Sequential fixed-point ICA based on mutual information minimization

A new gradient technique is introduced for linear independent component analysis (ICA) based on the Edgeworth expansion of mutual information, for which the algorithm operates sequentially using fixed-point iterations. In order to address the adverse effect of outliers, a robust version of the Edgeworth expansion is adopted, in terms of robust cumulants, and robust derivatives of the Hermite polynomials are used. Also, a new constrained version of ICA is introduced, based on goal programming of mutual information objectives, which is applied to the extraction of the antepartum fetal electrocardiogram from multielectrode cutaneous recordings on the mother's thorax and abdomen.     

Universities in Evolutionary Systems of Innovation

This paper criticizes the current narrow view on the role of universities in knowledge‐based economies. We propose to extend the current policy framework of universities in national innovation systems (NIS) to a more dynamic one, based on evolutionary economic principles. The main reason is that this dynamic view fits better with the practice of innovation processes. We contribute on ontological and methodological levels to the literature and policy discussions on the effectiveness of university‐industry knowledge transfer and the third mission of universities. We conclude with a discussion of the policy implications for the main stakeholders.     

Design of neural network-based estimator for tool wear modeling in hard turning

Hard turning with cubic boron nitride (CBN) tools has been proven to be more effective and efficient than traditional grinding operations in machining hardened steels. However, rapid tool wear is still one of the major hurdles affecting the wide implementation of hard turning in industry. Better prediction of the CBN tool wear progression helps to optimize cutting conditions and/or tool geometry to reduce tool wear, which further helps to make hard turning a viable technology. The objective of this study is to design a novel but simple neural network-based generalized optimal estimator for CBN tool wear prediction in hard turning. The proposed estimator is based on a fully forward connected neural network with cutting conditions and machining time as the inputs and tool flank wear as the output. Extended Kalman filter algorithm is utilized as the network training algorithm to speed up the learning convergence. Network neuron connection is optimized using a destructive optimization algorithm. Besides performance comparisons with the CBN tool wear measurements in hard turning, the proposed tool wear estimator is also evaluated against a multilayer perceptron neural network modeling approach and/or an analytical modeling approach, and it has been proven to be faster, more accurate, and more robust. Although this neural network-based estimator is designed for CBN tool wear modeling in this study, it is expected to be applicable to other tool wear modeling applications.     

Architectures for Fast Transcoding of H.264/AVC to Quality-Scalable SVC Streams

The scalable extension of H.264/AVC (SVC) was recently standardized, and offers scalability at a minor penalty in rate-distortion efficiency when compared to single-layer H.264/AVC coding. In SVC, a scaled version of the original video sequence can easily be extracted by dropping layers from the stream. However, most of the video content nowadays is still produced in a single-layer format. While decoding and reencoding is a possible solution to introduce scalability in the existing bitstreams, this is an approach which requires a tremendous amount of time and effort. In this paper, we show that transcoding can be used to intelligently derive scalable bitstreams from existing single-layer streams. We focus on SNR scalability, and introduce techniques that are able to create multiple quality layers in the bitstreams. We also discuss bitstream rewriting from SVC to H.264/AVC, and examine how our newly proposed architectures can benefit from the changes that were introduced for bitstream rewriting. Architectures with different rate distribution flexibility and computational complexity are discussed. Rate-distortion performance of transcoding is shown to be comparable to that of reencoding at a fraction of the time needed for the latter.     

Effectiveness of participatory ergonomic interventions on health outcomes: a systematic review

The objective of this study was to conduct a systematic review of the literature on the effectiveness of participatory ergonomic (PE) interventions for improving workers' health. The search strategy targeted six electronic databases and identified 442 potential articles. Each article was examined by pairs of reviewers for relevance (assessed a participative ergonomic workplace intervention, with at least one health outcome, published in English in peer reviewed literature). Twenty-three articles met relevance criteria and were then appraised for methodological strength. Using a best evidence synthesis approach, 12 studies that were rated as 'medium' or higher provided partial to moderate evidence that PE interventions have a positive impact on: musculoskeletal symptoms, reducing injuries and workers' compensation claims, and a reduction in lost days from work or sickness absence. However, the magnitude of the effect requires more precise definition.     

Thermal efficiency of manifold-heat-pipe heat exchangers

The thermal efficiency of manifold-heat-pipe heat exchangers is considered. A method for predicting the efficiency and an analysis of effects of various factors of the actual process are presented.Academic Scientific Complex A. V. Luikov Heat and Mass Transfer Institute of the Academy of Sciences of Belarus, Minsk. Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 66, No. 2, pp. 173–178, February, 1994.     

Cognitive distortions and adolescent affective disorder. Validity of the CNCEQ in an inpatient sample. Children's Negative Cognitive Error Questionnaire

Despite a proliferation of recent research examining childhood and adolescent depression, the area still lags behind the adult depression field, particularly in the investigation of cognitive correlates of affective psychopathology. To advance cognitive research with youth, the Children's Negative Cognitive Error Questionnaire (CNCEQ) was developed to provide a measure of cognitive distortions or errors in children and adolescents. Yet, few studies have employed the CNCEQ and no evidence exists supporting the validity of its four component cognitive error scales. The purpose of the present study was to examine the construct validity of the CNCEQ and its constituent scales through the use of factor analysis and criterion-group comparisons. Groups of adolescent psychiatric inpatients, diagnosed as affective or disruptive disordered, completed the CNCEQ following admission. Results failed to support the implicit four-factor structure of the CNCEQ, instead suggesting the appropriateness of a single-factor solution labeled "negative thinking." Despite no diagnostic group differences on the CNCEQ total or other scale scores, affective disordered patients evinced more cognitive errors on the Overgeneralizing scale. Findings suggest that the CNCEQ in its current stage of development holds promise, yet requires refinement to produce a valid measure of cognitive functioning in youth.     

The effects of smoking schedules on cessation outcome: can we improve on common methods of gradual and abrupt nicotine withdrawal?

This study compared the efficacy of 2 traditional methods of smoking cessation, gradual reduction and "cold turkey," with a new approach involving variation in the intercigarette interval. One hundred twenty-eight participants quit smoking on a target date, after a 3-week period of (a) scheduled reduced smoking (progressive increase in the intercigarette interval), (b) nonscheduled reduced smoking (gradual reduction, no specific change in the intercigarette interval), (c) scheduled nonreduced smoking (fixed intercigarette interval, no reductions in frequency), or (c) nonscheduled nonreduced smoking (no change in intercigarette interval or smoking frequency). Participants also received cognitive-behavioral relapse prevention training. Abstinence at 1 year averaged 44%, 18%, 32%, and 22% for the 4 groups, respectively. Overall, the scheduled reduced group performed the best and the nonscheduled reduced group performed the worst. Both scheduled groups performed better than nonscheduled ones. Scheduled reduced smoking was associated with reduced tension, fatigue, urges to smoke, withdrawal symptoms, increased coping effort (ratio of coping behavior to urges), and self-efficacy, suggesting an improved adaptation to nonsmoking and reduced vulnerability to relapse.