easy retrieval and inspection when needed.