Artificial Intelligence Research Center (AIRC)

1. Abasi, A. K., Makhadmeh, S. N., Al-Betar, M. A., Alomari, O. A., Awadallah, M. A., Alyasseri, Z. A. A., . . . Hadjouni, M. (2022). Lemurs optimizer: A new metaheuristic algorithm for global optimization. Applied Sciences (Switzerland), 12(19) doi:10.3390/app121910057
2. Abbas, F., Yasmin, M., Fayyaz, M., Elaziz, M. A., Lu, S., & Abd El-Latif, A. A. (2021). Gender classification using proposed CNN-based model and ant colony optimization. Mathematics, 9(19) doi:10.3390/math9192499
3. Abd Elaziz, M., Abualigah, L., Ibrahim, R. A., & Attiya, I. (2021). IoT workflow scheduling using intelligent arithmetic optimization algorithm in fog computing. Computational Intelligence and Neuroscience, 2021 doi:10.1155/2021/9114113
4. Abd Elaziz, M., Abualigah, L., Issa, M., & Abd El-Latif, A. A. (2023). Optimal parameters extracting of fuel cell based on gorilla troops optimizer. Fuel, 332 doi:10.1016/j.fuel.2022.126162
5. Abd Elaziz, M., Abu-Donia, H. M., Hosny, R. A., Hazae, S. L., & Ibrahim, R. A. (2022). Improved evolutionary-based feature selection technique using extension of knowledge based on the rough approximations. Information Sciences, 594, 76-94. doi:10.1016/j.ins.2022.01.026
6. Abd Elaziz, M., Almodfer, R., Ahmadianfar, I., Ibrahim, I. A., Mudhsh, M., Abualigah, L., . . . Yousri, D. (2022). Static models for implementing photovoltaic panels characteristics under various environmental conditions using improved gradient-based optimizer. Sustainable Energy Technologies and Assessments, 52 doi:10.1016/j.seta.2022.102150
7. Abd Elaziz, M., Al-qaness, M. A. A., Dahou, A., Ibrahim, R. A., & El-Latif, A. A. A. (2023). Intrusion detection approach for cloud and IoT environments using deep learning and capuchin search algorithm. Advances in Engineering Software, 176 doi:10.1016/j.advengsoft.2022.103402
8. Abd Elaziz, M., Chelloug, S., Alduailij, M., & Al-qaness, M. A. A. (2023). Boosted reptile search algorithm for engineering and optimization problems. Applied Sciences (Switzerland), 13(5) doi:10.3390/app13053206
9. Abd Elaziz, M., Dahou, A., Alsaleh, N. A., Elsheikh, A. H., Saba, A. I., & Ahmadein, M. (2021). Boosting covid-19 image classification using mobilenetv3 and aquila optimizer algorithm. Entropy, 23(11) doi:10.3390/e23111383
10. Abd Elaziz, M., Dahou, A., Orabi, D. A., Alshathri, S., Soliman, E. M., & Ewees, A. A. (2023). A hybrid multitask learning framework with a fire hawk optimizer for arabic fake news detection. Mathematics, 11(2) doi:10.3390/math11020258
11. Abd Elaziz, M., Ghoneimi, A., Elsheikh, A. H., Abualigah, L., Bakry, A., & Nabih, M. (2022). Predicting shale volume from seismic traces using modified random vector functional link based on transient search optimization model: A case study from netherlands north sea. Natural Resources Research, 31(3), 1775-1791. doi:10.1007/s11053-022-10049-4
12. Abd Elaziz, M., Mabrouk, A., Dahou, A., & Chelloug, S. A. (2022). Medical image classification utilizing ensemble learning and levy flight-based honey badger algorithm on 6G-enabled internet of things. Computational Intelligence and Neuroscience, 2022 doi:10.1155/2022/5830766
13. Abd Elaziz, M., Ouadfel, S., Abd El-Latif, A. A., & Ali Ibrahim, R. (2022). Feature selection based on modified bio-inspired atomic orbital search using arithmetic optimization and opposite-based learning. Cognitive Computation, 14(6), 2274-2295. doi:10.1007/s12559-022-10022-6
14. Abd Elaziz, M., Ouadfel, S., & Ibrahim, R. A. (2023). Boosting capuchin search with stochastic learning strategy for feature selection. Neural Computing and Applications, doi:10.1007/s00521-023-08400-8
15. Abd Elaziz, M., Ewees, A. A., Yousri, D., Abualigah, L., & Al-qaness, M. A. A. (2022). Modified marine predators algorithm for feature selection: Case study metabolomics. Knowledge and Information Systems, 64(1), 261-287. doi:10.1007/s10115-021-01641-w
16. Abdalkareem, Z. A., Al-Betar, M. A., Amir, A., Ehkan, P., Hammouri, A. I., & Salman, O. H. (2022). Discrete flower pollination algorithm for patient admission scheduling problem. Computers in Biology and Medicine, 141 doi:10.1016/j.compbiomed.2021.105007
17. Abdalkareem, Z. A., Amir, A., Al-Betar, M. A., Ekhan, P., & Hammouri, A. I. (2021). Healthcare scheduling in optimization context: A review. Health and Technology, 11(3), 445-469. doi:10.1007/s12553-021-00547-5
18. Abdi Alkareem Alyasseri, Z., Alomari, O. A., Al-Betar, M. A., Awadallah, M. A., Hameed Abdulkareem, K., Abed Mohammed, M., . . . Rho, S. (2022). EEG channel selection using multiobjective cuckoo search for person identification as protection system in healthcare applications. Computational Intelligence and Neuroscience, 2022 doi:10.1155/2022/5974634
19. Abed-alguni, B. H., Alawad, N. A., Al-Betar, M. A., & Paul, D. (2022). Opposition-based sine cosine optimizer utilizing refraction learning and variable neighborhood search for feature selection. Applied Intelligence, doi:10.1007/s10489-022-04201-z
20. Abu Doush, I., Al-Betar, M. A., Awadallah, M. A., Alyasseri, Z. A. A., Makhadmeh, S. N., & El-Abd, M. (2022). Island neighboring heuristics harmony search algorithm for flow shop scheduling with blocking. Swarm and Evolutionary Computation, 74 doi:10.1016/j.swevo.2022.101127
21. Abu Doush, I., Awadallah, M. A., Al-Betar, M. A., Alomari, O. A., Makhadmeh, S. N., Abasi, A. K., & Alyasseri, Z. A. A. (2023). Archive-based coronavirus herd immunity algorithm for optimizing weights in neural networks. Neural Computing and Applications, doi:10.1007/s00521-023-08577-y
22. Abualigah, L., Almotairi, K. H., Al-qaness, M. A. A., Ewees, A. A., Yousri, D., Elaziz, M. A., & Nadimi-Shahraki, M. H. (2022). Efficient text document clustering approach using multi-search arithmetic optimization algorithm. Knowledge-Based Systems, 248 doi:10.1016/j.knosys.2022.108833
23. Abualigah, L., Almotairi, K. H., Elaziz, M. A., Shehab, M., & Altalhi, M. (2022). Enhanced flow direction arithmetic optimization algorithm for mathematical optimization problems with applications of data clustering. Engineering Analysis with Boundary Elements, 138, 13-29. doi:10.1016/j.enganabound.2022.01.014
24. Abualigah, L., Al-Okbi, N. K., Elaziz, M. A., & Houssein, E. H. (2022). Boosting marine predators algorithm by salp swarm algorithm for multilevel thresholding image segmentation. Multimedia Tools and Applications, 81(12), 16707-16742. doi:10.1007/s11042-022-12001-3
25. Abualigah, L., Diabat, A., Altalhi, M., & Elaziz, M. A. (2022). Improved gradual change-based harris hawks optimization for real-world engineering design problems. Engineering with Computers, doi:10.1007/s00366-021-01571-9
26. Abualigah, L., Diabat, A., Svetinovic, D., & Elaziz, M. A. (2022). Boosted harris hawks gravitational force algorithm for global optimization and industrial engineering problems. Journal of Intelligent Manufacturing, doi:10.1007/s10845-022-01921-4
27. Abualigah, L., Elaziz, M. A., Khasawneh, A. M., Alshinwan, M., Ibrahim, R. A., Al-qaness, M. A. A., . . . Gandomi, A. H. (2022). Meta-heuristic optimization algorithms for solving real-world mechanical engineering design problems: A comprehensive survey, applications, comparative analysis, and results. Neural Computing and Applications, 34(6), 4081-4110. doi:10.1007/s00521-021-06747-4
