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Performance of evolutionary optimized machine learning for modeling total organic carbon in core samples of shale gas fields

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Petroleum 2024年第1期10卷 150-164页

作者： Leonardo Goliatt c.m.Saporetti L.c.Oliveira E.Pereira Department of computational and Applied mechanics Federal University of Juiz de ForaJuiz de ForaBrazil Department of computational modeling Polytechnic InstituteRio de Janeiro State UniversityNova FriburgoBrazil Petrobras Rio de JaneiroBrazil Department of Stratigraphy and Paleontology Rio de Janeiro State UniversityRio de JaneiroBrazil

Rock samples'TOc content is the best indicator of the organic matter in source *** origin rock samples’analysis is used to calculate it manually by *** method requires time and resources because it relies on samples from many well intervals in source ***,research has been done to aid this *** learning algorithms can estimate total organic carbon instead of well logs and stratigraphic *** light of these efforts,the current work present a study on automating the total organic carbon estimation using machine learning approaches improved by an evolutionary methodology to give the model flexibility and *** algorithms,differential evolution,particle swarm optimization,grey wolf optimization,artificial bee colony,and evolution strategies were used to improve machine learning models to predict *** six metaheuristics were integrated into four machine learning methods:extreme learning machine,elastic net linear model,linear support vector regression,and multivariate adaptive regression *** samples from the YuDong-Nan shale gas field,located in the Sichuan basin,were used to evaluate the hybrid *** findings show that combining machine learning models with an evolutionary algorithms in a hybrid fashion produce flexible models that accurately predict *** results show that,independent of the metaheuristic used to guide the model selection,optimized extreme learning machines attained the best performance scores according to six *** hybrid models can be used in exploratory geological research,particularly for unconventional oil and gas resources.

关键词： Total organic carbon Hybrid models Automated machine learning Evolutionary algorithms Geology

Technical efficiency of cocoa farms at varying elevation levels in Davao city, Philippines: implications to sustainable upland farming systems

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Journal of mountain Science 2024年第1期21卷 33-48页

作者： francis Levi A.DURANO Jon marx SARmIENTO Larry N.DIGAL Pedro A.ALVIOLA IV School of management University of the Philippines MindanaoDavao City 8000Philippines

Elevation is one of many components that influence agriculture, and this in turn affects the level of both inputs and outputs of farmers. This article focuses on the productivity and technical efficiency of 100 cocoa farms using cross-sectional data from areas ranging from 190 to 1021 m above sea level which were classified as low, medium, and high elevation in Davao city, considered as the chocolate capital of the Philippines. Using stochastic frontier analysis, the results showed that the cost of inputs per ha and the number of cocoa trees per ha significantly increase yield. Farms at high elevations were less technically efficient, as this entails lower temperatures and increased rainfall, and cocoa farming in those areas and conditions can be more challenging, especially with changes in farming practices, terrain, and distance to markets. Other significant variables were age of cocoa farms, married farmers, and age of the farmers. Older farms may be more developed, farmers who are married benefit from their spouses being able to readily contribute as farm labor, and lastly, older farmers' inefficiency may likely stem from nonadaptation of newer farming practices. With an average technical efficiency of 0.61, 0.63, and 0.26 in low, medium, and high elevation areas, respectively, farmers therefore have an incentive to improve farm practices and consider topographical variations found in high elevation areas. Recommendations for the improvement of technical efficiency of cocoa farms are better connectivity to markets, enhancing farm practices, and continuation and improvement of government programs on cocoa with an added emphasis on research. For farmers in high elevation areas, mitigating solutions such as sustainable agriculture practices and ecolabelling are key to improving efficiency and minimizing the potential negative impact on upland farming systems. moreover, such adaptation measures may also contribute to sustainability of cocoa farming in high elevation

关键词： cocoa farms cobb-Douglas production function Elevation Philippines Stochastic frontier analysis Technical efficiency

A Grid middleware for Distributed Java computing with mPI Binding and Process migration Supports

