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Multimodal Deep Neural Networks for Digitized Document Classification

Computer Systems Science & Engineering 2024年第3期48卷 793-811页

作者： Aigerim Baimakhanova Ainur Zhumadillayeva Bigul Mukhametzhanova Natalya Glazyrina Rozamgul Niyazova Nurseit Zhunissov Aizhan Sambetbayeva Department of Computer Engineering Khoja Akhmet Yassawi International Kazakh-Turkish UniversityTurkistanKazakhstan Department of Computer and Software Engineering L.N.Gumilyov Eurasian National UniversityAstanaKazakhstan Department of Information and Computing Systems Non-Profit Joint Stock Company Abylkas Saginov Karaganda Technical UniversityKaragandaKazakhstan Department of Information Systems Al-Farabi Kazakh National UniversityAlmatyKazakhstan

As digital technologies have advanced more rapidly,the number of paper documents recently converted into a digital format has exponentially *** respond to the urgent need to categorize the growing number of digitized documents,the classification of digitized documents in real time has been identified as the primary goal of our study.A paper classification is the first stage in automating document control and efficient knowledge discovery with no or little human *** intelligence methods such as Deep Learning are now combined with segmentation to study and interpret those traits,which were not conceivable ten years *** learning aids in comprehending input patterns so that object classes may be *** segmentation process divides the input image into separate segments for a more thorough image *** study proposes a deep learning-enabled framework for automated document classification,which can be implemented in higher *** further this goal,a dataset was developed that includes seven categories:Diplomas,Personal documents,Journal of Accounting of higher education diplomas,Service letters,Orders,Production orders,and Student ***,a deep learning model based on Conv2D layers is proposed for the document classification *** the final part of this research,the proposed model is evaluated and compared with other machine-learning *** results demonstrate that the proposed deep learning model shows high results in document categorization overtaking the other machine learning models by reaching 94.84%,94.79%,94.62%,94.43%,94.07%in accuracy,precision,recall,F-score,and AUC-ROC,*** achieved results prove that the proposed deep model is acceptable to use in practice as an assistant to an office worker.

关键词： Document categorization deep learning machine learning classification digitization

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ON SOME BOUNDARY VALUE PROBLEMS FOR NONHOMOGENOUS POLYHARMONIC EQUATION WITH BOUNDARY OPERATORS OF FRACTIONAL ORDER

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Acta Mathematica Scientia 2016年第3期36卷 831-846页

作者： Batirkhan TURMETOV Institute of Mathematics and Mathematical Modeling Ministry of Education and Science Republic of Kazakhstan Department of Mathematics Akhmet Yasawi International Kazakh-Turkish University

In the paper we study questions about solvability of some boundary value prob- lems for a non-homogenous poly-harmonic equation. As a boundary operator we consider differentiation operator of fractional order in Mille... 详细信息

关键词： polyharmonic equation boundary value problem Dirichlet problem Neumann problem fractional derivative Miller-Ross operator

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Artificial Intelligence in Medicine:Real Time Electronic Stethoscope for Heart Diseases Detection

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Computers, Materials & Continua 2022年第2期70卷 2815-2833页

作者： Batyrkhan Omarov Nurbek Saparkhojayev Shyrynkyz Shekerbekova Oxana akhmetova Meruert Sakypbekova Guldina Kamalova Zhanna Alimzhanova Lyailya Tukenova Zhadyra Akanova Al-Farabi Kazakh National university AlmatyKazakhstan Khoja akhmet Yassawi International Kazakh-Turkish university TurkistanKazakhstan Abai Kazakh National Pedagogical university Kazakhstan NARXOZ university AlmatyKazakhstan

Diseases of the cardiovascular system are one of the major causes of death *** diseases could be quickly detected by changes in the sound created by the action of the *** dynamic auscultations need extensive professional knowledge and emphasis on listening *** is also an unmet requirement for a compact cardiac condition early warning *** this paper,we propose a prototype of a digital stethoscopic system for the diagnosis of cardiac abnormalities in real time using machine learning *** system consists of three subsystems that interact with each other(1)a portable digital subsystem of an electronic stethoscope,(2)a decision-making subsystem,and(3)a subsystemfor displaying and visualizing the results in an understandable *** electronic stethoscope captures the patient’s phonocardiographic sounds,filters and digitizes them,and then sends the resulting phonocardiographic sounds to the decision-making *** decision-making systemclassifies sounds into normal and abnormal using machine learning techniques,and as a result identifies abnormal heart *** display and visualization subsystem demonstrates the results obtained in an understandable way not only for medical staff,but also for patients and recommends further actions to *** a result of the study,we obtained an electronic stethoscope that can diagnose cardiac abnormalities with an accuracy of more than 90%.More accurately,the proposed stethoscope can identify normal heart sounds with 93.5%accuracy,abnormal heart sounds with 93.25%***,speed is the key benefit of the proposed stethoscope as 15 s is adequate for examination.