28. Abualigah, L., Elaziz, M. A., Sumari, P., Geem, Z. W., & Gandomi, A. H. (2022). Reptile search algorithm (RSA): A nature-inspired meta-heuristic optimizer. Expert Systems with Applications, 191 doi:10.1016/j.eswa.2021.116158
29. Abualigah, L., Elaziz, M. A., Sumari, P., Khasawneh, A. M., Alshinwan, M., Mirjalili, S., . . . Gandomi, A. H. (2022). Black hole algorithm: A comprehensive survey. Applied Intelligence, 52(10), 11892-11915. doi:10.1007/s10489-021-02980-5
30. Abualigah, L., Elaziz, M. A., Yousri, D., Al-qaness, M. A. A., Ewees, A. A., & Zitar, R. A. (2022). Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering. Journal of Intelligent Manufacturing, doi:10.1007/s10845-022-02016-w
31. Abualigah, L., Ewees, A. A., Al-qaness, M. A. A., Elaziz, M. A., Yousri, D., Ibrahim, R. A., & Altalhi, M. (2022). Boosting arithmetic optimization algorithm by sine cosine algorithm and levy flight distribution for solving engineering optimization problems. Neural Computing and Applications, 34(11), 8823-8852. doi:10.1007/s00521-022-06906-1
32. Abualigah, L., Zitar, R. A., Almotairi, K. H., Hussein, A. M., Elaziz, M. A., Nikoo, M. R., & Gandomi, A. H. (2022). Wind, solar, and photovoltaic renewable energy systems with and without energy storage optimization: A survey of advanced machine learning and deep learning techniques. Energies, 15(2) doi:10.3390/en15020578
33. Abu-Doush, I., Ahmed, B., Awadallah, M. A., Al-Betar, M. A., & Rababaah, A. R. (2023). Enhancing multilayer perceptron neural network using archive-based harris hawks optimizer to predict gold prices. Journal of King Saud University - Computer and Information Sciences, 35(5) doi:10.1016/j.jksuci.2023.101557
34. Adel, H., Dahou, A., Mabrouk, A., Elaziz, M. A., Kayed, M., El-Henawy, I. M., . . . Ali, A. A. (2022). Improving crisis events detection using DistilBERT with hunger games search algorithm. Mathematics, 10(3) doi:10.3390/math10030447
35. Ahmed, I., Dahou, A., Chelloug, S. A., Al-Qaness, M. A. A., & Elaziz, M. A. (2022). Feature selection model based on gorilla troops optimizer for intrusion detection systems. Journal of Sensors, 2022 doi:10.1155/2022/6131463
36. Ahmed, I. E., Mehdi, R., & Mohamed, E. A. (2023). The role of artificial intelligence in developing a banking risk index: An application of adaptive neural network-based fuzzy inference system (ANFIS). Artificial Intelligence Review, doi:10.1007/s10462-023-10473-9
37. Aighuraibawi, A. H. B., Abdullah, R., Manickam, S., & Alyasseri, Z. A. A. (2021). Detection of ICMPv6-based DDoS attacks using anomaly based intrusion detection system: A comprehensive review. International Journal of Electrical and Computer Engineering, 11(6), 5216-5228. doi:10.11591/ijece.v11i6.pp5216-5228
38. Akbari, M. A., Zare, M., Azizipanah-abarghooee, R., Mirjalili, S., & Deriche, M. (2022). The cheetah optimizer: A nature-inspired metaheuristic algorithm for large-scale optimization problems. Scientific Reports, 12(1) doi:10.1038/s41598-022-14338-z
39. Al Shinwan, M., Abualigah, L., Huy, T. -., Shdefat, A. Y., Altalhi, M., Kim, C., . . . Kwak, K. S. (2022). An efficient 5G data plan approach based on partially distributed mobility architecture. Sensors, 22(1) doi:10.3390/s22010349
40. Alanazi, M., Alanazi, A., Akbari, M. A., Deriche, M., & Memon, Z. A. (2023). A non-simulation-based linear model for analytical reliability evaluation of radial distribution systems considering renewable DGs. Applied Energy, 342 doi:10.1016/j.apenergy.2023.121153
41. Alani, S., Zakaria, Z., Saeidi, T., Ahmad, A., Imran, M. A., & Abbasi, Q. H. (2021). Microwave imaging of breast skin utilizing elliptical uwb antenna and reverse problems algorithm. Micromachines, 12(6) doi:10.3390/mi12060647
42. Al-Betar, M. A. (2021). Island-based harmony search algorithm for non-convex economic load dispatch problems. Journal of Electrical Engineering and Technology, 16(4), 1985-2015. doi:10.1007/s42835-021-00758-w
43. Al-Betar, M. A., Abasi, A. K., Al-Naymat, G., Arshad, K., & Makhadmeh, S. N. (2023). Optimization of scientific publications clustering with ensemble approach for topic extraction. Scientometrics, 128(5), 2819-2877. doi:10.1007/s11192-023-04674-w
44. Al-Betar, M. A., Awadallah, M. A., Doush, I. A., Alomari, O. A., Abasi, A. K., Makhadmeh, S. N., & Alyasseri, Z. A. A. (2022). Boosting the training of neural networks through hybrid metaheuristics. Cluster Computing, doi:10.1007/s10586-022-03708-x
45. Al-Betar, M. A., Awadallah, M. A., Makhadmeh, S. N., Doush, I. A., Zitar, R. A., Alshathri, S., & Abd Elaziz, M. (2023). A hybrid harris hawks optimizer for economic load dispatch problems. Alexandria Engineering Journal, 64, 365-389. doi:10.1016/j.aej.2022.09.010
46. Al-Betar, M. A., Awadallah, M. A., Zitar, R. A., & Assaleh, K. (2022). Economic load dispatch using memetic sine cosine algorithm. Journal of Ambient Intelligence and Humanized Computing, doi:10.1007/s12652-022-03731-1
47. Aldeeb, B. A., Azmi Al-Betar, M., Md Norwawi, N., Alissa, K. A., Alsmadi, M. K., Hazaymeh, A. A., & Alzaqebah, M. (2022). Hybrid intelligent water drops algorithm for examination timetabling problem. Journal of King Saud University - Computer and Information Sciences, 34(8), 4847-4859. doi:10.1016/j.jksuci.2021.06.016
48. Alfarhan, M., Deriche, M., & Maalej, A. (2022). Robust concurrent detection of salt domes and faults in seismic surveys using an improved UNet architecture. IEEE Access, 10, 39424-39435. doi:10.1109/ACCESS.2020.3043973
49. Al-Fawa'reh, M., Al-Fayoumi, M., Nashwan, S., & Fraihat, S. (2022). Cyber threat intelligence using PCA-DNN model to detect abnormal network behavior. Egyptian Informatics Journal, 23(2), 173-185. doi:10.1016/j.eij.2021.12.001
50. Alhaj, Y. A., Dahou, A., Al-Qaness, M. A. A., Abualigah, L., Abbasi, A. A., Almaweri, N. A. O., . . . Damaševičius, R. (2022). A novel text classification technique using improved particle swarm optimization: A case study of arabic language. Future Internet, 14(7) doi:10.3390/fi14070194
51. Alharbi, K. A. M., Riasat, S., Ramzan, M., & Kadry, S. (2023). Role of surface catalyzed reaction in the flow of temperature-dependent viscosity fluid over a rotating disk. Numerical Heat Transfer; Part A: Applications, doi:10.1080/10407782.2023.2173344
52. Alhawari, A. R. H., Majeed, S. F., Saeidi, T., Mumtaz, S., Alghamdi, H., Hindi, A. T., . . . Abbasi, Q. H. (2021). Compact elliptical uwb antenna for underwater wireless communications. Micromachines, 12(4) doi:10.3390/mi12040411
53. Alhawari, A. R. H., Saeidi, T., Almawgani, A. H. M., Hindi, A. T., Alghamdi, H., Alsuwian, T., . . . Imran, M. A. (2021). Wearable metamaterial dual-polarized high isolation uwb mimo vivaldi antenna for 5g and satellite communications. Micromachines, 12(12) doi:10.3390/mi12121559
54. Alhijawi, B., & AL-Naymat, G. (2022). Novel positive multi-layer graph based method for collaborative filtering recommender systems. Journal of Computer Science and Technology, 37(4), 975-990. doi:10.1007/s11390-021-0420-2
55. Ali, S. M., Sovuthy, C., Noghanian, S., Ali, Z., Abbasi, Q. H., Imran, M. A., . . . Socheatra, S. (2021). Design and evaluation of a flexible dual-band meander line monopole antenna for on-and off-body healthcare applications. Micromachines, 12(5) doi:10.3390/mi12050475
56. Alian, M., & Al-Naymat, G. (2022). Questions clustering using canopy-K-means and hierarchical-K-means clustering. International Journal of Information Technology (Singapore), 14(7), 3793-3802. doi:10.1007/s41870-022-01012-w
