A hybrid homogeneously weighted moving average control chart for process monitoring: Discussion

The sensitivity of a monitoring scheme depends on many factors including the variance of the charting statistic which is very important in the computation of the control limits. This paper discusses the computation of the variance of the recently proposed hybrid homogeneously weighted moving average (HHWMA) $\overline{X}$ scheme which was based on an incorrect assumption. The correct variance is used to evaluate the run-length characteristics of the HHWMA $\overline{X}$ scheme. It is observed that the incorrect variance has a significant impact on the sensitivity (or performance) of the HHWMA $\overline{X}$ scheme.     

基于学科竞赛的中医药类院校程序设计课程教学模式的探索

高素质人才培养是我国可持续发展战略、科教兴国战略以及人才强国战略等多项发展战略的一项基础性工程。本文针对中医药类院校程序设计类课程实践教学模式单一等教学实际，以“学科竞赛”为平台，“赛教结合”为理念，以《C语言程序设计》为例，从现存问题、赛教结合模式的引入、建立实施及其评价机制4个方面展开阐述，旨在提高学生学习积极性和能力。     

云杉八齿小蠹Ips typographus L.虚拟模型构建方法研究

本文以云杉八齿小蠹Ips typographus Linnaeus为例,经标本选取,观察虫体整体形态,绘制整体结构草图,电子显微镜观察局部、得到局部数字图像,分别建立虫体每一部分的高精度细节。把模型每部分拼装在一起组成整体模型,构建出了云杉八齿小蠹三维虚拟昆虫数字化模型。     

An experiential account of phantom vibration syndrome

A small handful of recent studies have addressed a phenomenon known as “phantom vibration syndrome”. This refers to when phone users perceive their device to vibrate, indicating that a call or text is incoming, when in fact the phone did not vibrate at all. Though these studies show that most users do not find phantom vibration hallucinations to be very bothersome, they also find that a large majority of users experience this phenomenon. This paper explores what the striking prevalence of phantom vibration syndrome means for our contemporary relationships with technology. I begin with a review of the theories purporting to explain these data, which largely rely on particular understandings of the brain. Next I develop an alternative theory of phantom vibration syndrome based on insights from the philosophical tradition of phenomenology. This account considers the ways users develop bodily and perceptual habits regarding how the phone is understood and used. By critically contrasting these different theories, we can refine our questions about what the high prevalence of phantom vibration syndrome implies about our contemporary technological situation.     

Simple Sequence Repeat Markers in Genetic Divergence and Marker-Assisted Selection of Rice Cultivars: A Review

Sequencing of rice genome has facilitated the understanding of rice evolution and has been utilized extensively for mining of DNA markers to facilitate marker-assisted breeding. Simple sequence repeat (SSR) markers that are tandemly repeated nucleotide sequence motifs flanked by unique sequences are presently the maker of choice in rice improvement due to their abundance, co-dominant inheritance, high levels of allelic diversity, and simple reproducible assay. The current level of genome coverage by SSR markers in rice is sufficient to employ them for genotype identification and marker-assisted selection in breeding for mapping of genes and quantitative trait loci analysis. This review provides comprehensive information on the mapping and applications of SSR markers in investigation of rice cultivars to study their genetic divergence and marker-assisted selection of important agronomic traits.     

TCBR-HMM: An HMM-based text classifier with a CBR system

This paper presents an innovative solution to model distributed adaptive systems in biomedical environments. We present an original TCBR-HMM (Text Case Based Reasoning-Hidden Markov Model) for biomedical text classification based on document content. The main goal is to propose a more effective classifier than current methods in this environment where the model needs to be adapted to new documents in an iterative learning frame. To demonstrate its achievement, we include a set of experiments, which have been performed on OSHUMED corpus. Our classifier is compared with Naive Bayes and SVM techniques, commonly used in text classification tasks. The results suggest that the TCBR-HMM Model is indeed more suitable for document classification. The model is empirically and statistically comparable to the SVM classifier and outperforms it in terms of time efficiency.