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 |
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 |
Opportunistic CPU sharing in Mobile Edge Computing deploying the Cloud-RAN
IEEE Transactions on Network and Service Management (2023).Status: Accepted
Opportunistic CPU sharing in Mobile Edge Computing deploying the Cloud-RAN
| Afilliation | Communication Systems |
| Project(s) | The Center for Resilient Networks and Applications, SMIL: SimulaMet Interoperability Lab |
| Publication Type | Journal Article |
| Year of Publication | 2023 |
| Journal | IEEE Transactions on Network and Service Management |
| Publisher | IEEE |
| Keywords | Cloud-RAN, Containers, Mobile edge computing, resource management |
| DOI | 10.1109/TNSM.2023.3304067 |
Online Joint Topology Identification and Signal Estimation from Streams with Missing Data
IEEE Transactions on Signal and Information Processing over Networks (2023).Status: Accepted
Online Joint Topology Identification and Signal Estimation from Streams with Missing Data
| Afilliation | Machine Learning |
| Project(s) | Signal and Information Processing for Intelligent Systems |
| Publication Type | Journal Article |
| Year of Publication | 2023 |
| Journal | IEEE Transactions on Signal and Information Processing over Networks |
| Publisher | IEEE Transactions on Signal and Information Processing over Networks |
| Notes | This work is a joint collaboration between SimulaMet and University of Agder. This work was supported by the SFI Offshore Mechatronics grant 237896/O30 from the Research Council of Norway. |
Journal articles
Cell exclusion during human embryo development result in altered morphokinetic patterns up to morula formation
Human Reproduction (2022).Status: Accepted
Cell exclusion during human embryo development result in altered morphokinetic patterns up to morula formation
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Journal Article |
| Year of Publication | 2022 |
| Journal | Human Reproduction |
| Publisher | Human Reproduction |
Journal articles
Measuring Roaming in Europe: Infrastructure and Implications on Users’ QoE
IEEE Transactions on Mobile Computing (2021).Status: Accepted
Measuring Roaming in Europe: Infrastructure and Implications on Users’ QoE
| Afilliation | Communication Systems |
| Project(s) | Department of Mobile Systems and Analytics |
| Publication Type | Journal Article |
| Year of Publication | 2021 |
| Journal | IEEE Transactions on Mobile Computing |
| Publisher | IEEE |
Energy Efficient AoI Minimization in Opportunistic NOMA/OMA Broadcast Wireless Networks
IEEE Transactions on Green Communications and Networking (2021).Status: Accepted
Energy Efficient AoI Minimization in Opportunistic NOMA/OMA Broadcast Wireless Networks
The concept of Age of Information (AoI) minimization in wireless networks has garnered huge interest in recent times. While current literature focuses on scheduling for AoI minimization, there is also a need to efficiently utilize the underlying physical layer resources. In this paper, we consider the problem of energy-efficient scheduling for AoI minimization in an opportunistic NOMA/OMA downlink broadcast wireless network, where the user equipment operate with diverse QoS requirements. We first formulate a resource allocation problem to minimize the average AoI of the network, with energy-efficiency factored in by restricting the long term average transmit power to a predetermined threshold. A heuristic adaptation of the driftplus-penalty approach from the Lyapunov framework is then utilized to solve the original long-term mixed-integer nonlinear problem on a per time-slot basis. The single time-slot problem is further decomposed into multiple sub-problems, solving for power allocation and user scheduling separately. However, the attained power allocation sub-problems being non-convex, we propose an efficient piece-wise linear approximation to obtain a tractable solution. The scheduling sub-problem is solved optimally by using the integrality property of the linear program. Finally, we provide extensive numerical simulations to show that our proposed approach outperforms the state of the art.
