Automated and Continuous Production of Microstructured Metallic Plates via Cold Embossing

Many critical issues need to be addressed when microstructured reactors are manufactured in large unit volumes. The most crucial of these are cost, ease of production, and reliability. The lack of breakthrough manufacturing technology to provide high‐efficiency, low‐cost, high‐precision plates is a hindrance to the early market implementation of systems requiring metallic microstructured plates. This contribution focuses on the development and optimization of a combined embossing and bending tool for the quick and continuous manufacture of easily machined plates.     

Ball cocks for liquid abrasive media

Translated from Khimicheskoe i Neftyanoe Mashinostroenie, No. 6, pp. 8–9, June, 1991.     

Influence of Ti Powder Characteristics on Combustion Synthesis of Porous NiTi Alloy

Porous NiTi shape memory alloy (SMA) is a novel biomedical material used for human hard tissue implant .The influence of elemental titanium powder characteristics such as powder morphology, particle size and specific surface area( SSA) on the minimal ignition temperature ,combustion temperature and final product of porous Ni-Ti SMA fabricated by combustion synthesis method was investigated in this paper by scanning electron microscopy (SEM) and laser diffraction.The preliminary data indicated that the titanium powder characteristics had a strong effect on combustion synthesis of porous NiTi SMA.     

Improvement of the engineering properties of asphalt pavements using a ‘soft’ compaction technique (AMIR-Compaction)

In most countries of the world asphalt pavement of road networks represents the biggest single investment in the transportation system. In Canada, asphalt pavement built over the past decade is worth more than 70 billion dollars (in 1984 dollars). In order to maintain the current road network at the present level of service and prevent it from further deterioration, over 6 billion dollars is needed anually.

Traditionally, asphalt overlays are widely used to rehabilitate existing deteriorated pavements. Unfortunately the new overlays have been observed to fail in a relatively short time. Thus the investment in overlays is lost.

Recent research based on the concept of relative rigidity has indicated that the rapid deterioration of new asphalt overlays is directly related to current construction equipment. It has been shown analytically and experimentally that steel rollers used in compacting the asphalt layer will result in surface cracks during construction. Traffic and environmental influences will accelerate the failure of the new layer.

This paper presents the results of a testing programme evaluating the engineering properties of asphalt slabs compacted by a new method using a compactor termed AMIR. The results showed that the AMIR compactor will prevent the formation of constitution cracks resulting in an increase of indirect tensile strength of 10% and an increase of direct tensile strength of up to 60% when compared to steel roller compacted asphalt slabs.     

On the structure of polybutadiene: 4. 13C n.m.r. spectrum of polybutadienes with cis-1,4-, trans-1,4- and 1,2-units

¹³C n.m.r. spectra of polybutadienes with different contents of cis-1,4- and 1,2-units are assigned in the resonance region of the cis and trans carbon double bond. The observed signals are assigned to configurational triads.     

Interactive survival analysis with the OCDM system: From development to application

Medical data mining is currently actively pursued in computer science and statistical research but not in medical practice. The reasons therefore lie in the difficulties of handling and statistically analyzing medical data. We have developed a system that allows practitioners in the field to interactively analyze their data without assistance of statisticians or data mining experts. In the course of this paper we will introduce data mining of medical data and show how this can be achieved for survival data. We will demonstrate how to solve common problems of interactive survival analysis by presenting the Online Clinical Data Mining (OCDM) system. Thereby the main focus is on similarity based queries, a new method to select similar cases based on their covariables and the influence of these on their survival.     

Information-based adaptive fast-forward for visual surveillance

Automated video analysis lacks reliability when searching for unknown events in video data. The practical approach is to watch all the recorded video data, if applicable in fast-forward mode. In this paper we present a method to adapt the playback velocity of the video to the temporal information density, so that the users can explore the video under controlled cognitive load. The proposed approach can cope with static changes and is robust to video noise. First, we formulate temporal information as symmetrized Rényi divergence, deriving this measure from signal coding theory. Further, we discuss the animated visualization of accelerated video sequences and propose a physiologically motivated blending approach to cope with arbitrary playback velocities. Finally, we compare the proposed method with the current approaches in this field by experiments and a qualitative user study, and show its advantages over motion-based measures.     

A geometric view of conjugate priors

In Bayesian machine learning, conjugate priors are popular, mostly due to mathematical convenience. In this paper, we show that there are deeper reasons for choosing a conjugate prior. Specifically, we formulate the conjugate prior in the form of Bregman divergence and show that it is the inherent geometry of conjugate priors that makes them appropriate and intuitive. This geometric interpretation allows one to view the hyperparameters of conjugate priors as the effective sample points, thus providing additional intuition. We use this geometric understanding of conjugate priors to derive the hyperparameters and expression of the prior used to couple the generative and discriminative components of a hybrid model for semi-supervised learning.