机床的静压系统及润滑

对机床的静压系统及其发展过程进行了综述 ,介绍了静压系统的基本结构、特点及其在机床中的各种运用。     

200MW汽轮机焊接隔板检查与加固技术

阐述了200MW汽轮机焊接隔板变形这一在国内电站中多次出现的问题,以及由于隔板变形而对机组带来的危害.强调了在隔板发生严重变形时对隔板进行焊接加固的必要性,概述了隔板检查方法,包括隔板表面缺陷、内部缺陷、通流间隙、挠曲变形等的检查,以及隔板加固的工艺要点.     

现代化中厚板热处理机组及其使用效果

介绍了引进的辐射加热无氧化辊式热处理炉及连续辊式淬火机，有效地解决了钢板的表面质量问题，取得了满意的效果．     

一种新的变轴数控机床标定方法

本文论述了国内外并联数控机床所采用的标定方法，选择了序列法进行了标定试验。但在实际标定过程中，出现了部分数据误差较大的问题，本文针对所面临的问题，提出了数值逼近法，并应用到实际机床的标定中，获得了机床的相关参数。之后，通过数学模型的计算值和实际测量值对比，验证了数据的可靠性，从而验证了方法的可行性和正确性。     

用气冲气推成形触头造型机制造电机壳铸型的试验研究

扼要介绍了用气冲气推成形触头造型机制造电机壳铸型的成型过程及其实砂效果,试验结果表明,在工作气压为0,4￣0.45MPa的条件下,气冲气推成形触头造型机对电机壳类铸型的紧实,实砂效果十分理想,砂型紧实度高而且均匀。     

我国数控机床产业差距分析

分析了我国数控机床制造产业的现状以及制造水平，最后分析了我国机床制造产业的关键共性技术。     

“车家宝”胶在制氧机超低温管路漏气上的应用

本文对“东家宝”胶在制氧机超低温管路漏气上的应用作了简要的介绍。     

Level of interest sensing in spoken dialog using decision-level fusion of acoustic and lexical evidence

Automatic detection of a user's interest in spoken dialog plays an important role in many applications, such as tutoring systems and customer service systems. In this study, we propose a decision-level fusion approach using acoustic and lexical information to accurately sense a user's interest at the utterance level. Our system consists of three parts: acoustic/prosodic model, lexical model, and a model that combines their decisions for the final output. We use two different regression algorithms to complement each other for the acoustic model. For lexical information, in addition to the bag-of-words model, we propose new features including a level-of-interest value for each word, length information using the number of words, estimated speaking rate, silence in the utterance, and similarity with other utterances. We also investigate the effectiveness of using more automatic speech recognition (ASR) hypotheses (n-best lists) to extract lexical features. The outputs from the acoustic and lexical models are combined at the decision level. Our experiments show that combining acoustic evidence with lexical information improves level-of-interest detection performance, even when lexical features are extracted from ASR output with high word error rate.     

Computer aided detection system for micro calcifications in digital mammograms

Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. Mammogram breast X-ray is considered the most reliable method in early detection of breast cancer. However, it is difficult for radiologists to provide both accurate and uniform evaluation for the enormous mammograms generated in widespread screening. Micro calcification clusters (MCCs) and masses are the two most important signs for the breast cancer, and their automated detection is very valuable for early breast cancer diagnosis. The main objective is to discuss the computer-aided detection system that has been proposed to assist the radiologists in detecting the specific abnormalities and improving the diagnostic accuracy in making the diagnostic decisions by applying techniques splits into three-steps procedure beginning with enhancement by using Histogram equalization (HE) and Morphological Enhancement, followed by segmentation based on Otsu's threshold the region of interest for the identification of micro calcifications and mass lesions, and at last classification stage, which classify between normal and micro calcifications ‘patterns and then classify between benign and malignant micro calcifications. In classification stage; three methods were used, the voting K-Nearest Neighbor classifier (K-NN) with prediction accuracy of 73%, Support Vector Machine classifier (SVM) with prediction accuracy of 83%, and Artificial Neural Network classifier (ANN) with prediction accuracy of 77%.     

Event-driven,pattern-based methodology for cost-effective development of standardized personal health devices

Experiences applying standards in personal health devices (PHDs) show an inherent trade-off between interoperability and costs (in terms of processing load and development time). Therefore, reducing hardware and software costs as well as time-to-market is crucial for standards adoption. The ISO/IEEE11073 PHD family of standards (also referred to as X73PHD) provides interoperable communication between PHDs and aggregators. Nevertheless, the responsibility of achieving inexpensive implementations of X73PHD in limited resource microcontrollers falls directly on the developer. Hence, the authors previously presented a methodology based on patterns to implement X73-compliant PHDs into devices with low-voltage low-power constraints. That version was based on multitasking, which required additional features and resources. This paper therefore presents an event-driven evolution of the patterns-based methodology for cost-effective development of standardized PHDs. The results of comparing between the two versions showed that the mean values of decrease in memory consumption and cycles of latency are 11.59% and 45.95%, respectively. In addition, several enhancements in terms of cost-effectiveness and development time can be derived from the new version of the methodology. Therefore, the new approach could help in producing cost-effective X73-compliant PHDs, which in turn could foster the adoption of standards.