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Shaping the Metaverse into Reality: A Holistic Multidisciplinary Understanding of Opportunities, Challenges, and Avenues for Future Investigation

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Data Processor for Better Business Education 2023年第3期63卷 735-765页

作者： Alex Koohang Jeretta Horn Nord Keng-Boon Ooi Garry Wei-Han Tan Mostafa Al-Emran Eugene Cheng-Xi Aw Abdullah Mohammed Baabdullah Dimitrios Buhalis Tat-Huei Cham Charles Dennis Vincent Dutot Yogesh K. Dwivedi Laurie Hughes Emmanuel Mogaji Neeraj Pandey Ian Phau Ramakrishnan Raman Anshuman Sharma Marianna Sigala Akiko Ueno Lai-Wan Wong a School of Computing Middle Georgia State University Macon GA USA b Department of Management Science and Information Systems Oklahoma State University Stillwater OK USA c UCSI Graduate Business School UCSI University Kuala Lumpur Malaysiad School of Finance and Economics Nanchang Institute of Technology Nanchang People’s Republic of Chinau Faculty of Business Design and Arts Swinburne University of Technology Sarawak Campus Malaysia c UCSI Graduate Business School UCSI University Kuala Lumpur Malaysiad School of Finance and Economics Nanchang Institute of Technology Nanchang People’s Republic of Chinae School of Economics and Management Yunnan Normal University Kunming People’s Republic of Chinau Faculty of Business Design and Arts Swinburne University of Technology Sarawak Campus Malaysia f Faculty of Engineering & IT The British University in Dubai Dubai United Arab Emiratesg Department of Computer Techniques Engineering Dijlah University College Baghdad Iraq c UCSI Graduate Business School UCSI University Kuala Lumpur Malaysia h Department of Management Information Systems Faculty of Economics and Administration King Abdulaziz University Jeddah Saudi Arabia i Department of Tourism and Hospitality Bournemouth University Poole UK c UCSI Graduate Business School UCSI University Kuala Lumpur Malaysiaj Tashkent State University of Economics Tashkent Uzbekistan k Business School Middlesex University London UK l EM Normandie Business School Métis Lab Clichy France m Digital Futures for Sustainable Business & Society Research Group School of Management Swansea University Swansea UKn Department of Management Symbiosis Institute of Business Management Pune & Symbiosis International (Deemed University) Pune India m Digital Futures for Sustainable Business & Society Research Group School of Management Swansea University Swansea UK o School of Management & Marketing University of Greenwich London UK p National Institute of Industrial Engineering Mum

ABSTRACTABSTRACTThe term metaverse is described as the next iteration of the Internet. Metaverse is a virtual platform that uses extended reality technologies, i.e. augmented reality, virtual reality, mixed reality, 3D graphics, and other emerging technologies to allow real-time interactions and experiences in ways that are not possible in the physical world. Companies have begun to notice the impact of the metaverse and how it may help maximize profits. The purpose of this paper is to offer perspectives on several important areas, i.e. marketing, tourism, manufacturing, operations management, education, the retailing industry, banking services, healthcare, and human resource management that are likely to be impacted by the adoption and use of a metaverse. Each includes an overview, opportunities, challenges, and a potential research agenda.

关键词： Metaverse marketing tourism hospitality manufacturing operations management education the retailing industry banking services healthcare human resource management

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Online Public Opinion Deduction Based on an Innovative Cellular Automata 3rd

Online Public Opinion Deduction Based on an Innovative Cellu...

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3rd International Conference on Cyberspace Data and Intelligence, Cyber DI 2019, and the International Conference on Cyber-Living, Cyber-Syndrome, and Cyber-Health, CyberLife 2019

作者： Liu, Xin Cao, Shuai Cao, Yang He, Jie Zhang, Weishan Wang, Xueli Zheng, Liang College of Computer Science and Technology China University of Petroleum Qingdao266580 China Application on Improving Government Governance Capabilities National Engineering Laboratory Guiyang550022 China CETC Big Data Research Institute Co. Ltd. Guiyang550022 China Information Science Academy of China Electronics Technology Group Corporation Beijing China

