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Advancing sandstone reservoir compressibility prediction:A correlation-driven methodology

Petroleum Research 2024年第2期9卷 273-279页

作者： Tarek Ganat Meftah Hrairi Amr Badawy Vahid Khosravi mohammed Abdalla Department of Petroleum Chemical Engineering Sultan Qaboos UniversityP.O.Box 50Al-Khod123MuscatOman Department of Mechanical and Aerospace Engineering International Islamic University MalaysiaP.O.Box 1050728Kuala LumpurMalaysia Reservoir Engineering Section Petronas Carigali SDN BHDP.O.Box 10500088Kuala LumpurMalaysia Department of Chemical and Petroleum Engineering Faculty of EngineeringTechnologyand Built EnvironmentUCSI University56000Kuala LumpurMalaysia Chemical&Petroleum Engineering United Arab Emirates UniversityP.O.Box No.15551Al AinUAE

This study presents a correlation-based approach for predicting the compressibility of sandstone reservoir *** study proposes a matrix of new empirical equations that significantly improve the precision of measuring the pore volume compressibility,with the most optimal fit of results based on a cubic polynomial *** accuracy of the calculations was validated through comparison with actual data using root mean square method,and the suggested correlations significantly enhance the precise prediction of rock compressibility in sandstone *** this study,the source of data collection is consolidated and unconsolidated sandstone from East Asia offshore ***,variations in compressibility with net overburden pressure over the course of the field's lifespan have been *** results demonstrate the application of regression analysis in establishing a network of linkages between independent and dependent *** proposed correlations for consolidated and unconsolidated sandstones offer a remarkable improvement in the accurate calculation of rock compressibility compared to traditional laboratory procedures,with an average error of 2.5%compared to 5-10%for laboratory *** approach of this study offers a cost-effective and time-efficient alternative to remarkedly enhance the overall performance of sandstone reservoirs in the oil and gas industry.

关键词： Compressibility Consolidated and unconsolidated sandstone Rock properties Rock mechanics

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An Incentive Mechanism for Federated Learning:A Continuous Zero-Determinant Strategy Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 88-102页

作者： Changbing Tang Baosen Yang Xiaodong Xie Guanrong Chen mohammed A.A.Al-qaness Yang Liu IEEE the College of Physics and Electronic Information Engineering Zhejiang Normal UniversityUniversityJinhua 321004China the School of Mathematical Sciences Zhejiang Normal UniversityJinhua 321004China the Department of Electrical Engineering City University of Hong KongHong KongChina Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province Jinhua 321004China

As a representative emerging machine learning technique, federated learning(FL) has gained considerable popularity for its special feature of “making data available but not visible”. However, potential problems remain, including privacy breaches, imbalances in payment, and inequitable *** shortcomings let devices reluctantly contribute relevant data to, or even refuse to participate in FL. Therefore, in the application of FL, an important but also challenging issue is to motivate as many participants as possible to provide high-quality data to FL. In this paper, we propose an incentive mechanism for FL based on the continuous zero-determinant(CZD) strategies from the perspective of game theory. We first model the interaction between the server and the devices during the FL process as a continuous iterative game. We then apply the CZD strategies for two players and then multiple players to optimize the social welfare of FL, for which we prove that the server can keep social welfare at a high and stable level. Subsequently, we design an incentive mechanism based on the CZD strategies to attract devices to contribute all of their high-accuracy data to ***, we perform simulations to demonstrate that our proposed CZD-based incentive mechanism can indeed generate high and stable social welfare in FL.