57. Aliyu, F., Sheltami, T., Deriche, M., & Nasser, N. (2022). Human immune-based intrusion detection and prevention system for fog computing. Journal of Network and Systems Management, 30(1) doi:10.1007/s10922-021-09616-6
58. AlJarrah, M. N., Yaseen, Q. M., & Mustafa, A. M. (2022). A context-aware android malware detection approach using machine learning. Information (Switzerland), 13(12) doi:10.3390/info13120563
59. Alkareem Alyasseri, Z. A., Al-Betar, M. A., Awadallah, M. A., Makhadmeh, S. N., Abasi, A. K., Doush, I. A., & Alomari, O. A. (2022). A hybrid flower pollination with β-hill climbing algorithm for global optimization. Journal of King Saud University - Computer and Information Sciences, 34(8), 4821-4835. doi:10.1016/j.jksuci.2021.06.015
60. Alkhraisat, H., Dalbah, L. M., Al-Betar, M. A., Awadallah, M. A., Assaleh, K., & Deriche, M. (2023). Size optimization of truss structures using improved grey wolf optimizer. IEEE Access, 11, 13383-13397. doi:10.1109/ACCESS.2023.3243164
61. Alkoffash, M. S., Awadallah, M. A., Alweshah, M., Zitar, R. A., Assaleh, K., & Al-Betar, M. A. (2021). A non-convex economic load dispatch using hybrid salp swarm algorithm. Arabian Journal for Science and Engineering, 46(9), 8721-8740. doi:10.1007/s13369-021-05646-z
62. Almadhor, A., Irfan, R., Gao, J., Saleem, N., Tayyab Rauf, H., & Kadry, S. (2023). E2E-DASR: End-to-end deep learning-based dysarthric automatic speech recognition. Expert Systems with Applications, 222 doi:10.1016/j.eswa.2023.119797
63. Almodfer, R., Abd Elaziz, M., Alshathri, S., Abualigah, L., Mudhsh, M., Shahzad, K., & Issa, M. (2022). Improving parameter estimation of fuel cell using honey badger optimization algorithm. Frontiers in Energy Research, 10 doi:10.3389/fenrg.2022.875332
64. Almodfer, R., Mudhsh, M., Alshathri, S., Yousri, D., Abualigah, L., Hassan, O. F., & Abd Elaziz, M. (2022). Chaotic honey badger algorithm for single and double photovoltaic cell/module. Frontiers in Energy Research, 10 doi:10.3389/fenrg.2022.1011887
65. Almodfer, R., Mudhsh, M., Chelloug, S., Shehab, M., Abualigah, L., & Abd Elaziz, M. (2022). Quantum mutation reptile search algorithm for global optimization and data clustering. Human-Centric Computing and Information Sciences, 12 doi:10.22967/HCIS.2022.12.030
66. Almodfer, R., Zayed, M. E., Elaziz, M. A., Aboelmaaref, M. M., Mudhsh, M., & Elsheikh, A. H. (2022). Modeling of a solar-powered thermoelectric air-conditioning system using a random vector functional link network integrated with jellyfish search algorithm. Case Studies in Thermal Engineering, 31 doi:10.1016/j.csite.2022.101797
67. Almomani, A., Al-Nawasrah, A., Alauthman, M., Al-Betar, M. A., & Meziane, F. (2021). Botnet detection used fast-flux technique, based on adaptive dynamic evolving spiking neural network algorithm. International Journal of Ad Hoc and Ubiquitous Computing, 36(1), 50-65. doi:10.1504/IJAHUC.2021.112981
68. Alnaimy, M. A., Shahin, S. A., Afifi, A. A., Ewees, A. A., Junakova, N., Balintova, M., & Abd Elaziz, M. (2022). Spatio prediction of soil capability modeled with modified RVFL using aptenodytes forsteri optimization and digital soil assessment technique. Sustainability (Switzerland), 14(22) doi:10.3390/su142214996
69. Al-Naymat, G., Hussain, H., Al-Kasassbeh, M., & Al-Dmour, N. (2021). Accurate detection of network anomalies within SNMP-MIB data set using deep learning. International Journal of Computer Applications in Technology, 66(1), 74-85. doi:10.1504/IJCAT.2021.119606
70. Al-Okaily, A., Teoh, A. P., Al-Okaily, M., Iranmanesh, M., & Al-Betar, M. A. (2023). The efficiency measurement of business intelligence systems in the big data-driven economy: A multidimensional model. Information Discovery and Delivery, doi:10.1108/IDD-01-2022-0008
71. Alomari, O. A., Makhadmeh, S. N., Al-Betar, M. A., Alyasseri, Z. A. A., Doush, I. A., Abasi, A. K., . . . Zitar, R. A. (2021). Gene selection for microarray data classification based on gray wolf optimizer enhanced with TRIZ-inspired operators. Knowledge-Based Systems, 223 doi:10.1016/j.knosys.2021.107034
72. Al-Qaness, M. A. A., Dahou, A., Elaziz, M. A., & Helmi, A. M. (2023). Multi-ResAtt: Multilevel residual network with attention for human activity recognition using wearable sensors. IEEE Transactions on Industrial Informatics, 19(1), 144-152. doi:10.1109/TII.2022.3165875
73. Al-qaness, M. A. A., Dahou, A., Ewees, A. A., Abualigah, L., Huai, J., Abd Elaziz, M., & Helmi, A. M. (2023). ResInformer: Residual transformer-based artificial time-series forecasting model for PM2.5 concentration in three major chinese cities. Mathematics, 11(2) doi:10.3390/math11020476
74. Al-qaness, M. A. A., Ewees, A. A., Abualigah, L., AlRassas, A. M., Thanh, H. V., & Abd Elaziz, M. (2022). Evaluating the applications of dendritic neuron model with metaheuristic optimization algorithms for crude-oil-production forecasting. Entropy, 24(11) doi:10.3390/e24111674
75. Al-qaness, M. A. A., Ewees, A. A., Elaziz, M. A., & Samak, A. H. (2022). Wind power forecasting using optimized dendritic neural model based on seagull optimization algorithm and aquila optimizer. Energies, 15(24) doi:10.3390/en15249261
76. Al-qaness, M. A. A., Ewees, A. A., Fan, H., Abualigah, L., & Elaziz, M. A. (2022). Boosted ANFIS model using augmented marine predator algorithm with mutation operators for wind power forecasting. Applied Energy, 314 doi:10.1016/j.apenergy.2022.118851
77. Al-qaness, M. A. A., Ewees, A. A., Fan, H., Abualigah, L., Elsheikh, A. H., & Abd Elaziz, M. (2023). Wind power prediction using random vector functional link network with capuchin search algorithm. Ain Shams Engineering Journal, doi:10.1016/j.asej.2022.102095
78. Al-qaness, M. A. A., Ewees, A. A., Fan, H., AlRassas, A. M., & Abd Elaziz, M. (2022). Modified aquila optimizer for forecasting oil production. Geo-Spatial Information Science, 25(4), 519-535. doi:10.1080/10095020.2022.2068385
79. Al-qaness, M. A. A., Ewees, A. A., Thanh, H. V., AlRassas, A. M., & Abd Elaziz, M. (2022). An optimized neuro-fuzzy system using advance nature-inspired aquila and salp swarm algorithms for smart predictive residual and solubility carbon trapping efficiency in underground storage formations. Journal of Energy Storage, 56 doi:10.1016/j.est.2022.106150
80. Al-qaness, M. A. A., Ewees, A. A., Thanh, H. V., AlRassas, A. M., Dahou, A., & Elaziz, M. A. (2023). Predicting CO2 trapping in deep saline aquifers using optimized long short-term memory. Environmental Science and Pollution Research, 30(12), 33780-33794. doi:10.1007/s11356-022-24326-5
81. Al-qaness, M. A. A., Helmi, A. M., Dahou, A., & Elaziz, M. A. (2022). The applications of metaheuristics for human activity recognition and fall detection using wearable sensors: A comprehensive analysis. Biosensors, 12(10) doi:10.3390/bios12100821
82. Al-Quraan, M., Mohjazi, L., Bariah, L., Centeno, A., Zoha, A., Arshad, K., . . . Muhammad, M. (2023). Edge-native intelligence for 6G communications driven by federated learning: A survey of trends and challenges. IEEE Transactions on Emerging Topics in Computational Intelligence, , 1-23. doi:10.1109/TETCI.2023.3251404
83. AlRassas, A. M., Al-qaness, M. A. A., Ewees, A. A., Ren, S., Sun, R., Pan, L., & Abd Elaziz, M. (2022). Advance artificial time series forecasting model for oil production using neuro fuzzy-based slime mould algorithm. Journal of Petroleum Exploration and Production Technology, 12(2), 383-395. doi:10.1007/s13202-021-01405-w