ISBN: (纸本)9789811519215

As the Internet entered the 2.0 era, online users have become the main part of public opinion, and significant events happened around the world quickly disseminate through the Internet. Some negative comments usually are mixed into posts and articles. If let public opinion develop at will, some serious social events may trigger very fierce online volatility and they will have adverse effects on social stability. Therefore, to simulate the propagation mode of topic events on the Internet, and to predict the trending of public opinion on the entire Internet, this paper constructs a new type of model based on the idea of cellular automata and applies it to the online public opinion situation deduction. We arrange the nodes in new ways. An individual user is represented by a cell node in our model, and we build the cellular space based on directed graph to represent social network topology that users follow about each other in an innovative way. We delineate the users’ portrait based on the users’ attributes, design evolutionary rules based on the behaviors of users on the Internet and the law of information dissemination. Experiments with real data of online users showed that the proposed model in this paper had excellent performance, it not only reflected the law of information dissemination on the Internet, but also its deduction result was similar to the trending of real historical events. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Cellular automata

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Correction: Exergame (ExerG)-Based Physical-Cognitive Training for Rehabilitation in Adults With Motor and Balance Impairments: Usability Study

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JMIR serious games 2025年 13卷 e73405页

作者： Silvia Herren Barbara Seebacher Sarah Mildner Yanick Riederer Ulrike Pachmann Nija Sonja Böckler Stephan Niedecken Sabrina Alicia Sgandurra Leo Bonati Isabella Hotz Alexandra Schättin Roman Jurt Christian Brenneis Katharina Lenfert Frank Behrendt Stefan Schmidlin Lennart Nacke Corina Schuster-Amft Anna Lisa Martin-Niedecken Research Department Reha Rheinfelden Rheinfelden Switzerland. Department of Rehabilitation Science Clinic for Rehabilitation Muenster Gröben 700 Muenster 6232 Austria 43 533720004 ext 6205. Clinical Department of Neurology Medical University of Innsbruck Innsbruck Austria. Karl Landsteiner Institute for Interdisciplinary Rehabilitation Research Muenster Austria. Sphery Ltd Zurich Switzerland. VASCage - Centre on Clinical Stroke Research Innsbruck Austria. Department of Design Institute for Design Research Zurich University of the Arts Zurich Switzerland. English Language and Literature Faculty of Arts University of Waterloo Waterloo ON Canada. Stroke Center and Department of Neurology University Hospital Basel Basel Switzerland. Department of Clinical Research University of Basel Basel Switzerland. Department of Neurology Clinic for Rehabilitation Muenster Muenster Austria. School of Engineering and Computer Science Bern University of Applied Sciences Burgdorf Switzerland. HCI Games Group Stratford School of Interaction Design and Business University of Waterloo Waterloo ON Canada. Department for Sport Exercise and Health University of Basel Basel Switzerland.

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NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

