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Optimizing Average Electric Power During the Charging of Lithium-Ion Batteries Through the Taguchi Method

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Transactions of Tianjin University 2024年第2期30卷 152-166页

作者： Mohd H.s.Alrashdan Department of Electrical Engineering Al-Hussein Bin Talal UniversityMaan 71110Jordan

In recent times, lithium-ion batteries have been widely used owing to their high energy density, extended cycle lifespan, and minimal self-discharge rate. The design of high-speed rechargeable lithium-ion batteries faces a significant challenge owing to the need to increase average electric power during charging. This challenge results from the direct influence of the power level on the rate of chemical reactions occurring in the battery electrodes. In this study, the Taguchi optimization method was used to enhance the average electric power during the charging process of lithium-ion batteries. The Taguchi technique is a statistical strategy that facilitates the systematic and efficient evaluation of numerous experimental variables. The proposed method involved varying seven input factors, including positive electrode thickness, positive electrode material, positive electrode active material volume fraction, negative electrode active material volume fraction, separator thickness, positive current collector thickness, and negative current collector thickness. Three levels were assigned to each control factor to identify the optimal conditions and maximize the average electric power during charging. Moreover, a variance assessment analysis was conducted to validate the results obtained from the Taguchi analysis. The results revealed that the Taguchi method was an eff ective approach for optimizing the average electric power during the charging of lithium-ion batteries. This indicates that the positive electrode material, followed by the separator thickness and the negative electrode active material volume fraction, was key factors significantly infl uencing the average electric power during the charging of lithium-ion batteries response. The identification of optimal conditions resulted in the improved performance of lithium-ion batteries, extending their potential in various applications. Particularly, lithium-ion batteries with average electric power of 16 W and 17

关键词： Lithium-ion batteries Average electric power during charging Taguchi method COMsOL Multiphysics software C rate L27 orthogonal array

A Locality-sensitive Hashing-Based Jamming Detection system for IoT Networks

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Computers, Materials & Continua 2022年第12期73卷 5943-5959页

作者： P.Ganeshkumar talal Albalawi Computer science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)RiyadhSaudi Arabia

Internet of things(IoT)comprises many heterogeneous nodes that operate together to accomplish a human friendly or a business task to ease the ***,IoT nodes are connected in wireless media and thus they are prone to jamming *** the present scenario jamming detection(JD)by using machine learning(ML)algorithms grasp the attention of the researchers due to its virtuous *** this research,jamming detection is modelled as a classification problem which uses several *** one/two or minimumnumber of features produces vague results that cannot be *** the relationship between the feature and the class label cannot be efficiently determined,specifically,if the chosen number of features for training is minimum(say 1 or 2).To obtain good results,machine-learning algorithms are trained by large number of data ***,collection of large number of datasets to solve jamming detection is not easy and most of the times generation and collection of large data sets become *** this paper,to solve this problem,more number of features with nominal number of data’s is considered that eases the data collection and the classification *** this research,an efficient technique based on locality sensitive hashing(LsH)for k-nearest neighbor algorithm(k-NN),which takes less time for constructing and querying the hash table that gives good accuracy is proposed and *** the results,it is clear that the obtained results are validatable and the model is more sensible.

关键词： IoT jamming detection k-NN machine learning

Bridging finite element and deep learning: High-resolution stress distribution prediction in structural components

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Frontiers of structural and Civil Engineering 2022年第11期16卷 1365-1377页

作者： Hamed BOLANDI Xuyang LI talal sALEM Vishnu Naresh BODDETI Nizar LAJNEF Department of Civil and Environmental Engineering Michigan State UniversityEast LansingMI 48824USA Department of Computer science and Engineering Michigan State UniversityEast LansingMI 48824USA

Finite-element analysis(FEA)for structures has been broadly used to conduct stress analysis of various civil and mechanical engineering *** methods,such as FEA,provide high fidelity results but require the solution of large linear systems that can be computationally ***,Deep Learning(DL)techniques can generate results significantly faster than conventional run-time *** can prove extremely valuable in real-time structural assessment *** proposed method uses deep neural networks in the form of convolutional neural networks(CNN)to bypass the FEA and predict high-resolution stress distributions on loaded steel plates with variable loading and boundary *** CNN was designed and trained to use the geometry,boundary conditions,and load as input to predict the stress *** proposed technique’s performance was compared to finite-element simulations using a partial differential equation(PDE)*** trained DL model can predict the stress distributions with a mean absolute error of 0.9%and an absolute peak error of 0.46%for the von Mises stress *** study shows the feasibility and potential of using DL techniques to bypass FEA for stress analysis applications.

