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ON DESIGN OF PREDICTIVE MODEL FOR HEART DISEASE

Authors:

Soumyendu Bhattacharjee, Susmita Das, Sangita Roy, Arpita Santra, Anasuya Sarkar, Moumita Pal, Biswarup Neogi

DOI NO:

https://doi.org/10.26782/jmcms.2025.06.00007

June 15, 2025

Abstract:

Because it regularly results in more spending than any other explanation, coronary disease is the leading source of fear and mortality on a global scale. The WHO estimates that 17.9 million people died annually from heart disease in 2016, which accounted for 31% of all deaths. More than 75% of these fatalities occurred in developing and middle-income nations. We create a coronary disease prediction model based on the patient's clinical history to assess whether or not the patient is most likely to develop a coronary illness. We used several artificial intelligence (AI) techniques, such as the critical backslide and KNN, to predict and group patients with cardiovascular sickness. The given coronary illness hypothesis system utilizes clinical reasoning and reduces the cost. We categorize a patient based on 14 medical characteristics or features to determine whether they are likely to develop a heart condition to anticipate this. Three algorithms are used to train these medical features: Random Forest Classifier, KNN, and Logistic Regression.

Keywords:

Predictive Model,Random Forest Classifier,KNN,Logistic Regression,

Refference:

I. Adelstein, E.C., Liu, J., Jain, S., et al. “Clinical outcomes in cardiac resynchronization therapy-defibrillator recipients 80 years of age and older”. Europace. 2016;18(3):420. 10.1093/europace/euv222.
II. Alba, A.C, Braga, J., Gewarges, M., Walter, S.D., Guyatt, G.H., Ross, H.J. “Predictors of mortality in patients with an implantable cardiac defibrillator: a systematic review and meta-analysis.” Can J Cardiol. 2013;29(12):1729–40. 10.1016/j.cjca.2013.09.024.
III. Bernardini, A., Bindini, L., Antonucci E., Berteotti M., Giusti B., Testa S., Palareti G., Poli D., Frasconi, P., Marcucci, R. “Machine learning approach for prediction of outcomes in anticoagulated patients with atrial fibrillation.” Int J Cardiol. 2024;15(407):132088. 10.1016/j.ijcard.2024.132088
IV. Bozkurt, B.; Ahmad, T.; Alexander, K.M.; Bosak, K.; Breathett, K.; Fonarow, G.C.; Heidenreich, P.; Ho, J.E.; Hsich, E.; Ibrahim, N.E.; et al. “Heart failure epidemiology and outcomes statistics: A report of the Heart Failure” Society of America. J. Card. Fail. 2023, 29, 1412–1451. 10.1016/j.cardfail.2023.07.006
V. Behon, A, Merkel, E.D., Schwertner, W.R., et al. “Long-term outcome of cardiac resynchronization therapy patients in the elderly.” Geroscience. 2023;45(4):2289–301. 10.1007/s11357-023-00739-z. Epub 2023 Feb 17.
VI. Cebro-Márquez, M.; Rodríguez-Mañero, M.; Serrano-Cruz, V.; Vilar-Sánchez, M.E.; González-Melchor, L.; García-Seara, J.; Martínez-Sande, J.L.; Aragón- Herrera, A.; Martínez-Monzonís, M.A.; González-Juanatey, J.R.; et al. “Plasma miR-486-5p Expression Is Upregulated in Atrial Fibrillation Patients with Broader Low-Voltage Areas.” Int. J. Mol. Sci. 2023, 24, 15248. 10.3390/ijms242015248
VII. Förster, C.Y.; Künzel, S.R.; Shityakov, S.; Stavrakis, S. Synergistic “Effects of Weight Loss and Catheter Ablation: Can microRNAs Serve as Predictive Biomarkers for the Prevention of Atrial Fibrillation Recurrence?” Int. J. Mol. Sci. 2024, 25, 4689. 10.3390/ijms25094689
VIII. Ghio, S., Freemantle, N., Scelsi, L., et al. Long-term left ventricular reverse remodelling with cardiac resynchronization therapy: results from the CARE-HF trial. Eur J Heart Fail. 2009;11(5):480–8. 10.1093/eurjhf/hfp034. Epub 2009 Mar 14
IX. Lippi, G.; Sanchis-Gomar, F. “Global epidemiology and future trends of heart failure.” AME Med. J. 2020, 5, 15. 10.21037/amj.2020.03.03
X. Lofrumento, F.; Irrera, N.; Licordari, R.; Perfetti, S.; Nasso, E.; Liotta, P.; Isgrò, G.; Garcia-Ruiz, V.; Squadrito, F.; Carerj, S.; et al. “Off-target effects of P2Y12 receptor inhibitors: Focus on early myocardial fibrosis modulation.” Int. J. Mol. Sci. 2023, 24, 17546. 10.3390/ijms242417546
XI. L’Abbate, S.; Nicolini, G.; Marchetti, S.; Forte, G.; Lepore, E.; Unfer, V.; Kusmic, C. “Lithium treatment induces cardiac dysfunction in mice.” Int. J. Mol. Sci. 2023, 24, 15872. 10.3390/ijms242115872
XII. Picchio, V.; Gaetani, R.; Pagano, F.; Derevyanchuk, Y.; Pagliarosi, O.; Floris, E.; Cozzolino, C.; Bernava, G.; Bordin, A.; Rocha, F.; et al. “Early impairment of paracrine and phenotypic features in resident cardiac mesenchymal stromal cells after thoracic radiotherapy.” Int. J. Mol. Sci. 2024, 25, 2873. 10.3390/ijms25052873
XIII. Sunagawa, Y.; Tsukabe, R.; Irokawa, Y.; Funamoto, M.; Suzuki, Y.; Yamada, M.; Shimizu, S.; Katanasaka, Y.; Hamabe-Horiike, T.; Kawase, Y.; et al. Anserine, “A histidine-containing dipeptide, suppresses pressure overload-induced systolic dysfunction by inhibiting histone acetyltransferase activity of p300 in mice.” Int. J. Mol. Sci. 2024, 25, 2344. 10.3390/ijms25042344
XIV. Salvatori, F.; D’Aversa, E.; Serino, M.L.; Singh, A.V.; Secchiero, P.; Zauli, G.; Tisato, V.; “Epigenetic tuning of wall remodelling in the early phase after myocardial infarction: A novel epidrug approach.” Int. J. Mol. Sci. 2023, 24, 13268. 10.3390/ijms241713268
XV. Thorkelsson, A.; Chin, M.T. “Role of the Alpha-B-crystallin protein in cardiomyopathic disease.” Int. J. Mol. Sci. 2024, 25, 2826. 10.3390/ijms25052826
XVI. Zheng, H.; Xu, Y.; Liehn, E.A.; Rusu, M. “Vitamin C as scavenger of reactive oxygen species during healing after myocardial infarction.” Int. J. Mol. Sci. 2024, 25, 3114. 10.3390/ijms25063114
XVII. Zhang,H.; Dhalla, N.S. “The role of pro-inflammatory cytokines in the pathogenesis of cardiovascular disease.” Int. J. Mol. Sci. 2024, 25, 1082. 10.3390/ijms25021082

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Journal Vol – 20 No – 6, June 2025

DESIGN OF AN IMPROVED MODEL FOR CARDIOVASCULAR DISEASE DETECTION USING DEEP CANONICAL CORRELATION ANALYSIS AND BIOINSPIRED OPTIMIZATION

Authors:

Prakash Chandra Sahoo, Binod Kumar Pattanayak, Rajani Kanta Mohanty, Ayasa Kanta Mohanty

DOI NO:

https://doi.org/10.26782/jmcms.2025.06.00008

June 15, 2025

Abstract:

Cardio Vascular Diseases (CVDs) are one of the most prevalent causes of death in the world and require an appropriate early detection method that could satisfactorily integrate diversified patient data available in today's healthcare. Traditional diagnosis is often based on single-modality data, either ECG or imaging, which seldom can unfold the complex and multi-faceted nature of cardiovascular conditions. Moreover, these models have incomplete interpretation and optimization issues, which do not suit their application in a clinical setting. On this, we propose a novel framework for the detection of cardiovascular diseases and presiding analysis through multimodal data fusion, optimized neural networks, and explainable AI techniques. Our approach begins with Deep Canonical Correlation Analysis (DCCA), which fuses multiple modalities of data such as ECG time series, medical imaging, electronic health records, and genetic data into a unified latent representation that represents correlated information across these heterogeneous sources. This will not only enhance the prediction accuracy but also retain modality-specific unique aspects, thus going beyond traditional models. We will go one step beyond this by using a Genetic Algorithm in combination with the Neuro-evolution of Augmenting Topologies for optimization not only for neural network architecture and hyperparameters but also for going into the process. This bioinspired methodology makes dynamic adjustments in the complexity of a model, substantially reducing error rates. To ensure interpretability in our predictions, we will finally integrate Shapley Additive explanations (SHAP) into the multimodal fusion network. SHAP values provide a clear, quantitative measure of the contribution of each feature and modality to the model predictions, most significantly corresponding to a priori known clinical risk factors that offer critical insights for healthcare professionals. Impact: we have more than halved error rates by 15%, reached an Area Under the Curve of 0.92, and demonstrated a very strong correlation with expert-annotated risk scores of r = 0.87 using SHAP values. This framework has set a new standard in the CVD prediction area by putting together cutting-edge AI techniques and practical, interpretable healthcare applications.

