Abbasov, B., & Korukoglu, S. (2009). Effective RED: An algorithm to improve RED's performance by reducing packet loss rate. Journal of Network and Computer Applications, 32(3), 703-709. doi:10.1016/j.jnca.2008.07.001

Abdulkareem, K. H. (0000). A New Standardisation and Selection Framework for Real-Time Image Dehazing Algorithms from Multi-Foggy Scenes Based on Fuzzy Delphi and Hybrid Multi-Criteria Decision Analysis Methods, Retrieved from www.scopus.com

Abdulkareem, K. H., Arbaiy, N., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., & Salih, M. M. (2020). A novel multi-perspective benchmarking framework for selecting image dehazing intelligent algorithms based on BWM and group VIKOR techniques. International Journal of Information Technology and Decision Making, 19(3), 909-957. doi:10.1142/S0219622020500169

Abdulkareem, K. H., Arbaiy, N., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., & Salih, M. M. (2020). A novel multi-perspective benchmarking framework for selecting image dehazing intelligent algorithms based on BWM and group VIKOR techniques. International Journal of Information Technology and Decision Making, 19(3), 909-957. doi:10.1142/S0219622020500169

Abdullah, L., Adawiyah, C. W. R., & Kamal, C. W. (2018). A decision making method based on interval type-2 fuzzy sets: An approach for ambulance location preference. Applied Computing and Informatics, 14(1), 65-72. doi:10.1016/j.aci.2017.04.003

Abdullateef, B. N., Elias, N. F., Mohamed, H., Zaidan, A. A., & Zaidan, B. B. (2016). An evaluation and selection problems of OSS-LMS packages. SpringerPlus, 5(1), 1-35. doi:10.1186/s40064-016-1828-y

Abualhaj, M. M., Abu-Shareha, A. A., & Al-Tahrawi, M. M. (2018). FLRED: An efficient fuzzy logic based network congestion control method. Neural Computing and Applications, 30(3), 925-935. doi:10.1007/s00521-016-2730-9

Alaa, M., Albakri, I. S. M. A., Singh, C. K. S., Hammed, H., Zaidan, A. A., Zaidan, B. B., . . . Jasim, A. N. (2019). Assessment and ranking framework for the english skills of pre-service teachers based on fuzzy delphi and TOPSIS methods. IEEE Access, 7, 126201-126223. doi:10.1109/ACCESS.2019.2936898

Alamoodi, A. H., Garfan, S., Zaidan, B. B., Zaidan, A. A., Shuwandy, M. L., Alaa, M., . . . Alobaidi, O. R. (2020). A systematic review into the assessment of medical apps: Motivations, challenges, recommendations and methodological aspect. Health and Technology, 10(5), 1045-1061. doi:10.1007/s12553-020-00451-4

Albahri, A. S., Albahri, O. S., Zaidan, A. A., Zaidan, B. B., Hashim, M., Alsalem, M. A., . . . Baqer, M. J. (2019). Based multiple heterogeneous wearable sensors: A smart real-time health monitoring structured for hospitals distributor. IEEE Access, 7, 37269-37323. doi:10.1109/ACCESS.2019.2898214

Albahri, A. S., Alwan, J. K., Taha, Z. K., Ismail, S. F., Hamid, R. A., Zaidan, A. A., . . . Alsalem, M. A. (2021). IoT-based telemedicine for disease prevention and health promotion: State-of-the-art. Journal of Network and Computer Applications, 173 doi:10.1016/j.jnca.2020.102873

Albahri, A. S., Hamid, R. A., Albahri, O. S., & Zaidan, A. A. (2021). Detection-based prioritisation: Framework of multi-laboratory characteristics for asymptomatic COVID-19 carriers based on integrated Entropy–TOPSIS methods. Artificial Intelligence in Medicine, 111 doi:10.1016/j.artmed.2020.101983

Albahri, A. S., Zaidan, A. A., Albahri, O. S., Zaidan, B. B., & Alsalem, M. A. (2018). Real-time fault-tolerant mHealth system: Comprehensive review of healthcare services, opens issues, challenges and methodological aspects. Journal of Medical Systems, 42(8) doi:10.1007/s10916-018-0983-9

