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ECNU Review of Education 2024年第1期7卷 42-65页

作者： Mark Bray Anas Hajar East China Normal university&The university of Hong Kong nazarbayev university

Purpose:Private supplementary tutoringwidely known as shadow education because of the ways in which it mimics regular schooling-is increasingly visible across the globe.The Middle East is no exception,though the phenomenon has received relatively little attention in the English-language literature.This article maps some key features of shadow education,identifying ways in which contextual forces have shaped it.Design/Approach/Methods:The article focuses on patterns across and within the six members of the Gulf Cooperation Council(GCC),namely Bahrain,Kuwait,Oman,Qatar,Saudi Arabia,and the United Arab Emirates.It draws on literature in both Arabic and English and shows the value of multipleunits of comparison.Findings:Private tutoring has a long history as a significant phenomenon in some GCC countries,but in others developed more recently.Some governments have had active policies to dampen the phenomenon,but with little success.Factors in the complex dynamics include social,economic andcultural forces.OriginalityValue:The article assembles literature from around the region,noting both commonalities and diversities among GCC members.It contributes to the global literature by providing the regional mapping from this specific part of the world and by showing comparisons with other world regions.

关键词： Cultural forces Gulf Cooperation Council Middle East policies private tutoring shadow education

Detection and Defense Method Against False Data Injection Attacks for Distributed Load Frequency Control System in Microgrid

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 913-924页

作者： Zhixun Zhang Jianqiang Hu Jianquan Lu Jie Yu Jinde Cao Ardak Kashkynbayev the School of Cyber Science and Engineering Southeast University the School of Mathematics Southeast University School of Electronic Information and Electrical Engineering Chengdu University School of Electrical Engineering Southeast University the Yonsei Frontier Laboratory Yonsei University the Department of Mathematics Nazarbayev University

In the realm of microgrid(MG), the distributed load frequency control(LFC) system has proven to be highly susceptible to the negative effects of false data injection attacks(FDIAs). Considering the significant responsibility of the distributed LFC system for maintaining frequency stability within the MG, this paper proposes a detection and defense method against unobservable FDIAs in the distributed LFC system. Firstly, the method integrates a bi-directional long short-term memory(Bi LSTM) neural network and an improved whale optimization algorithm(IWOA) into the LFC controller to detect and counteract FDIAs. Secondly, to enable the Bi LSTM neural network to proficiently detect multiple types of FDIAs with utmost precision, the model employs a historical MG dataset comprising the frequency and power variances. Finally, the IWOA is utilized to optimize the proportional-integral-derivative(PID) controller parameters to counteract the negative impacts of FDIAs. The proposed detection and defense method is validated by building the distributed LFC system in Simulink.

关键词： Power system stability Frequency control Renewable energy sources Neural networks Power generation Stability criteria Microgrids

护理人员对医院护理科研学术氛围感知的质性研究

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International Journal of Nursing Sciences 2024年第2期11卷 233-240页

作者： Ejercito Mangawa Balay-odao Jonas Preposi Cruz Joseph UAlmazan Department of Medicine School of MedicineNazarbayev UniversityAstanaKazakhstan

目的医疗机构面临的挑战是建立一种促进护理科研发展的组织文化。护理科研的建设一直被认为是护理学科进步的重要组成部分。因此,本研究描述了护士对所在医院护理科研学术氛围的看法。方法采用半结构式个人访谈法收集资料。于2022年12月... 详细信息

目的医疗机构面临的挑战是建立一种促进护理科研发展的组织文化。护理科研的建设一直被认为是护理学科进步的重要组成部分。因此,本研究描述了护士对所在医院护理科研学术氛围的看法。方法采用半结构式个人访谈法收集资料。于2022年12月至2023年4月,在菲律宾东部1所医院选取17名护士参与研究。采用Braun和Clarke主题分析法对数据进行分析。结果共提炼出3个主题及7个副主题:影响护士的行为和绩效(帮助获取研究信息和学习、灵活性和适应性、护士之间的合作与沟通),影响护士的研究参与(领导策略、培训与专业发展),以及影响医院对变化的适应(组织绩效与成功、护士参与和工作满意度)。结论积极的护理研究文化对塑造护士的行为和绩效、参与护理研究以及医院对变化的适应具有至关重要的作用,因此对医院护理研究文化的益处提供了支持。总之,提炼出的主题有助于护理管理者更深入地了解护理研究文化对医疗保健系统各层面的影响。

