Background:Skin Psoriasis is a chronic autoimmune skin disorder the diagnosis and detection of which can be a challenging task because of its versatility in clinical presentation and it also resembles with many skin conditions. This disease may manifest in various ways in difference people and sometimes appears like eczema and tineacorporis. Furthermore in some areas the issue may be more challenging due to lack of access to specialized dermatology care..........

[1]. Parisi R, Symmons DPM, Griffiths CEM, Ashcroft DM. Global epidemiology of psoriasis: a systematic review of incidence and prevalence. J Invest Dermatol. 2013;133(2):377–85.
[2]. Bolognia, J. L., Schaffer, J. V., &Cerroni, L. (2018). Dermatology (4th ed.). Elsevier.
[3]. Aurangabadkar SJ., Comorbidities in Psoriasis, Indian J DermatolVenereolLeprol 2013; 79:10-17.
[4]. Rendon A, Schäkel K. Psoriasis Pathogenesis and Treatment. Int J Mol Sci. 2019 Mar 23;20(6):1475. doi: 10.3390/ijms20061475. PMID: 30909615; PMCID: PMC6471628.
[5]. Gisondi P, Bellinato F, Girolomoni G. Topographic Differential Diagnosis of Chronic Plaque Psoriasis: Challenges and Tricks. J Clin Med. 2020 Nov 8;9(11):3594. doi: 10.3390/jcm9113594. PMID: 33171581; PMCID: PMC7695211.

It has been established that Nigeria is endowed with a variety of lithium ores, coupled with global interest in lithium production due to growing demand as an alternative source of energy. Therefore, thermal treatment of the obtained concentrate for lithium carbonate production cannot be overemphasised. Spodumene concentrate obtained from Zankan lithium ore was subjected to a decrepitation process and a sulfuric acid extraction process was used to obtain lithium carbonate from beta spodumene, with Na2CO3 as the leaching agent. In the process, temperature differences (200 °C, 225 °C, 250 oC, 275 °C, and 300 °C) of the acid roasting show a considerable significance grade of lithium carbonate; the highest grade of 78% was extracted at 250 °C. This suggests effective production of Li2CO3 as a key substance in lithium-ion batteries, even though further refining could lead to a higher yield for energy applications.

[1]. N. K. Salakjani, P. Singh, and A. N. Nikoloski, "Production of lithium–A literature review. Part 2. Extraction from spodumene," Mineral Processing and Extractive Metallurgy Review, vol. 42, no. 4, pp. 268-283, 2021.
[2]. P. K. Choubey, M.-s. Kim, R. R. Srivastava, J.-c. Lee, and J.-Y. Lee, "Advance review on the exploitation of the prominent energy-storage element: Lithium. Part I: From mineral and brine resources," Minerals Engineering, vol. 89, pp. 119-137, 2016.
[3]. N. K. Salakjani, P. Singh, and A. N. Nikoloski, "Production of lithium–A literature review part 1: Pretreatment of spodumene," Mineral Processing and Extractive Metallurgy Review, vol. 41, no. 5, pp. 335-348, 2020.
[4]. C. Dessemond, F. Lajoie-Leroux, G. Soucy, N. Laroche, and J.-F. Magnan, "Spodumene: The lithium market, resources and processes," Minerals, vol. 9, no. 6, p. 334, 2019.

Marriage is the union of two adults who, along with their families, form a union and, as a result, provide matrimony legal status. This union is known as a "holy union" in Indian civilization because the people here believe that it is solemnised in the presence of the Gods.But when such partnerships are solemnised by particular traditional or customary procedures, they are considered to be full. Here the main objective of the study is to find out The ceremonies performed in the Hindu marriage .The researcher has followed the Empirical research method using convenient sampling method.The sample size of the study is 201.The result observed from the study is that most people are aware about all the ceremonies I.e. Kanyadan, Saptapadi and Sagai.Religion shapes people's perspectives on particular issues and has an impact on a number of institutions, including the institution of marriage. Personal freedom and a person's needs are given a lot of weight in the individualistic culture.

[1]. Ramalinggam Rajamickam ,Hindu Marriage and its position in the Malaysian Marriage law, International Journal of Arts and Commerce, October 2012, Vol 1, Issue 5.
[2]. R. T. Smith and C. Jayawardena,Hindu Marriage Customs in British Guiana,Social and Economic Studies, June 1958, Vol 7, Issue 2, PP: 178-194, DOI:https://www.jstor.org/stable/27851148.
[3]. M.P.Chandrika(2015),Ceremony and Valid Marriage among the Hindus-A Dichotomy,International Journal of Law and Legal Jurisprudence Studies, ISSN:2348-8212 ,Volume 2 ,Issue 3
[4]. Louis Dumont(1999),Dowry in Hindu Marriage As a Social Scientist Sees It, the economic weekly,Volume3,Issue 2
[5]. Shailaja Rawal (2020), Essential Ceremonies in Hindu Marriage: A Sanskara or a Tool in the Hands of Judiciary to Thwart Gender Equality,International journal of Law Management &~ Human,Vol. 3 , Issue 4

This study develops an explainable machine learning model to enhance the accuracy and transparency of pneumonia diagnosis. The research addresses the critical "black-box" problem in clinical AI by integrating the Boruta algorithm for robust feature selection with a Random Forest classifier for prediction. The pipeline employs SHAP (SHapley Additive exPlanations) for global and local interpretability and LIME (Local Interpretable Model-agnostic Explanations) for intuitive, case-specific rationales..........

