Search results for "VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550"
showing 10 items of 469 documents
Modelling and Control of a 2-DOF Robot Arm with Elastic Joints for Safe Human-Robot Interaction
2021
Collaborative robots (or cobots) are robots that can safely work together or interact with humans in a common space. They gradually become noticeable nowadays. Compliant actuators are very relevant for the design of cobots. This type of actuation scheme mitigates the damage caused by unexpected collision. Therefore, elastic joints are considered to outperform rigid joints when operating in a dynamic environment. However, most of the available elastic robots are relatively costly or difficult to construct. To give researchers a solution that is inexpensive, easily customisable, and fast to fabricate, a newly-designed low-cost, and open-source design of an elastic joint is presented in this w…
Indoor Space Classification Using Cascaded LSTM
2020
Author's accepted manuscript. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Indoor space classification is an important part of localization that helps in precise location extraction, which has been extensively utilized in industrial and domestic domain. There are various approaches that employ Bluetooth Low Energy (BLE), Wi-Fi, magnetic field, object detecti…
Hidden Markov Model Based Machine Learning for mMTC Device Cell Association in 5G Networks
2019
Massive machine-type communication (mMTC) is expected to play a pivotal role in emerging 5G networks. Considering the dense deployment of small cells and the existence of heterogeneous cells, an MTC device can discover multiple cells for association. Under traditional cell association mechanisms, MTC devices are typically associated with an eNodeB with highest signal strength. However, the selected eNodeB may not be able to handle mMTC requests due to network congestion and overload. Therefore, reliable cell association would provide a smarter solution to facilitate mMTC connections. To enable such a solution, a hidden Markov model (HMM) based machine learning (ML) technique is proposed in …
An Empirical Investigation of Performance Overhead in Cross-Platform Mobile Development Frameworks
2020
AbstractThe heterogeneity of the leading mobile platforms in terms of user interfaces, user experience, programming language, and ecosystem have made cross-platform development frameworks popular. These aid the creation of mobile applications – apps – that can be executed across the target platforms (typically Android and iOS) with minimal to no platform-specific code. Due to the cost- and time-saving possibilities introduced through adopting such a framework, researchers and practitioners alike have taken an interest in the underlying technologies. Examining the body of knowledge, we, nonetheless, frequently encounter discussions on the drawbacks of these frameworks, especially with regard…
Reliable Underlay Device-to-Device Communications on Multiple Channels
2019
Device-to-device (D2D) communications provide a substantial increase in spectrum usage and efficiency by allowing nearby users to communicate directly without passing their packets through the base station (BS). In previous works, proper channel assignment and power allocation algorithms for sharing of channels between cellular users and D2D pairs, usually require exact knowledge of the channel-state-information (CSI). However, due to the non-stationary wireless environment and the need to limit the communication and computation overheads, obtaining perfect CSI in the D2D communication scenario is generally not possible. In this work, we propose a joint channel assignment and power allocati…
Real Models are Really on M0 - Or How to Make Programmers Use Modeling
2020
This paper discusses the term ’model’ and the role of the level M0 in the four-layer metamodeling architecture of MOF/OMG. It illustrates the failures of the OMG MOF standard and how a model is an abstraction, not a description. We apply two simple approaches: (1) observing the use of models (of real or planned systems) in system development, including prototyping, simulations, and models in general, and (2) comparing modeling with programming. These approaches lead to the conclusion that models should be placed on M0, while UML models are model descriptions. This conclusion leads to a better understanding of InstanceSpecification for description of snapshots, and of metamodeling applied to…
Dynamic Flow-Adaptive Spectrum Leasing with Channel Aggregation in Cognitive Radio Networks.
2020
Cognitive radio networks (CRNs), which allow secondary users (SUs) to dynamically access a network without affecting the primary users (PUs), have been widely regarded as an effective approach to mitigate the shortage of spectrum resources and the inefficiency of spectrum utilization. However, the SUs suffer from frequent spectrum handoffs and transmission limitations. In this paper, considering the quality of service (QoS) requirements of PUs and SUs, we propose a novel dynamic flow-adaptive spectrum leasing with channel aggregation. Specifically, we design an adaptive leasing algorithm, which adaptively adjusts the portion of leased channels based on the number of ongoing and buffered PU …
An exploration of semi-supervised text classification
2021
Master's thesis in Information- and communication technology (IKT590) Obtaining labeled data to train natural language machine learning algorithms is often expensive and time-consuming, while unlabeled data usually is free and easy to get. Frequently a large amount of labeled data is required by supervised learning to achieve good text classification performance. Semi-supervised learning (SSL) for text classification is an exciting area of research. SSL is a technique exploiting unlabeled and labeled data to achieve better classification performance than using labeled data alone and is particularly useful with limited labeled data. This thesis explores the impact of different parameters on …
Generative Adversarial Networks for Improving Face Classification
2017
Master's thesis Information- and communication technology IKT590 - University of Agder 2017 Facial recognition can be applied in a wide variety of cases, including entertainment purposes and biometric security. In this thesis we take a look at improving the results of an existing facial recognition approach by utilizing generative adversarial networks to improve the existing dataset. The training data was taken from the LFW dataset[4] and was preprocessed using OpenCV[2] for face detection. The faces in the dataset was cropped and resized so every image is the same size and can easily be passed to a convolutional neural network. To the best of our knowledge no generative adversarial network…
More than experience? On the unique opportunities of virtual reality to afford a holistic experiential learning cycle
2021
Virtual reality has been proposed as a promising technology for higher education since the combination of immersive and interactive features enables experiential learning. However, previous studies did not distinguish between the different learning modes of the four-stage experiential learning cycle (i.e., concrete experience, reflective observation, abstract conceptualization, and active experimentation). With our study, we contribute a deeper understanding of how the unique opportunities of virtual reality can afford each of the four experiential learning modes. We conducted three design thinking workshops with interdisciplinary teams of students and lecturers. These workshops resulted in…