A database for publications published by researchers and students at SimulaMet.
Status
Research area
Journal articles
Live Streaming Technology and Online Child Sexual Exploitation and Abuse - A Scoping Review
Trauma, Violence, & Abuse (2023).Status: Accepted
Live Streaming Technology and Online Child Sexual Exploitation and Abuse - A Scoping Review
Livestreaming of child sexual abuse is an established form of online child sexual exploitation
and abuse. However, only a limited body of research has examined this issue. The Covid-19
pandemic has accelerated internet use and user knowledge of livestreaming services
emphasising the importance of understanding this crime. In this scoping review, existing
literature was brought together through an iterative search of eight databases containing peer-
reviewed journal articles, as well as grey literature. Records were eligible for inclusion if the
primary focus was on livestream technology and online child sexual exploitation and abuse,
the child being defined as eighteen years or younger. Fourteen of the 2,218 records were
selected. The data were charted and divided into four categories: victims, offenders,
legislation, and technology. Limited research, differences in terminology, study design, and
population inclusion criteria present a challenge to drawing general conclusions on the
current state of livestreaming of child sexual abuse. The records show that victims are
predominantly female. The average livestream offender was found to be older than the
average online child sexual abuse offender. Therefore, it is unclear whether the findings are
representative of the global population of livestream offenders. Furthermore, there appears to
be a gap in what the records show on platforms and payment services used and current digital
trends. The lack of a legal definition and privacy considerations pose a challenge to
investigation, detection, and prosecution. The available data allow some insights into a
potentially much larger issue.
Afilliation | Communication Systems, Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Journal Article |
Year of Publication | 2023 |
Journal | Trauma, Violence, & Abuse |
Publisher | SAGE Publications |
Unsupervised EHR-based Phenotyping via Matrix and Tensor Decompositions
WIREs Data Mining and Knowledge Discovery (2023).Status: Accepted
Unsupervised EHR-based Phenotyping via Matrix and Tensor Decompositions
Afilliation | Machine Learning |
Project(s) | Department of Data Science and Knowledge Discovery , DeCipher |
Publication Type | Journal Article |
Year of Publication | 2023 |
Journal | WIREs Data Mining and Knowledge Discovery |
Publisher | Wiley |
URL | https://arxiv.org/abs/2209.00322 |
Network-Aware RF-Energy Harvesting for Designing Energy Efficient IoT Networks
Elsevier Internet of Things 22 (2023).Status: Accepted
Network-Aware RF-Energy Harvesting for Designing Energy Efficient IoT Networks
Afilliation | Communication Systems |
Project(s) | Signal and Information Processing for Intelligent Systems |
Publication Type | Journal Article |
Year of Publication | 2023 |
Journal | Elsevier Internet of Things |
Volume | 22 |
Date Published | 07/2023 |
Publisher | Elsevier |
DOI | 10.1016/j.iot.2023.100770 |
Towards a Lightweight Task Scheduling Framework for Cloud and Edge Platform
Internet of Things; Engineering Cyber Physical Human Systems (2023).Status: Accepted
Towards a Lightweight Task Scheduling Framework for Cloud and Edge Platform
Mobile devices are becoming ubiquitous in our daily lives, but they have limited computational capacity. Thanks to the advancement in the network infrastructure, task offloading from resource-constrained devices to the near edge and the cloud becomes possible and advantageous. Complete task offloading is now possible to almost limitless computing resources of public cloud platforms. Generally, the edge computing resources support latency-sensitive applications with limited computing resources, while the cloud supports latency-tolerant applications. This paper proposes one lightweight task-scheduling framework from cloud service provider perspective, for applications using both cloud and edge platforms. Here, the challenge is using edge and cloud resources efficiently when necessary. Such decisions have to be made quickly, with a small management overhead. Our framework aims at solving two research questions. They are: i) How to distribute tasks to the edge resource pools and multi-clouds? ii) How to manage these resource pools effectively with low overheads? To answer these two questions, we examine the performance of our proposed framework based on Reliable Server Pooling (RSerPool). We have shown via simulations that RSerPool, with the correct usage and configuration of pool member selection policies, can accomplish the cloud/edge setup resource selection task with a small overhead.