[1]. Ahmad, T., Munir, A., Bhatti, S. H., Aftab, M., & Raza, M. A. (2022). A hybrid random forest and support vector machine model
for robust pneumonia prediction from clinical data. Healthcare Informatics Research, 28(1), 45– 54. https://doi.org/10.4258/hir.2022.28.1.45
[2]. Ahmed, S. F., & Al-Mistarehi, A. H. (2024). A comparative analysis of deep learning and ensemble models for the detection of
pneumonia from chest X-ray images. Journal of Digital Imaging, 37(1), 235–248. https://doi.org/10.1007/s10278-023-00922-w

Continuous streams of pressure, temperature, vibration and sound readings are produced by downhole sensors and are essential for monitoring production performance and wellbore integrity. The efficiency of traditional supervised machine learning techniques for anomaly detection is limited by expensive, time-consuming, and often unavailable manual labeling of such data. To identify anomalous operating conditions without labeled examples, this work proposes a self-supervised learning (SSL) system that utilizes unlabeled downhole sensor information. The framework learns robust feature representations that capture operational.........

[1]. Abdullah, M., Rahman, F. & Said, A. (2023) 'Self-supervised feature learning for industrial IoT anomaly detection', IEEE Internet of Things Journal, 10(4), pp. 3550–3562.
[2]. Alkan, F., Yilmaz, S. & Ozturk, I. (2021) 'Noise reduction techniques for high-frequency drilling data', Journal of Petroleum Science and Engineering, 206, 109011.
[3]. Al-Shammari, M. & Li, X. (2022) 'Unsupervised detection of drilling dysfunctions using temporal clustering', Energy Reports, 8, pp. 2335–2344.
[4]. Chen, Y., Li, D. & Khoshnevis, B. (2021) 'Machine learning for fault detection in drilling operations', Journal of Energy Resources Technology, 143(9), 093001.
[5]. Gao, P. & Kanevsky, D. (2020) 'Downhole analytics for drilling performance optimisation', SPE Journal, 25(4), pp. 1912–1924.

Hydraulic fracturing generates a complex network of fractures that controls hydrocarbon flow and, hence, the production performance in unconventional reservoirs. While numerical simulation is able to characterize such fracture networks, it is computationally intensive and hence difficult to use in real-time decision-making. The present study develops a GNN-based approach to model hydraulic fracture connectivity and predict well production performance. Simulation results of 3D discrete fracture network (DFN) systems were converted into graph representations and nodes are fracture segments and edges are connection indicators.........

[1]. Chen, Y., Li, B., & Zhao, X. (2023).Machine learning approaches for production forecasting in unconventional reservoirs: A review and future directions.Journal of Petroleum Science and Engineering, 224, 111238.https://doi.org/10.1016/j.petrol.2022.111238
[2]. Cipolla, C. L., Warpinski, N. R., & Mayerhofer, M. J. (2020a).Hydraulic fracture complexity: Diagnosis, remediation, and prediction. SPE Production & Operations, 35(3), 496–512. https://doi.org/10.2118/199746-PA
[3]. Cipolla, C. L., Warpinski, N. R., & Mayerhofer, M. J. (2020b).The relationship between fracture complexity, reservoir properties,
and fracture treatment design.SPE Production & Operations, 35(3), 456–468.
[4]. Jiang, H., Wang, Y., & Lin, C. (2023).Modeling hydraulic fracture propagation in heterogeneous formations using coupled numerical simulations.Journal of Natural Gas Science and Engineering, 112, 104615.https://doi.org/10.1016/j.jngse.2022.104615
[5]. King, G. E. (2019). Hydraulic fracturing 101: What every representative, environmentalist, regulator, reporter, investor, university researcher, neighbor and engineer should know about estimating frac risk and improving frac performance in unconventional gas and oil wells.SPE Hydraulic Fracturing Technology Conference.https://doi.org/10.2118/152596-MS

The fact that the data owners outsource their data to external service providers introduces many security and privacy issues. Among them, the most significant research questions relate to data confidentiality and user privacy. Encryption was regarded as a solution for data confidentiality. The privacy of a user is characterized by the query he poses to the server and its result. We explore the techniques to execute the SQL query over the encrypted data without revealing to the server any information about the query such as the query type or the query pattern, and its result........

