A Markovian model for TCP over ATM

This paper focuses on the development of an approximate Markov chain model and a detailed simulation model for the performance analysis of TCP connections supporting long file transfers within highspeed ATM networks. The Markov model construction is first illustrated, emphasizing the simplifying assumptions introduced to maintain an acceptable complexity in the performance study. Then the model validation is described, comparing the analytical results with those produced by a very detailed simulation setup in which the officially distributed BSD 4.3 TCPreno code was adapted to run on top of a software tool for the simulation of ATM networks. Numerical results indicate that the analytical model is able to capture the overall behavior of the system with respect to the performance measures we consider, with a cost which is orders of magnitude less than the one necessary to obtain reliable estimates from the detailed simulation model.     

A hierarchical Markovian model for multiscale region-based classification of vector-valued images

We propose a new classification method for vector-valued images, based on: 1) a causal Markovian model, defined on the hierarchy of a multiscale region adjacency tree (MRAT), and 2) a set of nonparametric dissimilarity measures that express the data likelihoods. The image classification is treated as a hierarchical labeling of the MRAT, using a finite set of interpretation labels (e.g., land cover classes). This is accomplished via a noniterative estimation of the modes of posterior marginals (MPM), inspired from existing approaches for Bayesian inference on the quadtree. The paper describes the main principles of our method and illustrates classification results on a set of artificial and remote sensing images, together with qualitative and quantitative comparisons with a variety of pixel-based techniques that follow the Bayesian-Markovian framework either on hierarchical structures or the original image lattice.     

A multiscale stochastic image model for automated inspection

We develop a novel multiscale stochastic image model to describe the appearance of a complex three-dimensional object in a two-dimensional monochrome image. This formal image model is used in conjunction with Bayesian estimation techniques to perform automated inspection. The model is based on a stochastic tree structure in which each node is an important subassembly of the three-dimensional object. The data associated with each node or subassembly is modeled in a wavelet domain. We use a fast multiscale search technique to compute the sequential MAP (SMAP) estimate of the unknown position, scale factor, and 2-D rotation for each subassembly. The search is carried out in a manner similar to a sequential likelihood ratio test, where the process advances in scale rather than time. The results of this search determine whether or not the object passes inspection. A similar search is used in conjunction with the EM algorithm to estimate the model parameters for a given object from a set of training images. The performance of the algorithm is demonstrated on two different real assemblies.     

Fully automated colon segmentation for the computation of complete colon centerline in virtual colonoscopy

Virtual colonoscopy detects polyps by navigating along a colon centerline. Complete colon segmentation based on computed tomography (CT) data is a prerequisite to the computation of complete colon centerline. There are two main problems impeding complete segmentation: overdistention/underdistention of colon and the use of oral contrast agents. Overdistention produces loops in the segmented colon, while underdistention may cause the segmented colon collapse into a series of disconnected segments. Use of oral contrast agents, which have high attenuation on CT, may add redundant structures (bones and small bowels) to the segmented colon. A fully automated colon segmentation method is proposed in this paper to address the two problems. We tested the proposed method in 170 cases, including 37 "moderate" and 133 "challenging" cases. Computer-generated centerlines were compared with human-generated centerlines (plotted by three radiologists). The proposed method achieved a 90.56% correct coverage rate with respect to the human-generated centerlines. We also compared the proposed method with two existing colon segmentation methods: Uitert's method and Nappi's method. The results of these two methods were 75.16% and 72.59% correct coverage rates, respectively. Our experimental results indicate that the proposed method could yield more complete colon centerlines than the existing methods.     

A new statistical model for Markovian classification of urban areas in high-resolution SAR images

We propose a classification method suitable for high-resolution synthetic aperture radar (SAR) images over urban areas. When processing SAR images, there is a strong need for statistical models of scattering to take into account multiplicative noise and high dynamics. For instance, the classification process needs to be based on the use of statistics. Our main contribution is the choice of an accurate model for high-resolution SAR images over urban areas and its use in a Markovian classification algorithm. Clutter in SAR images becomes non-Gaussian when the resolution is high or when the area is man-made. Many models have been proposed to fit with non-Gaussian scattering statistics (K, Weibull, Log-normal, Nakagami-Rice, etc.), but none of them is flexible enough to model all kinds of surfaces in our context. As a consequence, we use a mathematical model that relies on the Fisher distribution and the log-moment estimation and which is relevant for one-look data. This estimation method is based on the second-kind statistics, which are detailed in the paper. We also prove its accuracy for urban areas at high resolution. The quality of the classification that is obtained by mixing this model and a Markovian segmentation is high and enables us to distinguish between ground, buildings, and vegetation.     

