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Satellite Image Classification Using a Hybrid Manta Ray Foraging Optimization Neural Network

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Big Data Mining and Analytics 2023年第1期6卷 44-54页

作者： Amit Kumar Rai Nirupama Mandal Krishna Kant Singh ivan Izonin Department of Electronics Engineering Indian Institute of TechnologyDhanbad(ISMDhanbad)Dhanbad 826004India Department of Electronics and Communication Engineering Asansol Engineering CollegeAsansol 713305India Department of CSE ASETAmity UniversityNoida 201301India Department of Artificial Intelligence Lviv Polytechnic National UniversityLviv 79000Ukraine

A semi supervised image classification method for satellite images is proposed in this *** satellite images contain enormous data that can be used in various *** analysis of the data is a tedious task due to the amount of data and the heterogeneity of the ***,in this paper,a Radial Basis Function Neural Network(RBFNN)trained using Manta Ray Foraging Optimization algorithm(MRFO)is *** is a three-layer network comprising of input,output,and hidden layers that can process large *** trained network can discover hidden data patterns in unseen *** learning algorithm and seed selection play a vital role in the performance of the *** seed selection is done using the spectral indices to further improve the performance of the *** manta ray foraging optimization algorithm is inspired by the intelligent behaviour of manta *** emulates three unique foraging behaviours namelys chain,cyclone,and somersault *** satellite images contain enormous amount of data and thus require exploration in large search *** spiral movement of the MRFO algorithm enables it to explore large search spaces *** proposed method is applied on pre and post flooding Landsat 8 Operational Land Imager(OLI)images of New Brunswick *** method was applied to identify and classify the land cover changes in the area induced by *** images are classified using the proposed method and a change map is developed using post classification *** change map shows that a large amount of agricultural area was washed away due to *** measurement of the affected area in square kilometres is also performed for mitigation *** results show that post flooding the area covered by water is increased whereas the vegetated area is *** performance of the proposed method is done with existing state-of-the-art methods.

关键词： Radial Basis Function Neural Network(RBFNN) Manta Ray Foraging Optimization algorithm(MRFO) Landsat 8 classification change detection disaster mitigation planning

PNN-SVM Approach of Ti-Based Powder’s Properties Evaluation for Biomedical Implants Production

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Computers, Materials & Continua 2022年第6期71卷 5933-5947页

作者： ivan Izonin Roman Tkachenko Michal Gregus Zoia Duriagina Nataliya Shakhovska Lviv Polytechnic National University Lviv79013Ukraine Comenius University in Bratislava Bratislava82005Slovak Republic The John Paul II Catholic University of Lublin Lublin20-708Poland

The advent of additive technologies has provided a significant breakthrough in the production of medical *** has reduced costs,increased productivity and accuracy of the implant manufacturing ***,there are problems associated with assessing defects in the microstructure,mechanical and technological properties of alloys,both during their production by powder metallurgy and in the process of 3D *** traditional research methods of alloys properties demand considerable human,material,and time *** the same time,artificial intelligence tools create opportunities for intelligent evaluation of the conformity for the microstructure,phase composition,and properties of titanium powder’s *** provides new possibilities for the efficient production of biocompatible implants for various functional ***,the accuracy of the methods and models used should be as high as *** this paper we designed a hybrid PNN-SVM(Probabilistic Neural Network-Support Vector Machine)high-precision approach for the intelligent evaluation of alloy properties for additive manufacturing of biomedical *** have proposed a new approach for extending the dimensionality of input data space by the outputs of the summation layer of the modified PNN *** classification based on the expanded dataset is performed using *** conducted experimental modeling of the proposed approach using a data set on the properties of titanium alloys Ti-6Al-4V and *** have demonstrated a significant increase in the accuracy of the PNN-SVM scheme compared to the single classifiers that form it and other machine learning methods.

关键词： PNN SVM hybrid systems classification accuracy medical implants additive manufacturing 3D printing titanium alloys

Comparison between Merrifield–Simmons Index and Wiener Index of Graphs

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Acta Mathematica Sinica,English Series 2022年第12期38卷 2220-2230页

作者： Ke Xiang XU Kinkar Chandra DAS ivan GUTMAN Meng Lu WANG College of Mathematics Nanjing University of Aeronautics&AstronauticsNanjing 210016P.R.China MIIT Key Laboratory of Mathematical Modelling and High Performance Computing of Air Vehicles Nanjing 210016P.R.China Department of Mathematics Sungkyunkwan UniversitySuwon16419Republic of Korea Facultyof Science Universityof KragujevacP.O.Bor 6034000 KragujevacSerbia

The Merrifield–Simmons indexσis the total number of independent vertex sets(including the empty set)of the graph *** Wiener index W is the sum of distances in all unordered pairs of vertices of *** construct some new graphs satisfyingσ>W and W>σ,*** particular,infinite graphs satisfying W>σare invented with graphs with diameter 2 and infinite ones satisfyingσ>W are discovered with so-called universally diametrical graphs.