[1]. "A Generic Data Privacy Approach for Relational Databases and Data Warehouses" – Rahul Kumar Sharma & Vivek Kapoor (2023).
[2]. "J. H. Yu and Z. M. Zhou, Components and development in big data system" - J. Electr. Sci. Technol., vol. 17, no. 1, pp. 51–72, (2019)
[3]. "Experiments & Analysis of Privacy-Preserving SQL Query Sanitization Systems" – Loïs Ecoffet, Veronika Rehn-Sonigo, Jean- François Couchot & Catuscia Palamidessi (2025).
[4]. "CryptDB: Protecting Confidentiality with Encrypted Query Processing" – Raluca Ada Popa, Catherine M. S. Redfield, Nickolai Zeldovich & Hari Balakrishnan (2011).
[5]. "Unstructured data big data using map reduce"- V. Subramaniyaswamy, V. Vijayakumar, R. Logesh, and V. Indragandhi, vol. 50, pp. 456–465, (2015).

Industry 5.0 advances a human-centric and sustainability-driven vision of smart manufacturing, yet empirical evidence that links ergonomic system design to measurable environmental performance remains limited. This study develops and validates a multilevel data analytics framework that connectsHuman–Robot Collaboration (HRC), cognitive load dynamics, productivity variability, and sustainability outcomes in digitally integrated manufacturing environments. Data were collected from 12 smart factories across automotive, electronics, and precision assembly sectors, comprising 486 operators and 18,742 task cycles over 14 months........

[1]. Ajaefobi, J. O., and Okpala, C. C. (2026). Optimization of smart manufacturing systems through renewable energy integration and sustainable material utilization. International Journal of Engineering Inventions, 15(2). https://www.ijeijournal.com/papers/Vol15-Issue2/15021832.pdf
[2]. Attaran, M. (2017). The rise of 3-D printing: The advantages of additive manufacturing over traditional manufacturing. Business Horizons, 60(5), 677–688. https://doi.org/10.1016/j.bushor.2017.05.011
[3]. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108
[4]. Chukwumuanya, E. O., Okpala, C. C., andOnukwuli, S. K. (2025a). Ergonomics-aware scheduling: Biomechanical models with production planning integration for musculoskeletal risk reduction. Journal MajelisPaspama, 3(1). https://paspama.org/index.php/majelis/article/view/209
[5]. Chukwumuanya, E. O., Udu, C. E., and Okpala, C. C. (2025b). Lean principles integration with digital technologies: A synergistic approach to modern manufacturing. International Journal of Industrial and Production Engineering, 3(2). https://journals.unizik.edu.ng/ijipe/article/view/6006/5197

The rapid diffusion of Industry 4.0 technologies likeArtificial Intelligence (AI), the Internet of Things (IoT), big data analytics, and digital twinshave transformed how organizations pursue operational excellence and sustainability. Six Sigma, traditionally grounded in statistical process control and structured DMAIC problemsolving, is increasingly being augmented by these digital capabilities, and thus giving rise to what is often termed Digital Six Sigma or Six Sigma 4.0. This study presents a comprehensive bibliometric and benchmarking review of 214 peer-reviewed publications that were published between..........

[1]. Aguh, P. S., and Okpala, C. C. (2025). Learning in the age of artificial intelligence tutors: Cognitive outcomes and equity in automated education systems. International Journal of Engineering Research and Development, 21(12). https://ijerd.com/paper/vol21-issue12/21128898.pdf
[2]. Aguh, P. S., Udu, C. E., Chukwumuanya, E. O., and Okpala, C. C. (2025). Machine learning applications for production scheduling optimization. Journal of Exploratory Dynamic Problems, 2(4). https://edp.web.id/index.php/edp/article/view/137
[3]. Antony, J. (2006). Six Sigma for service processes. Business Process Management Journal, 12(2), 234–248.
[4]. Chiarini, A., and Kumar, M. (2020). Lean Six Sigma and Industry 4.0 integration for operational excellence: Evidence from manufacturing. Total Quality Management and Business Excellence, 31(13–14), 1–16.
[5]. Chukwumuanya, E. O., and Okpala, C. C. (2025). Responsible artificial intelligence for global challenges: Frameworks for fairness, transparency, and policy impact. International Journal of Engineering Research and Development, 21(12). https://ijerd.com/paper/vol21-issue12/21127787.pdf

Manufacturing firms are increasingly required to achieve high equipment reliability while simultaneously reducing energy consumption, material waste, and carbon emissions. Although Total Productive Maintenance (TPM) has historically improved equipment effectiveness, its traditional preventive orientation limits responsiveness in digitally intensive production environments. This study proposes and empirically validates a Data-Driven Predictive TPM (P-TPM) framework that integrates Industrial Internet of Things (IIoT) sensing, hybrid machine learning, digital twin simulation, and explainable artificial intelligence to optimize Overall Equipment Effectiveness (OEE) while delivering measurable sustainability gains..........

