The application of identification methods in the U.S.S.R.—A survey

The paper is an attempt to describe the use of identification methods in the U.S.S.R. where these develop and extend at a rate comparable to that of the rest of the world. Therefore complete coverage seems to be impossible in one article. Furthermore, many of the methods used in the U.S.S.R. were described in surveys presented to preceding IFAC Congresses and Symposia. Therefore attention is focused on methods which have not been adequately covered in those papers. Relatively much attention is given to adaptive, dispersional, ‘standard’ and distributed models. The essence of each method is described in brief and actual plants are listed where these methods are applied. References are made to papers which describe these methods in more detail. The final part of the paper is a very brief account of other kinds of models and their application.     

Acoustic and radio-acoustic remote sensing studies in C.I.S. (Former U.S.S.R,)-current status

This paper presents brief review of studies carried out in the U.S.S.R. from about 1940 to 1960, which serve as the basis for methods of probing the atmosphere by directed sound waves. The remote sensing techniques developed in the U.S.S.R. are described. A summary of some theoretical and experimental results, as well as the results of applying the sodars and rasdars (RASS) to studies of the atmospheric boundary layer in the 1980s are also given     

VLSI research in the U.S.A.

Co-operative R&D in Advanced Information Technologies is not a Japanese privilege.     

Machine translation and the SYGMART system

Language Resources and Evaluation -     

Forecasting the consumption of gasoline in the U.S.

The scarce oil situation in the 1970s gave rise to pressures to improve the Miles per Gallon efficiency of the U.S. car fleet. Responding to that pressure, at least one Corporate Strategic Planning group modeled forecasted U.S. gasoline consumption for personal vehicles. The pattern for the usage of U.S. gasoline usage was shown to decline through the year 2000, if current trends continued. Current rumors of the U.S. government's intention to again target the automobile led the authors to revisit that analysis with the intention of making the findings public.

This paper updates this model to show U.S. gasoline consumption patterns through the year 2002.     

Are You Listening to Your Spanish Speakers? How Spanish Speakers in the U.S. Say U.S. Addresses

This work presents research analyzing the structure of how U.S. addresses are spoken by Spanish speakers living in the U.S. The findings, based on live-call recordings of Spanish speakers interacting with call center agents, reveal that an English-like format with the street number spoken before the street name was used in 91% of the cases, even though the street number was said in Spanish 100% of the time. How audio prompt wording can be used to influence the way addresses are spoken and also how street names consisting of numbers are said are possible areas for future study. In addition, some best practices related to dialog design for bilingual Spanish-English speech recognition applications are also revealed during this study.     

美国电子政务E-Authentication介绍与分析

文章对E-Authentication进行了分析讨论,指出其存在的一些问题及可以采用的相应解决方案。     

Computer applications in U.S. law enforcement

The article is based partially on findings of a completed study assessing the status and impact of computer applications in U.S. law enforcement. Inasmuch as the applications have been most significant in the police, command, control, and communications (PCCC) area, the article focuses on the PCCC technologies of nine-one-one, computer-aided dispatch, automatic vehicle monitoring, mobile digital communications, and management information systems. In particular, the article reviews the nature of these PCCC applications, especially in terms of the police functions they are intended to impact and the objectives they are intended to achieve; assesses the current status and actual impact of these applications; and outlines areas where further considerations are required.     

Machine translation inching toward human quality

The goal of reaching near-human quality translation probably depends on some degree of pre- and post-editing for years to come. But, the growing number of global corporations (such as Philips, Samsung, and HP) and international agencies and institutions (such as the UN and the European Commission) using the technology illustrates that machine translation - the first nonnumerical application of AI - is finally delivering practical solutions. Popular perception of MT has suffered from low-quality "gisting" translation that Web-based translation engines, such as Babelfish and other online services, generate. But MT engines designed for limited domains, and tailor-made systems that use controlled language, are already delivering services.     

美国军用自动测试系统的发展趋势

在总结美国军用自动测试系统发展现状的基础上,针对美国国防部提出的军用自动测试系统体系结构,重点分析了下一代军用测试系统研制方向,所涉及的国际标准和关键技术。     

Machine translation evaluation versus quality estimation

Most evaluation metrics for machine translation (MT) require reference translations for each sentence in order to produce a score reflecting certain aspects of its quality. The de facto metrics, BLEU and NIST, are known to have good correlation with human evaluation at the corpus level, but this is not the case at the segment level. As an attempt to overcome these two limitations, we address the problem of evaluating the quality of MT as a prediction task, where reference-independent features are extracted from the input sentences and their translation, and a quality score is obtained based on models produced from training data. We show that this approach yields better correlation with human evaluation as compared to commonly used metrics, even with models trained on different MT systems, language-pairs and text domains.     

Machine translation between Hebrew and Arabic

Hebrew and Arabic are related but mutually incomprehensible languages with complex morphology and scarce parallel corpora. Machine translation between the two languages is therefore interesting and challenging. We discuss similarities and differences between Hebrew and Arabic, the benefits and challenges that they induce, respectively, and their implications on machine translation. We highlight the shortcomings of using English as a pivot language and advocate a direct, transfer-based and linguistically-informed (but still statistical, and hence scalable) approach. We report preliminary results of the two systems we are currently developing, for translation in both directions.