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DESIGN AND ANALYSIS OF INTRUSION DETECTION SYSTEM USING MACHINE LEARNING IN SMART HEALTHCARE SYSTEM

Authors:

K. S. Yamuna, M. Sugumaran, A. Arthi , R. Premkumar

DOI NO:

https://doi.org/10.26782/jmcms.2024.07.00002

July 7, 2024

Abstract:

The integration of the Internet of Things (IoT) in medical applications into healthcare applications has enabled the remote monitoring of patients' information, facilitating timely diagnostics as required. The technology of the Internet of Medical Things (IoMT) empowers doctors to treat patients through real-time monitoring and remote diagnostics. Nevertheless, implementing high-security features that ensure the accuracy and confidentiality of patients' data poses a substantial challenge. IoMT devices have limited processing power and memory, making it impossible to build security technology on them. Methodology: So the proposed work formulates a machine learning-based topology to construct an efficient and precise intrusion detection system using network traffic and patient data. Findings: In this topology, modified Whale optimization topology has been implemented for feature selection, and the intrusion is detected using two ML algorithms namely, Random Forest and SVM. Hence, the proposed method surpasses the current state-of-the-art, achieving an accuracy rate of 99.82%.

Keywords:

Intrusion Detection System (IDS),Network Attacks,SVM,Random Forest (RF),Modified Whale Optimization Algorithm (MWOA),

Refference:

I. Awotunde Joseph Bamidele et al., : ‘A deep learning-based intrusion detection technique for a secured IoMT system’. International Conference on Informatics and Intelligent Applications. Cham: Springer International Publishing, 2021. 10.1007/978-3-030-95630-1_4
II. Binbusayyis Adel et al., : ‘An investigation and comparison of machine learning approaches for intrusion detection in IoMT network’. The Journal of Supercomputing. Vol. 78(15), pp. 17403-17422, 2022. 10.1007/s11227-022-04568-3
III. Ghubaish Ali et al., : ‘Recent advances in the internet-of-medical-things (IoMT) systems security’. IEEE Internet of Things Journal. Vol. 8(11), pp. 8707-8718, 2020. 10.1109/JIOT.2020.3045653
IV. Gupta Karan et al., : ‘A tree classifier based network intrusion detection model for Internet of Medical Things’. Computers and Electrical Engineering. Vol. 102, 108158, 2022. 10.1016/j.compeleceng.2022.108158
V. Hady Anar A. et al., : ‘Intrusion detection system for healthcare systems using medical and network data: A comparison study’. IEEE Access. Vol. 8, pp. 106576-106584, 2020. 10.1109/ACCESS.2020.3000421
VI. Khan Soneila, and Adnan Akhunzada. : ‘A hybrid DL-driven intelligent SDN-enabled malware detection framework for Internet of Medical Things (IoMT)’. Computer Communications. Vol. 170, pp. 209-216, 2021. 10.1016/j.comcom.2021.01.013
VII. Kumar P., Gupta G. P. and Tripathi R., : ‘An ensemble learning and fog-cloud architecture-driven cyber-attack detection framework for IoMT networks’. Computer Communications. Vol. 166, pp.110-124, 2021. 10.1016/j.comcom.2020.12.003
VIII. Malamas Vangelis et al., : ‘Risk assessment methodologies for the internet of medical things: A survey and comparative appraisal’. IEEE Access. Vol. 9, pp. 40049-40075, 2021. 10.1109/ACCESS.2021.3064682
IX. Manimurugan S., et al., : ‘Effective attack detection in internet of medical things smart environment using a deep belief neural network’. IEEE Access. Vol. 8, pp. 77396-77404, 2020. 10.1109/ACCESS.2020.2986013
X. Nandy S., Adhikari M., Khan, M. A., Menon V.G. and Verma S., : ‘An intrusion detection mechanism for secured IoMT framework based on swarm-neural network’. IEEE Journal of Biomedical and Health Informatics. Vol. 26(5), pp.1969-1976, 2021. 10.1109/JBHI.2021.3101686
XI. Radoglou-Grammatikis, Panagiotis et al., : ‘A self-learning approach for detecting intrusions in healthcare systems’. ICC 2021-IEEE International Conference on Communications. IEEE, 2021. 10.1109/ICC42927.2021.9500354
XII. Ravi Vinayakumar et al., : ‘A Multi-View attention-based deep learning framework for malware detection in smart healthcare systems’. Computer Communications. Vol. 195, pp. 73-81, 2022. 10.1016/j.comcom.2022.08.015
XIII. Rbah Yahya et al., : ‘Machine learning and deep learning methods for intrusion detection systems in iomt: A survey’. 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET). IEEE, 2022. 10.1109/IRASET52964.2022.9738218
XIV. Saheed Y. K. and Arowolo M. O., : ‘Efficient cyber attack detection on the internet of medical things-smart environment based on deep recurrent neural network and machine learning algorithms’. IEEE Access. Vol. 9, pp.161546-161554, 2021. 10.1109/ACCESS.2021.3128837
XV. Unal Devrim, Shada Bennbaia, and Ferhat Ozgur Catak. : ‘Machine learning for the security of healthcare systems based on Internet of Things and edge computing’. Cybersecurity and Cognitive Science. Academic Press, 2022. Pp. 299-320. 10.1016/B978-0-323-90570-1.00007-3

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Journal Vol – 19 No – 7, July 2024

OPTIMAL INVENTORY DECISIONS FOR DETERIORATING ITEMS WITH ALL-UNITS DISCOUNT UNDER FUZZY ENVIRONMENT

Authors:

Dharti Arvadiya, Ajay S. Gor

DOI NO:

https://doi.org/10.26782/jmcms.2024.07.00003

July 7, 2024

Abstract:

The proposed inventory model has been developed for deteriorating items subject to all-unit discount in a fuzzy environment. Considering demand as price dependent, holding cost depends on time, and purchase cost depends on order size. The inventory parameters, such as ordering cost, holding cost, and demand rate, are all represented as triangular fuzzy numbers to capture the uncertainty in the system. The objective of the model is to determine the optimal time length, selling price, and order quantity to maximize the total profit function. Numerical examples are carried out to validate the models. Sensitivity analysis is performed to check the effect of fuzzy parameters on profit function and decision variables to get further insights. Results stated that a fuzzy model works better than a crisp model, and an all-units discount policy helps in maximizing a retailer's profit. It allows for flexibility and adaptability, leading to a potential increase in revenue.

Keywords:

Deterioration,All-units discount,Graded mean integration method,Price dependent demand,Time dependent holding cost,Triangular fuzzy number,

Refference:

I. Alfares H. K., & Ghaithan A. M., : ‘Inventory and pricing model with price-dependent demand, time-varying holding cost, and quantity discounts’. Computers and Industrial Engineering. Vol. 94, pp. 170–177, 2016. 10.1016/j.cie.2016.02.009
II. Bellman R. E., & Zadeh L. A., : ‘Decision-Making in a Fuzzy Environment’. Management Science. Vol. 17(4), pp. 141–164, 1970. 10.1142/9789812819789_0004
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IV. Chen S. H., : ‘Operations on fuzzy numbers with function principle’. Tamkang Journal of Management Sciences. Vol. 6(1), pp. 13–25, 1986.
V. Chen S. H. & Hsieh C. H., : ‘Optimization of fuzzy backorder inventory models’. IEEE International Fuzzy System Conference (Seoul, Korea) Proceedings. Vol. 1, pp. 470–480, 1999. 10.1109/ICSMC.1999.815564
VI. Chen S. H. & Hsieh C. H., : ‘Representation, ranking, distance, and similarity of L-R type fuzzy number and application’. Australian Journal of Intelligent Information Processing Systems. Vol. 6(4), pp. 217–229, 2000.
VII. Dubois D., & Prade H., : ‘Fuzzy Sets and Systems: Theory and Applications’. Academic Press. NY, pp. 71-73, 1980.
VIII. Garai T., Chakraborty D., & Roy T. K., : ‘Fully fuzzy inventory model with price-dependent demand and time varying holding cost under fuzzy decision variables’. Journal of Intelligent and Fuzzy Systems. Vol. 36(4), pp. 3725–3738, 2019. 10.3233/JIFS-18379
IX. Huang T. S., Yang M. F., Chao Y. S., Yan Kei, E. S., & Chung, W. H., : ‘Fuzzy supply chain integrated inventory model with quantity discounts and unreliable process in uncertain environments’. Lecture Notes in Engineering and Computer Science. Vol. 2, pp. 14–19, 2018.
X. Indrajitsingha S. K., : ‘A fuzzy inventory model for linear deteriorating items with selling price dependent demand and allowable shortages under partially backlogged condition’. International Journal of Procurement Management. Vol. 12(4), pp. 457–474, 2019. 10.1504/IJPM.2019.101245
XI. Jaggi C. K., Pareek S., Sharma A., & hi N., : ‘Fuzzy Inventory Model for Deteriorating Items with Time-varying Demand and Shortages’. American Journal of Operational Research. Vol. 2(6), pp. 81–92, 2012. 10.5923/j.ajor.20120206.01
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XIII. Khan M. A. A., Ahmed S., Babu M. S., & Sultana, N., : ‘Optimal lot-size decision for deteriorating items with price-sensitive demand, linearly time-dependent holding cost under all-units discount environment’. International Journal of Systems Science: Operations and Logistics. Vol. 9(1), pp. 61–74, 2022. 10.1080/23302674.2020.1815892
XIV. Kristiyani I. M., & Daryanto Y., : ‘An Inventory Model Considering All Unit Discount and Carbon Emissions’. International Journal of Industrial Engineering and Engineering Management. Vol. 1(2), pp. 43–50, 2019. 10.24002/ijieem.v1i2.3410
XV. Kumar N., & Kumar S., : ‘An inventory model for deteriorating items with partial backlogging using linear demand in fuzzy environment’. Cogent Business and Management. Vol. 4(1), pp. 1307687, 2017. 10.1080/23311975.2017.1307687
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XVII. Maragatham M., & Lakshmidevi P. K., : ‘A Fuzzy Inventory Model for Deteriorating Items with Price Dependent Demand’. International Journal of Fuzzy Mathematical Archive. Vol. 5(1), pp. 39-47, 2014.
XVIII. Rani N., & Kumar V., : ‘An Fuzzy Inventory Model for Decaying Items with a Demand-Dependent Selling Price as a Degree n Polynomial, Linear Deterioration Rate, and Constant Holding Cost’. International Journal of Engineering Research and Technology (IJERT), Vol. 10(10), pp. 42–46, 2021.
XIX. Roy A., : ‘Fuzzy inventory model for deteriorating items with price dependent demand’. International Journal of Management Science and Engineering Management. Vol. 10(4), pp. 237–241, 2015. 10.1080/17509653.2014.959086
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XXIV. Shah N. H., & Soni H., : ‘Continuous review inventory model for fuzzy price dependent demand’. International Journal of Modelling in Operations Management. Vol. 1(3), pp. 209–222, (]2011. 10.1504/ijmom.2011.039527
XXV. Shaikh A. A., Bhunia A. K., Cárdenas-Barrón L. E., Sahoo L., & Tiwari S., : ‘A Fuzzy Inventory Model for a Deteriorating Item with Variable Demand, Permissible Delay in Payments and Partial Backlogging with Shortage Follows Inventory (SFI) Policy’. International Journal of Fuzzy Systems. Vol. 20(5), pp. 1606–1623, 2018. 10.1007/s40815-018-0466-7
XXVI. Shaikh A. A., Khan M. A.-A., Panda G. C., & Konstantaras I., : ‘Price discount facility in an EOQ model for deteriorating items with stock-dependent demand and partial backlogging’. International Transactions in Operational Research. Vol. 26(4), pp. 1365–1395, 2019. 10.1111/itor.12632
XXVII. Shaikh T. S., & Gite S. P., : ‘Fuzzy Inventory Model with Variable Production and Selling Price Dependent Demand under Inflation for Deteriorating Items’. American Journal of Operations Research. Vol. 12(6), pp. 233–249, 2022. 10.4236/ajor.2022.126013
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Journal Vol – 19 No – 7, July 2024

ESTABLISHING EQUATIONS FOR CALCULATING THE CHANGE OF LOWER YIELD POINT DEPENDING ON THE TIME OF CORROSION EFFECT

Authors:

Antonio Shopov

DOI NO:

https://doi.org/10.26782/jmcms.2024.07.00004

July 7, 2024

Abstract:

In this paper, equations are established to predict how the values of the lower yield point in the stress-strain curve depending on a time of corrosion influence will change. Although this point is of theoretical importance in the theory of strength of materials, its change in corroded steel is of practical importance, since this point determines according to the theory which minimum load or stress is required to maintain the plastic behavior of material. A well-founded mathematical principle was used to process experimentally obtained data in two main directions - the stochastic method and the average method. Diagrams of the variation of values in corroded steel were drawn up and equations of the 9th degree were established using polynomial approximation.

Keywords:

Corrosion,Equations,Establishing,Lower Yield Point,Time,

Refference:

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III. A. Shopov and B. Bonev. : ‘Ascertainment of the change of the ductility in corroded steel specimens by experiment’. International Journal of Civil Engineering and Technology. Vol. 10(1), pp. 1551-1560, 2019. https://iaeme.com/MasterAdmin/Journal_uploads/IJCIET/VOLUME_10_ISSUE_1/IJCIET_10_01_142.pdf
IV. A. Shopov and B. Bonev. : ‘Experimental study of the change of the strengthening zone on corroded steel specimens’. International Journal of Civil Engineering and Technology. Vol.10(1), pp. 2285-2293, 2019. https://iaeme.com/MasterAdmin/Journal_uploads/IJCIET/VOLUME_10_ISSUE_1/IJCIET_10_01_206.pdf
V. A. Shopov and B. Bonev. : ‘Study by experimental of the zone of fracture on S355JR steel specimens with corrosion’. International Journal of Civil Engineering and Technology. Vol. 10(2), pp.751-760, 2019. Study by experimental of the zone of fracture on S355JR steel specimens with corrosion
VI. A. Shopov and B. Bonev. : ‘Experimental study of the zone of yield strength on corroded construction steel specimens for reuse’. MATEC Web of Conferences. Vol. 279 (02009), 2019. 10.1051/matecconf/201927902009
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Journal Vol – 19 No – 7, July 2024

A COMPREHENSIVE REVIEW ON LOW POWER FIXED WIDTH DIGITAL MULTIPLIER ARCHITECTURES

Authors:

Biswarup Mukherjee

DOI NO:

https://doi.org/10.26782/jmcms.2024.07.00005

July 7, 2024

Abstract:

In contemporary portable electronic devices featuring real-time DSP chips, a pivotal challenge lies in minimizing power consumption. The efficiency of these DSP chips is directly impacted by the substantial power dissipation of their multiplier sub-circuits. Consequently, numerous architectures emphasizing low-power consumption, high-speed operation, and compact layout structures for multiplier units have emerged in the literature over recent decades. This manuscript offers insights into select state-of-the-art fixed-width multiplier architectures tailored for low-power operation, presenting a detailed comparative analysis in terms of power consumption, area utilization, and processing delay. Notable among the fixed-width multiplier architectures are the serial, array, Vedic, Booth, Wallace-tree, and Modified Booth-Wallace designs. For operations involving larger operands, the Modified Booth-Wallace architecture is favored due to its reduced latency. This study concentrates on a comprehensive examination and evaluation of various low-power fixed-width multiplier architectures, highlighting diverse operand sizes. Simulation-based assessments utilizing the 45nm PTM model indicate that the Modified Booth-Wallace tree architecture achieves a 73% reduction in latency compared to a basic array multiplier. Moreover, CMOS-based designs demonstrate superior noise margin performance compared to GDI and CCGDI techniques. Notably, the dynamic voltage-controlled CCGDI-based architecture showcases a 60% enhancement in Power-Delay Product (PDP) compared to the conventional CMOS-based Modified Booth-Wallace multiplier architecture. The manuscript's novelty lies in its succinct overview of the latest multiplier architectures implemented at the 45nm technology node, specifically tailored for low-power DSP chips.