84. Alsadoon, A., Al-Naymat, G., Osman, A. H., Alsinglawi, B., Maabreh, M., & Islam, M. R. (2023). DFCV: A framework for evaluation deep learning in early detection and classification of lung cancer. Multimedia Tools and Applications, doi:10.1007/s11042-023-15238-8
85. Alshathri, S., Abd Elaziz, M., Yousri , D., Hassan , O. F., & Ibrahim , R. A. (2022). Quantum chaotic honey badger algorithm for feature selection. Electronics (Switzerland), 11(21) doi:10.3390/electronics11213463
86. Al-Shourbaji, I., Helian, N., Sun, Y., Alshathri, S., & Elaziz, M. A. (2022). Boosting ant colony optimization with reptile search algorithm for churn prediction. Mathematics, 10(7) doi:10.3390/math10071031
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87. Alsoruji, G. S., Sadoun, A. M., Elaziz, M. A., Al-Betar, M. A., Abdallah, A. W., & Fathy, A. (2023). On the prediction of the mechanical properties of ultrafine grain al-TiO2 nanocomposites using a modified long-short term memory model with beluga whale optimizer. Journal of Materials Research and Technology, 23, 4075-4088. doi:10.1016/j.jmrt.2023.01.212
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175. Makhadmeh, S. N., Al-Betar, M. A., Alyasseri, Z. A. A., Abasi, A. K., Khader, A. T., Damaševičius, R., . . . Abdulkareem, K. H. (2021). Smart home battery for the multi-objective power scheduling problem in a smart home using grey wolf optimizer. Electronics (Switzerland), 10(4), 1-35. doi:10.3390/electronics10040447
176. Makhadmeh, S. N., Al-Betar, M. A., Assaleh, K., & Kassaymeh, S. (2022). A hybrid white shark equilibrium optimizer for power scheduling problem based IoT. IEEE Access, 10, 132212-132231. doi:10.1109/ACCESS.2022.3229434
177. Makhadmeh, S. N., Al-Betar, M. A., Awadallah, M. A., Abasi, A. K., Alyasseri, Z. A. A., Doush, I. A., . . . Mohammed, M. A. (2022). A modified coronavirus herd immunity optimizer for the power scheduling problem. Mathematics, 10(3) doi:10.3390/math10030315
178. Makhadmeh, S. N., Alomari, O. A., Mirjalili, S., Al-Betar, M. A., & Elnagar, A. (2022). Recent advances in multi-objective grey wolf optimizer, its versions and applications. Neural Computing and Applications, 34(22), 19723-19749. doi:10.1007/s00521-022-07704-5
179. Manic, K. S., Rajinikanth, V., Al-Bimani, A. S., Taniar, D., & Kadry, S. (2023). Framework to detect schizophrenia in brain MRI slices with mayfly algorithm-selected deep and handcrafted features. Sensors, 23(1) doi:10.3390/s23010280
180. Meqdad, M. N., Husain, S. O., Jawad, A. M., Kadry, S., & Khekan, A. R. (2023). Classification of electroencephalography using cooperative learning based on participating client balancing. International Journal of Electrical and Computer Engineering, 13(4), 4692-4699. doi:10.11591/ijece.v13i4.pp4692-4699
181. Meqdad, M. N., Hussein, A. H., Husain, S. O., Jawad, A. M., & Kadry, S. (2023). Human activity recognition method using joint deep learning and acceleration signal. IAES International Journal of Artificial Intelligence, 12(3), 1459-1467. doi:10.11591/ijai.v12.i3.pp1459-1467
182. Meqdad, M. N., Kadry, S., & Rauf, H. T. (2022). Improved dragonfly optimization algorithm for detecting IoT outlier sensors. Future Internet, 14(10) doi:10.3390/fi14100297
183. Meqdad, M. N., Rauf, H. T., & Kadry, S. (2023). Bone anomaly detection by extracting regions of interest and convolutional neural networks. Applied System Innovation, 6(1) doi:10.3390/asi6010021
184. Mohammed, H. J., Al-Fahdawi, S., Al-Waisy, A. S., Zebari, D. A., Ibrahim, D. A., Mohammed, M. A., . . . Kim, J. (2022). ReID-DeePNet: A hybrid deep learning system for person re-identification. Mathematics, 10(19) doi:10.3390/math10193530
185. Mohan, R., Kadry, S., Rajinikanth, V., Majumdar, A., & Thinnukool, O. (2022). Automatic detection of tuberculosis using VGG19 with seagull-algorithm. Life, 12(11) doi:10.3390/life12111848
186. Mostafa, R. R., Gaheen, M. A., Abd ElAziz, M., Al-Betar, M. A., & Ewees, A. A. (2023). An improved gorilla troops optimizer for global optimization problems and feature selection. Knowledge-Based Systems, 269 doi:10.1016/j.knosys.2023.110462
187. Murtaza, M., Sharif, M., Yasmin, M., Fayyaz, M., Kadry, S., & Lee, M. Y. (2022). Clothes retrieval using M-AlexNet with mish function and feature selection using joint shannon's entropy pearson's correlation coefficient. IEEE Access, 10, 115469-115490. doi:10.1109/ACCESS.2022.3218322
188. Nabih, M., Ghoneimi, A., Bakry, A., Chelloug, S. A., Al-Betar, M. A., & Abd Elaziz, M. (2023). Rock physics analysis from predicted poisson's ratio using RVFL based on wild geese algorithm in scarab gas field in WDDM concession, egypt. Marine and Petroleum Geology, 147 doi:10.1016/j.marpetgeo.2022.105949
189. Nadimi-Shahraki, M. H., Fatahi, A., Zamani, H., Mirjalili, S., Abualigah, L., & Elaziz, M. A. (2021). Migration-based moth-flame optimization algorithm. Processes, 9(12) doi:10.3390/pr9122276
190. Nadimi-Shahraki, M. H., Taghian, S., Mirjalili, S., Abualigah, L., Elaziz, M. A., & Oliva, D. (2021). Ewoa-opf: Effective whale optimization algorithm to solve optimal power flow problem. Electronics (Switzerland), 10(23) doi:10.3390/electronics10232975
191. Nadimi-Shahraki, M. H., Taghian, S., Mirjalili, S., Ewees, A. A., Abualigah, L., & Elaziz, M. A. (2021). Mtv-mfo: Multi-trial vector-based moth-flame optimization algorithm. Symmetry, 13(12) doi:10.3390/sym13122388
192. Najjar, I. M. R., Sadoun, A. M., Alsoruji, G. S., Elaziz, M. A., & Wagih, A. (2022). Predicting the mechanical properties of Cu–Al2O3 nanocomposites using machine learning and finite element simulation of indentation experiments. Ceramics International, 48(6), 7748-7758. doi:10.1016/j.ceramint.2021.11.322
193. Naveenkumar, R., Iyyappan, J., Pravin, R., Kadry, S., Han, J., Sindhu, R., . . . Baskar, G. (2023). A strategic review on sustainable approaches in municipal solid waste management and energy recovery: Role of artificial intelligence, economic stability and life cycle assessment. Bioresource Technology, 379 doi:10.1016/j.biortech.2023.129044
194. Nayak, J., Naik, B., Dash, P. B., Vimal, S., & Kadry, S. (2022). Hybrid bayesian optimization hypertuned catboost approach for malicious access and anomaly detection in IoT nomalyframework. Sustainable Computing: Informatics and Systems, 36 doi:10.1016/j.suscom.2022.100805
195. Niu, Z., Awad, M. I., Shah, U. H., Boushaki, M. N., Zweiri, Y., Seneviratne, L., & Hussain, I. (2022). Towards safe physical human-robot interaction by exploring the rapid stiffness switching feature of discrete variable stiffness actuation. IEEE Robotics and Automation Letters, 7(3), 8084-8091. doi:10.1109/LRA.2022.3185366
196. Odat, E., & Yaseen, Q. M. (2023). A novel machine learning approach for android malware detection based on the co-existence of features. IEEE Access, 11, 15471-15484. doi:10.1109/ACCESS.2023.3244656
197. Ouadfel, S., & Abd Elaziz, M. (2021). A multi-objective gradient optimizer approach-based weighted multi-view clustering. Engineering Applications of Artificial Intelligence, 106 doi:10.1016/j.engappai.2021.104480
198. Ouadfel, S., & Abd Elaziz, M. (2022). Efficient high-dimension feature selection based on enhanced equilibrium optimizer. Expert Systems with Applications, 187 doi:10.1016/j.eswa.2021.115882
     
