Search results for "NETWORKING"
showing 10 items of 1776 documents
Evaluation of Ensemble Machine Learning Methods in Mobile Threat Detection
2017
The rapid growing trend of mobile devices continues to soar causing massive increase in cyber security threats. Most pervasive threats include ransom-ware, banking malware, premium SMS fraud. The solitary hackers use tailored techniques to avoid detection by the traditional antivirus. The emerging need is to detect these threats by any flow-based network solution. Therefore, we propose and evaluate a network based model which uses ensemble Machine Learning (ML) methods in order to identify the mobile threats, by analyzing the network flows of the malware communication. The ensemble ML methods not only protect over-fitting of the model but also cope with the issues related to the changing be…
Assessment of Deep Learning Methodology for Self-Organizing 5G Networks
2019
In this paper, we present an auto-encoder-based machine learning framework for self organizing networks (SON). Traditional machine learning approaches, for example, K Nearest Neighbor, lack the ability to be precisely predictive. Therefore, they can not be extended for sequential data in the true sense because they require a batch of data to be trained on. In this work, we explore artificial neural network-based approaches like the autoencoders (AE) and propose a framework. The proposed framework provides an advantage over traditional machine learning approaches in terms of accuracy and the capability to be extended with other methods. The paper provides an assessment of the application of …
Language Learning Methodology for Adults: A Study of Linguistic Transfer
2014
Abstract The purpose of the present research is to bring together the evidence on transfer in adult L2 and L3 language acquisition and investigate the use and the relationship between languages in contact. The role of linguistic transfer ( Odlin, 1989 ) i.e. the imposition of previously learned patterns onto a new learning situation, has a facilitation or inhibition effect on the learner's progress in mastering a new language (L2 or L3). Our findings reveal that the cross-linguistic influence occurs both from the direction of the L2 to the L3 and from the L3 to the L2 ( Odlin, 2003 , Jarvis and Pavlenko, 2008 ). In the case of our participants, in the acquisition of L2 as the foreign langua…
Fast Implementation of Double-coupled Nonnegative Canonical Polyadic Decomposition
2019
Real-world data exhibiting high order/dimensionality and various couplings are linked to each other since they share some common characteristics. Coupled tensor decomposition has become a popular technique for group analysis in recent years, especially for simultaneous analysis of multi-block tensor data with common information. To address the multiblock tensor data, we propose a fast double-coupled nonnegative Canonical Polyadic Decomposition (FDC-NCPD) algorithm in this study, based on the linked CP tensor decomposition (LCPTD) model and fast Hierarchical Alternating Least Squares (Fast-HALS) algorithm. The proposed FDCNCPD algorithm enables simultaneous extraction of common components, i…
A Parallel Approach to HRTF Approximation and Interpolation Based on a Parametric Filter Model
2017
[EN] Spatial audio-rendering techniques using head-related transfer functions (HRTFs) are currently used in many different contexts such as immersive teleconferencing systems, gaming, or 3-D audio reproduction. Since all these applications usually involve real-time constraints, efficient processing structures for HRTF modeling and interpolation are necessary for providing real-time binaural audio solutions. This letter presents a parametric parallel model that allows us to perform HRTF filtering and interpolation efficiently from an input HRTF dataset. The resulting model, which is an adaptation from a recently proposed modeling technique, not only reduces the size of HRTF datasets signific…
Managing sensor data streams in a smart home application
2020
A challenge in developing an ambient activity recognition system for use in elder care is finding a balance between the sophistication of the system and a cost structure that fits within the budgets of public and private sector healthcare organisations. Much activity recognition research in the context of elder care is based on dense networks of sensors and advanced methods, such as supervised machine learning algorithms. This paper presents the data processing aspects of an activity recognition system based on a simpler, knowledge-based unsupervised approach, designed for a sparse network of sensors. By structuring sensor data management as a streaming system, we provide a simple programmi…
A Generic Approach to Scheduling and Checkpointing Workflows
2018
This work deals with scheduling and checkpointing strategies to execute scientific workflows on failure-prone large-scale platforms. To the best of our knowledge, this work is the first to target fail-stop errors for arbitrary workflows. Most previous work addresses soft errors, which corrupt the task being executed by a processor but do not cause the entire memory of that processor to be lost, contrarily to fail-stop errors. We revisit classical mapping heuristics such as HEFT and MinMin and complement them with several checkpointing strategies. The objective is to derive an efficient trade-off between checkpointing every task (CkptAll), which is an overkill when failures are rare events, …
Teaching networking: an interpersonal communication competence perspective
2015
Modern working life calls for competences that enable people to be creative, innovative and effective. Studies looking at contemporary enterprises and organisations such as businesses and schools have shown that many of the qualifications that graduating students would need, including informal learning (see Gielen, Hoeve & Nieuwenhuis 2003), innovativeness (e.g. Moolenaar & Sleegers 2010; Obstfeld 2005) and creativity (e.g. Burt 2004; Perry-Smith & Shalley 2003), are associated with interpersonal relationships and social networks. According to a report on the national career survey (EK 2011a), effective networking is dependent on social skills such as the ability to establish contacts in mu…
Automated detection of patient movement during a CBCT scan based on the projection data.
2015
Objectives To develop an automated procedure to detect patient motion on the projection images acquired during a cone beam computed tomography (CBCT) scan and to evaluate the method's feasibility on small real-world CBCT images in relation to visual assessment. Methods Based on optical flow theory, software was developed using the sequence of the projection images of a CBCT machine for automated detection of patient motion. Averaged acceleration vectors were used as measurement data and compared with visual assessment of the projection images displayed as video. Seventy-nine CBCT data sets (small field-of-view: 40 mm) from our patient database were selected in a sequential fashion and evalu…
Extracting modular-based backbones in weighted networks
2021
Abstract Networks are an adequate representation for modeling and analyzing a great variety of complex systems. However, understanding networks with millions of nodes and billions of connections can be pretty challenging due to memory and time constraints. Therefore, selecting the relevant nodes and edges of these large-scale networks while preserving their core information is a major issue. In most cases, the so-called backbone extraction methods are based either on coarse-graining or filtering approaches. Coarse-graining techniques reduce the network size by gathering similar nodes into super-nodes, while filter-based methods eliminate nodes or edges according to a statistical property.In…