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Kadhuim, Z. A., & Al-Janabi, S. (2023). Codon-mRNA prediction using deep optimal neurocomputing technique (DLSTM-DSN-WOA) and multivariate analysis. Results in Engineering, 17, 100847.KadhuimZ. A.Al-JanabiS. (2023). Codon-mRNA prediction using deep optimal neurocomputing technique (DLSTM-DSN-WOA) and multivariate analysis. Results in Engineering, 17, 100847.Search in Google Scholar
Yang, J., Li, Y., Liu, Q., Li, L., Feng, A., Wang, T., … & Lyu, J. (2020). Brief introduction of medical database and data mining technology in big data era. Journal of Evidence‐Based Medicine, 13(1), 57-69.YangJ.LiY.LiuQ.LiL.FengA.WangT.LyuJ. (2020). Brief introduction of medical database and data mining technology in big data era. Journal of Evidence‐Based Medicine, 13(1), 57-69.Search in Google Scholar
Rubinfeld, D. L., & Gal, M. S. (2017). Access barriers to big data. Ariz. L. Rev., 59, 339.RubinfeldD. L.GalM. S. (2017). Access barriers to big data. Ariz. L. Rev., 59, 339.Search in Google Scholar
Sharma, I., Tiwari, R., & Anand, A. (2017). Open source big data analytics technique. In Proceedings of the International Conference on Data Engineering and Communication Technology: ICDECT 2016, Volume 1 (pp. 593-602). Springer Singapore.SharmaI.TiwariR.AnandA. (2017). Open source big data analytics technique. In Proceedings of the International Conference on Data Engineering and Communication Technology: ICDECT 2016, Volume 1 (pp. 593-602). Springer Singapore.Search in Google Scholar
Mishra, D., Gunasekaran, A., Papadopoulos, T., & Childe, S. J. (2018). Big Data and supply chain management: a review and bibliometric analysis. Annals of Operations Research, 270, 313-336.MishraD.GunasekaranA.PapadopoulosT.ChildeS. J. (2018). Big Data and supply chain management: a review and bibliometric analysis. Annals of Operations Research, 270, 313-336.Search in Google Scholar
Wang, L., Yang, M., Pathan, Z. H., Salam, S., Shahzad, K., & Zeng, J. (2018). Analysis of influencing factors of big data adoption in Chinese enterprises using DANP technique. Sustainability, 10(11), 3956.WangL.YangM.PathanZ. H.SalamS.ShahzadK.ZengJ. (2018). Analysis of influencing factors of big data adoption in Chinese enterprises using DANP technique. Sustainability, 10(11), 3956.Search in Google Scholar
Dai, H. N., Wang, H., Xu, G., Wan, J., & Imran, M. (2020). Big data analytics for manufacturing internet of things: opportunities, challenges and enabling technologies. Enterprise Information Systems, 14(9-10), 1279-1303.DaiH. N.WangH.XuG.WanJ.ImranM. (2020). Big data analytics for manufacturing internet of things: opportunities, challenges and enabling technologies. Enterprise Information Systems, 14(9-10), 1279-1303.Search in Google Scholar
Chang, V. (2018). A proposed social network analysis platform for big data analytics. Technological Forecasting and Social Change, 130, 57-68.ChangV. (2018). A proposed social network analysis platform for big data analytics. Technological Forecasting and Social Change, 130, 57-68.Search in Google Scholar
Liao, H., Tang, M., Luo, L., Li, C., Chiclana, F., & Zeng, X. J. (2018). A bibliometric analysis and visualization of medical big data research. Sustainability, 10(1), 166.LiaoH.TangM.LuoL.LiC.ChiclanaF.ZengX. J. (2018). A bibliometric analysis and visualization of medical big data research. Sustainability, 10(1), 166.Search in Google Scholar
Thangavelooa, R., Jinga, W. W., Lenga, C. K., & Abdullaha, J. (2020). Datdroid: Dynamic analysis technique in android malware detection. International Journal on Advanced Science, Engineering and Information Technology, 10(2), 536-541.ThangavelooaR.JingaW. W.LengaC. K.AbdullahaJ. (2020). Datdroid: Dynamic analysis technique in android malware detection. International Journal on Advanced Science, Engineering and Information Technology, 10(2), 536-541.Search in Google Scholar