[1]. Ahuja, I. P. S., & Khamba, J. S. (2008). Total productive maintenance: Literature review and directions. International Journal of
Quality & Reliability Management, 25(7), 709–756. https://doi.org/10.1108/02656710810890890
[2]. Ajaefobi, J. O., & Okpala, C. C. (2026). Optimization of smart manufacturing systems through renewable energy integration and
sustainable material utilization. International Journal of Engineering Inventions, 15(2). https://www.ijeijournal.com/papers/Vol15-Issue2/15021832.pdf
[3]. Bousdekis, A., Apostolou, D., & Mentzas, G. (2021). A proactive event-driven decision model for joint equipment predictive maintenance and spare parts inventory optimization. Procedia CIRP, 99, 531–536. https://doi.org/10.1016/j.procir.2021.03.072
[4]. Carvalho, T. P., Soares, F. A. A. M. N., Vita, R., Francisco, R. D. P., Basto, J. P., & Alcalá, S. G. S. (2019). A systematic literature review of machine learning methods applied to predictive maintenance. Computers & Industrial Engineering, 137, 106024. https://doi.org/10.1016/j.cie.2019.106024
[5]. Chukwumuanya, E. O., Okpala, C. C., & Udu, C. E. (2025b). Carbon accounting at the shop-floor: The integration of real-time energy monitoring, process modeling and LCA for net-zero targets. Jurnal Teknik Indonesia, 4(1). https://jurnal.seaninstitute.or.id/index.php/juti/article/view/728

Antibiotic contamination of aquatic systems has emerged as a critical environmental driver of Antimicrobial Resistance (AMR), as it intensifies global concerns over water security and public health. Despite rapid advances in adsorption-based treatment technologies, comparative evaluation remains fragmented, with limited integration of sustainability and scalability metrics. This study presents a PRISMA-guided global systematic review of 412 peer-reviewed articles that were published between 2000 and 2025, and synthesizes performance data across five major antibiotic classes and six adsorbent categories. Adsorption capacities ranged from 50 to 1,200 mg g⁻ ¹, with Metal–Organic Frameworks (MOFs) and carbon nanomaterials demonstrating the highest laboratory-scale efficiencies.........

[1]. Ahmed, M. B., Zhou, J. L., Ngo, H. H., Guo, W., & Chen, M. (2015). Progress in the biological and chemical treatment technologies for emerging contaminant removal from wastewater: A critical review. Journal of Hazardous Materials, 282, 52–77. https://doi.org/10.1016/j.jhazmat.2014.06.045
[2]. Arena, U., Di Gregorio, F., & Santonastasi, M. (2016). Life cycle assessment of activated carbon production from waste materials. Journal of Cleaner Production, 132, 295–305.
[3]. Berendonk, T. U., Manaia, C. M., Merlin, C., Fatta-Kassinos, D., Cytryn, E., Walsh, F., … Martinez, J. L. (2015). Tackling antibiotic resistance: The environmental framework. Nature Reviews Microbiology, 13(5), 310–317. https://doi.org/10.1038/nrmicro3439
[4]. Bhatnagar, A., Hogland, W., Marques, M., & Sillanpää, M. (2013). An overview of the modification methods of activated carbon for its water treatment applications. Chemical Engineering Journal, 219, 499–511.
[5]. Chukwumuanya, E. O., Okpala, C. C., & Udu, C. E. (2025). Carbon accounting at the shop-floor: The integration of real-time energy monitoring, process modeling and LCA for net-zero targets. Jurnal Teknik Indonesia, 4(1). https://jurnal.seaninstitute.or.id/index.php/juti/article/view/728

Global supply chains are increasingly exposed to overlapping and systemic disruptions which arise from climate change, geopolitical conflicts, and pandemics, thereby challenge traditional risk management and sustainability strategies. Recent crises have revealed that reactive and static resilience approaches often exacerbate environmental impacts while failing to ensure continuity under compound shocks. This study proposes an integrated AI-driven risk modeling and optimization framework that is designed to enhance supply chain resilience, while delivering measurable sustainability benefits...........

