Data distribution schemes of sparse arrays on distributed memory multicomputers

A data distribution scheme of sparse arrays on a distributed memory multicomputer, in general, is composed of three phases, data partition, data distribution, and data compression. To implement the data distribution scheme, many methods proposed in the literature first perform the data partition phase, then the data distribution phase, followed by the data compression phase. We called a data distribution scheme with this order as Send Followed Compress (SFC) scheme. In this paper, we propose two other data distribution schemes, Compress Followed Send (CFS) and Encoding-Decoding (ED), for sparse array distribution. In the CFS scheme, the data compression phase is performed before the data distribution phase. In the ED scheme, the data compression phase can be divided into two steps, encoding and decoding. The encoding step and the decoding step are performed before and after the data distribution phase, respectively. To evaluate the CFS and the ED schemes, we compare them with the SFC scheme. In the data partition phase, the row partition, the column partition, and the 2D mesh partition with/without load-balancing methods are used for these three schemes. In the compression phase, the CRS/CCS methods are used to compress sparse local arrays for the SFC and the CFS schemes while the encoding/decoding step is used for the ED scheme. Both theoretical analysis and experimental tests were conducted. In the theoretical analysis, we analyze the SFC, the CFS, and the ED schemes in terms of the data distribution time and the data compression time. In experimental tests, we implemented these three schemes on an IBM SP2 parallel machine. From the experimental results, for most of test cases, the CFS and the ED schemes outperform the SFC scheme. For the CFS and the ED schemes, the ED scheme outperforms the CFS scheme for all test cases.

Probabilistic analysis on mesh network fault tolerance

Mesh networks are among the most important interconnection network topologies for large multicomputer systems. Mesh networks perform poorly in tolerating faults in the view of worst-case analysis. On the other hand, such worst cases occur very rarely in realistic situations. In this paper, we study the fault tolerance of 2-D and 3-D mesh networks under a more realistic model in which each network node has an independent failure probability. We first observe that if the node failure probability is fixed, then the connectivity probability of these mesh networks can be arbitrarily small when the network size is sufficiently large. Thus, it is practically important for multicomputer system manufacture to determine the upper bound for node failure probability when the probability of network connectivity and the network size are given. We develop a novel technique to formally derive lower bounds on the connectivity probability for 2-D and 3-D mesh networks. Our study shows that these mesh networks of practical size can tolerate a large number of faulty nodes thus are reliable enough for multicomputer systems. For example, it is formally proved that as long as the node failure probability is bounded by 0.5%$0.5\%$, a 3-D mesh network of up to a million nodes remains connected with a probability larger than 99%$99\%$.     

A resource broker with an efficient network information model on grid environments

This paper describes a resource broker whose main function is to match available resources to user needs. The resource broker provides a uniform interface for accessing available and appropriate resources via user credentials. We also focus on providing approximate measurement models for network-related information using NWS for future scheduling and benchmarking. We first propose a network measurement model for gathering network-related information (including bandwidth, latency, forecasting, error rates, etc.) without generating excessive system overhead. Second, we constructed a grid platform using Globus Toolkit that integrates the resources of five schools in Taichung integrated grid environment resources (TIGER). The resource broker runs on top of TIGER. Therefore, it provides security and current information about available resources and serves as a link to the diverse systems available in the Grid.

Classification of hematologic malignancies using texton signatures

We describe a decision support system to distinguish among hematology cases directly from microscopic specimens. The system uses an image database containing digitized specimens from normal and four different hematologic malignancies. Initially, the nuclei and cytoplasmic components of the specimens are segmented using a robust color gradient vector flow active contour model. Using a few cell images from each class, the basic texture elements (textons) for the nuclei and cytoplasm are learned, and the cells are represented through texton histograms. We propose to use support vector machines on the texton histogram based cell representation and achieve major improvement over the commonly used classification methods in texture research. Experiments with 3,691 cell images from 105 patients which originated from four different hospitals indicate more than 84% classification performance for individual cells and 89% for case based classification for the five class problem.

