Search results for "VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550"
showing 10 items of 469 documents
Positionless aspect based sentiment analysis using attention mechanism.
2021
Abstract Aspect-based sentiment analysis (ABSA) aims at identifying fine-grained polarity of opinion associated with a given aspect word. Several existing articles demonstrated promising ABSA accuracy using positional embedding to show the relationship between an aspect word and its context. In most cases, the positional embedding depends on the distance between the aspect word and the remaining words in the context, known as the position index sequence. However, these techniques usually employ both complex preprocessing approaches with additional trainable positional embedding and complex architectures to obtain the state-of-the-art performance. In this paper, we simplify preprocessing by …
Online or offline – Does it matter?: A study of in-service teachers' perceptions of learning outcomes in Norway
2020
Policymakers and scholars are scaling up online professional development programmes for teachers. We studied how in-service teachers in Norway perceived their learning outcomes for professional development programmes conducted either as campus-based or online courses. Based on survey data, we found teachers studying online and in campus-based settings have relatively similar perceptions of the learning outcomes. This changes when indicators of collaboration and support from teachers are controlled for, suggesting that these factors are more strongly related to learning outcomes for those in campus-based studies than those in online studies. Our findings contribute new insights on how percei…
Location-Free Spectrum Cartography
2019
Spectrum cartography constructs maps of metrics such as channel gain or received signal power across a geographic area of interest using spatially distributed sensor measurements. Applications of these maps include network planning, interference coordination, power control, localization, and cognitive radios to name a few. Since existing spectrum cartography techniques require accurate estimates of the sensor locations, their performance is drastically impaired by multipath affecting the positioning pilot signals, as occurs in indoor or dense urban scenarios. To overcome such a limitation, this paper introduces a novel paradigm for spectrum cartography, where estimation of spectral maps rel…
Channel Gain Cartography via Mixture of Experts
2020
In order to estimate the channel gain (CG) between the locations of an arbitrary transceiver pair across a geographic area of interest, CG maps can be constructed from spatially distributed sensor measurements. Most approaches to build such spectrum maps are location-based, meaning that the input variable to the estimating function is a pair of spatial locations. The performance of such maps depends critically on the ability of the sensors to determine their positions, which may be drastically impaired if the positioning pilot signals are affected by multi-path channels. An alternative location-free approach was recently proposed for spectrum power maps, where the input variable to the maps…
Data-Driven Spectrum Cartography via Deep Completion Autoencoders
2019
Spectrum maps, which provide RF spectrum metrics such as power spectral density for every location in a geographic area, find numerous applications in wireless communications such as interference control, spectrum management, resource allocation, and network planning to name a few. Spectrum cartography techniques construct these maps from a collection of measurements collected by spatially distributed sensors. Due to the nature of the propagation of electromagnetic waves, spectrum maps are complicated functions of the spatial coordinates. For this reason, model-free approaches have been preferred. However, all existing schemes rely on some interpolation algorithm unable to learn from data. …
Learning Automata Based Q-learning for Content Placement in Cooperative Caching
2019
An optimization problem of content placement in cooperative caching is formulated, with the aim of maximizing sum mean opinion score (MOS) of mobile users. Firstly, a supervised feed-forward back-propagation connectionist model based neural network (SFBC-NN) is invoked for user mobility and content popularity prediction. More particularly, practical data collected from GPS-tracker app on smartphones is tackled to test the accuracy of mobility prediction. Then, a learning automata-based Q-learning (LAQL) algorithm for cooperative caching is proposed, in which learning automata (LA) is invoked for Q-learning to obtain an optimal action selection in a random and stationary environment. It is p…
Understanding Situational Disabilities and Situational Awareness in Disasters
2019
In this paper, a scenario-based approach augmented with personas typically used in universal design and interactive design domains is used to illustrate the occurrence of situational disabilities in emergency situations, and to show how environmental factors can trigger these situational disabilities. With the help of personas representing selected archetypical characteristics and roles, the scenarios are further examined to show how these situational disabilities can affect the situational awareness of different stakeholders, not only in the command and control centers, but also first responders in the field as well as affected members of the public. This approach provides a better underst…
Capacity driven small cell deployment in heterogeneous cellular networks : Outage probability and rate coverage analysis
2020
Author's accepted manuscript. This is the peer reviewed version of the following article: Ullah, A., Haq Abbas, Z., Muhammad, F., Abbas, G. & Lei, J. (2020). Capacity driven small cell deployment in heterogeneous cellular networks: Outage probability and rate coverage analysis. Transactions on Emerging Telecommunications Technologies, 31(6): e3876, which has been published in final form at https://doi.org/10.1002/ett.3876. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
Quantum computing challenges in the software industry. A fuzzy AHP-based approach
2022
Context The current technology revolution has posed unexpected challenges for the software industry. In recent years, the field of quantum computing (QC) technologies has continued to grow in influence and maturity, and it is now poised to revolutionise software engineering. However, the evaluation and prioritisation of QC challenges in the software industry remain unexplored, relatively under-identified and fragmented. Objective The purpose of this study is to identify, examine and prioritise the most critical challenges in the software industry by implementing a fuzzy analytic hierarchy process (F-AHP). Method First, to identify the key challenges, we conducted a systematic literature rev…
Biometric Fish Classification of Nordic Species Using Convolutional Neural Network with Squeeze-and-Excitation
2018
Master's thesis Information- and communication technology IKT590 - University of Agder 2018 Squeeze-and-Excitation (SE) is a technique within convolutional neural networks (CNN) that can be applied to existing CNNs by applying fullyconnected layers between convolutional layers and merging the outputs. SE was the winning architecture of the ImageNet Large Scale Visual Recognition Challenge (ILSVRC) in 2017. In this thesis, we propose a CNN using the SE architecture for classifying images of sh. Previous work in the eld relies on applying lters to the images to separate the sh from the background or sharpen the images by removing background noise. The images from the dataset are extracted fro…