     

1. Aldhanhani, M., Al-Betar, M. A., & Makhadmeh, S. N. (2022). Business intelligence solution for covid-19 pandemic. Paper presented at the 2022 International Conference on Emerging Trends in Computing and Engineering Applications, ETCEA 2022 - Proceedings, doi:10.1109/ETCEA57049.2022.10009694
2. Almohammedi, A. M., Zerguine, A., Deriche, M., & Sait, S. M. (2022). Artificial bee colony DLMS beyond mean square error boundary in ad-hoc WSN. Paper presented at the Proceedings - 2022 14th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2022, 572-576. doi:10.1109/CICN56167.2022.10008253
3. Al-Omoush, R., Fraihat, S., Al-Naymat, G., & Awad, M. (2022). Design and implementation of business intelligence framework for a global online retail business. Paper presented at the 2022 International Conference on Emerging Trends in Computing and Engineering Applications, ETCEA 2022 - Proceedings, doi:10.1109/ETCEA57049.2022.10009688
4. Alyasiri, O. M., Cheah, Y. -., & Abasi, A. K. (2021). Hybrid filter-wrapper text feature selection technique for text classification. Paper presented at the International Conference on Communication and Information Technology, ICICT 2021, 80-86. doi:10.1109/ICICT52195.2021.9567898
5. Alyasseri, Z. A. A., Al-Betar, M. A., Awadallah, M. A., Makhadmeh, S. N., Alomari, O. A., Abasi, A. K., & Doush, I. A. (2021). EEG feature fusion for person identification using efficient machine learning approach. Paper presented at the Proceedings - 2021 Palestinian International Conference on Information and Communication Technology, PICICT 2021, 97-102. doi:10.1109/PICICT53635.2021.00029
6. Arbateni, K., & Deriche, M. (2022). Support vector machine for heart beats classification based on robust filtering. Paper presented at the 2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022, 653-656. doi:10.1109/SSD54932.2022.9955703
7. Awad, M., Al Redhaei, A., & Fraihat, S. (2022). Using business intelligence to analyze road traffic accidents. Paper presented at the ACM International Conference Proceeding Series, 83-92. doi:10.1145/3551504.3551507
8. Dalbah, L. M., Ali, S., & Al-Naymat, G. (2022). An interactive dashboard for predicting bank customer attrition. Paper presented at the 2022 International Conference on Emerging Trends in Computing and Engineering Applications, ETCEA 2022 - Proceedings, doi:10.1109/ETCEA57049.2022.10009818
9. Faraj, M. A., Maalej, B., Derbel, N., & Deriche, M. (2022). Modeling and robust computed torque control for lower limb exoskeleton contacting with ground. Paper presented at the 2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022, 571-579. doi:10.1109/SSD54932.2022.9955781
10. Fraihat, S., Innab, H., Makhadmeh, S. N., & Al-Betar, M. A. (2022). Business intelligence system for human resource management system. Paper presented at the 2022 International Conference on Emerging Trends in Computing and Engineering Applications, ETCEA 2022 - Proceedings, doi:10.1109/ETCEA57049.2022.10009861
11. Hellara, H., Barioul, R., Choura, A., Sahnoun, S., Fakhfakh, A., Bouchaala, D., . . . Kanoun, O. (2022). sEMG features selection by a chaotic salp swarm algorithm for hand gestures classification. Paper presented at the 2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022, 622-628. doi:10.1109/SSD54932.2022.9955800
12. Khurma, R. A., Awadallah, M. A., & Aljarah, I. (2021). Binary harris hawks optimisation filter based approach for feature selection. Paper presented at the Proceedings - 2021 Palestinian International Conference on Information and Communication Technology, PICICT 2021, 59-64. doi:10.1109/PICICT53635.2021.00022
13. Makhadmeh, S. N., Al-Betar, M. A., Abasi, A. K., Awadallah, M. A., Alkareem Alyasseri, Z. A., Alomari, O. A., & Doush, I. A. (2021). Wind driven optimization with smart home battery for power scheduling problem in smart home. Paper presented at the Proceedings - 2021 Palestinian International Conference on Information and Communication Technology, PICICT 2021, 82-87. doi:10.1109/PICICT53635.2021.00026
14. Mashaleh, A. S., Binti Ibrahim, N. F., Al-Betar, M. A., Mustafa, H. M. J., & Yaseen, Q. M. (2022). Detecting spam email with machine learning optimized with harris hawks optimizer (HHO) algorithm. Paper presented at the Procedia Computer Science, , 201(C) 659-664. doi:10.1016/j.procs.2022.03.087
15. Sharif, A., Liaqat, S., Arshad, K., Assaleh, K., & Ramzan, N. (2023). Inkjet printed passive RFID sensor for wetness detection of diapers. Paper presented at the 2023 International Microwave and Antenna Symposium, IMAS 2023, 172-175. doi:10.1109/IMAS55807.2023.10066932
16. Taib, Y., Qasim, M., Hayek, B. A., Kabalan, A., Shehieb, W., Yacoub, P., . . . Assaleh, K. (2022). Primary diagnosis of thyroid stimulating hormone using a non-invasive method. Paper presented at the Proceedings of the 2022 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2022, 1-5. doi:10.1109/IoTaIS56727.2022.9975924
17. Toubar, H., Hameed Shah, U., & Hussain, I. (2022). A compliant-rigid underwater manipulator for enhanced safety and precision performance. Paper presented at the ASCC 2022 - 2022 13th Asian Control Conference, Proceedings, 1505-1510. doi:10.23919/ASCC56756.2022.9828337
18. Zarzour, H., Maazouzi, F., Al-Zinati, M., Nusayr, A., Alsmirat, M., Al-Ayyoub, M., & Jararweh, Y. (2022). Using K-means clustering ensemble to improve the performance in recommender systems. Paper presented at the 2022 International Conference on Intelligent Data Science Technologies and Applications, IDSTA 2022, 176-180. doi:10.1109/IDSTA55301.2022.9923070
    

