Search results for "Computer science"
showing 10 items of 22367 documents
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.…
Operator Revenue Analysis for Device-to-Device Communications Overlaying Cellular Network
2018
Device-to-device (D2D) communications has recently gathered significant research interest due to its efficient utilization of already depleting wireless spectrum. In this article, we considered a scenario where D2D users communicate in the presence of cellular users in an overlay network setup. In order to analyze the revenue of service providers in monetary terms, the paper provides exact expressions of operator profit for both D2D and cellular users. More specifically, we take into account different network parameters including user density, transmit power and channel variations to understand their impact on the total revenue of the operator. Finally, we derive the balancing value of freq…
Lattice Boltzmann Simulations at Petascale on Multi-GPU Systems with Asynchronous Data Transfer and Strictly Enforced Memory Read Alignment
2015
The lattice Boltzmann method is a well-established numerical approach for complex fluid flow simulations. Recently general-purpose graphics processing units have become accessible as high-performance computing resources at large-scale. We report on implementing a lattice Boltzmann solver for multi-GPU systems that achieves 0.69 PFLOPS performance on 16384 GPUs. In addition to optimizing the data layout on the GPUs and eliminating the halo sites, we make use of the possibility to overlap data transfer between the host CPU and the device GPU with computing on the GPU. We simulate flow in porous media and measure both strong and weak scaling performance with the emphasis being on a large scale…
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