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Full-Text Articles in Computer Engineering
Predicting Stock Market Using Online Communities Raw Web Traffic Streams, Pierpaolo Dondio
Predicting Stock Market Using Online Communities Raw Web Traffic Streams, Pierpaolo Dondio
Articles
This paper investigates the predictive power of online communities traffic in regard to stock prices. Using the largest dataset to date, spanning 8 years and almost the complete set of SP500 stocks, we analyze the predictive power of raw unstructured traffic by filtering stock daily returns with traffic features. Our results partially challenge the assumption that raw traffic simply trails stock prices, as expected from a noisy signal without the sentiment direction. Raw traffic is shown to predict prices with statistical significance but with small economic impact. Anyway, this impact rises to moderate under the following conditions: 3 to 7 …
A Review Of Situation Identification Techniques In Pervasive Computing, Juan Ye, Simon Dobson, Susan Mckeever
A Review Of Situation Identification Techniques In Pervasive Computing, Juan Ye, Simon Dobson, Susan Mckeever
Articles
Pervasive systems must offer an open, extensible, and evolving portfolio of services which integrate sensor data from a diverse range of sources. The core challenge is to provide appropriate and consistent adaptive behaviours for these services in the face of huge volumes of sensor data exhibiting varying degrees of precision, accuracy and dynamism. Situation identification is an enabling technology that resolves noisy sensor data and abstracts it into higher-level concepts that are interesting to applications. We provide a comprehensive analysis of the nature and characteristics of situations, discuss the complexities of situation identification, and review the techniques that are most …
Speech Intelligibility Prediction Using A Neurogram Similarity Index Measure, Andrew Hines, Naomi Harte
Speech Intelligibility Prediction Using A Neurogram Similarity Index Measure, Andrew Hines, Naomi Harte
Articles
Performance Intensity functions can be used to provide additional information over measurement of speech reception threshold and maximum phoneme recognition by plotting a test subject's recognition probability over a range of sound intensities. A computational model of the auditory periphery was used to replace the human subject and develop a methodology that simulates a real listener test. The newly developed NSIM is used to evaluate the model outputs in response to Consonant-Vowel-Consonant (CVC) word lists and produce phoneme discrimination scores.