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Software evolution has been extensively studied in the past decade for various properties and interesting patterns. In this work, we study the effect of evolution on branch prediction techniques. Typically for any program, at the hardware level, all dynamic branch prediction strategies learn the branch behaviors at run time and later re-use them to predict the direction of future branches. The duration...
Prior research in neutrally-inspired perceptron predictors and Geometric History Length-based TAGE predictors has shown significant improvements in branch prediction accuracy by exploiting correlations in long branch histories. However, not all branches in the long branch history provide useful context. Biased branches resolve as either taken or not-taken virtually every time. Including them in the...
In this paper, we present a novel self-maintaining, domain-independent, and context-sensitive Sentiment Lexicon (SL) which finds and maps opinion words and phrases to a fuzzy sentiment score ranging from strong negative to strong positive. We show that our automatically built SL has advantage over other already existing lexicons in various aspects, namely, reducing the number of word false-matches...
Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) is a sleep related breathing disorder that has important consequences in the health and development of infants and young children. To enhance the early detection of OSAHS, we propose a methodology based on automated analysis of nocturnal blood oxygen saturation (SpO2) from respiratory polygraphy (RP) at home. A database composed of 50 SpO2 recordings...
SemioTag is an approach towards tagging that utilizes the semiotic sign categories icon, index, and symbol as classification structures to be used by users during the annotation and search of images within social media-oriented repositories. We compared the influence of this approach on the tagging and querying behaviour of users, with respect to usability, efficiency, and user experience, between...
In view of extreme points of the Delphi method, this paper introduces the penalty factor to improve it and overcome the influence of subjective factors. Then, it applies the improved Delphi method to determine weight factor of stroke rehabilitation evaluation indicator in the context of stroke rehabilitation evaluation system. Simulation results show the effectiveness of the improved method.
This paper proposes a lattice-based method for keyword spotting in online Chinese handwriting to improve the trade-off between accuracy and speed, and to overcome the out-of-vocabulary (OOV) problem of lexicon-driven approach. Using a character string recognition algorithm, the lattice-based method generates a candidate lattice of N-best list. We observe that search multiple candidate strings reduces...
Data prefetching is an effective way to accelerate data access in high-end computing systems and to bridge the increasing performance gap between processor and memory. In recent years, the context based data prefetching has received intensive attention because of its general applicability. In this study, we provide a preliminary analysis of the impact of orders on the effectiveness of the context-based...
This paper describes an effort to estimate variations in cognitive effort among cancer survivors experiencing treatment related cognitive decline. EEG-based cognitive state sensing algorithms were validated in the context of an experiment with 5 brain cancer and 5 breast cancer survivors. Workload was manipulated by varying text complexity and time pressure. Analysis indicates that EEG-based cognitive...
In the last years, the area of Multicriteria Decision Analysis (MCDA) has brought about new methods to cope with classification problems, among which those based on the concept of prototypes. These refer to specific alternatives (samples) of the training dataset that are good representatives of the groups they fit in. In this paper, experiments are conducted over two prototype selection (PS) techniques...
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