关键词： Stethoscope phonocardiogram machine learning classification heart diseases PCG

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About Radiation in ^natGd for Neutron Capture Therapy

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Journal of Health Science 2016年第1期4卷 35-44页

作者： Gayratulla A. Kulabdullaev G. A. Abdullaeva A. A. Kim T. T. Rakhmonov A. Kurmantaev Institute of Nuclear Physics Uz AS Tashkent Uzbekistan university of akhmet yasawi Turkestan Kazakhstan

In the present work, based on publications dedicated to ^natGd natural gadolinium isotopes, characteristics of secondary particles are analysed in details for various neutron-induced reactions. Characteristics of the secondary particles produced in these reactions that make significant contribution to absorbed dose are estimated. It is also established that the main contribution to the absorbed dose is made by secondary particles produced in interactions of neutrons and ^155Gd and ^157Gd isotopes. From comparison of gamma-radiation spectra it is defined that the amount of γ-quanta with energies 0-400 keV （i.e. effective γ-quanta） produced in the （n,γ）-reaction by ^155Gd is higher than that by ^157Gd. Compared spectra of other particles （internal conversion electrons, Auger electrons, x-ray radiation） have shown that earlier used average values of their energy must be defined more precisely. When biological objects are irradiated for approximately 30 minutes by epithermal neutrons in the ^natGd NCT （Gadolinium-based neutron-capture therapy）, one should take into account energies of secondary particles produced by ^152Gd, ^154Gd, ^156Gd, ^158Gd and ^160Gd isotopes as they have high linear energy transfer （LET）. It is demonstrated that when combined, all these secondary particles can make significant contribution to the absorbed dose at neutron-irradiation of biological objects by the ^natGd NCT technique.

关键词： Nuclear reactions natural gadolinium isotopes secondary particles conversion electrons epithermal neutrons neutron capture therapy radiation biological effect.

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A Review of Machine Learning Techniques in Cyberbullying Detection

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Computers, Materials & Continua 2023年第3期74卷 5625-5640页

作者： Daniyar Sultan Batyrkhan Omarov Zhazira Kozhamkulova Gulnur Kazbekova Laura Alimzhanova Aigul Dautbayeva Yernar Zholdassov Rustam Abdrakhmanov Al-Farabi Kazakh National university AlmatyKazakhstan International Information Technology university AlmatyKazakhstan International university of Tourism and Hospitality TurkistanKazakhstan Almaty university of Power Engineering and Telecommunications AlmatyKazakhstan Khoja akhmet Yassawi International Kazakh-Turkish university TurkistanKazakhstan Korkyt Ata Kyzylorda State university KyzylordaKazakhstan

Automatic identification of cyberbullying is a problem that is gaining traction,especially in the Machine Learning *** only is it complicated,but it has also become a pressing necessity,considering how social media has become an integral part of adolescents’lives and how serious the impacts of cyberbullying and online harassment can be,particularly among *** paper contains a systematic literature review of modern strategies,machine learning methods,and technical means for detecting cyberbullying and the aggressive command of an individual in the information space of the *** undertake an in-depth review of 13 papers from four scientific *** article provides an overview of scientific literature to analyze the problem of cyberbullying detection from the point of view of machine learning and natural language *** this review,we consider a cyberbullying detection framework on social media platforms,which includes data collection,data processing,feature selection,feature extraction,and the application ofmachine learning to classify whether texts contain cyberbullying or *** article seeks to guide future research on this topic toward a more consistent perspective with the phenomenon’s description and depiction,allowing future solutions to be more practical and effective.

