Detecting Android malware in its spread or download stage is a challenging work, which can realize early detection of before it reaches user side. In this paper, we propose two-stage framework based on feature enhancement and cascade deep forest. This method detect the traffic generated encrypted transmission process malware. The first realizes binary classification benign malicious software. s...

Aspect-level sentiment classification aims to integrating the context predict polarity of aspect-specific in a text, which has been quite useful and popular, e.g., opinion survey products’ recommending e-commerce. Many recent studies exploit Long Short-Term Memory (LSTM) networks perform aspect-level classification, but limitation long-term dependencies is not solved well, so that semantic corr...

In today’s competitive business environment, the design and management of supply chainnetwork is one of the most important challenges that managers encounter. The supply chain network shouldbe designed for satisfying of customer demands as well as minizing the total system costs. This paper presentsa multi-period multi-stage supply chain network design problem under demand uncertainty. The prob...

A two tier system for MR image segmentation is proposed. The first stage involves probabilistically classifying the pixels of the input image based on second order grey level statistics obtained from the co-occurrence matrix. These probabilities then form the input to a multi-layer perceptron, allowing contextual constraints to be applied to local areas of the image thereby improving the spatia...

The paper presents methodology for the incremental map formation in a multi-stage process of a search engine with the map based user interface. The architecture of the experimental system allows for comparative evaluation of different constituent technologies for various stages of the process. The quality of the map generation process has been investigated based on a number of clustering and cl...

This project proposes a three-stage time series model to identify the relationship between properties of news information shocks and patterns in market reactions to such news. Then, given a specific news update, the model predicts how market players will subsequently respond. We apply multivariate time series segmentation and clustering techniques on gold commodity futures, and then run various...

Regression Trees from Data Streams with Drift Detection p. 121 Mining Frequent Bipartite Episode from Event Sequences p. 136 Chronicle: A Two-Stage Density-Based Clustering Algorithm for Dynamic Networks p. 152 Learning Large Margin First Order Decision Lists for Multi-class Classification p. 168 Ceutrality Measures from Complex Networks in Active Learning p. 184 Player Modeling for Intelligent...

Multi-atlas based methods have been recently used for classification of Alzheimer's disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Compared with traditional single-atlas based methods, multiatlas based methods adopt multiple predefined atlases and thus are less biased by a certain atlas. However, most existing multiatlas based methods simply average or concatena...