关键词： Deep Learning finite element analysis stress contours structural components

Effect of Litter Diversity and Evenness on Decomposition in Baijianghe Peatland of Changbai Mountains,China

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Effect of Litter Diversity and Evenness on Decomposition in ...

作者： talal Asif 东北师范大学

学位级别：硕士

Peatlands make a large carbon（C）pool but their carbon sink is susceptible and labile to fluctuations in land-use and climate especially moisture *** decomposition is effected by degradation in addition to litter quality and diversity components that’s why in peatlands litter decomposition is *** litter decomposition studies had well documented the effects of species richness and composition,whereas the effect of evenness（relative abundance）along with pristine and drained peatland got less *** this study,we explored the effect of diversity and evenness（relative abundance）on decomposition at two microsites of peatland as a pristine and drained by using a litter bag *** species including two bryophytes（nonvascular）species as sphagnum flexuosum,sphagnum magellanicum and two vascular species Potentilla fruticosa（dwarf shrub）and Carex lasiocarpa（sedge）were chosen as mono litter and 6 compositions with 3 ratios of relative abundance: M1（50%:50%）,M2（30%:70%）and M3（70%:30%）.Annually,mono litter results showed that mass loss（%）of vascular species（*** and ***）was significantly higher than the non-vascular species（*** and ***）on pristine and drained *** nutrients study,vascular species（*** and ***）showed greater C and N contents in pristine and drained peatlands than non-vascular species（*** and ***）therefore C/N contents were lower in vascular species than non-vascular *** using the General Linear Model（GLM）,we found that diversity and evenness produce non-additive effects of litter mixing on mass loss but the direction for all the compositions was antagonistic which means that mass loss was not accelerated by litter mixing on both sites however evenness does not play a significant role in mass loss within each specific composition *** nutrients study,litter mixing produces non-additive effects on C content but in the case of N content（%）an

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Impact of preterm birth and low birth weight on medical conditions, medication use and mortality among neonates: a prospective observational cohort study

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World Journal of Pediatrics 2019年第3期15卷 281-288页

作者： krishna Undela Bashar talal saad Mohammed Parthasarathi Gurumurthy srinivasa Murthy Doreswamy Department of Pharmacy Practice JSS College of Pharmacy.JSS Academy of Higher Education and ResearchSS NagaraMysuru.Karnataka 570 015.India Department of Pediatrics JSS Medical College and Hospital.JSS Academy of Higher Education and ResearchMahatma Gandhi RoadMysuruKarnataka 570 004India

Background There is a paucity of studies conducted in India on neonatal outcomes of preterm birth and low birth ***,we aimed to assess the impact of preterm birth and low birth weight on medical conditions,medication use and mortality among *** A prospective observational cohort study was conducted at the neonatal intensive care unit (NICU) over a period of 9 *** of either sex,admitted to NICU and who received at least one medication were enrolled in the *** and demographic data,reason(s) for NICU admission,diagnoses,medications prescribed,medication-related problems,discharge status and the direct medical cost were documented and *** Four hundred and five neonates Were included in the study:60.5% were boys,32.7% were preterm and 44.2% were born *** sepsis (n =125,16.7%),unconjugated hyperbilirubinemia (n =83,11.1%) and respiratory distress syndrome (n =62,8.3%) were the most common medical conditions and were significantly more common among preterm and underweight *** half of the medications prescribed were anti-infectives for systemic use (n =1310,47.4%).The mean number of medications received by neonates increased from term to extremely preterm (5.2-15.0) and normal birth weight to extremely low birth weight (5.0-14.9).Mortality rate was significantly higher among extremely preterm (66.7%),and very preterm (15.2%) neonates compared to term (2.9%) *** median direct medical cost for NICU admission was INR 21,430 (UsD 331).Conclusion Medical conditions,medications prescribed and mortality rate were significantly higher among preterm and underweight neonates admitted to NICU.