关键词： Cyberbullying hate speech digital drama online harassment detection classification machine learning NLP

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Cyberbullying-related Hate Speech Detection Using Shallow-to-deep Learning

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Computers, Materials & Continua 2023年第1期74卷 2115-2131页

作者： Daniyar Sultan Aigerim Toktarova Ainur Zhumadillayeva Sapargali Aldeshov Shynar Mussiraliyeva Gulbakhram Beissenova Abay Tursynbayev Gulmira Baenova Aigul Imanbayeva Al-Farabi Kazakh National university AlmatyKazakhstan International Information Technology university AlmatyKazakhstan akhmet Yassawi International Kazakh-Turkish university TurkistanKazakhstan L.N.Gumilyov Eurasian National university AstanaKazakhstan South Kazakhstan State Pedagogical university ShymkentKazakhstan M.Auezov South Kazakhstan university ShymkentKazakhstan university of Friendship of People’s Academician A.Kuatbekov ShymkentKazakhstan National Academy of Education named after Y.Altynsarin AstanaKazakhstan

Communication in society had developed within cultural and geographical boundaries prior to the invention of digital *** latest advancements in communication technology have significantly surpassed the conventional constraints for communication with regards to time and *** new platforms have ushered in a new age of user-generated content,online chats,social network and comprehensive data on individual ***,the abuse of communication software such as social media websites,online communities,and chats has resulted in a new kind of online hostility and aggressive *** to widespread use of the social networking platforms and technological gadgets,conventional bullying has migrated from physical form to online,where it is termed as ***,recently the digital technologies as machine learning and deep learning have been showing their efficiency in identifying linguistic patterns used by cyberbullies and cyberbullying detection *** this research paper,we aimed to evaluate shallow machine learning and deep learning methods in cyberbullying detection *** deployed three deep and six shallow learning algorithms for cyberbullying detection *** results show that bidirectional long-short-term memory is the most efficient method for cyberbullying detection,in terms of accuracy and recall.

关键词： Cyberbullying machine learning deep learning classification NLP

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Modified UNet Model for Brain Stroke Lesion Segmentation on Computed Tomography Images

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Computers, Materials & Continua 2022年第6期71卷 4701-4717页

作者： Batyrkhan Omarov Azhar Tursynova Octavian Postolache Khaled Gamry Aidar Batyrbekov Sapargali Aldeshov Zhanar Azhibekova Marat Nurtas Akbayan Aliyeva Kadrzhan Shiyapov Al-Farabi Kazakh National university AlmatyKazakhstan International university of Tourism and Hospitality TurkistanKazakhstan Khoja akhmet Yassawi International Kazakh-Turkish university TurkistanKazakhstan Instituto Universitário de Lisboa LisbonPortugal International Information Technology university AlmatyKazakhstan South Kazakhstan State Pedagogical university ShymkentKazakhstan M.Auezov South Kazakhstan university ShymkentKazakshtan Kazakh-British Technical university AlmatyKazakhstan Asfendiyarov Kazakh National Medical university AlmatyKazakhstan Kazakh National Women’s Teacher Training university AlmatyKazakhstan Abai Kazakh National Pedagogical university AlmatyKazakhstan

The task of segmentation of brain regions affected by ischemic stroke is help to tackle important challenges of modern stroke imaging ***,at the moment,the models for solving this problem using machine learning methods are far from *** this paper,we consider a modified 3D UNet architecture to improve the quality of stroke segmentation based on 3Dcomputed tomography *** use the ISLES 2018(Ischemic Stroke Lesion Segmentation Challenge 2018)open dataset to train and test the proposed *** of the obtained results,as well as the ideas for further experiments are included in the *** evaluation is performed using the Dice or f1 score coefficient and the Jaccard *** architecture may simply be extended to ischemia segmentation and computed tomography image identification by selecting relevant *** Dice/f1 score similarity coefficient of our model shown58%and results close to ground truth which is higher than the standard 3D UNet model,demonstrating that our model can accurately segment ischemic *** modified 3D UNet model proposed by us uses an efficient averaging method inside a neural *** this set of ISLES is limited in number,using the data augmentation method and neural network regularization methods to prevent overfitting gave the best *** addition,one of the advantages is the use of the Intersection over Union loss function,which is based on the assessment of the coincidence of the shapes of the recognized zones.

关键词： Stroke ischemic stroke UNet deep learning segmentation ISLES 2018

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ON SOLVABILITY OF A BOUNDARY VALUE PROBLEM FOR A NONHOMOGENEOUS BIHARMONIC EQUATION WITH A BOUNDARY OPERATOR OF A FRACTIONAL ORDER

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Acta Mathematica Scientia 2014年第6期34卷 1695-1706页

作者： A.S.BERDYSHEV A.CABADA B.Kh.TURMETOV Department of Applied Mathematics and Informatics Kazakh National Pedagogical University named after AbaiAlmatyKazakhstan Departmento de Analise Matematica Facultade de Matematicas University of Santiago de CompostelaSantiago de Compostela Spain Khoja Ahmet yasawi International Kazakh-Turkish university Kazakhstan

This paper is concerned with the solvability of a boundary value problem for a nonhomogeneous biharmonic equation. The boundary data is determined by a differential operator of fractional order in the Riemann-Liouvill... 详细信息

