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Process Mining over Unordered Event Streams
Published 2020“…This requires online algorithms that, instead of keeping the whole history of event data, work incrementally and update analysis results upon the arrival of new events. …”
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I Will Survive: An Event-driven Conformance Checking Approach Over Process Streams
Published 2023“…Finally, the algorithm is stress tested for performance using a simulation of high-traffic event streams.…”
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Efficient Approximate Conformance Checking Using Trie Data Structures
Published 2021“…Conformance checking compares a process model and recorded executions of a process, i.e., a log of traces. …”
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Generic metadata representation framework for social-based event detection, description, and linkage
Published 2020“…SEDDaL consists of four main modules for: i) describing social media objects in a generic Metadata Representation Space Model (MRSM) consisting of three composite dimensions: temporal, spatial, and semantic, ii) evaluating the similarity between social media objects’ descriptions following MRSM, iii) detecting events from similar social media objects using an adapted unsupervised learning algorithm, where events are represented as clusters of objects in MRSM, and iv) identifying directional, metric, and topological relationships between events following MRSM’s dimensions. …”
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Prediction of EV Charging Behavior Using Machine Learning
Published 2021“…Therefore, in this paper we propose the usage of historical charging data in conjunction with weather, traffic, and events data to predict EV session duration and energy consumption using popular machine learning algorithms including random forest, SVM, XGBoost and deep neural networks. …”
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Metaheuristic Algorithm for State-Based Software Testing
Published 2018“…This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. …”
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Metaheuristic algorithm for testing web 2.0 applications. (c2012)
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Reconfigured Photovoltaic Model to Facilitate Maximum Power Point Tracking for Micro and Nano-Grid Systems
Published 2022“…Performance of the proposed reconfiguration model is tested for four various shade events and its row current evaluations are comprehensively analyzed. …”
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Boosting the visibility of services in microservice architecture
Published 2023“…We utilized parameter optimization techniques, namely Grid Search, Random Search, Bayes Search, Halvin Grid Search, and Halvin Random Search to fine-tune the hyperparameters of our classifier models. Experimental results demonstrated that the CatBoost algorithm achieved the highest level of accuracy (90.42%) in predicting microservice quality.…”
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Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
Published 2023“…The use of such biomarkers to monitor glycemic events represents a major shift in technology for self-monitoring and developing digital biomarkers using non-invasive WDs. …”
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Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d...
Published 2020“…This model accurately estimated normal glucose levels in 2584/2715 (95.2%) readings and hyperglycaemic events in 852/1031 (82.6%) readings, but fewer hypoglycaemic events (48/172 (27.9%)). …”
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Cost-Benefit Analysis of Genotype-Guided Interruption Days in Warfarin Pre-Procedural Management
Published 2022“…The cost of the algorithm was the cost of the genotyping assay. The model event probability inputs were extracted from major literature clinical trials, and the setting-specifc and cost inputs were locally obtained. …”
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Cost-Benefit Analysis of Genotype-Guided Interruption Days in Warfarin Pre-Procedural Management
Published 2023“…The cost of the algorithm was the cost of the genotyping assay. The model event probability inputs were extracted from major literature clinical trials, and the setting-specifc and cost inputs were locally obtained. …”