The social & economic significance of the automatic tool

Reprinted from Michigan academy of science. Report no.21, 1919.

Graph-based Semi-Supervised Learning in Acoustic Modeling for Automatic Speech Recognition

Thesis (Ph.D.)--University of Washington, 2016-06

Indefinite determiner introducing definite referent: a special use of 'yi 'one' + classifier' in Chinese

The indefinite determiner yi 'one'+ classifier' is the most approximate to an indefinite article, like the English a, in Chinese. It serves all the functions characteristic of representative stages of grammaticalization from a numeral to a generalized indefinite determiner as elaborated in the literature. It is established in this paper that the Chinese indefinite determiner has developed a special use with definite expressions, serving as a backgrounding device marking entities as of low thematic importance and unlikely to receive subsequent mentions in ensuing discourse. 'yi+ classifier' in the special use with definite expressions displays striking similarities in terms of semantic bleaching and phonological reduction with the same determiner at the advanced stage of grammaticalization characterized by uses with generics, nonspecifics and nonreferentials. An explanation is offered in terms of an implicational relation between nonreferentiality and low thematic importance which characterize the two uses of the indefinite determiner. While providing another piece of evidence in support of the claim that semantically nonreferentials and entities of low thematic importance tend to be encoded in terms of same linguistic devices in language, findings in this paper have shown how an indefinite determiner can undergo a higher degree of grammaticalization than has been reported in the literature-it expands its scope to mark not only indefinite but also definite expressions as semantically nonreferential and/or thematically unimportant. (C) 2003 Elsevier B.V. All rights reserved.

A review of the first year's experience with an automatic message-routing system for low-cost telemedicine

The Swinfen Charitable Trust has used email for some years as a low-cost telemedicine medium to provide consultant support for doctors in developing countries. A scalable, automatic message-routing system was constructed which automates many of the tasks involved in message handling. During the first 12 months of its use, 1510 messages were processed automatically. There were 128 referrals from 18 hospitals in nine countries. Of these 128 queries, 89 (70%) were replied to within 72 h; the median delay was 1.1 day. The 39 unanswered queries were sent to backup specialists for reply and 36 of them (92%) were replied to within 72 h. In the remaining three cases, a second-line (backup) specialist was required. The referrals were handled by 54 volunteer specialists from a panel of over 70. Two system operators, located 10 time zones apart, managed the system. The median time from receipt of a new referral to its allocation to a specialist was 0.2 days (interquartile range, IQR, 0.1-0.8). The median interval between receipt of a new referral and first reply was 2.6 days (IQR 0.8-5.9). Automatic message handling solves many of the problems of manual email telemedicine systems and represents a potentially scalable way of doing low-cost telemedicine in the developing world.

Gene-expression profiling reveals distinct expression patterns for classic versus variant Merkel cell phenotypes and new classifier genes to distinguish Merkel cell from small-cell lung carcinoma

Merkel cell carcinoma (MCC) is a rare aggressive skin tumor which shares histopathological and genetic features with small-cell lung carcinoma (SCLC), both are of neuroendocrine origin. Comparable to SCLC, MCC cell lines are classified into two different biochemical subgroups designated as 'Classic' and 'Variant'. With the aim to identify typical gene-expression signatures associated with these phenotypically different MCC cell lines subgroups and to search for differentially expressed genes between MCC and SCLC, we used cDNA arrays to pro. le 10 MCC cell lines and four SCLC cell lines. Using significance analysis of microarrays, we defined a set of 76 differentially expressed genes that allowed unequivocal identification of Classic and Variant MCC subgroups. We assume that the differential expression levels of some of these genes reflect, analogous to SCLC, the different biological and clinical properties of Classic and Variant MCC phenotypes. Therefore, they may serve as useful prognostic markers and potential targets for the development of new therapeutic interventions specific for each subgroup. Moreover, our analysis identified 17 powerful classifier genes capable of discriminating MCC from SCLC. Real-time quantitative RT-PCR analysis of these genes on 26 additional MCC and SCLC samples confirmed their diagnostic classification potential, opening opportunities for new investigations into these aggressive cancers.

