Reading handwritten digits: a ZIP code recognition system

A neural network algorithm-based system that reads handwritten ZIP codes appearing on real US mail is described. The system uses a recognition-based segmenter, that is a hybrid of connected-components analysis (CCA), vertical cuts, and a neural network recognizer. Connected components that are single digits are handled by CCA. CCs that are combined or dissected digits are handled by the vertical-cut segmenter. The four main stages of processing are preprocessing, in which noise is removed and the digits are deslanted, CCA segmentation and recognition, vertical-cut-point estimation and segmentation, and directly lookup. The system was trained and tested on approximately 10000 images, five- and nine-digit ZIP code fields taken from real mail     

Physical training: a tool for increasing work tolerance limits of employees engaged in manual handling tasks.

The lack of physical fitness is a contributing factor to the etiology of musculoskeletal disorders resulting from the manual handling of material in industry. Thus the major objectives of this paper were (1) to discuss the role of physical fitness in the control of occupational injuries; (2) to review techniques available in the exercise physiology literature for increasing human physical capacity in industry; and (3) to review and evaluate studies on the effects of physical training on individuals engaged in manual handling tasks.     

A study of impact toughness of Fe-Cr-X damping alloys

A study was carried out on the impact toughness of Fe- Cr- Х damping alloys. Two measures proved to be effective in improving impact toughness. One was to lower carbon plus nitrogen content to an ultra- low level. This method is suitable for single- phase ferrite alloy. The other is to use dual- phase damping alloys. The presence of martensite in Fe- Cr- Х alloys can enhance impact toughness remarkably, but lower damping capacity drastically. This shows the importance of achieving balance between mechanical prop-erties and damping capacity by properly controlling martensite volume fraction in dual- phase alloys.     

USE OF DIELECTRIC SPECTROSCOPY TO ASSESS ADHESIVELY BONDED COMPOSITE STRUCTURES, PART I: WATER PERMEATION IN EPOXY ADHESIVE

This three-part series of papers describes studies on water penetration into epoxy resins and the use of low- and high-frequency dielectric spectroscopy as a method of monitoring the health of adhesive bond lines in bonded epoxy/graphite composite structures. The first paper is concerned with an investigation of the effect of water ingress into the epoxy adhesive resin used in the manufacturing of the adhesive bond. This study reports a dynamic mechanical thermal analysis (DMTA) and gravimetric analysis of the effects of water uptake and interprets the data in terms of various processes that can occur within the adhesive. Surprisingly high values of water absorption were observed in samples where the edges were unconstrained and presented direct access to the fibre matrix for the moisture. The study demonstrated the effects of postcure and leaching on the sorption and desorption processes and provided background data, which are necessary for the interpretation of the study described in Parts II and III of this series of articles.     

Intergranular stresses in ZIRCALOY-2

The development of the understanding of the intergranular stresses in ZIRCALOY-2 is reviewed. Neutron diffraction measurements of the intergranular strains were made on rod-textured material and highly textured plate. The elastoplastic self-consistent (EPSC) model provides a sound theoretical foundation for our understanding of the behavior. The strain response of ZIRCALOY-2 to applied tensile stress is well described for two very different textures with the same slip and hardening parameters. It is almost certain that tensile twinning is the explanation for the response to compressive stress and rolling that is, as yet, incompletely understood. This article is based on a presentation made in the symposium entitled “Defect Properties and Mechanical Behavior of HCP Metals and Alloys” at the TMS Annual Meeting, February 11–15, 2001, in New Orleans, Louisiana, under the auspices of the following ASM committees: Materials Science Critical Technology Sector, Structural Materials Division, Electronic, Magnetic & Photonic Materials Division, Chemistry & Physics of Materials Committee, Joint Nuclear Materials Committee, and Titanium Committee.     

Tracking nonstationary probabilities in adaptive binary arithmeticcoding

Adaptive arithmetic coders sometimes exhibit nonstationary symbol probabilities when coding digital halftone images with neighborhood-template models. If these nonstationary probabilities vary nonrandomly, the variations can be tracked robustly when each context derived from the coding model is expanded by conditioning on previously coded values for that model context.     

A comprehensive approach to the solution of direct-coupledmultislice model of skewed rotor induction motors using time-steppingeddy-current finite element method

Normally a complicated three-dimensional (3-D) approach is needed to study the field pattern of induction machines with skewed rotor bars. In this paper, a time-stepping two-dimensional (2-D) eddy-current finite element method, based on multislice technique, is described to study the steady-state operation and the starting process of skewed rotor induction machines. The fields of the multislices are being solved en bloc simultaneously, and thus, the effects of the eddy current and saturation can be taken into account directly. New forms of the governing equations for the multislice model are derived, which allow the meshes of multislices to be taken as one 2-D mesh so that the algorithm is very similar to that of general 2-D problems. Special techniques required for the mesh generation in the multislice model and the salient structures of the software are also described. The results obtained by using the program being developed have very good correlation with test data     

Plasma immersion ion implantation for SOI synthesis: SIMOX and ion-cut

We have demonstrated feasibility to form silicon-on-insulator (SOI) substrates using plasma immersion ion implantation (PIII) for both separation by implantation of oxygen and ion-cut. This high throughput technique can substantially lower the high cost of SOI substrates due to the simpler implanter design as well as ease of maintenance. For separation by plasma implantation of oxygen wafers, secondary ion mass spectrometry analysis and cross-sectional transmission electron micrographs show continuous buried oxide formation under a single-crystal silicon overlayer with sharp Si/SiO₂ interfaces after oxygen plasma implantation and high-temperature (1300°C) annealing. Ion-cut SOI wafer fabrication technique is implemented for the first time using PIII. The hydrogen plasma can be optimized so that only one ion species is dominant in concentration and there are minimal effects by other residual ions on the ion-cut process. The physical mechanism of hydrogen induced silicon surface layer cleavage has been investigated. An ideal gas law model of the microcavity internal pressure combined with a two-dimensional finite element fracture mechanics model is used to approximate the fracture driving force which is sufficient to overcome the silicon fracture resistance.     

Inductive learning from preclassified training examples: anempirical study

Many real-world decision-making problems fall into the general category of classification. Algorithms for constructing knowledge by inductive inference from example have been widely used for some decades. Although these learning algorithms frequently address the same problem of learning from preclassified examples and much previous work in inductive learning has focused on the algorithms' predictive accuracy, little attention has been paid to the effect of data factors on the performance of a learning system. An experiment was conducted using five learning algorithms on two data sets to investigate how the change in labeling the class attribute can alter the behavior of learning algorithms. The results show that different preclassification rules applied on the training examples can affect either the classification accuracy or classification structure     

Optimal structural design with damping constraint limitations

The algorithm optimization presented uses the optimality criteria method so as to minimize the total weight of the structure in the presence of a constraint of the damping type. The goal of this study is to increase the structural damping by optimizing the viscoelastic and elastic material distribution over the structure. The types of damping considered are hysteristic. The gradient of the constraint function in relation to the design variables is calculated with the aid of a complex variable sensitivity method. Several numerical results are presented to validate the algorithm proposed.