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Search results for: DAO
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Is DAO Governance Fostering Democracy? Reviewing Decision-Making in Decentraland
PublicationThis study analyzes voting dynamics and proposal outcomes within Decentraland, a prominent Decentralized Autonomous Organization (DAO), by examining its voting behaviors and decision outcomes. We offer insights into how a DAO is employed to facilitate decision-making and discern the nature of the issues about which decisions are made. DAOs promise horizontal and democratic decision-making. However, our research reveals...
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Dao-A Journal of Comparative Philosophy
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Phong B. Dao D.Sc., Ph.D.
PeoplePhong B. Dao received the Engineer degree in Cybernetics in 2001, the M.Sc. degree in Instrumentation and Control in 2004, both from Hanoi University of Science and Technology in Vietnam, and the Ph.D. degree in Control Engineering in 2011 from the University of Twente, the Netherlands. In May 2020, Dr. Dao received the degree of D.Sc. (Habilitation) in Mechanical Engineering from the AGH University of Science and Technology, Poland....
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Journal of Daoist Studies
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Cailiao Daobao/Materials Review
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A CUSUM-Based Approach for Condition Monitoring and Fault Diagnosis of Wind Turbines
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Cointegration Modelling for Health and Condition Monitoring of Wind Turbines - An Overview
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On Wilcoxon rank sum test for condition monitoring and fault detection of wind turbines
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On Cointegration Analysis for Condition Monitoring and Fault Detection of Wind Turbines Using SCADA Data
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Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems
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Condition monitoring and fault diagnosis of wind turbines based on structural break detection in SCADA data
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Condition monitoring of wind turbines based on cointegration analysis of gearbox and generator temperature data
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OROMACS: A Design Framework for Multi-agent Control System
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Data normalisation for Lamb wave–based damage detection using cointegration: A case study with single- and multiple-temperature trends
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Lamb wave based structural damage detection using cointegration and fractal signal processing
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Cointegration and how it works for structural health monitoring
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Lamb Wave Based Structural Damage Detection Using Stationarity Tests
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Damage Detection Using Cointegration Technique and Wavelet Analysis of the Post-Cointegrated Lamb Waves
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Cointegration and wavelet-analysis-based approach for Lamb-wave-based structural damage detection
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Cointegration approach for temperature effect compensation in Lamb-wave-based damage detection
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Stationarity-Based Approach for the Selection of Lag Length in Cointegration Analysis Used for Structural Damage Detection
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Safe-Guarded Agent Design Pattern for Mechatronic Systems
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Operational Condition Monitoring of Wind Turbines Using Cointegration Method
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Trichobezoar due to psychiatric co-morbidity: A rare case report
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Damage Detection in Composite Materials Using Hyperspectral Imaging
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Condition monitoring and fault detection in wind turbines based on cointegration analysis of SCADA data
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Towards homoscedastic nonlinear cointegration for structural health monitoring
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An Experimental Study on the Effect of Temperature on Acoustic Emission Characteristics in Metallic Structures
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Nonlinear Cointegration Approach for Condition Monitoring of Wind Turbines
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Variation de l’épaisseur du placage de déroulage des bois et son influence sur les caractéristiques mécaniques des panneaux LVL
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Impact damage detection in smart composites using nonlinear acoustics—cointegration analysis for removal of undesired load effect
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Giant Nernst effect in the incommensurate charge density wave state of P4W12O44
PublicationWe report the study of Nernst effect in quasi-low-dimensional tungsten bronze P4W12O44 showing a sequence of Peierls instabilities. We demonstrate that both condensation of the electronic carriers in the charge density wave state and the existence of high-mobility electrons and holes originating from the small pockets remaining in the incompletely nested Fermi surface give rise to a Nernst effect of a magnitude similar to that...
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Reduction of CO2 Emissions from Offshore Combined Cycle Diesel Engine-Steam Turbine Power Plant Powered by Alternative Fuels
PublicationDiverse forms of environmental pollution arise with the introduction of materials or energy that exert adverse effects on human health, climate patterns, ecosystems, and beyond. Rigorous emission regulations for gases resulting from fuel combustion are being enforced by the European Union and the International Maritime Organization (IMO), directed at maritime sectors to mitigate emissions of SOx, NOx, and CO2. The IMO envisions...
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Fault detection in the marine engine using a support vector data description method
PublicationFast detection and correct diagnosis of any engine condition changes are essential elements of safety andenvironmental protection. Many diagnostic algorithms significantly improve the detection of malfunctions.Studies on diagnostic methods are rarely reported and even less implemented in the marine engine industry.To fill this gap, this paper presents the Support Vector Data Description (SVDD) method as applied to thefault detection...
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The beneficial use of nitric oxide during cardiopulmonary bypass on postoperative outcomes in children and adult patients: a systematic review and meta-analysis of 2897 patients
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Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublicationIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Fuzzy logic-supported building design for low-energy consumption in urban environments
PublicationClimate, building materials, occupancy patterns, and HVAC (heating, ventilation, and air conditioning) systems all interact in complex ways, making it difficult to design low-energy buildings. Thus, innovative architectural and engineering design strategies are required to meet the worldwide need to decrease building energy usage. To improve the calculation of energy consumption of buildings, this work introduces the FCR-BCS (fuzzy...
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Techno-economic analysis of a hybrid energy system for electrification using an off-grid solar/biogas/battery system employing HOMER: A case study in Vietnam
PublicationThe electrification of off-grid /island villages is a critical step towards improving the techno-economic circumstances of rural regions and the overall general growth of the country. However, consistent supply from a single source is not possible in these areas. Thus, a hybrid renewable energy system performs better in these conditions. The research challenge now is to identify the optimal combinations of HRES from the available...
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Desirability-based optimization of dual-fuel diesel engine using acetylene as an alternative fuel
Publicationhe study examined the dual-fuel engine performance employing acetylene gas as primary fuel and diesel as pilot fuel. The engine's operational parameters were adjusted using the Box-Behnken design, and the results were recorded. The best operating settings were yielded as 81.25 % engine load, 4.48 lpm acetylene gas flow rate and the compression ratio were 18. At this optimized setting the BTE was 27.1 % and the engine emitted 360...
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Performance and emission characteristics of diesel engines running on gaseous fuels in dual-fuel mode
PublicationConventional fossil fuels are being substituted with alternative green fuels because of their greenhouse gas emissions and pollution problems, which pose a severe threat to the environment. Several studies have reported the usage of biodiesel and gaseous fuels in both single and dual-fuel modes. Gaseous fuels such as producer gas, biogas, syngas, and hydrogen produced from renewable biomass could potentially be used along with...
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Global wealth disparities drive adherence to COVID-safe pathways in head and neck cancer surgery
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Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study
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Global variation in anastomosis and end colostomy formation following left‐sided colorectal resection
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Pooled analysis of WHO Surgical Safety Checklist use and mortality after emergency laparotomy
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Elective surgery system strengthening: development, measurement, and validation of the surgical preparedness index across 1632 hospitals in 119 countries
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Outcomes of gynecologic cancer surgery during the COVID-19 pandemic: an international, multicenter, prospective CovidSurg-Gynecologic Oncology Cancer study
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Effect of COVID-19 pandemic lockdowns on planned cancer surgery for 15 tumour types in 61 countries: an international, prospective, cohort study
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