关键词： Low birth weight Medical conditions Medications Mortality Preterm birth

Experimental investigation of the effects of various parameters on viscosity reduction of heavy crude by oil-water emulsion

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Petroleum science 2015年第1期12卷 170-176页

作者： talal Al-Wahaibi Yahya Al-Wahaibi Abdul-Aziz R.Al-Hashmi Farouq s.Mjalli safiya Al-Hatmi Petroleum & Chemical Engineering Department College of Engineering Sultan Qaboos University

The effects of water content, shear rate, temperature, and solid particle concentration on viscosity reduction （VR） caused by forming stable emulsions were investigated using Omani heavy crude oil. The viscosity of the crude oil was initially measured with respect to shear rates at different temperatures from 20 to 70℃. The crude oil exhibited a shear thinning behavior at all the temperatures. The strongest shear thinning was observed at 20℃. A non-ionic water soluble surfactant （Triton X-100） was used to form and stabilize crude oil emulsions. The emulsification process has significantly reduced the crude oil viscosity. The degree of VR was found to increase with an increase in water content and reach its maximum value at 50 % water content. The phase inversion from oil- oil emulsion occurred at 30 in-water emulsion to water-in- % water content. The results indicated that the VR was inversely proportional to temperature and concentration of silica nanoparticles. For water-in-oil emulsions, VR increased with shear rate and eventually reached a plateau at a shear rate of around 350 s^-1. This was attributed to the thinning behavior of the continuous phase. The VR of oil-in-water emulsions remained almost constant as the shear rate increased due to the Newtonian behavior of water, the continuous phase.

关键词： Viscosity reduction Phase inversion Non-newtonian fluid Oil-in-water emulsions Heavy crude oil

An IoT-Based Energy Conservation smart Classroom system

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Intelligent Automation & soft Computing 2023年第3期35卷 3785-3799页

作者： talal H.Noor El-sayed Atlam Abdulqader M.Almars Ayman Noor Amer s.Malki College of Computer science and Engineering Taibah UniversityYanbu46421-7143MedinahKSA Department of Computer science Faculty of ScienceTanta UniversityTantaEgypt College of Computer science and Engineering Taibah UniversityMedinahKSA

With the increase of energy consumption worldwide in several domains such as industry,education,and transportation,several technologies played an inﬂuential role in energy conservation such as the Internet of Things(IoT).In this article,we describe the design and implementation of an IoT-based energy conser-vation smart classroom system that contributes to energy conservation in the edu-cation *** proposed system not only allows the user to access and control IoT devices(e.g.,lights,projectors,and air conditions)in real-time,it also has the capability to aggregate the estimated energy consumption of an IoT device,the smart classroom,and the building based on the energy consumption and cost model that we ***,the proposed model aggregates the estimated energy cost according to the saudi Electricity Company(sEC)***,the model aggregates in real-time the estimated energy conservation percentage and estimated money-saving percentage compared to data collected when the system wasn't *** feasibility and beneﬁts of our system have been validated on a real-world scenario which is a classroom in the college of computer science and engineering,Taibah University,Yanbu *** results of the experimental studies are promising in energy conservation and cost-saving when using our proposed system.

关键词： Energy consumption energy conservation energy cost Internet of Things(IoT) smart classroom

Fine-Grained soft Ear Biometrics for Augmenting Human Recognition

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Computer systems science & Engineering 2023年第11期47卷 1571-1591页

作者： Ghoroub talal Bostaji Emad sami Jaha Department of Computer science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia

Human recognition technology based on biometrics has become a fundamental requirement in all aspects of life due to increased concerns about security and privacy ***,biometric systems have emerged as a technology with the capability to identify or authenticate individuals based on their physiological and behavioral *** different viable biometric modalities,the human ear structure can offer unique and valuable discriminative characteristics for human recognition *** recent years,most existing traditional ear recognition systems have been designed based on computer vision models and have achieved successful ***,such traditional models can be sensitive to several unconstrained environmental *** such,some traits may be difficult to extract automatically but can still be semantically perceived as soft *** research proposes a new group of semantic features to be used as soft ear biometrics,mainly inspired by conventional descriptive traits used naturally by humans when identifying or describing each ***,the research study is focused on the fusion of the soft ear biometric traits with traditional(hard)ear biometric features to investigate their validity and efficacy in augmenting human identification *** proposed framework has two subsystems:first,a computer vision-based subsystem,extracting traditional(hard)ear biometric traits using principal component analysis(PCA)and local binary patterns(LBP),and second,a crowdsourcing-based subsystem,deriving semantic(soft)ear biometric *** feature-level fusion experiments were conducted using the AMI database to evaluate the proposed algorithm’s *** obtained results for both identification and verification showed that the proposed soft ear biometric information significantly improved the recognition performance of traditional ear biometrics,reaching up to 12%for LBP and 5%for PCA descriptors;when fusing all three capa