1. Al-Naymat, G., Khader, M., Al-Betar, M. A., Hriez, R., & Hadi, A. (2023). MR-VDENCLUE: Varying density clustering using MapReduce doi:10.1007/978-3-031-16072-1_55
2. Anuar, N. A., Muniandy, L., Jaafar, K. A. B., Lim, Y., Sabeeh, A. L. L., Sumari, P., . . . Hussein, A. M. A. (2023). Rambutan image classification using various deep learning approaches doi:10.1007/978-3-031-17576-3_2
3. Dashtipour, K., Taylor, W., Ansari, S., Zahid, A., Gogate, M., Ahmad, J., . . . Abbasi, Q. (2022). Detecting Alzheimer’s disease using machine learning methods doi:10.1007/978-3-030-95593-9_8
4. Kadry, S., Rajinikanth, V., Srivastava, G., & Meqdad, M. N. (2022). Mayfly-algorithm selected features for classification of breast histology images into Benign/Malignant class doi:10.1007/978-3-031-21517-9_6
5. Kadry, S., Taniar, D., Meqdad, M. N., Srivastava, G., & Rajinikanth, V. (2022). Assessment of brain tumor in flair MRI slice with joint thresholding and segmentation doi:10.1007/978-3-031-21517-9_5
6. Suresh Kumar, S., Dashtipour, K., Gogate, M., Ahmad, J., Assaleh, K., Arshad, K., . . . Ahmad, W. (2022). Comparing the performance of different classifiers for posture detection doi:10.1007/978-3-030-95593-9_17
7. Taha, A., Ge, Y., Taylor, W., Zoha, A., Assaleh, K., Arshad, K., . . . Imran, M. A. (2022). Indoor activity position and direction detection using software defined radios doi:10.1007/978-3-030-95593-9_2
8. Taylor, W., Shah, S. A., Dashtipour, K., Le Kernec, J., Abbasi, Q. H., Assaleh, K., . . . Imran, M. A. (2022). Wireless sensing for human activity recognition using USRP doi:10.1007/978-3-030-95593-9_5

