Forecasting the United States gross domestic product with a neural network

Forecasting the Gross Domestic Product (GDP) of the United States is one of many estimates to predict the economic health of the country. Current forecasting techniques use consensus estimates of experts, econometric models, or other statistical methods. Relatively little research has been devoted to how artificial neural networks may improve these forecasts, however. This paper describes how a neural network using leading economic indicator data predicted annual GDP percentage changes one year into thefiiture more accurately than competing techniques over a ten-year period

Brainwriting in virtual legislative sessions

Many studies have demonstrated the efficiency and effectiveness of using group support systems in large, face-to-face meetings known as legislative sessions. However, few have investigated how individual participants or sub-groups in different rooms linked via a computer network, forming a virtual group, may use the systems. An experiment using two sizes of virtual groups (8 and 16 participants) showed that participants were satisfied with the meeting process. In addition, there were no significant differences in five process and outcome variables between the two sizes of groups, indicating that an upper limit on the size of the virtual groups had not been reached

A neural network to predict civilian unemployment rates

Forecasting national unemployment is one of the most important problems of modern economies, and most researchers have relied upon statistical techniques with their stringent data assumptions and low accuracy rates to predict changes in this macroeconomic data. This paper describes how a neural network using leading economic indicator data can help to predict civilian unemployment rates. Results show that the neural network provides superior estimates of rates one month into the future compared to multi-linear regression and two naive forecasting techniques

An Updated Evaluation of Google Translate Accuracy

In 2011, a comprehensive evaluation of accuracy using 51 languages with Google Translate showed that many European languages had good results, but several Asian languages performed poorly. The online service has improved its accuracy over the intervening eight years, and a reevaluation using the same text as the original study shows a 34% improvement based upon BLEU scores. This new study shows that translations between English and German, Afrikaans, Portuguese, Spanish, Danish, Greek, Polish, Hungarian, Finnish, and Chinese tend to be the most accurate

Transterpreting Multilingual Electronic Meetings

Communicating in a non-native language during a traditional, oral meeting is difficult, but a Group Support System (GSS) along with online machine translation (MT) can increase the efficiency and effectiveness of the discussion. An experimental study shows that a group facilitator can use a Web-based translation service to support a multilingual meeting, but completely automated language support is likely to be more efficient for large groups.

The Temporal Dimension of Electronic Meetings: A Study of Synchronous and Asynchronous Idea Generation

Electronic meeting systems can increase the efficiency and effectiveness of group discussions, but relatively little research has investigated use of the technology in asynchronous environments. In this study, five groups of 10 students participated in synchronous legislative sessions and five groups of 10 met in asynchronous settings. Results showed that there were no differences in meeting process satisfaction, production blocking, evaluation apprehension, and total and relevant comments generated, but synchronous groups believed there was more participation and were more satisfied with the comments. Although there could be less feeling of social presence, use of asynchronous, distributed meetings might become more prevalent as groups seek to reduce travel

The effect of anonymity on electronic meetings

The use of anonymity has been attributed to be a major factor in the success of electronic meetings, contributing to greater participation, more and better comments, and higher satisfaction. Several studies have attempted to measure its affect on meetings, but none has investigated non-anonymous, pseudo-anonymous, and anonymous treatments in the same experiment. A study using these three types of groups in electronic meetings to discuss a relatively noncontroversial topic revealed no statistically significant difference in the number of comments generated per person, level of process satisfaction, and other self-perceived measures

Machine Translation in a Multilingual Electronic Meeting

Electronic meetings can be more efficient and effective than traditional, oral discussions, but until only recently, groups with no common language could not benefit from machine translation. Although it is possible for linguists or other staff members using machines to translate comments during a multilingual discussion, the research presented here shows that this is not feasible for large groups speaking many languages. As a solution, we propose a fully automated multilingual meeting system, and an example of its use in a meeting with Chinese, Korean, and English comments shows its potential to reduce multinational communication barriers

Likelihood of Purchase On-Line: Reliability, Security, and Design

Several factors can influence a consumer\u27s likelihood of purchasing on the Web including trust, ease-of-use, and price discounts. This study examines over a dozen different variables that affect the decision to conduct business online. A survey of experienced Web users validated that poor design, security, and reliability tend to decrease a person\u27s willingness to purchase through the Web

Comment Distribution in Electronic Poolwriting and Gallery Writing Meetings

Two types of electronic brainwriting are used typically in Group Support Systems research: poolwriting and gallery writing. While a large number of academic studies have used the former technique, the latter is more efficient and effective, but has been used less frequently. This paper describes these two group idea generation techniques and discusses prior comparison studies. An experiment using the two brainwriting techniques shows that subjects were more satisfied with and preferred gallery writing. In addition, subjects using poolwriting were able to see only about 50% of the comments generated in the electronic meeting, while gallery writing subjects were able to view all comments