Search results for "war"
showing 10 items of 11970 documents
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…
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
Assessing the Effectiveness of Two Theoretically Motivated Computer-Assisted Reading Interventions in the United Kingdom: GG Rime and GG Phoneme
2013
We report an empirical comparison of the effectiveness of two theoretically motivated computer-assisted reading interventions (CARI) based on the Finnish GraphoGame CARI: English GraphoGame Rime (GG Rime) and English GraphoGame Phoneme (GG Phoneme). Participants were 6–7-year-old students who had been identified by their teachers as being relatively poor at reading. The students were divided into three groups. Two of the groups played one of the games as a supplement to normal classroom literacy instruction for five sessions per week for a period of 12 weeks. The third group formed an untreated control. Both games led to gains in reading, spelling, and phonological skills in comparison with…
Scalable implementation of dependence clustering in Apache Spark
2017
This article proposes a scalable version of the Dependence Clustering algorithm which belongs to the class of spectral clustering methods. The method is implemented in Apache Spark using GraphX API primitives. Moreover, a fast approximate diffusion procedure that enables algorithms of spectral clustering type in Spark environment is introduced. In addition, the proposed algorithm is benchmarked against Spectral clustering. Results of applying the method to real-life data allow concluding that the implementation scales well, yet demonstrating good performance for densely connected graphs. peerReviewed
Are they different? affect, feeling, emotion, sentiment, and opinion detection in text
2014
A major limitation in the automatic detection of affect, feelings, emotions, sentiments, and opinions in text is the lack of proper differentiation between these subjective terms and understanding of how they relate to one another. This lack of differentiation not only leads to inconsistency in terminology usage but also makes the subtleties and nuances expressed by the five terms difficult to understand, resulting in subpar detection of the terms in text. In light of such limitation, this paper clarifies the differences between these five subjective terms and reveals significant concepts to the computational linguistics community for their effective detection and processing in text.
Video Streaming and Internalized Surveillance
2018
This paper aims to develop knowledge about the complicated ways in which the modern individual uses surveillance (techniques) and the ways surveillance uses the individual. My observational analysis of a videostreaming community reveals the central role that surveillance plays in participating and becoming visible in an online environment. The results show that through disciplinary and lateral surveillance, participants produced context-defined I-narrations and formed themselves following the normative judgment of the environment. The same mechanism may be observed in other videostreaming social media environments and the modern social media-saturated society in general. This is an inconspi…