[1]. Aguh, P. S., and Okpala, C. C. (2025). Learning in the age of artificial intelligence tutors: Cognitive outcomes and equity in automated education systems. International Journal of Engineering Research and Development, 21(12). https://ijerd.com/paper/vol21-issue12/21128898.pdf
[2]. Aguh, P. S., Udu, C. E., Chukwumuanya, E. O., and Okpala, C. C. (2025). Machine learning applications for production scheduling optimization. Journal of Exploratory Dynamic Problems, 2(4). https://edp.web.id/index.php/edp/article/view/137
[3]. Baryannis, G., Dani, S., and Antoniou, G. (2019). Predicting supply chain risks using machine learning: The trade-off between performance and interpretability. Future Generation Computer Systems, 101, 993–1004. https://doi.org/10.1016/j.future.2019.07.017
[4]. Brandenburg, M., Govindan, K., Sarkis, J., andSeuring, S. (2014). Quantitative models for sustainable supply chain management :
Developments and directions. European Journal of Operational Research, 233(2), 299–312. https://doi.org/10.1016/j.ejor.2013.09.032
[5]. Choi, T. M., Wallace, S. W., and Wang, Y. (2021). Big data analytics in operations management. Production and Operations Management, 30(10), 2918–2934. https://doi.org/10.1111/poms.13448

Spotting people in busy settings matters more now, thanks to uses like city monitoring, keeping crowds safe, helping machines understand humans, and watching video feeds. Figuring out who is who gets tough when bodies block each other, lighting shifts, angles change, visuals are fuzzy, or surroundings get messy. This summary digs into up-to-date methods that aim to name persons in packed scenes - pulling apart how these tools work on photos and footage, mainly through code built with Python and powered by OpenCV. Starting off, the article outlines key steps in identifying people: spotting a person first, pulling out distinguishing traits, then matching that identity...........

[1]. Sun, D., Huang, J., Hu, L., Tang, J., & Ding, Z. (2022). ―Multitask Multigranularity Aggregation with Global Guided Attention for Video Person Re-Identification‖. IEEE Transactions on Circuits and Systems for Video Technology, 32(11), 7758–7771.
[2]. Jia, M., Cheng, X., Lu, S., & Zhang, J. (2022). ―Learning Disentangled Representation Implicitly via Transformer for Occluded Person Re-Identification‖. IEEE Transactions on Multimedia, 2022.
[3]. (IEEE) ―Structure-aware Positional Transformer for Visible-Infrared Person Re-Identification‖ — Chen et al., IEEE Transactions on Image Processing (2022). Useful when multi-sensor surveillance is used in crowds

Potable water security represents one of the most critical public health challenges in coastal Sub-Saharan Africa, yet the shallow unconfined aquifers of the Niger Delta Basin remain among the least-protected freshwater systems on the continent. This review synthesizes hydrogeochemical and bacteriological data from hand-dug wells and riverine systems across four communities in the Obio/Akpor Local Government Area, Rivers State, Nigeria—Choba, Rumuokparali, Rumuekini, and Ozuoba—with the objective of characterizing the compounded threat landscape confronting the Benin Formation aquifer. Measured pH values ranging from 4.60 to 5.78 confirm a state of critical aquifer acidification that falls far below..........

[1]. American Public Health Association (APHA). (2012). Standard methods for the examination of water and wastewater (22nd ed.). American Water Works Association.
[2]. Appelo, C. A. J., & Postma, D. (2005). Geochemistry, groundwater and pollution (2nd ed.). A.A. Balkema.
[3]. Atekwana, E. A., & Atekwana, E. A. (2010). Geophysical signatures of microbial activity at hydrocarbon contaminated sites: A review. Surveys in Geophysics, 31(2), 247–283. https://doi.org/10.1007/s10712-009-9089-8
[4]. Bouchard, M. F., Sauvé, S., Barbeau, B., Legrand, M., Brodeur, M. È., Bouffard, T., & Mergler, D. (2011). Intellectual impairment in school-age children exposed to manganese from drinking water. Environmental Health Perspectives, 119(1), 138–143. https://doi.org/10.1289/ehp.1002321

Process improvement techniques are constantly sought after by the software business in an effort to increase delivery speed, lower faults, and improve quality. Two of the most well-known strategies are Agile, an adaptable framework that prioritizes flexibility and customer collaboration, and Six Sigma, a data-driven methodology centered on defect reduction. Despite having the same goal of enhancing software development results, their implementation, philosophy, and applicability for various project circumstances vary greatly..........

[1] Gonen B. and Sawant D. (2020). Significance of Agile Software Development and SQA Powered by Automation. In 2020 3rd International Conference on Information and Computer Technologies – ICICT, pp. 7-11.
[2] Jain P., Sharma A., and Ahuja L. (2018). The Impact of Agile Software Development Process on the Quality of Software Product. In 2018 7th International Conference on Reliability, Infocom Technologies and Optimization: Trends and Future Directions – ICRITO, pp. 812-815.
[3] Saleh S., Huq S., and Rahman M. (2019). Comparative Study within Scrum, Kanban, XP Focused on Their Practices. In 2019 International Conference on Electrical, Computer and Communication Engineering – ECCE, pp. 1-6.
[4] Sharma P., and Hasteer N. (2016). Analysis of linear sequential and extreme programming development methodology for a gaming application. In 2016 International Conference on Communication and Signal Processing – ICCSP, pp. 1916-1920.
[5] H. Edison, X. Wang and K. Conboy, "Comparing Methods for Large-Scale Agile Software Development: A Systematic Literature Review," in IEEE Transactions on Software Engineering, vol. 48, no. 8, pp. 2709- 2731, 1 Aug. 2022, doi: 10.1109/TSE.2021.3069039.

