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Device-free human micro-activity recognition method using WiFi signals

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Geo-Spatial Information Science 2019年第2期22卷 128-137,I0005页

作者： Mohammed a.a.al-qaness School of Computer Science Wuhan UniversityWuhanChina

Human activity tracking plays a vital role in human–computer *** human activity recognition(HAR)methods adopt special devices,such as cameras and sensors,to track both macro-and ***,wireless signals have been exploited to track human motion and activities in indoor environments without additional *** study proposes a device-free WiFi-based micro-activity recognition method that leverages the channel state information(CSI)of wireless *** from existed CSI-based microactivity recognition methods,the proposed method extracts both amplitude and phase information from CSI,thereby providing more information and increasing detection *** proposed method harnesses an effective signal processing technique to reveal the unique patterns of each *** applied a machine learning algorithm to recognize the proposed *** proposed method has been evaluated in both line of sight(LOS)and none line of sight(NLOS)scenarios,and the empirical results demonstrate the effectiveness of the proposed method with several users.

关键词： Human activity recognition channel state information WiFi device-free microactivity recognition machine learning

The optimal semi-analytical modeling for the infinite-conductivity horizontal well performance under rectangular bounded reservoir based on a new instantaneous source function

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Petroleum 2024年第1期10卷 68-84页

作者： Firas a.a.al-Kabbawi Independent scholar LivingstonScotlandUNITED KINGDOM

The main objective of this study is to develop the optimal semi-analytical modeling for the infiniteconductivity horizontal well performance under rectangular bounded reservoir based on a new instantaneous source *** available semi-analytical infinite-conductivity models(ICMs)for horizontal well under rectangular bounded reservoir in literature were developed by applying superposition of pressures in space(SPS).A new instantaneous source function(i.e.,instantaneous uniform-flux segmentary source function under bounded reservoir)is derived to be used instead of SPS to develop the optimal semi-analytical *** new semi-analytical ICM is verified with ICM of Schlumberger[1]and with previous semi-analytical ICMs in terms of bottom hole pressure(BHP)profile and inflow rate distribution along the *** model is also validated with real horizontal wells in terms of inflow rate distribution along the *** results show that the developed model gives the optimal semi-analytical modeling for the infinite-conductivity horizontal well performance under rectangular bounded *** that,high computationalefficiency and high-resolution of wellbore discretization have been achieved(i.e.,wellbore segment number could be tens of hundreds depending on solution requirement).The results also show that at pseudosteady state(PSS)flow regime,inflow rate distribution along the wellbore by previous semi-analytical ICMs is stabilized U-shaped as performance of inflow rate distribution at late radial flow ***,the previous semi-analytical ICMs are incorrectly modeling inflow rate distribution at PSS flow regime due to the negative influence of applying *** optimal semi-analytical ICM is in a general form and real time domain,and can be applicable for 3D horizontal well and 2D vertical fracture well under infinite and rectangular bounded reservoirs,of uniform-flux and infinite-conductivity wellbore conditions at any time of well life.

关键词： Infinite-conductivity model Horizontal well performance Semi-analytical modeling Rectangular bounded reservoir Instantaneous source functions Flow regimes

Status and prospects for symmetric organic redox flow batteries

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Journal of Energy Chemistry 2025年第1期100卷 125-143页

作者： Md al Raihan C.Adam Dyker Department of Chemistry University of New Brunswick

As environmental concerns from fossil fuel consumption intensify, large-scale energy storage becomes imperative for the integration of renewable sources like wind, hydro, and solar with the electrical *** flow batteries, particularly those employing organic molecules, are positioned as a key technology for this purpose. This review explores the growing field of symmetric organic redox flow batteries(ORFBs) within this context. Unlike traditional asymmetric designs based on unique active materials for each electrode, symmetric ORFBs involve a single bipolar species for both electrodes. This review highlights the benefits of a symmetric design, and categorizes five distinct classes of organic bipolar molecules used in both aqueous and non-aqueous solvents. By providing a comprehensive overview of their cell cycling and performance characteristics, the strengths and weaknesses of the diverse categories of bipolar molecules are highlighted for both solvent systems, as are opportunities for future development. This should guide new research directions and advance the development of practical symmetric ORFBs.

