The Aeroleaf project is an innovative renewable energy solution that combines wind and solar power generation in a compact and efficient system. It is designed in the shape of a tree, where the leaf-like structures function as mini wind turbines while also integrating solar panels. This hybrid approach allows the system to generate electricity from both wind and sunlight, increasing overall energy efficiency and reliability...........

[1]. Hosseinian, S.M., Mohseni, M., & Karimi, M.S. Advanced blade profiles for improved efficiency in Savonius wind turbines: the Aeroleaf case study. Scientific Reports, 16, 1022.
[2]. Rathore, M.K., Agrawal, M., Baredar. Fabrication and Performance Analysis of the Aero-Leaf Savonius Wind Turbine Tree. Energies, 16(7), 3015.
[3]. Yadav, S., Mishra. Aero Leaf Wind Turbine Tree for Electricity Generation. IJSDR, Vol. 7, Issue 4, pp. 173–179.
[4]. Karimi, Hosseinian, & Mohseni, M. Performance comparison of Aeroleaf and conventional Savonius turbines. Scientific Reports.
[5]. Manwell, J.F., McGowan, J.G., & Rogers, A.L. Wind Energy Explained: Theory, Design and Application. Wiley.

The massive development in the Internet of Things deployments requires efficient methods for selecting optimal wireless protocols in conflicting situations. In this paper, the authors propose a hybrid Multi-Criteria Decision-Making model augmented with sensitivity analysis for selecting optimal IoT protocols. Five wireless protocols: Wi-Fi HaLow, NB-IoT, LoRaWAN, Sigfox, and Zigbee are considered in terms of Power consumption, Data Rate, Latency, Coverage range, and Cost. Robustness of ranking of the wireless protocols was tested by One-at-a-Time (OAT) sensitivity analysis by changing the value of criterion weights by ±10%. Results proved the robustness and reliability of the framework since.........

[1]. Ahmad, M., Hu, J., Ahmad, M., & Khurshid, F. (2019). Optimal Cluster Leader Selection Using MCDM Methods in MWSN: A comparative study. IEEE International Conference on Intelligent Systems and Knowledge Engineering, 240-247. https://doi.org/10.1109/ISKE47853.2019.9170426
[2]. Cui, H., Dong, S., Hu, J., Chen, M., Hou, B., Zhang, J., Zhang, B., Xian, J., & Chen, F. (2023). A hybrid MCDM model with Monte Carlo simulation to improve decision-making stability and reliability. Information Sciences, 647, 119439. https://doi.org/10.1016/j.ins.2023.119439
[3]. IHS Technology, (2016). IoT Platforms: Enabling the Internet of Things https://cdn.ihs.com/www/pdf/enabling_IoT.pdf
[4]. Radulescu, C. Z., & Radulescu, M. (2024). A Hybrid Group Multi-Criteria Approach Based on SAW, TOPSIS, VIKOR, and COPRAS Methods for Complex IoT Selection Problems. Electronics. https://doi.org/10.3390/electronics13040789

This study presents the design and simulation of a 4,000 MTPD Urea plant in Aspen HYSYS. The plant was first designed through detailed material to get per day requirement of 3,256.887 Tons of CO2 and 2,266.80152 Tons for NH3 to get the 4,000TPD at 99% urea purity. Conclusive energy balance gave heat duties for the different units was done and the Urea Reactor design gave a volume of 396.991m3 with a length of 80.86m. A simulation was developed for the high-pressure urea synthesis section of the plant. The validity of the simulation was demonstrated by comparing against plant data from the Indorama plant.........

[1]. Agarwal A., Patel R., & Kumar S. (2019). "Modeling and simulation of urea synthesis reactor: A thermodynamic and kinetic approach." Chemical Engineering Research and Design.
[2]. Agarwal, M., Gupta, R. & Saxena, R. K. (2008). "Kinetic modelling of Urea Synthesis Reactor". Chemical Engineering Journal,136(2–3),302 308
[3]. Ahmed, K., Osman, A., & Hassan, M. (2021). Dynamic simulation and analysis of urea synthesis processes using Aspen HYSYS: Start-up, shutdown, and upset scenarios. Journal of Chemical Engineering and Process Technology, 12(3), 415–429.
[4]. Alexandre C. D., (2003), "Computer Aided Chemical Engineering," Elsevier, (13) 33-58
[5]. Alexey L. V. & Gennady F. V, (2016), "Thermodynamic Model of the Urea Synthesis Process", Journal of Chemical and Engineering Data.