Albahri, O. S., Albahri, A. S., Mohammed, K. I., Zaidan, A. A., Zaidan, B. B., Hashim, M., & Salman, O. H. (2018). Systematic review of real-time remote health monitoring system in triage and priority-based sensor technology: Taxonomy, open challenges, motivation and recommendations. Journal of Medical Systems, 42(5) doi:10.1007/s10916-018-0943-4

Albahri, O. S., Albahri, A. S., Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., Mohsin, A. H., . . . Shareef, A. H. (2019). Fault-tolerant mHealth framework in the context of IoT-based real-time wearable health data sensors. IEEE Access, 7, 50052-50080. doi:10.1109/ACCESS.2019.2910411

Albahri, O. S., Al-Obaidi, J. R., Zaidan, A. A., Albahri, A. S., Zaidan, B. B., Salih, M. M., . . . Zulkifli, C. Z. (2020). Helping doctors hasten COVID-19 treatment: Towards a rescue framework for the transfusion of best convalescent plasma to the most critical patients based on biological requirements via ml and novel MCDM methods. Computer Methods and Programs in Biomedicine, 196 doi:10.1016/j.cmpb.2020.105617

Albahri, O. S., Zaidan, A. A., Salih, M. M., Zaidan, B. B., Khatari, M. A., Ahmed, M. A., . . . Alazab, M. (2021). Multidimensional benchmarking of the active queue management methods of network congestion control based on extension of fuzzy decision by opinion score method. International Journal of Intelligent Systems, 36(2), 796-831. doi:10.1002/int.22322

Albahri, O. S., Zaidan, A. A., Zaidan, B. B., Albahri, A. S., Mohsin, A. H., Mohammed, K. I., & Alsalem, M. A. (2022). New mHealth hospital selection framework supporting decentralised telemedicine architecture for outpatient cardiovascular disease-based integrated techniques: Haversine-GPS and AHP-VIKOR. Journal of Ambient Intelligence and Humanized Computing, 13(1), 219-239. doi:10.1007/s12652-021-02897-4

Albahri, O. S., Zaidan, A. A., Zaidan, B. B., Hashim, M., Albahri, A. S., & Alsalem, M. A. (2018). Real-time remote health-monitoring systems in a medical centre: A review of the provision of healthcare services-based body sensor information, open challenges and methodological aspects. Journal of Medical Systems, 42(9) doi:10.1007/s10916-018-1006-6

Aliyeva, K. (2017). Multi-criteria house buying decision making based on type-2 fuzzy sets. Paper presented at the Procedia Computer Science, , 120 515-520. doi:10.1016/j.procs.2017.11.273 Retrieved from www.scopus.com

Almahdi, E. M., Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., Albahri, O. S., & Albahri, A. S. (2019). Mobile patient monitoring systems from a benchmarking aspect: Challenges, open issues and recommended solutions. Journal of Medical Systems, 43(7) doi:10.1007/s10916-019-1336-z

Almahdi, E. M., Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., Albahri, O. S., & Albahri, A. S. (2019). Mobile-based patient monitoring systems: A prioritisation framework using multi-criteria decision-making techniques. Journal of Medical Systems, 43(7) doi:10.1007/s10916-019-1339-9

Alsalem, M. A., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alamoodi, A. H., Albahri, A. S., . . . Mohammed, K. I. (2019). Multiclass benchmarking framework for automated acute leukaemia detection and classification based on BWM and group-VIKOR. Journal of Medical Systems, 43(7) doi:10.1007/s10916-019-1338-x

Alsalem, M. A., Zaidan, A. A., Zaidan, B. B., Hashim, M., Albahri, O. S., Albahri, A. S., . . . Mohammed, K. I. (2018). Systematic review of an automated multiclass detection and classification system for acute leukaemia in terms of evaluation and benchmarking, open challenges, issues and methodological aspects. Journal of Medical Systems, 42(11) doi:10.1007/s10916-018-1064-9