Two faculty members from Ajman University's Artificial Intelligence Research Centre (AIRC) and College of Engineering and Information Technology (CEIT) has made an achievement in the realm of scientific research by publishing a paper in the prestigious IEEE Transactions on Emerging Topics in Computational Intelligence journal, that has been listed as one of the 50 most frequently accessed documents on the Journal website (https://ieeexplore.ieee.org/xpl/topAccessedArticles.jsp?punumber=7433297). This journal is considered a top-tier journal and boasts a remarkable CiteScore percentile of 98% on Scopus with an impressive impact factor of 4.851. The research paper, titled "Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges," is co-authored by Prof Khaled Assaleh and Prof Kamran Arshad from AIRC. The IEEE Transactions on Emerging Topics in Computational Intelligence focuses on publishing original and innovative articles on emerging aspects of computational intelligence, including theories, applications, and surveys. The paper is an outcome of Ajman University's Internal Research Grant, and collaboration with international collaborators from distinguished universities such as the University of Glasgow (UK), Technology Innovation Institute (Abu Dhabi, UAE), Khalifa University (UAE), and Carleton University (Canada), have played a significant role in making this research a success. This work paves the way for Edge-Native Intelligence and Federated Learning, which can revolutionize the way we approach 6G Communications.

The VDENCLUE is an enhanced variant of the DENCLUE algorithm capable of discovering clusters with varying densities. However, to compute an object density, VDENCLUE computes this object's influence from all other objects, which is repeated for each data object. Hence, incurring high computation overhead that is impractical for large datasets. This proposal introduces the first parallel variant of VDENCLUE (and DENCLUE) algorithm, an approximated variant of VDENCLUE, called MR-VDENCLUE. The MR-VDENCLUE uses the Locality-Sensitive Hashing (LSH) technique to partition the big dataset, performs local clustering using adaptive grid structure, and aggregates local results based on a new merging approach to generate the final approximated results. Besides discovering clusters with arbitrary shapes, MR-VDENCLUE will discover clusters with varying densities and scale-up to handle big datasets.

