Search results for "computer"
showing 10 items of 30657 documents
Modelling Recurrent Events for Improving Online Change Detection
2016
The task of online change point detection in sensor data streams is often complicated due to presence of noise that can be mistaken for real changes and therefore affecting performance of change detectors. Most of the existing change detection methods assume that changes are independent from each other and occur at random in time. In this paper we study how performance of detectors can be improved in case of recurrent changes. We analytically demonstrate under which conditions and for how long recurrence information is useful for improving the detection accuracy. We propose a simple computationally efficient message passing procedure for calculating a predictive probability distribution of …
Identity Use and Misuse of Public Persona on Twitter
2016
Social media sites have appeared during the last 10 years and their use has exploded all over the world. Twitter is a microblogging service that has currently 320 million user profiles and over 100 million daily active users. Many celebrities and leading politicians have a verified profile on Twitter, including Justin Bieber, president Obama, and the Pope. In this paper we investigate the '‘hundreds of Putins and Obamas phenomenon’ on Twitter. We collected two data sets in 2015 containing 582 and 6477 profiles that are related to the G20 leaders’ profiles on Twitter. The number of namesakes varied from 5 to 1000 per leader. We analysed in detail various aspects of the Putin and Erdogan rela…
Does the Learning Channel Really Matter? - Insights from Commercial Online ICT-training
2017
Evolving ICT has provided new options to participate to training. Online participation has been found to be cost effective, helping people to deal with the time and cost pressures they are facing on their jobs. Previous studies conducted in higher education sector indicates that student satisfaction or learning outcomes does not differ between online and classroom participants. However, little is known what is the situation in commercial ICT-training. This paper studied course feedbacks from courses having both online and classroom participants of a commercial ICT-training provider. Results revealed that the learning channel has no effect on satisfaction, perceived teacher’s substance and t…
Methods for estimating forest stem volumes by tree species using digital surface model and CIR images taken from light UAS
2012
In this paper we consider methods for estimating forest tree stem volumes by species using images taken from light unmanned aircraft systems (UAS). Instead of using LiDAR and additional multiband imagery a color infrared camera mounted to a light UAS is used to acquire both imagery and the DSM of target area. The goal of this study is to accurately estimate tree stem volumes in three classes. The status of the ongoing work is described and an initial method for delineating and classifying treetops is presented.
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…
Recommending Serendipitous Items using Transfer Learning
2018
Most recommender algorithms are designed to suggest relevant items, but suggesting these items does not always result in user satisfaction. Therefore, the efforts in recommender systems recently shifted towards serendipity, but generating serendipitous recommendations is difficult due to the lack of training data. To the best of our knowledge, there are many large datasets containing relevance scores (relevance oriented) and only one publicly available dataset containing a relatively small number of serendipity scores (serendipity oriented). This limits the learning capabilities of serendipity oriented algorithms. Therefore, in the absence of any known deep learning algorithms for recommend…
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…
Towards enabling privacy preserving smart city apps
2016
Smart city applications are increasingly relying on personally identifiable data. A disclosure of such a data to a platform provider and possible 3rd parties represents a risk to the privacy of the application users. To mitigate the privacy risk, two-layer privacy-preserving platform architecture is introduced, wherein the personally identifiable information is dealt with at the inner layer (executed in a trusted environment), whereas only generic and personally unidentifiable information is made available to the apps at the outer layer of the architecture — e.g., in a form of app-specific events. The essential requirements for the platform are described, and the architectural implications …
Essence : Reference Architecture for Software Engineering - Representing Essence in Archimate Notation
2018
Essence is a standard for working with methods in software engineering. As such, it can be seen as the reference architecture for software engineering. The Essence consists of the Kernel, and a notation called the Language. This representation is not widely known and likely hinders the adoption of the Essence. This paper represents the work-in-progress of representing the Essence using ArchiMate, the de facto notation for enterprise architecture. Our purpose is to help organisations to adopt Essence by representing it in the language already understood by different stakeholders. peerReviewed
Customer Perception Driven Product Evolution - Facilitation of Structured Feedback Collection
2016
Competitive environment not only requires effective advertising strategies from the product producers and service providers, but also to do comprehensive and sufficient analysis of their customers to understand their needs and expectations. Successfully involving customers into a product/service co-creation process, companies more likely increase their future revenue. Customer feedback analysis is widely applied in marketing and product development. Among other challenges (e.g. customer engagement, feedback collection, etc.) automation of customer feedback analysis becomes very demanding task and requires advance intelligent tools to understand customers’ product perception and preferences.…