Keywords:

Cardiovascular Disease,Correlation Analysis,Deep Canonical Genetic Algorithm,Explainable AI,Multimodal Data Fusion,Scenarios,

Refference:

I. Abdellatif, A., et al. “An Effective Heart Disease Detection and Severity Level Classification Model Using Machine Learning and Hyperparameter Optimization Methods.” IEEE Access, vol. 10, 2022, pp. 79974–79985. 10.1109/ACCESS.2022.3191669.
II. Abrar, S., C. K. Loo, and N. Kubota. “A Multi-Agent Approach for Personalized Hypertension Risk Prediction.” IEEE Access, vol. 9, 2021, 10.1109/ACCESS.2021.3074791.
III. Asma-Ull, H., I. D. Yun, and B. L. Yun. “Regression to Classification: Ordinal Prediction of Calcified Vessels Using Customized ResNet50.” IEEE Access, vol. 11, 2023, pp. 48783–48796. 10.1109/ACCESS.2023.3270562.
IV. Chushig-Muzo, D., et al. “Interpretable Data-Driven Approach Based on Feature Selection Methods and GAN-Based Models for Cardiovascular Risk Prediction in Diabetic Patients.” IEEE Access, vol. 12, 2024, pp. 84292–84305. 10.1109/ACCESS.2024.3412789.
V. Das, S., et al. “Analysis of Cardiac Anomalies by Selection and Extraction of Features Using Machine Learning Methods.” Indian Journal of Computer Science and Engineering, vol. 13, no. 6, 2022. 10.21817/indjcse/2022/v13i6/221306116.
VI. Ghorashi, S., et al. “Leveraging Regression Analysis to Predict Overlapping Symptoms of Cardiovascular Diseases.” IEEE Access, vol. 11, 2023, pp. 60254–60266. 10.1109/ACCESS.2023.3286311.
VII. Ghosh, P., et al. “Efficient Prediction of Cardiovascular Disease Using Machine Learning Algorithms with Relief and LASSO Feature Selection Techniques.” IEEE Access, vol. 9, 2021, pp. 19304–19326. 10.1109/ACCESS.2021.3053759.
VIII. Jha, P. K., et al. “A Fully Analog Autonomous QRS Complex Detection and Low-Complexity Asystole, Extreme Bradycardia, and Tachycardia Classification System.” IEEE Transactions on Instrumentation and Measurement, vol. 71, 2022, Art. no. 4009813, pp. 1–13. 10.1109/TIM.2022.3216392.
IX. Kancharla, P., and S. S. Channappayya. “Completely Blind Quality Assessment of User Generated Video Content.” IEEE Transactions on Image Processing, vol. 31, 2022, pp. 263–274. 10.1109/TIP.2021.3130541.
X. Loizou, C. P., et al. “Association of Intima-Media Texture with Prevalence of Clinical Cardiovascular Disease.” IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 68, no. 9, Sept. 2021, pp. 3017–3026. 10.1109/TUFFC.2021.3081137.
XI. Mahajan, A., et al. “A Hybrid Feature Selection and Ensemble Stacked Learning Models on Multi-Variant CVD Datasets for Effective Classification.” IEEE Access, vol. 12, 2024, pp. 87023–87038. 10.1109/ACCESS.2024.3412077.
XII. Mondal, S., et al. “An Efficient Computational Risk Prediction Model of Heart Diseases Based on Dual-Stage Stacked Machine Learning Approaches.” IEEE Access, vol. 12, 2024, pp. 7255–7270. 10.1109/ACCESS.2024.3350996.

XIII. Nayak, Debasish Swapnesh Kumar, et al. “Enhancing Cardiovascular Disease Prediction Based on AI and IoT Concepts.” International Journal on Recent and Innovation Trends in Computing and Communication, vol. 11, no. 10, 2023. 10.17762/ijritcc.v11i10.8483.
XIV. Omkari, D. Y., and K. Shaik. “An Integrated Two-Layered Voting (TLV) Framework for Coronary Artery Disease Prediction Using Machine Learning Classifiers.” IEEE Access, vol. 12, 2024, pp. 56275–56290. 10.1109/ACCESS.2024.3389707.
XV. Pati, Abhilash, Manoranjan Parhi, and Binod Kumar Pattanayak. “IHDPM: An Integrated Heart Disease Prediction Model for Heart Disease Prediction.” International Journal of Medical Engineering and Informatics, vol. 14, no. 6, 2022, pp. 564–577. 10.1504/IJMEI.2022.126526.
XVI. Sinha, N., et al. “DASMcC: Data Augmented SMOTE Multi-Class Classifier for Prediction of Cardiovascular Diseases Using Time Series Features.” IEEE Access, vol. 11, 2023, pp. 117643–117655. 10.1109/ACCESS.2023.3325705.
XVII. Swain, Satyaprakash, Mihir Narayan Mohanty, and Binod Kumar Pattanayak. “Precision Medicine in Hepatology: Harnessing IoT and Machine Learning for Personalized Liver Disease Stage Prediction.” International Journal of Reconfigurable & Embedded Systems, vol. 13, no. 3, 2023, pp. 724–734. 10.11591/ijres.v13.i3.pp724-734.
XVIII. Tripathy, Jogeswar, R. Dash, and Binod Kumar Pattanayak. “Unleashing the Power of Machine Learning in Cancer Analysis: A Novel Gene Selection and Classifier Ensemble Strategy.” Research on Biomedical Engineering, vol. 40, no. 1, 2024, pp. 125–137. 10.1007/s42600-023-00335-2.
XIX. Tripathy, Jogeswar, et al. “Combination of Reduction Detection Using TOPSIS for Gene Expression Data Analysis.” Big Data and Cognitive Computing, vol. 6, no. 1, 2022, p. 24. 10.3390/bdcc6010024.
XX. Ullah, T., et al. “Machine Learning-Based Cardiovascular Disease Detection Using Optimal Feature Selection.” IEEE Access, vol. 12, 2024, pp. 16431–16446. https://doi.org/10.1109/ACCESS.2024.3359910.

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Journal Vol – 20 No – 6, June 2025

TERABIT DATA RATE, OPTICAL SYSTEM DESIGN AND ANALYSIS FOR DIFFERENT COMPENSATION METHODS

Authors:

Ahmed Abdul Salam ALobaidi, Meena AlBaghdadi, Ali Kareem Najm AL-ASADI, Mustafa Kareem Najm AL-ASADI, Ahmed Hussein Ahmed

DOI NO:

https://doi.org/10.26782/jmcms.2025.06.00009

June 15, 2025

Abstract:

In recent times, several sectors and businesses have been doing extensive research on the use of Dense Wavelength Division Multiplexing (DWDM) and Radio Frequency Over Fiber (RFOF). These two technologies are considered to be the most significant features. Increasing the data rate was a significant challenge that needed to be addressed, and the goal was to successfully implement a fiber optic system that was dependable and had a high number of associated channels. As a consequence of this, a 64-channel DWDM RFOF system that is capable of supporting a larger number of data rates of 2.56 Tbps has been designed and implemented in this study. A significant number of channels that have been sampled will be chosen for inquiry based on the characteristics of Quality Factor (QF) and Bit Error Rate (BER) that have been researched. This study will be carried out with the assistance of Optisystem software. These findings would be investigated at distances ranging from sixty to one hundred eighty kilometers, with the NRZ modulation format being used and a lunched power of zero decibels per meter. Additionally, the purpose of this study would be to explore the three distinct techniques of compensation, namely pre, post, and symmetrical, to quantify the individual performance of each approach on the suggested system. According to the findings, the use of symmetrical-based compensation yielded the most favorable outcomes, with the average QF acquired falling within the range of (20.33-14.09) dBm over distances ranging from (60-180) km. This demonstrates the dependability of the proposed system.

Keywords:

Bit Error Rate (BER),Dense Wavelength Division Multiplexing (DWDM),Optisystem Software,Radio Frequency Over Fiber (RFOF),

Refference:

I. Al-Obaidi, Sami Hassan, S. (2025). Blue Laser Optical NOMA Communication Applied on Control Drone-to-Underwater Vehicle. Al-Iraqia Journal for Scientific Engineering Research, 4(1), 89–98. https://doi.org/10.58564/IJSER.4.1.2025.299 Bhattacharjee, R., Dey, P., & Saha, A. (2022). Implementation of an enhanced 32 channel 256Gbps DWDM based Radio over Fiber optical system for constricted channel spacing employing Fiber Bragg Grating. Optik, 168598.‏
II. Ji, W., & Kang, Z. (2013). Design of WDM RoF PON based on OFDM and optical heterodyne. Journal of Optical Communications and Networking, 5(6), 652–657.
III. Jihad, N. J., & Almuhsan, M. A. A. (2023). Enhancement on the performance of radio-over-fiber ROF technology. Journal of Optics, 1–9.
IV. Juven, M. K., Roy, M., & Dristy, F. T. (2018). A study of the effects of digital modulation and length of optical fiber in a Radio over Fiber (RoF) Communication System (Doctoral dissertation, East West University).
V. Kaur, B., & Sharma, N. (2022). Radio over Fiber (RoF) for Future Generation Networks. In Broadband Connectivity in 5G and Beyond: Next Generation Networks (pp. 161–184). Cham: Springer International Publishing.
VI. A. Jasim Mohammed, “Impact of Rain Weather Conditions over Hybrid FSO/58GHz Communication Link in Tropical Region ”, IJSER, vol. 3, no. 3, pp. 117–134, Sep. 2024.
VII. Liu, A., Yin, H., Wu, B., & Zhou, Z. (2018). Flexible TWDM–RoF system with good dispersion tolerance for downlink and uplink based on additional SCS. Applied Optics, 57(31), 9432–9438.
VIII. Malak, A. A. R., & Kurnaz, S. (July 2021). Design and Implementation of high data rate system based DWDM–RoF technique for 5G Front haul Communication. Aurum Journal of Engineering System and Architecture.
IX. Mohsen, D. E., Hammadi, A. M., & Al-Askary, A. J. (2021). WDM and DWDM based RoF system in fiber optic communication systems: a review. International Journal of Communication Networks and Information Security, 13(1), 22–32.
X. Mohsen, D. E., Hammadi, A. M., & Alaskary, A. J. (2021, July). Design and Implementation of 1.28 Tbps DWDM based RoF system with External Modulation and Dispersion Compensation Fiber. In Journal of Physics: Conference Series (Vol. 1963, No. 1, p. 012026). IOP Publishing.‏
XI. Mousa, M. I., Cansevera, G., & Abd, T. H. (2020). Design and Implementation DWDM toward Terabit for Long-Haul Transmission System. In 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). IEEE.
XII. Okoumassoun, T. P., Antwiwaa, A., & Gerrar, N. K. (2023). Performance Evaluation of Optical Amplifiers in a Hybrid RoF-WDM Communication System. Journal of Communications, 18(8).
XIII. Pandey, V. K., Gupta, S., & Chaurasiya, B. (2014). Performance analysis of WDM PON and ROF Technology in optical communication based on FBG. International Journal of Engineering Research, 3(10), 608–612.
XIV. Patel, D., & Dalal, U. D. (2017). A novel wavelength reused bidirectional RoF-WDM-PON architecture to mitigate reflection and Rayleigh backscattered noise in multi-Gb/s m-QAM OFDM SSB upstream and downstream transmission over a single fiber. Optics Communications, 390, 26–35.
XV. Rahman, S., Ali, F., Smagor, A., Muhammad, F., Habib, U., Glowacz, A., … & Mursal, S. N. F. (2020). Mitigation of nonlinear distortions for a 100 Gb/s radio-over-fiber-based WDM network. Electronics, 9(11), 1796.
XVI. Rather, I. A., Kumar, G., & Saha, R. (2021). Survey on RoF technology and the mitigation schemes over the challenges in the RoF network. Optik, 247, 168007.
XVII. Reddy, V., & Jolly, L. (2016). Simulation and analysis of radio over fiber (RoF) systems using frequency up-conversion technique. International Journal of Computer Applications, 133(12), 36–43.
XVIII. Shan, D., Wen, A., Zhai, W., & Tan, M. (2021). All-optical double spectral-efficient ROF link with compensation of dispersion-induced power fading. IEEE Photonics Journal, 13(4), 1–7.
XIX. S.H. Alnajjar , & Kalid ALfaris , B. (2022). Enhancement of Light Fidelity System According to Multi-Users Utilizing OCDMA Technology under Weather Conditions. Al-Iraqia Journal for Scientific Engineering Research, 1(2), 9–15. Retrieved from https://ijser.aliraqia.edu.iq/index.php/ijser/article/view/47
XX. Y.S. Mezaal, H.H. Madhi, T. Abd, S.K. Khaleel, “Cloud computing investigation for cloud computer networks using cloudanalyst,”Journal of Theoretical and Applied Information Technology, vol. 96, no. 20, pp. 6937–6947, 2018.
XXI. Y. S. Mezaal, H. T. Eyyuboglu, and J. K. Ali, “A novel design of two loosely coupled bandpass filters based on Hilbert-zz resonator with higher harmonic suppression,” in 2013 Third International Conference on Advanced Computing and Communication Technologies (ACCT), 2013, https://doi.org/ 10.1109/ACCT.2013.54.
XXII. Y. S. Mezaal and H. T. Eyyuboglu, “Investigation of new microstrip bandpass filter based on patch resonator with geometrical fractal slot,” PLoS One, vol. 11, no. 4, p. e0152615, 2016, 10.1371/journal.pone.0152615.
XXIII. Y. S. Mezaal, “New compact microstrip patch antennas: Design and simulation results,” Indian J. Sci. Technol., vol. 9, no. 12, 2016, 10.17485/ijst/2016/v9i12/85950.
XXIV. Y. S. Mezaal and K. Al-Majdi, “New miniature narrow band microstrip diplexer for recent wireless communications,” Electronics (Basel), vol. 12, no. 3, p. 716, 2023, https://doi.org/10.3390/electronics12030716.
XXV. Zhang, L., Xin, X., Liu, B., Wang, Y., Yu, J., & Yu, C. (2010). OFDM modulated WDM-ROF system based on PCF-supercontinuum. Optics Express, 18(14), 15003–15008.