Müller, O., Fay, M., & Vom Brocke, J. (2018). The effect of big data and analytics on firm performance: An econometric analysis considering industry characteristics. Journal of management information systems, 35(2), 488-509.MüllerO.FayM.Vom BrockeJ. (2018). The effect of big data and analytics on firm performance: An econometric analysis considering industry characteristics. Journal of management information systems, 35(2), 488-509.Search in Google Scholar
Saggi, M. K., & Jain, S. (2018). A survey towards an integration of big data analytics to big insights for value-creation. Information Processing & Management, 54(5), 758-790.SaggiM. K.JainS. (2018). A survey towards an integration of big data analytics to big insights for value-creation. Information Processing & Management, 54(5), 758-790.Search in Google Scholar
Hulsen, T., Jamuar, S. S., Moody, A. R., Karnes, J. H., Varga, O., Hedensted, S., … & McKinney, E. F. (2019). From big data to precision medicine. Frontiers in medicine, 6, 34.HulsenT.JamuarS. S.MoodyA. R.KarnesJ. H.VargaO.HedenstedS.McKinneyE. F. (2019). From big data to precision medicine. Frontiers in medicine, 6, 34.Search in Google Scholar
Konar, A. (2018). Artificial intelligence and soft computing: behavioral and cognitive modeling of the human brain. CRC press.KonarA. (2018). Artificial intelligence and soft computing: behavioral and cognitive modeling of the human brain. CRC press.Search in Google Scholar
Wang, X., Han, Y., Leung, V. C., Niyato, D., Yan, X., & Chen, X. (2020). Convergence of edge computing and deep learning: A comprehensive survey. IEEE Communications Surveys & Tutorials, 22(2), 869-904.WangX.HanY.LeungV. C.NiyatoD.YanX.ChenX. (2020). Convergence of edge computing and deep learning: A comprehensive survey. IEEE Communications Surveys & Tutorials, 22(2), 869-904.Search in Google Scholar
Arthurs, P., Gillam, L., Krause, P., Wang, N., Halder, K., & Mouzakitis, A. (2021). A taxonomy and survey of edge cloud computing for intelligent transportation systems and connected vehicles. IEEE Transactions on Intelligent Transportation Systems, 23(7), 6206-6221.ArthursP.GillamL.KrauseP.WangN.HalderK.MouzakitisA. (2021). A taxonomy and survey of edge cloud computing for intelligent transportation systems and connected vehicles. IEEE Transactions on Intelligent Transportation Systems, 23(7), 6206-6221.Search in Google Scholar
Liu, Y., Yang, C., Jiang, L., Xie, S., & Zhang, Y. (2019). Intelligent edge computing for IoT-based energy management in smart cities. IEEE network, 33(2), 111-117.LiuY.YangC.JiangL.XieS.ZhangY. (2019). Intelligent edge computing for IoT-based energy management in smart cities. IEEE network, 33(2), 111-117.Search in Google Scholar
Tang, B., Chen, Z., Hefferman, G., Pei, S., Wei, T., He, H., & Yang, Q. (2017). Incorporating intelligence in fog computing for big data analysis in smart cities. IEEE Transactions on Industrial informatics, 13(5), 2140-2150.TangB.ChenZ.HeffermanG.PeiS.WeiT.HeH.YangQ. (2017). Incorporating intelligence in fog computing for big data analysis in smart cities. IEEE Transactions on Industrial informatics, 13(5), 2140-2150.Search in Google Scholar
Bargiela, A., & Pedrycz, W. (2022). Granular computing. In Handbook on Computer Learning and Intelligence: Volume 2: Deep Learning, Intelligent Control and Evolutionary Computation (pp. 97-132).BargielaA.PedryczW. (2022). Granular computing. In Handbook on Computer Learning and Intelligence: Volume 2: Deep Learning, Intelligent Control and Evolutionary Computation (pp. 97-132).Search in Google Scholar
Gill, S. S., Xu, M., Ottaviani, C., Patros, P., Bahsoon, R., Shaghaghi, A., … & Uhlig, S. (2022). AI for next generation computing: Emerging trends and future directions. Internet of Things, 19, 100514.GillS. S.XuM.OttavianiC.PatrosP.BahsoonR.ShaghaghiA.UhligS. (2022). AI for next generation computing: Emerging trends and future directions. Internet of Things, 19, 100514.Search in Google Scholar