关键词： Federated learning(FL) game theory incentive mechanism machine learning zero-determinant strategy

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GraphFlow+:Exploiting Conversation Flow in Conversational Machine Comprehension with Graph Neural Networks

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Machine Intelligence Research 2024年第2期21卷 272-282页

作者： Jing Hu Lingfei Wu Yu Chen Po Hu mohammed J.Zaki School of Computer Science Central China Normal UniversityWuhan 430079China Pinterest San Francisco 94016USA Meta Mountain View 94039USA Rensselaer Polytechnic Institute Troy 12180USA

The conversation machine comprehension(MC)task aims to answer questions in the multi-turn conversation for a single ***,recent approaches don’t exploit information from historical conversations effectively,which results in some references and ellipsis in the current question cannot be *** addition,these methods do not consider the rich semantic relationships between words when reasoning about the passage *** this paper,we propose a novel model GraphFlow+,which constructs a context graph for each conversation turn and uses a unique recurrent graph neural network(GNN)to model the temporal dependencies between the context graphs of each ***,we exploit three different ways to construct text graphs,including the dynamic graph,static graph,and hybrid graph that combines the *** experiments on CoQA,QuAC and DoQA show that the GraphFlow+model can outperform the state-of-the-art approaches.

关键词： Conversational machine comprehension(MC) reading comprehension question answering graph neural networks(GNNs) natural language processing(NLP)

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Effect of geopolitical risk and economic uncertainty indices on renewable energy

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Geoscience Frontiers 2024年第3期15卷 237-247页

作者： Xin Zhao Kamel Si mohammed Yaohui Wang PawełSte˛pien Grzegorz Mentel School of Statistics and Applied Mathematics Anhui University of Finance and EconomicsBengbuPR China Faculty of Economics and Management University Ain Temouchent Belhadj BouchaibAlgeria School of Urban and Regional Science Institute of Finance and Economics ResearchShanghai University of Finance and EconomicShanghaiPR China Institute of Economics and Finance University of SzczecinPoland Department of Quantitative Methods Faculty of ManagementRzeszow University of TechnologyRzeszow 35-959Poland

In this study,the relationships between five renewable energy sub-sectors markets and the geopolitical risk(GPR)and economic uncertainty indices(EUI)were examined using daily data from March 30,2012,to April 1,*** cross mapping results show that the renewable energy indices have definite relationships with the GPR and *** renewable energy indices show differences in response directions,speed and trends for a standard information difference impulse from the GPR and the EUI.A positive dynamic conditional correlation between renewable energies and EUI was observed in the first and second waves of the COVID-19 *** contrast,there was a relatively decreased effect for two risk indices during the Russia-Ukraine conflict of February-March *** results show that renewable energy may act as a time-varying hedge against economic uncertainty and GPR owing to its safehaven properties at various ***,building more secure and reliable renewable energy systems can help countries to increase their energy independence,which protects them against the risks of political and economic uncertainty.

关键词： Renewable energy Uncertainty indices Impulse response Safe-haven

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Catalytic Effect of Transition Metal Complexes of Triaminoguanidine on the Thermolysis of Energetic NC/DEGDN Composite

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火炸药学报 2024年第3期47卷 209-219,I0003页

作者： mohammed Dourari Ahmed Fouzi Tarchoun Djalal Trache Amir Abdelaziz Roufaida Tiliouine Tessnim Barkat Weiqiang Pang Energetic Materials Laboratory(EMLab) Teaching and Research Unit of Energetic ProcessesEcole Militaire PolytechniqueBP 17Bordj El-Bahri16046AlgiersAlgeria Xi′an Modern Chemistry Research Institute Xi′an 710065China

The transition metal complexes of triaminoguanidine(TAG-M,where M=Cobalt(Co)or Iron(Fe))have been *** catalytic effect of these complexes on the thermolysis of energetic composite based on nitrocellulose and diethylene glycol dinitrate,has been *** characterization of the resulting energetic composites was carried out using scanning electron microscopy(SEM),X-ray diffraction(XRD),Fourier transform infrared spectroscopy(FTIR),and differential scanning calorimetry(DSC).Isoconversional kinetic analysis was performed to determine the Arrhenius parameters associated with the thermolysis of the elaborated energetic *** is found that TAG-M complexes have strong catalytic effect on the thermo-kinetic decomposition of NC/DEGDN by decreasing the apparent activation energy and significantly increased the total heat *** models that govern the decomposition processes are also studied,and it is revealed that different reaction processes are accomplished by introduction metal complexes of ***,this study serves as a valuable reference for future research focused on the investigation of catalytic combustion features of solid propellants.