| Afilliation | Communication Systems |
| Project(s) | Signal and Information Processing for Intelligent Systems |
| Publication Type | Journal Article |
| Year of Publication | 2021 |
| Journal | IEEE Transactions on Green Communications and Networking |
| Publisher | IEEE |
| Place Published | IEEE Transactions on Green Communications and Networking |
| Notes | This research work was carried out at University of Agder and completed after the SIGIPRO Department was created. This work was supported by the Research Council of Norway through FRIPRO TOPPFORSK under Grant WISECART 250910/F20. |
| DOI | 10.1109/TGCN.2021.3135351 |
DeepFake electrocardiograms: the key for open science for artificial intelligence in medicine
Scientific Reports (2021).Status: Accepted
DeepFake electrocardiograms: the key for open science for artificial intelligence in medicine
Recent global developments underscore the prominent role big data have in modern medical science. Privacy issues are a prevalent problem for collecting and sharing data between researchers. Synthetic data generated to represent real data carrying similar information and distribution may alleviate the privacy issue.In this study, we present generative adversarial networks (GANs) capable of generating realistic synthetic DeepFake 12-lead 10-sec electrocardiograms (ECGs). We have developed and compare two methods, WaveGAN* and Pulse2Pulse GAN. We trained the GANs with 7,233 real normal ECG to produce 121,977 DeepFake normal ECGs. By verifying the ECGs using a commercial ECG interpretation program (MUSE 12SL, GE Healthcare), we demonstrate that the Pulse2Pulse GAN was superior to the WaveGAN to produce realistic ECGs. ECG intervals and amplitudes were similar between the DeepFake and real ECGs. These synthetic ECGs are fully anonymous and cannot be referred to any individual, hence they may be used freely. The synthetic dataset will be available as open access for researchers at OSF.io and the DeepFake generator available at the Python Package Index (PyPI) for generating synthetic ECGs.In conclusion, we were able to generate realistic synthetic ECGs using adversarial neural networks on normal ECGs from two population studies, i.e., there by addressing the relevant privacy issues in medical datasets.Competing Interest StatementThe authors have declared no competing interest.Clinical TrialN/AFunding StatementThis work is funded in part by Novo Nordisk Foundation project number NNF18CC0034900.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:We confirm that all experiments were performed in accordance with Helsinki guidelines and regulations of the Danish Regional Committees for Medical and Health Research Ethics. The data studies were approved by the ethical committee of Region Zealand (SJ-113, SJ-114, SJ-191), ethical committee of Copenhagen Amt (KA 98 155).All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesThe Normal DeepFake ECGs are available at OSF (https://osf.io/6hved/) with corresponding MUSE 12SL ground truth values freely downloadable and usable for ECG algorithm development. The DeepFake generative model is available at https://pypi.org/project/deepfake-ecg/ to generate only synthetic ECGs. https://osf.io/6hved/ https://pypi.org/project/deepfake-ecg/
| Afilliation | Scientific Computing, Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Journal Article |
| Year of Publication | 2021 |
| Journal | Scientific Reports |
| Publisher | Nature Publishing Group |
| URL | https://www.medrxiv.org/content/early/2021/05/10/2021.04.27.21256189.1 |
| DOI | 10.1101/2021.04.27.21256189 |
Journal articles
Equivalence projective simulation as a framework for modeling formation of stimulus equivalence classes
Neural computation 32 (2020): 912-968.Status: Accepted
Equivalence projective simulation as a framework for modeling formation of stimulus equivalence classes
Stimulus equivalence (SE) and projective simulation (PS) study complex behavior, the former in human subjects and the latter in artificial agents. We apply the PS learning framework for modeling the formation of equivalence classes. For this purpose, we first modify the PS model to accommodate imitating the emergence of equivalence relations. Later, we formulate the SE formation through the matching-to-sample (MTS) procedure. The proposed version of PS model, called the equivalence projective simulation (EPS) model, is able to act within a varying action set and derive new relations without receiving feedback from the environment. To the best of our knowledge, it is the first time that the field of equivalence theory in behavior analysis has been linked to an artificial agent in a machine learning context. This model has many advantages over existing neural network models. Briefly, our EPS model is not a black box model, but rather a model with the capability of easy interpretation and flexibility for further modifications. To validate the model, some experimental results performed by prominent behavior analysts are simulated. The results confirm that the EPS model is able to reliably simulate and replicate the same behavior as real experiments in various settings, including formation of equivalence relations in typical participants, nonformation of equivalence relations in language-disabled children, and nodal effect in a linear series with nodal distance five. Moreover, through a hypothetical experiment, we discuss the possibility of applying EPS in further equivalence theory research.
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Journal Article |
| Year of Publication | 2020 |
| Journal | Neural computation |
| Volume | 32 |
| Number | 5 |
| Pagination | 912–968 |
| Publisher | {MIT Press |
Equivalence projective simulation as a framework for modeling formation of stimulus equivalence classes
Neural computation 32 (2020): 912-968.Status: Accepted
Equivalence projective simulation as a framework for modeling formation of stimulus equivalence classes
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Journal Article |
| Year of Publication | 2020 |
| Journal | Neural computation |
| Volume | 32 |
| Number | 5 |
| Pagination | 912–968 |
| Publisher | {MIT Press One Rogers Street, Cambridge, MA 02142-1209, USA journals-info … |