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Journal Vol – 20 No – 6, June 2025

SMART DELAY PREDICTION: SUPERVISED MACHINE LEARNING SOLUTIONS FOR CONSTRUCTION PROJECTS

Authors:

Pramodini Sahu, Dillip Kumar Bera, Pravat Kumar Parhi, Meenakshi Kandpal

DOI NO:

https://doi.org/10.26782/jmcms.2025.06.00010

June 15, 2025

Abstract:

With construction project delays being a key factor influencing their financial sinews, issues related to contract law, thus rendering resources incapable, remain a contemporary issue all over the globe. Conventional techniques for predicting delays often do not deliver concrete predictions due to the multiplicity and dynamic character of construction tasks. In the study discussed here, different machine learning (ML) algorithms were investigated to foresee construction delays, and these include Gaussian Naïve Bayes, Adaboost, Logistic Regression, Gradient Boosting (GB), Random Forest (RF), Decision Tree (DT) and Extreme Gradient Boosting (XGBoost). These models were measured for performance using various metrics such as accuracy, precision, recall, and F1 score to assess their validity in real-life situations. The results indicate that the use of ensemble learning techniques such as Random Forest (RF), and XGBoost scores higher than others, thus exhibiting more accuracy and better predictive capacity. These can relate to convoluted relationships in construction data, which makes them suitable for yet another application in project risk management. In contrast, simpler models like Adaboost and Gaussian Naïve Bayes, despite being interpretable, held lesser predictive accuracy and hence were less qualified for construction delay forecasting. The study highlights the potential of ML-driven predictive models in aiding project management timely by enabling timely identification of prospective delays, thereby allowing for proactive decision-making and project control. Hence, hurdles like quality of data, interpretability of models, and integration with real-time project management systems ought to be surmounted for wide-scale adoption in the industry. Future studies ought to develop hybrid ML models that fit in explainable AI techniques and real-time data on construction applications to assure predictive accuracy and usability in practice. The findings show that ensemble-based delay prediction models have the potential to reduce the uncertainties related to projects, control delays, schedule resources efficiently, and ultimately improve the infrastructure project efficiency in costing and timely project completion.

Keywords:

Adaboost,Construction Delay,Decision Tree,Gaussian Naïve Bayes,Gradient Boosting,Logistic Regression,Random Forest,XGBoost,

Refference:

I. Bilal, Muhammad, et al. “Big Data in the construction industry: A review of present status, opportunities, and future trends.” Advanced engineering informatics 30.3 (2016): 500-521. 10.1016/j.aei.2016.07.001
II. Chao, Li-Chung, and Ching-Fa Chien. “Estimating project S-curves using polynomial function and neural networks.” Journal of Construction Engineering and Management 135.3 (2009): 169-177. 10.1061/(ASCE)0733-9364(2009)135:3(169)
III. Desai, Vijaya S., and Sharad Joshi. “Application of decision tree technique to analyze construction project data.” Information Systems, Technology and Management: 4th International Conference, ICISTM 2010, Bangkok, Thailand, March 11-13, 2010. Proceedings 4. Springer Berlin Heidelberg, 2010. 10.1007/978-3-642-12035-0_30
IV. Egwim, Christian Nnaemeka, et al. “Applied artificial intelligence for predicting construction projects delay.” Machine Learning with Applications 6 (2021): 100166. 10.1016/j.mlwa.2021.100166
V. Egwim, Christian Nnaemeka, et al. “Systematic review of critical drivers for delay risk prediction: Towards a conceptual framework for BIM-based construction projects.” Frontiers in Engineering and Built Environment 3.1 (2022): 16-31. 10.1108/FEBE-05-2022-0017
VI. Elazouni, Ashraf M. “Classifying construction contractors using unsupervised-learning neural networks.” Journal of construction engineering and management 132.12 (2006): 1242-1253.10.1061/(ASCE)0733-9364(2006)132:12(1242)
VII. Gerassis, S., et al. “Bayesian decision tool for the analysis of occupational accidents in the construction of embankments.” Journal of construction engineering and management 143.2 (2017): 04016093. 10.1061/(ASCE)CO.1943-7862.0001225
VIII. Gondia, Ahmed, et al. “Machine learning algorithms for construction projects delay risk prediction.” Journal of Construction Engineering and Management 146.1 (2020): 04019085. 10.1061/(ASCE)CO.1943-7862.0001736
IX. Gurgun, Asli Pelin, Kerim Koc, and Handan Kunkcu. “Exploring the adoption of technology against delays in construction projects.” Engineering, Construction and Architectural Management 31.3 (2024): 1222-1253. 10.1108/ECAM-06-2022-0566
X. Heravi, Gholamreza, and Ehsan Eslamdoost. “Applying artificial neural networks for measuring and predicting construction-labor productivity.” Journal of Construction Engineering and Management 141.10 (2015): 04015032.10.1061/(ASCE)CO.1943-7862.0001006
XI. Sanni-Anibire, Muizz O., Rosli M. Zin, and Sunday O. Olatunji. “Machine learning-Based framework for construction delay mitigation.” Journal of Information Technology in Construction 26 (2021). 10.36680/j.itcon.2021.017
XII. Sanni-Anibire, Muizz O., Rosli Mohamad Zin, and Sunday Olusanya Olatunji. “Machine learning model for delay risk assessment in tall building projects.” International Journal of Construction Management 22.11 (2022): 2134-2143. 10.1080/15623599.2020.1768326
XIII. Saunders, Mark, Philip Lewis, and Adrian Thornhill. Research methods for business students. Pearson education, 2009.
XIV. Un, Buse, et al. “Forecasting the outcomes of construction contract disputes using machine learning techniques.” Engineering, Construction and Architectural Management (2024). 10.1108/ECAM-05-2023-0510
XV. 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

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Journal Vol – 20 No – 6, June 2025

DEVELOPING AN EFFICIENT AIR PURIFICATION SYSTEM: FOCUS ON AIRBORNE DISEASE AND ALLERGEN CONTROL

Authors:

Ali Samir A., Hasan Jumaah Mrayeh, Salih Meri Al-Absi, Gabriella Bognar Vadászné, Alaa Alrudhan Abed

DOI NO:

https://doi.org/10.26782/jmcms.2025.06.00011

June 15, 2025

Abstract:

The objective of this paper was to design an air purifier system to solve the relevant problem of airborne disease and allergen spread in classrooms and retail settings. While reducing the risk of COVID exposure through airborne particles was the main objective of the system, reducing the risk of Influenza, and the concentration of common allergens such as dust and pollen were also central to the design. The implementation involved a portable air purification system that was affordable and a size appropriate for classrooms and small businesses. The design was tested using CAD designs and various component specifications. These specifications were as follows; filtration ability, airflow capacity, floor space used, noise level, the time before UV decay took place, price of both a prototype and final market design, weight, and time before maintenance was required. This design met all main requirements, excluding the noise level, which was found to be 10% higher than required in the engineering specification. However, this was overruled by the need to reduce costs and increase power. Future recommendations and next steps include adding more advanced electrical control components, considering the effectiveness of UVC light specifically against COVID-19, soundproofing the design, and other minor changes to improve the system.

Keywords:

Indoor Air Quality,Engineering Design,Air Filtration,Respiratory Infection Control,Ventilation Strategies,Air Cleaning Technologies,

Refference:

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Journal Vol – 20 No – 6, June 2025

MATHEMATICAL SIMULATION OF NOSOCOMIAL INFECTION SPREAD AND THE ROLE OF NURSING-BASED INTERVENTIONS

Authors:

Sinjit Mukherjee, Soumya Sonalika

DOI NO:

https://doi.org/10.26782/jmcms.2025.06.00012

June 15, 2025

Abstract:

Hospital-acquired infections (HAIs), or nosocomial infections, compromise patient safety and the provision of care worldwide. With their extensive patient contact, nurses are key to HAIs transmission and prevention. This article employs a mathematical simulation of HAI dynamics for 60 days in a theoretical 1,000-person hospital ward using a modified Susceptible-Infected-Recovered (SIR) model, with and without nurse interventions such as hand hygiene, patient isolation, personal protective equipment (PPE) use, and environmental disinfection. Enhanced advancements, including the incorporation of genomic and epidemiological data, enhance the model's ability to track transmission clusters, particularly in the case of multidrug-resistant organisms (MDROs) such as MRSA (Illingworth et al., 2022). The simulation demonstrates that nurse interventions reduce infection rate by over 70%, retarding peak and lowering total cases (from ~830 to ~240). Findings are congruent with observations comparing interventions such as chlorhexidine bathing (Climo et al., 2016). Through model assumptions, e.g., asymptomatic transmission, this article offers a concrete basis for hospital decision-making, emphasizing evidence-based nursing and interprofessional infection control practices.

