A new supervised classification algorithm in artificial immune systems with its application to carotid artery Doppler signals to diagnose atherosclerosis

Because of its self-regulating nature, immune system has been an inspiration source for usually unsupervised learning methods in classification applications of Artificial Immune Systems (AIS). But classification with supervision can bring some advantages to AIS like other classification systems. Indeed, there have been some studies, which have obtained reasonable results and include supervision in this branch of AIS. In this study, we have proposed a new supervised AIS named as Supervised Affinity Maturation Algorithm (SAMA) and have presented its performance results through applying it to diagnose atherosclerosis using carotid artery Doppler signals as a real-world medical classification problem. We have employed the maximum envelope of the carotid artery Doppler sonograms derived from Autoregressive (AR) method as an input of proposed classification system and reached a maximum average classification accuracy of 98.93% with 10-fold cross-validation method used in training-test portioning. To evaluate this result, comparison was done with Artificial Neural Networks and Decision Trees. Our system was found to be comparable with those systems, which are used effectively in literature with respect to classification accuracy and classification time. Effects of system's parameters were also analyzed in performance evaluation applications. With this study and other possible contributions to AIS, classification algorithms with effective performances can be developed and potential of AIS in classification can be further revealed.     

递归程序设计的公式化方法

如果在设计递归程序时首先写出它的递归公式,那么编码过程会大大简化,而且得到的程序具有极好的可读性。这一思想有助于递归程序的标准化,并具有很大的普遍性。     

Quantum chemical studies on protonation of some substituted thiazole derivatives

The acidity constants, pK(a) values for protonation of some substituted thiazole derivatives were calculated by using AM1 and PM3 basis sets of semi-empirical methods and B3LYP/6-31G(d) basis sets of density functional theory (DFT) calculated physical and thermodynamic parameters. Correlation search among the experimental and calculated acidity constants, pK(a) values, revealed that the best correlation exist between the experimental and ab initio calculated pK(a) values with a regression of R(2)=0.98.     

Efficient storage of healthcare data in XML-based smart cards

In this paper we present storage structures for efficiently processing XML path queries on healthcare data stored in smart cards using XML format. In the design of the storage structures that we present, properties of healthcare data and fundamental types of queries on the healthcare data are taken into account as well as the constraints of the smart cards. We compare the space and time efficiency of the proposed storage structures for various types of queries.     

基于B B C电子商务模式的用户权限控制

通过对传统的用户权限控制方法的全面分析,结合BBC电子商务模式用户多样化的特点,提出了一种基于角色和用户功能项相结合的权限控制方法,并给出了具体的实现方法。     

企业门户Web资源整合及其实现的研究*

讨论了企业门户Web资源整合中的关键问题,分析并给出了相关整合技术方案。提出了一种特殊的远程门户组件Web服务（WSRP）实现机制WA2WP（Web Application to WSRP Portlet）,可将普通Web网站映射封装为虚拟门户组件发布;给出了改进的跨域单点登录机制SSO4EPI（Single Sign On for Enterprise Portal Integration）,可提供开放的接口形式和对跨安全域异构性的良好支持。最后结合应用实例说明以上方法的可行性和推广价值。     

Clustering of high throughput gene expression data

High throughput biological data need to be processed, analyzed, and interpreted to address problems in life sciences. Bioinformatics, computational biology, and systems biology deal with biological problems using computational methods. Clustering is one of the methods used to gain insight into biological processes, particularly at the genomics level. Clearly, clustering can be used in many areas of biological data analysis. However, this paper presents a review of the current clustering algorithms designed especially for analyzing gene expression data. It is also intended to introduce one of the main problems in bioinformatics – clustering gene expression data – to the operations research community.     

Honeymoon with IWBs: A qualitative insight in primary students' views on instruction with interactive whiteboard

The main purpose of this study was to investigate the views of primary students about interactive whiteboard [IWB] use in their classes from attitudinal and pedagogical perspectives. Research was designed as an empirical approach to phenomenology. Data was collected from fifty primary students (fourth to eighth) through focus group interviews. Nvivo 9 qualitative data analysis software was used to analyze data. Results showed that students like instruction with IWB especially for such reasons/capabilities as practical and economical use, better visual presentation, and test-based use. Students were predominantly uncomfortable with the technical problems. They believed that instruction with IWB positively impacted their learning especially because of visualization and contextualization, effective presentation, test-based use, and motivational factors. Finally it was inferred that IWBs were not used to their full potential, and both technical problems and common practices indicated that teachers were still at an initial stage of transmission to instruction with IWB and they needed both technical and pedagogical training.     

Multirobot coordination in pick-and-place tasks on a moving conveyor

This paper considers the problem of multirobot coordination in pick-and-place tasks on a conveyor band. The robot team is composed of identical robots with mutually exclusive, but neighboring workspaces. The products are fed in at one end of the band, move through each workspace sequentially until being picked up and are collected at the other end—if not picked up interim. Each robot has the same task—that is picking up and packaging as many products as possible. We propose an approach based on noncooperative game theory where each robot uses local observations of the conveyor band and their neighbors' actions in order to decide on its actions. The developed algorithm has been implemented and tested in a simulated manufacturing environment using Webots. Results obtained from the simulations are analyzed using a variety of statistical performance measures.     

Design of a framework for modeling, integration and simulation of physiological models

Multiscale modeling and integration of physiological models carry challenges due to the complex nature of physiological processes. High coupling within and among scales present a significant challenge in constructing and integrating multiscale physiological models. In order to deal with such challenges in a systematic way, there is a significant need for an information technology framework together with related analytical and computational tools that will facilitate integration of models and simulations of complex biological systems. Physiological Model Simulation, Integration and Modeling Framework (Phy-SIM) is an information technology framework providing the tools to facilitate development, integration and simulation of integrated models of human physiology. Phy-SIM brings software level solutions to the challenges raised by the complex nature of physiological systems. The aim of Phy-SIM, and this paper is to lay some foundation with the new approaches such as information flow and modular representation of the physiological models. The ultimate goal is to enhance the development of both the models and the integration approaches of multiscale physiological processes and thus this paper focuses on the design approaches that would achieve such a goal.