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SECURING CYBERSPACE: AN EFFICIENT MACHINE LEARNING BASED APPROACH TO PHISHING ATTACK DETECTION

Authors:

Attiq Ur Rehman, Hamayun Khan, Arshad Ali, Yazed ALsaawy, Irfan Ud din, Saif ur Rehman, Rao Muhammad Asif, Mohammad Husain

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00008

August 15, 2024

Abstract:

We explore machine learning strategies and evaluate their viability in distinguishing characteristics that separate secure websites from phishing ones. Given the essential need to defend delicate information and maintain network integrity, we aim to determine the most proficient strategy for identifying phishing websites. Our research focuses on the Random Forest Classifier, illustrating its predominance over other strategies. We have achieved significant improvements in detection rates, with the Random Forest Classifier accomplishing an F1 score of 0.99, precision of 0.99, recall of 0.99, and an AUC of 1.00, outperforming other classifiers. By specifying each strategy and utilizing various assessment methods for visual performance representation, we provide a robust model for phishing detection.

Keywords:

Phishing assault recognition,AI,Random Forest,phishing site location,

Refference:

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XXIII. M. Y. A. Khan, “A GSM based Resource Allocation technique to control Autonomous Robotic Glove for Spinal Cord Implant paralysed Patients using Flex Sensors”, Sukkur IBA Journal of Emerging Technologies, Vol.3, No.2, pp 13-23, 2020
XXIV. M. Y. A. Khan, “A high state of modular transistor on a 105 kW HVPS for X-rays tomography Applications”, Sukkur IBA Journal of Emerging Technologies, Vol.2, No.2, pp 1-6, 2019
XXV. M. Shah, S. Ahmed, K. Saeed, M. Junaid, H. Khan, “Penetration testing active reconnaissance phase–optimized port scanning with nmap tool” In 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), IEEE, pp 1-6, 2019
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XXVIII. M. U. Hashmi, S. A. ZeeshanNajam, “Thermal-Aware Real-Time Task Schedulabilty test for Energy and Power System Optimization using Homogeneous Cache Hierarchy of Multi-core Systems” Journal of Mechanics of Continua and Mathematical Sciences, Vol.14, No.4, pp 442-452, 2023
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XXXI. S. Khan, I. Ullah, M. U. Rahman, H. Khan, A. B. Shah, R. H. Althomali, M. M. Rahman, “Inorganic-polymer composite electrolytes: basics, fabrications, challenges and future perspectives” Reviews in Inorganic Chemistry, Vol.44, No.3, pp 1-29, 2024.
XXXII. S. Khan, I. Ullah, H. Khan, F. U. Rahman, M. U. Rahman, M. A. Saleem, A. Ullah, “Green synthesis of AgNPs from leaves extract of Salvia Sclarea their characterization, antibacterial activity and catalytic reduction ability” Zeitschrift für Physikalische Chemie, Vol.238, No.5, pp 931-947, 2024
XXXIII. T. M. Gondal, Z. Hameed, M. U. Shah, H. Khan, “Cavitation phenomenon and its effects in Francis turbines and amassed adeptness of hydel power plant” In 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), IEEE, pp 1-9, 2019

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Journal Vol – 19 No – 8, August 2024

ATANGANA-BALEANU TIME-STOCHASTIC FRACTIONAL NEUTRAL INTEGRO-DIFFERENTIAL EQUATIONS

Authors:

R. Pradeepa, R. Jayaraman

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00009

August 15, 2024

Abstract:

This study investigates the Atangana-Baleanu time-stochastic fractional neutral integro-differential equation, a complex mathematical model with broad applications in various scientific disciplines. Utilizing Banach's fixed point theory, we rigorously establish the existence and uniqueness of the mild solution to this equation. Our analysis centrally revolves around investigating the Mittag-Leffler non-singular and non-local kernel, emphasizing its crucial significance in elucidating the behavior of the equation. By integrating concepts from fractional differential equations and stochastic differential systems, we contribute to a deeper comprehension of these mathematical phenomena. Our findings not only contribute significantly to advancing theoretical understanding but also establish a solid groundwork for practical applications across various fields.

Keywords:

Existence and uniqueness,Mittag-Leffler Non-singular and non-local kernel,Fractional differential equations,Stochastic differential system and fixed point theorem.,

Refference:

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VI. Caputo, M., Fabrizio, M.: ‘A new definition of fractional derivative without singular kernel’, Progr Fract Differ Appl., Vol. 1 (2015), Pages 73-85.
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VIII. Guendouzi, T., Hamada, I.: ‘Existence and controllability result for fractional neutral stochastic integro-differential equations with infinite delay’, Advanced Modeling and Optimization, Vol. 15(2) (2013), Pages 281-299.
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XIII. Omaba, M.E., Enyi, C.D.: ‘Atangana-Baleanu time-fractional stochastic integrodifferential equation’, Partial Differential Equations in Applied Mathematics, Vol. 4 (2021), Page 100100.
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XVI. Podlubny, I.: ‘Fractional Differential Equations’, Academic Press, New York (1999).

XVII. Ravichandran, C., Logeswari, K., Jarad, F.: ‘New results on existence in the framework of Atangana-Baleanu derivative for fractional integro-differential equations’, Chaos Solitons Fractals, Vol. 125 (2019), Pages 194-200.
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XXVII. Zhou, Y.: ‘Basic Theory of Fractional Differential Equations’, World Scientific, Singapore (2014).

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Journal Vol – 19 No – 8, August 2024

INVESTIGATING THE RAIN IMPACT IN DWDM FSO ENVIRONMENT WITH DIFFERENT MODULATION FORMAT

Authors:

Basim Galeb, Dalal Abdulmohsin Hammood, Haitham Bashar, Aqeel Al-Hilali

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00010

August 15, 2024

Abstract:

Because of its high transmission information rates, accessibility of permit to drive range, signal security, and cost proficiency, free space optical (FSO) correspondence is turning out to be progressively appealing as an option for radio recurrence (RF) correspondence. A 32-channel DWDM FSO framework with an information throughput of 1.28 Tbps has been planned in this review. The recommended framework was tried over a scope of distances (5-20 km) and for three distinct sorts of downpour (light, medium, and weighty), with constriction upsides of (1.988, 5.844, and 9.29) dB, individually. The exhibition of elective balance organizations like NRZ and RZ, as well as 5 situations of fluctuating information force of (- 5,- 10,0,5,10) dBm, has been examined in this paper. The framework execution worked on as the information power was expanded, as per the outcomes from the broken down boundaries of QF and BER. Furthermore, it has been found that utilizing RZ creates improved results for light downpour cases in totally input power situations. While the RZ regulation sort performed better in medium downpours for distances up to 5 km, the NRZ adjustment style is suggested for longer distances. Furthermore, in a weighty downpour climate, using 0 dBm and 5 dBm power showed that NRZ is extensively prevalent, while expanding the capacity to 10 dBm furnished substantially more versatile results regarding the got distance of just 5 km.

Keywords:

Downpour,Fluctuating Information Force,Free Space Optical,Radio Recurrence,

Refference:

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XXVIII. Sharma, A., Kaur, S., & Chaudhary, S. (2021). Performance analysis of 320 Gbps DWDM—FSO System under the effect of different atmospheric conditions. Optical and Quantum Electronics, 53(5), 1-9.‏‏
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Journal Vol – 19 No – 8, August 2024

SOME EXTENDED MUTUAL RELATIONSHIPS BETWEEN THE CONVOLUTIONS TRANSFORM

Authors:

A. K. Thakur, Amar Pandey, Hetram Suryawanshi, Anjali Dubey

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00011

August 15, 2024

Abstract:

In this paper, we establish several interesting mutual relationships between two integral transforms of convolutions transform have been established

Keywords:

Convolution Theorem,Inverse Laplace Transform,Laplace Transform,

Refference:

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VII. Kim, B. J., Kim, B. S. and Skoug, D. (2004) Integral transforms, convolution products and first variations. Int. J. Math. Math. Soc.,11: 579 – 598.
VIII. Kim, J. G., KO, J. W., Park, C. and Skoug, D. (1999) Relationships among transforms, convolutions and first variations. Int. J. Math. Math. Sci., 22. pp. 191 – 204.
IX. N.M. Tuan, P.D. Tuan, Generalized convolutions relative to the Hartley transforms with applications, Sci. Math. Jpn. 70 (2009), 77–89.
X. Park, C., Skoug, D. and Storvick, D. (1998)Relationships among the first variation, the convolution product and the Fourier–Feynman transform Rocky Mt. J. Math. , 28: 1447 – 1468.
XI. Sharma, H. N. (1973), Evaluation of definite integrals by the method of convolution transform Indian Jl. Of math, Vol.15, No.1.
XII. Singh, B.P. (1989), Ph.D. thesis, Integral transform with special reference to convolution transform, Ranchi University.