关键词： triaminoguanidine transition metal complexes nitrocellulose diethylene glycol dinitrate catalytic effect

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Exploring public perception and willingness to pay for a renewable source of energy:evidence from an emerging economy of renewable-energy development

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Clean Energy 2024年第2期8卷 177-188页

作者： mohammed J.K.Bashir Senadjki Abdelhak Wael A.Salah Mai Abuhelwa School of Engineering&Technology Central Queensland University120 Spencer St.MelbourneQLD 3000Australia Faculty of Business and Finance Universiti Tunku Abdul RahmanKamparPerakMalaysia Department of Electrical Engineering College of Engineering and TechnologyPalestine Technical University-KadooriePO Box 7Yafa StreetTulkarmPalestine Department of Electrical Engineering and Computer Science University of MissouriColumbiaMO 65211USA

The study focuses on the transition from conventional energy sources to sustainable renewable energy(RE)in Palestine,particularly in the West Bank and Gaza *** research aims to understand the relationship between key factors and residents’willingness to invest in the RE sector,with a specific focus on the impact of *** the unified theory of acceptance and use of technology,the study analyzes data from 400 residents through a questionnaire and employs ordinary least-squares regression analysis with Eviews *** key findings indicate that residents’inclination to invest in RE is significantly influenced by factors such as resource availability,knowledge level and power ***,the study suggests that educated residents are more likely to invest in RE when factors such as knowledge,effort expectation,enabling conditions and resource availability are relatively *** conclusion emphasizes the importance of policymakers’allocating sufficient funds to research and development to promote technological innovation in RE sources,thereby enhancing the population’s energy efficiency.

关键词： renewable energy technology energy security public perceptions sustainable development

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A hydrodynamic modelling of wave-activated bodies for wavelet marine regions

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Clean Energy 2024年第2期8卷 35-47页

作者： J.S.Peh mohammed W.Muhieldeen N.H.Shuaib Mechanical Engineering Department Faculty of EngineeringTechnology&Built EnvironmentUCSI UniversityKuala Lumpur56000Malaysia MTC Engineer Sdn.Bhd Shah AlamSelangorMalaysia

Recently,most wave energy research has targeted sea areas with high power density under extreme wave conditions for *** trend often leads to higher energy costs for wave power ***,many marine areas with low power density,characterized by wavelet conditions and less destructive forces than extreme wave conditions,remain ***,this study aimed to propose a wave-activated body model for sea regions with wavelet *** wave-activated body design process encompassed site selection,parameter determination,geometry design,comparison and performance evaluation using the ANSYS®AQWA *** results indicated that the proposed device achieved the desired heave motion,with an amplitude range of 1.2 to-2.5 m,validating its potential for deployment in marine regions with wavelet ***,while the proposed design is optimized for wavelet conditions,it was found to have potential limitations in extreme wave *** observation emphasizes the challenge of formulating a generalized design suitable for both ***,it is pivotal for wave-activated body designs to be customized based on the specific ocean conditions they target,underscoring the need for specialized designs of wave energy converters that consider the unique wave characteristics of their deployment sites.

关键词： wave energy converter South China sea renewable and sustainable energy wavelet ANSYS AQWA hydrodynamic wave-activated bodies

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Results Involving Partial Differential Equations and Their Solution by Certain Integral Transform

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1593-1616页

作者： Rania Saadah mohammed Amleh Ahmad Qazza Shrideh Al-Omari Ahmet Ocak Akdemir Department of Mathematics Faculty of ScienceZarqa UniversityZarqa13110Jordan Department of Mathematics Faculty of ScienceAl-Balqa Applied UniversityAmman11134Jordan Department of Mathematics Faculty of Science and LettersAgri Ibrahim莈鏴n UniversityAgri04100Turkey

In this study,we aimto investigate certain triple integral transformand its application to a class of partial *** discuss various properties of the new transformincluding inversion, linearity, existence, scaling andshifting, etc. Then,we derive several results enfolding partial derivatives and establish amulti-convolution ***, we apply the aforementioned transform to some classical functions and many types of partial differentialequations involving heat equations,wave equations, Laplace equations, and Poisson equations ***,wedraw some figures to illustrate 3-D contour plots for exact solutions of some selected examples involving differentvalues in their variables.