Keywords:

Booth Algorithm,GDI,Low power VLSI,Multiplier,Wallace Tree architecture,

Refference:

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III. B. Mukherjee, A Ghosal. : ‘Design and Analysis of a Low Power High Performance GDI Based Radix 4 Multiplier Using Modified Booth Wallace Algorithm’. IEEE Electron Device Kolkata Conference (2018 IEEE EDKCON), 2018. 10.1109/EDKCON.2018.8770494
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XXXII. X. Zhang, F. Boussaid and A. Bermak. : ‘32 Bit X 32 Bit Multiprecision Razor-Based Dynamic Voltage Scaling Multiplier With Operands Scheduler’. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. Vol. 22(4), pp. 759-770, 2014. 10.1109/TVLSI.2013.2252032
XXXII. Z. Huang and M. D. Ercegovac. : ‘High-performance low-power left to right array multiplier design’. IEEE Trans. Computers. Vol. 54(2), pp. 272–283, 2005. 10.1109/TC.2005.51

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Journal Vol – 19 No – 7, July 2024

SOME FIXED POINT PROPOSITIONS FOR NON-SELF FUNCTIONS IN METRICALLY CONVEX SPACES

Authors:

S. Savitha, P. Thirunavukarasu

DOI NO:

https://doi.org/10.26782/jmcms.2024.07.00006

July 7, 2024

Abstract:

This intriguing article delves deep into the concept of non-self-plottings within the intricate realm of metrically curved planetary systems, meticulously analyzing and dissecting various fixed point propositions that govern these celestial bodies. Within the confines of this chapter, we embark on a journey to explore and elucidate Assad's groundbreaking discovery, delving into its complexities and implications to present a more elaborate and all-encompassing single-valued plotting. This development not only serves as a noteworthy extension of Assad's work but also emerges as a significant and groundbreaking generalization of Chatterjea's fundamental primary proposition, shedding new light on the dynamics of planetary motion and positioning in the vast expanse of the universe.

Keywords:

Convex space,Fixed point proposition,Metrically convex planetary,Non-self-mappings,Single valued plotting,

Refference:

I. Chaira Karim, Mustapha Kabil, and Abdessamad Kamouss. : ‘Fixed Point Results for C‐Contractive Mappings in Generalized Metric Spaces with a Graph’. Journal of Function Spaces 2021.1 (2021), 8840347. 10.1155/2021/8840347
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IV. Assad Nadim, and William Kirk. : ‘Fixed point theorems for set-valued mappings of contractive type’. Pacific Journal of Mathematics. Vol.43(3), pp. 553-562, 1972. 10.2140/pjm.1972.43.553
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VI. Chatterjea, S. K., : ‘Fixed point theorems’. C.R. Acad. Bulgare Sc. Vol. 25(18), pp. 727-730, 1972.
VII. Chang T. H., : ‘Common fixed point theorems for multi-valued mappings’. Math. Japon. Vol. 41, pp. 311-320, 1995.
VIII. Chouhan Sarla, and Bhumi Desai. : ‘Fixed-Point Theory and Its Some Real-Life Applications’. Mathematics and Computer Science Vol. 16, pp. 119-125, 2022. 10.9734/bpi/rhmcs/v1/3160C
IX. Ćirić L., & Ume J., : ‘Some common fixed point theorems for weakly compatible mappings’. Journal of Mathematical Analysis and Applications. Vol. 314(2), pp. 488-499, 2006. 10.1016/j.jmaa.2005.04.007
X. Fallahi Kamal, and Aris Aghanians. : ‘Fixed points for Chatterjea contractions on a metric space with a graph’. International Journal of Nonlinear Analysis and Applications. Vol. 7(2) pp. 49-58, 2016. 10.22075/ijnaa.2016.449
XI. Gairola U. C., and Ram Krishan. : ‘A Fixed Point Theorem for Generalized-Weak Hybrid Contraction’. Jñ–an–abha. (2017): 107.https://www.vijnanaparishadofindia.org/jnanabha
XII. Gautam Pragati et al., : ‘On Nonunique Fixed Point Theorems via Interpolative Chatterjea Type Suzuki Contraction in Quasi‐Partial b‐Metric Space’. Journal of Mathematics. 2022.1 (2022): 2347294.
XIII. Hadzic O. and Gajic Lj. : ‘Coincidence points for set-valued mappings in convex metric spaces’. Fac. Ser. Mat. Vol. 16(1) pp. 13, 1986.
XIV. Imdad M., and S. Kumar. : ‘Rhoades-type fixed-point theorems for a pair of nonself mappings’. Computers & Mathematics with Applications. Vol. 46(5-6), pp. 919-927, 2003.10.1016/S0898-1221(03)90153-2
XV. Itoh, S., : ‘Multivalued generalized contractions and fixed point theorems’. Comm. Math. Univ. Caroline. Vol. 18(2), pp. 247-258, 1977. http://dml.cz/dmlcz/105770
XVI. Khan M. S., : ‘Common fixed point theorems for multivalued mappings’. Pacific J. Math. Vol. 95(2), pp. 337-347, 1981.
XVII. Khan Ladlay. : ‘Non-Self Mappings and their Fixed Points in Convex Metric Spaces’. Diss. Aligarh Muslim University, Aligarh. India, 2002. 10.1515/gmj.2000.523
XVIII. Kir M., Dutta H., Ansari A. H., Kumam P., : ‘A Weak Contractive Condition and Some Fixed Point Theorems. In: Castillo, O., Jana, D., Giri, D., Ahmed, A. (eds) Recent Advances in Intelligent Information Systems and Applied Mathematics. ICITAM 2019. Studies in Computational Intelligence. Vol. 863. Springer,Cham. 10.1007/978-3-030-34152-7_63
XIX. Klim D., and D. Wardowski. : ‘Fixed point theorems for set-valued contractions in complete metric spaces’. Journal of Mathematical Analysis and Applications. Vol. 334(1), pp. 132-139, 2007.10.1016/j.jmaa.2006.12.012
XX. Kumar Santosh, and David Aron. : ‘Common fixed-point theorems for non-linear non-self contractive mappings in convex metric spaces’. Topological Algebra and its Applications. Vol. 11(1), 20220122, 2023. 10.1515/taa-2022-0122.
XXI. Masmali Ibtisam, and Saleh Omran. : ‘Chatterjea and Ciri C-Type Fixed-Point Theorems Using (α− ψ) Contraction on C*-Algebra-Valued MetriSpace’. Mathematics. Vol. 10(9), pp. 615, 2022.10.3390/math10091615
XXII. Markin J. T., : ‘A fixed point theorems for set-valued mappings’. Bull. Amer. Math. Soc. Vol. 74, pp. 639-642, 1968.https://community.ams.org/journals/bull/1968-74-04/S0002-9904-1968-11971-8/S0002-9904-1968-11971-8.pdf
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XXIV. Özavşar Muttalip. : ‘Fixed Point Theorems for $(k, l) $-Almost Contractions in Cone Metric Spaces over Banach Algebras’. Mathematical Advances in Pure and Applied Sciences Vol. 1(1), pp. 46-51, 2018. https://dergipark.org.tr/en/pub/mapas/issue/37031/366581#article_cite
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XXVII. Park S. A., : ‘Unified Fixed Point Theory in Generalized Convex Spaces’. Acta Math Sinica. Vol. 23, pp. 1509–1526, 2007. 10.1007/s10114-007-0947-3
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XXX. Shukla Satish, and Rosana Rodríguez-López. : ‘Fixed points of multi-valued relation-theoretic contractions in metric spaces and application’. Quaestiones Mathematicae. Vol. 43(3), pp. 409-424, 2020. 10.2989/16073606.2019.1578293
XXXI. Tong-Huei C. H. A. N. G. : ‘Common fixed point theorems for
multivalued mappings’. Mathematica japonicae. Vol. 41(2), pp. 311-320, 1995.
https://cir.nii.ac.jp/crid/1573105974540679808