关键词： biharmonic equation boundary value problem fractional derivative the RiemannLiouville operator

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Safflower (Carthamus Tinctorius L.) a Potential Source of Drugs against Cryptococcal Infections, Malaria and Leishmaniasis

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Phyton-International Journal of Experimental Botany 2020年第1期89卷 137-146页

作者： Aknur Turgumbayeva Gulbaram Ustenova Ubaidilla Datkhayev Khairolla Rahimov Silvijus Abramavicius Agile Tunaityte Kairat Zhakipbekov Kaldanay Kozhanova Saken Tulemissov Ozikhan Ustenova Gulmira Datkayeva Edgaras Stankevicius School of Pharmacy Asfendiyarov Kazakh National Medical UniversityAlmaty050000Kazakhstan National Center for Natural Product Research University of MississippiMS38677USA Department of Clinical Pharmacology Asfendiyarov Kazakh National Medical UniversityAlmaty050000Kazakhstan Institute of Physiology and Pharmacology Lithuanian University of Health SciencesKaunasLT44307Lithuania Intensive Care Unit Republican Vilnius University HospitalVilnius04130Lithuania Department of Pharmaceutical Disciplines Astana Medical UniversityAstana010000Kazakhstan Department of Chemistry and Biology Kazakhstan University of Peoples friendshipShymkent160000Kazakhstan Sub-Faculty of Tourism and Service Narxoz UniversityAlmaty050035Kazakhstan Department of General Clinical Disciplines and Ambulance Akhmet Yassawi International Kazakh-Turkish UniversityTurkestan161200Kazakhstan Institute of Cardiology Lithuanian University of Health SciencesKaunasLT44307Lithuania

In this research we present that Carthamus Tinctorius L.(***,otherwise known as Safflower)(Fig.1)may contain agents active in Cryptococcal infections,malaria and Leishmaniasis,as treatment options are becoming scarce due to drug resistance *** and pharmacological activities(antimicrobial,antimalarial,antileishmanial)of *** *** *** composition of volatile oil of safflower dried flowers was analyzed by gas chromatography-mass spectrophotometry with flame ionization detector(GC-FID)and in vitro sensitivity assays were performed to assess biological activity.8 known and 3 unknown compounds were detected in the extract(Fig.1).Then the Safflower ointment was manufactured and its acute toxicity study on rats was *** volatile oil of *** L exhibited activity against Cryptococcus neoformans,Plasmodium falciparum and Leishmania *** volatile oil has anticryptococcal,antimalarial and antileishmanial *** prepared ointment had an excellent acute toxicity safety profile.

关键词： Carthamus tinctorius L. Safflower volatile oil GC-FID biological activity

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Variability in precipitation,temperature and river runoff in West Central Asia during the past-2000 years

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地球环境学报 2011年第1期 320-320页

作者： Oberhnsli H Novotná K Písková A Chabrillat S Nourgaliev D K Kurbaniyazov A K Grygar T Helmholtz-Centre Potsdam German Geoscience Centre(GFZ)TelegraphenbergD-14473 PotsdamGermany Institute of Inorganic Chemistry of the ASCR v.v.i.250 68 RezCzech Republic Faculty of Science Charles University in PragueCzech Republic Faculty of Geology Kazan State UniversityKazanTatarstanRussia Federation420008Russia Ahmed yasawi International Kazakh-Turkish university TurkestanKazakhstan

The tributary rivers Amu Darya and Syr Darya contribute major amounts of water to the hydrological budget of the endorheic Aral *** controlling the flow of water into rivers in the headwater systems in Tien Shan（Kyrgyzstan） and Pamir（Tajikistan） are therefore most *** water mineralization is strongly dependent on river discharge and has been inferred from spectrometrically determined gypsum *** of highresolution mineralization data with other proxies for tracing precipitation in NW China indicate that mineralization over the past;000 years in the Aral Sea reflects snow cover variability and glacier extent in Tien Shan and Pamir（at the NW and W edges of the Tibetan Plateau）.Snow cover in W Central Asia is preferentially a winter expression controlled by temperature patterns that impact the moisture-loading capacity over N Europe and NW *** observed that the runoff,resulting from warmer winter temperatures in W Central Asia and resulting in a reduction of snow cover,decreased between AD 100-300,AD 1150-1250,AD 1380-1450,AD 1580-1680 and during several low frequency events after AD 1800.

关键词： Asia Variability in precipitation,temperature and river runoff in West Central Asia during the past-2000 years AD

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