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Model technology Service E-Participation - Voting (E-PV) for Political Communication between the Council of Regional Representatives (DPRD) and the Citizens Using the Framework Information technology Infrastructure Library (ITIL V.3) Transition Domain Service 7

Model Technology Service E-Participation - Voting (E-PV) for...

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7th International Conference on ICT for Smart Society, ICISS 2020

作者： Hilabi, Shofa Shofiah Harso Supangat, Suhono Hendric Spits Warnars, Harco Leslie Prabowo, Harjanto Mursitama, Tirta Nugraha Universitas Buana Perjuangan Faculty of Engineering and Computer Science Karawang Indonesia Institute of Technology Bandung School of Electrical Engineering and Informatics Bandung Indonesia Nusantara University Doctor of Computer Science Bina Computer Science Department BINUS Graduate Program Jakarta11530 Indonesia Bina Nusantara University Doctor of Computer Science Jakarta11530 Indonesia Bina Nusantara University Faculty of Humanities International Relations Department Jakarta11480 Indonesia

ISBN: (纸本)9781665404228

E-voting is an electronic voting information technology service, while E-participation is an information technology service for citizens of the public to provide reports, polls, or suggestions on government policies electronically. The technology Services E-Participation-VOT (EPV) model is a combined E-Participation and E-Voting service model. The concept of this service model is that citizens transform from E-participation and E-voting services into an EPV model. The purpose of this model is to provide information to participants (citizens) about online-based voting services. This method of developing the EP-Voting Anticipation (EPV) technology model uses agile methods that are effective and flexible in various cases of designing Information technology models for Information technology (IT) services that apply a Framework Information technology Infrastructure Library (ITIL). The results obtained from this study are an Information technology service system model that provides recommendations for participation in conducting electronic elections (E-Voting). © 2020 IEEE.

关键词： Surveys

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High Level Learning Approach for High Level Collision Avoidance Using Sensors

High Level Learning Approach for High Level Collision Avoida...

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Interdisciplinary Humanitarian Conference for Sustainability (IIHC), International

作者： Lamhot Naibaho Razauddin L. Vertivendan V. Karunakaran Ashish Oberoi N.C. Ajay Vishwath English Language Education Study Program Faculty of Letters and Languages Christian University of Indonesia Department of computer and information sciences Gulf Colleges Saudia Arabia Department of CSE Galgotias University Greater Noida Uttar Pradesh India Department of CSE Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore INDIA Department of CSE RIMT University Mandi Godindgarh India Aeronautical Department Parul Institute of Engineering and Technology Parul University

Motion planning for many unmanned aircraft is challenging because they have a larger configuration space than self-driving automobile development (Automated guided vehicles). Additionally, there are more significant uncertainties and disruptions in UAV environments, which makes inter automatic navigation more difficult. In this letter, I proposed a 2 recurrent neural networks (RL) oriented multi-UAV collision avoidance technique by modeling the unpredictability or noise in the environment. Our objective is to create a strategy that can construct a path without clashing with anything using local noisy data. But unlike supervised algorithms, RL lacks a steady training data set with floor labels, thus its collision avoidance strategies often show significant fluctuation and are difficult to reproduce. To solve these issues, we created a two-stage training method for RL-based collision avoidance. We first optimize the policy, and then we utilize a supervised learning methodology with a loss function that encourages the agents to adopt the well-known reciprocity obstacle detection mechanism. In the second step, we use transmission to fine-tune the policy. The complete computer simulation findings demonstrate that this approach can handle noisy local views with erratic sound levels and can design moment & accident paths under inadequate sensing. We review the impact of our policies in a variety of ways.

关键词： Training Uncertainty Supervised learning Training data Aircraft navigation Sensors Noise measurement

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Data Analysis and Visualization Technique for Exploring of Factor Associated with the Incidence of Complication in Pregnancy and Newborn 17

Data Analysis and Visualization Technique for Exploring of F...

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17th International Conference on Electrical engineering/Electronics, computer, Telecommunications and Information technology, ECTI-CON 2020

作者： Prappre, Tagoon Vasupongayya, Sangsuree Liabsuetrakul, Tippawan Prince of Songkla University Management of Information Technology Program Hat Yai Thailand Prince of Songkla University Department of Computer Engineering Hat Yai Thailand Prince of Songkla University Department of Medicine Hat Yai Thailand

ISBN: (纸本)9781728164861

To assist the scientists in understanding the large amount of health data, this project aims to develop a prototype for visualizing the data related to the factors associated with the incidence of complication in pregnancy and newborn. The data for this work is from the improving health system response through epidemiological surveillance in improving maternal and newborn health and survival: field testing in Thailand project. The prototype converts the statistical significance level obtained from the data analysis to 2D graphics using the iconographic data presentation technique. And, the hierarchical data representation technique is used by the prototype to represent the relationship between the statistical significance level and the factors and the complication in pregnancy and newborn. The prototype evaluation results by the statistical expert show that the data presentation in graphic formats enables the researcher to better understand the results and to better interpret the results. The data representation technique in this work can be applied to other area of researches. © 2020 IEEE.