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Journal Vol – 19 No – 7, July 2024

RC FRAME RESISTANCE TO PROGRESSIVE COLLAPSE CONSIDERING CRACK OPENING EFFECTS

Authors:

Sergei Y. Savin, Le Vo Phu Toan, Manonkhodja Sharipov

DOI NO:

https://doi.org/10.26782/jmcms.2024.07.00007

July 7, 2024

Abstract:

In this paper, an approach is developed to account for the effect of discrete cracks on the response of reinforced concrete building frames under a column failure scenario. The approach implies the introduction of traditional finite element models of discrete ties that take into account the relationship between moments and rotations, considering the specifics of the performance of materials, sections, and structures under conditions of redistribution of forces as a result of initial local failure in the structural system of a building. Validation of the proposed approach is performed on the experimental data. Also, it is compared with the modeling results of the existing approaches. The effect of discrete cracking on the deformed state of reinforced concrete building frames under the scenario of column failure is established. The discrete cracks practically did not affect the values of axial forces in the elements. However, for bending moments within the proposed method, a decrease was observed in comparison with the traditional approach. The analysis of the diagrams shows that for reinforced concrete frames with 3 and 5 stories, there is an excess of tensile axial forces in the beam over the values according to the traditional calculation method.

Keywords:

Crack,Failure,Frame,Finite Element Method,Modelling,Moment,Reinforced Concrete,Rotation,

Refference:

I. Adam, J. M., Parisi, F., Sagaseta, J., Lu, X., : ‘Research and practice on progressive collapse and robustness of building structures in the 21st century’. Engineering Structures. Vol. 173, pp. 122-149, 2018. 10.1016/j.engstruct.2018.06.082.
II. Adam J.M., Buitrago M., Bertolesi E., Sagaseta J., Moragues J. J., : ‘Dynamic performance of a real-scale reinforced concrete building test under a corner-column failure scenario’. Engineering Structures. Vol. 210, pp. 1-14, 2020.
III. Alanani, M., Ehab, M., Salem, H., : ‘Progressive Collapse Assessment of Precast Prestressed Reinforced Concrete Beams Using Applied Element Method’. Case Studies in Construction Materials. Vol. 13, e00457, 2020. 10.1016/j.cscm.2020.e00457.
IV. Almusallam, T., Al-Salloum, Y., Elsanadedy, H., Tuan, N., Mendis, P., Abbas, H., : ‘Development limitations of compressive arch and catenary actions in reinforced concrete special moment resisting frames under column-loss scenarios’. Structure and Infrastructure Engineering. Vol. 16(12), pp. 1616-1634, 2020. 10.1080/15732479.2020.1719166.
V. Almazov V. O., Plotnikov A. I., : ‘Rastorguyev B.S. Problems of buildings resistance to progressive collapse’. Vestnik MGSU. Vol. 2(1), pp. 16–20, 2011.
VI. Belostotsky, A. M., & Pavlov, A. S., : ‘Long span buildings analysis under physical, geometric and structural nonlinearities consideration’. Int. J. Comput. Civ. Struct. Eng. Vol. 6(1), pp. 80, 2010.
VII. Bondarenko V.M., Kolchunov V.I., : ‘Calculation models evaluating reinforced concrete force resistance’. Moscow: Publishing ASV. 2004.
VIII. Caredda, G., Makoond, N., Buitrago, M., Sagaseta, J., Chryssanthopoulos, M., & Adam, J. M., : ‘Learning from the progressive collapse of buildings’. Developments in the built environment. Vol. 15, pp. 100194, 2023. 10.1016/j.dibe.2023.100194.
IX. Geniyev G. A., : ‘Dynamic effects in rod systems made of physical non-linear brittle materials’. Promyshlennoe i grazhdanskoe stroitel’stvo. Vol. 9, pp. 23–24, 1999.
X. Grunwald, C., Khalil, A. A., Schaufelberger, B., Ricciardi, E.M., Pellecchia, C., De Iuliis, E., Riedel, W., : ‘Reliability of Collapse Simulation – Comparing Finite and Applied Element Method at Different Levels’. Eng Struct. Vol. 176, pp. 265–278, 2018. 10.1016/j.engstruct.2018.08.068.
XI. Kaklauskas, G., Sokolov, A., Sakalauskas, K., : ‘Strain Compliance Crack Model for RC Beams: Primary versus Secondary Cracks’. Engineering Structures. Vol. 281, pp. 115770, 2023. 10.1016/j.engstruct.2023.115770.
XII. Kodysh E.N., Mamin A.N., : ‘Discrete-connection model for determining the stress-strain state of plane structures. News of higher educational institutions’. Construction. Vol. 540(12), pp.13–20, 2003.
XIII. Kokot, S., Solomos, G., : ‘Progressive collapse risk analysis: literature survey, relevant construction standards and guidelines’. Ispra: Joint Research Centre, European Commission. 2012.
XIV. Kolchunov, V. I., Dem’yanov, A. I., : ‘The Modeling Method of Discrete Cracks in Reinforced Concrete under the Torsion with Bending’. Magazine of Civil Engineering. Vol. 81, pp. 160–173, 2018. 10.18720/MCE.81.16.
XV. Kolchunov, V. I., Dem’Yanov, A. I., ‘The modeling method of discrete cracks and rigidity in reinforced concrete’. Magazine of Civil Engineering. Vol. 4 (88), pp. 60-69, 2019. 10.18720/MCE.81.16.
XVI. Mkrtychev, O.V., : ‘Развитие Прямых Нелинейных Динамических Методов Расчета На Сейсмические Воздействия’. Промышленное и гражданское строительство. Pp. 12–16, 2022.
XVII. Niki, V., Erkmen, R. E., : ‘Shear Deformable Hybrid Finite Element Formulation for Buckling Analysis of Composite Columns’. Canadian Journal of Civil Engineering. Vol. 45, pp. 279–288, 2018. 10.1139/cjce-2017-0159.
XVIII. Pearson, C., Delatte, N., : ‘Ronan point apartment tower collapse and its effect on building codes’. Journal of Performance of Constructed Facilities. Vol. 19(2), pp. 172-177, 2005, 10.1061/(asce)0887-3828(2005)19:2(172).
XIX. Savin S. Y., Fedorova N.V., Kolchunov V. I., : ‘Dynamic forces in the eccentrically compressed members of reinforced concrete frames under accidental impacts’. International Journal for Computational Civil and Structural Engineering. Vol. 18(4), pp. 111–123, 2022.
XX. Savin, S., Kolchunov, V., Fedorova, N., Tuyen Vu, N., : ‘Experimental and Numerical Investigations of RC Frame Stability Failure under a Corner Column Removal Scenario’. Buildings. Vol. 13, pp. 908, 2023. 10.3390/buildings13040908.
XXI. SP 20.13330. Loads and actions. Revised version of SNiP 2.01.07-85. Standardinform, Moscow, Russia, 2016.
XXII. SP 385.1325800. Protection of buildings and structures against progressive collapse. Design code. Basic statements. Standardinform, Moscow, Russia, 2018.
XXIII. SP 63.13330. Concrete and reinforced concrete structures. General provisions. SNiP 52-01-2003. Standardinform, Moscow, Russia, 2018.
XXIV. Tagel-Din H., Rahman N.A., : ‘Simulation of the Alfred P. Murrah federal building collapse due to blast loads’. Building Integration Solutions. Vol. 32, pp. 1-15, 2006. 10.1061/40798(190)32.
XXV. Tagel-Din, H., Meguro, K., : ‘Nonlinear simulation of RC structures using applied element method’. Doboku Gakkai Ronbunshu. Vol. 654, 13-24, 2000. doi:10.1016/j.cscm.2020.e00457.
XXVI. Yu, J., Tan, K.H., : ‘Analytical Model for the Capacity of Compressive Arch Action of Reinforced Concrete Sub-Assemblages’. Magazine of Concrete Research. Vol. 66, pp. 109–126, 2014. 10.1680/macr.13.00217.