Keywords:

Chlorhexidine Bathing,Healthcare Delivery,Hospital-Acquired Infections (HAIs),Infection Control Patient Safety,Multidrug-Resistant Organisms (MDROs),Nurse-led Interventions,Personal Protective Equipment (PPE),Susceptible-Infected-Recovered (SIR),

Refference:

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Journal Vol – 20 No – 6, June 2025

ORIGIN OF POSITION DEPENDENT MASS IN A ROTATING PARABOLIC OR SEMI-PARABOLIC PATH: CLASSICAL AND SEMI-CLASSICAL

Authors:

Rabab Jarrar, Tapas Roy, B. Rath, Prachi Prava Mohapatra, Dilip K Maiti, Jihad Asad

DOI NO:

https://doi.org/10.26782/jmcms.2025.06.00013

June 15, 2025

Abstract:

For both classical and quantum elements of the system, parabolic and semi-parabolic nature paths have been examined and analyzed. We use the most powerful semi-analytical techniques, namely the optimal and modified homotopy perturbation approach, to examine the dynamics of the particle motion with stability analysis. It is demonstrated that the particle's motion on a rotating parabolic path is precisely harmonic oscillator motion with mass depending on location. We find the exact analytical expression for the motion's frequency and amplitude. We then discuss the dependencies of amplitude and frequency on specific parameters and compare the accuracy of the analytical solutions to numerical simulations. We explore the effectiveness of analytical methodologies in solving the complex nature of particle motion and their significance to scientific and technical research.

Keywords:

Analytical solution,Harmonic Oscillator,Parabolic,Particle Motion,Semi-parabolic,Series solution,

Refference:

I. Asad, Jihad, et al. “Asymmetric Variation of a Finite Mass Harmonic Like Oscillator.” Results in Physics, vol. 19, 2020, 103335. https://doi.org/10.1016/j.rinp.2020.103335.
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V. Dong, S. H., et al. “Exact Solutions of an Exponential Type Position Dependent Mass Problem.” Results in Physics, vol. 34, 2022, pp. 105294–105298. https://doi.org/10.1016/j.rinp.2022.105294.
VI. Dong, Shi-Hai, et al. “Exact Solutions of an Exponential Type Position Dependent Mass Problem.” Results in Physics, vol. 34, 2022, 105294. https://doi.org/10.1016/j.rinp.2022.105294.
VII. Eigoli, A. K., and M. Khodabakhsh. “A Homotopy Analysis Method for Limit Cycle of the Van der Pol Oscillator with Delayed Amplitude Limiting.” Applied Mathematics and Computation, vol. 217, 2011, pp. 9404–9411. http://dx.doi.org/10.1016/j.amc.2011.04.029.
VIII. El-Nabulsi, R. A. “A Generalized Self-Consistent Approach to Study Position-Dependent Mass in Semiconductors Organic Heterostructures and Crystalline Impure Materials.” Physica E: Low-Dimensional Systems and Nanostructures, vol. 134, 2021, 114295. https://doi.org/10.1016/j.physe.2020.114295.
IX. El-Nabulsi, R. A. “A New Approach to Schrödinger Equation with Position Dependent Mass and Its Implications in Quantum Dots and Semiconductors.”Journal of Physics and Chemistry of Solids, vol. 140, 2020, 109384. https://doi.org/10.1016/j.jpcs.2020.109384.
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Parabola Using Lagrangian and High Accuracy Multi-Step Differential
Transformation Method.” Powder Technology, vol. 258, 2014, pp. 94–98.
10.1016/j.powtec.2014.03.064.
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XVIII. Rath, Biswanath, et al. “Position-Dependent Finite Symmetric Mass Harmonic Like Oscillator: Classical and Quantum Mechanical Study.” Open Physics, vol. 19, no. 1, 2021, pp. 266–276. 10.1515/phys-2021-0024. [11]
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Journal Vol – 20 No – 6, June 2025

QUANTITATIVE ASSESSMENT OF RELATIVE HUMIDITY, K INDEX, AND TT INDEX USING PROGRAMMATIC ANALYSIS

Authors:

Indrajit Ghosh, Ananya Roy, Vanshika Gupta, Shruti Bhattacharya

DOI NO:

https://doi.org/10.26782/jmcms.2025.06.00014

June 15, 2025

Abstract:

This study conducted a quantitative analysis to evaluate the statistical significance of climatic parameters such as Relative Humidity (RH), K Index and Total Totals (TT) Index. Given Kolkata's susceptibility to various atmospheric extreme events—including discomfort indices, cyclones, thunderstorms, hailstorms and torrential rains—the city was selected as the focus for this analysis. The research aimed to develop accurate predictive models by performing extensive statistical analyses on available upper air data from Kolkata across all three seasons: summer, winter and the monsoon. Python was utilized for statistical computations to derive semi-empirical relationships between RH, geopotential height and pressure. The primary objective was to establish predictive equations that could be validated against real-time data. The models demonstrated a low Mean Squared Error (MSE) of approximately 20.69, indicating their potential as reliable tools for significant statistical assessments.

Keywords:

Relative Humidity,K Index,TT Index,Atmospheric Instability,Computational Programming,Climate Modeling,Error Analysis,Weather Forecasting,

Refference:

I. Chindaphol, S., et al. “A Suitable Thermal Stress Index for the Elderly in Summer Tropical Climates.” Procedia Engineering, vol. 180, 2017, pp. 932-43. 10.1016/j.proeng.2017.04.253.
II. Dasgupta, S., et al. “A Megacity in a Changing Climate: The Case of Kolkata.” Climate Change, vol. 116, 2013, pp. 747-66. 10.1007/s10584-012-0516-3.
III. Fernando, M., et al. “Analyze and Comparison of the Atmospheric Instability Using K-Index, Lifted Index Total Totals Index Convective Availability Potential Energy (CAPE) and Convective Inhibition (CIN) in Development of Thunderstorms in Sri Lanka During Second Inter-Monsoon.” Multi-Hazard Early Warning and Disaster Risks, edited by D. Amaratunga, et al., Springer, 2021. 10.1007/978-3-030-73003-1_41.
IV. Ghosh, I., et al. “Anomaly Temperature in the Genesis of Tropical Cyclone.” Natural Hazards, vol. 114, 2022, pp. 1477-503. https://doi.org/10.1007/s11069-022-05434-4.
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VI. Tajbakhsh, S., et al. “Instability Indices and Forecasting Thunderstorms: The Case of 30 April 2009.” Natural Hazards and Earth System Sciences, vol. 12, 2012, pp. 403-13. 10.5194/nhess-12-403-2012.
VII. Talapatra, A., et al. “Geospatial Analysis of the Dynamics of Climate in Kolkata Metropolitan Area.” Journal of Physics: Conference Series, vol. 1964, 2021, p. 042038. 10.1088/1742-6596/1964/4/042038.
VIII. “University of Wyoming Data Archive of South-East Asia (Kolkata Region).” University of Wyoming Department of Atmospheric Science, https://weather.uwyo.edu/upperair/sounding_legacy.html. Accessed 15 March 2025.

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Journal Vol – 20 No – 6, June 2025

NUMERICAL EXPLORATION OF CHEMICAL REACTION AND JOULE HEATING EFFECTS ON THE DYNAMICS OF THNF CU-TIO_2-SIO_2/H_2 O:HEAT AND MASS TRANSMISSION ANALYSIS

Authors:

Naga Lakshmi, Ch. Maheswari, Venkata Rao Kanuri, J.V. Ramanaiah, R. S. Durga Rao, V. S. Bhagavan

DOI NO:

https://doi.org/10.26782/jmcms.2025.07.00001

July 14, 2025

Abstract:

This analysis attempts to explain the theoretical analysis of Joule heating and chemical reactions on the systematic flow of a ternary hybrid nanofluid. The flow of the tri-nanofluids was examined on thermal, momentum, and concentration boundary layers (BL). The physical problem was developed as a partial differential equation (PDEs). This was changed to total differential equations by suitable similarity variables. The Runge-Kutta, along with the shooting technique, was employed on the transformed flow equations. These solutions were presented in a pictorial form to discuss the physical problem, while the quantities of interest in engineering are tabulated. The Eckert number was found to enhance the thermal analysis by elevating the temperature along with the velocity distribution. The Joule heating along the magnetic field in the analysis was discovered to limit the speed of the fluid by reducing the velocity distribution.