arXiv

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arXiv 2022年

作者： Li, Yawei Zhang, Kai Timofte, Radu Van Gool, Luc Kong, Fangyuan Li, Mingxi Liu, Songwei Du, Zongcai Liu, Ding Zhou, Chenhui Chen, Jingyi Han, Qingrui Li, Zheyuan Liu, Yingqi Chen, Xiangyu Cai, Haoming Qiao, Yu Dong, Chao Sun, Long Pan, Jinshan Zhu, Yi Zong, Zhikai Liu, Xiaoxiao Hui, Zheng Yang, Tao Ren, Peiran Xie, Xuansong Hua, Xian-Sheng Wang, Yanbo Ji, Xiaozhong Lin, Chuming Luo, Donghao Tai, Ying Wang, Chengjie Zhang, Zhizhong Xie, Yuan Cheng, Shen Luo, Ziwei Yu, Lei Wen, Zhihong Wu, Qi Li, Youwei Fan, Haoqiang Sun, Jian Liu, Shuaicheng Huang, Yuanfei Jin, Meiguang Huang, Hua Liu, Jing Zhang, Xinjian Wang, Yan Long, Lingshun Li, Gen Zhang, Yuanfan Cao, Zuowei Sun, Lei Alexander, Panaetov Wang, Yucong Cai, Minjie Wang, Li Tian, Lu Wang, Zheyuan Ma, Hongbing Liu, Jie Chen, Chao Cai, Yidong Tang, Jie Wu, Gangshan Wang, Weiran Huang, Shirui Lu, Honglei Liu, Huan Wang, Keyan Chen, Jun Chen, Shi Miao, Yuchun Huang, Zimo Zhang, Lefei Ayazoglu, Mustafa Xiong, Wei Xiong, Chengyi Wang, Fei Li, Hao Wen, Ruimian Yang, Zhijing Zou, Wenbin Zheng, Weixin Ye, Tian Zhang, Yuncheng Kong, Xiangzhen Arora, Aditya Zamir, Syed Waqas Khan, Salman Hayat, Munawar Khan, Fahad Shahbaz Gao, Dandan Zhou, Dengwen Ning, Qian Tang, Jingzhu Huang, Han Wang, Yufei Peng, Zhangheng Li, Haobo Guan, Wenxue Gong, Shenghua Li, Xin Liu, Jun Wang, Wanjun Zeng, Kun Lin, Hanjiang Chen, Xinyu Fang, Jinsheng Zhang, Shuhao Zhang, Yuhao Sinha, Abhishek Kumar Moorthi, S. Manthira Dhar, Debajyoti Yang, Hao-Hsiang Huang, Zhi-Kai Chen, Wei-Ting Chang, Hua-En Kuo, Sy-Yen Tan, Wei Chen, Hao Xu, Qian Narang, Pratik Singh, Usneek Sameen, Syed Khaitan, Harsh Yinghua, Liu Tianlin, Zhang Xiaoming, Zhang Meng, Dingxuan Tian, Chunwei Morshed, Mashrur M. Ahsan, Ahmad Omar Computer Vision Lab ETH Zurich Switzerland University of Würzburg Germany ByteDance Shenzhen China State Key Laboratory for Novel Software Technology Nanjing University China ByteDance Inc China NetEase Inc. China Shenzhen Institutes of Advanced Technology CAS China University of Macau China Shanghai AI Lab Shanghai China Nanjing University of Science and Technology China Amazon Web Services United States China Alibaba DAMO Academy EFC Yuhang District Zhejiang Hangzhou China East China Normal University China Youtu Lab Tencent China Megvii Technology China University of Electronic Science and Technology of China China School of Artificial Intelligence Beijing Normal University China Alibaba Group China Bilibili AI China Nankai-Baidu Joint Lab Nankai University Tianjin China Platform Technologies Tencent Online Video China Higher School of Economics Russia Huawei Moscow Research Center Russia Hunan University China Xidian University China Xilinx Technology Beijing Limited China College of Information Science and Engineering Xinjiang University Urumqi China Department of Electronic Engineering Tsinghua University Beijing China Nanjing University China McMaster University Canada School of Telecommunication Engineering Xidian University Xi’an China School of Computer Science Wuhan University Wuhan China School of Mathematical Science University of Electronic Science and Technology of China Chengdu China School of Computer Science The University of Sydney Sydney Australia Aselsan Research Ankara Turkey School of Electronic and Information Engineering South-Central University for Nationalities Wuhan China Guangdong University of Technology China Fujian Normal University Fuzhou University Jimei University China Design Group China Abu Dhabi United Arab Emirates Monash University Melbourne Australia Mohamed bin Zayed University of AI United Arab Emirates North China Electric Power University Changping District Beijing China The School of Art

This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-resolve an input image with a magnification factor of ×4 based on pairs of low and corresponding high resolution images. The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29.00dB on DIV2K validation set. IMDN is set as the baseline for efficiency measurement. The challenge had 3 tracks including the main track (runtime), sub-track one (model complexity), and sub-track two (overall performance). In the main track, the practical runtime performance of the submissions was evaluated. The rank of the teams were determined directly by the absolute value of the average runtime on the validation set and test set. In sub-track one, the number of parameters and FLOPs were considered. And the individual rankings of the two metrics were summed up to determine a final ranking in this track. In sub-track two, all of the five metrics mentioned in the description of the challenge including runtime, parameter count, FLOPs, activations, and memory consumption were considered. Similar to sub-track one, the rankings of five metrics were summed up to determine a final ranking. The challenge had 303 registered participants, and 43 teams made valid submissions. They gauge the state-of-the-art in efficient single image super-resolution. © 2022, CC BY.