关键词： Merrifield–Simmons index Wiener index Cartesian product independence number Fibonacci number universally diametrical graph

Double-skin façade simulation with computational fluid dynamics:A review of simulation trends,validation methods and research gaps

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Building Simulation 2023年第12期16卷 2307-2331页

作者： Simon Pommerencke Melgaard ivan Titov Nikolaisson Chen Zhang Hicham Johra Olena Kalyanova Larsen Department of the Built Environment Aalborg UniversityDenmarkThomas Manns Vej 239220 AalborgDenmark

Dynamic simulation of a double-skin façade(DSF)with computational fluid dynamics(CFD)can be challenging due to the lack of validated models and benchmarking ***,there is a lack of consensus in the scientific community on what constitutes a successfully validated DSF *** present review study identifies simulation trends and research gaps for DSFs simulated with ***,this article presents a series of CFD simulations in which key aspects of the DSF modelling are varied:2D or 3D modelling approaches,turbulence viscosity models(TVMs),radiation models,and wall *** simulation results are compared to the empirical data(both temperature and velocity fields)of a benchmark test with laboratory-controlled boundary *** analysis shows that using the k-εRNG model with enhanced wall treatment and surface-to-surface(S2S)radiation model yields the best results for the 2D case of natural convection ***,it is shown that accounting for the velocity field in the validation process is essential to ensure the suitability of a ***,the authors advocate for the use of selected dimensionless numbers to improve the comparability of the different DSF scientific *** would also help to identify relevant experimental datasets for validation and suitable CFD simulation settings for specific DSF cases.

关键词： double-skin facade ventilated cavity computational fluid dynamics empirical validation modelling parameters dimensionless numbers convection

Optimization of ultrasound procedure for the sustainable production of oil from plum seeds

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Carbon Resources Conversion 2023年第1期6卷 20-26页

作者： ivana M.Savic Gajic ivan M.Savic Faculty of Technology in Leskovac University of NisBulevar oslobodjenja 12416000 LeskovacSerbia

In this study,the energy-efficient advanced procedure for the production of oil from plum seeds was *** optimization of ultrasound-assisted extraction(UAE)of oil was carried out using the response surface methodology with the Box-Behnken *** microwave pretreatment(MWP)of 460 W for 3 min was also applied to reduce the total extraction *** extraction time(15-45 min),liquid-to-solid ratio(4-10 mL g􀀀1),and extraction temperature(40-60◦C)were defined as the *** oil yield was considered a response in this optimization *** ultrasonic bath of 150 W and 40 kHz was used for the production of cavitation energy during the *** optimal conditions were the extraction time of 42 min,the liquid-to-solid ratio of 10 mL g􀀀1,and the extraction temperature of 50◦*** on quality analysis,it was concluded that the oil obtained by MWP-UAE had adequate physico-chemical *** MWP-UAE was an efficient extraction technique in terms of extraction time and energy consumption.

关键词： Plum seeds Oil Microwave pretreatment Optimization Physicochemical properties Energy-efficient

Photoelectrochemical CO_(2) electrolyzers: From photoelectrode fabrication to reactor configuration

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Journal of Energy Chemistry 2023年第10期85卷 455-480,I0012页

作者： Jose Antonio Abarca Guillermo Díaz-Sainz ivan Merino-Garcia Angel Irabien Jonathan Albo Departamento de Ingenierías Química y Biomolecular Universidad de CantabriaETSIITAvenida de los Castros s/n39005 SantanderSpain

The photoelectrochemical conversion of CO_(2) into value-added products emerges as an attractive approach to alleviate climate change. One of the main challenges in deploying this technology is, however, the development and optimization of(photo)electrodes and photoelectrolyzers. This review focuses on the fabrication processes, structure, and characterization of(photo)electrodes, covering a wide range of fabrication techniques, from rudimentary to automated fabrication processes. The work also highlights the most relevant features of(photo)electrodes, with special emphasis on how to measure and optimize them. Finally, the review analyses the integration of(photo)electrodes in different photoelectrolyzer architectures, analyzing the most recent research work that comprises photocathode, photoanode,photocathode-photoanode, and tandem photoelectrolyzer configurations to ideally achieve self-sustained CO_(2) conversion systems. Overall, comprehensive guidelines are provided for future advancements in developing effective devices for CO_(2) conversion, bridging the gap towards the use of sunlight as the unique energy input and practical applications.