关键词： Data visualization

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Time-domain methods for quantifying dynamic cerebral blood flow autoregulation: Review and recommendations. A white paper from the Cerebrovascular Research Network (CARNet)

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Journal of Cerebral Blood Flow and Metabolism 2024年第9期44卷 1480-1514页

作者： Kostoglou, Kyriaki Bello-Robles, Felipe Brassard, Patrice Chacon, Max Claassen, Jurgen AHR Czosnyka, Marek Elting, Jan-Willem Hu, Kun Labrecque, Lawrence Liu, Jia Marmarelis, Vasilis Z Payne, Stephen J Shin, Dae Cheol Simpson, David Smirl, Jonathan Panerai, Ronney B Mitsis, Georgios D Department of Electrical and Computer Engineering McGill University Montreal QC Canada Institute of Neural Engineering Graz University of Technology Graz Austria Departamento de Ingeniería Informática Universidad de Santiago de Chile Santiago Chile Department of Kinesiology Faculty of Medicine Université Laval QC Canada Research Center of the Institut universitaire de cardiologie et de pneumologie de Québec Quebec QC Canada Department of Geriatrics Radboud University Medical Center Research Institute for Medical Innovation and Donders Institute Nijmegen Netherlands Cerebral Haemodynamics in Ageing and Stroke Medicine (CHiASM) Department of Cardiovascular Sciences University of Leicester Leicester United Kingdom Department of Clinical Neurosciences Neurosurgery Department University of Cambridge Cambridge United Kingdom Department of Neurology and Clinical Neurophysiology University Medical Center Groningen Groningen Netherlands Medical Biodynamics Program Division of Sleep and Circadian Disorders Brigham and Women's Hospital Harvard Medical School Boston MA United States Division of Sleep Medicine Harvard Medical School Boston MA United States Laboratory for Engineering and Scientific Computing Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China Department Biomedical Engineering Viterbi School of Engineering University of Southern California Los Angeles CA United States Institute of Applied Mechanics National Taiwan University Taipei Taiwan Institute of Sound and Vibration Research University of Southampton Southampton United Kingdom Cerebrovascular Concussion Laboratory Faculty of Kinesiology University of Calgary Calgary AB Canada Sport Injury Prevention Research Centre Faculty of Kinesiology University of Calgary Calgary AB Canada Hotchkiss Brain Institute University of Calgary Calgary AB Canada NIHR Leicester Biomedical Research Centre Bri

Cerebral Autoregulation (CA) is an important physiological mechanism stabilizing cerebral blood flow (CBF) in response to changes in cerebral perfusion pressure (CPP). By maintaining an adequate, relatively constant supply of blood flow, CA plays a critical role in brain function. Quantifying CA under different physiological and pathological states is crucial for understanding its implications. This knowledge may serve as a foundation for informed clinical decision-making, particularly in cases where CA may become impaired. The quantification of CA functionality typically involves constructing models that capture the relationship between CPP (or arterial blood pressure) and experimental measures of CBF. Besides describing normal CA function, these models provide a means to detect possible deviations from the latter. In this context, a recent white paper from the Cerebrovascular Research Network focused on Transfer Function Analysis (TFA), which obtains frequency domain estimates of dynamic CA. In the present paper, we consider the use of time-domain techniques as an alternative approach. Due to their increased flexibility, time-domain methods enable the mitigation of measurement/physiological noise and the incorporation of nonlinearities and time variations in CA dynamics. Here, we provide practical recommendations and guidelines to support researchers and clinicians in effectively utilizing these techniques to study CA. © The Author(s) 2024.

