Search results for "Software"
showing 10 items of 7396 documents
A Network-Based Framework for Mobile Threat Detection
2018
Mobile malware attacks increased three folds in the past few years and continued to expand with the growing number of mobile users. Adversary uses a variety of evasion techniques to avoid detection by traditional systems, which increase the diversity of malicious applications. Thus, there is a need for an intelligent system that copes with this issue. This paper proposes a machine learning (ML) based framework to counter rapid evolution of mobile threats. This model is based on flow-based features, that will work on the network side. This model is designed with adversarial input in mind. The model uses 40 timebased network flow features, extracted from the real-time traffic of malicious and…
A Cooperative Coevolution Framework for Parallel Learning to Rank
2015
We propose CCRank, the first parallel framework for learning to rank based on evolutionary algorithms (EA), aiming to significantly improve learning efficiency while maintaining accuracy. CCRank is based on cooperative coevolution (CC), a divide-and-conquer framework that has demonstrated high promise in function optimization for problems with large search space and complex structures. Moreover, CC naturally allows parallelization of sub-solutions to the decomposed sub-problems, which can substantially boost learning efficiency. With CCRank, we investigate parallel CC in the context of learning to rank. We implement CCRank with three EA-based learning to rank algorithms for demonstration. E…
A Repository for Multirelational Dynamic Networks
2012
Nowadays, WWW contains a number of social media sites, which are growing rapidly. One of the main features of social media sites is to allow to its users creation and modification of contents of the site utilizing the offered WWW interfaces. Such contents are referred to as user generated contents and their type varies from site to site. Social media sites can be modeled as constantly evolving multirelational directed graphs. In this paper we discuss persistent data structures for such graphs, and present and analyze queries performed against the structures. We also estimate the space requirements of the proposed data structures, and compare them with the naive "store each complete snapshot…
Wastewater treatment: New insight provided by interactive multiobjective optimization
2011
In this paper, we describe a new interactive tool developed for wastewater treatment plant design. The tool is aimed at supporting the designer in designing new wastewater treatment plants as well as optimizing the performance of already available plants. The idea is to utilize interactive multiobjective optimization which enables the designer to consider the design with respect to several conflicting evaluation criteria simultaneously. This is more important than ever because the requirements for wastewater treatment plants are getting tighter and tighter from both environmental and economical reasons. By combining a process simulator to simulate wastewater treatment and an interactive mul…
Gear classification and fault detection using a diffusion map framework
2015
This article proposes a system health monitoring approach that detects abnormal behavior of machines. Diffusion map is used to reduce the dimensionality of training data, which facilitates the classification of newly arriving measurements. The new measurements are handled with Nyström extension. The method is trained and tested with real gear monitoring data from several windmill parks. A machine health index is proposed, showing that data recordings can be classified as working or failing using dimensionality reduction and warning levels in the low dimensional space. The proposed approach can be used with any system that produces high-dimensional measurement data. peerReviewed
Quantile index for gradual and abrupt change detection from CFB boiler sensor data in online settings
2012
In this paper we consider the problem of online detection of gradual and abrupt changes in sensor data having high levels of noise and outliers. We propose a simple heuristic method based on the Quantile Index (QI) and study how robust this method is for detecting both gradual and abrupt changes with such data. We evaluate the performance of our method on the artificially generated and real datasets that represent different operational settings of a pilot circulating fluidized bed (CFB) reactor and CFB cold model. Our experiments suggest that QI can be used for designing very simple yet effective methods for gradual change detection in the noisy sensor data. It can be also used for detectin…
Fault-proneness of open source software: Exploring its relations to internal software quality and maintenance process
2013
The goal of this study is to explore how fault-proneness of open source software (OSS) could be explained in terms of internal quality attributes and maintenance process metrics. We reviewed earlier studies and performed a multiple case study of eight Java-based projects based on data available in the Source Forge repository. Overall, we studied 342 re- leases of those systems. As is usual, software quality was regarded as a set of internal and external quality attributes. A to- tal of 76 internal quality attributes were measured from the source code of the selected systems via the tool SoftCalc. Two external quality attributes contributing to fault-proneness were in turn obtained from the …
Anomaly Detection Algorithms for the Sleeping Cell Detection in LTE Networks
2015
The Sleeping Cell problem is a particular type of cell degradation in Long-Term Evolution (LTE) networks. In practice such cell outage leads to the lack of network service and sometimes it can be revealed only after multiple user complains by an operator. In this study a cell becomes sleeping because of a Random Access Channel (RACH) failure, which may happen due to software or hardware problems. For the detection of malfunctioning cells, we introduce a data mining based framework. In its core is the analysis of event sequences reported by a User Equipment (UE) to a serving Base Station (BS). The crucial element of the developed framework is an anomaly detection algorithm. We compare perfor…
Understanding beginners' mistakes with Haskell
2015
AbstractThis article presents an overview of student difficulties in an introductory functional programming (FP) course taught in Haskell. The motivation for this study stems from our belief that many student difficulties can be alleviated by understanding the underlying causes of errors and by modifying the educational approach and, possibly, the teaching language accordingly. We analyze students' exercise submissions and categorize student errors according to compiler error messages and then manually according to the observed underlying cause. Our study complements earlier studies on the topic by applying computer and manual analysis while focusing on providing descriptive statistics of d…
A modelling framework for social media monitoring
2013
This paper describes a hierarchical, three-level modelling framework for monitoring social media. Immediate social reality is modelled through the first level of the models. They represent various virtual communities at social media sites and adhere to the social world models of the sites, i.e., the "site ontologies". The second-level model is a temporal multirelational graph that captures the static and dynamic properties of the first-level models from the perspective of the monitoring site. The third-level model consists of a temporal relational database scheme that models the temporal multirelational graph within the database. The models are specified and instantiated at the monitoring s…