Baklizi, M., Abdel-Jaber, H., Abu-Shareha, A. A., Abualhaj, M. M., & Ramadass, S. (2014). Fuzzy logic controller of gentle random early detection based on average queue length and delay rate. International Journal of Fuzzy Systems, 16(1), 9-19. Retrieved from www.scopus.com

Belamfedel Alaoui, S., Tissir, E. H., & Chaibi, N. (2020). Analysis and design of robust guaranteed cost active queue management. Computer Communications, 159, 124-132. doi:10.1016/j.comcom.2020.05.009

Chen, J., Hu, C., & Ji, Z. (2011). Self-tuning random early detection algorithm to improve performance of network transmission. Mathematical Problems in Engineering, 2011 doi:10.1155/2011/872347

Chen, S. -., & Lee, L. -. (2010). Fuzzy multiple attributes group decision-making based on the ranking values and the arithmetic operations of interval type-2 fuzzy sets. Expert Systems with Applications, 37(1), 824-833. doi:10.1016/j.eswa.2009.06.094

Chen, W., Li, Y., & Yang, S. -. (2007). An average queue weight parameterization in a network supporting TCP flows with RED. Paper presented at the 2007 IEEE International Conference on Networking, Sensing and Control, ICNSC'07, 590-595. doi:10.1109/ICNSC.2007.372845 Retrieved from www.scopus.com

Chitra, K., & Padamavathi, D. G. (2010). Adaptive CHOKe: An algorithm to increase the fairness in internet routers. Int.J.Advanced Networking and Applications, 1(6), 382-386. Retrieved from www.scopus.com

Dai, Y., Hu, B., Su, Y., Mao, C., Chen, J., Zhang, X., . . . Cai, H. (2015). Feature selection of high-dimensional biomedical data using improved SFLA for disease diagnosis. Paper presented at the Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015, 458-463. doi:10.1109/BIBM.2015.7359728 Retrieved from www.scopus.com

De Campos, L. M., Cano, A., Castellano, J. G., & Moral, S. (2011). Bayesian networks classifiers for gene-expression data. Paper presented at the International Conference on Intelligent Systems Design and Applications, ISDA, 1200-1206. doi:10.1109/ISDA.2011.6121822 Retrieved from www.scopus.com

Enaizan, O., Zaidan, A. A., Alwi, N. H. M., Zaidan, B. B., Alsalem, M. A., Albahri, O. S., & Albahri, A. S. (2020). Electronic medical record systems: Decision support examination framework for individual, security and privacy concerns using multi-perspective analysis. Health and Technology, 10(3), 795-822. doi:10.1007/s12553-018-0278-7

Hamdi, M. M., Rashid, S. A., Ismail, M., Altahrawi, M. A., Mansor, M. F., & Abufoul, M. K. (2018). Performance evaluation of active queue management algorithms in large network. Paper presented at the ISTT 2018 - 2018 IEEE 4th International Symposium on Telecommunication Technologies, doi:10.1109/ISTT.2018.8701716 Retrieved from www.scopus.com

Hong, J., Joo, C., & Bahk, S. (2007). Active queue management algorithm considering queue and load states. Computer Communications, 30(4), 886-892. doi:10.1016/j.comcom.2006.10.012

Hu, H., Wang, Y., & Cai, Y. (2012). Advantages of the enhanced opposite direction searching algorithm for computing the centroid of an interval type-2 fuzzy set. Asian Journal of Control, 14(5), 1422-1430. doi:10.1002/asjc.477

Ibrahim, N. K., Hammed, H., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., . . . Alaa, M. (2019). Multi-criteria evaluation and benchmarking for young learners' english language mobile applications in terms of LSRW skills. IEEE Access, 7, 146620-146651. doi:10.1109/ACCESS.2019.2941640

Jumaah, F. M., Zadain, A. A., Zaidan, B. B., Hamzah, A. K., & Bahbibi, R. (2018). Decision-making solution based multi-measurement design parameter for optimization of GPS receiver tracking channels in static and dynamic real-time positioning multipath environment. Measurement: Journal of the International Measurement Confederation, 118, 83-95. doi:10.1016/j.measurement.2018.01.011