关键词： CARNet cerebral autoregulation cerebral blood flow time-domain methods white paper

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Prediction of Hydrogen Production Rate in Anaerobic Fermentation Using Grey Relation Analysis and Machine Learning

SSRN

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SSRN 2023年

作者： Wang, Yifan Wu, Jinghui Tseng, Yu-Yao Zhao, Chunliang Li, Keqing Wang, Xianze Wang, Ming-Hung Lay, Chyi-How Huo, Mingxin Engineering Research Center of Low-Carbon Treatment Green Development of Polluted Water in Northeast China Ministry of Education Changchun130117 China Science and Technology Innovation Center for Municipal Wastewater Treatment and Water Quality Protection Northeast Normal University Changchun130117 China Key Laboratory of Songliao Aquatic Environment Ministry of Education Jilin Jianzhu University Changchun130118 China Master's Program of Green Energy Science and Technology Feng Chia University Taichung40724 Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Chiayi County Taiwan

Anaerobic fermentation for hydrogen production has many environmental factors that limit microbial activity, but machine learning has enormous potential in handling the complexity of biological processes. This study explores the potential of machine learning in predicting hydrogen production rates (HPR) from anaerobic fermentation of biomass energy. Grey relation analysis was conducted to determine the correlation between operational parameters and HPR. Five machine learning algorithms, such as decision tree (DT), random forest (RF), extreme gradient boosting (XGBoost), and K-nearest neighbor (KNN), were then paired with operating conditions and water quality performance as features and HPR as a label, with mean squared error (MSE) and R2 as evaluation indexes. Butyric acid, oxidation-reduction potential (ORP), and volatile suspended solids (VSS) were found to play crucial roles in hydrogen production from sucrose anaerobic fermentation. XGBoost had the highest accuracy with R2 of 0.91 and MSE of 0.0052. © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Optimal First-Order Algorithms as a Function of Inequalities

arXiv

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arXiv 2021年

作者： Park, Chanwoo Ryu, Ernest K. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology MA United States Department of Mathematical Sciences Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Korea Republic of

In this work, we present a novel algorithm design methodology that finds the optimal algorithm as a function of inequalities. Specifically, we restrict convergence analyses of algorithms to use a prespecified subset of inequalities, rather than utilizing all true inequalities, and find the optimal algorithm subject to this restriction. This methodology allows us to design algorithms with certain desired characteristics. As concrete demonstrations of this methodology, we find new state-of-the-art accelerated first-order gradient methods using randomized coordinate updates and backtracking line searches. © 2021, CC BY-NC-ND.

关键词： Gradient methods

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Towards a Prosodic Model for Synthesized Speech of Mathematical Expressions in MathML 2020

Towards a Prosodic Model for Synthesized Speech of Mathemati...

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9th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion

作者： Adriana Souza Diamantino Freitas Doctoral Program in Digital Media Faculty of Engineering - University of Porto Porto Portugal Bahia Federal Institute of Education Science and Technology Porto Seguro Brazil BR Department of Electrical and Computer EngineeringFaculty of Engineering - University of PortoPorto Portugal PT

ISBN: (纸本)9781450389372

The use of the MathML language made possible to improve the accessibility of mathematics for blind or low-vision persons in digital media. Synthetic speech technologies have advanced significantly using MathML, however, the speech synthesizers' standard reading style is still not suitable for mathematics. Making mathematical reading of the speech synthesizers more natural and expressive is still a challenge. The creation of models to produce the appropriate prosody in the synthesized speech of math content is therefore necessary, as shown in previous research. This article presents a proposal for a model to improve prosody in the synthesized speech of mathematical expressions based on MathML. A corpus of mathematical expressions spoken by Mathematics teachers was created to support the model's development. The Fujisaki intonation model was adopted for intonation control, accent and phrase commands have been extracted from the corpus, and some adjustments have been made to manipulate prosodic parameters in the speech of mathematical expression in correlation with the MathML tree; additionally, a pattern of pauses control is being created.

关键词： Accessibility Mathematics Visual Impairment

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Comparison heuristics method for solving two echelon vehicle routing problem

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AIP Conference Proceedings 2024年第1期3029卷

作者： Muhammad Khahfi Zuhanda Saib Suwilo Opim Salim Sitompul Mardiningsih Informatics Engineering Study Program Faculty Engineering Universitas Medan Area Medan Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

Today, almost everyone has done online shopping activities. The presence of e-commerce makes it easier for humans to do shopping. E-commerce companies compete to provide the best service to the community. One of them is in the delivery within the city. In terms of city delivery, the 2E-VRP model has been discussed a lot lately in terms of consolidating shipments. This study aims to present the 2E-VRP mathematical model and work in two stages to find a solution. In this article, the author also compares solutions with several heuristic models including 2-opt, repetitive nearest neighbor, nearest neighbor, farthest insertion, cheapest insertion, arbitrary insertion, and nearest insertion. From the results of research conducted by the 2-opt method, farthest insertion, cheapest insertion, and nearest insertion, the total distance is the best, all three get the same distance, then followed by the nearest insertion, arbitrary insertion, and nearest insertion methods.