关键词： ARA transform double ARA transform triple ARA transform partial differential equations integral transform

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Terrorism Attack Classification Using Machine Learning: The Effectiveness of Using Textual Features Extracted from GTD Dataset

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1427-1467页

作者： mohammed Abdalsalam Chunlin Li Abdelghani Dahou Natalia Kryvinska School of Computer Science and Technology Wuhan University of TechnologyWuhan430070China LDDI Laboratory Faculty of Science and TechnologyUniversity of Ahmed DRAIAAdrar01000Algeria Information Systems Department Faculty of ManagementComenius UniversityBratislava82005Slovakia

One of the biggest dangers to society today is terrorism, where attacks have become one of the most significantrisks to international peace and national security. Big data, information analysis, and artificial intelligence (AI) havebecome the basis for making strategic decisions in many sensitive areas, such as fraud detection, risk management,medical diagnosis, and counter-terrorism. However, there is still a need to assess how terrorist attacks are related,initiated, and detected. For this purpose, we propose a novel framework for classifying and predicting terroristattacks. The proposed framework posits that neglected text attributes included in the Global Terrorism Database(GTD) can influence the accuracy of the model’s classification of terrorist attacks, where each part of the datacan provide vital information to enrich the ability of classifier learning. Each data point in a multiclass taxonomyhas one or more tags attached to it, referred as “related tags.” We applied machine learning classifiers to classifyterrorist attack incidents obtained from the GTD. A transformer-based technique called DistilBERT extracts andlearns contextual features from text attributes to acquiremore information from text data. The extracted contextualfeatures are combined with the “key features” of the dataset and used to perform the final classification. Thestudy explored different experimental setups with various classifiers to evaluate the model’s performance. Theexperimental results show that the proposed framework outperforms the latest techniques for classifying terroristattacks with an accuracy of 98.7% using a combined feature set and extreme gradient boosting classifier.

关键词： Artificial intelligence machine learning natural language processing data analytic DistilBERT feature extraction terrorism classification GTD dataset

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Nodule Detection Using Local Binary Pattern Features to Enhance Diagnostic Decisions

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Computers, Materials & Continua 2024年第3期78卷 3377-3390页

作者： Umar Rashid Arfan Jaffar Muhammad Rashid mohammed S.Alshuhri Sheeraz Akram Faculty of Computer Science and Information Technology The Superior UniversityLahore54600Pakistan Intelligent Data Visual Computing Research(IDVCR) Lahore54600Pakistan Department of Computer Science National University of TechnologyIslamabad45000Pakistan Department of Radiological Sciences and Medical Imaging College of AppliedMedical SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh12571Saudi Arabia

Pulmonary nodules are small, round, or oval-shaped growths on the lungs. They can be benign (noncancerous) or malignant (cancerous). The size of a nodule can range from a few millimeters to a few centimeters in diameter. Nodules may be found during a chest X-ray or other imaging test for an unrelated health problem. In the proposed methodology pulmonary nodules can be classified into three stages. Firstly, a 2D histogram thresholding technique is used to identify volume segmentation. An ant colony optimization algorithm is used to determine the optimal threshold value. Secondly, geometrical features such as lines, arcs, extended arcs, and ellipses are used to detect oval shapes. Thirdly, Histogram Oriented Surface Normal Vector (HOSNV) feature descriptors can be used to identify nodules of different sizes and shapes by using a scaled and rotation-invariant texture description. Smart nodule classification was performed with the XGBoost classifier. The results are tested and validated using the Lung Image Consortium Database (LICD). The proposed method has a sensitivity of 98.49% for nodules sized 3–30 mm.

关键词： Pulmonary nodules segmentation histogram thresholding

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