关键词：文化医院护理人员菲律宾定性研究研究

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Concurrent hetero-/homo-geneous electrocatalysts to bi-phasically mediate sulfur species for lithium-sulfur batteries

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Journal of Energy Chemistry 2024年第6期93卷 663-668,I0016页

作者： Rui-Bo LingHu Jin-Xiu Chen Jin-Hao Zhang Bo-Quan Li Qing-Shan Fu Gulnur Kalimuldina Geng-Zhi Sun Yunhu Han Long Kong Xi’an Institute of Flexible Electronics(IFE) Northwestern Polytechnical UniversityXi’an 710129ShaanxiChina Institute of Advanced Materials Nanjing Tech UniversityNanjing 211816JiangsuChina Advanced Research Institute of Multidisciplinary Science Beijing Institute of TechnologyBeijing 100081China Department of Mechanical and Aerospace Engineering School of Engineering and Digital SciencesNazarbayev UniversityKabanbay Batyr Ave.53Astana 010000Kazakhstan

Expediting redox kinetics of sulfur species on conductive scaffolds with limited charge accessible surface is considered as an imperative approach to realize energy-dense and power-intensive lithium-sulfur(Li-S)batteries.In this work,the concept of concurrent hetero-/homo-geneous electrocatalysts is proposed to simultaneously mediate liquid-solid conversion of lithium polysulfides(LiPSs)and solid lithium disulfide/sulfide(Li_(2)S_(2)/Li_(2)S)propagation,the latter of which suffers from sluggish reduction kinetics due to buried conductive scaffold surface by extensive deposition of Li_(2)S_(2)/Li_(2)S.The selected model material to verify this concept is a two-in-one catalyst:carbon nanotube(CNT)scaffold supported iron-cobalt(Fe-Co)alloy nanoparticles and partially carbonized selenium(C-Se)component.The Fe-Co alloy serves as a heterogeneous electrocatalyst to seed Li_(2)S_(2)/Li_(2)S through sulphifilic active sites,while the C-Se sustainably releases soluble lithium polyselenides and functions as a homogeneous electrocatalyst to propagate Li_(2)S_(2)/Li_(2)S via solution pathways.Such bi-phasic mediation of the sulfur species benefits reduction kinetics of LiPS conversion,especially for the massive Li_(2)S_(2)/Li_(2)S growth scenario by affording an additional solution directed route in case of conductive surface being largely buried.This strategy endows the Li-S batteries with improved cycling stability(836 mA h g^(-1)after 180 cycles),rate capability(547 mA h g^(-1)at 4 C)and high sulfur loading superiority(2.96 mA h cm^(-2)at 2.4 mg cm^(-2)).This work hopes to enlighten the employment of bi-phasic electrocatalysts to dictate liquid-solid transformation of intermediates for conversion chemistry batteries.

关键词： Lithium-sulfur batteries Electrocatalysis Lithium polysulfides Sulfur cathode Energy density

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Sentiment Analysis of Low-Resource Language Literature Using Data Processing and Deep Learning

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Computers, Materials & Continua 2024年第4期79卷 713-733页

作者： Aizaz Ali Maqbool Khan Khalil Khan Rehan Ullah Khan Abdulrahman Aloraini Department of IT and Computer Science Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripur22620Pakistan Software Competence Center Hagenberg Softwarepark 32aHagenberg4232Austria Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstana010000Kazakhstan Department of Information Technology College of ComputerQassim UniversityP.O.Box 1162BuraydahSaudi Arabia

Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse languages.While numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiveness of the models. The research findings revea

关键词： Urdu sentiment analysis convolutional neural networks recurrent neural network deep learning natural language processing neural networks

ABMRF:An Ensemble Model for Author Profiling Based on Stylistic Features Using Roman Urdu

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Intelligent Automation & Soft Computing 2024年第2期39卷 301-317页

作者： Aiman Muhammad Arshad Bilal Khan Khalil Khan Ali Mustafa Qamar Rehan Ullah Khan Department of Computer Science City University of Science and Information TechnologyPeshawarPakistan Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstanaKazakhstan Department of Computer Science College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia

This study explores the area of Author Profiling(AP)and its importance in several industries,including forensics,security,marketing,and education.A key component of AP is the extraction of useful information from text,with an emphasis on the writers’ages and genders.To improve the accuracy of AP tasks,the study develops an ensemble model dubbed ABMRF that combines AdaBoostM1(ABM1)and Random Forest(RF).The work uses an extensive technique that involves textmessage dataset pretreatment,model training,and assessment.To evaluate the effectiveness of several machine learning(ML)algorithms in classifying age and gender,including Composite Hypercube on Random Projection(CHIRP),Decision Trees(J48),Na飗e Bayes(NB),K Nearest Neighbor,AdaboostM1,NB-Updatable,RF,andABMRF,they are compared.The findings demonstrate thatABMRFregularly beats the competition,with a gender classification accuracy of 71.14%and an age classification accuracy of 54.29%,respectively.Additional metrics like precision,recall,F-measure,Matthews Correlation Coefficient(MCC),and accuracy support ABMRF’s outstanding performance in age and gender profiling tasks.This study demonstrates the usefulness of ABMRF as an ensemble model for author profiling and highlights its possible uses in marketing,law enforcement,and education.The results emphasize the effectiveness of ensemble approaches in enhancing author profiling task accuracy,particularly when it comes to age and gender identification.

关键词： Machine learning author profiling AdaBoostM1 random forest ensemble learning text classification

Application of anionic surfactant\engineered water hybrid EOR in carbonate formations:An experimental analysis

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Petroleum 2022年第4期8卷 466-475页

作者： Aigerim Sekerbayeva Peyman Pourafshary Muhammad Rehan Hashmet Department of Petroleum Engineering School of Mining and GeosciencesNazarbayev UniversityNur-SultanKazakhstan

A hybrid enhanced oil recovery(EOR)method by combining low salinity water(LSW)and low salinity surfactant(LSS)flooding techniques was designed.Different experiments were done to screen the Caspian seawater(SW)with altered ionic composition and surfactant,for the optimized performance in Kazakhstani carbonate oil fields.Changing to a more water-wet state and creating the middle phase were studied as the main criteria to select the best-engineered brine and anionic surfactant.The largest alteration towards the water-wet condition was recorded at 10 times dilution of the SW with 3-and 6-times spiked calcium and sulfate ions,respectively(10xSW-6SO4,Mg,3Ca).This combination of anionic surfactants with carbonate formations is considered as a new approach in hybrid EOR methods.Among the anionic surfactants screened,Soloterra-113H(alkyl benzenesulfonic acid)showed the best solubilization ratio,aqueous stability and Winsor type 3 microemulsions.The wettability alteration by the combination of optimized brine and screened surfactant was greater compared to the standalone LSW,which was confirmed by the 10difference in contact angle measurement.The microemulsion phase constituted nearly 40%of the total height of the oil/brine column by the hybrid method.The recovery factor after injecting formation water was 52%,and it increased to 61%after optimized LSW injection.After switching to the engineered brine/surfactant,the recovery factor reached 70%,which proves the effectiveness of the hybrid method.The proposed combined method works better than either standalone EOR method due to the higher alteration in capillary number by changing wettability and reducing IFT,which leads to higher oil recovery.

关键词： method. surfactant anionic

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Flue gas analysis for biomass and coal co‑fring in fuidized bed:process simulation and validation

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International Journal of Coal Science & Technology 2022年第4期9卷 71-81页

作者： Daulet Zhakupov Lyazzat Kulmukanova Yerbol Sarbassov Dhawal Shah Department of Chemical and Materials Engineering School of Engineering and Digital SciencesNazarbayev University010001 Nur-SultanKazakhstan

