Using machine learning and optical imaging to identify malignant tumor cells

Using Machine Learning to Identify Intonational Segments

The intonational phrase is hypothesized to represent a meaningful unit of analysis in spoken language interpretation. We present results on the identification of intonational phrase boundaries from acoustic features using classification and regression trees (CART). Our training and test data are taken from the Boston Directions Corpus (task-oriented monologue) and the HUB-IV Broadcast News data...

Using Machine Learning Techniques to Identify Botnet Traffic

To date, techniques to counter cyber-attacks have predominantly been reactive; they focus on monitoring network traffic, detecting anomalies and cyber-attack traffic patterns, and, a posteriori, combating the cyber-attacks and mitigating their effects. Contrary to such approaches, we advocate proactively detecting and identifying botnets prior to their being used as part of a cyber-attack [12]....

Using machine learning to identify disease-relevant regulatory RNAs.

A complex eukaryotic genome contains several hundred to thousands of transcriptional and posttranscriptional regulators, which together make it possible to encode specific patterns of gene expression for many different conditions (1). The cooperation between transcription factors (TFs) and microRNAs (miRNAs) has been a particularly interesting topic, because they can regulate each other and def...

Determination of experimental Tumor Volume of a mouse using optical imaging system in different processing stages

Using Machine Learning ARIMA to Predict the Price of Cryptocurrencies

The increasing volatility in pricing and growing potential for profit in digital currency have made predicting the price of cryptocurrency a very attractive research topic. Several studies have already been conducted using various machine-learning models to predict crypto currency prices. This study presented in this paper applied a classic Autoregressive Integrated Moving Average(ARIMA) model ...