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Journal Vol – 19 No – 8, August 2024

A WEAK FORM FOR EXTENDING ACTS

Authors:

Shaymaa Amer Abdul-Kareem

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00012

August 15, 2024

Abstract:

Important areas for study in the field of act theory include expansions for the notion for extending acts. There has already been an introduction to the idea of extending acts. Our focus recently has been on semi-extending acts as a means for investigating one of these generalizations. The condition that every sub-act for an S-act  has been semi -large in a retracted from has been what defines it as a semi-extending S-act. Based on this, we provide several characteristics for semi-extending acts. Also included are examples that show how this idea works. We prove relationships between semi-extending acts and related conceptions utilizing a fully essential notion.

Keywords:

Semi ⋂-large sub-acts,⋂-large sub-acts,strongly closed sub-acts,Closed sub-acts,fully ⋂-large acts,

Refference:

I. J. Ahsan and L.Zhongkui, prime and semiprime acts over monoids with zero, Math.J., Ibaraki University, Vol.33, pp. 9 – 15, 2001. https://www.researchgate.net/publication/251080153_Prime_and_semiprime_acts_over_monoids_with_zero
II. Z. A. AL-Bast and P. F. Smith, Multiplication modules, Communication in Algebra, Vol. 10, 755-779, 2007. https://www.tandfonline.com/doi/pdf/10.1080/00927878808823601
III. P. Berthiaume, The injective envelope for S-sets, Canad . Math. Bull.,10, 261 – 273, 2018. https://www.cambridge.org/core/journals/canadian-mathematical-bulletin/article/injective-envelope-of-ssets/CC5C688B45202403E48AE8B5C75CEC0F
IV. N. V. Dungh, D. V. Huynh, P. F. Smith and R. Wisbauer, Extending modules, Pitman Researh Notes in Mathematics Series 313, Longmon, New York, 2019. https://www.researchgate.net/publication/330967788_Extending_modules
V. E. H., Feller and R. L.Gantos, Indecomposable and injective S-acts with zero , Math.Nachr., 41, pp37-48,1969. https://doi.org/10.1002/mana.19690410104
VI. C. V. Hinkle and Jr., The extended centralizer of an S-set, Pacific journal for mathematics, Vol.53, No.1, pp163-170, 1974. https://msp.org/pjm/1974/53-1/pjm-v53-n1-p14-s.pdf
VII. M. Kilp, U. Knauer and A.V. Mikhalev, Monoids acts and categories. Walter de Gruyter, Berlin, New York, 2000. https://doi.org/10.1515/9783110812909
VIII. A. M. Lopez, Jr. and J. K. Luedeman, Quasi-injective S-acts and their S-endomorphism Semigroup, Czechoslovak Math.J., Vol. 29, No.104, pp 97-104,1979. https://eudml.org/doc/13107
IX. A. M. Lopez, Jr. and J.K.Luedeman , The Bicommutator for the injective hull for a non- singular semigroup , Semigroup forum , Vol.12 , pp71-77, 1976. https://link.springer.com/article/10.1007/BF02195910
X. R. Mohammad and E.Majid, Strongly duo and duo right S-acts , Italian journal for pure and applied mathematics,32, 143-154, 2014. https://ijpam.uniud.it/online_issue/201432/14-RooeintanErshad.pdf
XI. A. Shaymaa , Generalizations of injective S-acts, Communications in algebra, Vol.51,No.4 , PP.1743-1751, 2022. https://doi.org/10.1080/00927872.2022.2141766
XII. A. Shaymaa and A. A. Ahmed, ⋂-large pseudo injective acts, Journal for discrete mathematical sciences and cryptography, Vol.25, No.2, PP.511-522, 2022. DOI:10.1080/09720529.2020.1734294
XIII. A. Shaymaa, Extending and P-extending S-act over monoids , International Journal for advanced scientific and technical research, Vol.2 , No. 7, pp.171-178,2017. https://rspublication.com/ijst/2017/april17/19.pdf
XIV. K. Sungjin and K.Jupil , Weakly large subsystems of S-system , J. for Chungcheong Math. Soc., Vol.20, no.4, pp486-493,2007. http://www.ccms.or.kr/data/pdfpaper/jcms20_4/20_4_485.pdf
XV. T. Yan , A.Javed , X.FEI and G.XIAO, Monoids characterized by their injectivity and projectivity classes, Advances in mathematics, Vol.36,No.3 ,pp. 321-326,2007. http://china.oriprobe.com/articles/12275678/Monoids_Characterized_by_Their_Injectivity_and_Pro.htm

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Journal Vol – 19 No – 8, August 2024

PERFORMANCE ANALYSIS OF TASK SCHEDULING USING HYBRID GENETIC MODIFIED WHALE OPTIMIZATION ALGORITHM IN CLOUD COMPUTING

Authors:

S. Kavitha, G. Paramasivam

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00013

August 15, 2024

Abstract:

Cloud computing plays a vital role, which is used to access computing resources and information online. There are a lot of challenges in accessing cloud computing systems. One of the major challenges among these is resource Management which includes scheduling, allocation, and sharing. In this paper, the Hybrid Genetic Modified Whale optimization algorithm which is a combined Genetic and Modified Whale optimization algorithm to analyze the performance of the cloud computing system such as task completion time, execution cost, speedup, and efficiency with proper allocation and sharing of resources The performance of the proposed algorithm is compared with Genetic algorithm and Whale optimization algorithm. The main target of this Proposed system is to reduce the completion time of the task by increasing the speed. Cloud Sim environment tool kit is used for the testing of the proposed system.

Keywords:

Cloud computing,Task scheduling,GA (Genetic Algorithm),HGMWOA (Hybrid Genetic Modified Whale optimization algorithm),VM (Virtual Machine),

Refference:

I. A..Al-maamari and F.A. Omara.: ‘Task scheduling using hybrid algorithm in cloud computing environments’, Journal of Computer Engineering (IOSR-JCE), 17(3): p. 96-106, 2015. https://www.iosrjournals.org/iosr-jce/papers/Vol17-issue3/Version-6/N0173696106.pdf
II. A. S. Kumar and M. Venkatesan.: ‘Task scheduling in a cloud computing environment using HGPSO algorithm’, Cluster Computing, vol.22(6),p. 1-7, 2019. 10.1007/s10586-018-2515-2
III. Ahmed Y. Hamed, M. Kh. Elnahary and Hamdy H. El-Sayed.: ‘Task Scheduling Optimization in Cloud Computing by Jaya Algorithm’. Egypt Applied Science and Innovative Research. Vol. 7, No. 2, 2023. 10.22158/asir.v7n2p30
IV. C.T..Joseph, K. Chandrasekaran and R. Cyriac.: ‘A novel family genetic approach for virtual machine allocation’, Procedia Computer Science, vol.46, pp. 558-565, 2015. 10.1016/j.procs.2015.02.090
V. G. Jorge, C. Erik and A. Omar.: ‘Flower Pollination Algorithm for Multimodal Optimization’, Int. J.Comput. Intell. Syst., vol.10, pp.627–646, 2017. 10(1):627-646
VI. H. Hu, Y. Bai and T. Xu.: ‘A whale optimization algorithm with inertia weight’, WSEAS Trans. Comput., vol.15, pp.319-326, 2016. https://www.wseas.org/multimedia/journals/computers/2016/a545805-085.pdf
VII. H. Li and J. Zhang.: ‘Fast source term estimation using the PGA-NM hybrid method’, Eng. Appl.Artif. Intell., vol.62, pp.68–79,2017. 10.1016/j.engappai.2017.03.010
VIII. J. Yang, B. Jiang, Z. Lv and K. K. R. Choo.: ‘A task scheduling algorithm considering game theory designed for energy management in cloud computing’, Future Generation Computer Systems, vol. 105, pp. 985–992, 2020. https://doi.org/10.1016/j.future.2017.03.024
IX. Jia, LiWei, Kun Li and Xiaoming Shi.: ‘Cloud computing task scheduling model based on improved whale optimization algorithm’. Wireless Communications and Mobile Computing, 2021): 4888154. https://doi.org/10.1155/2021/4888154
X. M. H. Zhong and W. Long.: ‘Whale optimization algorithm based on stochastic adjustment control parameter’, Science Technology & Engineering, 2017.
XI. M. Ibrahim.: ‘Task scheduling algorithms in cloud computing: a review’. Turkish Journal of Computer and Mathematics Education, vol. 12, no. 4, pp. 1041–1053, 2021. 10.17762/turcomat.v12i4.612
XII. M. S. Sanaj and P. M. J. Prathap.: ‘An efficient approach to the map-reduce framework and genetic algorithm based whale optimization algorithm for task scheduling in cloud computing environment’. Materials Today Proceedings, vol. 37, pp. 3199–3208, 2021. 10.1016/j.matpr.2020.09.064
XIII. M.Agarwal and G.M.S. Srivastava.: ‘A Cuckoo Search Algorithm-Based Task Scheduling in Cloud Computing’, Advances in Computer and Computational Sciences, p. 293-299, 2018. 10.1007/978-981-10-3773-3_29
XIV. Majeed, MA Mushahhid and Sreehari Rao Patri.: ‘A hybrid of WOA and mGWO algorithms for global optimization and analog circuit design automation’, COMPEL-The international journal for computation and mathematics in electrical and electronic engineering, vol.38, pp.452-476, 2019. 10.1108/COMPEL-04-2018-0175
XV. N.Dordaie and N.J. Navimipour.: ‘A hybrid particle swarm optimization and hill climbing algorithm for task scheduling in the cloud environments’, ICT Express, 2017. 10.1016/j.icte.2017.08.001
XVI. P.K.Senyo, E. Addae and R. Boateng.: ‘Cloud computing research: A review of research themes, frameworks, methods and future research directions’, International Journal of Information Management, 38(1): p. 128-139, 2018. 10.1016/j.ijinfomgt.2017.07.007
XVII. R. Kaur and S. Kinger.: ‘Enhanced Genetic Algorithm based Task Scheduling in Cloud Computing’, International Journal of Computer Applications, vol. 101(14), 2014. DOI:10.5120/17752-8653
XVIII. R.S.Rathore, S.Sangwan, S.Mazumdar et al.,: ‘W-GUN: whale optimization for energy and delay-centric green underwater networks’, Sensors, vol. 20, no. 5, pp. 1377–1399, 2020. https://doi.org/10.3390/s20051377
XIX. S. H. Jang, T. Y. Kim, J. K. Kim and J. S. Lee.: ‘The study of genetic algorithm-based task scheduling for cloud computing’, International Journal of Control and Automation, vol. 5(4), pp. 157-162, 2012.C:/Users/ASUS/Downloads/2012.12 The Study of Genetic Algorithm-based Task Scheduling for Cloud Computing.pdf
XX. S. Ravichandran and D. E. Naganathan.: ‘Dynamic Scheduling of Data Using Genetic Algorithm in Cloud Computing’, International Journal of Computing Algorithm, vol. 2, pp. 127-133, 2013. 10.20894/IJCOA.101.002.001.003
XXI. S.A. Hamad, and F.A. Omara.: ‘Genetic-based task scheduling algorithm in cloud computing environment’, International Journal of Advanced computer Science and Applications, vol.7(4), p. 550-556, 2016.
XXII. T. Goyal and A. Agrawal.: ‘Host Scheduling Algorithm Using Genetic Algorithm In Cloud Computing Environment’, International Journal of Research in Engineering & Technology (IJRET), vol. 1, 2013. file:///C:/Users/ASUS/Downloads/–1372166085-2.%20Eng-Host%20Scheduling-Tarun%20Goyal%20(2).pdf
XXIII. W. Jing, C. Zhao, Q. Miao, H. Song and G. Chen.: ‘QoS-DPSO: QoS-aware task scheduling for cloud computing system’. Journal of Network and Systems Management, vol. 29, no. 1, pp. 1–29, 2021. https://doi.org/10.1007/s10922-020-09573-6
XXIV. W.Z. Sun and J.S.Wang.: ‘Elman neural network soft-sensor model of conversion velocity in polymerization process optimized by chaos whale optimization algorithm’, IEEE Access, vol.5, pp.13062- 13076, 2017. 10.1109/ACCESS.2017.2723610
XXV. X. Chen and D. Long.: ‘Task scheduling of cloud computing using integrated particle swarm algorithm and ant colony algorithm’, Cluster Computing, vol. 22 (4), pp. 2761–2769, 2019. DOI:10.1007/s10586-017-1479-y
XXVI. X. Chen, L. Cheng, C. Liu et al.,: ‘A WOA-based optimization approach for task scheduling in cloud computing systems’, IEEE Systems Journal, vol. 14, no. 3, pp. 3117–3128, 2020. 10.1109/JSYST.2019.2960088
XXVII. Y. Khalil, M. Alshayeji and I. Ahmad.: ‘Distributed Whale Optimization Algorithm based on Map Reduce’, Concurr. Comp. Pract. E., vol.31, 2019. https://doi.org/10.1002/cpe.4872
XXVIII. Zhihao Peng, Poria Pirozmand, Masoumeh Motevalli and Ali Esmaeili. : ‘Genetic Algorithm-Based Task Scheduling in Cloud Computing Using MapReduce Framework’. Mathematical Problems in Engineering, vol 4, pp.1-11, 2022. 10.1155/2022/4290382

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Journal Vol – 19 No – 8, August 2024

AN EFFICIENT MACHINE LEARNING-BASED DETECTION AND PREDICTION MECHANISM FOR CYBER THREATS USING INTELLIGENT FRAMEWORK IN IOTS

Authors:

Sadia Saif, Hamayun Khan, Arshad Ali, Sami Albouq, Muhammad Zunnurain Hussain, Muhammad Zulkifl Hasan, Irfan Uddin, Shahab Khan, Mohammad Husain

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00014

August 15, 2024

Abstract:

The dangers that Internet of Things (IoT) devices pose to large corporate corporations and smart districts have been dissected by several academics. Given the ubiquitous use of IoT and its unique characteristics, such as mobility and normalization restrictions, intelligent frameworks that can independently detect suspicious activity in privately linked IoT devices are crucial. The IoTs have led an explosion in traffic through the network, bringing information processing techniques for attack detection. The increase in traffic poses challenges in detecting attacks and differentiating traffic that is harmful. In this work, we have proposed a mechanism that uses the standard algorithms in a system that is designed to detect, track, measure and identify online traffic from organizations with malignant transmission: Random Forest (RF), gradient-boosted decision trees (GBDT), and support vector machines (SVM) gives an optimal accuracy of 80.34%,87.5%, and 88.6% while the random forest-based supervised approach is 5.5% better than the previous techniques. To facilitate comparisons between training time, prediction time, specificity, and accuracy, the proposed approach leverages the NSL KDD dataset accuracy.

Keywords:

NSL-KDD dataset distribution,IoT Security,Fog Computing,Deep Learning,Random Forest (RF) machine learning,

Refference:

I. Asish Mitra, Numerical Simulation Of Laminar Convection Flow And Heat Transfer At The Lower Stagnation Point Of A Solid Sphere., J. Mech. Cont.& Math. Sci., Vol.10, No.1, Pp 1469-1480, 2015.
II. A. Belabed, E. Aïmeur And A. Chikh, “A Personalized Whitelist Approach For Phishing Webpage Detection”, 2012 Seventh International Conference On Availability, Reliability And Security, Prague, Pp. 249-254, 2012.
III. A. Naz, H. Khan, I. U. Din, A. Ali, M. Husain, “An Efficient Optimization System for Early Breast Cancer Diagnosis based on Internet of Medical Things and Deep Learning”, Engineering, Technology & Applied Science Research, Vol.14, No.4, pp. 15957-15962, 2024.
IV. Hassan, H. Khan, I. Uddin, A. Sajid, “Optimal Emerging trends of Deep Learning Technique for Detection based on Convolutional Neural Network”, Bulletin of Business and Economics (BBE), Vol.12, No.4, pp. 264-273, 2023.
V. H. Khan, A. Ali, S. Alshmrany, “Energy-Efficient Scheduling Based on Task Migration Policy Using DPM for Homogeneous MPSoCs”, Computers, Materials & Continua, Vol.74, No.1, pp. 965-981, 2023.
VI. H. Sarwar, H. Khan, I. Uddin, R. Waleed, S. Tariq, “An Efficient E-Commerce Web Platform Based on Deep Integration of MEAN Stack Technologies”, Bulletin of Business and Economics (BBE), Vol. 12, No.4, pp. 447-453, 2023.
VII. Hammad. A , E. Zhao, “Mitigating link insecurities in smart grids via QoS multi-constraint routing“, In 2016 IEEE International Conference on Communications Workshops (ICC)”, pp. 380-386. 2016.
VIII. H. Khan, I. Uddin, A. Ali, M. Husain, “An Optimal DPM Based Energy-Aware Task Scheduling for Performance Enhancement in Embedded MPSoC” Computers, Materials & Continua, Vol.74, No.1, pp. 2097-2113, 2023.
IX. Hammad, A. A., Ahmed, “Deep Reinforcement Learning for Adaptive Cyber Defense in Network Security”, In Proceedings of the Cognitive Models and Artificial Intelligence Conference, pp. 292-297, 2016.
X. H. Khan, M. U. Hashmi, Z. Khan, R. Ahmad, “Offline Earliest Deadline first Scheduling based Technique for Optimization of Energy using STORM in Homogeneous Multi-core Systems,” IJCSNS Int. J. Comput. Sci. Netw. Secur, Vol.18, No.12, pp 125-130, 2018.
XI. Hossein Shirazi, Bruhadeshwar. B,”Kn0w Thy Doma1n Name”: Unbiased Phishing Detection Using Domain Name Based Features. In Proceedings Of The 23nd Acm On Symposium On Access Control Models And Technologies (Sacmat ’18). Association For Computing Machinery, New York, Ny, Usa, pp. 69-75, 2018.
XII. Hussain, S., Rajput, U. A., Kazi, Q. A., & Mastoi, S, “Numerical investigation of thermohydraulic performance of triple concentric-tube heat exchanger with longitudinal fins”, J. Mech. Cont. & Math. Sci, Vol. 16, No. 8, pp 61-73, 2021.
XIII. H. Khan, S. Ahmad, N. Saleem, M. U. Hashmi, Q. Bashir, “Scheduling Based Dynamic Power Management Technique for offline Optimization of Energy in Multi Core Processors” Int. J. Sci. Eng. Res, Vol.9, No.12, pp 6-10, 2018.
XIV. H. Khan, K. Janjua, A. Sikandar, M. W. Qazi, Z. Hameed, “An Efficient Scheduling based cloud computing technique using virtual Machine Resource Allocation for efficient resource utilization of Servers” In 2020 International Conference on Engineering and Emerging Technologies (ICEET), IEEE, pp 1-7, 2020.
XV. Hammad, M., Jillani, R. M., Ullah, S., Namoun, A., Tufail, A., Kim, K. H., & Shah, H, “Security framework for network-based manufacturing systems with personalized customization”, An industry 4.0 approach, Sensors, vol. 23. No. 17-55, 2022.
XVI. H. Khan, Q. Bashir, M. U. Hashmi, “Scheduling based energy optimization technique in multiprocessor embedded systems” In 2018 International Conference on Engineering and Emerging Technologies (ICEET), IEEE, pp 1-8, 2018.
XVII. H. Khan, A. Yasmeen, S. Jan, U. Hashmi, “Enhanced Resource Leveling Indynamic Power Management Techniqueof Improvement In Performance For Multi-Core Processors”, Journal Of Mechanics Of Continua And Mathematical Sciences, Vol.6, No.14, pp. 956-972, 2019.
XVIII. H. Khan, K. Janjua, A. Sikandar, M. W. Qazi, Z. Hameed, “An Efficient Scheduling based cloud computing technique using virtual Machine Resource Allocation for efficient resource utilization of Servers” In 2020 International Conference on Engineering and Emerging Technologies (ICEET), IEEE, pp 1-7, 2020.
XIX. H. Huang, J. Tan And L. Liu, “Countermeasure Techniques For Deceptive Phishing Attack”, International Conference On New Trends In Information And Service Science, Beijing, pp. 636-641, 2009.
XX. H. Khan, M. U. Hashmi, Z. Khan, R. Ahmad, “Offline Earliest Deadline first Scheduling based Technique for Optimization of Energy using STORM in Homogeneous Multi-core Systems” IJCSNS Int. J. Comput. Sci. Netw. Secur, Vol.18, No.12, pp 125-130, 2018.
XXI. H. Khan, M. U. Hashmi, Z. Khan, R. Ahmad, A. Saleem, “Performance Evaluation for Secure DES-Algorithm Based Authentication & Counter Measures for Internet Mobile Host Protocol” IJCSNS Int. J. Comput. Sci. Netw. Secur, Vol.18, No.12, pp 181-185, 2018.
XXII. J. Chen; J. Tan, C. Chang, F. Feng, “A New Cost-Aware Sensitivity-Driven Algorithm for the Design of FIR Filters”, IEEE Transactions on Circuits and Systems I, Vol. 64, No. 6 pp: 1588 – 1598, 2017.
XXIII. M. Y. A. Khan, F. Khan, H. Khan, S. Ahmed, M. Ahmad, “Design and Analysis of Maximum Power Point Tracking (MPPT) Controller for PV System” Journal of Mechanics of Continua and Mathematical Sciences, Vol.14, No.1, pp 276-288, 2019.
XXIV. M. Y. A. Khan, “A GSM based Resource Allocation technique to control Autonomous Robotic Glove for Spinal Cord Implant paralysed Patients using Flex Sensors”, Sukkur IBA Journal of Emerging Technologies, Vol.3, No.2, pp 13-23, 2020.
XXV. M. Y. A. Khan, “A high state of modular transistor on a 105 kW HVPS for X-rays tomography Applications”, Sukkur IBA Journal of Emerging Technologies, Vol.2, No.2, pp 1-6, 2019.
XXVI. M. Shah, S. Ahmed, K. Saeed, M. Junaid, H. Khan, “Penetration testing active reconnaissance phase–optimized port scanning with nmap tool” In 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), IEEE, pp 1-6, 2019.
XXVII. M. Y. A. Khan, M. Ibrahim, M. Ali, H. Khan, E. Mustafa, “Cost Benefit Based Analytical Study of Automatic Meter Reading (AMR) and Blind Meter Reading (BMR) used by PESCO (WAPDA),” In 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), IEEE, pp 1-7, 2020.
XXVIII. M. Y. A. Khan, “Enhancing Energy Efficiency in Temperature Controlled Dynamic Scheduling Technique for Multi Processing System on Chip” Sukkur IBA Journal of Emerging Technologies, Vol.2, No.2, pp 46-53,2019.
XXIX. M. U. Hashmi, S. A. ZeeshanNajam, “Thermal-Aware Real-Time Task Schedulabilty test for Energy and Power System Optimization using Homogeneous Cache Hierarchy of Multi-core Systems” Journal of Mechanics of Continua and Mathematical Sciences, Vol.14, No.4, pp 442-452, 2023.
XXX. M. Y. A. Khan, U. Khalil, H. Khan, A. Uddin, S. Ahmed, “Power flow control by unified power flow controller” Engineering, Technology & Applied Science Research, Vol.9, No.2, pp 3900-3904, 2019.
XXXI. R. Waleed, A. Ali, S. Tariq, G. Mustafa, H. Sarwar, S. Saif, I. Uddin, “An Efficient Artificial Intelligence (AI) and Internet of Things (IoT’s) Based MEAN Stack Technology Applications” Bulletin of Business and Economics (BBE), Vol.13, No.2, pp 200-206, 2024.
XXXII. S. Khan, I. Ullah, M. U. Rahman, H. Khan, A. B. Shah, R. H. Althomali, M. M. Rahman, “Inorganic-polymer composite electrolytes: basics, fabrications, challenges and future perspectives” Reviews in Inorganic Chemistry, Vol.44, No.3, pp 1-29, 2024.
XXXIII. S. Khan, I. Ullah, H. Khan, F. U. Rahman, M. U. Rahman, M. A. Saleem, A. Ullah, “Green synthesis of AgNPs from leaves extract of Salvia Sclarea their characterization, antibacterial activity and catalytic reduction ability” Zeitschrift für Physikalische Chemie, Vol.238, No.5, pp 931-947, 2024.
XXXIV. T. M. Gondal, Z. Hameed, M. U. Shah, H. Khan, “Cavitation phenomenon and its effects in Francis turbines and amassed adeptness of hydel power plant” In 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), IEEE, pp 1-9, 2019.

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Journal Vol – 19 No – 8, August 2024

MOTION OF NON-NEWTONIAN FLUID BETWEEN TWO CO-AXIAL POROUS CIRCULAR CYLINDER

Authors:

G. Chakraborty, S. Panja

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00015

August 15, 2024

Abstract:

This paper aims to study the flow of a non-Newtonian fluid of Reiner-Rivlin type between two co-axial porous circular cylinders. The inner cylinder moves with a transient velocity while the outer one is fixed.