关键词： Ear biometrics soft biometrics human ear recognition semantic features feature-level fusion computer vision machine learning

Landscape of global urban environmental resistome and its association with local socioeconomic and medical status

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science China(Life sciences) 2024年第6期67卷 1292-1301页

作者： Jun Wu Yige Hu Michael H Perlin David Danko Jun Lu Manuela Oliveira Johannes Werner Maria M Zambrano Maria A sierra Olayinka O Osuolale Paweł Łabaj Nicolás Rascovan Nur Hazlin Hazrin-Chong soojin Jang Haruo suzuki Marina Nieto-Caballero Bharath Prithiviraj Patrick k H Lee Agnieszka Chmielarczyk Anna Różańska Yongxiang Zhao Lan Wang Christopher E Mason Tieliu shi Center for Bioinformatics and Computational Biology and the Institute of Biomedical SciencesSchool of Life SciencesEast China Normal UniversityShanghai 200241China Department of Biology Program on Disease EvolutionUniversity of LouisvilleLouisville 40292USA Weill Cornell Medicine New York 10065USA The Bin talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine New York 10065USA Department of Pulmonary Medicine Shanghai Chest HospitalShanghai Jiao Tong UniversityShanghai 200025China i3s-Instituto de Investiga玢o e Inova玢o em saúde Universidade do PortoPorto 4050-290Portugal Ipatimup-Instituto de Patologia e Imunologia Molecular da Universidade do Porto Porto 4200-465Portugal Departamento de Biologia Faculdade de CiênciasUniversidade do PortoPorto 4050-290Portugal High Performance and Cloud Computing Group Zentrum für Datenverarbeitung(ZDV)Eberhard Karls University of TübingenW鋍hterstra遝7672074TübingenGermany Corporación Corpogen Research Center Bogotá110311Colombia Applied Environmental Metagenomics and Infectious Diseases Research(AEMIDR) Department of Biological SciencesElizade UniversityIlara-Mokin 340271Nigeria Maopolska Centre of Biotechnology Jagiellonian UniversityKraków 30-005Poland Aix-Marseille Université Mediterranean Institute of OceanologyUniversitéde ToulonCNRSIRDUM 110Marseille 83041France Department of Biological sciences and Biotechnology Faculty of Science and TechnologyUniversiti Kebangsaan Malaysia43600 UKM BangiSelangor Institut Pasteur korea Seoul 13488Republic of Korea Faculty of Environment and Information studies Keio UniversityFujisawaKanagawa 252-0882Japan University of Colorado at Boulder CivilEnvironmental and Architectural DepartmentBoulder 80303USA Brooklyn College of the City University of New York Brooklyn 11210USA school of Energy and Environment City University of Hong KongHong Kong 999077China Department of Microbiology Faculty of MedicineJagiellonian UniversityKraków 30-005Poland Biological Targeting Diagnosis and The

Antimicrobial resistance(AMR)poses a critical threat to global health and development,with environmental factors—particularly in urban areas—contributing significantly to the spread of antibiotic resistance genes(ARGs).However,most research to date has been conducted at a local level,leaving significant gaps in our understanding of the global status of antibiotic resistance in urban *** address this issue,we thoroughly analyzed a total of 86,213 ARGs detected within 4,728 metagenome samples,which were collected by the Meta sUB International Consortium involving diverse urban environments in 60 cities of 27 countries,utilizing a deep-learning based *** findings demonstrated the strong geographical specificity of urban environmental resistome,and their correlation with various local socioeconomic and medical *** also identified distinctive evolutionary patterns of ARG-related biosynthetic gene clusters(BGCs)across different countries,and discovered that the urban environment represents a rich source of novel *** study provides a comprehensive overview of the global urban environmental resistome,and fills a significant gap in our knowledge of large-scale urban antibiotic resistome analysis.

关键词： urban environment metagenome antibiotic resistance resistance diversity biosynthetic gene clusters