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Journal of computer Science & Technology 2003年第4期18卷 505-514页

作者：陈琳王卓立 francis.c.m.lau Department of computer Science and Information Systems The University of Hong Kong P.R. China

"Grid" computing has emerged as an important new research field. With years of efforts, grid researchers have successfully developed grid technologies including security solutions,resource management protocols, information query protocols, and data management services. However, as the ultimate goal of grid computing is to design an infrastructure which supports dynamic,cross-organizational resource sharing, there is a need of solutions for efficient and transparent task re-scheduling in the *** this research, a new grid middleware is proposed, called G-JavamPI. This middleware adds the parallel computing capability of Java to the grid with the support of a Grid-enabled message passing interface (mPI) for inter-process communication between Java processes executed at different grid points. A special feature of the proposed G-JavamPI is the support of Java process migration with post-migration message redirection. With these supports, it is possible to migrate executing Java process from site to site for continuous computation, if some site is scheduled to be turned down for system reconfiguration. moreover, the proposed G-JavamPI middleware is very portable since it requires no modification of underlying OS, Java virtual machine, and mPI package. Preliminary performance tests have been conducted. The proposed mechanisms have shown good migration efficiency in a simulated grid environment.

关键词： grid middleware mPI Java process migration

An improved pulse coupled neural networks model for semantic IoT

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Digital communications and Networks 2024年第3期10卷 557-567页

作者： Rong ma Zhen Zhang Yide ma Xiping Hu Edith c.H.Ngai Victor c.m.Leung School of Information Science and Engineering Lanzhou UniversityLanzhou 730000China School of medical Technology Beijing Institute of TechnologyBeijing100081China Department of Electrical and Electronic Engineer The University of Hong KongHong Kong 999077China college of computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China Department of Electrical and computer Engineering the University of British ColumbiaVancouverBC V6T 1Z4Canada

In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data ***,with the rapid development of artificial intelligence,semantic communication has attracted great attention as a new communication ***,for IoT devices,however,processing image information efficiently in real time is an essential task for the rapid transmission of semantic *** the increase of model parameters in deep learning methods,the model inference time in sensor devices continues to *** contrast,the Pulse coupled Neural Network(PcNN)has fewer parameters,making it more suitable for processing real-time scene tasks such as image segmentation,which lays the foundation for real-time,effective,and accurate image ***,the parameters of PcNN are determined by trial and error,which limits its *** overcome this limitation,an Improved Pulse coupled Neural Networks(IPcNN)model is proposed in this *** IPcNN constructs the connection between the static properties of the input image and the dynamic properties of the neurons,and all its parameters are set adaptively,which avoids the inconvenience of manual setting in traditional methods and improves the adaptability of parameters to different types of *** segmentation results demonstrate the validity and efficiency of the proposed self-adaptive parameter setting method of IPcNN on the gray images and natural images from the matlab and Berkeley Segmentation *** IPcNN method achieves a better segmentation result without training,providing a new solution for the real-time transmission of image semantic information.

关键词： Internet of things(IoT) Semantic information Real-time application Improved pulse coupled neural network Image segmentation

Semi-analytical investigation of heat transfer in a porous convective radiative moving longitudinal fin exposed to magnetic field in the presence of a shape-dependent trihybrid nanofluid

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Applied mathematics and mechanics(English Edition) 2024年第1期45卷 197-216页

作者： c.G.PAVITHRA B.J.GIREESHA m.L.KEERTHI Department of PG Studies and Research in mathematics Kuvempu UniversityShankaraghatta 577451India Department of mathematics and Statistics M.S.Ramaiah University of Applied SciencesBengaluru 560058India

