Language engineering - a champion for European culture

Language is key to culture. It is a direct cultural medium as well as a means of recording and providing access to non-lingual elements of culture. Language is also fundamental to a sense of cultural identity. For this reason, it is vital, in a changing Europe, that we preserve the multi-lingual character of our society in order to move successfully towards closer co-operation at a political, economic, and social level. Language engineering is the application of knowledge of language to the development of computer software which can recognise, understand, interpret, and generate human language in all its forms. The paper provides a high level view of the ‘state of the art’ in language engineering and indicates ways in which it will have a profound impact on our culture in the future. It shows how advances in language engineering are an important aid in maintaining cultural diversity in a multi-lingual European society, while enabling the development of social cohesion across cultural and national divides. It addresses issues raised by the prospect of the Multi-lingual Information Society, including education, human communication with technology and information management, as well as aspects of digital cities such as tele-presence in digital libraries, virtual art galleries and electronic museums. The paper raises the issue of language as a factor in cultural domination, showing the contribution that language engineering can make towards countering it. The paper also raises a number of controversial issues concerning the likely benefits arising from the ways in which language is likely to influence the culture of Europe

Security of Tenure and Land Registration in Africa: Literature Review and Synthesis

In 1984, the Land Tenure Center embarked on a project to evaluate the experiences with land registration and tenure reform in Africa. The goal was to determine is African states been able to use tenure reform and land registration to provide greater security of tenure than was available through customary tenure systems. Donor agencies focused attention on the creation of individual freehold title, emphasizing the heightened security of holding, marketability, and access to credit under such tenure. National governments, on the other hand, were more concerned to see that land was used productively rather than merely accumulated for purposes of prestige or inheritance or as a hedge against inflation, and for this reason have tended to favor granting more circumscribed rights, such as leaseholds or rights of occupancy. This literature review and synthesis was prepared as part of an effort to increase very substantially our knowledge, especially on a quantitative level, of tenure and development relationships in Africa. The literature review is an attempt to gather in one place data about the diverse efforts at land registration and to describe briefly for each country the various registration programs that have taken place (if any), why they were undertaken, and what subsequent studies of these programs have found. Among other things, it will be seen that the intended benefits, and beneficiaries, of land registration have changed over the century or so since the first systems were put in place. In addition to these variations over time, there are also differences among Anglophone, Francophone, and Lusophone countries, differences that not only influenced the structure of registration systems established during the colonial era, but also continue to inform the kinds of registration systems adopted today.Land Economics/Use,

Service operations in DMV (division of motor vehicles) offices of the USA - a comparative study

Purpose: Division of motor vehicle (DMV) offices serve a wide swath of Americans in all states and can therefore serve as excellent vehicles to study the quality of public services in the country. However, relatively little attention has been devoted in the academic literature to studying operations in DMV offices, especially as it relates to service quality and productivity. In an attempt to address the same, this paper aims to present the results of a study of DMV offices across the USA through a nationwide survey about vehicle titling and registration services, that received response from 31 of the 50 states and District of Columbia. Design/methodology/approach: The authors use a mixed methods approach – a sequential unequal weight mixed methods approach starting with a quantitative analysis of DMV operational data followed by a qualitative case study approach. The primary data collected for this study were with a nationwide survey of the highest DMV office in each state, conducted through the American Association of Motor Vehicle Administrators. Out of the 50 states, 31 states and District of Columbia responded to the survey. In addition to descriptive statistical analysis performed to glean nationwide findings, Data Envelopment Analysis was used to determine efficiency of operations. Finally, extensive in-person interviews with senior managers of DMV offices in Ohio and Indiana were conducted to get more in-depth information for case studies and identification of best practices. Findings: States exhibit significant variations in labor and capital productivity and based on Data Envelopment Analysis, Texas and Minnesota DMVs are the most efficient in terms of using their labor and capital inputs to maximize the number of transactional services rendered. The authors also find that while operational performance of vehicle titling and registration services is monitored by most DMV offices across the nation, assessment of customer satisfaction received much less attention. Among the states that do well on both are Indiana and Ohio; the case studies presented based on interviews with their officials that also identify best practices. Research limitations/implications: This research was limited to the USA as are its findings. Additionally, it focuses only on vehicle titling and registration at DMV offices because that represents the bulk of services performed by a DMV and the output is standard across all states. Nonetheless, a future study should be extended to other DMV services. Practical implications: Given the finding that assessment of customer satisfaction is not widely practiced in DMV offices, DMV officials should address this by putting appropriate systems in place. Additionally, practitioners and state officials can use the findings of this study to develop best practices for their operations and also determine the most appropriate ways to structure the provision of those services that result in enhanced efficiencies and customer satisfaction. Social implications: DMV services are among the most widely used services offered by the government in the USA and the overall size and scope of services provided by them across the country is immense. Thus, any improvements in productivity and service quality has significant implications in terms of improving public satisfaction with government services. Originality/value: To the best of our knowledge, this represents the first nationwide comparative study of DMV offices in the USA that focuses on service quality and analyzes productivity across the states. Additionally, the case study provided at the end of the paper identifies best practices from two states that have received national recognition for service quality which could be adopted by all DMV offices across the USA. The findings also conform/strengthen numerous hypotheses espoused in existing models and theories from service operations literature by providing evidence in their favor