关键词： Decarbonization CO_(2)photoelectroreduction (Photo)Electrodes Fabrication techniques Photoelectrolyzer configuration

Interplay between chronic hepatitis B and atherosclerosis:Innovative perspectives and theories

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World Journal of Gastroenterology 2022年第4期28卷 497-499页

作者： ivan Ranković Vladimir Milivojević Aleksandra PavlovićMarković Mihailo Bezmarević Clinic for Gastroenterology and Hepatology University Clinical Center of SerbiaBelgrade 11000Serbia Clinic for Gastroenterology and Hepatology University Clinical Center of SerbiaSchool of MedicineUniversity of BelgradeBelgrade 11000Serbia Department of Hepatobiliary and Pancreatic Surgery Clinic for General SurgeryMilitary Medical AcademyUniversity of DefenseBelgrade 11000Serbia

Elaboration of carotid atherosclerosis in the setting of hepatitis B virus(HBV)infection should emphasize the significance of extrahepatic manifestations of the infection *** processes comprise the pathoevolution of HBV infection,rendering it a multi-systemic disease in its *** work not only exemplified atherosclerosis as an often-underestimated contributor to the severity of HBV infection but has also highlighted the bidirectional relationship between the ***,it is suggested that HBV-induced inflammation is one of the root causes of atherosclerosis,which in turn has a consequent effect on the severity of the chronic infection disease state,creating a vicious ***,we coupled prior data with the current concepts of HBV infection to postulate intriguing perspectives and theories.

关键词： Hepatitis B virus infection Carotid atherosclerosis Hepatitis B e antigen Arterial inflammation Perspectives and trends

Machine learning for recovery factor estimation of an oil reservoir:A tool for derisking at a hydrocarbon asset evaluation

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Petroleum 2022年第2期8卷 278-290页

作者： ivan Makhotin Denis Orlov Dmitry Koroteev Evgeny Burnaev Aram Karapetyan Dmitry Antonenko Skolkovo Institute of Science and Technology MoscowRussia JSC Zarubezhneft MoscowRussia

Well-known oil recovery factor estimation techniques such as analogy,volumetric calculations,material balance,decline curve analysis,hydrodynamic simulations have certain *** techniques are time-consuming,and require specific data and expert ***,though uncertainty estimation is highly desirable for this problem,the methods above do not include this by *** this work,we present a data-driven technique for oil recovery factor(limited to water flooding)estimation using reservoir parameters and representative *** apply advanced machine learning methods to historical worldwide oilfields datasets(more than 2000 oil reservoirs).The data-driven model might be used as a general tool for rapid and completely objective estimation of the oil recovery *** addition,it includes the ability to work with partial input data and to estimate the prediction interval of the oil recovery *** perform the evaluation in terms of accuracy and prediction intervals coverage for several tree-based machine learning techniques in application to the following two cases:(1)using parameters only related to geometry,geology,transport,storage and fluid properties,(2)using an extended set of parameters including development and production *** both cases,the model proved itself to be robust and *** conclude that the proposed data-driven approach overcomes several limitations of the traditional methods and is suitable for rapid,reliable and objective estimation of oil recovery factor for hydrocarbon reservoir.

关键词： Oil recovery factor Machine learning Regression Uncertainty estimation Conformal predictors Clustering Oilfield Oil reservoir

Methods for the Efficient Energy Management in a Smart Mini Greenhouse

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Computers, Materials & Continua 2022年第2期70卷 3169-3187页

作者： Vasyl Teslyuk ivan Tsmots Michal Gregus ml. Taras Teslyuk Iryna Kazymyra Department of Automated Control Systems Lviv Polytechnic National UniversityLviv79013Ukraine Faculty of Management Comenius University in BratislavaBratislava2582005Slovakia Department of Information Systems and Networks Lviv Polytechnic National UniversityLviv79013Ukraine

To solve the problem of energy efficiency of modern enterprise it is necessary to reduce energy *** of the possible ways is proposed in this research.A multi-level hierarchical system for energy efficiency management of the enterprise is designed,it is based on the modular principle providing rapid *** novelty of the work is the development of new and improvement of the existing methods and models,in particular:1)models for dynamic analysis of IT tools for data acquisition and processing(DAAP)in multilevel energy management systems,which are based on Petri nets;2)method of synthesis of DAAP tools in energy efficiency management information systems(EEMIS)of the enterprise which provides a reduction in hardware and time costs from 10%to 40%;3)method of conflict-free data exchange determining the minimum memory speed for the synthesis of realtime exchanges,it reduces the cost and energy consumption;4)method of calculating the signal of postsynaptic excitation of neural elements decreases the processing time of technological data two or more *** proposed methods,models and tools have been tested while implementing the EEMIS of the intelligent mini-greenhouse,as a result,energy efficiency has increased by 12%-25%(depending on season and peculiarities of growing plants).

关键词： Energy efficiency management information system(EEMIS) data acquisition and processing(DAAP) industry 4.0 Petri nets smart mini greenhouse