Keywords:

Chemical reaction,Heat and Mass Transmission Analysis,Ternary hybrid nanofluid,Viscous dissipation,

Refference:

I. Ahmed, Saleem, Huma Iram, and Asif Mahmood. “Joule and viscous dissipation effects on MHD boundary layer flow over a stretching sheet with variable thickness.” Int J Emerg Multidisciplinaries Math 1.2 (2022): 1-10. 10.54938/ijemdm.2022.01.2.27
II. AL Garalleh, Hakim. “Numerical simulation of heat transport mechanism in chemically influenced ternary hybrid nanofluid flow over a wedge geometry.” Discover Applied Sciences 6.9 (2024): 449. 10.1007/s42452-024-06141-4
III. Alqawasmi, Khaled, et al. “Numerical approach toward ternary hybrid nanofluid flow with nonlinear heat source-sink and fourier heat flux model passing through a disk.” International Journal of Thermofluids 18 (2023): 100367. 10.1016/j.ijft.2023.100367
IV. Alshahrani, Saad, et al. “Numerical simulation of ternary nanofluid flow with multiple slip and thermal jump conditions.” Frontiers in Energy Research 10 (2022): 967307. 10.3389/fenrg.2022.967307
V. Al-Turef, Gadah Abdulrahman, et al. “Computational Study and Application of the Hamilton and Crosser Model for Ternary Hybrid Nanofluid Flow Past a Riga Wedge with Heterogeneous Catalytic Reaction.” Nano, vol. 20, no. 01, Jan. 2025, p. 2450105. 10.1142/S1793292024501054.
VI. Arshad, Mubashar, et al. “Rotating hybrid nanofluid flow with chemical reaction and thermal radiation between parallel plates.” Nanomaterials 12.23 (2022): 4177. 10.3390/nano12234177
VII. Bilal, Muhammad, et al. “Numerical analysis of an unsteady, electroviscous, ternary hybrid nanofluid flow with chemical reaction and activation energy across parallel plates.” Micromachines 13.6 (2022): 874. 10.3390/mi13060874
VIII. Bilal, Muhammad, et al. “Numerical simulations through PCM for the dynamics of thermal enhancement in ternary MHD hybrid nanofluid flow over plane sheet, cone, and wedge.” Symmetry 14.11 (2022): 2419. 10.3390/sym14112419
IX. Boubaker, Karem, et al. “Effects of Viscous Dissipation on the Thermal Boundary Layer of Pseudoplastic Power‐Law Non‐Newtonian Fluids Using Discretization Method and the Boubaker Polynomials Expansion Scheme.” International Scholarly Research Notices 2012.1 (2012): 181286. 10.5402/2012/181286
X. Coelho, Paulo M., and Robert J. Poole. “Heat transfer of power-law fluids in plane Couette–Poiseuille flows with viscous dissipation.” Heat Transfer Engineering 41.13 (2020): 1189-1207. 10.1080/01457632.2019.1611139
XI. Farooq, Umar, et al. “Analysis of Kerosene oil conveying silver and manganese zinc ferrite nanoparticles with hybrid nanofluid: effects of increasing the Lorentz force, suction, and volume fraction.” Ain Shams Engineering Journal 15.1 (2024): 102326. 10.1016/j.asej.2023.102326
XII. Guedri, Kamel, et al. “Thermal flow for radiative ternary hybrid nanofluid over nonlinear stretching sheet subject to Darcy–Forchheimer phenomenon.” Mathematical Problems in Engineering 2022.1 (2022): 3429439. 10.1155/2022/3429439
XIII. Kanuri, Venkat Rao, et al. “Investigating Poiseuille Flows in Rotating Inclined Pipes: An Analytical Approach.” Journal homepage: http://iieta. org/journals/ijht 42.1 (2024): 329-336. 10.18280/ijht.420135
XIV. Karthik, K., et al. “Impacts of thermophoretic deposition and thermal radiation on heat and mass transfer analysis of ternary nanofluid flow across a wedge.” International Journal of Modelling and Simulation (2024): 1-13. 10.1080/02286203.2023.2298234
XV. Khan, Shan Ali, et al. “Entropy optimized Ferro-copper/blood based nanofluid flow between double stretchable disks: Application to brain dynamic.” Alexandria Engineering Journal 79 (2023): 296-307. 10.1016/j.aej.2023.08.017
XVI. Khan, Muhammad Naveed, et al. “Flow and heat transfer insights into a chemically reactive micropolar Williamson ternary hybrid nanofluid with cross-diffusion theory.” Nanotechnology Reviews 13.1 (2024): 20240081. 10.1515/ntrev-2024-0081
XVII. Khan, Humera, et al. “Insights into the Significance of Ternary Hybrid Nanofluid Flow Between Two Rotating Disks in the Presence of Gyrotactic Microorganisms.” Nano (2024): 2450110. 10.1142/s1793292024501108
XVIII. Lakshmi, Bhavanam Naga, et al. “Numerical Analysis of Three-Dimensional Magneto hybridized Nanofluid (Al2O3-Cu/H2O) Radiative Stretchable rotating Flow with Suction.” Engineering, Technology & Applied Science Research 14.5 (2024): 16902-16910. 10.48084/etasr.8183
XIX. Li, Shuguang, et al. “Aspects of an induced magnetic field utilization for heat and mass transfer ferromagnetic hybrid nanofluid flow driven by pollutant concentration.” Case Studies in Thermal Engineering 53 (2024): 103892. 10.1016/j.csite.2023.103892.
XX. Manjunatha, S., et al. “Theoretical study of convective heat transfer in ternary‎ nanofluid flowing past a stretching sheet.” Journal of Applied and Computational Mechanics 8.4 (2022): 1279-1286. 10.22055/jacm.2021.37698.3067
XXI. Nihaal, Kandavkovi Mallikarjuna, et al. “Combined impact of joule heating, activation energy, and viscous dissipation on ternary nanofluid flow over three different geometries.” Int. J. Comput. Methods Exp. Meas 11.4 (2023): 251-258. 10.18280/ijcmem.110407
XXII. Priyadharshini, P., et al. “Ternary hybrid nanofluid flow emerging on a symmetrically stretching sheet optimization with machine learning prediction scheme.” Symmetry 15.6 (2023): 1225. 10.3390/sym15061225
XXIII. Ramzan, Muhammad, et al. “A theoretical analysis of the ternary hybrid nanofluid flows over a non-isothermal and non-isosolutal multiple geometries.” Heliyon 9.4 (2023). 10.1016/j.heliyon.2023.e14875
XXIV. Raza, Qadeer, et al. “Numerically analyzed of ternary hybrid nanofluids flow of heat and mass transfer subject to various shapes and size factors in two-dimensional rotating porous channel.” Case Studies in Thermal Engineering 56 (2024): 104235. 10.1016/j.csite.2024.104235
XXV. Rehman, Ali, et al. “Viscous dissipation effects on time-dependent MHD Casson nanofluid over stretching surface: A hybrid nanofluid study.” Journal of Molecular Liquids 408 (2024): 125370. 10.1016/j.molliq.2024.125370
XXVI. Sajid, Tanveer, et al. “Trace of chemical reactions accompanied with arrhenius energy on ternary hybridity nanofluid past a wedge.” Symmetry 14.9 (2022): 1850. 10.3390/sym14091850

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Journal Vol – 20 No – 7, July 2025

THE INFLUENCE OF TEMPERATURE ACTIONS ON THE CRACK RESISTANCE OF LOAD-BEARING STRUCTURES IN A CAST-IN-SITU BUILDING DURING CONSTRUCTION

Authors:

A. E. Lapshinov, Yu. A. Shaposhnikova

DOI NO:

https://doi.org/10.26782/jmcms.2025.07.00002

July 14, 2025

Abstract:

This study empirically assesses temperature effects on load-bearing systems using field data from an ongoing multifunctional complex featuring cast-in-situ reinforced concrete framing. The calculation-analytical method was employed for design justification, along with mathematical modeling using the LIRA 10.12 software. The results revealed that the strength utilization factor, considering the design reinforcement, exceeded 100% by up to 200% in certain sections of the 2nd underground floor slab, and ranged from 105% to 200% in sections of the 1st underground floor slab. Based on the results of the research, the following conclusions were drawn: cracks in the load-bearing structures of floor slabs and external load-bearing walls of the -2nd and -1st underground floors occurred due to the insufficiency of the calculated reinforcement for the perception of all types of impacts, including temperature; the main reason for the formation of cracks is the absence of expansion joints in the design document of load-bearing structures of the -2nd and -1st floors. According to the research findings the following recommendations are given: when designing cast-in-situ reinforced concrete frame buildings it is necessary to perform a temperature calculation; in case of failure to perform the calculation, it is necessary to arrange expansion joints per the code recommendations; the use of expansion joints in design can be avoided only with appropriate justification.

Keywords:

Cast-in-situ Frame Building,Cracks,Expansion Joint,Temperature Actions,Temperature Deformations,Temperature Shrinkage Block,

Refference:

I. Aleksandrovsky, S.V. Calculation of concrete and reinforced concrete structures for temperature and humidity effects (taking into account creep). Moscow: Stroyizdat (1966).
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III. Bofang, Z.: Thermal stresses and temperature control of mass concrete. Printed in the United States of America. (2014) 518. 10.1016/C2012-0-06038-3
IV. Bui, K.A., Sancharoen, P., Tanapornraweekit, G., Tangtermsirikul, S., Nanakorn, P.: An evaluation of thermal effects on behavior of a concrete arch dam. Songklanakarin J. Sci.Technol. 41(5) (2019)
V. Chen, H., Liu, Z.: Temperature control and thermal-induced stress field analysis of GongGuoQiao RCC dam. J. Therm. Anal. Calorim. 135(3), 11 (2018). 10.1007/s10973-018-7450-1
VI. Chepurnenko, A.S. Improving the methods for calculating plates and shells for force and temperature effects during nonlinear creep: specialty 05.23.17 “Structural Mechanics”: dissertation for the degree of Doctor of Technical (2021) 349.
VII. Do, T.M.D., Lam, T.Q.K.: Solutions to improve the quality of mass concrete construction in climate conditions of Southern Vietnam. Int. J. Innovative Technol. Exploring Eng. (IJITEE) 8(6C2), (2019) 188–192.
VIII. Gordeev, V.N., Lantukh-Lyaschenko, A.I., Pashinsky, V.A., Perelmuter, A.V., Pichugin, S.F. Loads and impacts on buildings and structures. Moscow: ASV (2007) 476.
IX. Karabanov, B.V. Features of calculation of monolithic reinforced concrete buildings for temperature effects. Concrete and reinforced concrete. 1 (2010).
X. Kodysh, E.N., Trekin, N.N., Nikitin, I.K. Design of multi-storey buildings with a reinforced concrete frame (2009) 347.
XI. Korsun, V.I.; Khon K. Strains and strength of reinforced concrete beams manufacturing by high-strength concrete for non-coincident planes of temperature gradient and loading; 2023; Construction of Unique Buildings and Structures; 109 Article No 10914. 10.4123/CUBS.109.14.
XII. Kunin, Yu.S. Kotov, V. I., Safina, L. Kh. Reduction of operational qualities of a building as a result of design errors. Part 1. Scientific Review. 7 (2017) 36-40.
XIII. Makeeva, A., Amelina, A., Semenov, K., Yuriy, B.: Temperature action in analysis of thermalstressed state of massive concrete and reinforced concrete structures. MATEC Web of Conferences. 245(03016), (2018). 10.1051/matecconf/201824503016
XIV. Mishchenko, N.A. Methodology for determining temperature deformation of building structures. Engineering Geodesy. 32 (1988) 69-71.
XV. Mkrtychev, O.V., Sidorov, D.S. Calculation of reinforced concrete building for temperature effects. Vestnik MGSU, 5 (2012) 50-55.
XVI. Muneer, K.S., Muhammad, K.R., Mohammed, H.B., Lutf, A.T.: Cracking in concrete watertank due to restrained shrinkage and heat of hydration: field investigations and 3D finite element simulation. J. Perform. Constructed Facil. 34(1), 12 (2020). 10.1061/(ASCE)CF.1943-5509.0001356
XVII. Nguyen, T.C., Bui, K.A., Hoang, Q.L. Thermal cracks in concrete structure ‒ the basic issues to be understood. Structural Health Monitoring and Engineering Structures. Lecture Notes in Civil Engineering 148. (June 2021). 10.1007/978-981-16-0945-9_19
XVIII. Plotnikov, A.A. Taking into account temperature effects in the design of load-bearing structures. Housing construction. 11 (2021) 21-26. 10.31659/0044-4472-2021-11-21-26.
XIX. Sabirov, R. A. On the calculation of plates under plane stress conditions for temperature effects using the variational-difference method in stress functions. Vestnik of the Siberian State Aerospace University named after Academician M.F. Reshetnev. 2 (54) (2014) 67-72.
XX. Samaeva, G.D., Kurmangaliyeva, A.R. Justification of expansion joints of a multi-story high-rise residential complex along Bakinskaya Street. Innovative development of regions: the potential of science and modern education: Proceedings of the VI National Scientific and Practical Conference with international participation, dedicated to the Day of Russian Science, Astrakhan, February 8–9. 6 (2023) 59-64.
XXI. Slesareva, A.D. Displacements of a residential building structure under the influence of temperature effects arising from solar radiation. Student Bulletin. 15-7 (301) (2024) 29-32.
XXII. Snegirev, A.I., Alkhimenko, A.I. Effect of short-circuit temperature during construction on stresses in load-bearing structures. Engineering and construction journal, 2 (2008).
XXIII. Shelkova, E.O. Korosteleva, A.I. Sheshenev, N.V. Analysis of design measures in the device of expansion joints. New technologies in the educational process and production: Proceedings of the XVII International Scientific and Technical Conference, Ryazan, April 17-19 (2019) 203-206.
XXIV. Voldřich, F. Expansion joints in structures of above-ground buildings: translated from Czech by T.M. Vankevich. Moscow: Stroyizdat (1978) 224.
XXV. Vladimir I.K., Valeriy I.M., Ashot G.T., Anatoly V.A. Nonlinear Deformation Model for Analysis of Temperature Effects on Reinforced Concrete Beam Elements // Buildings. 2023. (13). С. 1–16. 10.3390/buildings13112734.