Afilliation | Communication Systems |
Project(s) | The Center for Resilient Networks and Applications, Simula Metropolitan Center for Digital Engineering, Simula Metropolitan Center for Digital Engineering, NorNet, SMIL: SimulaMet Interoperability Lab |
Publication Type | Journal Article |
Year of Publication | 2023 |
Journal | Internet of Things; Engineering Cyber Physical Human Systems |
Publisher | Elsevier |
Keywords | Cloud computing, Edge Computing, Reliable Server Pooling (RSerPool), Resource Pools, Task Scheduling |
Proxy Path Scheduling and Erasure Reconstruction for Low Delay mmWave Communication
IEEE Communications Letters (2023).Status: Accepted
Proxy Path Scheduling and Erasure Reconstruction for Low Delay mmWave Communication
Afilliation | Communication Systems |
Project(s) | The Center for Resilient Networks and Applications, Information Theory Section |
Publication Type | Journal Article |
Year of Publication | 2023 |
Journal | IEEE Communications Letters |
Publisher | IEEE |
ISSN | 1558-2558 |
URL | https://ieeexplore.ieee.org/document/10107383 |
DOI | 10.1109/LCOMM.2023.3269526 |
Posters
Concept Explanations for Deep Learning-Based Diabetic Retinopathy Diagnosis
Nordic AI Meet 2023, 2023.Status: Accepted
Concept Explanations for Deep Learning-Based Diabetic Retinopathy Diagnosis
Diabetic retinopathy (DR) is a common complication of diabetes that damages the eye and potentially leads to blindness. The severity and treatment choice of DR depends on the presence of medical findings in fundus images. Much work has been done in developing complex machine learning (ML) models to automatically diagnose DR from fundus images. However, their high level of complexity increases the demand for techniques improving human understanding of the ML models. Explainable artificial intelligence (XAI) methods can detect weaknesses in ML models and increase trust among end users. In the medical field, it is crucial to explain ML models in order to apply them in the clinic. While a plethora of XAI methods exists, heatmaps are typically applied for explaining ML models for DR diagnosis. Heatmaps highlight image areas that are regarded as important for the model when making a prediction. Even though heatmaps are popular, they can be less appropriate in the medical field. Testing with Concept Activation Vectors (TCAV), providing explanations based on human-friendly concepts, can be a more suitable alternative for explaining models for DR diagnosis, but it has not been thoroughly investigated for DR models. We develop a deep neural network for diagnosing DR from fundus images and apply TCAV for explaining the resulting model. Concept generation with and without masking is compared. Based on diagnostic criteria for DR, we evaluate the model’s concept ranking for different severity levels of DR. TCAV can explain individual images to gain insight into a specific case, or an entire class to evaluate overall consistency with diagnostic standards. The most important concepts for the DR model agree with diagnostic criteria for DR. No large differences are detected between the two concept generation approaches. TCAV is a flexible explanation method where human-friendly concepts provide insights and trust in ML models for medical image analyses, and it shows promising results for DR grading.
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Poster |
Year of Publication | 2023 |
Place Published | Nordic AI Meet 2023 |
Keywords | concept-based explanations, diabetic retinopathy, Explainable artificial intelligence |
Proceedings, refereed
Multimedia datasets: challenges and future possibilities
In International conference on multimedia modeling, 2023.Status: Accepted
Multimedia datasets: challenges and future possibilities
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2023 |
Conference Name | International conference on multimedia modeling |
PRINCIPIA: Opportunistic CPU and CPU-shares Allocation for Containerized Virtualization in Mobile Edge Computing
In IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023.Status: Accepted
PRINCIPIA: Opportunistic CPU and CPU-shares Allocation for Containerized Virtualization in Mobile Edge Computing
Afilliation | Communication Systems |
Project(s) | The Center for Resilient Networks and Applications |
Publication Type | Proceedings, refereed |
Year of Publication | 2023 |
Conference Name | IEEE/IFIP Network Operations and Management Symposium |
Publisher | IEEE |
Location-free Indoor Radio Map Estimation using Transfer learning
In IEEE Vehicular Technology Conference. Florence: IEEE, 2023.Status: Accepted
Location-free Indoor Radio Map Estimation using Transfer learning
Afilliation | Machine Learning |
Project(s) | Signal and Information Processing for Intelligent Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2023 |
Conference Name | IEEE Vehicular Technology Conference |
Date Published | 2023 |
Publisher | IEEE |
Place Published | Florence |
Notes | This work is a joint collaboration between SimulaMet and University of Agder. This work was supported by the FRIPRO TOPPFORSK Grant WISECART 250910/F20 from the Research Council of Norway. |
A Survey on the Use and Effects of Goal Hierarchies in Digitalization Efforts
In Portland International Conference on Management of Engineering and Technology: Managing Technology, Engineering and Manufacturing for a Sustainable World (PICMET 2023), 2023.Status: Accepted
A Survey on the Use and Effects of Goal Hierarchies in Digitalization Efforts
Digitalization has become a primary goal for organizations. Successfully adopting the digital context both in daily operations and in business management and strategy entails great benefits at different levels (organizational, economic, social, environmental...). Thus, it is very important that practitioners have clear conceptions of the goals in this regard and that those goals are “alive” in organizations.
For this reason, in this study we present a survey that we performed among practitioners related to the management of Information Technology (IT) from both the private and public sectors in Norway. Through this survey we have tried to find out how organizations understand and translate the current context of digitalization from different goal levels. For that, we asked respondents to relate to one of three goal hierarchies: A) a classical governance approach; B) an organizational tier approach; and C) an effects-based approach.
Among the results obtained we found that the first two are the most used and the goal achievement is slightly higher for the classical governance approach than for the organizational tier approach. Likewise, we identified that while top level management has a good understanding of the goals, this understanding deteriorates as one moves down the organizational hierarchy.
Afilliation | Software Engineering |
Project(s) | Department of IT Management |
Publication Type | Proceedings, refereed |
Year of Publication | 2023 |
Conference Name | Portland International Conference on Management of Engineering and Technology: Managing Technology, Engineering and Manufacturing for a Sustainable World (PICMET 2023) |
Keywords | Digitalization, information technology, Management, strategy, sustainability |