The concept of wet dark fluid has emerged as a promising alternative to conventional dark energy models in modified gravity theories. This review examines the theoretical framework, cosmological implications, and observational constraints of wet dark fluid models within various modified gravity theories including f(R), f(T), f(Q), and f(R, T) gravity. The wet dark fluid equation of state, modeled as 𝑝=𝛾(𝜌−𝜌0), exhibits liquid-like properties that can effectively describe the transition between different cosmological epochs. Recent investigations demonstrate that wet dark fluid models can successfully..........

[1]. Riess, A. G., et al. (1998). Observational evidence from supernovae for an accelerating universe and a cosmological constant. Astronomical Journal, 116(3), 1009-1038.
[2]. Perlmutter, S., et al. (1999). Measurements of Omega and Lambda from 42 high-redshift supernovae. Astrophysical Journal, 517(2), 565-586.
[3]. Weinberg, S. (1989). The cosmological constant problem. Reviews of Modern Physics, 61(1), 1-23.

Surface runoff estimation is a key component of hydrological modeling in watersheds exposed to flooding and land-use variability. In this context, the Soil Conservation Service Curve Number (SCS-CN) method has been widely adopted as an effective approach for representing watershed hydrological response based on terrain, soil, and land-cover characteristics. This study aimed to derive the Curve Number map and weighted average CN values for the Río Grande watershed, considered as a case study within the Chone River basin, Ecuador, through the application of Geographic Information System tools..........

[1]. Ajith, A., & Kumar, D. (2024). Impact of land use and land cover changes on runoff generation in the Kidangoor watershed, Kerala. Journal of Water Management Modeling (JWMM), 32. https://doi.org/10.14796/JWMM.H522
[2]. Alsaidi, M., Ahmed Hamdam, A., & Yaseen, D. (2025). Runoff Modeling Using the GIS-Based Curve Number Method. The Eurasia Proceedings of Science, Technology, Engineering and Mathematics, 37, 754-764. https://doi.org/10.55549/epstem.1346
[3]. Cabrera, E., Minaya, F., Santisteban, L., Barreiro, D., Moreira, M., Giler, P., & Alcivar, F. (2016). Procesamieto estadístico de la lluvia, obtención de las curvas IFD y aguaceros sintéticos para la estación M0162 del INAMHI en Chone. Informe técnico parcial del proyecto de investigación: "Evaluación del funcionamiento integrado del sistema de alcantarillado pluvial de Chone", Universidad Laica Eloy Alfaro de Manabí. Extensión Chone, Chone.
[4]. Clavijo, H., Peñaherrera, C., & Andrade, L. (2013). Diseño de una red de estaciones meteorológicas e hidrológicas para previsión de crecidas e inundaciones, en las subcuencas de los ríos Chone, Portoviejo, Bulu-Bulu y Chongón [Bachelor Thesis]. Quito, Ecuador: Escuela Politécnica Nacional. Facultad de Ingeniería Civil y Ambiental. https://bibdigital.epn.edu.ec/handle/15000/6730
[5]. El Yousfi, Y., Himi, M., El Ouarghi, H., Aqnouy, M., Benyoussef, S., Gueddari, H., . . . Tahiri, A. (2023). GIS preprocessing for rainfall-runoff modeling using HEC-HMS in Nekkor watershed (Al-Hoceima, Northern Morocco). The 3ʳᵈ Edition of Oriental Days for the Environment "Green Lab. Solution for Sustainable Development" (JOE3).364. E3S Web of Conferences. EDP Sciences. https://doi.org/10.1051/e3sconf/202336401005

Moving goods by commercial truck fleets matters a lot in shipping products across regions. Still, problems pop up - drivers get tired, lose focus behind the wheel, fuel goes missing, packages vanish, and tough weather adds risk. Older tracking tools lean heavily on GPS signals plus remote computing, costing too much while slowing down updates. This study introduces a budget-friendly setup using many small sensors to watch both driver safety and fuel levels in delivery trucks. Inside it: an ESP32 chip runs things, joined by motion detectors, a camera unit based on ESP32, sound wave distance finder, smoke and gas sniffer, location signal receiver, mobile network link, and a basic fuel gauge..........