关键词： Redox flow battery Symmetric battery Organic battery Aqueous electrolyte Non-aqueous electrolyte

Dynamic mechanical analysis of single walled carbon nanotubes/polymethyl methacrylate nanocomposite films

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Chinese Physics B 2015年第10期24卷 331-335页

作者： ali badawi N.al-Hosiny Department of Physics Faculty of ScienceTaif University Department of Physics Faculty of ScienceAljouf University

Dynamic mechanical properties of nanocomposite films with different ratios of single walled carbon nanotubes/polymethyl methacrylate（SWCNTs/PMMA） are studied. Nanocomposite films of different ratios（0, 0.5, 1.0, and2.0 weight percent（wt%）） of SWCNTs/PMMA are fabricated by using a casting technique. The morphological and structural properties of both SWCNT powder and SWCNTs/PMMA nanocomposite films are investigated by using a high resolution transmission electron microscope and x-ray diffractometer respectively. The mechanical properties including the storage modulus, loss modulus, loss factor（tan δ） and stiffness of the nanocomposite film as a function of temperature are recorded by using a dynamic mechanical analyzer at a frequency of 1 Hz. Compared with pure PMMA film, the nanocomposite films with different ratios of SWCNTs/PMMA are observed to have enhanced storage moduli, loss moduli and high stiffness, each of which is a function of temperature. The intensity of the tan δ peak for pure PMMA film is larger than those of the nanocomposite films. The glass transition temperature（T g） of SWCNTs/PMMA nanocomposite film shifts towards the higher temperature side with respect to pure PMMA film from 91.2？C to 99.5？C as the ratio of SWCNTs/PMMA increases from 0 to 2.0 wt%.

关键词： SWCNTs/PMMA nanocomposite mechanical properties stiffness glass transition temperature

Massless Dirac perturbations of black holes in f(Q)gravity:quasinormal modes and a weak deflection angle

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Communications in Theoretical Physics 2024年第9期76卷 73-82页

作者： Ahmad al-badawi Sohan Kumar Jha Department of Physics Al-Hussein Bin Talal UniversityPO Box 2071111Ma'anJordan Department of Physics Chandernagore CollegeChandernagoreHooghlyWest BengalIndia

This article considers a static and spherical black hole(BH)in f(Q)gravity.f(Q)gravity is the extension of symmetric teleparallel general relativity,where both curvature and torsion are vanishing and gravity is described by *** this study,we investigate the possible implications of quasinormal mode(QNM)modified Hawking spectra and deflection angles generated by the *** Wentzel–Kramers–Brillouin method is used to solve the equations of motion for massless Dirac perturbation fields and explore the impact of the nonmetricity parameter(Q_(0)).Based on the QNM computation,we can ensure that the BH is stable against massless Dirac perturbations and as Q_(0)increases the oscillatory frequency of the mode *** then discuss the weak deflection angle in the weak field limit *** compute the deflection angle up to the fourth order of approximation and show how the nonmetricity parameter affects *** find that the Q_(0)parameter reduces the deflection angle.

关键词： black holes in f(Q)gravity massless Dirac perturbations quasinormal modes deflection angle

Naturally Occurring Terpenes:A Promising Class of Organic Molecules to Address Influenza Pandemics

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Natural Products and Bioprospecting 2021年第4期11卷 405-419页

作者： Suhad a.a.al-Salihi Fabrizio alberti Applied Sciences Department University of TechnologyBaghdadIraq School of Life Sciences and Department of Chemistry University of WarwickGibbet Hill RoadCoventry CV47ALUK

Since the olden times,infectious diseases have largely affected human *** newly emerged infections are excessively caused by viruses that are largely associated with mammal *** casualties of these emergencies are significantly influenced by the way human beings interact with the reservoirs,especially the animal *** our review we will consider the evolutionary and the ecological scales of such infections and their consequences on the public health,with a focus on the pathogenic influenza A *** nutraceutical properties of fungal and plant terpene-like molecules will be linked to their ability to lessen the symptoms of viral infections and shed light on their potential use in the development of new *** challenging methods in antiviral discovery will also be discussed in this *** authors believe that pharmacognosy is the“wave of future pharmaceuticals”,as it can be continually produced and scaled up under ecofriendly *** diagnostic methods and strategies however are required to standardise those naturally occurring resources.

