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| 1 | Biological relevance of a stable biochemical interaction between the tombusvirus-encoded P19 and short interfering RNAs显示文摘 | Omarov R Sparks K Smith L et ol | 2006 | J Virol2006，80，： | 1 |
| 2 | Thermal and Electrical Properties of Gadolinium Sulfides at High Temperatures显示文摘 | G. G. Gadzhiev Sh. M. Ismailov Kh. Kh. Abdullaev M. M. Khamidov Z. M. Omarov | 2001 | High Temperature2001，，3： | 1 |
| 3 | Biological relevance of a stable biochemical interaction between the tombusvirus-encoded P19 and short interfering RNAs 显示文摘 | Omarov R Sparks K Smith L | 2006 | Virol2006，80，： | 1 |
| 4 | Biological relevance of a stable biochemical interaction between the tombusvirus-encoded P19 and short interfering RNAs显示文摘 | Omarov R Sparks K Smith L | 2006 | Virology2006，80，： | 1 |
| 5 | Biological chemistry of virus- encoded suppressors of RNA silencing: an overview 显示文摘 | Omarov R T Scholthof H B | 2012 | Methods Mol Biol2012，894，： | 1 |
| 6 | The efficiency of drip irrigation in Dagestan显示文摘 | Alibekov T S Omarov L O Mustafaev G M | 1998 | Kukuruzai Sorgo1998，6，： | 1 |
| 7 | The function of the maxillofacial muscles in dentition defects and periodontal diseases显示文摘 | Omarov OG Persin LS Erokhina IG | 1995 | Stomatologiia (Mosk)1995，74，4： | 1 |
| 8 | Biochemical mechanisms ofsuppression of RNA interference by plant viruses显示文摘 | Omarov R T Bersimbai R I | 2010 | Biochemistry(Mosc)2010，75，8： | 1 |
| 9 | The Mo-hydroxylases xanthine dehydrogenaseand aldehyde oxidase in ryegrass as affected by nitrogen and salinity显示文摘 | Sagi M Omarov R T Lios S H | 1998 | Plant Science1998，135，： | 1 |
| 10 | Distribution of the Mo-enzymes aldehyde oxidase, xanthine dehydrogenase and nitrate reductase in maize ( Zea mays L.) nodal roots as affected by nitrogen and salinity显示文摘 | N. Katalin Barabás Rustem T. Omarov László Erdei S. Herman Lips | 2000 | Plant Science2000，，1： | 1 |
| 11 | A role of D-dimer and fibrinopeptide A in diagnosis of a hemostasis system disorders显示文摘 | Omarov TI Sultanov GA Ragimov VS | | 0，，01： | 1 |
| 12 | Deep Learning-Enabled Brain Stroke Classification on Computed Tomography Images显示文摘In the field of stroke imaging, deep learning (DL) has enormousuntapped potential.When clinically significant symptoms of a cerebral strokeare detected, it is crucial to make an urgent diagnosis using available imagingtechniques such as computed tomography (CT) scans. The purpose of thiswork is to classify brain CT images as normal, surviving ischemia or cerebralhemorrhage based on the convolutional neural network (CNN) model. In thisstudy, we propose a computer-aided diagnostic system (CAD) for categorizingcerebral strokes using computed tomography images. Horizontal flip datamagnification techniques were used to obtain more accurate categorization.Image Data Generator to magnify the image in real time and apply anyrandom transformations to each training image. An early stopping method toavoid overtraining. As a result, the proposed methods improved several estimationparameters such as accuracy and recall, compared to other machinelearning methods. A python web application was created to demonstrate theresults of CNN model classification using cloud development techniques. Inour case, the model correctly identified the drawing class as normal with 79%accuracy. Based on the collected results, it was determined that the presentedautomated diagnostic system could be used to assist medical professionals indetecting and classifying brain strokes. | Azhar Tursynova Batyrkhan Omarov Natalya Tukenova Indira Salgozha Onergul Khaaval Rinat Ramazanov Bagdat Ospanov | 2023 | Computers, Materials & Continua2023，，4： | 1 |
| 13 | Biological relevance of a stable biochemical interaction between the tombusvirus-encoded P19 and short interfering RNAs显示文摘 | SPARKS K SMITH L | 2006 | J Virol2006，80，6： | 1 |
| 14 | Biological chemistry of vi- res-encoded suppressors of RNA silencing: an overview 显示文摘 | Omarov R T Scholthof H B | 2012 | Methods Mol Biol2012，894，： | 1 |
| 15 | Al- dehyde oxidase isoforms and subunit composition in roots of barley as affected by ammonium and nitrate 显示文摘 | OMAROV R T DRAGER D TISCHNER R | 2003 | Phys- iol Plantarum2003，117，： | 1 |
| 16 | Methods of struggle withcalcium carbonate overgrowth of geothermal heatequipment显示文摘 | Chalaev D R Omarov M A | 1999 | Transactions-Geothermal ResourcesCouncil1999，23，： | 1 |
| 17 | Artificial Intelligence-Enabled Chatbots in Mental Health:A Systematic Review显示文摘Clinical applications of Artificial Intelligence(AI)for mental health care have experienced a meteoric rise in the past few years.AIenabled chatbot software and applications have been administering significant medical treatments that were previously only available from experienced and competent healthcare professionals.Such initiatives,which range from“virtual psychiatrists”to“social robots”in mental health,strive to improve nursing performance and cost management,as well as meeting the mental health needs of vulnerable and underserved populations.Nevertheless,there is still a substantial gap between recent progress in AI mental health and the widespread use of these solutions by healthcare practitioners in