[1] A. Mohamed, K. Singh, and M. Patel, "Real-time driver drowsiness detection using deep facial landmark analysis," IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 5, pp. 2150–2159, May 2020.
[2] Y. Zhao, H. Liu, and J. Chen, "Head pose estimation for driver monitoring using low-cost inertial sensors," IEEE Sensors Journal, vol. 19, no. 12, pp. 4567–4575, June 2019.
[3] V. Ramachandran and P. Krishnamurthy, "Driver fatigue detection using PERCLOS and EEG-based features," in Proceedings of the IEEE International Conference on Signal Processing and Communication, Bangalore, India, 2021, pp. 112–117.
[4] S. Patel, A. Jain, and R. Verma, "Accelerometer-based driver behaviour classification for fleet monitoring," International Journal of Engineering Research and Technology, vol. 9, no. 4, pp. 112–118, April 2020.
[5] InvenSense Inc., "MPU-6000 and MPU-6050 Product Specification, Revision 3.4," TDK InvenSense, San Jose, CA, USA, 2013.

This study presents a comparative analysis of gas-based enhanced oil recovery (EOR) methods using fractionated associated gas in Middle Eastern carbonate reservoirs. The Nasiriyah oil field in Iraq, characterized by high-viscosity oil (15-25 cP) and heterogeneous carbonate formations, serves as the primary case study. Unlike Saudi Arabia and UAE strategies focusing on CO2-EOR, this research proposes using fractionated hydrocarbon gas enriched with C2-C6 components to reduce minimum miscibility pressure (MMP). An adaptive water-alternating-gas (WAG) process with variable gas composition was developed and evaluated through PVT modeling and hydrodynamic simulation..........

[1]. Al-Ameri, T. K., & Al-Zaidi, M. D. (2014). Geochemical Correlation of Mishrif Formation in AL-Nasiriyah Oil Field/South of Iraq. Iraqi Journal of Science, 55(2B), 750-759.
[2]. Aljibouri, R. D., et al. (2022). 3D geological modeling for Yamama reservoir in Al-Nasiriyah oil field. International Journal of Health Sciences, 6, 8949-8962.
[3]. Khashman, M. A., et al. (2025). Comparative evaluation of productivity indicators in carbonate reservoir modeling. Discover Geoscience, 3(1), 17.
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This paper presents the design, modeling, and simulation of a 10 MW hybrid microgrid system intended to improve electricity supply reliability in Onitsha, Nigeria. The proposed grid system integrates solar photovoltaic (PV) generation, wind energy conversion systems, battery energy storage systems (BESS), and a diesel generator backup, with the capability of operating in both grid-connected and islanded modes. MATLAB/Simulink was used to develop detailed system models and to evaluate the operational performance of the hybrid grid under varying renewable resource availability and load demand conditions...........

[1]. Agupugo, E., &Tochukwu, O. (2022). Economic analysis of renewable microgrids in Nigerian communities: Opportunities and challenges. International Journal of Energy and Power Systems, 12(3), 45–58. https://doi.org/
[2]. Guerrero, J. M., Chandorkar, M., Lee, T. L., &Loh, P. C. (2018). Advanced control architectures for intelligent microgrids. IEEE Transactions on Industrial Electronics, 60(4), 1254–1262.
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[5]. Lasseter, R. H. (2019). Smart distribution: Coupled microgrids. Proceedings of the IEEE, 99(6), 1074–1082.

Microstriata antennas are widely used in modern wireless communication systems due to theircompact size, low profile structure, light weight and ease of fabrication.The dual band Microsinta antenna operates at two distinct frequency bands such as 2.4 GHz and 5 GHz. The antenna consists of a radiating patch, dielectric substrate and ground plane. HFSS (High Frequency Structure Simulator) software is used for accurate electromagnetic simulation. Performance parameters such as Return Loss (S11), VSWR, Gain, Bandwidth, Radiation Pattern and Efficiency are analyzed in detail. The antenna design is based on transmission line model equations and electromagnetic field theory...........

[1]. Dr.Dola Sanjay S1, M.Gayathri2, N.Gayathri2, P.Vasantha2, Ch. SaiKiran Chandu2 "ANALYSIS OF EMISSION AND SUSCEPTIBILITY OF INTERFERENCE ON AIR TANK PRESSURE SENSOR USING MICROSTRIP LPF" © 2019 JETIR March 2019, Volume 6, Issue 3, JETIR1903F39, Journal of Emerging Technologies and Innovative Research (JETIR), pp 564-567, www.jetir.org (ISSN-2349-5162).
[2]. Dola Sanjay S, Prof. S Varadarajan" Radiated Emission Measurement of Microstrip Patch Antenna", National conference on Thrust areas in Engineering,Jan.2012.
[3]. ChMurali Krishna, Dr Dola Sanjay S "SRR Inspired Moore Antenna With Fractal Techniques For Multiband Applications" Test Engineering and Management Published by: The Mattingley Publishing Co.,
Inc. , Jan - Feb 2020 ISSN: 0193 - 4120 PP:11746 –11752.
[4]. Dr.SaidaiahBandi, Dr Dola Sanjay S, P. Triveni, V. Naga Deepika, V. Kali Krishna Nikhil, Venkata Naga sivasai, "Design And Simulation Of Ultra Wide And Narrow Band Antenna For C-Band And X-Band Applications" AIJREAS, ONLINE Anveshana's International Journal of Research in Engineering and Applied Sciences, ISSN:2455-6300, Volume 7, Issue V, May 2022.
[5]. Dola Sanjay S, Prof. S Varadarajan" AMSA as EMI/EMC Sensor", Journal of innovation in Electronics and Communication-Special Issue, Vol. 2, issue 2,ISSN:2249-9946, Jan.2012, 126-129.