Special Libraries, May-June 1937

Volume 28, Issue 5https://scholarworks.sjsu.edu/sla_sl_1937/1004/thumbnail.jp

Automatic Quality Estimation for ASR System Combination

Recognizer Output Voting Error Reduction (ROVER) has been widely used for system combination in automatic speech recognition (ASR). In order to select the most appropriate words to insert at each position in the output transcriptions, some ROVER extensions rely on critical information such as confidence scores and other ASR decoder features. This information, which is not always available, highly depends on the decoding process and sometimes tends to over estimate the real quality of the recognized words. In this paper we propose a novel variant of ROVER that takes advantage of ASR quality estimation (QE) for ranking the transcriptions at "segment level" instead of: i) relying on confidence scores, or ii) feeding ROVER with randomly ordered hypotheses. We first introduce an effective set of features to compensate for the absence of ASR decoder information. Then, we apply QE techniques to perform accurate hypothesis ranking at segment-level before starting the fusion process. The evaluation is carried out on two different tasks, in which we respectively combine hypotheses coming from independent ASR systems and multi-microphone recordings. In both tasks, it is assumed that the ASR decoder information is not available. The proposed approach significantly outperforms standard ROVER and it is competitive with two strong oracles that e xploit prior knowledge about the real quality of the hypotheses to be combined. Compared to standard ROVER, the abs olute WER improvements in the two evaluation scenarios range from 0.5% to 7.3%

Gender in Agriculture Sourcebook

The purpose of the Sourcebook is to act as a guide for practitioners and technical staff in addressing gender issues and integrating gender-responsive actions in the design and implementation of agricultural projects and programs. It speaks not with gender specialists on how to improve their skills but rather reaches out to technical experts to guide them in thinking through how to integrate gender dimensions into their operations. The Sourcebook aims to deliver practical advice, guidelines, principles, and descriptions and illustrations of approaches that have worked so far to achieve the goal of effective gender mainstreaming in the agricultural operations of development agencies. It captures and expands the main messages of the World Development Report 2008: Agriculture for Development and is considered an important tool to facilitate the operationalization and implementation of the report's key principles on gender equality and women's empowerment

Trending topic extraction from social media

Social media has become the first source of information for many people. The amount of information posted on social media daily has become very vast that it became difficult to track. One of the most popular social media applications is Twitter. Users follow lots of news accounts, public figures, and their friends so they can be updated by the latest events around them. Since the dialect language and the style of writing differ from a region to another, our objective in this research is to extract trending topics for an Egyptian twitter user. In this way, the user can easily get at a glimpse of the trending topics discussed by the people he follows. To find the best approach achieving our objective, we investigate the document pivot and the feature pivot approaches. By applying the document pivot approach on the baseline data using tf-itf (term frequency-inverse tweet frequency) representation, repeated bisecting k-means clustering technique and extracting most frequent n-grams from each cluster we could achieve a recall value of 100% and F1 measure of 0.8. The application of the feature pivot approach on the baseline data using the content similarity algorithm to group related unigrams together, could achieve a recall value of 100% and F1 measure of 0.923. To validate our results we collected 12 different data sets of different sizes (200, 400, 600, and 1200) and from three different domains (sports, entertainment, and news) then applied both approaches to them. The average recall, precision and F1 measure values resulted from applying the feature pivot approach are larger than those achieved by applying the document pivot approach. To make sure this difference in results is statistically significant we applied the Two-sample one-tailed paired significance t-test that showed the results are significantly better at confidence interval of 90% The results showed that the document pivot approach could extract the trending topics for an Egyptian twitter user with an average recall value of 0.714, average precision value of 0.521, and average F1 measure value of 0.556 versus average recall, precision and F1 measure values of 0.981, 0.754, and 0.833 respectively, when applying the feature pivot approach. â€