Jumaah, F. M., Zaidan, A. A., Zaidan, B. B., Bahbibi, R., Qahtan, M. Y., & Sali, A. (2018). Technique for order performance by similarity to ideal solution for solving complex situations in multi-criteria optimization of the tracking channels of GPS baseband telecommunication receivers. Telecommunication Systems, 68(3), 425-443. doi:10.1007/s11235-017-0401-5

Kalid, N., Zaidan, A. A., Zaidan, B. B., Salman, O. H., Hashim, M., Albahri, O. S., & Albahri, A. S. (2018). Based on real time remote health monitoring systems: A new approach for prioritization “Large scales data” patients with chronic heart diseases using body sensors and communication technology. Journal of Medical Systems, 42(4) doi:10.1007/s10916-018-0916-7

Kalid, N., Zaidan, A. A., Zaidan, B. B., Salman, O. H., Hashim, M., & Muzammil, H. (2018). Based real time remote health monitoring systems: A review on patients prioritization and related "big data" using body sensors information and communication technology. Journal of Medical Systems, 42(2) doi:10.1007/s10916-017-0883-4

Khatari, M., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., & Alsalem, M. A. (2019). Multi-criteria evaluation and benchmarking for active queue management methods: Open issues, challenges and recommended pathway solutions. International Journal of Information Technology and Decision Making, 18(4), 1187-1242. doi:10.1142/S0219622019300039

Lee, L. -., & Chen, S. -. (2008). A new method for fuzzy multiple attributes group decision-making based on the arithmetic operations of interval type-2 fuzzy sets. Paper presented at the Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC, , 6 3084-3089. doi:10.1109/ICMLC.2008.4620938 Retrieved from www.scopus.com

Liang, Q., & Mendel, J. M. (2000). Interval type-2 fuzzy logic systems: Theory and design. IEEE Transactions on Fuzzy Systems, 8(5), 535-550. doi:10.1109/91.873577

Liao, T. W. (2015). Two interval type 2 fuzzy TOPSIS material selection methods. Materials and Design, 88, 1088-1099. doi:10.1016/j.matdes.2015.09.113

Liu, S., Başar, T., & Srikant, R. (2008). TCP-illinois: A loss- and delay-based congestion control algorithm for high-speed networks. Performance Evaluation, 65(6-7), 417-440. doi:10.1016/j.peva.2007.12.007

Malik, R. (2021). Novel roadside unit positioning framework in the context of the vehicle-to-infrastructure communication system based on AHP—Entropy for weighting and borda—VIKOR for uniform ranking. Int J Inform Technol Decision Making, , 1-34. Retrieved from www.scopus.com

Mendel, J. M. (2007). Type-2 fuzzy sets and systems: An overview. IEEE Computational Intelligence Magazine, 2(1), 20-29. doi:10.1109/MCI.2007.380672

Mliki, H., Chaari, L., & Kamoun, L. (2015). A comprehensive survey on carrier ethernet congestion management mechanism. Journal of Network and Computer Applications, 47, 107-130. doi:10.1016/j.jnca.2014.09.003

Mohammed, K. I., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., Albahri, A. S., . . . Hashim, M. (2019). Real-time remote-health monitoring systems: A review on patients prioritisation for multiple-chronic diseases, taxonomy analysis, concerns and solution procedure. Journal of Medical Systems, 43(7) doi:10.1007/s10916-019-1362-x

Mohammed, R. T. (0000). Determining importance of many-objective optimisation competitive algorithms evaluation criteria based on a novel fuzzy-weighted zero-inconsistency method. Int J Inf Technol Decis Mak, , 1-47. Retrieved from www.scopus.com

Mohammed, R. T., Yaakob, R., Zaidan, A. A., Sharef, N. M., Abdullah, R. H., Zaidan, B. B., & Dawood, K. A. (2020). Review of the research landscape of multi-criteria evaluation and benchmarking processes for many-objective optimization methods: Coherent taxonomy, challenges and recommended solution. International Journal of Information Technology and Decision Making, 19(6), 1619-1693. doi:10.1142/S0219622020300049