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Journal Vol – 19 No – 7, July 2024

FLOW THROUGH STEAM TURBINE CASCADE FOR ROUGHNESS ANALYSIS

Authors:

Manjunath K., Ajeet Singh Sikarwar, Naushad Ahmad Ansari

DOI NO:

https://doi.org/10.26782/jmcms.2024.07.00008

July 7, 2024

Abstract:

The flow of liquids is essential to our understanding of the world. Traditionally, this is done by studying the flow of liquids using wind tunnels in the model. However, the field of computer fluid dynamics has been born over the past century. A program that can model fluid flow is CFD software. Gambit 2.4.6 created a three-dimensional geometry of four reaction blades with a square cascade and studied the secondary losses using FLUENT 6.2. The air is chosen as a working material. Air passes through the turbine cascade at a maximum input speed of 102 m/s. The cascade opens to the atmosphere when exiting. Firstly, the two surfaces of the blade cascade have been smoothed and the secondary losses analyzed. This total flow loss was compared with a roughness applied individually to the suction and pressure surfaces of 250 microns, 750 microns, and 1000 microns in thickness and examined the effect of the thickness on flow loss.

Keywords:

Blade surface,Effect of roughness,End loss phenomena,Loss Coefficient,Turbine steam path,

Refference:

I. A. A. Adeniyi, A. Mohammed and S. O. Emmanuel. : ‘CFD Modelling of Wakes on Cascade Compressor Blades’. International Journal of Advances in Science and Technology. Vol. 4(2), pp. 60-67, 2012.
II. A. D. Scillitoe, P. G. Tucker and P. Adami. : ‘Large eddy simulation of boundary layer transition mechanisms in a gas-turbine compressor cascade’. Journal of Turbomachinery. Vol. 141(6), pp. 61-68, 2019. 10.1115/1.4042023
III. A. K. Saha and S. Acharya. : ‘Computations of turbulent flow and heat transfer through a three-dimensional nonaxisymmetric blade passage’. ASME Journal of Turbo-machinery. Vol. 130(3), pp. 1008-1018, 2008. 10.1115/1.2776952
IV. ANSYS Fluent Meshing User’s Guide. (2015).
V. A. Peyvan, and A. H. Benisi. : ‘Axial-Flow Compressor Performance Prediction in Design and Off-Design Conditions through 1-D and 3-D Modeling and Experimental Study’. Journal of Applied Fluid Mechanics. Vol. 9(5), pp. 2149-2160, 2016. 10.18869/acadpub.jafm.68.236.25222
VI. D. Baumgärtner, J. J. Otter and A. P Wheeler. : ‘The effect of isentropic exponent on transonic turbine performance’. Journal of Turbomachinery. Vol. 142(8), pp. 81-87, 2020. 10.1115/1.4046528
VII. FLUENT, 2005. FLUENT 6.2 Users Guide. Lebanon, USA.
VIII. H. R. Singh and S. R. Kale. : ‘A numerical study of the effect of roughness on the turbine blade cascade performance’. Progress in Computational Fluid Dynamics. Vol. 8(7), pp. 439-46, 2008. 10.1504/PCFD.2008.021320
IX. J. Li, J. Teng, M. Ferlauto, M. Zhu and X. Qiang. : ‘An improved stall prediction model for axial compressor stage based on diffuser analogy’. Aerospace Science and Technology. Vol. 127, 2022. 10.1016/j.ast.2022.107692
X. J. Y. Moon and K. S. Yong. : ‘Counter-rotating stream-wise vortex formation in the turbine cascade with end wall fencing’. Int. J. Computers and Fluids. Vol. 30(4), pp. 473-490, 2001. 10.1016/S0045-7930(00)00026-8
XI. M. J. Brear, H. P. Hodson, P. Gonzalez and N. W. Harvey. : ‘Pressure surface separations in low-pressure turbines—Part 2: Interactions with the secondary flow’. Int. J. Turbomach. Vol.124(3), pp. 402-409, 2002. 10.1115/1.1450765
XII. M. Majcher, M. Frant and R. Kieszek. : ‘Preliminary Numerical Study of a Rectilinear Blade Cascade Flow for a Determination of Aerodynamic Characteristics. International Review of Aerospace Engineering (I.RE.AS.E), Vol. 16(4), pp. 143-151, 2023. 10.15866/irease.v16i4.24065
XIII. M. Mesbah., V. G. Gribin and K. Souri. : ‘Investigation of the effects of main geometric parameters and flow characteristics on secondary flow losses in a turbine cascade’. Journal of Physics: Conference Series. Vol. 3, pp. 21-31, 2021. 10.1088/1742-6596/2131/3/032081
XIV. M. N. Goodhand. : ‘Laminar flow compressor blades’. 9th Osborne Reynolds Colloquium and Research Student Award, Department of Aeronautics Imperial College London, 2011.
XV. P. K. Zachos, N. Grech, B. Charnley, V. Pachidis and R. Singh. : ‘Experimental and numerical investigation of a compressor cascade at highly negative incidence’. : ‘Engineering Applications of Computational Fluid Mechanics. Vol. 5(1), pp. 26-36, 2011. 10.1080/19942060.2011.11015350
XVI. R. Azim, M. M. Hasan and M. Ali. : ‘Numerical investigation on the delay of boundary layer separation by suction for NACA 4412’. Procedia Engineering. Vol. 105, pp. 329-334, 2015. 10.1016/j.proeng.2015.05.013
XVII. Samsher. : ‘Effects of localized roughness over reaction and impulse blades on loss coefficient’. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy. Vol. 221(1), pp. 21-32, 2007. 10.1243/09576509JPE214
XVIII. T. Bai, J. Liu, W. Zhang, and Z. Zou. : ‘Effect of surface roughness on the aerodynamic performance of turbine blade cascade’. Propulsion and Power Research. Vol. 3(2), pp. 82-89, 2014. 10.1016/j.jppr.2014.05.001
XIX. T. Sonoda, M. Hasenjäger, T. Arima and B. Sendhoff. : ‘Effect of end wall contouring on performance of ultra-low aspect ratio transonic turbine inlet guide vanes’. ASME Journal of Turbomachinery. Vol. 131(1), pp. 11020-11031, 2009. 10.1115/1.2813015
XX. V. K. Singoria and Samsher. : ‘The Study of End Losses in a Three Dimensional Rectilinear Turbine Cascade’. Int. J. of Emerging Technology and Advanced Engineering. Vol. 3(8), pp. 782-797, 2013. https://www.scribd.com/document/389319869/IJETAE-0813-122
XXI. Y. Tang, Y. Liu and L. Lu. : ‘Solidity effect on corner separation and its control in a high-speed low aspect ratio compressor cascade’. Int. J. of Mechanical Sciences. Vol. 142, pp. 304-325, 2018. 10.1016/j.ijmecsci.2018.04.048
XXII. Zhang, Y. Wu, Y. Li, and H. Lu. : ‘Experimental investigation on a high subsonic compressor cascade flow’. Chinese Journal of Aeronautics. Vol. 28(4), pp. 1034-1043, 2015. 10.1016/j.cja.2015.06.019

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Journal Vol – 19 No – 7, July 2024

BEHAVIOR ANALYSIS OF A REPAIRABLE 2-OUT-OF-4 SYSTEM USING EVOLUTIONARY ALGORITHM

Authors:

Shakuntla Singla, Shilpa Rani, Diksha Mangla

DOI NO:

https://doi.org/10.26782/jmcms.2024.07.00009

July 7, 2024

Abstract:

This research paper explores the behavior analysis of a repairable 2-out-of-4 system utilizing an evolutionary algorithm approach. The 2-out-of-4 system configuration is a critical setup widely employed in various engineering applications, necessitating thorough understanding and optimization for reliability and performance enhancement. By integrating evolutionary algorithms with system analysis, this paper aims to optimize system parameters, such as redundancy allocation and maintenance scheduling, to improve reliability and availability. The proposed methodology offers a novel approach to address the challenges associated with the complex behavior of repairable 2-out-of-4 systems, providing insights for system designers and engineers.