Keywords:

Co-axial Porous,Non-Newtonian fluid,Transient Velocity,

Refference:

I. Bagchi, K. C. : Appl. Sci. Ros., 16, 131, 1966.
II. Goutam Chakraborty & Supriya Panja. : ‘ON THE FLOW OF TWO IMMISCIBLE VISCO-ELASTIC FLUIDS THROUGH A RECTANGULAR CHANNEL’. J. Mech. Cont. & Math. Sci. Vol. 10(1), pp. 1464-1448. 10.26782/jmcms.2015.10.00003
III. Khamrui, S. R. : Ball. Cal. Math. Soc., 25, 45, 1950.
IV. Rivlin, R. S. : Proc. Roy. Soc. Lond., 193, 260, 1948.
V. Rukhsar Khatun, Goutam Chakraborty, Md Sadikur Rahman. : ‘OPTIMAL POLICY OF THE INTERVAL EPQ MODEL USING C-L INTERVAL INEQUALITY’. J. Mech. Cont. & Math. Sci. Vol. 18(12), pp. 20-31, 2023. 10.26782/jmcms.2023.12.00002
VI. Sommerfeld, A. : Partial Differential Equations in Physics., New York.
VII. Watson, G. N. : ‘Theory of Bessel Functions.

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Journal Vol – 19 No – 8, August 2024

NATURAL HAZARD ELIMINATION USING ELECTROCHEMICAL PROPERTIES – WATER FLOOD

Authors:

Imadeldin Elmutasim, Mohamad Shaiful, Izzeldin Mohamed, Khalid Bilal, Mohamed Hassan

DOI NO:

https://doi.org/10.26782/jmcms.2024.09.00001

September 12, 2024

Abstract:

A combination of science is a way to accommodate various effective phenomena that could influence the entire life cycle. Recently, emphasis has been placed on the electrochemical polymerization mechanism that is involved in numerous technological applications, including sensors and detectors. Accordingly, daily promises were raised to eliminate life disasters and alleviate the challenges such as water floods as a part of weather changes, which could cause severe damage to life health explicitly, infrastructure, economic productivity, and much more. The proposal considers the matter via compromising the water overflow as well as eliminating the disaster that would come in no warning time and tackling the climate emergency flooding with the potential of water reclamation and offers scholarly suggestions by the requirements of the scientific approach. The investigation clarified the electromagnetic absorber beside the electrochemical polymerization through engagement in the flooded water track stations and the calculation result shows that 19.73% could be absorbed when using 300 grams of polymer gel capacity in 240 grams of water. Generally, the paper explores the electromagnetic flood disaster and how to address it to build a more secure forthcoming.

Keywords:

Wavelength,Climate Change,Water Flood,Electromagnetic Chamber,Frequency,

Refference:

I. Chao‐Song Huang. : ‘Global Pc5 Pulsations From the Polar Cap to the Equator: Wave Characteristics, Phase Variations, Disturbance Current System, and Signal Transmission.’ Journal of Geophysical Research: Space Physics. (2021) 126, 7. 10.1029/2020JA029093
II. E. R. Banfe. : “Abstract of Kelvin Water Dropper,” 2020 IEEE Integrated STEM Education Conference (ISEC), pp. 1-1, 2020. 10.1109/ISEC49744.2020.9397857
III. H. H. Kadar, P. A. A. Rafee and S. S. Sameon. : “Internet of Things (IoT) and Water Crisis,” 4th International Conference on Computer and Information Sciences (ICCOINS), pp. 1-6, 2018. 10.1109/ICCOINS.2018.8510561
IV. I. E. Elmutasim and I. I. Mohd. : “Investigate the Electromagnetic Waves to Desalinate Gulf Water and Beyond.” 7th International Conference on Frontiers of Industrial Engineering (ICFIE), pp. 119-122, 2020. 10.1109/ICFIE50845.2020.9266726
V. I. E. Elmutasim and I. I. Mohd. : “Modeling over the Sea Surface within Elevated Duct,” 7th International Conference on Frontiers of Industrial Engineering (ICFIE), pp. 98-103, 2020, 10.1109/ICFIE50845.2020.9266731
VI. L.Abhishek, R. A. Karthick, K. D. Kumar and G. Sivakumar. : “Efficient water treatment using smart materials,” 2014 International Conference on Smart Structures and Systems (ICSSS), pp. 94-99, 2014. 10.1109/ICSSS.2014.7006180
VII. Mehrotra P, Chatterjee B, Sen S. : ‘EM-Wave Biosensors: A Review of RF, Microwave, mm-Wave and Optical Sensing.’ Sensors (Basel). Vol. 19(5):1013. Published 2019 Feb 27. 10.3390/s19051013
VIII. M. E. Borisova, A. M. Kamalov and Y. K. Osina, “Absorption Phenomena in Capacitors Based on PPS Films,” IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), 2019, pp. 84-86, doi: 10.1109/EIConRus.2019.8657265
IX. N. Anusha, B. Bharathi. : ‘Flood detection and flood mapping using multi-temporal synthetic aperture radar and optical data.’ The Egyptian Journal of Remote Sensing and Space Science. Volume 23(2), pp. 207-219, 2020. ISSN1110-9823, 10.1016/j.ejrs.2019.01.001
X. R. Lopatkiewicz, Z. Nadolny and P. Przybylek. : “The influence of water content on thermal conductivity of paper used as transformer windings insulation.” 2012 IEEE 10th International Conference on the Properties and Applications of Dielectric Materials. pp. 1-4, 2012. 10.1109/ICPADM.2012.6318991
XI. Soraj A. Rahem; Mohsin E. Aldokheily; Athraa H. Mekky. : “Evaluation of fabricated IR absorbing films of polymer nanocapsules.” Eurasian Chemical Communications. Volume 4(12) Pages 1228-1240, December 2022. 10.22034/ecc.2022.345613.1487
XII. Xia, Wenjie, et al., : “Discharge characteristics and bactericidal mechanism of Ar plasma jet with ethanol and oxygen gas admixtures.” Plasma Sources Science and Technologyi. Vol. 28.12, 125005, 2019.
XIII. Xu, T.; Zhu, W.; Sun, J. : ‘Structural Modifications of Sodium Polyacrylate-Polyacrylamide to Enhance Its Water Absorption Rate.’ Coatings 2022, 12, 1234. 10.3390/coatings12091234
XIV. X.Wang, F. Wang, Lanzhigao and R. Chen. : “Understanding and Application of Gauss Theorem in Electrostatic Field,” International Conference on Intelligence Science and Information Engineering, pp. 386-388, 2011. 10.1109/ISIE.2011.118
XV. Zhukovsky, Konstantin V., and Hari M. Srivastava. : “Analytical solutions for heat diffusion beyond Fourier law.” Applied Mathematics and Computation. Vol 293, pp.423-437, 2017

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Journal Vol – 19 No – 9, September 2024

AN ENCRYPTION ALGORITHM EMPLOYING GRAPHS

Authors:

Bipanchy Buzarbarua, Parismita Phukan, Mridusmita Das, Bikash Barman

DOI NO:

https://doi.org/10.26782/jmcms.2024.09.00002

September 12, 2024

Abstract:

With the advancement of technology, maintaining secrecy is a crucial concern that requires a variety of skills. A scientific method for protecting communication against unauthenticated access is cryptography. In cryptography, there are several encryption techniques for data security. It has been suggested that new nonstandard encryption techniques are needed to shield communication from conventional threats. This work presents a method that uses graphs together with some algebraic features to provide some new encryption techniques for safe message transfer. The transmission of secret communications will be safer because of the suggested encryption techniques.

Keywords:

Cryptography,Decryption,Encryption,Star Graph,

Refference:

I. Baizhu N., Rabiha Q., Shafiqur R., and Ghulam F., : “Some Graph-Based EncryptionSchemes”, Journal of Mathematics, vol. 2021, no. 6, 2021, 10.1155/2021/6614172.
II. Burton D.M. Elementary Number Theory, 6th Edition, New Delhi:Tata McGraw-Hill Publishing Company Limited, 2007.
III. Chandrasekaran V. M., Praba B., Manimaran A. and Kailash G., : “Data transfer using complete bipartite graph.” IOP Conf. Ser.: Mater. Sci. Eng.,vol. 263, no 4, 2017, 10.1088/1757-899X/263/4/042120.
IV. Charles D. X., Lauter K. E., and Goren E. Z., : “Cryptographic Hash Functionsfrom Expander Graphs.” J Cryptol, vol. 22, 2009, 10.1007/s00145-007-9002-x
V. Harary F. Graph theory, Addison-Wesley Publishing Company, Inc., Reading, Mass., 1969.
VI. Hu J., Liang J., and Dong S., : “A bipartite graph propagation approach for mobile advertising fraud detection.” Mobile Information Systems, vol. 2017, pp. 12, 2017.
VII. Priyadarsini P.L.K., : “A Survey on some Applications of Graph Theory in Cryptography”. Journal of Discrete Mathematical Sciences and Cryptography, vol. 18, 2015, 18. 209-217. 10.1080/09720529.2013.878819.
VIII. Rosen K. H., Elementary Number theory and its Applications, 5th edition, USA, AddisonWesley, 2005.
IX. Selim G. A., : “How to encrypt a graph, International Journal of Parallel.” Emergent and Distributed Systems, vol. 35(6) pp. 668–681, 2020, 10.1080/09720529.2013.878819
X. Sharma A. K. and Mittal S. K., : “Cryptography & Network Security Hash Function Applications, Attacks and Advances: A Review.” Third International Conference on Inventive Systems and Control (ICISC), Coimbatore, India, 2019, pp. 177-188. 10.1109/ICISC44355.2019.9036448.
XI. Sinha D. and Sethi A., “Encryption using network and matrices through signed graphs.” International Journal of Computer Applications, vol. 138(4) pp. 6–13, 2016. 10.5120/ijca2016908780

