From software extensions to product lines of dataflow programs

Dataflow programs are widely used. Each program is a directed graph where nodes are computations and edges indicate the flow of data. In prior work, we reverse-engineered legacy dataflow programs by deriving their optimized implementations from a simple specification graph using graph transformations called refinements and optimizations. In MDE speak, our derivations were PIM-to-PSM mappings. In this paper, we show how extensions complement refinements, optimizations, and PIM-to-PSM derivations to make the process of reverse engineering complex legacy dataflow programs tractable. We explain how optional functionality in transformations can be encoded, thereby enabling us to encode product lines of transformations as well as product lines of dataflow programs. We describe the implementation of extensions in the \(\mathtt{ReFlO}\) tool and present two non-trivial case studies as evidence of our work’s generality.     

A noise attribute thresholding method for document image binarization

A new thresholding method, called the noise attribute thresholding method (NAT), for document image binarization is presented in this paper. This method utilizes the noise attribute features extracted from the images to make the selection of threshold values for image thresholding. These features are based on the properties of noise in the images and are independent of the strength of the signals (objects and background) in the image. A simple noise model is given to explain these noise properties. The NAT method has been applied to the problem of removing text and figures printed on the back of the paper. Conventional global thresholding methods cannot solve this kind of problem satisfactorily. Experimental results show that the NAT method is very effective. Received July 05, 1999 / Revised July 07, 2000     

Kinematics of heelstrike during walking and carrying: implications for slip resistance testing

Slip resistance measurements of shoes and floors are used to evaluate the potential for slip and fall injuries. These measurements are believed to have increased validity when they more closely reflect actual heelstrike biomechanics during locomotion. The purpose of this study was to describe heelstrike kinematics during load carrying to provide data towards improved slip resistance testing. Foot kinematics during load carrying (unladen and carrying from 0 to 13.5 kg) at various cadences (70, 90, 100 steps/min) was recorded. Measures before, during and after heelstrike were analysed. Cadence was an important predictor for all variables measured, associated with changes from 13% to over 100%. The load carried was an important predictor for only the heel slip distance after heelstrike, but this effect needs to be investigated further. These results can be used to improve the fidelity of slip resistance measurements, which is critical to reduce slip and fall injuries in the workplace or during activities of daily living.     

Design of an adaptive self-organizing fuzzy neural network controller for uncertain nonlinear chaotic systems

Though the control performances of the fuzzy neural network controller are acceptable in many previous published papers, the applications are only parameter learning in which the parameters of fuzzy rules are adjusted but the number of fuzzy rules should be determined by some trials. In this paper, a Takagi–Sugeno-Kang (TSK)-type self-organizing fuzzy neural network (TSK-SOFNN) is studied. The learning algorithm of the proposed TSK-SOFNN not only automatically generates and prunes the fuzzy rules of TSK-SOFNN but also adjusts the parameters of existing fuzzy rules in TSK-SOFNN. Then, an adaptive self-organizing fuzzy neural network controller (ASOFNNC) system composed of a neural controller and a smooth compensator is proposed. The neural controller using the TSK-SOFNN is designed to approximate an ideal controller, and the smooth compensator is designed to dispel the approximation error between the ideal controller and the neural controller. Moreover, a proportional-integral (PI) type parameter tuning mechanism is derived based on the Lyapunov stability theory, thus not only the system stability can be achieved but also the convergence of tracking error can be speeded up. Finally, the proposed ASOFNNC system is applied to a chaotic system. The simulation results verify the system stabilization, favorable tracking performance, and no chattering phenomena can be achieved using the proposed ASOFNNC system.     

Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data

Knowledge of the distribution of vegetation on the landscape can be used to investigate ecosystem functioning. The sizes and movements of animal populations can be linked to resources provided by different plant species. This paper demonstrates the application of imaging spectroscopy to the study of vegetation in Yellowstone National Park (Yellowstone) using spectral feature analysis of data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS data, acquired on August 7, 1996, were calibrated to surface reflectance using a radiative transfer model and field reflectance measurements of a ground calibration site. A spectral library of canopy reflectance signatures was created by averaging pixels of the calibrated AVIRIS data over areas of known forest and nonforest vegetation cover types in Yellowstone. Using continuum removal and least squares fitting algorithms in the US Geological Survey's Tetracorder expert system, the distributions of these vegetation types were determined by comparing the absorption features of vegetation in the spectral library with the spectra from the AVIRIS data. The 0.68 μm chlorophyll absorption feature and leaf water absorption features, centered near 0.98 and 1.20 μm, were analyzed. Nonforest cover types of sagebrush, grasslands, willows, sedges, and other wetland vegetation were mapped in the Lamar Valley of Yellowstone. Conifer cover types of lodgepole pine, whitebark pine, Douglas fir, and mixed Engelmann spruce/subalpine fir forests were spectrally discriminated and their distributions mapped in the AVIRIS images. In the Mount Washburn area of Yellowstone, a comparison of the AVIRIS map of forest cover types to a map derived from air photos resulted in an overall agreement of 74.1% (kappa statistic=0.62).     

The majority theorem of centralized multiple BAMs networks

A method for modeling the learning of belief combination in evidential reasoning using a neural network is presented. A centralized network composed of multiple bidirectional associative memories (BAMs) sharing a single output array of neurons is proposed to process the uncertainty management of many pieces of evidence simultaneously. The convergence properties of the multi-BAM network are proved. The combination process of evidence is considered as a resonant process through the multi-BAM networks. Most important of all, a majority rule of decision making in presentation of multiple evidence is also found by the study of signal-noise-ratio (SNR) of the multi-BAM network. Some simulation examples are given. The result is coherent with the intuition of reasoning.     

以公共结构及语言进行应用系统一体化

介绍了美国佛罗里达电力照明公司对主要业务系统基于公共结构及语言,进行信息集成的工作过程和经验,对企业信息一体化的技术内容和框架结构做了总体介绍,并根据应用实际阐述了公共信息模型的扩展,对其他企业开展信息系统一体化工作具有一定的借鉴作用.     

Turbulence enhancement by ultrasonically induced gaseous cavitation in the CO2 saturated water

Recent primary concern for the design of high performance heat exchanger and highly integrated electronic equipments is to develop an active and creative technologies which enhance the heat transfer without obstructing the coolant flows. In this study, we found through the LDV measurement that the gaseous cavitation induced by ultrasonic vibration applied to the CO₂ saturated water in the square cross-sectioned straight duct flow enhances the turbulence much more than the case of non-ultrasonic or normal ultrasonic conditions without gaseous cavitation does. We also found that gaseous cavitation can enhance effectively the turbulent heat transfer between the heating surfaces and coolants by destructing the viscous sublayer.     

Designing to Facilitate Browsing: A Look Back at the Hyperties Workstation Browser

Since browsing hypertext can present a formidable cognitive challenge, user interface design plays a major role in determining acceptability. In the Unix workstation version of Hyperties, a research-oriented prototype, we focussed on design features that facilitate browsing. We first give a general overview of Hyperties and its markup language. Customizable documents can be generated by the conditional text feature that enables dynamic and selective display of text and graphics. In addition we present: — an innovative solution to link identification: pop-out graphical buttons of arbitrary shape.

— application of pie menus to permit low cognitive load actions that reduce the distraction of common actions, such as page turning or window selection.

— multiple window selection strategies that reduce clutter and housekeeping effort. We preferred piles-of-tiles, in which standard-sized windows were arranged in a consistent pattern on the display and actions could be done rapidly, allowing users to concentrate on the contents.