The thermal examination of a non-integer-ordered mobile fin with a magnetism in the presence of a trihybrid nanofluid(Fe_3O_4-Au-Zn-blood) is carried out. Three types of nanoparticles, each having a different shape, are considered. These shapes include spherical(Fe_3O_4), cylindrical(Au), and platelet(Zn) configurations. The combination approach is utilized to evaluate the physical and thermal characteristics of the trihybrid and hybrid nanofluids, excluding the thermal conductivity and dynamic viscosity. These two properties are inferred by means of the interpolation method based on the volume fraction of nanoparticles. The governing equation is transformed into a dimensionless form, and the Adomian decomposition Sumudu transform method(ADSTm) is adopted to solve the conundrum of a moving fin immersed in a trihybrid nanofluid. The obtained results agree well with those numerical simulation results, indicating that this research is reliable. The influence of diverse factors on the thermal overview for varying noninteger values of γ is analyzed and presented in graphical representations. Furthermore, the fluctuations in the heat transfer concerning the pertinent parameters are studied. The results show that the heat flux in the presence of the combination of spherical, cylindrical, and platelet nanoparticles is higher than that in the presence of the combination of only spherical and cylindrical nanoparticles. The temperature at the fin tip increases by 0.705 759% when the value of the Peclet number increases by 400%, while decreases by 11.825 13% when the value of the Hartman number increases by 400%.

关键词： convection radiation moving longitudinal fin Adomian decomposition Sumudu transform method(ADSTm) trihybrid nanofluid magnetic field

Optimization of a photovoltaic-battery system using deep reinforcement learning and load forecasting

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Energy and AI 2024年第2期16卷 168-183页

作者： António corte Real G.Pontes Luz J.m.c.Sousa m.c.Brito S.m.Vieira IDmEc Instituto Superior TécnicoUniversidade de LisboaLisboa1049-001Portugal Instituto Dom Luiz Faculdade de CiênciasUniversidade de LisboaCampo Grande1749-016LisboaPortugal

Home Energy management Systems(HEmS)are increasingly relevant for demand-side management at the residential level by collecting data(energy,weather,electricity prices)and controlling home appliances or storage *** control can be performed with classical models that find optimal solutions,with high real-time computational cost,or data-driven approaches,like Reinforcement Learning,that find good and flexible solutions,but depend on the availability of load and generation data and demand high computational resources for *** this work,a novel HEmS is proposed for the optimization of an electric battery operation in a real,online and data-driven environment that integrates state-of-the-art load forecasting combining cNN and LSTm neural networks to increase the robustness of *** Reinforcement Learning agents are trained with different algorithms(Double DQN,Dueling DQN,Rainbow and Proximal Policy Optimization)in order to minimize the cost of electricity purchase and to maximize photovoltaic self-consumption for a PV-Battery residential *** show that the best Reinforcement Learning agent achieves a 35%reduction in total cost when compared with an optimization-based agent.

关键词： Energy management system Deep reinforcement learning Demand-side management Load forecasting Deep learning Energy storage systems

Towards a new avenue for rapid synthesis of electrocatalytic electrodes via laser-induced hydrothermal reaction for water splitting

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International Journal of Extreme manufacturing 2024年第1期6卷 340-351页

作者： Yang Sha menghui Zhu Kun Huang Yang Zhang francis moissinac Zhizhou Zhang Dongxu cheng Paul mativenga Zhu Liu Department of materials School of Natural SciencesThe University of ManchesterOxford RoadManchester M139PLUnited Kingdom Laser Processing Research centre Department of MechanicalAerospace and Civil EngineeringSchool of EngineeringThe University of ManchesterOxford RoadManchester M139PLUnited Kingdom National Graphene Institute The University of ManchesterOxford RoadManchester M139PLUnited Kingdom Department of chemical Engineering and Analytical Science School of EngineeringThe University of ManchesterOxford RoadManchester M139PLUnited Kingdom Research centre for Laser Extreme manufacturing Ningbo Institute of Materials Engineering and TechnologyChinese Academy of SciencesNingboPeople’s Republic of China