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Journal Vol – 19 No – 9, September 2024

ALGORITHM FOR FINDING DOMINATION RESOLVING NUMBER OF A GRAPH

Authors:

Iqbal M. Batiha, Nidal Anakira, Basma Mohamed

DOI NO:

https://doi.org/10.26782/jmcms.2024.09.00003

September 12, 2024

Abstract:

A minimum resolving set is a resolving set with the lowest cardinality and its cardinality is a dimension of connected graph , represented by . A dominating set  is a set of vertices such that each  of  is either in  or has at least one neighbor in .  The dominance number of  is the lowest cardinality of such a set. The lowest cardinality of the dominant resolving set is called a dominant metric dimension of , represented by . This paper presents an algorithm for finding the domination resolving number of a graph.

Keywords:

Domination Number,Metric Dimension,Resolving Dominating Set,

Refference:

I. A. A. Khalil. : ‘Determination and testing the domination numbers of Helm graph, web graph and Levi graph using MATLAB’. Journal of Education Science. Vol. 24, pp. 103-116, 2011. https://www.iasj.net/iasj/download/2b430f4e0c4f89fd
II. A. Sugumaran, E. Jayachandran. : ‘Domination number of some graphs’. International Journal of Scientific Development and Research. Vol. 3, pp. 386-391, 2018. https://api.semanticscholar.org/CorpusID:213194763
III. B. Mohamed. : ‘A comprehensive survey on the metric dimension problem of graphs and its types’. International Journal of Theoretical and Applied Mathematics. Vol. 9, pp. 1-5, 2023. 10.11648/j.ijtam.20230901.11
IV. B. Mohamed, L. Mohaisen, M. Amin. : ‘Binary equilibrium optimization algorithm for computing connected domination metric dimension problem’. Scientific Programming. Vol. 2022, pp. 1-15, 2022. 10.1155/2022/6076369
V. B. Mohamed, L. Mohaisen, M. Amin. : ‘Computing connected resolvability of graphs using binary enhanced Harris Hawks optimization’. Intelligent Automation & Soft Computing. Vol. 36, pp. 2349-2361, 2023. 10.32604/iasc.2023.032930
VI. B. Mohamed, M. Amin. : ‘A hybrid optimization algorithms for solving metric dimension problem’. Graph-HOC. Vol. 15, pp. 1-10, 2023. https://ssrn.com/abstract=4504670
VII. B. Mohamed, M. Amin. : ‘Domination number and secure resolving sets in cyclic networks’. Applied and Computational Mathematics. Vol. 12, pp. 42-45, 2023. 10.11648/j.acm.20231202.12
VIII. B. Mohamed, M. Amin. : ‘The metric dimension of subdivisions of Lilly graph, tadpole graph and special trees’. Applied and Computational Mathematics. Vol. 12, pp. 9-14, 2023. 10.11648/j.acm.20231201.12
IX. B. Mohamed. : ‘Metric dimension of graphs and its application to robotic navigation’. International Journal of Computer Applications. Vol. 184, pp. 1-3, 2022. 10.5120/ijca2022922090
X. B. N. Kavitha, I. Kelkar. : ‘Split and equitable domination in book graph and stacked book graph’. International Journal of Advanced Research in Computer Science. Vol. 8, pp. 108-112, 2017. 10.26483/ijarcs.v8i6.4475
XI. C. S. Nagabhushana, B. N. Kavitha, H. M. Chudamani. : ‘Split and equitable domination of some special graph’. International Journal of Science Technology & Engineering. Vol. 4, pp. 50-54, 2017.
XII. F. Muhammad, L. Susilowati. : ‘Algorithm and computer program to determine metric dimension of graph’. Journal of Physics. Vol. 1494, 012018, 2020. 10.1088/1742-6596/1494/1/012018
XIII. H. Al-Zoubi, H. Alzaareer, A. Zraiqat, T. Hamadneh, W. Al-Mashaleh. : ‘On ruled surfaces of coordinate finite type’. WSEAS Transactions on Mathematics. Vol. 21, pp. 765–769, 2022. 10.37394/23206.2022.21.87
XIV. H. Iswadi, E. T. Baskoro, A. N. M. Salman, R. Simanjuntak. : ‘The resolving graph of amalgamation of cycles’. Utilitas Mathematica. Vol. 83, pp. 121-132, 2010. https://api.semanticscholar.org/CorpusID:55139163
XV. I. M. Batiha, B. Mohamed. : ‘Binary rat swarm optimizer algorithm for computing independent domination metric dimension problem’. Mathematical Models in Engineering. Vol. 10, pp. 6-13, 2024. 10.21595/mme.2024.24037
XVI. I. M. Batiha, B. Mohamed, I. H. Jebril. : ‘Secure metric dimension of new classes of graphs’. Mathematical Models in Engineering. Vol. 10, pp. 1-6, 2024. 10.21595/mme.2024.24168
XVII. I. M. Batiha, J. Oudetallah, A. Ouannas, A. A. Al-Nana, I. H. Jebril. : ‘Tuning the fractional-order PID-Controller for blood glucose level of diabetic patients’. International Journal of Advances in Soft Computing and its Applications. Vol. 13, pp. 1–10, 2021. https://www.i-csrs.org/Volumes/ijasca/2021.2.1.pdf
XVIII. I. M. Batiha, M. Amin, B. Mohamed, H. I. Jebril. : ‘Connected metric dimension of the class of ladder graphs’. Mathematical Models in Engineering. Vol. 10, pp. 65–74, 2024. 10.21595/mme.2024.23934
XIX. I. M. Batiha, N. Anakira, A. Hashim, B. Mohamed. : ‘A special graph for the connected metric dimension of graphs’. Mathematical Models in Engineering. Vol. 10, pp. 1-8, 2024. 10.21595/mme.2024.24176
XX. I. M. Batiha, S. A. Njadat, R. M. Batyha, A. Zraiqat, A. Dababneh, S. Momani. : ‘Design fractional-order PID controllers for single-joint robot ARM model’. International Journal of Advances in Soft Computing and its Applications. Vol. 14, pp. 97–114, 2022. 10.15849/IJASCA.220720.07
XXI. K. B. Murthy. : ‘The end equitable domination of dragon and some related graphs’. Journal of Computer and Mathematical sciences. Vol. 7, pp. 160-167, 2016.
XXII. L. Susilowati, I. Sa’adah, R. Z. Fauziyyah, A. Erfanian. : ‘The dominant metric dimension of graphs’. Heliyon. Vol. 6, 03633, 2020. 10.1016/j.heliyon.2020.e03633
XXIII. P. Sumathi, A. Rathi, A. Mahalakshmi. : ‘Quotient labeling of corona of ladder graphs’. International Journal of Innovative Research in Applied Sciences and Engineering. Vol. 1, pp. 1-12, 2017. 10.29027/IJIRASE.v1.i3.2017.80-85
XXIV. R. Alfarisi, Dafik, A. Kristiana. : ‘Resolving domination number of graphs’. Discrete Mathematics, Algorithms and Applications. Vol. 11, 1950071, 2019. 10.1142/S179383091950071X
XXV. R. C. Brigham, G. Chartrand, R. D. Dutton, P. Zhang. : ‘Resolving domination in graphs’. Mathematica Bohemica. Vol. 128, pp. 25-36, 2003. 10.21136/MB.2003.133935
XXVI. S. Kurniawati, D. A. R. Wardani, E. R. Albirri. : ‘On resolving domination number of friendship graph and its operation’. Journal of Physics. Vol. 1465, 012019, 2020. 10.1088/1742-6596/1465/1/012019
XXVII. R. P. Adirasari, H. Suprajitno, L. Susilowati. : ‘The dominant metric dimension of corona product graphs’. Baghdad Science Journal. Vol. 18, 0349, 2021. https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/5039
XXVIII. T. Mazidah, Dafik, Slamin, I. H. Agustin, R. Nisviasari. : ‘Resolving independent domination number of some special graphs’. Journal of Physics. Vol. 1832, 012022, 2021. 10.1088/1742-6596/1832/1/012022

