OSUVAfi=Vaasan yliopiston julkaisuarkisto|en=The University of Vaasa publications archive|https://osuva.uwasa.fi:443/handle/123456789/22024-03-28T15:19:28Z2024-03-28T15:19:28ZDay-Ahead Parametric Probabilistic Forecasting of Wind and Solar Power Generation using Bounded Probability Distributions and Hybrid Neural NetworksKonstantinou, TheodorosHatziargyriou, Nikoshttps://osuva.uwasa.fi:443/handle/10024/170802024-03-27T09:00:06Z2023-04-27T00:00:00ZDay-Ahead Parametric Probabilistic Forecasting of Wind and Solar Power Generation using Bounded Probability Distributions and Hybrid Neural Networks
Konstantinou, Theodoros; Hatziargyriou, Nikos
The penetration of renewable energy sources in modern power systems increases at an impressive rate. Due to their intermittent and uncertain nature, it is important to forecast their generation including its uncertainty. In this article, an ensemble artificial neural network is applied for day ahead solar and wind power generation parametric probabilistic forecasting. The proposed architecture includes two components: a sub-models component and a Meta-Learner component. The first component includes an ensemble of artificial neural networks that have the ability to estimate the parameters of an underlying probability distribution. The Meta-Learner is responsible for grouping the training samples based on the estimated level of generation, through a classification-clustering process and use the output of the corresponding sub-models to calculate the final parametric probabilistic estimation. The proposed model is compared to both parametric and non-parametric state of the art probabilistic techniques for solar and wind power generation forecasting, exhibiting superior performance.
2023-04-27T00:00:00ZMulti-Area Frequency Restoration Reserve SizingPediaditis, PanagiotisPapamatthaiou, DimitriosPapadaskalopoulos, DimitriosPrešić, DušanHatziargyriou, Nikos D.https://osuva.uwasa.fi:443/handle/10024/170792024-03-27T09:00:07Z2023-02-06T00:00:00ZMulti-Area Frequency Restoration Reserve Sizing
Pediaditis, Panagiotis; Papamatthaiou, Dimitrios; Papadaskalopoulos, Dimitrios; Prešić, Dušan; Hatziargyriou, Nikos D.
Frequency Restoration Reserves are traditionally sized using deterministic methods. The constant growth in non-dispatchable renewable energy, however, is increasing the importance of probabilistic methods for reserve sizing. In addition, as the geographical scope of reserve sizing expands, overall power imbalance stochasticity is reduced. In this article, we propose a probabilistic method for shared cross-border frequency restoration reserve commitment and sizing, based on the concept of system generation margin and employing mathematical optimization. The aim is to reduce overall reserve volumes and costs. The cross-border interconnection capacities among countries are taken into account, and the shared uncertainty across interconnections is addressed via a novel robust approach. The method is tested on the cross-border system of south-east Europe that includes 9 countries. 5 different operational scenarios are used and a detailed calculation of the uncertainty distributions in each country is employed. Results show that cross-border shared sizing can significantly reduce overall reserve volumes and costs in a secure way.
2023-02-06T00:00:00ZDiagnostic Accuracy of MRI in Detecting the Perineural Spread of Head and Neck Tumors : A Systematic Review and Meta-AnalysisAbdullaeva, UmidaPape, BerndHirvonen, Jussihttps://osuva.uwasa.fi:443/handle/10024/170782024-03-25T14:00:08Z2024-01-04T00:00:00ZDiagnostic Accuracy of MRI in Detecting the Perineural Spread of Head and Neck Tumors : A Systematic Review and Meta-Analysis
Abdullaeva, Umida; Pape, Bernd; Hirvonen, Jussi
The purpose of this study was to review the diagnostic accuracy of MRI in detecting perineural spreading (PNS) of head and neck tumors using histopathological or surgical evidence from the afflicted nerve as the reference standard. Previous studies in the English language published in the last 30 years were searched from PubMed and Embase databases. We included studies that used magnetic resonance imaging (MRI) (with and without contrast enhancement) to detect PNS, as well as the histological or surgical confirmation of PNS, and that reported the exact numbers of patients required for assessing diagnostic accuracy. The outcome measures were sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Heterogeneity was assessed with the Higgins inconsistency test (I2). P-values smaller than 0.05 were considered statistically significant. A total of 11 retrospective studies were found, reporting 319 nerve samples from 245 patients. Meta-analytic estimates and their 95% confidence intervals were as follows: sensitivity 0.85 (0.70–0.95), specificity 0.85 (0.80–0.89), PPV 0.86 (0.70–0.94), and NPV 0.85 (0.71–0.93). We found statistically significant heterogeneity for sensitivity (I2 = 72%, p = 0.003) and PPV (I2 = 70%, p = 0.038), but not for NPV (I2 = 65%, p = 0.119) or specificity (I2 = 12%, p = 0.842). The most frequent MRI features of PNS were nerve enlargement and enhancement. Squamous cell carcinoma and adenoid cystic carcinoma were the most common tumor types, and the facial and trigeminal nerves were the most commonly affected nerves in PNS. Only a few studies provided examples of false MRI diagnoses. MRI demonstrated high diagnostic accuracy in depicting PNS of cranial nerves, yet this statement was based on scarce and heterogeneous evidence.
2024-01-04T00:00:00ZInformation Security Failures Measured and ISO/IEC 27001:2022 Controls Ranked by General Data Protection Regulation Penalty AnalysisSuorsa, MikkoHelo, Petrihttps://osuva.uwasa.fi:443/handle/10024/170722024-03-21T08:00:05Z2023-11-30T00:00:00ZInformation Security Failures Measured and ISO/IEC 27001:2022 Controls Ranked by General Data Protection Regulation Penalty Analysis
Suorsa, Mikko; Helo, Petri
Selecting the most important information security controls is a critical and difficult process. Therefore, the decision-making on how to manage risks and threats has to be supported with data-driven performance measurement metrics. This paper identifies and explores the failures and impacts of information security, as well as the most effective controls to mitigate information security risks in organizations. The method of the study was root cause analysis. All year 2020 GDPR penalty cases (n=81) based on misconduct, as defined in GDPR Article 32: “Security of processing” were matched with ISO/IEC 27001:2022 controls, which were used as failure identifiers in the analysis. As a result, the study presents both, the top 10 most frequent and the top 10 most expensive information security failures corresponding to ISO/IEC
27001:2022 controls. Furthermore, the study also illustrates the correlation of these controls.
2023-11-30T00:00:00Z