石油工程师计算机使用情况的调查及其对石油工程教育的启示

在过去的２０年里，计算机的运算能力及信息处理能力有了快速的重大提高、这对石油工程师的工作已经产生了极大的影响。为了证明这一点，我们就石油工程师是如何在工作中使用计算机的总是进行了一次调查。根据调查结果，我们对大学生的工程课如何与计算机和计算法接轨提出了建议。本文还对为什么和如何把计算柚我入大学生的课程中进行了一般性的讨论。     

A methodology for modeling the distributions of medical images and their stochastic properties

The probabilistic distribution properties of a set of medical images are studied. It is shown that the generalized Gaussian function provides a good approximation to the distribution of AP chest radiographs. Based on this result and a goodness-of-fit test, a generalized Gaussian autoregressive model (GGAR) is proposed. Its properties and limitations are also discussed. It is expected that the GGAR model will be useful in describing the stochastic characteristics of some classes of medical images and in image data compression and other applications.     

On the assessment of water-holding capacity of hot- vs cold-boned pork

The effects of time of boning and storage period on creatine kinase (CK) activity, transmission value, drip losses and water-holding capacity (WHC) measured by various methods was investigated. At 40 min post-mortem 30 pig carcasses with pH values > 6·2 in the loin were selected. The right loin of each carcass was hot boned and vacuum packaged immediately. The left loin was cold boned and packaged after overnight chilling at 2 ± 2°C. After 1, 5 and 12 days of storage at 0 ± 1°C, 10 hot- and cold-boned loins were unpacked and sampled. Time of boning did not affect drip losses. At 1 day post-mortem the CK activity was higher in hot- than in cold-boned pork. Sarcomere lengths were not affected by time of boning. The WHC was investigated by two controlled methods. A filter-paper press method was not sensitive enough to assess differences in WHC of hot- vs cold-boned pork. The results of a gravimetric method depended on the sample location. Results of the gravimetric test decreased with increasing storage periods. The results suggest that under the experimental conditions the chilling rates of hot-boned vs carcass-attached muscles were similar.     

Recognition of moving objects using feature signatures

An important application of machine vision systems is the recognition of known three-dimensional objects. A major difficulty arises when two or more objects project the same or similar two-dimensional image, often resulting in misclassification and degradation of system performance. The changes in images which result from the motion of objects provide a source of three-dimensional information which can greatly aid the classification process, but this three-dimensional analysis is computationally complex and subject to many sources of error. This work develops a methodology which utilizes the information derived from the apparent changes in object features over time to facilitate the recognition task, without the need to actually recover the three-dimensional structure of the objects under view. The basic approach is to generate a ``feature signature' by combining the feature measurements of the individual regions in a long sequence of images. The static information in the individual frames is analyzed along with the temporal information from the entire sequence. These techniques are particularly applicable in situations where static image processing methods cannot discriminate between ambiguous objects. Two example implementations are presented to illustrate the application of the techniques of object recognition using motion information.