关键词： Chemical activation

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Identification of novel phytotherapeutic agents for understanding hypertrophic cardiomyopathy via genetic mapping and advanced computational analysis

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Genome Instability & Disease 2024年第6期5卷 262-286页

作者： Aborode, Abdullahi Tunde Ayobami, Onifade Isreal Danazumi, Ammar Usman Olowosoke, Christopher Busayo Umar, Haruna Isiyaku Osinuga, Abraham Awaji, Aeshah A. Awaji, Fatmah Ali Omojowolo, Ebenezer Ayomide Kuthi, Najwa Ahmad Shaikh, Tanveer Anidu, Babatunde Shuaib Alexiou, Athanasios Adesola, Ridwan Olamilekan Olapade, Zainab Matthew, Awah Favour Ameh, Blessing Oni, Toluwalope Yinka Bakre, Adetolase Azizat Scott, Godfred Yawson Department of Chemistry Mississippi State University Starkville USA Department of Biology University at Albany Albany USA Faculty of Chemistry Warsaw University of Technology Warsaw Poland Groningen Research Institute of Pharmacy University of Groningen Groningen The Netherlands Department of Biotechnology Federal University of Technology Akure Nigeria Computer-Aided Therapeutic Discovery and Design Group FUTA Akure Nigeria Department of Chemical and Biomolecular Engineering University of Nebraska-Lincoln Lincoln USA Department of Biology Faculty of Science University College of Taymaa University of Tabuk Tabuk Saudi Arabia King Fahad Specialist Hospital Laboratory and Blood Bank Health Cluster Tabuk Saudi Arabia Department of Chemistry University of Albany State University of New York Albany USA Department of Chemistry Faculty of Science Universiti Teknologi Malaysia (UTM) Johor Bahru Malaysia Department of Integrative Biology and Physiology University of Minnesota Medical School Minneapolis USA Department of Science and Engineering Novel Global Community Educational Foundation Hebersham Australia AFNP Med Wien Austria Department of Veterinary Medicine Faculty of Veterinary Medicine University of Ibadan Ibadan Nigeria Department of Biology Lamar University Texas USA Department of Biochemistry Center for Discovery and Innovation City University of New York New York USA University of West Georgia Carrolton USA Department of Biochemistry Federal University of Technology Akure Nigeria Department of Medical Diagnostics Faculty of Allied Health Sciences Kwame Nkrumah University of Science and Technology Kumasi Ghana

Hypertrophic cardiomyopathy (HCM) is a monogenic cardiovascular disorder that has been poorly studied at the molecular, genetic, and computational levels. Here, we examined the genetic map of HCM polymorphic targets using a computational approach to identify new phytochemicals with potential therapeutic properties. We demonstrate the range of mutations associated with cardiomyopathies, and identify new associations between genes and phenotypes in this disease category. Specifically, our findings suggest that several genes associated with channelopathies might serve as genetic modifiers, altering the clinical features and severity of cardiomyopathic phenotypes, thus likely impacting disease manifestation.

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Energy Efficient User Clustering, Hybrid Precoding and Power Optimization in Terahertz MIMO-NOMA Systems

arXiv

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arXiv 2020年

作者： Zhang, Haijun Zhang, Haisen Liu, Wei Long, Keping Dong, Jiangbo Leung, Victor C.M. Institute of Artificial Intelligence Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services University of Science and Technology Beijing Beijing100083 China China Mobile Group Design Institute Co. Ltd Beijing100080 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering University of British Columbia VancouverBC V6T 1Z4 Canada

Terahertz (THz) band communication has been widely studied to meet the future demand for ultra-high capacity. In addition, multi-input multi-output (MIMO) technique and non-orthogonal multiple access (NOMA) technique with multi-antenna also enable the network to carry more users and provide multiplexing gain. In this paper, we study the maximization of energy efficiency (EE) problem in THz-NOMA-MIMO systems for the first time. And the original optimization problem is divided into user clustering, hybrid precoding and power optimization. Based on channel correlation characteristics, a fast convergence scheme for user clustering in THz-NOMA-MIMO system using enhanced K-means machine learning algorithm is proposed. Considering the power consumption and implementation complexity, the hybrid precoding scheme based on the sub-connection structure is adopted. Considering the fronthaul link capacity constraint, we design a distributed alternating direction method of multipliers (ADMM) algorithm for power allocation to maximize the EE of THz-NOMA cache-enabled system with imperfect successive interference cancellation (SIC). The simulation results show that the proposed user clustering scheme can achieve faster convergence and higher EE, the design of the hybrid precoding of the sub-connection structure can achieve lower power consumption and power optimization can achieve a higher EE for the THz cache-enabled network. Copyright © 2020, The Authors. All rights reserved.

