A FPGA system for QRS complex detection based on Integer Wavelet Transform

Due to complexity of their mathematical computation, many QRS detectors are implemented in software and cannot operate in real time. The paper presents a real-time hardware based solution for this task. To filter ECG signal and to extract QRS complex it employs the Integer Wavelet Transform. The system includes several components and is incorporated in a single FPGA chip what makes it suitable for direct embedding in medical instruments or wearable health care devices. It has sufficient accuracy (about 95%), showing remarkable noise immunity and low cost. Additionally, each system component is composed of several identical blocks/cells what makes the design highly generic. The capacity of today existing FPGAs allows even dozens of detectors to be placed in a single chip. After the theoretical introduction of wavelets and the review of their application in QRS detection, it will be shown how some basic wavelets can be optimized for easy hardware implementation. For this purpose the migration to the integer arithmetic and additional simplifications in calculations has to be done. Further, the system architecture will be presented with the demonstrations in both, software simulation and real testing. At the end, the working performances and preliminary results will be outlined and discussed. The same principle can be applied with other signals where the hardware implementation of wavelet transform can be of benefit

Real-time grammar processing by native and non-native speakers : constructions unique to the second language

We investigated second language (L2) comprehension of grammatical structures that are unique to the L2, and which are known to cause persistent difficulties in production. A visual-world eye-tracking experiment focused on online comprehension of English articles by speakers of the article-lacking Mandarin, and a control group of English native speakers. The results show that non-native speakers from article-lacking backgrounds can incrementally utilise the information signalled by L2 articles in real time to constrain referential domains and resolve reference more efficiently. The findings support the hypothesis that L2 processing does not always over-rely on pragmatic affordances, and that some morphosyntactic structures unique to the target language can be processed in a targetlike manner in comprehension – despite persistent difficulties with their production. A novel proposal, based on multiple meaning-to-form, but consistent form-to-meaning mappings, is developed to account for such comprehension–production asymmetries

Customer Churn Prediction in B2B Non-Contractual Business Settings Using Invoice Data

Customer churn is a problem virtually all companies face, and the ability to predict it reliably can be a cornerstone for successful retention campaigns. In this study, we propose an approach to customer churn prediction in non-contractual B2B settings that relies exclusively on invoice-level data for feature engineering and uses multi-slicing to maximally utilize available data. We cast churn as a binary classification problem and assess the ability of three established classifiers to predict it when using different churn definitions. We also compare classifier performance when different amounts of historical data are used for feature engineering. The results indicate that robust models for different churn definitions can be derived by using invoice-level data alone and that using more historical data for creating some of the features tends to lead to better performing models for some classifiers. We also confirm that the multi-slicing approach to dataset creation yields better performing models compared to the traditionally used single-slicing approach

Machiavellian males with high emotional intelligence exhibit fewer depressive symptoms

Research on the link between Machiavellianism and depression has yielded equivocal results. In this study, we examined the possible moderating role of ability emotional intelligence (a-EI) on the Machiavellianism-depression relationship. a-EI was approached as a factor influencing the effectiveness of Machiavellians' manipulative strategies. A total of 469 participants were recruited (34% male; mean age: 42.37). Machiavellian dispositions were assessed with the Machiavellianism subscale of the Dirty Dozen. a-EI was measured with the 10-scenario version of the Geneva EMOtion Knowledge-Blends—a performance-based test. Depressive symptoms were evaluated with the PHQ-9, a scale covering both cognitive-affective and somatic aspects of depression. Correlational analyses revealed no raw association between Machiavellianism, a-EI, and depression. In men, a-EI was found to moderate the effect of Machiavellianism on depression in such a way that Machiavellianism was protective against depressive symptoms when coupled with high a-EI. Component-level analyses indicated that the observed interaction was essentially underpinned by somatic depression. Machiavellianism predicted somatic depression negatively in males with high a-EI and positively in males with low a-EI. No association was identified in females. This study suggests that Machiavellianism is not depressogenic in itself. Remarkably, Machiavellianism might have antidepressant virtues in men exhibiting high a-EI