Roy, K., Jaiswal, A., & Panda, P. (2019). Towards spike-based machine intelligence with neuromorphic computing. Nature, 575(7784), 607-617.RoyK.JaiswalA.PandaP. (2019). Towards spike-based machine intelligence with neuromorphic computing. Nature, 575(7784), 607-617.Search in Google Scholar
Zhou, Z., Chen, X., Li, E., Zeng, L., Luo, K., & Zhang, J. (2019). Edge intelligence: Paving the last mile of artificial intelligence with edge computing. Proceedings of the IEEE, 107(8), 1738-1762.ZhouZ.ChenX.LiE.ZengL.LuoK.ZhangJ. (2019). Edge intelligence: Paving the last mile of artificial intelligence with edge computing. Proceedings of the IEEE, 107(8), 1738-1762.Search in Google Scholar
Nayak, A., & Dutta, K. (2017, June). Impacts of machine learning and artificial intelligence on mankind. In 2017 international conference on intelligent computing and control (I2C2) (pp. 1-3). IEEE.NayakA.DuttaK. (2017, June). Impacts of machine learning and artificial intelligence on mankind. In 2017 international conference on intelligent computing and control (I2C2) (pp. 1-3). IEEE.Search in Google Scholar
Deng, S., Zhao, H., Fang, W., Yin, J., Dustdar, S., & Zomaya, A. Y. (2020). Edge intelligence: The confluence of edge computing and artificial intelligence. IEEE Internet of Things Journal, 7(8), 7457-7469.DengS.ZhaoH.FangW.YinJ.DustdarS.ZomayaA. Y. (2020). Edge intelligence: The confluence of edge computing and artificial intelligence. IEEE Internet of Things Journal, 7(8), 7457-7469.Search in Google Scholar
Wang, D., Chen, D., Song, B., Guizani, N., Yu, X., & Du, X. (2018). From IoT to 5G I-IoT: The next generation IoT-based intelligent algorithms and 5G technologies. IEEE Communications Magazine, 56(10), 114-120.WangD.ChenD.SongB.GuizaniN.YuX.DuX. (2018). From IoT to 5G I-IoT: The next generation IoT-based intelligent algorithms and 5G technologies. IEEE Communications Magazine, 56(10), 114-120.Search in Google Scholar
C. P. Saranya & N. Nagarajan. (2024). Retraction Note: Efficient agricultural yield prediction using metaheuristic optimized artificial neural network using Hadoop framework. Soft Computing(prepublish), 1-1.C. P.SaranyaN.Nagarajan (2024). Retraction Note: Efficient agricultural yield prediction using metaheuristic optimized artificial neural network using Hadoop framework. Soft Computing(prepublish), 1-1.Search in Google Scholar
Bao Yi,Huang Zhou,Gong Xuri,Zhang Yuyang,Yin Ganmin & Wang Han. (2023). Optimizing segmented trajectory data storage with HBase for improved spatio-temporal query efficiency. International Journal of Digital Earth(1),1124-1143.BaoYiHuangZhouGongXuriZhangYuyangYinGanminWangHan (2023). Optimizing segmented trajectory data storage with HBase for improved spatio-temporal query efficiency. International Journal of Digital Earth(1),1124-1143.Search in Google Scholar
Fang Huang,Qiang Zhu,Ji Zhou,Jian Tao,Xiaocheng Zhou,Du Jin… & Lizhe Wang. (2017). Research on the Parallelization of the DBSCAN Clustering Algorithm for Spatial Data Mining Based on the Spark Platform. Remote Sensing(12),1301.FangHuangQiangZhuJiZhouJianTaoXiaochengZhouDuJinLizheWang (2017). Research on the Parallelization of the DBSCAN Clustering Algorithm for Spatial Data Mining Based on the Spark Platform. Remote Sensing(12),1301.Search in Google Scholar
Chuanjia Yao,Rong Jiang,Bin Wu,Pinghui Li & Chenguang Wang. (2024). A cross domain access control model for medical consortium based on DBSCAN and penalty function.BMC Medical Informatics and Decision Making(1),260-260.ChuanjiaYaoRongJiangBinWuPinghuiLiChenguangWang (2024). A cross domain access control model for medical consortium based on DBSCAN and penalty function.BMC Medical Informatics and Decision Making(1),260-260.Search in Google Scholar