Urban flooding has become a persistent environmental challenge in many Nigerian cities due to poor drainage infrastructure, rapid urbanization, indiscriminate waste disposal, and increasing rainfall intensity associated with climate variability. This study presents a Geographic Information System (GIS) and Remote Sensing-based assessment of drainage channels and flood pathways within the extension area of Imo State University (IMSU), Owerri, Nigeria. The objectives of the study were to map the drainage network, identify flood-prone zones and flood pathways, evaluate the effectiveness of existing drainage systems, and develop a geospatial database for flood management and sustainable urban planning..........

[1]. Barde, M. M., Tukur, A. L., &Mubi, M. A. (2019).Detection and mapping of flood prone areas of Jimeta, Adamawa State, Nigeria using GIS techniques.Journal of Environmental Sciences, 12(4), 45–58.
[2]. Eteh, D. R., &Okpobiri, O. (2021). Floodplain mapping and risk assessment of the Orashi River using remote sensing and GIS in the Niger Delta region, Nigeria. Journal of Geology and Environmental Management, 8(2), 66–80.
[3]. Ejikeme, J. O., &Idowu, S. B. (2024).Mapping and analysis of urban drainage system in Asaba Metropolis using remote sensing and geographic information system.International Journal of Geospatial Research, 11(1), 21–39.
[4]. Folorunsho, R., &Awosika, L. (2001).Flood mitigation and drainage system management in Nigeria.Environmental Management Journal, 6(2), 13–21.
[5]. Okorafor, O. O., Chibuike, M. I., Nwakuba, N. R., &Nwaobi, F. A. (2021).Mapping of flood prone areas in Imo State, South Eastern Nigeria using GIS techniques.Nigerian Journal of Environmental Sciences, 14(3), 102–118.

The rapid advancement of deep learning techniques has increased the demand for explainable models, particularly in critical domains such as medical image analysis where decision transparency is essential. This survey provides a comprehensive review of explainable artificial intelligence (XAI) approaches applied to deep learning-based medical image analysis. A structured XAI framework is proposed to categorize these methods based on specific explainability criteria. Existing research on XAI techniques in medical imaging is examined and organized according to the proposed framework as well as different anatomical regions. Finally, the survey highlights future research directions and emerging opportunities for XAI in medical image analysis.

[1] Arun, N., et al. (2021). Assessing the validity of saliency maps for explainable AI in medical imaging. Medical Image Analysis.
[2] Adadi, A., Berrada, M., 2018. Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI). IEEE Access 6, 52138–52160. doi:10.1109/ACCESS. 2018.2870052.
[3] D. T. Huff, A. J. Weisman, R. Jeraj, 2021. Interpretation and visualization techniques for deep learning models in medical imaging. Physics in Medicine & Biology, 66, 04TR01.
[4] Jia, X., et al. (2020). Explainable AI in medical imaging: Current status and future directions. Frontiers in Artificial Intelligence.
[5] Murdoch, W.J., Singh, C., Kumbier, K., Abbasi-Asl, R., Yu, B., 2019. Definitions, methods, and applications in interpretable machine learning. Proc. Natl. Acad. Sci. USA 116, 22071–22080. doi:10.1073/pnas.1900654116

The rapid rise of cybercrime, fraud, and network-related offenses has stressed manual forensic investigation to its limits. Investigators must now sift through massive amounts of digital data—disk images, packet captures, chat logs, and surveillance footage—under tight judicial deadlines. This task greatly exceeds what human analysts can do without computer support. To address this issue, this paper introduces AI-FAF (Artificial Intelligence Forensic Analytics Framework), a seven-stage pipeline that integrates deep learning, traditional machine learning, and graph reasoning into a unified workflow...........