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Journal Vol – 19 No – 9, September 2024

ANALYZING THE IMPACT OF CONSTRUCTION DELAYS ON DISPUTES IN INDIA: A STATISTICAL AND MACHINE LEARNING APPROACH

Authors:

Pramodini Sahu, Dillip Kumar Bera, Pravat Kumar Parhi

DOI NO:

https://doi.org/10.26782/jmcms.2024.09.00004

September 12, 2024

Abstract:

In Major construction projects execution and performance were being negatively impacted by claims and disputes in terms of cost overrun, quality, stakeholders relationships, and productivity. Therefore understanding the significance of underlying the claims is essential. In this study, the primary root causes behind delay claims and disputes in construction projects were identified, examined, and rated. The significance of these factors was assessed using Relative Importance Index (RII) values. In addition, a machine learning model employing the Random Forest Genetic Algorithm (RFGA) was implemented to foresee the related risks and ascertain their levels. In a pilot survey, the data were collected across multiple construction projects at different phases such as scrutiny stage, design and planning stage, bidding stage, operation stage, and maintenance or after-construction stage. From Relative Important Index values from the statistical approach, it emerges that delay claims are generally causes from the owner followed by project-specific activities. Delays in processing bill payments, natural disasters, lack of contract awareness, and delay in final bill payment are the top causes of delay claims which converted to conflicts and disputes in mostly operating stage. The Random Forest Genetic Algorithm model predicted that factors like altering the original design, reluctance to cooperate by contractor, and increase of wages have lower risk whereas factors Poor site conditions, delay in approvals of schedules and change orders, natural calamities, late in running bill payment, repetition of work due to error in original work are at higher risk in terms of conflict and dispute. The model gives an accuracy of 0.89 and 0.87 for training data and testing data. The study will highlight possible research avenues and enhance project management strategies so that the project succeeds its goal.

Keywords:

Relative Important Index,Construction Delay claims,RFGA,Risk prediction,conflict and dispute,

Refference:

I. Al-Mohsin, Mohammed. “Claim analysis of construction projects in Oman.” Int. J. Adv. Sci. Eng. Inf. Technol 2 (2012): 73-78. DOI: 10.18517/ijaseit.2.2.182
II. Apte, Bhagyashree, and Sudhanshu Pathak. “Review of types and causes of construction claims.” International Journal of Research in Civil Engineering, Architecture and Design 4.2 (2016): 43-50. https://www.ijres.org/papers/Volume-10/Issue-4/Ser-9/F10042732.pdf
III. Gündüz, Murat, Yasemin Nielsen, and Mustafa Özdemir. “Quantification of delay factors using the relative importance index method for construction projects in Turkey.” Journal of management in engineering 29.2 (2013): 133-139. 10.1061/(ASCE)ME.1943-5479.0000129
IV. Horta, I. M., et al. “Performance trends in the construction industry worldwide: an overview of the turn of the century.” Journal of productivity analysis 39 (2013): 89-99. DOI 10.1007/s11123-012-0276-0
V. Kometa, Simon T., Paul O. Olomolaiye, and Frank C. Harris. “Attributes of UK construction clients influencing project consultants’ performance.” Construction Management and economics 12.5 (1994): 433-443. 10.1080/01446199400000053
VI. Sahu, Pramodini, D. K. Bera, and P. K. Parhi. “Gradation of the Relative Significance of the Claims Obtained from Construction Industry.” Recent Developments in Sustainable Infrastructure (ICRDSI-2020)—Structure and Construction Management: Conference Proceedings from ICRDSI-2020 Volume 1. Singapore: Springer Nature Singapore, 2022. 10.1007/978-981-16-8433-3_11
VII. Sambasivan, Murali, and Yau Wen Soon. “Causes and effects of delays in Malaysian construction industry.” International Journal of project management 25.5 (2007): 517-526. 10.1016/j.ijproman.2006.11.007
VIII. Tariq, Junaid, and S. Shujaa Safdar Gardezi. “Study the delays and conflicts for construction projects and their mutual relationship: A review.” Ain Shams Engineering Journal 14.1 (2023): 101815. DOI: 10.1016/j.asej.2023.101815. 10.1016/j.asej.2022.101815
IX. Yaseen, Zaher Mundher, et al. “Prediction of risk delay in construction projects using a hybrid artificial intelligence model.” Sustainability 12.4 (2020): 1514. 10.3390/su12041514
X. Zaneldin, Essam K. “Construction claims in United Arab Emirates: Types, causes, and frequency.” International journal of project management 24.5 (2006): 453-459. 10.1016/j.ijproman.2006.02.006
XI. Zhang, YuXiang, et al. “How does experience with delay shape managers’ making-do decision: Random forest approach.” Journal of Management in Engineering 36.4 (2020): 04020030. 10.1061/(ASCE)ME.1943-5479.0000776

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Journal Vol – 19 No – 9, September 2024

THE PERFORMANCE ANALYSIS OF PRECODED SPACE-TIME FREQUENCY MIMO-GFDM OVER RAYLEIGH FADING CHANNELS

Authors:

R. Anil Kumar, Adireddy Ramesh, Sarala Patchala, U. Sreenivasulu, R. Prakash Kumar

DOI NO:

https://doi.org/10.26782/jmcms.2024.09.00005

September 12, 2024

Abstract:

The physical layer is implemented in the present communication era with new multicarrier modulation schemes such as Generalized Frequency Division Multiplexing with Multi-Input and Multi-Output (MIMO-GFDM) antenna systems to achieve good spectral efficiency and diversity order. This paper presents precoded Space-Time-Frequency MIMO-GFDM performance analysis to improve the bit error rate performance without increasing transmission power and bandwidth compared to conventional techniques. The proposed system also enhances the diversity order over frequency selective fading channels. In general, we need to perform channel matrix inversion operations at the receiver or channel precoding matrix operations at the transmitter to detect the symbols of MIMO-GFDM systems. This paper's proposed scheme completes the same task without performing channel matrix inversion. Orthogonal transform techniques such as Haar, Harley, Walsh-Hadamard, and Slant transforms are used as precoders at the transmitter for the proposed scheme. The simulation results are validated on the MATLAB working platform. We have compared the bit error rate of the PSTF-MIMO-GFDM system with Space-Time (ST) and Space Frequency (SF) as baseline schemes and different orthogonal transform precoding techniques.

Keywords:

MIMO,GFDM,ST,SF,PSTF,

Refference:

I. Alves, Bruno M., et al. “Performance of GFDM over Frequency-Selective Channels.” Proceedings of the International Workshop on Telecommunication 2013.
https://inatel.br/docentes/documents/dayan/Publications/61.pdf
II. Abass, Eman S., Hesham M. El-Badawy, and Hadia M. El-Hennawy. “On the Design of Quasi-Orthogonal Space-Time-Frequency Block Code over MIMO OFDM Channel.” 2011 7th International Conference on Wireless Communications, Networking and Mobile Computing. IEEE, 2011. https://ieeexplore.ieee.org/abstract/document/6040106
III. Bolcskei, Helmut, and Arogyaswami J. Paulraj. “Space-Frequency Coded Broadband OFDM Systems.” 2000 IEEE Wireless Communications and Networking Conference. Conference Record (Cat. No. 00TH8540). Vol. 1. IEEE, 2000. https://ieeexplore.ieee.org/abstract/document/904589
IV. Deepthi, Pasupuleti Sai, et al. “Review of 5G Communications over OFDM and GFDM.” ICCCE 2020: Proceedings of the 3rd International Conference on Communications and Cyber Physical Engineering. Springer Singapore, 2021. https://link.springer.com/chapter/10.1007/978-981-15-7961-5_81
V. Debnath, Sourav, Samin Ahmed, and SM Shamsul Alam. “Performance Comparison of OFDM, FBMC, and UFMC for Identifying the Optimal Solution for 5G Communications.” International Journal of Wireless and Microwave Technologies 13.5 (2023): 1-10. https://www.mecs-press.org/ijwmt/ijwmt-v13-n5/IJWMT-V13-N5-1.pdf
VI. Falkowski, Bogdan J., and Shixing Yan. “Matrix Decomposition and Butterfly Diagrams for Mutual Relations between Hadamard-Haar and Arithmetic Spectra.” IEEE Transactions on Circuits and Systems I: Regular Papers 53.5 (2006): 1119-1129. https://ieeexplore.ieee.org/abstract/document/1629250
VII. Fettweis, Gerhard, Marco Krondorf, and Steffen Bittner. “GFDM—Generalized Frequency Division Multiplexing.” VTC Spring 2009—IEEE 69th Vehicular Technology Conference. IEEE, 2009. https://ieeexplore.ieee.org/abstract/document/5073571
VIII. Kumar, R. Anil, and Kodati Satya Prasad. “Comparative Analysis of OFDM, FBMC, UFMC & GFDM for 5G Wireless Communications.” International Journal of Advanced Science and Technology 29.5 (2020): 2097-2108. http://sersc.org/journals/index.php/IJAST/article/view/10903
IX. Kumar, R. Anil, and K. Satya Prasad. “Performance Analysis of GFDM Modulation in Heterogeneous Network for 5G NR.” Wireless Personal Communications 116.3 (2021): 2299-2319. https://link.springer.com/article/10.1007/s11277-020-07791-4
X. Lee, King F., and Douglas B. Williams. “A Space-Time Coded Transmitter Diversity Technique for Frequency Selective Fading Channels.” Proceedings of the 2000 IEEE Sensor Array and Multichannel Signal Processing Workshop. SAM 2000 (Cat. No. 00EX410). IEEE, 2000. https://ieeexplore.ieee.org/abstract/document/877987
XI. Lin, Yuan-Pei, and See-May Phoong. “BER Minimized OFDM Systems with Channel Independent Precoders.” IEEE Transactions on Signal Processing 51.9 (2003): 2369-2380.
https://ieeexplore.ieee.org/abstract/document/1223548
XII. Mahender, Kommabatla, Tipparti Anil Kumar, and K. S. Ramesh. “Simple Transmit Diversity Techniques for Wireless Communications.” Smart Innovations in Communication and Computational Sciences: Proceedings of ICSICCS 2017, Volume 1. Springer Singapore, 2019. https://link.springer.com/chapter/10.1007/978-981-10-8968-8_28
XIII. Matthe, Maximilian, et al. “Widely Linear Estimation for Space-Time-Coded GFDM in Low-Latency Applications.” IEEE Transactions on Communications 63.11 (2015): 4501-4509. https://ieeexplore.ieee.org/abstract/document/7194753
XIV. Matthé, Maximilian, Luciano Leonel Mendes, and Gerhard Fettweis. “Generalized Frequency Division Multiplexing in a Gabor Transform Setting.” IEEE Communications Letters 18.8 (2014): 1379-1382. https://ieeexplore.ieee.org/abstract/document/6853349
XV. Ramakrishnan, Balamurali, et al. “Analysis of FBMC Waveform for 5G Network Based Smart Hospitals.” Applied Sciences 11.19 (2021): 8895. https://www.mdpi.com/2076-3417/11/19/8895
XVI. Rani, P. Naga, and Ch Santhi Rani. “UFMC: The 5G Modulation Technique.” 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC). IEEE, 2016. https://ieeexplore.ieee.org/abstract/document/7919714
XVII. Rohling, Hermann, ed. OFDM: Concepts for Future Communication Systems. Springer Science & Business Media, 2011. https://link.springer.com/book/10.1007/978-3-642-17496-4
XVIII. Suto, Kenji, and Tomoaki Ohtsuki. “Performance Evaluation of Space-Time-Frequency Block Codes over Frequency Selective Fading Channels.” Proceedings IEEE 56th Vehicular Technology Conference. Vol. 3. IEEE, 2002. https://ieeexplore.ieee.org/abstract/document/1040459
XIX. Thepade, Sudeep D., and Smita S. Chavan. “Cosine Walsh and Slant Wavelet Transforms for Robust Image Steganography.” 2013 Tenth International Conference on Wireless and Optical Communications Networks (WOCN). IEEE, 2013. https://ieeexplore.ieee.org/abstract/document/6616220
XX. Vijay, et al. “Intertwine Connection‐Based Routing Path Selection for Data Transmission in Mobile Cellular Networks and Wireless Sensor Networks.” Wireless Communications and Mobile Computing 2022.1 (2022): 8398128. https://onlinelibrary.wiley.com/doi/full/10.1155/2022/8398128
XXI. Wu, Jinsong, Honggang Hu, and Murat Uysal. “High-Rate Distributed Space-Time-Frequency Coding for Wireless Cooperative Networks.” IEEE Transactions on Wireless Communications 10.2 (2010): 614-625. https://ieeexplore.ieee.org/abstract/document/5669241
XXII. Yeh, Hen-Geul. “Design Precoded Space-Time-Frequency 4×1 and 4×2 OFDM Architectures in Frequency-Selective Fading Channels.” IEEE Systems Journal 14.1 (2019): 277-287. https://ieeexplore.ieee.org/abstract/document/8744548

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Journal Vol – 19 No – 9, September 2024

YOLO V3 AND CCN FOR THE TRACKING AND CLASSIFICATION OF AERIAL OBJECT AND DRONES

Authors:

Zainab Mohanad Issa, Layla H. Abood, Dalal Abdulmohsin, Basim Galeb, Aqeel Al-Hilali

DOI NO:

https://doi.org/10.26782/jmcms.2024.09.00006

September 12, 2024

Abstract:

The goal of this study is to give headways in aeronautical article ID that will help with making recognitions that are both more exact and more precise. Specifically, we revamp the meaning of the article recognition anchor enclose request to remember turns for expansion to level and width, and besides, we make it conceivable to have erratic four corner point structures. Furthermore, the consideration of new anchor boxes gives the model additional adaptability to address protests that are focused at a pivot of turn that gives a 45-degree point. By accomplishing these results, we can make an organization that considers negligible tradeoffs about speed and unwavering quality, while likewise giving more exact restrictions. The latest ways to deal with PC vision and article acknowledgment are for the most part dependent on brain organizations and different advances that utilize profound learning. This powerful field of study is utilized in various applications, including military and observation, aeronautical photography, independent driving, and airborne perception. To precisely locate the location of an item, contemporary object identification techniques make use of bounding boxes that are drawn over the object and have a rectangular form (horizontal and vertical). These orthogonal bounding boxes do not consider the posture of the object, which leads to a decrease in the amount of object localization and restricts subsequent tasks such as object comprehension and tracking. We have used the DOTA dataset to present all of the results, demonstrating the value of flexible object boundaries, particularly with rotated and non-rectangular objects. We have also achieved an accuracy of 98.47% for the detection and classification of aerial objects, with forty percent of the data being used for training and the remaining twenty percent being used for testing. There was a minimum of 2.8 seconds of processing time required for the whole program to be executed to categorize all of the aerial items that were parked on the base.

Keywords:

Aerial Imaging,Aeronautical Article ID,CNN,Classification,DOTA,YOLO,

Refference:

I. Ahmad, M., Khan, A. M., Mazzara, M., Distefano, S., Ali, M., & Sarfraz, M. S. (2020). A fast and compact 3-D CNN for hyperspectral image classification. IEEE Geoscience and Remote Sensing Letters, 19, 1-5.
II. Audebert, N.; Le Saux, B.; Lefèvre, S. Beyond RGB: Very High Resolution Urban Remote Sensing with Multimodal Deep Networks. ISPRS J. Photogramm. Remote Sens. 2018, 140, 20–32.
III. Audebert, N., Le Saux, B., & Lefèvre, S. (2019). Deep learning for classification of hyperspectral data: A comparative review. IEEE geoscience and remote sensing magazine, 7(2), 159-173.
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V. Ben Hamida, A.; Benoit, A.; Lambert, P.; Ben Amar, C. 3-D Deep Learning Approach for Remote Sensing Image Classification. IEEE Trans. Geosci. Remote Sens. 2018, 56, 4420–4434.
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Journal Vol – 19 No – 9, September 2024

EFFICIENT CUSTOMER SERVICE AND OPERATION MAINTENANCE BY INVENTORY MANAGEMENT

Authors:

Nilesh Kumar, Quazzafi Rabbani, Nurul Azeez Khan

DOI NO:

https://doi.org/10.26782/jmcms.2024.09.00007

September 12, 2024

Abstract:

Effective customer service and operational excellence are critical components of corporate success, particularly in today's changing business world. This paper examines the crucial role that inventory management plays in controlling and improving customer service and operational efficiency in businesses. Companies that efficiently manage inventory levels may ensure the timely fulfillment of client orders, minimize stockpiles, and increase efficiency. Furthermore, efficient inventory management contributes to boosting operating efficiency, lowering logistical costs, and increasing profitability. This study extensively reviews the literature and case studies to explore the best strategies utilized in inventory management to attain these objectives. It also investigates the influence of inventory management on performance and offers useful insights for companies looking to use inventory management as a strategic strategy to gain a sustained competitive advantage.

Keywords:

Customer Service,Customer Satisfaction,Operational Efficiency,Inventory Management,

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Journal Vol – 19 No – 9, September 2024