Mohammed, T. J., Albahri, A. S., Zaidan, A. A., Albahri, O. S., Al-Obaidi, J. R., Zaidan, B. B., . . . Hadi, S. M. (2021). Convalescent-plasma-transfusion intelligent framework for rescuing COVID-19 patients across centralised/decentralised telemedicine hospitals based on AHP-group TOPSIS and matching component. Applied Intelligence, 51(5), 2956-2987. doi:10.1007/s10489-020-02169-2

Napi, N. M., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., & Albahri, A. S. (2019). Medical emergency triage and patient prioritisation in a telemedicine environment: A systematic review. Health and Technology, 9(5), 679-700. doi:10.1007/s12553-019-00357-w

Park, T., & Shin, S. (2021). Mobius: Packet re-processing hardware architecture for rich policy handling on a network processor. Journal of Network and Systems Management, 29(1) doi:10.1007/s10922-020-09568-3

Pei, L., & Wu, F. (2021). Periodic solutions, chaos and bi-stability in the state-dependent delayed homogeneous additive increase and multiplicative Decrease/Random early detection congestion control systems. Mathematics and Computers in Simulation, 182, 871-887. doi:10.1016/j.matcom.2020.06.001

Qader, M. A., Zaidan, B. B., Zaidan, A. A., Ali, S. K., Kamaluddin, M. A., & Radzi, W. B. (2017). A methodology for football players selection problem based on multi-measurements criteria analysis. Measurement: Journal of the International Measurement Confederation, 111, 38-50. doi:10.1016/j.measurement.2017.07.024

Rahmatullah, B., Zaidan, A. A., Mohamed, F., & Sali, A. (2017). Multi-complex attributes analysis for optimum GPS baseband receiver tracking channels selection. Paper presented at the 2017 4th International Conference on Control, Decision and Information Technologies, CoDIT 2017, , 2017-January 1084-1088. doi:10.1109/CoDIT.2017.8102743 Retrieved from www.scopus.com

Rawat, J., Singh, A., Bhadauria, H. S., & Virmani, J. (2015). Computer aided diagnostic system for detection of leukemia using microscopic images. Paper presented at the Procedia Computer Science, , 70 748-756. doi:10.1016/j.procs.2015.10.113 Retrieved from www.scopus.com

Salih, M. M., Zaidan, B. B., & Zaidan, A. A. (2020). Fuzzy decision by opinion score method. Applied Soft Computing Journal, 96 doi:10.1016/j.asoc.2020.106595

Salih, M. M., Zaidan, B. B., Zaidan, A. A., & Ahmed, M. A. (2019). Survey on fuzzy TOPSIS state-of-the-art between 2007 and 2017. Computers and Operations Research, 104, 207-227. doi:10.1016/j.cor.2018.12.019

Salih, M. M., Zaidan, B. B., Zaidan, A. A., & Ahmed, M. A. (2019). Survey on fuzzy TOPSIS state-of-the-art between 2007 and 2017. Computers and Operations Research, 104, 207-227. doi:10.1016/j.cor.2018.12.019

Salman, O. H., Zaidan, A. A., Zaidan, B. B., Naserkalid, & Hashim, M. (2017). Novel methodology for triage and prioritizing using "big data" patients with chronic heart diseases through telemedicine environmental. International Journal of Information Technology and Decision Making, 16(5), 1211-1245. doi:10.1142/S0219622017500225

Stanojević, R., Shorten, R. N., & Kellett, C. M. (2006). Adaptive tuning of drop-tail buffers for reducing queueing delays. IEEE Communications Letters, 10(7), 570-572. doi:10.1109/LCOMM.2006.1673016

Talal, M., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., Albahri, A. S., . . . Alaa, M. (2019). Comprehensive review and analysis of anti-malware apps for smartphones. Telecommunication Systems, 72(2), 285-337. doi:10.1007/s11235-019-00575-7

Tariq, I. (2018). MOGSABAT: A metaheuristic hybrid algorithm for solving multi-objective optimisation problems. Neural Computing and Applications, 32, 1-15. Retrieved from www.scopus.com

Wu, D., & Wan Tan, W. (2006). Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers. Engineering Applications of Artificial Intelligence, 19(8), 829-841. doi:10.1016/j.engappai.2005.12.011