A simple Markovian method for MTTF calculation

The MTTF of a system design with constant failure and repair rates and with some forms of stand-by redundancy and switching is an important characteristic of the system. Commonly, calculation of the MTTF requires knowledge of the reliability function R(t), which is integrated to yield the MTTF. In many cases obtaining the reliability function is a non-trivial task and its analytic integration may be quite tedious. In the following we describe a simple method of obtaining the MTTF of such systems which avoids the need of knowledge of R(t). The method is Markovian in nature and is based on summing the probabilities of all the possible routes (in the space of states) by which the system can get from its initial state at t = 0 to an absorbing state (failed state), where each such probability is multiplied by the average time required for the system to follow that route. This weighted sum yields the MTTF for any given initial conditions. The method is demonstrated on some useful systems and analytical formulas for the MTTF are derived. It is further demonstrated how the results of the method may be used in the calculation of the MTBF of the system in steady-state.     

激光诱发荧光用于结肠肿瘤早期诊断

激光诱导荧光法（ＬａｓｅｒＩｎｄｕｃｅｄ Ｆｌｕｏｒｅｓｃｅｎｃｅ ＬＩＦ）利用生物组织的自体荧光特性判断组织性质,能实时、无损地提供组织信息,从而区分正常与病变组织。本文采用固体可调谐激光器Ｃｒ：ＬｉＣＡＦ作为激发光源,在３６０ｎｍ ～４１０ｎｍ 波段范围选择多种波长对结肠癌和结肠正常组织标本进行ＬＩＦ测试,找出了能诱导结肠正常组织与癌变组织产生最大荧光光谱差异的最佳激发波长,并对３１ 组正常组织与病变组织标本进行测式,结果表明结肠正常组织与癌变组织自体荧光光谱存在明显差异。     

On verifying the first-order Markovian assumption for a Rayleighfading channel model

The use of received signal-to-noise ratio (SNR) as the side information in communication systems has been widely accepted especially when the channel quality is time varying. On many occasions, this side information is treated as the received SNR of the current channel symbol or that of previous symbols. In particular, the first-order Markov channel provides a mathematically tractable model for time-varying channels and uses only the received SNR of the symbol immediately preceding the current one. With the first-order Markovian assumption, given the information of the symbol immediately preceding the current one, any other previous symbol should be independent of the current one. Although the experimental measurements confirm the usefulness of the first-order Markovian assumption, one may argue that second or higher-order Markov processes should provide a more accurate model. We answer this question by showing that given the information corresponding to the previous symbol, the amount of uncertainty remaining in the current symbol should be negligible     

A model for sequential machine testing and diagnosis

A mathematical framework for the testing and diagnosis of sequential machines is developed. A very general fault model is used in which a faulty machine is represented as a sequential machine, possibly with state and output sets different from those of the good machine. A deterministic finite automaton, called observer, describes the process by which one gains information from the observation of the responses to test sequences. It generalizes the work of Hennie on distinguishing and homing sequences, by modelling all the possible conclusions that could be drawn from observing the circuit under test. A nondeterministic acceptor is derived from the observer; it accepts diagnosing sequences and can also be used to generate test sequences. We then associate probabilities with this nondeterministic acceptor which, together with a stochastic source of input symbols, provides a probabilistic diagnoser. As a particular application we consider the testing and diagnosis of random-access memories by random test sequences. Our model generalizes the work by David et al. on the calculation of the length of a random test sequence required to guarantee that the probability of detection of a fault exceeds a prescribed threshold.This work was supported by the Natural Sciences and Engineering Research Council of Canada, Grants OGP0000871 and OGP0000243, and a grant from the Information Technology Research Centre of Ontario. Preliminary papers leading to this work have appeared earlier [1] [2].     

