Well-formedness judgment: A comparison of offline and online performance in Broca's aphasics

0na eg rcarmitimcaal tfieca tcuorem opfr ethhee nospieornat iodneafli cdietf i(nAitiCoDn )o ft hthaet frequently co-occurs with Broca’s aphasia is above-chance performance on well-formedness judgment tasks for many syntactic constructions, but impaired performance where syntactic binding of traces to their antecedents occurs. However, the methodologies used to establish this aspect of the performance profile of the ACD have been predominantly offline. Offline well-formedness tasks entail extralinguistic processing (e.g. perception, attention, short-term memory, conscious reflection) in varying amounts and the influence of such processes on parsing mechanisms is yet to be fully established. In order to (a) further understand the role of extra-linguistic processing on parsing, and (b) gain a more direct insight into the online nature of parsing in Broca’s aphasia, 8 subjects underwent a series of wellformedness judgment investigations using both offline and online test batteries. The sentence types and error types used were motivated by three current theories about the nature of the ACD, namely, the Trace-Based Account (Grodzinsky, 2000), the Mapping Hypothesis (Linebarger et al., 1983) and Capacity proposals (e.g. Frazier & Friederici, 1991). The results from the present investigation speak directly to the three aforementioned theories and also demonstrate the important role that extralinguistic processing plays during offline assessment. The clinical implications of the different outcomes from the offline vs. online tasks are also discussed.

The Brazilian Business World: the difficult adaptation to globalization

The article deals with the internationalization of Brazilian businesses in the current decade. In the 1990s, Brazil embraced economic neoliberalism and promoted a huge opening up of its economy. At that time, Brazilian companies had to adapt rapidly. Twenty years later, the country has reinforced its presence in Latin America and has ensured a better position in the global markets, especially by through agricultural exports.

A mobile health care rule-based system

The relation between patient and physician in most modern Health Care Sys- tems is sparse, limited in time and very in exible. On the other hand, and in contradiction with several recent studies, most physicians do not rely their patient diagnostics evaluations on intertwined psychological and social nature factors. Facing these problems and trying to improve the patient/physician relation we present a mobile health care solution to im- prove the interaction between the physician and his patients. The solution serves not only as a privileged mean of communication between physicians and patients but also as an evolutionary intelligent platform delivering a mobile rule based system.

On the discovery of business processes orchestration patterns

COORDINSPECTOR is a Software Tool aiming at extracting the coordination layer of a software system. Such a reverse engineering process provides a clear view of the actually invoked services as well as the logic behind such invocations. The analysis process is based on program slicing techniques and the generation of, System Dependence Graphs and Coordination Dependence Graphs. The tool analyzes Common Intermediate Language (CIL), the native language of the Microsoft .Net Framework, thus making suitable for processing systems developed in any .Net Framework compilable language. COORDINSPECTOR generates graphical representations of the coordination layer together with business process orchestrations specified in WSBPEL 2.0

The perceived potential of business social networking sites

Business social networking is a facilitator of several business activities, such as market studies, communication with clients, and identification of business partners. This paper traduces the results of a study undertaken with the purpose of getting to know how the potential of networking is perceived in the promotion of business by participants of the LinkedIn network, and presents two main contributions: (1) to disseminate within the business community which is the relevance given to social networking; and (2) which are the social networks best suitable to the promotion of business, to support the definition of strategies and approaches accordingly. The results confirm that LinkedIn is the most suitable network to answer the needs of those that look for professional contacts and for the promotion of business, while innovation is the most recognized factor in the promotion of business through social networking. This study contributes to a better understanding of the potential of different business social networking sites, to support organizations and professionals to align their strategies with the perceived potential of each network.

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

“Enriquecimento Injustificado”: simples ignorância ou disparatada incompetência?

Pelos fundamentos expostos no Acórdão nº 377/2015, de 27/7, o T.C. decidiu pronunciar-se pela inconstitucionalidade das normas constantes do n.º 1 do artigo 1º e do artigo 2º do Decreto da Assembleia da República nº 369/XII, por violação dos artigos 18º/2 (necessidade, adequação, proporcionalidade e intervenção mínima do Direito Criminal/Penal), 29º/1 (Princípio da Legalidade Criminal) e 32º/2 (Presunção da Inocência) da Constituição. Imagine-se que depois de se ser condenado pela Comunicação Social, ainda temos que provar a nossa inocência! § On those grounds in Judgment No 377/2015 of 27/7, the Constitutional Court decided to rule the unconstitutionality of the rules in paragraph 1 of Article 1 and Article 2 of Decree of the National Assembly No. 369 / XII, for violation of articles 18/2 (necessity, appropriateness, proportionality and minimum intervention of Criminal Law / Criminal), 29/1 (Principle of Criminal Legality) and 32/2 (Presumption of Innocence) of the Constitution. Imagine that after being convicted by the Social Communication, we still have to prove our innocence!

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.