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The effect of shoe sole tread groove depth on the friction coefficient with different tread groove widths, floors and contaminants

Slipping and falling are common phenomena in both workplaces and our daily activities. The risks associated with slipping and falling are related to the materials of footwear/floor, contamination condition, and geometric design of the sole. Shoe soles of various tread design are very common. Tread pattern of the shoe affects friction especially under liquid-contaminated conditions. Verification of the effects of tread groove depth is significant in assisting designers in designing proper footwear for workers exposed to slippery floor conditions. In this study, we measured the friction coefficients using the Neolite footwear pads on the terrazzo, steel, and vinyl floors under three liquid-contaminated conditions. A Brungraber Mark II slipmeter was used. The footwear pads had tread grooves with a width of either 3 or 9 mm. The depth of the tread grooves ranged from 1 to 5 mm. The results showed that tread groove depth affected the friction coefficients significantly. Higher friction values were recorded for footwear pads with deeper tread grooves on wet and water–detergent-contaminated floors. The averaged coefficient of friction (COF) gain per tread groove depth increase in millimeter under these two surface conditions ranged from 0.018 to 0.108, depending on the tread groove width, floor, and contaminant.     

Integral-based filtering of continuous glucose sensor measurements for glycaemic control in critical care

Hyperglycaemia is prevalent in critical illness and increases the risk of further complications and mortality, while tight control can reduce mortality up to 43%. Adaptive control methods are capable of highly accurate, targeted blood glucose regulation using limited numbers of manual measurements due to patient discomfort and labour intensity. Therefore, the option to obtain greater data density using emerging continuous glucose sensing devices is attractive. However, the few such systems currently available can have errors in excess of 20-30%. In contrast, typical bedside testing kits have errors of approximately 7-10%. Despite greater measurement frequency larger errors significantly impact the resulting glucose and patient specific parameter estimates, and thus the control actions determined creating an important safety and performance issue. This paper models the impact of the continuous glucose monitoring system (CGMS, Medtronic, Northridge, CA) on model-based parameter identification and glucose prediction. An integral-based fitting and filtering method is developed to reduce the effect of these errors. A noise model is developed based on CGMS data reported in the literature, and is slightly conservative with a mean Clarke Error Grid (CEG) correlation of R=0.81 (range: 0.68-0.88) as compared to a reported value of R=0.82 in a critical care study. Using 17 virtual patient profiles developed from retrospective clinical data, this noise model was used to test the methods developed. Monte-Carlo simulation for each patient resulted in an average absolute 1-h glucose prediction error of 6.20% (range: 4.97-8.06%) with an average standard deviation per patient of 5.22% (range: 3.26-8.55%). Note that all the methods and results are generalizable to similar applications outside of critical care, such as less acute wards and eventually ambulatory individuals. Clinically, the results show one possible computational method for managing the larger errors encountered in emerging continuous blood glucose sensors, thus enabling their more effective use in clinical glucose regulation studies.     

基于AJAX的Web无刷新页面快速更新数据方法*

针对B/S应用中的Web服务器与浏览器间频繁操作导致Web应用执行速度慢的问题,提出了一种基于AJAX的Web无刷新页面更新数据的方法。     

SrTiO3基沿面放电电极材料配方优化

采用均匀设计法设计配方,研究了以SrTiO3为基料,掺杂PbTiO3,TiO2,Bi2O3对臭氧发生器用SrTiO3基陶瓷电极材料的介电常数,正切损耗,击穿电压,电阻率等电性能的影响,通过对实验结果进行回归分析表明了各掺杂料的比例与各电参数的关系,其中Bi2O3含量对材料性能的影响最大,优化结果表明,为了获得U＞10Kv/mm,ε约100左右,thδ＜0．01,ρ＜1010Ω 材料,最适合的掺杂配方是：Bi2O31.40%,TiO20.30%,PbTiO3 0.30%和CeO20.50%。     

企业财务管理辅助决策探讨

通过对财务数据的分析,结合数据仓库开发原理,完成对财务数据仓库的数据组织及模型建立,介绍了财务管理辅助决策分析的思路及设计方法。     

嵌入式中长图无纸记录仪数据分析软件包的研究和开发

随着电子技术的发展、传统的机械式记录仪被无纸记录仪所取代是不争的事实。本文介绍了无纸记录仪数据分析软件包的结构、功能及其实现技术。