关键词： MIMO systems

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Adsorption kinetics, isotherms and desorption studies of mercury from aqueous solution at different temperatures on magnetic sodium alginate-thiourea microbeads

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Environmental Nanotechnology, Monitoring and Management 2019年 12卷

作者： Patiño-Ruiz, D. Bonfante, H. De Ávila, G. Herrera, Adriana Doctorate in Engineering Program Nanomaterials and Computer Aided Process Engineering Research Group Universidad de Cartagena Cartagena Colombia Chemical Engineering Program Process Design and Biomass Use Group Universidad de Cartagena Cartagena Colombia Chemical Engineering Program Nanomaterials and Computer Aided Process Engineering Research Group Universidad de Cartagena Cartagena Colombia

Magnetite (Fe3O4) nanoparticles and thiourea were employed to modify sodium alginate microbeads for adsorption of Hg ions from aqueous solution. The Fe3O4 nanoparticles were initially synthesized by co-precipitation m... 详细信息

Magnetite (Fe₃O₄) nanoparticles and thiourea were employed to modify sodium alginate microbeads for adsorption of Hg ions from aqueous solution. The Fe₃O₄ nanoparticles were initially synthesized by co-precipitation method. Fourier infrared spectroscopy (FTIR) determined the presence of hydroxyl, carboxyl, thiol and amine functional groups in the microbead molecular structure. According to BET and BJH methods, the MAT microbeads had surface area, pore diameter and volume of 7.3472 m²/g, 12.9058 nm and 0.0255 cm³/g, respectively. Scanning electron microscopy (SEM) equipped with an EDX system allowed to obtain morphological information of the MAT microbeads, in which was observed the main elements introduced by the presence of thiol groups and iron ions. The result of saturation magnetization (M_s) performed by a vibrating sample magnetometer (VSM), is common for superparamagnetic materials, which slightly decreased due to the low amount of magnetic nanoparticles in the microbead structure. Adsorption kinetics showed that highest rate was about 98% in the first 20 min, and then decreased to zero. Pseudo-first order was the model that better fitted to experimental data with a value about 2.6 mg/g. Meanwhile, adsorption isotherm was better described using Langmuir model, suggesting that the Hg ions adsorption was mainly given by electrostatic interaction and chemical bonding among the functional groups, as well as the formation of a saturated layer onto the microbead surface occupying all the available sites. © 2019

关键词： Adsorption Magnetic nanoparticles Mercury Sodium alginate microbeads Thiourea

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Corrigendum/Erratum to "Protein music of enhanced musicality by music style guided exploration of diverse amino acid properties" [Heliyon 7, Issue 9, SEPTEMBER 2021, Article e07933]

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Heliyon 2024年第13期10卷 e33412页

作者： Nicole WanNi Tay Fanxi Liu Wang Chaoxin Zhang Hui Zhang Peng Yu Zong Chen Raffles Institution 1 Raffles Institution Ln 575954 Singapore. Department of Computer Science Kansas State University Manhattan KS 66506 USA. School of Arts Minnan Normal University Zhangzhou 363000 China. Bioinformatics and Drug Design Group Department of Pharmacy and Center for Computational Science and Engineering National University of Singapore 117543 Singapore. Qian Xuesen Collaborative Research Center of Astrochemistry and Space Life Sciences Institute of Drug Discovery Technology Ningbo University Ningbo 315211 China.

[This corrects the article DOI: 10.1016/***.2021.e07933.].

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Energy-economy analysis of a novel spiral channeled conical turbulator inserted within the parabolic trough solar collector absorber tube

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Case Studies in Thermal engineering 2025年 73卷

作者： Sarminah Samad Salman Saeidlou Ibrahim Mahariq Naoufel Kraiem Ali Alamry Priya A. Hoskeri S.P. Ghoushchi Department of Management College of Business Administration Princess Nourah bint Abdulrahman University Riyadh 11671 Saudi Arabia School of Engineering Technology and Design Canterbury Christ Church University Canterbury Kent UK Department of Mathematics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai 602105 Tamil Nadu India Najjad Zeenni Faculty of Engineering Al Quds University Jerusalem Palestine University College Korea University Seoul 02481 South Korea Department of Medical Research China Medical University Hospital China Medical University Taichung Taiwan Applied Science Research Center Applied Science Private University Amman Jordan College of Computer Science King Khalid University Abha 61413 Saudi Arabia Department of Mechanical Engineering College of Engineering in Al-Kharj Prince Sattam Bin Abdulaziz University 11942 Al-Kharj Saudi Arabia VTU Research Center Department of Physics Dayanand Sagar College of Engineering Kumarswamy Layout Bangalore 560 078 India Sustainable Management of Natural Resources and Environment Research Group Faculty of Environment and Labour Safety Ton Duc Thang University Ho Chi Minh City Viet Nam