Electrochemical production of hydrogen from water requires the development ofelectrocatalysts that are active,stable,and low-cost for water *** address these challenges,researchers are increasingly exploring binder-free electrocatalytic integratedelectrodes (IEs) as an alternative to conventional powder-based electrode preparation methods,for the former is highly desirable to improve the catalytic activity and long-term stability for large-scale applications of ***,we demonstrate a laser-inducedhydrothermal reaction (LIHR) technique to grow NimoO4nanosheets on nickel foam,which is then calcined under H2/Ar mixed gases to prepare the IE *** electrode exhibits superior hydrogen evolution reaction performance,requiring overpotentials of 59,116 and143 mV to achieve current densities of 100,500 and 1000 mA·*** the 350 h chronopotentiometry test at current densities of 100 and 500 m A·cm-2,the overpotentialremains essentially *** addition,NiFe-layered double hydroxide grown on Ni foam is also fabricated with the same LIHR method and coupled with IE-Nimo-IR to achieve water *** combination exhibits excellent durability under industrial current *** energy consumption and production efficiency of the LIHR method are systematicallycompared with the conventional hydrothermal *** LIHR method significantly improves the production rate by over 19 times,while consuming only 27.78%of the total energy required by conventional hydrothermal methods to achieve the same production.

关键词： electrocatalytic electrode laser-induced hydrothermal reaction NiFe layered double hydroxides hydrogen evolution reaction water splitting energy consumption production rate

Hybrid ionic/electronic interphase enabling uniform nucleation and fast diffusion kinetics for stable lithium metal anode

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chinese chemical Letters 2024年第2期35卷 626-633页

作者： Lun Li Pengxia Ji meng Huang Zixin Zhang Hong Wang francis Verpoort Jinlong Yang Daping He State Key Laboratory of Advanced Technology for materials Synthesis and Processing School of Materials Science and EngineeringWuhan University of TechnologyWuhan 430070China Guangdong Research center for Interfacial Engineering of Functional materials College of Materials Science and EngineeringShenzhen UniversityShenzhen 518060China Sanya Science and Education Innovation Park of Wuhan University of Technology Sanya 572000China Hubei Engineering Research center of RF-microwave Technology and Application Wuhan University of TechnologyWuhan 430070China State Key Laboratory of Silicate materials for Architectures Wuhan University of TechnologyWuhan 430070China

Lithium(Li)dendrite issue,which is usually caused by inhomogeneous Li nucleation and fragile solid electrolyte interphase(SEI),impedes the further development of high-energy Li metal ***,the integrated construction of a high-stable SEI layer that can regulate uniform nucleation and facilitate fast Li-ion diffusion kinetics for Li metal anode still falls ***,we designed an artificial SEI with hybrid ionic/electronic interphase to regulate Li deposition by in-situ constructing metal co clusters embedded in LiF *** generated co and LiF both enable fast Li-ion diffusion kinetics,meanwhile,the lithiophilic properties of co clusters can serve as Li-ion nucleation sites,thereby contributing to uniform Li nucleation and non-dendritic *** a result,a dendrite-free Li deposition with a low overpotential(16.1 mV)is achieved,which enables an extended lifespan over 750 h under strict *** full cells with high-mass-loading LiFePO_(4)(11.5 mg/cm^(2))as cathodes exhibit a remarkable rate capacity of 84.1 mAh/g at 5 c and an improved cycling performance with a capacity retention of 96.4%after undergoing 180 cycles.

关键词： Lithium metal anode Hybrid ionic/electronic interphase Solid electrolyte interphase Fast diffusion kinetics Dendritic growth of lithium

Wan-Yee Joseph lau:the promoter of modernization and internationalization of chinese surgery

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Oncology and Translational medicine 2024年第1期10卷 1-3页

作者： Wan-Yee Joseph lau Faculty of medicine The Chinese University of Hong KongHong KongChina

To my knowledge,there have been 3 books[1–3]and 2 book chapters written about me.[4–5]For those who are interested in the details of my life,please refer to these books/book *** title of this article is an English translation of the title of the book I refer to as reference 1,which I find appropriate to describe the role that I play in china.

关键词： please details translation