Keywords:

Behavior Analysis,Evolutionary Algorithm,Maintenance Scheduling Reliability Optimization,Repairable 2-out-of-4system,

Refference:

I. Kumar A., : ‘Reliability And Sensitivity Analysis Of Linear Consecutiv2-Out-Of-4: F System’. European Journal of Molecular & Clinical Medicine. Vol. 7(7), pp. 3791-3804, 2020. https://www.researchgate.net/publication/349179413_Reliability_And_Sensitivity_Analysis_Of_Linear_Consecutive_2-Out-Of-4_F_System
II. Kumar A., Garg D., Goel P., : ‘Mathematical Modelling and Behavioural Analysis of a Washing Unit in Paper Mill’. International Journal of System Assurance Engineering and Management, Vol.10, pp: 1639-1645, 2019. 10.1007/s13198-019-00916-4
III. Kumari S., Khurana P., Singla S., : ‘Behaviour and profit analysis of a thresher plant under steady state’. International Journal of System Assurance Engineering and Management. Vol. 13, pp: 166-171, 2022. 10.1007/s13198-021-01183-y
IV. Kumari S., Singla S., Khurana P., : ‘Partical swarm optimization for constrained cost reliability of rubber plant Life Cycle’. Reliability and Safety Engineering. Vol.11(3), pp: 273-277, 2022. 10.1007/s41872-022-00199-y
V. Malik S., Verma S., Gupta A., Sharma G., Singla S., : ‘Performability evaluation, validation and optimization for the steam generation system of a coal-fired thermal power plant’. Methods X, Vol. 9, 101852, 2022. doi.org/10.1016/j.mex.2022.101852
VI. Naithani A., Parashar B., Bhatia P. K., Taneja G., : ‘Cost benefit analysis of a 2-out-of-3 induced draft fans system with priority for operation to cold standby over working at reduced capacity’. Advanced Modelling and Optimization. Vol. 15(2), pp: 499-509, 2013. https://camo.ici.ro/journal/vol15/v15b23.pdf
VII. Singla. S., Dhawan. P., : ‘Mathematical analysis of regenerative point graphical technique (RPGT)’. Mathematical Analysis and its Contemporary Applications. Vol.4(4), pp:49-56, 2022. 10.30495/maca.2022.1964808.1062
VIII. Singla. S., Mangla. D., Panwar. P., Taj. S. Z .,: ‘Reliability optimization of a degraded system preventive maintenance using Genetic algorithm’. Journal of Mechanics of Continua and Mathematics Science. Vol.19(1), pp. 1-14, 2024. 10.26782/jmcms.2024.01.00001
IX. Singla. S., Rani. S., Modibbo. M. U., Ali. I., : ‘Optimization of system parameters of 2:3 Good serial system using deep learing’. Reliability Theory and Application. Vol. 18(4), pp. 670-679, 2023. 10.24412/1932-2321-2023-476-670-679
X. Singla. S., Rani. S., : ‘Performance optimization of 3:4: Good system’. International Conference on Intelligent Control and Instrumentation IEEE 979-8-3503-4383.

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Journal Vol – 19 No – 7, July 2024

EXPERIMENTAL STUDIES OF WELDED JOINTS OF PRECAST BUILDINGS FOR SHEAR AND TORSION

Authors:

Valery Lyublinskiy, Vladislav Struchkov

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00001

August 15, 2024

Abstract:

The spatial rigidity and strength of precast multi-story buildings are largely determined by the rigidity of the shear bonds connecting the vertical load-bearing reinforced concrete structures. When a horizontal load is applied in asymmetrical in-plan load-bearing systems of multi-story buildings, torsion occurs. In vertical shear bonds, especially those located furthest from the center of rigidity, a torque appears. This article presents the results of experimental studies of welded joints of precast buildings under the action of shear and torsion. The research study has been conducted using full-scale samples of shear bonds. The samples have been loaded with a static load vertical shear force and horizontal torsion moment. Various loading conditions are considered. Deformation diagrams of shear bonds were obtained. The limit state of a welded joint under shear and shear with torsion is described. The obtained experimental data on the rigidity of shear connections can be used in mathematical models for determining the stress-strain state of load-bearing systems of panel multi-story buildings.

Keywords:

Welded joints,Shear bonds,Torsion,Panel buildings,Stress-strain state,

Refference:

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IV. Botis M., Cerbu С. A., : ‘Method for Reducing of the Overall Torsion for Reinforced Concrete Multi-Storey Irregular Structures’. Applied Sciences. Vol. 10, 5555, 2020. 10.3390/app10165555
V. De Stefano M., Pintucchi B., :‘A review of research on seismic behaviour of irregular building structures since 2002’. Bull Earthquake Eng. Vol. 6, pp. 285–308, 2008. 0.1007/s10518-007-9052-3
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VIII. Karyakin A.A., Derbentsev I.S., Tarasov M.V., : ‘Experimental and Numerical Research on Tensile Performance of Inter-Panel Fastener Joints of Large-Panel Buildings’. IOP Conf. Ser.: Mater. Sci. Eng. Vol. 262, 2017. 10.1088/1757-899X/262/1/012046
IX. Khatiwada P., Lumantarna E., : ‘Simplified Method of Determining Torsional Stability of the Multi-Storey Reinforced Concrete Buildings’. Civil Eng. Vol. 2, pp. 290–308, 2021. 10.3390/civileng2020016
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Journal Vol – 19 No – 8, August 2024

MULTIPLE ORDER HARMONIC ELIMINATION IN PHOTO VOLTAIC SYSTEM USING SPWM BASED ELEVEN LEVEL CASCADED H-BRIDGE MULTILEVEL INVERTER

Authors:

Supriya Sahu, Bijaya Kumar Mohapatra, Subash Ranjan Kabat, Sampurna Panda, Sunita Pahadasingh, Bibhu Prasad Ganthia

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00002

August 15, 2024

Abstract:

The detailed examination of utilizing renewable energy sources, particularly integrating Photovoltaic (PV) arrays and Multilevel Inverters (MLI), is thorough and underscores the importance of addressing environmental issues linked to fossil fuels. The selection of Sinusoidal Pulse Width Modulation (SPWM) and its benefits, such as low switching losses and high efficiency, are well-articulated. The simulation results showing sinusoidal waveforms for resistive loads and the focus on reducing Total Harmonic Distortion (THD) using an LC filter further highlight the commitment to achieving high-quality power output. THD reduction is crucial for maintaining the stability and reliability of power systems. The incorporation of a seven-level MLI adds complexity and sophistication to the system, potentially allowing for more precise control over the output waveform and enhancing the overall performance of the renewable energy system. The consideration of factors like efficiency, reliability, and grid compatibility aligns with best practices in the design and implementation of renewable energy systems. Your approach clearly aligns with the broader industry trend towards cleaner and more sustainable energy solutions. Overall, the strategic and effective use of renewable energy, SPWM for control, addressing THD through an LC filter, and incorporating an eleven-level MLI showcases multi-order harmonic elimination for maximum power generation as presented in this paper.