Role of polarisation in automatic target recognition using resonance descriptions

The role of polarisation in late time complex resonance based target identification is investigated numerically for the case of an L-shaped wire. While repeated extraction of the resonances for varying polarisation allows for better signal-to-noise immunity, it is also found that there are preferred polarisations for each complex resonance. The first few of these polarisations are extracted for the sample target.

Automatic message handling for a national counselling service

An automatic email handling system (AutoRouter) was introduced at a national counselling service in Australia. In 2003, counsellors responded to a total of 7421 email messages. Over nine days in early May 2004 the administrator responsible for the management of the manual email counselling service recorded the time spent on managing email messages. The AutoRouter was then introduced. Since the implementation of the AutoRouter the administrator's management role has become redundant, an average of 12 h 5 min per week of staff time has been saved. There have been further savings in supervisor time. Counsellors were taking an average of 6.2 days to respond to email messages (n=4307), with an average delay of 1.2 days from the time counsellors wrote the email to when the email was sent. Thus the response was sent on average 7.4 days after receipt of the original client email message. A significant decrease in response time has been noted since implementation of the AutoRouter, with client responses now taking an average of 5.4 days, a decrease of 2.0 days. Automatic message handling appears to be a promising method of managing the administration of a steadily increasing email counselling service.

Automatic building detection using the Dempster-Shafer algorithm

An approach and strategy for automatic detection of buildings from aerial images using combined image analysis and interpretation techniques is described in this paper. It is undertaken in several steps. A dense DSM is obtained by stereo image matching and then the results of multi-band classification, the DSM, and Normalized Difference Vegetation Index (NDVI) are used to reveal preliminary building interest areas. From these areas, a shape modeling algorithm has been used to precisely delineate their boundaries. The Dempster-Shafer data fusion technique is then applied to detect buildings from the combination of three data sources by a statistically-based classification. A number of test areas, which include buildings of different sizes, shape, and roof color have been investigated. The tests are encouraging and demonstrate that all processes in this system are important for effective building detection.

Automatic measurement of vertebral rotation in idiopathic scoliosis

Study Design. Development of an automatic measurement algorithm and comparison with manual measurement methods. Objectives. To develop a new computer-based method for automatic measurement of vertebral rotation in idiopathic scoliosis from computed tomography images and to compare the automatic method with two manual measurement techniques. Summary of Background Data. Techniques have been developed for vertebral rotation measurement in idiopathic scoliosis using plain radiographs, computed tomography, or magnetic resonance images. All of these techniques require manual selection of landmark points and are therefore subject to interobserver and intraobserver error. Methods. We developed a new method for automatic measurement of vertebral rotation in idiopathic scoliosis using a symmetry ratio algorithm. The automatic method provided values comparable with Aaro and Ho's manual measurement methods for a set of 19 transverse computed tomography slices through apical vertebrae, and with Aaro's method for a set of 204 reformatted computed tomography images through vertebral endplates. Results. Confidence intervals (95%) for intraobserver and interobserver variability using manual methods were in the range 5.5 to 7.2. The mean (+/- SD) difference between automatic and manual rotation measurements for the 19 apical images was -0.5 degrees +/- 3.3 degrees for Aaro's method and 0.7 degrees +/- 3.4 degrees for Ho's method. The mean (+/- SD) difference between automatic and manual rotation measurements for the 204 endplate images was 0.25 degrees +/- 3.8 degrees. Conclusions. The symmetry ratio algorithm allows automatic measurement of vertebral rotation in idiopathic scoliosis without intraobserver or interobserver error due to landmark point selection.

Automatic texture segmentation for texture-based image retrieval

Texture-segmentation is the crucial initial step for texture-based image retrieval. Texture is the main difficulty faced to a segmentation method. Many image segmentation algorithms either can’t handle texture properly or can’t obtain texture features directly during segmentation which can be used for retrieval purpose. This paper describes an automatic texture segmentation algorithm based on a set of features derived from wavelet domain, which are effective in texture description for retrieval purpose. Simulation results show that the proposed algorithm can efficiently capture the textured regions in arbitrary images, with the features of each region extracted as well. The features of each textured region can be directly used to index image database with applications as texture-based image retrieval.