关键词： Influenza A Virus Fungal terpenes Plant terpenes Antivirals

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

Effects of P301L-TAU on post-translational modifications of microtubules in human iPSC-derived cortical neurons and TAU transgenic mice

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Neural Regeneration Research 2025年第8期20卷 2348-2360页

作者： Mohamed Aghyad al Kabbani Christoph Köhler Hans Zempel Institute of Human Genetics Faculty of Medicine and University Hospital CologneUniversity of CologneCologneGermany Center for Molecular Medicine Cologne(CMMC) University of CologneCologneGermany Center Anatomy Department ⅡMedical FacultyUniversity of CologneCologneGermany

TAU is a microtubule-associated protein that promotes microtubule assembly and stability in the *** is missorted and aggregated in an array of diseases known as *** are essential for neuronal function and regulated via a complex set of post-translational modifications,changes of which affect microtubule stability and dynamics,microtubule interaction with other proteins and cellular structures,and mediate recruitment of microtubule-severing *** impairment of microtubule dynamics causes neuronal dysfunction,we hypothesize cognitive impairment in human disease to be impacted by impairment of microtubule *** therefore aimed to study the effects of a disease-causing mutation of TAU(P301L)on the levels and localization of microtubule post-translational modifications indicative of microtubule stability and dynamics,to assess whether P301L-TAU causes stability-changing modifications to *** investigate TAU localization,phosphorylation,and effects on tubulin post-translational modifications,we expressed wild-type or P301L-TAU in human MAPT-KO induced pluripotent stem cell-derived neurons(i Neurons)and studied TAU in neurons in the hippocampus of mice transgenic for human P301L-TAU(p R5 mice).Human neurons expressing the longest TAU isoform(2N4R)with the P301L mutation showed increased TAU phosphorylation at the AT8,but not the p-Ser-262 epitope,and increased polyglutamylation and acetylation of microtubules compared with endogenous TAU-expressing neurons.P301L-TAU showed pronounced somatodendritic presence,but also successful axonal enrichment and a similar axodendritic distribution comparable to exogenously expressed 2N4R-wildtype-TAU.P301L-TAU-expressing hippocampal neurons in transgenic mice showed prominent missorting and tauopathy-typical AT8-phosphorylation of TAU and increased polyglutamylation,but reduced acetylation,of microtubules compared with non-transgenic *** sum,P301L-TAU results in changes in micr

关键词： human induced pluripotent stem cell microtubules P301L pR5 mice TAU tauopathy tubulin code

Modified aquila optimizer for forecasting oil production

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Geo-Spatial Information Science 2022年第4期25卷 519-535页

作者： Mohammed a.a.al-qaness Ahmed A.Ewees Hong Fan Ayman Mutahar alRassas Mohamed Abd Elaziz State Key Laboratory for Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina Systems University of Bisha Department of e-BishaKingdom of Saudi Arabia Department of Computer Damietta UniversityDamiettaEgypt School of Petroleum Engineering China University of Petroleum(East China)QingdaoChina Department of Mathematics Faculty of ScienceZagazig UniversityZagazigEgypt Artificial Intelligence Research Center(AIRC) Ajman UniversityAjman 346United Arab Emirates Faculty of Computer Science&Engineering Galala UniversitySuze 435611Egypt

Oil production estimation plays a critical role in economic plans for local governments and ***,many studies applied different Artificial Intelligence(AI)based meth-ods to estimate oil production in different *** Adaptive Neuro-Fuzzy Inference System(ANFIS)is a well-known model that has been successfully employed in various applica-tions,including time-series ***,the ANFIS model faces critical shortcomings in its parameters during the configuration *** this point,this paper works to solve the drawbacks of the ANFIS by optimizing ANFIS parameters using a modified Aquila Optimizer(AO)with the Opposition-Based Learning(OBL)*** main idea of the developed model,AOOBL-ANFIS,is to enhance the search process of the AO and use the AOOBL to boost the performance of the *** proposed model is evaluated using real-world oil produc-tion datasets collected from different oilfields using several performance metrics,including Root Mean Square Error(RMSE),Mean Absolute Error(MAE),coefficient of determination(R2),Standard Deviation(Std),and computational ***,the AOOBL-ANFIS model is compared to several modified ANFIS models include Particle Swarm Optimization(PSO)-ANFIS,Grey Wolf Optimizer(GWO)-ANFIS,Sine Cosine algorithm(SCA)-ANFIS,Slime Mold algorithm(SMA)-ANFIS,and Genetic algorithm(GA)-ANFIS,***,it is compared to well-known time series forecasting methods,namely,Autoregressive Integrated Moving Average(ARIMA),Long Short-Term Memory(LSTM),Seasonal Autoregressive Integrated Moving Average(SARIMA),and Neural Network(NN).The outcomes verified the high performance of the AOOBL-ANFIS,which outperformed the classic ANFIS model and the compared models.

关键词： Oil production ANFIS opposition-based learning(OBL) Aquila Optimizer(AO) time series forecasting Tahe oilfield Sunah oilfield