clinical settings.Furthermore,treatments are frequently developed without clear ethical concerns.While AI-enabled solutions show promise in the realm of mental health,further research is needed to address the ethical and social aspects of these technologies,as well as to establish efficient research and medical practices in this innovative sector.Moreover,the current relevant literature still lacks a formal and objective review that specifically focuses on research questions from both developers and psychiatrists in AI-enabled chatbotpsychologists development.Taking into account all the problems outlined in this study,we conducted a systematic review of AI-enabled chatbots in mental healthcare that could cover some issues concerning psychotherapy and artificial intelligence.In this systematic review,we put five research questions related to technologies in chatbot development,psychological disorders that can be treated by using chatbots,types of therapies that are enabled in chatbots,machine learning models and techniques in chatbot psychologists,as well as ethical challenges. | Batyrkhan Omarov Sergazi Narynov Zhandos Zhumanov | 2023 | Computers, Materials & Continua2023，，3： | 0 |
| 18 | A Review of Machine Learning Techniques in Cyberbullying Detection显示文摘Automatic identification of cyberbullying is a problem that is gaining traction,especially in the Machine Learning areas.Not 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 teenagers.This 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 Internet.We undertake an in-depth review of 13 papers from four scientific databases.The 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 processing.In 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 not.This 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. | Daniyar Sultan Batyrkhan Omarov Zhazira Kozhamkulova Gulnur Kazbekova Laura Alimzhanova Aigul Dautbayeva Yernar Zholdassov Rustam Abdrakhmanov | 2023 | Computers, Materials & Continua2023，，3： | 0 |
| 19 | One Dimensional Conv-BiLSTM Network with Attention Mechanism for IoT Intrusion Detection显示文摘In the face of escalating intricacy and heterogeneity within Internet of Things(IoT)network landscapes,the imperative for adept intrusion detection techniques has never been more pressing.This paper delineates a pioneering deep learning-based intrusion detection model:the One Dimensional Convolutional Neural Networks(1D-CNN)and Bidirectional Long Short-Term Memory(BiLSTM)Network(Conv-BiLSTM)augmented with an Attention Mechanism.The primary objective of this research is to engineer a sophisticated model proficient in discerning the nuanced patterns and temporal dependencies quintessential to IoT network traffic data,thereby facilitating the precise categorization of a myriad of intrusion types.Methodology:The proposed model amal-gamates the potent attributes of 1D convolutional neural networks,bidirectional long short-term memory layers,and attention mechanisms to bolster the efficacy and resilience of IoT intrusion detection systems.A rigorous assessment was executed employing an expansive dataset that mirrors the convolutions and multifariousness characteristic of genuine IoT network settings,encompassing various network traffic paradigms and intrusion archetypes.Findings:The empirical evidence underscores the paramountcy of the One Dimensional Conv-BiLSTM Network with Attention Mechanism,which exhibits a marked superiority over conventional machine learning modalities.Notably,the model registers an exemplary AUC-ROC metric of 0.995,underscoring its precision in typifying a spectrum of intrusions within IoT infrastructures.Conclusion:The presented One Dimensional Conv-BiLSTM Network armed with an Attention Mechanism stands out as a robust and trustworthy vanguard against IoT network breaches.Its prowess in discerning intricate traffic patterns and inherent temporal dependencies transcends that of traditional machine learning frameworks.The commendable diagnostic accuracy manifested in this study advocates for its tangible deployment.This investigation indubitably advances the cybersecurity domain,amplifying the fortification and robustness of IoT frameworks and heralding a new era of bolstered security across pivotal sectors such as residential,medical,and transit systems. | Bauyrzhan Omarov Zhuldyz Sailaukyzy Alfiya Bigaliyeva Adilzhan Kereyev Lyazat Naizabayeva Aigul Dautbayeva | 2023 | Computers, Materials & Continua2023，77，12： | 0 |
| 20 | Thermophysical properties of BiFeO_(3)/REE multiferroics in a wide temperature range显示文摘The paper presents the results of a comprehensive study of the thermophysical properties(thermal conductivity,thermal diffusivity,heat capacity)of high-temperature multiferroic BiFeO_(3) modified with rare-earth elements(REEs)(La,Pr,Nd,Sm,Eu,Gd,Tb,Dy,Ho,Er,Tm,Lu).The regularities of the formation of the mentioned characteristics were established.The assumptions about the nature of the observed phenomena were suggested. | Sidek Khasbulatov Suleiman Kallaev Haji Gadjiev Zairbek Omarov Abumuslim Bakmaev Iliya Verbenko Aleksey Pavelko Larisa Reznichenko | 2020 | Journal of Advanced Dielectrics2020，10，1： | 0 |
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