Viser treff 61-80 av 955

    • Semantic Modeling, Development and Evaluation for the Resistance Spot Welding Industry 

      Yahya, Muhammad; Zhou, Baifan; Breslin, John G.; Ali, Muhammad Intizar; Kharlamov, Evgeny (Peer reviewed; Journal article, 2023)
      The ongoing industrial revolution termed Industry 4.0 (I4.0) has borne witness to a series of profound changes towards increasing smart automation, particularly in the industrial sectors of automotive, aerospace, manufacturing, ...
    • Real-Time Event Detection with Random Forests and Temporal Convolutional Networks for More Sustainable Petroleum Industry 

      Qu, Yuanwei; Zhou, Baifan; Waaler, Arild Torolv Søetorp; Cameron, David B. (Journal article, 2023)
      The petroleum industry is crucial for modern society, but the production process is complex and risky. During the production, accidents or failures, resulting from undesired production events, can cause severe environmental ...
    • Random Testing and Evolutionary Testing for Fuzzing GraphQL APIs 

      Belhadi, Asma; Zhang, Man; Arcuri, Andrea (Peer reviewed; Journal article, 2023)
      The Graph Query Language (GraphQL) is a powerful language for APIs manipulation in web services. It has been recently introduced as an alternative solution for addressing the limitations of RESTful APIs. This paper introduces ...
    • Experience with the use of a digital sleep diary in symptom management by individuals with insomnia -a pilot mixed method study 

      Thorshov, Thea Christine; Øverby, Caroline Tonje; Hansen, Diana Dobran; Bong, Way Kiat; Skifjeld, Knut; Hurlen, Petter; Dammen, Toril; Moen, Anne; Hrubos-Strøm, Harald (Peer reviewed; Journal article, 2023)
      Background: Insomnia is the most common sleep disorder. The recommended treatment is cognitive behavioural therapy for insomnia (CBTi). A sleep diary is a core tool in CBTi. We have developed a digital sleep diary with ...
    • A Deep Diagnostic Framework Using Explainable Artificial Intelligence and Clustering 

      Thunold, Håvard Horgen; Riegler, Michael; Yazidi, Anis; Hammer, Hugo Lewi (Peer reviewed; Journal article, 2023)
      An important part of diagnostics is to gain insight into properties that characterize a disease. Machine learning has been used for this purpose, for instance, to identify biomarkers in genomics. However, when patient ...
    • Identifying Important Proteins in Meibomian Gland Dysfunction with Explainable Artificial Intelligence 

      Storås, Andrea; Magnø, Morten Schjerven; Fineide, Fredrik; Thiede, Bernd; Chen, Xiangjun; Strumke, Inga; Halvorsen, Pål; Utheim, Tor Paaske; Riegler, Michael Alexander (Peer reviewed; Journal article, 2023)
      Meibomian gland dysfunction is the most common cause of dry eye disease and leads to significantly reduced quality of life and social burdens. Because meibomian gland dysfunction results in impaired function of the tear ...
    • S-Divergence-Based Internal Clustering Validation Index 

      Sharma, Krishna Kumar; Seal, Ayan; Yazidi, Anis; Krejcar, Ondrej (Peer reviewed; Journal article, 2023)
      A clustering validation index (CVI) is employed to evaluate an algorithm’s clustering results. Generally, CVI statistics can be split into three classes, namely internal, external, and relative cluster validations. Most ...
    • Exchange energies with forces in density-functional theory 

      Tancogne-Dejean, Nicolas; Penz, Markus; Laestadius, Andre; Csirik, Mihaly Andras; Ruggenthaler, Michael; Rubio, Angel (Peer reviewed; Journal article, 2024)
      We propose exchanging the energy functionals in ground-state density-functional theory with physically equivalent exact force expressions as a new promising route toward approximations to the exchange–correlation potential ...
    • Literal-Aware Knowledge Graph Embedding for Welding Quality Monitoring: A Bosch Case 

      Tan, Zhipeng; Zhou, Baifan; Zheng, Zhuoxun; Savkovic, Ognjen; Huang, Ziqiang; Gonzalez, Irlan-Grangel; Soylu, Ahmet; Kharlamov, Evgeny (Lecture Notes in Computer Science (LNCS);, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Recently there has been a series of studies in knowledge graph embedding (KGE), which attempts to learn the embeddings of the entities and relations as numerical vectors and mathematical mappings via machine learning (ML). ...
    • Investigating Rules and Parameters of Reservoir Computing with Elementary Cellular Automata, with a Criticism of Rule 90 and the Five-Bit Memory Benchmark 