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Journal Vol – 20 No – 7, July 2025

THERMOPHORESIS AND BROWNIAN MOTION EFFECTS ON HEAT AND MASS TRANSFER IN MIXED CONVECTIVE MHD HYBRID NANOFLUID FLOW PAST AN INCLINED MAGNETIC STRETCHING SHEET WITH CHEMICAL REACTION AND HEAT SOURCE

Authors:

David Kumar Parisa, K. Bhagya Swetha Latha, M. Gnaneswara Reddy

DOI NO:

https://doi.org/10.26782/jmcms.2025.07.00003

July 14, 2025

Abstract:

This study investigates the influence of thermophoresis, Brownian motion, and inclined magnetic fields on magnetohydrodynamic (MHD) mixed convective flow of a chemically reacting hybrid nanofluid over an inclined magnetic stretching sheet. The hybrid nanofluid comprises copper (Cu) and aluminum oxide (Al₂O₃) nanoparticles suspended in blood, serving as the base fluid. A heat source and first-order chemical reaction are incorporated into the model to analyze their combined impact on velocity, temperature, and concentration profiles. The governing system of highly nonlinear partial differential equations (PDEs) is transformed into a set of ordinary differential equations (ODEs) using similarity transformations. These equations are numerically solved using the fourth-order Runge-Kutta method coupled with the shooting technique, implemented in MATLAB. Graphical results illustrate the effects of key dimensionless parameters such as magnetic field strength, thermophoretic and Brownian motion parameters, chemical reaction rate, and heat source on flow characteristics. The numerical results show excellent agreement with previously published studies, validating the accuracy of the methodology. The findings have potential applications in biomedical engineering, targeted drug delivery, and thermal management systems.

Keywords:

Brownian motion,Chemical reaction,Heat source,Hybrid Nanofluid,Inclined magnetic field,Thermophoresis,

Refference:

I. Algehyne, E. A., Alrihieli, H. F., Bilal, M., Saeed, A., & Weera, W. (2022). Numerical approach toward ternary hybrid nanofluid flow using variable diffusion and non-Fourier’s concept. ACS Omega, 7(30), 29380–29390. 10.1021/acsomega.2c04309
II. Buongiorno, J. (2006). Convective transport in nanofluids. Journal of Heat Transfer, 128(3), 240–250. 10.1115/1.2150834
III. Bhattad, A., Sarkar, J., & Ghosh, P. (2020). Heat transfer characteristics of plate heat exchanger using hybrid nanofluids: Effect of nanoparticle mixture ratio. Heat and Mass Transfer, 56(9), 2457–2472. 10.1007/s00231-020-02864-z
IV. Chamkha, A. J., Aly, A. M., & Al-Mudhaf, H. (2011). Mixed convection flow of a nanofluid over a permeable stretching sheet in the presence of a magnetic field. International Journal of Microscale and Nanoscale Thermal and Fluid Transport Phenomena, 2(1), 51–72.
V. Chandrakala, P., Srinivasa Rao, V. (2024). Effect of Heat and Mass Transfer over Mixed Convective Hybrid Nanofluids past an Exponentially Stretching Sheet, CFD Letters 16, Issue 3, 125-140.

VI. Eid, M. R., & Nafe, M. A. (2022). Thermal conductivity variation and heat generation effects on magneto-hybrid nanofluid flow in a porous medium with slip condition. Waves in Random and Complex Media, 32(6), 1103–1127. 10.1080/17455030.2022.2032491
VII. Elsebaee, F. A. A., Bilal, M., Mahmoud, S. R., Balubaid, M., Shuaib, M., Asamoah, J. K. K., & Ali, A. (2023). Motile micro-organism based trihybrid nanofluid flow with an application of magnetic effect across a slender stretching sheet: Numerical approach. AIP Advances, 13(3), 035237. 10.1063/5.0139487
VIII. Guedri, K., Khan, A., Gul, T., Mukhtar, S., Alghamdi, W., Yassen, M. F., & Tag Eldin, E. (2022). Thermally dissipative flow and entropy analysis for electromagnetic trihybrid nanofluid flow past a stretching surface. ACS Omega, 7(41), 33432–33442. 10.1021/acsomega.2c03834
IX. Hazarika, S., Ahmed, S., & Chamkha, A. J. (2021). Numerical simulation of MHD hybrid nanofluid flow over a stretching surface: Influence of nanoparticle type and volume fraction. Mathematics and Computers in Simulation, 182, 819–832. 10.1016/j.matcom.2020.10.026
X. Ibrahim, W., & Negera, M. (2020). MHD slip flow of upper-convected Maxwell nanofluid over a stretching sheet with chemical reaction. Journal of the Egyptian Mathematical Society, 28, 1–28.
XI. Irfan, M., Khan, M., & Khan, W. A. (2020). Heat sink/source and chemical reaction in stagnation point flow of Maxwell nanofluid. Applied Physics A, 126(1), 1–8.
XII. Khan, M., Malik, M. Y., Salahuddin, T., et al. (2019). Generalized diffusion effects on Maxwell nanofluid stagnation point flow over a stretchable sheet with slip conditions and chemical reaction. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41(1), 1–9.
XIII. Khan, W. A., & Pop, I. (2010). Boundary-layer flow of a nanofluid past a stretching sheet. International Journal of Heat and Mass Transfer, 53(11–12), 2477–2483. 10.1016/j.ijheatmasstransfer.2010.01.032
XIV. Khan, A. S., Xu, H.-Y., & Khan, W. (2021). Magnetohydrodynamic Hybrid Nanofluid Flow Past an Exponentially Stretching Sheet with Slip Conditions. Mathematics, 9(24), 3291. 10.3390/math9243291
XV. Kuznetsov, A. V., & Nield, D. A. (2010). Natural convective boundary-layer flow of a nanofluid past a vertical plate. International Journal of Thermal Sciences, 49(2), 243–247. 10.1016/j.ijthermalsci.2009.07.015
XVI. Nield, D. A., & Kuznetsov, A. V. (2009). The Cheng–Minkowycz problem for natural convective boundary layer flow in a porous medium saturated by a nanofluid. International Journal of Heat and Mass Transfer, 52(25–26), 5792–5795. 10.1016/j.ijheatmasstransfer.2009.07.024
XVII. Noghrehabadi, A., Behseresht, A., Ghalambaz, M., & Behseresht, J. (2013). Heat and mass transfer of non-Darcy natural convection nanofluid flow over a vertical cone embedded in porous media. Journal of Thermophysics and Heat Transfer, 27(2), 334–342. 10.2514/1.T4086
XVIII. Patil, V.S., Patil A.B., Ganesh S, et al. (2021). Unsteady MHD flow of a nano Powell-Eyring fluid near stagnation point past a convectively heated stretching sheet in the existence of chemical reaction with thermal radiation. Materials Today: Proceedings, 44: 3767–3776.
XIX. Raizah, Z., Khan, A., Gul, T., Saeed, A., Bonyah, E., & Galal, A. M. (2023). Coupled Dufour and Soret effects on hybrid nanofluid flow through gyrating channel subject to chemically reactive Arrhenius activation energy. Journal of Nanomaterials, 2023, Article 6721294. 10.1155/2023/6721294
XX. Ramana, K. V., Reddy, G. R., Reddy, M. C., & Chamkha, A. J. (2021). Cattaneo–Christov model for MHD nanofluid flow past a stretching surface with thermal relaxation and viscous dissipation. Journal of Thermal Analysis and Calorimetry, 147, 2749–2761. 10.1007/s10973-020-09661-3
XXI. Rauf, A., Faisal, N. A., & Shah, T. B. (2022). Hall current and morphological effects on MHD micropolar non-Newtonian tri-hybrid nanofluid flow between two parallel surfaces. Scientific Reports, 12, 16608. 10.1038/s41598-022-20877-6
XXII. Reddy, P. S., Sreedevi, P., & Chamkha, A. J. (2017). Magnetohydrodynamic flow and heat transfer of nanofluids over a rotating disk embedded in porous media. Powder Technology, 307, 46–55. 10.1016/j.powtec.2016.11.013
XXIII. Sabu, A. S., Reddy, P. S., Sreedevi, P., & Chamkha, A. J. (2021). Effect of nanoparticle shape on MHD hybrid nanofluid flow in a rotating system with convective boundary conditions. International Communications in Heat and Mass Transfer, 129, 105711. 10.1016/j.icheatmasstransfer.2021.105711
XXIV. Seyedi, S. H., Saray, B. N., & Chamkha, A. J. (2020). Heat and mass transfer investigation of MHD Eyring–Powell flow in a stretching channel with chemical reactions. Physica A: Statistical Mechanics and its Applications, 544, 124109.
XXV. Shahzad, F., Jamshed, W., Eid, M. R., Ibrahim, R. W., Aslam, F., Isa, S. S. P. M., & Guedri, K. (2023). The effect of pressure gradient on MHD flow of a tri-hybrid Newtonian nanofluid in a circular channel. Journal of Magnetism and Magnetic Materials, 568, 170320. 10.1016/j.jmmm.2022.170320
XXVI. Sreedevi, P., Reddy, P. S., & Chamkha, A. J. (2018). Magnetohydrodynamic boundary-layer flow of nanofluids over a cone with free convection. International Journal of Mechanical Sciences, 135, 646. 10.1016/j.ijmecsci.2017.12.019
XXVII. Zhang, I., L., Bhatti, M. M., Michaelides, E. E., Marin, M., & Ellahi, R. (2022). Hybrid nanofluid flow towards an elastic surface with tantalum and nickel nanoparticles, under the influence of an induced magnetic field. European Physical Journal Special Topics, 231(1), 1–13. 10.1140/epjs/s11734-021-00293-7