Keywords:

Multilevel inverter (MLI),photovoltaic (PV),total harmonic distortion (THD),solar,sinusoidal pulse width modulation (SPWM),

Refference:

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II. Barick, C. K., Mohapatra, B. K., Kabat, S. R., Jena, K., Ganthia, B. P., & Panigrahi, C. K. (2022, October). Review on Scenario of Wind Power Generation and Control. In 2022 1st IEEE International Conference on Industrial Electronics: Developments & Applications (ICIDeA) (pp. 12-17). IEEE.
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VII. Ganthia, Bibhu Prasad, Subrat Kumar Barik, and Byamakesh Nayak. “Transient analysis of grid integrated stator voltage oriented controlled type-III DFIGdriven wind turbine energy system.” Journal of Mechanics of Continua and Mathematical Sciences 15.6 (2020): 139-157.
VIII. Ganthia, B. P., & Upadhyaya, M. “Bridgeless AC/DC Converter & DC-DC Based Power Factor Correction with Reduced Total Harmonic Distortion.” Design Engineering, pp. 2012-2018, 2021.
IX. Ganthia, B. P., Pradhan, R., Das, S., & Ganthia, S. “Analytical study of MPPT based PV system using fuzzy logic controller.” In 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), pp. 3266-3269, IEEE, 2017.
X. Ganthia, Bibhu Prasad, and B. M. Praveen. “Review on Scenario of Wind Power Generations in India.” Electrical Engineering 13, no. 2 (2023): 1-27p.
XI. Ganthia, Bibhu Prasad, and B. M. Praveen. “Design and Harmonic Elimination of sinusoidal pulse width modulation (SPWM) Based Five Level Cascaded H-Bridge Multilevel Inverter for Photovoltaic System for Educational Purposes.” Indonesian Journal of Teaching in Science 3, no. 2: 143-160.
XII. Ganthia, B. P., Sahu, P. K., & Mohanty, A. “Minimization Of Total Harmonic Distortion Using Pulse Width Modulation Technique.” IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-ISSN, 2278-1676.
XIII. Ganthia, B. P., Monalisa Mohanty, Sushree Shataroopa Mohapatra, Rosalin Pradhan, Subhasmita Satapathy, Shilpa Patra, & Sunita Pahadasingh. “Artificial Neural Network Optimized Load Forecasting of Smartgrid using MATLAB.” Control Systems and Optimization Letters [Online], vol. 1, no. 1, pp. 46-51, 2023.
XIV. Gonzalez, R., Gubia, E., Lopez, J., & Marroyo, L. “Transformerless single-phase multilevel-based photovoltaic inverter.” IEEE Transactions on Industrial Electronics, vol. 55, no. 7, pp. 2694–2702, 2008.
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Journal Vol – 19 No – 8, August 2024

DATA HIDING ON DIGITAL IMAGES USING DEEP NEURAL NETWORK (DNN)

Authors:

Bikash Chandra Bag, Hirak Kumar Maity, Chaitali Koley

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00003

August 15, 2024

Abstract:

In this paper, the framework of Data Hiding on Digital Images Using Deep Neural Network (DNN). Here DeepSteg architecture is considered to evaluate the performance of the multiple secret images that can be concatenated to the single cover image, the image data will be hidden on the single cover image using the Tiny ImageNet dataset. The proposed model outperformed earlier results. To compare our results two parameters, normally Secret loss(λs) and cover loss(λc) are considered. Our plan is to use deep neural networks for the encoding and decoding of multiple secret images inside a single cover image of a similar goal.

Keywords:

Deep Neural network,Deep Steganography,Multiple Secret Images,Single Cover Image,Tiny ImageNet dataset,

Refference:

I. Baluja, S. Hiding images in plain sight: Deep steganography. In Guyon, I., Luxburg, U. V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., and Garnett, R. (eds.), Advances in Neural Information Processing Systems 30, pp. 2069–2079. Curran Associates, Inc., 2017.

II. Bikash Chandra Bag, Hirak Kumar Maity , Chaitali Koley. : ‘UNET MOBILENETV2: MEDICAL IMAGE SEGMENTATION USING DEEP NEURAL NETWORK (DNN)’. J. Mech. Cont. & Math. Sci., Vol.-18(1), pp 21-29, 2023. 10.26782/jmcms.2023.01.00002

III. Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L. ImageNet: A Large-Scale Hierarchical Image Database. In CVPR09, 2009.

IV. Hayes, J. and Danezis, G. Generating steganographic images via adversarial training. In NIPS, 2017.

V. Ingham, F. Deepsteg: Implementation of hidding images in plain sight: Deep steganography in pytorch.

VI. Kreuk, F., Adi, Y., Raj, B., Singh, R., and Keshet, J. Hide and speak: Deep neural networks for speech steganography, 2019.

VII. Muzio, A. Deep-steg: Implementation of hidding images in plain sight: Deep steganography in keras.

VIII. Zhu, J., Kaplan, R., Johnson, J., and Fei-Fei, L. Hidden: Hiding data with deep networks. CoRR, abs/1807.09937, 2018.

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Journal Vol – 19 No – 8, August 2024

PERFORMANCE EVALUATION OF HANDOVER TECHNIQUES IN VEHICULAR NETWORKS

Authors:

Rafid Najm Abdullah Alsaadi

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00004

August 15, 2024

Abstract:

The VANET customized vehicle network's versatility, cost-effectiveness, accurate sensing, and potential to open up new and exciting remote sensing applications make it an intriguing subject of study. VANET, short for Vehicular Ad Hoc Network, is a network designed to build an automobile network for a specific purpose. VANETs are being developed as reliable networks used by automobiles to prevent road accidents and ensure passenger safety. They also allow automobiles to communicate, sending emergency alerts and entertainment updates on highways and in cities. VANET is a mobile network that predicts and assists drivers and others in life-threatening and road safety-related circumstances. Despite their many benefits, these networks face many challenges due to their nature. Random movement patterns and high-speed mobility change network structure, resulting in frequent deliveries. This issue is especially important in dedicated vehicle networks, which we will discuss here. This article investigates the possibility of transitioning from VANET to the incorporation of LTE, SDN, and ultimately 5G to establish performance.

Keywords:

Automobile network,Remote Sensing Applications,Road Accidents Vehicular Ad Hoc Network,

Refference:

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XLV. N. Taherkhani and S. Pierre, “Centralized and Localized Data Congestion Control Strategy for Vehicular Ad Hoc Networks Using a Machine Learning Clustering Algorithm,” IEEE Trans. Intell. Transp. Syst., vol. 17, no. 11, pp. 3275–3285, 2016.
XLVI. PATHRE, A. AGRAWAL, CH. and GAIN, A. ‗‗A Novel Defense Scheme against DDoS Attack in VANET‘‘ Tenth International Conference of Wireless and Optical Communications Networks (WOCN), , IEEE 2013.
XLVII. Piran, M. Murthy, G and Babu, G. ―VEHICULAR AD HOC AND SENSOR NETWORKS; PRINCIPLES AND CHALLENGES‖. International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.2, No.2, June 2011,38-49.
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Journal Vol – 19 No – 8, August 2024

EXTENSION OF SOME INTEGRAL TRANSFORM BY THE METHOD OF MULTIPLE INTEGRALS

Authors:

Dilip Kumar Jaiswal, D. S. Singh, Yashawant Jaiswal

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00005

August 15, 2024

Abstract:

Extension of some Integral Transform by the Method of Multiple Integrals by Lebesgue measurable and Lebesgue integrable.