Microsinta antennas are widely used in modern wireless communication systems due to thei rcompact size, low profile structure, light weight and ease of fabrication.The dual band Microsinta antenna operates at two distinct frequency bands such as 2.4 GHz and 5 GHz. The antenna consists of a radiating patch, dielectric substrate and ground plane. HFSS (High Frequency Structure Simulator) software is used for accurate electromagnetic simulation. Performance parameters such as Return Loss (S11), VSWR, Gain, Bandwidth, Radiation Pattern and Efficiency are analyzed in detail..........

[1]. Dr. Dola Sanjay S1, M.Gayathri2, N.Gayathri2, P.Vasantha2, Ch. Sai Kiran Chandu2 "ANALYSIS OF EMISSION AND SUSCEPTIBILITY OF INTERFERENCE ON AIR TANK PRESSURE SENSOR USING MICROSTRIP LPF" © 2019 JETIR March 2019, Volume 6, Issue 3, JETIR1903F39, Journal of Emerging Technologies and Innovative Research (JETIR), pp 564-567, www.jetir.org (ISSN-2349-5162).
[2]. Dola Sanjay S, Prof. S Varadarajan" Radiated Emission Measurement of Microstrip Patch Antenna", National conference on Thrust areas in Engineering,Jan.2012.
[3]. Ch Murali Krishna, Dr Dola Sanjay S "SRR Inspired Moore Antenna With Fractal Techniques For Multiband Applications" Test Engineering and Management Published by: The Mattingley Publishing Co., Inc. , Jan - Feb 2020 ISSN: 0193 - 4120 PP:11746 –11752.
[4]. Dr. Saidaiah Bandi, Dr Dola Sanjay S, P. Triveni, V. Naga Deepika, V. Kali Krishna Nikhil, Venkata Naga siva sai, "Design And Simulation Of Ultra Wide And Narrow Band Antenna For C-Band And X-Band Applications" AIJREAS, ONLINE Anveshana's International Journal of Research in Engineering and Applied Sciences, ISSN:2455-6300, Volume 7, Issue V, May 2022.

Unconventional and mature reservoir development continues to be based on hydraulic fracturing, but post-treatment production never meets the original predictions because of unpredicted geomechanical feedbacks caused by reservoir depletion. This review article is a compilation of a decade of rock mechanics advances (20152024) to systematically investigate how stress reorientation caused by depletion, the proppant embedment and the systematic loss of dynamic fracture conductivity are all contributing factors to the long-term well productivity in depleted unconventional reservoirs..........

[1]. Abass, H. H., Hedayati, S., & Meadows, D. L. (1996). Nonplanar fracture propagation from a horizontal wellbore: Experimental study. SPE Production & Facilities, 11(3), 133–137. https://doi.org/10.2118/24823-PA
[2]. Bandara, K. M. A. S., Ranjith, P. G., & Rathnaweera, T. D. (2019). Improved understanding of proppant embedment behavior under reservoir conditions: A review study. Powder Technology, 352, 170–192. https://doi.org/10.1016/j.powtec.2019.04.033
[3]. Bandara, K. M. A. S., Ranjith, P. G., & Rathnaweera, T. D. (2020). Laboratory-scale study on proppant behaviour in unconventional oil and gas reservoir formations. Journal of Natural Gas Science and Engineering, 78, Article 103329. https://doi.org/10.1016/j.jngse.2020.103329
[4]. Bennani, R., Wang, M., Wang, X., & Li, T. (2025). Porosity estimation using machine learning approaches for shale reservoirs: A case study of the Lianggaoshan Formation, Sichuan Basin, Western China. Journal of Applied Geophysics, 237, Article 105702. https://doi.org/10.1016/j.jappgeo.2025.105702
[5]. Chen, J., Xu, Z., & Leung, J. Y. (2022). Analysis of fracture interference — Coupling of flow and geomechanical computations with discrete fracture modeling using MRST. Journal of Petroleum Science and Engineering, 219, 111126. https://doi.org/10.1016/j.petrol.2022.110986