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Journal Vol – 20 No – 7, July 2025

FUTURE TRENDS AND EMERGING TECHNOLOGIES IN MECHANICAL ENGINEERING: AN ANALYTICAL PERSPECTIVE

Authors:

Raffi Mohammed, Bairysetti Prasad Babu, Subramanya Sarma S., C. Sailaja, Subhani Mohammed, Kiran Kumar Bunga, Chiranjeevi Aggala

DOI NO:

https://doi.org/10.26782/jmcms.2025.07.00004

July 14, 2025

Abstract:

Engineering is a specially designed course that includes the application of knowledge explicitly in the field of science and natural phenomena. The fields of engineering, technology, and physical sciences have been growing towards a new era of development and innovation across the globe. They include many fields, and one such significant area is mechanical engineering, which deals with the construction, working principles, and applications of various types of machines. Technical data of the products based on their scientific principles, along with parameters, are involved in the development of mechanical engineering. With this background, this study is designed to look forward to the future directions and emerging technologies in mechanical engineering. This review study investigated the future direction and emerging technology in mechanical engineering. It also highlighted the purpose and significance of mechanical engineering and discussed some of the research questions in mechanical engineering. Future directions of learning and technology, mechanical invention and development, the transportation industry, electric vehicles, and the artificial intelligence industrial revolution are also mentioned in this study. Mechanical engineering is a growing field of technology across the world. This review study indicated that it is essential to have upgraded knowledge and skills in the field of engineering and technology in this modern era. Many theories can be applied in the mechanical field with the support of upgrades in technology. The direction of mechanical engineering study is to learn the mechanical aspects of different technologies and the knowledge about that technology to optimize its use.

Keywords:

Additive Manufacturing,Artificial Intelligence,Bio-Engineering,Energy Harvesting,Internet of Things,Machine Learning,Nano-Technology,Robotics and Automation,Sustainable and Green Technologies,

Refference:

I. Adedoyin, F. F., Agboola, P. O., Ozturk, I., Bekun, F. V., & Agboola, M. O. (2021). Environmental consequences of economic complexities in the EU amidst a booming tourism industry: Accounting for the role of Brexit and other crisis events. Journal of Cleaner Production, 305, 127117. 10.1016/j.jclepro.2021.127117
II. Arinez, J. F., Chang, Q., Gao, R. X., Xu, C., & Zhang, J. (2020). Artificial intelligence in advanced manufacturing: Current status and future outlook. Journal of Manufacturing Science and Engineering, 142(11), 110804. 10.1115/1.4047851
III. Bongomin, O., Yemane, A., Kembabazi, B., Malanda, C., Mwape, M. C., Mpofu, N. S., & Tigalana, D. (2020). Industry 4.0 disruption and its neologisms in major industrial sectors: A state of the art. Journal of Engineering, 2020(1), 8090521. 10.1155/2020/8090521
IV. Fu, C., Xia, Z., Hurren, C., Nilghaz, A., & Wang, X. (2022). Textiles in soft robots: Current progress and future trends. Biosensors and Bioelectronics, 2022(197), 113722. 10.1016/j.bios.2021.113722
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VII. Jang, Y. E., Lee, J. M., & Son, J. W. (2022). Development and application of an integrated management system for off-site construction projects. Buildings, 12(1), 12. 10.3390/buildings12010012
VIII. Jiao, R., Commuri, S., Panchal, J., Milisavljevic-Syed, J., Allen, J. K., Mistree, F., & Schaefer, D. (2021). Design engineering in the age of Industry 4.0. Journal of Mechanical Design, 143(7), 070801. 10.1115/1.4050164
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Journal Vol – 20 No – 7, July 2025

DETERMINATION OF FRACTURE TOUGHNESS OF MILD STEEL UNDER MIXED-MODE CONDITIONS USING EXPERIMENTAL FINITE ELEMENT ANALYSIS

Authors:

Anita Pritam, Peer Mohamed Appa M.A.Y., S. Rahamat Basha, Bujjibabu Penumutchi, D. Naga Purnima, Ansari Faiyaz Ahmed, Yogesh Diliprao Sonawane, Chandrabhanu Malla, Rabinarayan Sethi

DOI NO:

https://doi.org/10.26782/jmcms.2025.07.00005

July 14, 2025

Abstract:

This paper explores the fracture toughness of mild steel through experimental and finite element mixed-mode loading modeling. The experiment set the plate of size rectangular of a through-edge inclined crack to find out the critical stress. The experimental results were then applied as input for modeling the specimen in ANSYS, where both the Mode I and Mode II stress intensity factors were computed. The hoop stress approach obtained the maximum hoop stress theory by use of which the critical stress intensity factor is calculated, which shows the fracture toughness of the material. These showed that the mild steel fracture toughness was between 53 and 78 MPa/m1/2. An experimental parametric study of crack length as well as crack inclination on stress intensity factors was carried out, giving insightful conclusions regarding material behavior in fracture in mixed-mode conditions.

Keywords:

ANSYS,Critical Stress Intensity Factor,Finite Element Method,Fracture Toughness,SIF,

Refference:

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VII. Fagerholt, E., C. Dørum, T. Børvik, H. I. Laukli, and O. S. Hopperstad, “Experimental and numerical investigation of fracture in a cast aluminium alloy,” International Journal of Solids and Structures, vol. 47, no. 24, pp. 3352–3365, 2010.
VIII. Guo, W., H. Dong, and Z. Yang, “Experimental investigation of thickness effects on mixed-mode I/II fracture of an aluminum alloy,” arXiv preprint arXiv:0807.1577v2, 2008.
IX. Hossain, R., L. R. Wilson, and C. Tang, “Advanced mixed-mode I/II fracture analysis of polymer-based adhesives,” Polym. Eng. Sci., vol. 64, no. 1, pp. 15–26, Jan. 2024. 10.1002/pen.26045.
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XI. Li, J., X.-B. Zhang, and N. Recho, “J–Mp based criteria for bifurcation assessment of a crack in elastic–plastic materials under mixed mode I–II loading,” Engineering Fracture Mechanics, vol. 71, no. 3, pp. 329–343, 2004.
XII. Matvienko, Y. G., A. S. Chernyatin, I. A. Razumovsky, H. J. Shi, and Z. X. Wang, “The effect of thickness on components of the nonsingular T-stress under mixed mode loading,” in Proc. of the 13th Int. Conf. on Fracture, Beijing, China, 2013.
XIII. Miao, X.-T., Q. Yu, C.-Y. Zhou, J. Li, Y.-Z. Wang, and X.-H. He, “Experimental and numerical investigation on fracture behavior of CTS specimen under I–II mixed mode loading,” European Journal of Mechanics – A/Solids, vol. 72, pp. 235–244, 2018.
XIV. Mu, M. Y., G. Z. Wang, S. T. Tu, and F. Z. Xuan, “Three-dimensional analyses of in-plane and out-of-plane crack-tip constraint characterization for fracture specimens,” Fatigue and Fracture of Engineering Materials and Structures, vol. 39, no. 12, pp. 1461–1476, 2016.
XV. Nasrnia, M. and F. H. Aboutalebi, “Experimental investigation and numerical simulations of U-notch specimens under mixed mode loading by the conventional and extended finite element methods,” Archive of Applied Mechanics, 2018. 10.1007/s00419-018-1381-y.
XVI. Nguyen, H. T., S. M. Nguyen, and J. D. Kim, “Evaluation of mixed-mode fracture properties of aerospace-grade aluminum alloys under varying thermal conditions,” J. Mater. Eng. Perform., vol. 32, no. 2, pp. 225–234, Feb. 2023. 10.1007/s11665-022-3015-8.
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Journal Vol – 20 No – 7, July 2025

EXTRACTION OF NEW EXACT TRAVELING WAVE SOLUTIONS OF THE (3+1)-DIMENSIONAL GENG EQUATION BY EMPLOYING TWO EXPANSION STRATEGIES IN MATHEMATICAL PHYSICS

Authors:

Tozam Hossain, J. R. M. Borhan, Md. Mamun Miah

DOI NO:

https://doi.org/10.26782/jmcms.2025.07.00006

July 14, 2025

Abstract:

We inspect a nonlinear partial differential equation, known as the Geng equation, which captures the behavior of systems such as shallow water wave dynamics and quantum field interactions and has notable applications in the areas of engineering sciences, mechanics, and quantum mechanics in the present research work. Multiple exact wave solutions are determined for the Geng equation by utilizing two effective strategies, namely, (G^'/(G^'+G+A))-expansion and two variables (G'⁄G,1⁄G)-expansion strategies. The solutions derived are formulated through elementary functions having rational, hyperbolic, exponential, and trigonometric forms. With specific values of chosen constants, the graphic representations of the obtained exact wave solutions are depicted using density, contour, 2D, and 3D plots to illuminate the inherent structure of the phenomenon. Additionally, we obtained kink-shaped, anti-kink-shaped, compacton, and singular-periodic-shaped solitons. The findings demonstrate that the mentioned strategies serve as influential mathematical tools and are shown to be highly efficient, computationally adaptable, and easily manageable for exploring solutions of nonlinear partial differential equations in mathematical physics.