      Glover, Tom Eivind; Lind, Pedro; Yazidi, Anis; Osipov, Evgeny; Nichele, Stefano (Peer reviewed; Journal article, 2023)
      Reservoir computing with cellular automata (ReCAs) is a promising concept by virtue of its potential for effective hardware implementation. In this paper, we explore elementary cellular automata rules in the context of ...
    • "Consent notices are obstructing my view”: Viewing sticky elements on responsive websites under the magnifying glass 

      Sandnes, Frode Eika (Peer reviewed; Journal article, 2023)
      The practice of using consent notices on websites has received much criticism and attention among researchers. Much of the research has addressed unethical aspects of consent notices while less attention has been devoted ...
    • Scaling Data Science Solutions with Semantics and Machine Learning: Bosch Case 

      Zhou, Baifan; Nikolov, Nikolay Vladimirov; Zheng, Zhuoxun; Luo, Xianghui; Savkovic, Ognjen; Roman, Dumitru; Soylu, Ahmet; Kharlamov, Evgeny (Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Industry 4.0 and Internet of Things (IoT) technologies unlock unprecedented amount of data from factory production, posing big data challenges in volume and variety. In that context, distributed computing solutions such ...
    • A Reference Data Model to Specify Event Logs for Big Data Pipeline Discovery 

      Benvenuti, Dario; Marrella, Andrea; Rossi, Jacopo; Nikolov, Nikolay Vladimirov; Roman, Dumitru; Soylu, Ahmet; Perales, Fernando (Lecture Notes in Business Information Processing;, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      State-of-the-art approaches for managing Big Data pipelines assume their anatomy is known by design and expressed through adhoc Domain-Specific Languages (DSLs), with insufficient knowledge of the dark data involved in the ...
    • Performance Evaluation and Comparison of Microservices and Serverless Deployments in Cloud 

      Shrestha, Raju; Nisha, Beebu (IEEE International Conference on Smart Cloud (SmartCloud);, Chapter; Peer reviewed; Conference object, 2023)
      Microservices and serverless are arguably the two most widely used architectures today for deploying applications in the cloud. With both these technologies, applications can take advantage of faster delivery, lightweight, ...
    • Towards Cloud Storage Tier Optimization with Rule-Based Classification 

      Khan, Akif Quddus; Nikolov, Nikolay Vladimirov; Matskin, Mihhail; Prodan, Radu; Bussler, Christoph; Roman, Dumitru; Soylu, Ahmet (Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Cloud storage adoption has increased over the years as more and more data has been produced with particularly high demand for fast processing and low latency. To meet the users’ demands and to provide a cost-effective ...
    • Revisiting Redundant Text Color Coding in User Interfaces 

      Sandvold, Fredrik Strømsvåg; Schuller, Thomas; Rolfsvåg, Andreas; Sikkerbøl, Knut-Erik; Medola, Fausto Orsi; Sandnes, Frode Eika (Lecture Notes in Computer Science;, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Practices for using redundant text color in user interfaces vary. Some designers have carefully incorporated redundant coding in their design, while in other instances redundant coding is not utilized. There is a vast body ...
    • Exploring the Usability of the LCH Color Model for Web Designers 

      Sandnes, Frode Eika (Lecture Notes in Computer Science;, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Although the LCH color models have been around for many years, it has just recently been included in web specifications and is currently being implemented by browser vendors. Several voices argue that the LCH color model ...
    • A Comparison of Form Navigation with Tabbing and Pointing 

      Ferner, Bernt; Gåsøy, Adrian; Nicolaysen, Martin Walberg; Sandnes, Frode Eika (Lecture Notes in Computer Science;, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      The form is a widely used metaphor in information gathering. Users typically navigate between form elements using a keyboard or a pointing device. This study set out to empirically compare tabbing and pointing in form ...
    • Can we identify prominent scholars using ChatGPT? 

      Sandnes, Frode Eika (Scientometrics;, Peer reviewed; Journal article, 2023)
      It may be tempting to learn about scholars using ChatGPT. To validate ChatGPT for this task a small experiment was conducted based on the 50 most cited researchers at the author’s university. The results show that ChatGPT ...
    • Towards “Image Reflow” on the Web: Avoiding Excessive Panning of Magnified Images by Multiplexing Automatically Cropped Regions of Interest 

      Sandnes, Frode Eika (Lecture Notes in Computer Science;, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Low vision users are often faced with large images when increasing the browser zoom level. Large images extending beyond the viewport are difficult to view due to the excessive two-dimensional panning involved. This demo ...