Yas, Q. M., Zadain, A. A., Zaidan, B. B., Lakulu, M. B., & Rahmatullah, B. (2017). Towards on develop a framework for the evaluation and benchmarking of skin detectors based on artificial intelligent models using multi-criteria decision-making techniques. International Journal of Pattern Recognition and Artificial Intelligence, 31(3) doi:10.1142/S0218001417590029

Yas, Q. M., Zaidan, A. A., Zaidan, B. B., Rahmatullah, B., & Abdul Karim, H. (2018). Comprehensive insights into evaluation and benchmarking of real-time skin detectors: Review, open issues & challenges, and recommended solutions. Measurement: Journal of the International Measurement Confederation, 114, 243-260. doi:10.1016/j.measurement.2017.09.027

Zaidan, A., Zaidan, B., Alsalem, M., Momani, F., & Zughoul, O. (2020). Novel multiperspective hiring framework for the selection of software programmer applicants based on AHP and group TOPSIS techniques. Int J Inf Technol Decis Mak, 18(4), 1-73. Retrieved from www.scopus.com

Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., Albahri, A. S., Yas, Q. M., & Hashim, M. (2018). A review on smartphone skin cancer diagnosis apps in evaluation and benchmarking: Coherent taxonomy, open issues and recommendation pathway solution. Health and Technology, 8(4), 223-238. doi:10.1007/s12553-018-0223-9

Zaidan, A. A., Zaidan, B. B., Al-Haiqi, A., Kiah, M. L. M., Hussain, M., & Abdulnabi, M. (2015). Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS. Journal of Biomedical Informatics, 53, 390-404. doi:10.1016/j.jbi.2014.11.012

Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., Albahri, O. S., Albahri, A. S., & Qahtan, M. Y. (2020). Multi-agent learning neural network and bayesian model for real-time IoT skin detectors: A new evaluation and benchmarking methodology. Neural Computing and Applications, 32(12), 8315-8366. doi:10.1007/s00521-019-04325-3

Zaidan, A. A., Zaidan, B. B., Hussain, M., Al-Haiqi, A. M., Mat Kiah, M. L., & Abdulnabi, M. (2015). Multi-criteria analysis for OS-EMR software selection problem: A comparative study. Decision Support Systems, 78, 15-27. doi:10.1016/j.dss.2015.07.002

Zaidan, B. B., & Zaidan, A. A. (2018). Comparative study on the evaluation and benchmarking information hiding approaches based multi-measurement analysis using TOPSIS method with different normalisation, separation and context techniques. Measurement: Journal of the International Measurement Confederation, 117, 277-294. doi:10.1016/j.measurement.2017.12.019

Zaidan, B. B., & Zaidan, A. A. (2017). Software and hardware FPGA-based digital watermarking and steganography approaches: Toward new methodology for evaluation and benchmarking using multi-criteria decision-making techniques. Journal of Circuits, Systems and Computers, 26(7) doi:10.1142/S021812661750116X

Zaidan, B. B., Zaidan, A. A., Abdul Karim, H., & Ahmad, N. N. (2017). A new approach based on multi-dimensional evaluation and benchmarking for data hiding techniques. International Journal of Information Technology and Decision Making, , 1-42. doi:10.1142/S0219622017500183

Zaidan, B. B., Zaidan, A. A., Karim, H. A., & Ahmad, N. N. (2017). A new digital watermarking evaluation and benchmarking methodology using an external group of evaluators and multi-criteria analysis based on ‘large-scale data’. Software - Practice and Experience, 47(10), 1365-1392. doi:10.1002/spe.2465

Zughoul, O. (2020). Novel triplex procedure for ranking the ability of software engineering students based on two levels of AHP and group TOPSIS techniques. International Journal of Information Technology & Decision Making, Retrieved from www.scopus.com

Zughoul, O., Momani, F., Almasri, O. H., Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., . . . Hashim, M. (2018). Comprehensive insights into the criteria of student performance in various educational domains. IEEE Access, 6, 73245-73264. doi:10.1109/ACCESS.2018.2881282