激光在治疗进展期结直肠癌中的应用

本文系统地介绍激光治疗进展期结直肠癌的适应症、激光治疗的具体方法和技术、治疗效果、治疗的并发症及处理等,并对国内外治疗研究现状进行述评;可为临床医师和研究人员提供参考。     

自体荧光诊断癌肿瘤

本文较全面地介绍了在激光的诱导下，利用生物组织的自体荧光光谱特性对多种癌肿瘤的诊断，并初步探讨了癌组织中自体荧光的来源。     

A novel in-line automated metrology for photolithography

Novel metrology has been developed for measuring in situ film thickness and absorption coefficient simultaneously. Designed specifically for photolithography processes, this metrology if applied to photoresist films, can measure thickness and photoactive compound concentration in situ, which are important parameters for photolithography process control and diagnosis     

A highly automated semi-custom approach for VLSI

The structured approach is aimed at optimizing the chip physical design while keeping design resources and time at a reasonable level. The logic is partitioned into data flow logic and control logic; a specialized physical structure has been defined to match the data flow logic structure and the gate array has been chosen for control logic implementation, both physical structures being customizable. A general purpose library and a set of design automation programs have been developed to allow fast physical design of the functional partitions according to the applications. A bipolar 16-bit slice microprocessor has been designed with this approach and built; compared to the widely used gate array chip implementation, it shows an improvement of 2 in gate density and 1.5 in power dissipation. The physical design of this 2000 gates chip took only two months.     

TNP-470对大鼠结肠癌肝转移形态结构的影响

TNP-470是目前公认的最有效的血管生成抑制剂,本文建立大鼠结肠癌肝转移动物模型,观察TNP-470对肿瘤细胞及肿瘤组织内毛细血管形态结构的影响。     

PRIME: An operational model for a hospital automated information system

PRIME is an acronym for a subject-oriented computer-based information storage and retrieval system which uses variable length, variable content, natural language, data collection forms. PRIME was developed as a model of a hospital automated information system and has been in operation since March 1965. Experience with this model system has shown that it is important to spend time planning the management and use of the computer system before the system is installed. Education programs for medical staff members and researchers are well worth the effort because it does take effort to get professional staff members to use a computer system. Data collection forms should be designed by the individual who uses them. It helps him to organize his thoughts about his project. Some conclusions about the administrative aspects of an automated information system in a hospital are presented.     

A control system for automated multiscale measuring systems

Quality inspection of micro systems on wafer scale must cope with conflicting demands: nanometer accuracy and high velocity in a comparatively large workspace. An Automated Multiscale Measuring System (AMMS) combines multiple sensors that operate at specific scales by an intelligent measurement strategy in order to balance speed and accuracy. The AMMS demonstrator is based on a modified Mahr MFU 100 with a position and tilt deflection measurement resolution of 1 nm. In this paper multiscale models of a horizontal axis with an operating range of 200 mm and their application to state linearization and control parameterization of the residual dynamics according to multiscale sensor system characteristics are developed and discussed. Main modeling issues are sliding and submicron presliding friction for model-based compensation and control, reaching from submicron positioning to high-velocity trajectory tracking with desired performance. A new experimental design for the identification of presliding friction parameters and a higher-order friction calculator are presented. Experimental results show the effectiveness of this approach.     

A headway safety policy for automated highway operations

The maximum capacity, cost, and safety of an automated highway system are largely dependent on the selected headway policy, i.e., the specification of a minimum acceptable headway (as a function of speed) for mainline operations. Here a policy, designed to avert collisions due to "reasonable" lead-car decelerations, is presented and evaluated in the context of achieving high capacity (≥3600 vehicle/lane/hr) over a range of typical highway speeds-13.5 to 30 m/s (30.2 to 67.2 mi/h). This involved a detailed analysis to determine both the relationships between, and the requirements on, the seven parameters which are embedded in this policy. These pertain to systems-level operations, the capabilities of a vehicle's automatic control system, and the vehicle/ roadway interface. The trade-offs associated with safety, capacity, and cost (in the form of required future development efforts) are identified, and three general approaches to selecting parameters for an operational system are specified.