Coal-conversion technologies,although used ubiquitously,are often discredited due to high pollutant emissions,thereby emphasizing a dire need to optimize the combustion process.The co-fring of coal/biomass in a fuidized bed reactor has been an efcient way to optimize the pollutants emission.Herein,a new model has been designed in Aspen Plus®to simultaneously include detailed reaction kinetics,volatile compositions,tar combustion,and hydrodynamics of the reactor.Validation of the process model was done with variations in the fuel including high-sulfur Spanish lignite,high-ash Ekibastuz coal,wood pellets,and locally collected municipal solid waste(MSW)and the temperature ranging from 1073 to 1223 K.The composition of the exhaust gases,namely,CO/CO_(2)/NO/SO_(2)were determined from the model to be within 2%of the experimental observations.Co-combustion of local MSW with Ekibastuz coal had fue gas composition ranging from 1000 to 5000 ppm of CO,16.2%–17.2%of CO_(2),200–550 ppm of NO,and 130–210 ppm of SO_(2).A sensitivity analysis on co-fring of local biomass and Ekibastuz coal demonstrated the optimal operating temperature for fuidized bed reactor at 1148 K with the recommended biomass-to-coal ratio is 1/4,leading to minimum emissions of CO,NO,and SO_(2).

关键词： Biomass cofring Fluidized-bed combustion Advanced process simulation Flue-gas emissions Fuel utilization Aspen plus

Investigation of replacing tracer flooding analysis by capacitance resistance model to estimate interwell connectivity

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Petroleum 2023年第1期9卷 61-71页

作者： Adilet Aliyev Davood Zivar Peyman Pourafshary School of Mining and Geosciences Nazarbayev UniversityAstanaKazakhstan PanTerra Geoconsultants B.V LeiderdorpNetherlands

Interwell connectivity is an essential parameter for managing waterflooding operations in a field.Analysis of the tracer injection operation is a well-known approach to studying injected fluids distribution in a reservoir and toward producer wells.Developed in the early 2000s,capacitance-resistance model(CRM)is an analytical approach for waterflooding modeling and optimization.Production/injection data are used as input to model the mass balance and estimate parameters such as the interwell connectivity.In this work,we investigated the accuracy of applying the capacitance-resistance model to mimic a tracer test.Such an approach helps assess the connection between the wells and decide on further field development steps cheaper and quicker.Connectivity values estimated by tracer tests and CRM were analyzed and compared for synthetic and real fields.CRM was capable of modeling waterflooding and estimating production in both fields with acceptable accuracy.Parameters such as well spacing and fluid loss during the injection were considered to improve the accuracy of the CRM approach to calculate the interwell connectivity between injector/producer pairs.Our study showed that CRM could serve as a tool for a quick approximate estimation of interwell connectivity under certain assumptions and is recommended as a replacement for tracer flooding analysis,where the tracer test is not possible or is expensive.

关键词： connectivity capacitance analysis

Comparative study of natural chemical for enhanced oil recovery: Focus on extraction and adsorption at quartz sand surface

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Petroleum 2023年第1期9卷 83-93页

作者： Azza Hashim Abbas Ramzi A.Abd Alsaheb Jaafar Kamil Abdullah School of Mining and Geosciences Nazarbayev UniversityKazakhstan Al-khwarizmi College of Engineering University of BaghdadIraq Basrah university College of Science and Technology Iraq

In chemical enhanced oil recovery(CEOR),it is very important to utilize the excessive usage of chemicals.A great opportunity lies in adopting natural surfactants,since it is cheaper,ecosystem friendly,and less toxic than their counterpart synthetic surfactants.Despite the availability of natural surfactant sources,it is yet very early to decide on their applicability.Therefore,this research focuses on natural-saponin extracted from different raw materials available in the Middle East and their interaction with quartz-sand.A special focus was given to the adsorption isotherm models to describe the interaction with the reservoir rocks.Three raw materials were investigated are fenugreek,sugar beet leaves and chickpeas.The main extraction method employed was the chemical extraction using the soxhelet.The study used Uv–vis spectrometer to investigate the micellization behaviour and the consequent adsorption on quartz-sand.The presence of triterpenoid saponin is found dominant in all the sample,the intensity and purity differed according to the raw material source.Tthe critical micelle concentration(CMC)was at a close range of 4–5.5 wt%in all the samples.The highest adsorption was obtained by sugar beet leaves which is 192 g/kg.It is 25%and 37%higher than the Fenugreek and chickpeas,respectively.Increasing the salinity resulted in adsorption reduction between 2%and 56%.For the adsorption isotherms,it showed good agreement with the Langmuir model fitting.The remarkable finding is that the sugar beet leaves heterogeneous model seems to be valid by Frendluich and Halsey isotherms.

关键词： Natural surfactants Quartz Adsorption isotherm Salinity Fenugreek Sugar beet leaves Chickpeas