Search results for "NR"
showing 10 items of 6911 documents
Smart Educational Process Based on Personal Learning Capabilities
2017
Personalized learning is increasingly gaining popularity, especially with the development of information technology and modern educational resources for learning. Each person is individual and has different knowledge background, different kind of memory, different learning speed. Teacher can adapt learning course, learning instructions or learning material according to the majority of learners in class, but that means that learning process is not adapted to the personality of each individual learner. That is why it is important to have smart educational process based on personal learning capabilities. This paper presents a literature survey on different learning systems which detects learni…
Evaluating the performance of artificial neural networks for the classification of freshwater benthic macroinvertebrates
2014
Abstract Macroinvertebrates form an important functional component of aquatic ecosystems. Their ability to indicate various types of anthropogenic stressors is widely recognized which has made them an integral component of freshwater biomonitoring. The use of macroinvertebrates in biomonitoring is dependent on manual taxa identification which is currently a time-consuming and cost-intensive process conducted by highly trained taxonomical experts. Automated taxa identification of macroinvertebrates is a relatively recent research development. Previous studies have displayed great potential for solutions to this demanding data mining application. In this research we have a collection of 1350 …
Using Video Conferencing and Video Recordings for Upper Secondary Distance Teaching: Teachers' View Points
2016
In Finland the “Isoverstas” (formely ISOverkosto) network of schools coordinates the development of upper secondary distance learning services. The community actually is quite extensive with 65 member schools. In this paper we introduce the results related using synchronous and asynchronous online video resources for distance teaching. The topic is approached broadly at the level of schools and different support services as well as the pedagogical practices of individual teachers. The research data consists of wiki stories written by teachers, the interviews of selected teachers, and an online survey. Data-based content analysis was chosen as the main analysis method with the aim of highlig…
Real-time recognition of personal routes using instance-based learning
2011
Predicting routes is a critical enabler for many new location-based applications and services, such as warning drivers about congestion- or accident-risky areas. Hybrid vehicles can also utilize the route prediction for optimizing their charging and discharging phases. In this paper, a new lightweight route recognition approach using instance-based learning is introduced. In this approach, the current route is compared in real-time against the route instances observed in past, and the most similar route is selected. In order to assess the similarity between the routes, a similarity measure based on the longest common subsequence (LCSS) is employed, and an algorithm for incrementally evaluat…
A Novel Model for Cybersecurity Economics and Analysis
2017
In recent times, major cybersecurity breaches and cyber fraud had huge negative impact on victim organisations. The biggest impact made on major areas of business activities. Majority of organisations facing cybersecurity adversity and advanced threats suffers from huge financial and reputation loss. The current security technologies, policies and processes are providing necessary capabilities and cybersecurity mechanism to solve cyber threats and risks. However, current solutions are not providing required mechanism for decision making on impact of cybersecurity breaches and fraud. In this paper, we are reporting initial findings and proposing conceptual solution. The paper is aiming to pr…
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 …
Listwise Collaborative Filtering
2015
Recently, ranking-oriented collaborative filtering (CF) algorithms have achieved great success in recommender systems. They obtained state-of-the-art performances by estimating a preference ranking of items for each user rather than estimating the absolute ratings on unrated items (as conventional rating-oriented CF algorithms do). In this paper, we propose a new ranking-oriented CF algorithm, called ListCF. Following the memory-based CF framework, ListCF directly predicts a total order of items for each user based on similar users' probability distributions over permutations of the items, and thus differs from previous ranking-oriented memory-based CF algorithms that focus on predicting th…
An Approach for Network Outage Detection from Drive-Testing Databases
2012
A data-mining framework for analyzing a cellular network drive testing database is described in this paper. The presented method is designed to detect sleeping base stations, network outage, and change of the dominance areas in a cognitive and self-organizing manner. The essence of the method is to find similarities between periodical network measurements and previously known outage data. For this purpose, diffusion maps dimensionality reduction and nearest neighbor data classification methods are utilized. The method is cognitive because it requires training data for the outage detection. In addition, the method is autonomous because it uses minimization of drive testing (MDT) functionalit…
Cognitive self-healing system for future mobile networks
2015
This paper introduces a framework and implementation of a cognitive self-healing system for fault detection and compensation in future mobile networks. Performance monitoring for failure identification is based on anomaly analysis, which is a combination of the nearest neighbor anomaly scoring and statistical profiling. Case-based reasoning algorithm is used for cognitive self-healing of the detected faulty cells. Validation environment is Long Term Evolution (LTE) mobile system simulated with Network Simulator 3 (ns-3) [1, 2]. Results demonstrate that cognitive approach is efficient for compensation of cell outages and is capable to improve network coverage. Anomaly analysis can be used fo…
Towards the cyber security paradigm of ehealth: Resilience and design aspects
2017
Digital technologies have significantly changed the role of healthcare clients in seeking and receiving medical help, as well as brought up more cooperative policy issues in healthcare cross-border services. Citizens continue to take a more co-creative role in decisions about their own healthcare, and new technologies can enable and facilitate this emergent trend. In this study, healthcare services have been intended as a critical societal sector and therefore healthcare systems are focused on as critical infrastructures that ought to be protected from all types of fears, including cyber security threats and attacks. Despite continual progress in the systemic risk management of cyber domain…