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In this paper we propose a complete frontier-based exploration method for Pose SLAM. The goal of current frontier-based exploration methods is to eliminate all frontiers in the environment map. This approach, however, does not meet the requirements of Pose SLAM mapping: besides arriving at a frontier free map, there is the need to close the loops in the environment. In fact, loop closing is instrumental...
We present a semi-supervised boosting algorithm for the multi-label classification by using the conditional label variance as a loss function over the unlabeled data. The experiments on the benchmark data sets show that the proposed algorithm outperforms its supervised counterpart as well as the existing information theoretic based semi-supervised methods, and its performance is steadily improving...
In the realm of cyber security, recent events have demonstrated the need for a significant change in the philosophies guiding the identification and mitigation of attacks. The unprecedented increase in the quantity and sophistication of cyber attacks in the past year alone has proven the inadequacy of current defensive philosophies that do not assume continuous compromise. This has given rise to new...
As the market for cellular telephones, and other mobile devices, keeps growing, the demand for new services arises to attract the end users. Location Based Services (LBS) are becoming important to the success and attractiveness of next generation wireless systems. To access location-based services, mobile users have to disclose their location information to service providers and third party applications...
Detecting anomalous traffic with low false alarm rates is of primary interest in IP networks management. In this paper we propose a novel anomaly detection system, based on a combined use of sketches and of a novel bivariate non-parametric detection method. The latter allows us to simultaneously analyse two different traffic features so as to improve the performance of the "classical" detection...
Location-Based Service (LBS) has become a vital part of our daily life. While enjoying the convenience provided by LBS, users may lose privacy since the untrusted LBS server has all the information about users in LBS and it may track them in various ways or release their personal data to third parties. To address the privacy issue, we propose a Dummy-Location Selection (DLS) algorithm to achieve k-anonymity...
In the analysis of iterative coding systems it is often necessary to compare two densities and to measure how close they are. Sometimes it is convenient to compare their entropy or their Battacharyya parameter. But sometimes a more powerful measure is required. The Wasserstein metric is a convenient choice. We derive some basic properties of the Wasserstein metric which are important in the context...
Identifiers are an important source of information during program understanding and maintenance. Programmers often use identifiers to build their mental models of the software artifacts. We have performed a preliminary study to examine the relation between the terms in identifiers, their spread in entities, and fault proneness. We introduced term entropy and context-coverage to measure how scattered...
Poorly-chosen identifiers have been reported in the literature as misleading and increasing the program comprehension effort. Identifiers are composed of terms, which can be dictionary words, acronyms, contractions, or simple strings. We conjecture that the use of identical terms in different contexts may increase the risk of faults. We investigate our conjecture using a measure combining term entropy...
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