This study introduces a novel spiral channeled conical turbulator (SCCT) to enhance the hydrothermal and economic performance of a parabolic trough solar collector. Key design parameters, including spiral channel width (1–3 mm) and pitch (1–9 mm), are investigated, and the results are compared to those of a plain conical turbulator (PCT) and plain absorber tube. The inclined surfaces of the PCT and SCCT induce a strong radial flow, significantly improving heat transfer. Heat transfer and friction coefficients exhibit a direct correlation with spiral channel pitch but an inverse relationship with channel width. The PCT achieves the highest heat transfer enhancement, up to 550 % over a plain tube. However, the SCCT's aerodynamic geometry, enabled by its spiral channels, reduces pressure drop, yielding a higher and optimal performance evaluation criterion (PEC) compared to the PCT. The SCCT achieves a maximum PEC of 3.05 at a channel pitch of 5 mm and a width of 3 mm. This results in a 375 % improvement in heat transfer and a 280 % increase in the friction coefficient compared to plain absorber tubes. Economically, the PCT outperforms, with a levelized cost of energy (LCOE) of 0.405$/kWh and a payback time of 2.7 years. These results indicate that PCT is the optimal choice for heat transfer and economic performance, while SCCT is superior from a hydrothermal perspective.

关键词： Solar collector Renewable energy Spiral channeled conical turbulator Economic analysis Heat transfer Friction coefficient

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Accurate machine-learning based modeling of apparent viscosity of waxy oils mixed with polymeric wax inhibitors

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Flow Measurement and Instrumentation 2025年

作者： Hongyan Lei Muntadher Abed Hussein Tarak Vora Anupam Yadav Asha Rajiv Aman Shankhyan Sachin Jaidka Mehul Manu Issa Mohammed Kadhim Zainab Jamal Hamoodah Fadhil Faez Mehrdad Mottaghi College of Computer and Electrical Engineering Hunan University of Arts and Science Changde hunan 415000 China Department of sciecnes Al-Manara College for Medical Sciences (Maysan) Iraq Marwadi University Research Center Department of Civil Engineering Faculty of Engineering & Technology Marwadi University Rajkot-360003 Gujarat India Department of Computer engineering and Application GLA University Mathura-281406 India Department of Physics & Electronics School of Sciences JAIN (Deemed to be University) Bangalore Karnataka India Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Rajpura 140401 Punjab India Department of Physics Department of Applied Sciences Chandigarh Engineering College Chandigarh Group of Colleges-Jhanjeri Mohali 140307 Punjab India Department of Allied Science (Physics) Graphic Era Hill University Bhimtal India Graphic Era Deemed to be University Dehradun Uttarakhand-248002 India Department of Medical Laboratories Technology Al-Nisour University College Nisour Seq. Karkh Baghdad Iraq Mazaya University college An Nasiriyah Dhi Qar Iraq Department of Dentistry College of Dentistry The Islamic University Najaf Iraq Department of medical analysis Medical laboratory technique college the Islamic University of Al Diwaniyah Al Diwaniyah Iraq Department of medical analysis Medical laboratory technique college the Islamic University of Babylon Babylon Iraq Faculty of chemistry Kabul University Kabul Afghanistan

While producing and then transporting waxy oils through pipeline network systems, wax precipitation commonly leads to issues such as wax build-up, gel creation, and decreased flow, negatively affecting pipeline efficiency. To address these problems, the petroleum industry frequently uses polymeric flow improvers to enhance the rheological properties, thereby increasing the mobility and flowability of oils. Experimental methods to measure oil viscosity are both expensive and time-consuming; hence, having reliable data driven frameworks are necessary in this regard. This work presents the use of accurate artificial intelligence methods including K-nearest neighbors, convolutional neural network, multi-layer perceptron artificial neural network, decision tree, support vector machine, adaptive boosting, random forest and ensemble learning to create smart methods for calculating the apparent viscosity of waxy crude oils that are doped with polymeric additives by actual databank sourced from prior studies. A databank containing 526 datapoints was used to both prepare and validate these machine learning algorithms. The predicted results were then evaluated against actual lab data using both graphical and statistical methods. The outcomes showed a strong agreement between the determined and real values for the constructed models. These developed models offer a way of accurate estimation capability bypassing the need for costly, labor-intensive, and time-consuming experimental procedures.

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