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Comprehensive energy, economic, and environmental analysis of a hybrid photovoltaic–thermal (PVT) heat pump system

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Energy 2025年 331卷

作者： Hugo Arnesson Andreas V. Olympios Asmaa A. Harraz Jingyuan Xu Institute for Microstructure Technology Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 76344 Eggenstein-Leopoldshafen Germany PV Technology Laboratory Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus Environmental Engineering Program University of Science and Technology Zewail City of Science and Technology Egypt

This study investigates a parallel indirect-expansion solar-assisted heat pump (SAHP) system integrating photovoltaic–thermal (PVT) collectors to meet domestic space heating, hot water, and appliance electricity demands for a typical household in Germany. A transient mathematical model captures the interdependencies between heat and electricity flows, enabling evaluation of thermodynamic, economic, and environmental performance across 54 heat pump designs with 3 refrigerants. The SAHP is compared to standalone heat pumps and natural gas boilers under varying electricity and natural gas prices. Results indicate that the SAHP system can cover over one-third of annual heating demand and half of appliance electricity demand using solar energy, with Munich achieving the highest solar coverage (39 %). HFC-32 (R32) outperforms propane, which in turn outperforms R410A, with levelized costs of energy, in electricity equivalents, of 0.272, 0.276 and 0.283 Euro/kWh, respectively. The SAHP system proves more cost-effective than standalone heat pumps or natural gas boilers unless energy prices are exceptionally low. Optimizing water tank designs for lower-temperature operation could further enhance SAHP competitiveness against PV-driven heat pumps.

关键词： Solar-assisted heat pump Energy–economic–environmental (3E) Photovoltaic–thermal (PVT) Propane refrigerant R32 refrigerant

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Detecting QT prolongation From a Single-lead ECG With Deep Learning

arXiv

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arXiv 2023年

作者： Alam, Ridwan Aguirre, Aaron D. Stultz, Collin M. Research Laboratory of Electronics MIT CambridgeMA United States Computer Science & Artificial Intelligence Laboratory MIT CambridgeMA United States Department of Electrical Engineering and Computer Science MIT CambridgeMA United States Wellman Center for Photomedicine Massachusetts General Hospital BostonMA United States Division of Cardiology Massachusetts General Hospital BostonMA United States Harvard Medical School BostonMA United States Harvard-MIT Program in Health Sciences and Technology CambridgeMA United States Institute for Medical Engineering and Science MIT CambridgeMA United States

Background and Aims For a number of antiarrhythmics, drug loading requires a 3-day hospitalization with monitoring for QT-prolongation. Automated QT monitoring with wearable ECG monitors would facilitate out-of-hospital care. We aim to develop a deep learning model that infers QT intervals from ECG lead-I - the lead most often acquired from ambulatory ECG monitors - and we use this model to detect clinically meaningful QT-prolongation episodes during Dofetilide drug loading. Methods Using 4.22 million 12-lead ECG recordings from 903.6 thousand patients at the Massachusetts General Hospital, we develop a deep learning model, QTNet, that infers QT intervals from lead-I. Over 3 million ECGs from 653 thousand patients are used to train the model and an internal-test set containing 633 thousand ECGs from 135 thousand patients was used for testing. QTNet is further evaluated on an external-validation set containing 3.1 million ECGs from 667 thousand patients at another institution. QTNet was used to detect Dofetilide-induced QT prolongation in a publicly available database (ECGRDVQ-dataset) containing ECGs from subjects enrolled in a clinical trial evaluating the effects of antiarrhythmic drugs. Results QTNet achieves mean absolute errors of 12.63ms (internal-test) and 12.30ms (external-validation) for estimating absolute QT intervals. The associated Pearson correlation coefficients are 0.91 (internal-test) and 0.92 (external-validation). For the ECGRDVQ-dataset, QTNet detects Dofetilide-induced QTc prolongation with 87% sensitivity and 77% specificity. The negative predictive value of the model is greater than 95% when the pre-test probability of drug-induced QTc prolongation is below 25%. Conclusions Drug-induced QT prolongation risk can be tracked from ECG lead-I using deep learning. This research leads the path toward out-of-hospital care using wearable ECG devices for antiarrhythmic therapies. © 2023, CC BY-NC-ND.

关键词： Electrocardiograms

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