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Various Markov models have been proposed to model individuals' mobility, i.e., the transitions between locations. Although these studies are able to show high predicting accuracy of individuals' next move, two basic assumptions of these studies, namely the stationarity of individuals' mobility sequence and the dependency of visiting the locations, have never been validated. Moreover, a famous recent...
The arrival of new devices and techniques has brought tracking out of the investigation stage and into the wider world. Using Wi-Fi signals is an attractive and reasonably affordable option to deal with the currently unsolved problem of widespread tracking in an indoor environment. Here we present a system called HABITS (History Aware Based Indoor Tracking System) which aims at overcoming weaknesses...
Cooking activities are complex activities consisting of multiple steps or tasks. These tasks can be associated with one another based on two properties the temporal structure that defines the sequence of occurrence of tasks and the objects that are used in the activity. This paper develops cooking activity models for the purpose of task prediction based on these two properties. The temporal structure...
Protein backbone dihedral angles are important descriptors of local conformation for amino acids. Protein backbone dihedral angle prediction lays the foundation for prediction of higher-order protein structure. Existing prediction methods of protein backbone angles mainly exploit traditional machine learning techniques. In this paper, we propose to use two well-known types of probabilistic models...
In next generation networks, mobile communication calls for service with higher quality, which brings new challenge for mobility management. Thereinto, utilization and improvement of mobility prediction helps for preserving resource and providing better performance. So this paper aims to propose a theoretical and factual method to perform mobility prediction in cellular network. By analyzing the demand...
Automatic text tagging is an important component in higher level analysis of text corpora, and its output can be used in many natural language processing applications. Trigrams tags is an efficient statistical part-of-speech tagging. This paper describes a POS tagging for Uyhur text based on hidden Markov model using trigrams tags. We describe the basic model of Trigrams Tags, the techniques used...
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