Search results for "Random"
showing 10 items of 3931 documents
Context–content systems of random variables : The Contextuality-by-Default theory
2016
Abstract This paper provides a systematic yet accessible presentation of the Contextuality-by-Default theory. The consideration is confined to finite systems of categorical random variables, which allows us to focus on the basics of the theory without using full-scale measure-theoretic language. Contextuality-by-Default is a theory of random variables identified by their contents and their contexts, so that two variables have a joint distribution if and only if they share a context. Intuitively, the content of a random variable is the entity the random variable measures or responds to, while the context is formed by the conditions under which these measurements or responses are obtained. A …
Online anomaly detection using dimensionality reduction techniques for HTTP log analysis
2015
Modern web services face an increasing number of new threats. Logs are collected from almost all web servers, and for this reason analyzing them is beneficial when trying to prevent intrusions. Intrusive behavior often differs from the normal web traffic. This paper proposes a framework to find abnormal behavior from these logs. We compare random projection, principal component analysis and diffusion map for anomaly detection. In addition, the framework has online capabilities. The first two methods have intuitive extensions while diffusion map uses the Nyström extension. This fast out-of-sample extension enables real-time analysis of web server traffic. The framework is demonstrated using …
An Efficient Network Log Anomaly Detection System Using Random Projection Dimensionality Reduction
2014
Network traffic is increasing all the time and network services are becoming more complex and vulnerable. To protect these networks, intrusion detection systems are used. Signature-based intrusion detection cannot find previously unknown attacks, which is why anomaly detection is needed. However, many new systems are slow and complicated. We propose a log anomaly detection framework which aims to facilitate quick anomaly detection and also provide visualizations of the network traffic structure. The system preprocesses network logs into a numerical data matrix, reduces the dimensionality of this matrix using random projection and uses Mahalanobis distance to find outliers and calculate an a…
Data mining framework for random access failure detection in LTE networks
2014
Sleeping cell problem is a particular type of cell degradation. There are various software and hardware reasons that might cause such kind of cell outage. In this study a cell becomes sleeping because of Random Access Channel (RACH) failure. This kind of network problem can appear due to misconfiguration, excessive load or software/firmware problem at the Base Station (BS). In practice such failure might cause network performance degradation, which is hardly traceable by an operator. In this paper we present a data mining based framework for the detection of problematic cells. In its core is the analysis of event sequences reported by a User Equipment (UE) to a serving BS. The choice of N i…
The influence of dataset size on the performance of cell outage detection approach in LTE-A networks
2015
The configuration and maintenance of constantly evolving mobile cellular networks are getting more and more complex and hence expensive. Self-Organizing Networks (SON) concept is an umbrella term for the set of automated solutions for network operations proposed by 3rd Generation Partnership Project (3GPP) group. Automated cell outage detection is one of the components of SON functionality. In early studies our research group developed data-driven approach for the detection of malfunctioning cells. In this paper we investigate the performance of the proposed solution as a function of the density of active users and the size of observation interval. The evaluation is conducted in Long Term E…
Coupling high-resolution satellite imagery with ALS-based canopy height model and digital elevation model in object-based boreal forest habitat type …
2014
We developed a classification workflow for boreal forest habitat type mapping. In object-based image analysis framework, Fractal Net Evolution Approach segmentation was combined with random forest classification. High-resolution WorldView-2 imagery was coupled with ALS based canopy height model and digital terrain model. We calculated several features (e.g. spectral, textural and topographic) per image object from the used datasets. We tested different feature set alternatives; a classification accuracy of 78.0 % was obtained when all features were used. The highest classification accuracy (79.1 %) was obtained when the amount of features was reduced from the initial 328 to the 100 most imp…
La spatialité des dommages et risques environnementaux comme point de convergence entre géographie, écologie et politique
2012
The analysis of complex systems such as those captured by scientific ecology shows that the occurrence of damaging events is difficult to predict. Moreover, most of these unpredictable events will be those with the strongest echoes, giving full meaning to the concept of risk as cross between hazard and vulnerability. Each of these two components of risk has a spatial dimension more or less obvious, and to understand the natural risk, occurrence and spatial extension of the hazard and the vulnerability should be analyzed jointly. Thus, we show that for environmental risk, the question of "where?" posed by the prediction refers certainly to ecological and geographical problems, but also econo…
The CANNA-TICS Study Protocol: A Randomized Multi-Center Double-Blind Placebo Controlled Trial to Demonstrate the Efficacy and Safety of Nabiximols i…
2020
Background: Gilles de la Tourette syndrome (TS) is a chronic neuropsychiatric disorder characterized by motor and vocal tics. First-line treatments for tics are antipsychotics and tic-specific behavioral therapies. However, due to a lack of trained therapists and adverse events of antipsychotic medication many patients seek alternative treatment options including cannabis. Based on the favorable results obtained from case studies on different cannabis-based medicines as well as two small randomized controlled trials using delta-9-tetrahydrocannabinol (THC), we hypothesize that the cannabis extract nabiximols can be regarded as a promising new and safe treatment strategy in TS.Objective: To …
Effect of RNS60 in amyotrophic lateral sclerosis: a phase II multicentre, randomized, double-blind, placebo-controlled trial
2022
Background and purpose: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with limited treatment options. RNS60 is an immunomodulatory and neuroprotective investigational product that has shown efficacy in animal models of ALS and other neurodegenerative diseases. Its administration has been safe and well tolerated in ALS subjects in previous early phase trials. Methods: This was a phase II, multicentre, randomized, double-blind, placebo-controlled, parallel-group trial. Participants diagnosed with definite, probable or probable laboratory-supported ALS were assigned to receive RNS60 or placebo administered for 24 weeks intravenously (375 ml) once a week and via nebul…
EXTRACORPOREAL SHOCK WAVE THERAPY (ESWT) IN CHRONIC LOW BACK PAIN: A SYSTEMATIC REVIEW OF RANDOMIZED CLINICAL TRIALS
2020
Background: Extracorporeal Shock Wave Therapy (ESWT) has become a popular tool to treat musculoskeletal disorders and chronic low back pain. Aim of the study: To review the current scientific literature and assess the utility of ESWT in treating chronic low back pain. Methods: This systematic review was conducted from November 2019 to January 2020. Its purpose was to determine what the effectiveness is of the various forms of ESWT for the treatment of chronic low back pain. The critical review of the literature on the use of ESWT in chronic low back was made using the scientifically recognized medical databases PubMed, MEDLINE, Physiotherapy Evidence Database (PEDro) and Web of Science Core…