Keywords:

The (3+1) - dimensional Geng equation,the exact travelling wave solutions,the (G^'/(G^'+G+A))-expansion strategy,the two variables (G'⁄G,1⁄G)-expansion strategy.,

Refference:

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II. Ahmed, Sarfaraz, et al. “Shallow-Water Wave Dynamics: Butterfly Waves, X-Waves, Multiple-Lump Waves, Rogue Waves, Stripe Soliton Interactions, Generalized Breathers, and Kuznetsov–Ma Breathers.” Fractal and Fractional 9.1 (2025): 31. 10.3390/fractalfract9010031
III. Akram, Ghazala, et al. “Simulations of exact explicit solutions of simplified modified form of Camassa–Holm equation.” Optical and Quantum Electronics 56.6 (2024): 1037. 10.1007/s11082-024-06940-4
IV. Akram, Ghazala, et al. “The dynamical study of Biswas–Arshed equation via modified auxiliary equation method.” Optik 255 (2022): 168614. 10.1016/j.ijleo.2022.168614
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VI. Ali, Mohammed, et al. “A variety of new periodic solutions to the damped (2+ 1)-dimensional Schrodinger equation via the novel modified rational sine–cosine functions and the extended tanh–coth expansion methods.” Results in Physics 37 (2022): 105462. 10.1016/j.rinp.2022.105462
VII. Alraddadi, Ibrahim, et al. “Dynamical Behaviors and Abundant New Soliton Solutions of Two Nonlinear PDEs via an Efficient Expansion Method in Industrial Engineering.” Mathematics 12.13 (2024): 2053. 10.3390/math12132053
VIII. Benoudina, Nardjess, et al. “New study of (3+1)-dimensional nonlinear evolution equation with main part mKdV equation and novel solitary wave solutions.” International Journal of Modern Physics B 38.22 (2024): 2450293. 10.1142/S021797922450293X
IX. Borhan, J. R. M., et al. “Abundant Closed-Form Soliton Solutions to the Fractional Stochastic Kraenkel–Manna–Merle System with Bifurcation, Chaotic, Sensitivity, and Modulation Instability Analysis.” Fractal and Fractional 8.6 (2024): 327. 10.3390/fractalfract8060327
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XVII. Hong, B., et al. “The G′/(G′+ G+ A)-expansion method for two types of nonlinear Schrödinger equations.” J. Math. Phys 31.5 (2019): 1155-1156.
XVIII. Iqbal, M. Ashik, et al. “New soliton solutions of the mZK equation and the Gerdjikov-Ivanov equation by employing the double (G′/G,1/G)-expansion method.” Results in Physics 47 (2023): 106391. 10.1016/j.rinp.2023.106391
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XXIII. Kumar, Dharmendra, et al. “Some new periodic solitary wave solutions of (3+ 1)-dimensional generalized shallow water wave equation by Lie symmetry approach.” Computers & Mathematics with Applications 78.3 (2019): 857-877. 10.1016/j.camwa.2019.03.007
XXIV. Kumar, Sachin, et al. “Generalised exponential rational function method for obtaining numerous exact soliton solutions to a (3+ 1)-dimensional Jimbo–Miwa equation.” Pramana 95.4 (2021): 152. 10.1007/s12043-021-02174-1
XXV. Li, Bang-Qing, et al. “Hybrid soliton and breather waves, solution molecules and breather molecules of a (3+1)-dimensional Geng equation in shallow water waves.” Physics Letters A 463 (2023): 128672. 10.1016/j.physleta.2023.128672
XXVI. Li, Nan, et al. “Data-driven localized waves of a nonlinear partial differential equation via transformation and physics-informed neural network.” Nonlinear Dynamics 113.3 (2025): 2559-2568. 10.1007/s11071-024-10359-7
XXVII. Ling, Liming, et al. “Inverse scattering and soliton solutions of nonlocal complex reverse-spacetime modified Korteweg-de Vries hierarchies.” Symmetry 13.3 (2021): 512. 10.3390/sym13030512
XXVIII. Lü, Hai-Ling, et al. “A generalized (G′/G)-expansion method and its applications to nonlinear evolution equations.” Applied Mathematics and Computation 215.11 (2010): 3811-3816. 10.1016/j.amc.2009.11.021
XXIX. Mamun, Abdulla-Al, et al. “Solitary and periodic wave solutions to the family of new 3D fractional WBBM equations in mathematical physics.” Heliyon 7.7.e07483(2021). 10.1016/j.heliyon.2021.e07483
XXX. Manafian, Jalil, et al. “Comparison between the generalized tanh–coth and the (G′/G)-expansion methods for solving NPDEs and NODEs.” Pramana 87 (2016): 1-14. 10.1007/s12043-016-1292-9
XXXI. Miah, M. Mamun, et al. “Chaotic Phenomena, Sensitivity Analysis, Bifurcation Analysis, and New Abundant Solitary Wave Structures of The Two Nonlinear Dynamical Models in Industrial Optimization.” Mathematics 12.13 (2024): 1959. 10.3390/math12131959
XXXII. Miah, M. Mamun, et al. “New applications of the two variable (G′/G, 1/G)-expansion method for closed form traveling wave solutions of integro-differential equations.” Journal of Ocean Engineering and Science 4.2 (2019): 132-143. 10.1016/j.joes.2019.03.001
XXXIII. Murad, Muhammad Amin Sadiq, et al. “Optical soliton solutions for time-fractional Ginzburg–Landau equation by a modified sub-equation method.” Results in Physics 53 (2023): 106950. 10.1016/j.rinp.2023.106950
XXXIV. Radha, B., et al. “Retracted article: The homogeneous balance method and its applications for finding the exact solutions for nonlinear equations.” Journal of Ambient Intelligence and Humanized Computing 12.6 (2021): 6591-6597. 10.1007/s12652-020-02278-3
XXXV. Rani, Mehwish, et al. “Traveling wave solutions of (3+1)-dimensional Boiti–Leon–Manna–Pempinelli equation by using improved tanh (ϕ/2)-expansion method.” Partial Differential Equations in Applied Mathematics 6 (2022): 100394. 10.1016/j.padiff.2022.100394
XXXVI. Rani, Mehwish, et al. “New exact solutions for nonlinear fourth-order Ablowitz–Kaup–Newell–Segur water wave equation by the improved tanh (φ(ξ)/2)-expansion method.” International Journal of Modern Physics B 37.05 (2023): 2350044. 10.1142/S0217979223500443
XXXVII. Rehman, Hamood Ur, et al. “Analysis of Brownian motion in stochastic Schrödinger wave equation using Sardar sub-equation method.” Optik 289 (2023): 171305. 10.1016/j.ijleo.2023.171305
XXXVIII. Shakeel, Muhammad, et al. “Application of modified exp-function method for strain wave equation for finding analytical solutions.” Ain Shams Engineering Journal 14.3 (2023): 101883. 10.1016/j.asej.2022.101883
XXXIX. Wang, Kang-Jia, et al. “Novel complexiton solutions to the new extended (3+1)-dimensional Boiti-Leon-Manna-Pempinelli equation for incompressible fluid.” Europhysics Letters 146.6 (2024): 62003. 10.1209/0295-5075/ad59c1
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XLIII. Younas, Usman, et al. “On the collision phenomena to the (3+ 1)-dimensional generalized nonlinear evolution equation: Applications in the shallow water waves.” The European Physical Journal Plus 137.10 (2022): 1166. 10.1140/epjp/s13360-022-03401-3

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Journal Vol – 20 No – 7, July 2025

PERFORMANCE ANALYSIS OF LARGE LANGUAGE MODELS IN DIALOGUE PROCESSING SYSTEMS FOR LOW-RESOURCE LANGUAGES COMPARED TO ENGLISH LANGUAGE

Authors:

Sauvik Bal, Lopa Mandal

DOI NO:

https://doi.org/10.26782/jmcms.2025.07.00007

July 14, 2025

Abstract:

This study investigates the performance of dialogue processing systems in low-resource languages, specifically Bengali and Hindi, using advanced transformer-based models. English, a high-resource language, is used as a benchmark for comparison. Transformer models such as BERT, RoBERTa, FLAN-T5, DistilBERT, and GPT-2 are fine-tuned for question answering tasks across these languages. The evaluation includes metrics like F1 Score, Precision, Recall, and Exact Match to assess language-specific performance. The experiment reveals that GPT-2 delivers the highest exact match scores in Bengali and Hindi, while RoBERTa achieves superior F1 scores, indicating balanced performance. The study emphasizes the importance of monitoring training and validation losses to ensure effective model convergence and to identify overfitting. These findings highlight the potential of transformer models in improving dialogue systems for low-resource linguistic contexts.

Keywords:

Chatbots,Dialog processing system,LLM,Low resource languages,Transformer model,

Refference:

I. Banerjee, Somnath, Sudip Kumar Naskar, Paolo Rosso, and Sivaji Bndyopadhyay. “Classifier combination approach for question classification for Bengali question answering system.” Sādhanā 44 (2019): 1-14. 10.1007/s12046-019-1224-8.
II. Baykara, Batuhan, and Tunga Güngör. 2023. : ‘Turkish Abstractive Text Summarization Using Pretrained Sequence-to-Sequence Models’. Natural Language Engineering 29(5): 1275–1304. 10.1017/S1351324922000195.
III. Cao K., Cheng W., Hao Y., Gan Y., Gao R., Zhu J. and Wu J., 2024.: ‘DMSeqNet-mBART: a state-of-the-art adaptive-DropMessage enhanced mBART architecture for superior Chinese short news text summarization’. Expert Systems with Applications, 257, p.125095. 10.1016/j.eswa.2024.125095.
IV. Chouhan, Sanjay, Shubha Brata Nath, and Aparajita Dutta. : ‘HindiLLM: Large Language Model for Hindi’. In International Conference on Pattern Recognition, pp. 255-270. Springer, Cham, 2025, 10.1007/978-3-031-78172-8.

V. Dabre Raj, Shrotriya Himani, Kunchukuttan Anoop, Puduppully Ratish, Khapra Mitesh and Kumar Pratyush. 2022.: ‘IndicBART: A Pre-trained Model for Indic Natural Language Generation’. In Findings of the Association for Computational Linguistics: ACL 2022, Dublin, Ireland. Association for Computational Linguistics, pp. 1849–1863, 10.18653/v1/2022.findings-acl.145.
VI. Das, Arijit, and Diganta Saha. “Question Answering System Using Deep Learning in the Low Resource Language Bengali.” Convergence of Deep Learning In Cyber‐IoT Systems and Security (2022): 207-230. 10.1002/9781119857686.ch10.
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Journal Vol – 20 No – 7, July 2025