Keywords:

Fourier transform,Inverse Fourier transform,Lebesgue measurable,

Refference:

I. AL-Qmari S. K. Q. (2020), Estimation of a modified integral associated with a special function kernel of fox’s h-function type, Commun. Korean Math. Soc. , No. 1, pp. 125–136.
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V. Gupta K.(2011), A Study of modified H-transform and generalized fractional integral operator of weyl type, International Journal of Pure and Applied Sciences and Technology, 7(1) (2011), pp. 59-67, ISSN 2229-6107.
VI. Gupta K. and Vandana Agrawal (2010) ,A Theorem Connecting the H-Transform and Fractional Integral Operators Involving the Multivariable H-Function, Tamsui Oxford Journal of Mathematical Sciences, Aletheia University, 26(4) , 383-395.
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XI. Watugala G. K.(1998), Sumudu transform- a new integral transform to solve differential equations and control engineering problems. Math. Engr. Indust., 6(4): 319-329.

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Journal Vol – 19 No – 8, August 2024

SOME FEATURES OF FUZZY SOFT α-T1 TOPOLOGICAL SPACES USING FUZZY SOFT POINTS

Authors:

Ruhul amin, Sumaiya Khatun Sumi, Hannan Miah

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00006

August 15, 2024

Abstract:

In this paper, we give new four notions of fuzzy soft α -T_1 topological space using the fuzzy soft points concept. We have discussed some implications and theorems, along with their proofs. Moreover, we have presented the hereditary, productive, and projective properties with proof. Finally, we have shown that our given notions are preserved under bijective, fuzzy soft open, and continuous mappings.

Keywords:

Soft set,Fuzzy soft set,Fuzzy soft topological space,Quasi-coincidence,Fuzzy Soft T1 topological spaces,

Refference:

I. Ahmad B., Kharal A. : On Fuzzy Soft Sets, Hindawi Publishing Corporation, Advances in Fuzzy Systems Article ID 586507, 2009.
II. Atmaca A. S., Zorlutuna I : On Fuzzy Soft Topological Spaces, Ann. Fuzzy Math. Inform., 5 (2), pp. 377-386, 2013.
III. Hannan Miah and Ruhul Amin : Some Features of Pairwise α-T_0 Spaces in Supra Fuzzy Bitopology, Journal of Mechanics of Continua and Mathematical Sciences, 15(11), pp. 1-11, 2020.
IV. Kandil A., Tantawy O. A. E., El-Sheikh S. A. and Abd El-latif A. M. : Some fuzzy soft topological properties based on fuzzy semi open soft sets, South Asian J. Math., 4 (4), pp. 154–169, 2014.
V. Kharal A. and Ahmad B.: Mappings on fuzzy soft classes, Hindawi Publishing Corporation, Adv. Fuzzy Syst., 2009.
VI. Mishra S. and Srivastava R. : On T_0 and T_1 Fuzzy Soft Topological Spaces, Ann. Fuzzy Math. Inform., 10 (4), pp. 591-605, 2015.
VII. Molodtsov D. : Soft Set Theory First Results, Comput. Math. Appl., 37 (4-5), pp 19-31, 1999.
VIII. Nazmul S. and Samanta S. K. : Soft Topological Groups, Kochi J. Math., 5, pp. 151-161, 2010.
IX. Pazar Varol B. and Aygun H. : Fuzzy soft topology, Hacettepe Journal of Mathematics and Statistics 41(3), pp. 407-419, 2012.
X. Roy S. and Samanta T. K. : A Note on Fuzzy Soft Topological Spaces, Ann. Fuzzy Math. Inform., 5 (2), pp. 305-311, 2012.
XI. Ruhul Amin and Raihanul Islam : New Concepts on R_1 Fuzzy Soft Topological Spaces, Ann. Fuzzy Math., 22 (2), (October), pp. 123-132, 2021.
XII. Ruhul Amin, Raihanul Islam, Sudipto Kumar Shaha and Saikh Shahjahan Miah : Some properties of T_0 fuzzy soft topological spaces in quasi-coincidence sense, Journal of Mechanics of Continua and Mathematical Sciences, 17(4), pp. 8-20, 2022.
XIII. Shabir M. and Naz M. : On Soft Topological Spaces, Comput. Math. Appl., 61, pp. 1786-1799, 2011.
XIV. Saleh S., Abd El-Latif A. M. and Al-Salemi A. : On Separation Axioms in Fuzzy Soft Topological Spaces, South Asian Journal of Mathematics, 8 (2), pp. 92-109, 2018.
XV. Tanay B. and Kandemir M. B. : Topological Structure of Fuzzy Soft Sets, Computer and Mathematics with Applications, 61, pp. 2952-2957, 2011.
XVI. Varol B. P. and Aygun H. : Fuzzy Soft Topology, Hacettepe Journal of Mathematics and Statistics, 41 (3), pp. 407-419, 2012.
XVII. Zadeh, L. A. : Fuzzy sets. Information and Control , 8, pp. 338-353, 1965.

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Journal Vol – 19 No – 8, August 2024

ROLE OF MATHEMATICS TO BUILD A SUSTAINABLE FUTURE FOR INDUSTRY 5.0

Authors:

Niranjan Bora, Bhargab Jyoti Saikia, Bharati Borgohain, Kaushik Das, Barnali Sharma

DOI NO:

https://doi.org/10.26782/jmcms.2024.08.00007

August 15, 2024

Abstract:

The fourth industrial revolution, in short Industry 4.0 is the next stage in the digitization of the industrial sector and is being driven by disruptive trends including the growth of data and connectivity, analytics, human-machine interaction, and advancements in robotics. For the past ten years, Industry 4.0 consistently addressed both the industry’s strengths and weaknesses. Industry 4.0 is limited by the higher productivity that smart manufacturing systems provide. The new version of Industry 4.0 is termed Industry 5.0 and it refers to the fifth industrial revolution and is an emerging concept that builds on the advancements of Industry 4.0. Thus, industry 5.0 is an extension and further advancement of Industry 4.0, which focuses on automation, connectivity, and data exchange in manufacturing processes. Industry 5.0 introduces a new level of human-machine collaboration and emphasizes the importance of human creativity and skills alongside advanced technologies. This study discusses the opportunities and directions of future mathematical research towards Industry 5.0.

Keywords:

Industry 4.0,Industry 5.0,Artificial Intelligence,Big Data,Cryptography,Machine Learning,Optimization Techniques,Quantum Computing,Robotics,

Refference:

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IX. B. Alojaiman. : ‘Technological Modernizations in the Industry 5.0 Era: A Descriptive Analysis and Future Research Directions’. Processes. Vol. 11(5), 1318, 2023. 10.3390/pr11051318.
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XVI. E. Kaasinen, A. –H. Anttila, P. Heikkilä, J. Laarni, H. Koskinen, A. Väätänen. : ‘Smooth and Resilient Human-Machine Teamwork as an Industry 5.0 Design Challenge’. Sustainability. Vol. 14, 2773, 2022. 10.3390/su14052773.
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XXII. J. Alves, T. M. Lima, P. D. Gaspar. : ‘Is Industry 5.0 a Human-Centred Approach? A Systematic Review’. Processes. Vol. 11(1): 193, 2023. 10.3390/pr11010193.
XXIII. J. Barata, I. Kayser. : ‘Industry 5.0-Past, Present, and Near Future’. Procedia Computer Science. Vol. 219, pp. 778-788, 2023.
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XXXV. M. Ghobakhloo, M. Iranmanesh, M. –L. Tseng, A. Grybauskas, A. Stefanini, A. Amran. : ‘Behind the definition of Industry 5.0: A systematic review of technologies, principles, components, and values’. Journal of Industrial and Production Engineering. Vol. 40(6), pp. 432-447, 2023. 10.1080/21681015.2023.2216701.
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Journal Vol – 19 No – 8, August 2024