The interest in defining theme structures in science (so-called topics) has grown over the past ten years in understanding new and historical ideas in scientific publications. In reality, the content of scientific publications can be represented in short sentences or phrases. Commonly, the topics are often done by researchers manually, for instance, when they create or update their online profile on various scientific platforms or submit an original manuscript to a journal. At present, an overwhelming number of scientific publications are published every day, making it difficult to get a complete overview of such studies using manual approaches. Hence, focusing on automatically extracting topics from scientific publications could be the best alternative. Until today, there is no intelligent system for extracting significant topics from the scientific publications in the United Arab Emirates academic especially for research institutions that are ranked in the QS World University Rankings. This project aims to propose an intelligent system for automatically extracting topics from scientific publications, enabling the researchers and decision-makers to obtain a comprehensive overview of multi-scale scientific publications to increase the opportunities for collaboration between the researchers in UAE universities common interest topics.  Technically, this system can be divided into two main tasks: (i) Text Document Clustering and (ii) Topic Extraction. To achieve the project aims, the main objectives will be addressed as (a) Collecting the scientific publications of UAE universities from the Scopus database of the last five years. b) Clustering the scientific publication's text using unsupervised clustering method c) Classifying the scientific publications based on the clustering results to extract the most important scientific topics for each cluster. d) Build a web-based system that can visualize the results of the topic extraction task.

In the current decade of the electrical power sector, traditional power grids and their primitive systems became not able to meet the user requirements of power due to the multitude of appliances that require a huge amount of power and population growth, particularly in overcrowded countries, such as UAE. Therefore, alternative systems based on smart technologies, known as smart grids (SGs), are emerged to overcome such issues. The SG is an upgraded generation of the traditional power grid proposed to improve the grid systems and capacity, increasing the power supplier companies' (PSCs) profits. In addition, SG allows users to get advantages by rescheduling smart appliances' operation time and reducing electricity bills. The problem of scheduling smart appliances' operation time according to several constraints, is known as the power scheduling problem in smart home (PSPSH). Several artificial intelligence (AI) methods have been proposed to address PSPSH and find the best schedule optimally. The AI methods can achieve their benefits through an automatic smart system called artificial intelligence smart system. In this research project, a new approach is proposed for PSCs in UAE based on upgrading the traditional power grid to SG to achieve its benefits. In addition, an AISS is constructed to automatically and optimally address PSPSH using a recent robust AI method. The AI method is adapted to find the best schedule for appliances' operation time and address PSPSH optimally. Furthermore, the adapted AI method’s performance is improved to enhance results and achieve better schedules.

LaTeX, which is pronounced «Lah-tech» or «Lay-tech» (to rhyme with «blech» or «Bertolt Brecht»), is a document preparation system for high-quality typesetting. It is most often used for medium-to-large technical or scientific documents but it can be used for almost any form of publishing.

LaTeX is not a word processor! Instead, LaTeX encourages authors not to worry too much about the appearance of their documents but to concentrate on getting the right content.

The AIRC has organized a workshop, titled LATEX workshop - The Gate for Professional Document, for the MSAI students on 23/01/2022.

The AIRC has provided a participation certificate for the participants.

 The LATEX workshop - The Gate for Professional Document is prepared and presented by:

• Dr. Sharif Naser Makhadmeh
• Eng. Lamees Mohammad Dalbah

• Eng. Shaimaa Mahmood Mounir Kouka

The main outlines of the LATEX workshop - The Gate for Professional Document are:

1. Introduction
2. Share and Download​
3. Basic Structure​
4. Text manipulation​
5. Mathematical Expression​
6. Figures
7. Tables​
8. Algorithms​
9. References​
10. Presentations​

Python is an open-source (free) programming language that is used in web programming, artificial intelligence, machine learning, data science, and many scientific applications. Learning Python allows the programmer to focus on solving problems, rather than focusing on syntax. Its relative size and simplified syntax give it an edge over languages like Java and C++, yet the abundance of libraries gives it the power needed to accomplish great things.

The AIRC has organized a new workshop for MSAI students at Ajman University, titled Python and Data Engineering Workshop, on 20/02/2022.

The AIRC has provided a participation certificate for the participants.

The Python and Data Engineering Workshop is prepared and presented by:

• Dr. Sharif Naser Makhadmeh
• Eng. Lamees Mohammad Dalbah

• Eng. Shaimaa Mahmood Mounir Kouka

The main outlines of the Python and Data Engineering Workshop are:

    Python Basics​

1. Introduction to Python​
2. Starting with Colab​
3. Add comment​
4. Variables and simple data types​
5. If Statements​
6. Loops​
7. Functions​

    Data Engineering ​

1. What is preprocessing ​
2. Loading the data​
3. Pandas dataframe​
4. Exploratory Data Analysis​
5. Data Cleaning​
6. Input-output separation​
7. Data Transformation ​
8. Data Reduction
9. Data Visualization​

Learn python language starting from basics to advanced topics and apply your knowledge in voice assistant applications. This workshop aims to teach python language to students without prior programming experience and deliver the basic programming principles such as operations, control structures, data types, etc. Also, it covers advanced topics in python such as dictionaries and list manipulation, creating and calling functions, and file manipulation. Our workshop includes practice and debugging sessions to enrich the students' knowledge and grasp of python and enhance their problem-solving skills. Finally, applying the knowledge of the course content in an innovative voice assistant application. At the end of the workshop, students have a comprehensive understanding of python and implement practical and innovative speech assistant project.

The Hands-On Python Workshop is prepared and presented by:

• Dr. Sharif Naser Makhadmeh
• Eng. Lamees Mohammad Dalbah

• Eng. Shaimaa Mahmood Mounir Kouka

This workshop is oriented around building a 3D rocket game using unity engine along with covering the basics of programming in unity with C# language, dives into the 3D game development fundamentals such as controlling objects in the game environment, scripting its functionality using C# language, simulating and applying physics laws in the game environment for a more realistic user experience. The aim of this workshop is to practice professionally creating 3D high-quality games efficiently using unity game engine with Graphical User Interface and deploy it for many platforms.

The Master Unity 3D Game Development Workshop is prepared and presented by:

• Dr. Sharif Naser Makhadmeh
• Eng. Lamees Mohammad Dalbah

• Eng. Shaimaa Mahmood Mounir Kouka