Search results for "VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550"

Hierarchical Object Detection applied to Fish Species

2022

Gathering information of aquatic life is often based on timeconsuming methods utilizing video feeds. It would be beneficial to capture more information cost-effectively from video feeds. Video based object detection has an ability to achieve this. Recent research has shown promising results with the use of YOLO for object detection of fish. As underwater conditions can be difficult and thus fish species are hard to discriminate. This study proposes a hierarchical structure-based YOLO Fish algorithm in both the classification and the dataset to gain valuable information. With the use of hierarchical classification and other techniques. YOLO Fish is a state-of-the-art object detector on Nordi…

Robust Interpretable Text Classification against Spurious Correlations Using AND-rules with Negation

2022

The state-of-the-art natural language processing models have raised the bar for excellent performance on a variety of tasks in recent years. However, concerns are rising over their primitive sensitivity to distribution biases that reside in the training and testing data. This issue hugely impacts the performance of the models when exposed to out-of-distribution and counterfactual data. The root cause seems to be that many machine learning models are prone to learn the shortcuts, modelling simple correlations rather than more fundamental and general relationships. As a result, such text classifiers tend to perform poorly when a human makes minor modifications to the data, which raises questi…

Affinity-Based Reinforcement Learning : A New Paradigm for Agent Interpretability

2023

The steady increase in complexity of reinforcement learning (RL) algorithms is accompanied by a corresponding increase in opacity that obfuscates insights into their devised strategies. Methods in explainable artificial intelligence seek to mitigate this opacity by either creating transparent algorithms or extracting explanations post hoc. A third category exists that allows the developer to affect what agents learn: constrained RL has been used in safety-critical applications and prohibits agents from visiting certain states; preference-based RL agents have been used in robotics applications and learn state-action preferences instead of traditional reward functions. We propose a new affini…

Hand Gesture Classification Using Grayscale Thermal Images and Convolutional Neural Network

2021

Accepted manuscript.

On abstraction in the OMG hierarchy: systems, models, and descriptions

2022

The Model-Driven Architecture (MDA) uses a metadata hierarchy with several layers that are placed on top of each other. The traditional view is that the layers provide abstractions related to models in languages defined by meta-models. Over the years, it has been difficult to define a consistent understanding of the layers. In this paper, we propose such a consistent understanding by clarifying the relations between the different elements in the hierarchy. This is done based on the Scandinavian approach to modelling that distinguishes between systems and system descriptions. Systems can be physical, digital, or even mental, while descriptions can be programs, language descriptions, specific…

LONG HORIZON ANOMALY PREDICTION IN MULTIVARIATE TIME SERIES WITH CAUSAL AUTOENCODERS

2022

Predictive maintenance is essential for complex industrial systems to foresee anomalies before major system faults or ultimate breakdown. However, the existing efforts on Industry 4.0 predictive monitoring are directed at semi-supervised anomaly detection with limited robustness for large systems, which are often accompanied by uncleaned and unlabeled data. We address the challenge of predicting anomalies through data-driven end-to-end deep learning models using early warning symptoms on multivariate time series sensor data. We introduce AnoP, a long multi-timestep anomaly prediction system based on unsupervised attention-based causal residual networks, to raise alerts for anomaly preventio…

MMSS: A storytelling simulation software to mitigate misinformation on social media

2022

This paper proposes a modular python implementation of a storytelling simulation. The software evaluates misinformation mitigation strategies over social media and visualizes the investigated scenarios’ potential outcomes. Our software integrates information diffusion and control models components. The control model mitigates users’ exposure to misinformation with social fairness awareness, while the diffusion model predicts the outcome from the control model. During the interaction of both models, a graph coloring algorithm traces the interaction within specific time intervals. Then, it generates meta-data to construct visuals of predicted near-future states of the social network to help s…

Multichannel Management in the Public Sector: A Literature Review

2019

Investigating the User Experience of Virtual Reality Rehabilitation Solution for Biomechatronics Laboratory and Home Environment

2021

Virtual reality (VR) technology is a promising tool in physical rehabilitation. Research indicates that VR-supported rehabilitation is beneficial for task-specific training, multi-sensory feedback, diversified rehabilitation tasks, and patient motivation. Our first goal was to create a biomechatronics laboratory with a VR setup for increasing immersion and a motion platform to provide realistic feedback to patients. The second goal was to investigate possibilities to replicate features of the biomechatronics laboratory in a home-based training system using commercially available components. The laboratory comprises of a motion platform with 6-degrees-of-freedom (Rexroth eMotion), fitted wit…

Development and Testing of Web GUI Application for the LHCb VELO Data Quality Monitoring System

2014

Masteroppgave i informasjons- og kommunikasjonsteknologi IKT590 Universitetet i Agder 2013 A great interest of IT engineers at CERN is to simplify the access to the Data Quality Monitoring(DQM) applications that usually lay behind several layers of security firewalls. In order to makeit simple and thus help to save time for the scientist who rely on this data, additional applicationfor the Web had to be developed and tested. The goal of this thesis work was to developsuch a Web DQM application for CERN. First, a Web Graphical User Interface (GUI) wasdeveloped. In parallel, an Apache server was installed and configured for testing. Moreover,software program called ROOTJS that processes and d…