[1] H. Farid, "Image forgery detection," IEEE Signal Processing Magazine, vol. 26, no. 2, pp. 16–25, Mar. 2009.
[2] B. Bayar and M. C. Stamm, "A deep learning approach to universal image manipulation detection using a new convolutional layer," in Proc. ACM Workshop on Information Hiding and Multimedia Security, 2016, pp. 5–10.
[3] P. Zhou, X. Han, V. I. Morariu, and L. S. Davis, "Learning rich features for image manipulation detection," in Proc. IEEE/CVF CVPR, 2018, pp. 1053–1061.
[4] C. Brun, A. Desnos, and J.-F. Marion, "Anomaly-based intrusion detection through LSTM sequence modelling on system call traces," Computers & Security, vol. 99, pp. 102–117, Dec. 2020.
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The Retail-Ease POS (Point of Sale) System is an intelligent and adaptive retail management solution designed to streamline sales operations, inventory control, and customer transactions. The system introduces an integrated framework for modern retail automation, dynamically managing billing, stock levels, and data reporting through a secure and scalable architecture. It incorporates automated inventory tracking, real-time billing, and data analytics modules to enhance operational efficiency and decision-making accuracy.........

1. A Retail Point-of-Sale (POS) system that integrates automated billing, real-time inventory management, and sales analytics to streamline retail operations, improve transaction accuracy, and enhance customer experience.
2. The system as claimed in Claim 1, wherein the automated billing module processes product information, calculates total amounts, applies discounts or taxes, and generates digital receipts for efficient and error-free checkout operations.
3. The system as claimed in Claim 1, further comprising an inventory management module configured to monitor stock levels in real time, trigger low-stock alerts, and automate reordering from suppliers.

Co3O4 thick films are deposited on glass substrate by screen printing technique. All characterization was carried out for unannealed, annealed at 250℃-400℃ . The XRD analysis indicates prepared films are polycrystalline nature with cubic structure having preferential orientation through (311) plane. Crystallite size is found to be 18.516nm. The lattice parameter found to be 8.036-8.138 A0. approaches to standard value. SEM analysis films show agglomeration of nanoparticles, occurrence of spherical-shaped grain aggregations. Spherical grain size increases 47.66 to 77.33nm with annealing temperature.........

[1] A. El Bachiri, L. Soussi, O. Karzazi, A. Louardi, A. Rmili, H. Erguig & B. El Idriss Electrochromic and photoluminescence properties of cobalt oxide thin films prepared by spray pyrolysis https://www.researchgate.net/ publication /00387010.2018.1556221 (2018) 1-7
[2] Manish Shinde, Nilam Qureshi, Sunit Rane, Uttam Mulik, Dinesh Amalnerkar Synthesis of Cobalt Oxide Nanostructures by Microwave Assisted Solvothermal Technique Using Binary Solvent System Physical Chemistry Communications, Volume 2 Issue 1 (2015) 1-9
[3] C. Ravi Dhasa, R. Venkatesha, K. Jothivenkatachalamb, nn,1 , A. Nithyab , B. Suji Benjaminc , A. Moses Ezhil Rajc , K. Jeyadheepand , C. SanjeevirajVisible light driven photocatalytic degradation of Rhodamine B and Direct Red using cobalt oxide nanoparticles : https://www.researchgate.net/publication/275227227 Ceramics International (2015) 1-13
[4] M. Manickam1 · V. Ponnuswamy1 · C. Sankar1 · R. Mariappan2 · R. Suresh1 Silicon Influence of Substrate Temperature on the Properties of Cobalt Oxide Thin Films Prepared by Nebulizer Spray Pyrolysis (NSP) Technique DOI 10.1007/s12633-015-9316-5 © Springer Science+Business Media Dordrecht (2015)1-11
[5] Mariappan R, Ponnuswamy V, Suresh P, Suresh R, Ragavendar M, Sankar C (2013) Mater Sci Semicond Process 16:825–832

This study aims to evaluate the investment attractiveness of provinces in the Central Anatolia Region of Türkiye using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), one of the most widely applied multi-criteria decision-making (MCDM) methods. In order to reflect the multidimensional structure of regional economic development, six key indicators were selected: population, housing sales, export value, motor vehicle ownership, gross domestic product (GDP), and agricultural production. These variables collectively represent both urban-industrial and rural-agricultural dimensions of regional performance, enabling a more comprehensive assessment of investment potential..........

[1]. Bhutia, P. W., & Phipon, R. (2012). Application of AHP and TOPSIS method for supplier selection problem. IOSR Journal of Engineering, 2(10), 43–50.
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The study was conducted with 580 students studying at the University of Hanoi, Vietnam through an online questionnaire. The purpose of this study is to analyze the factors that affect the behavior of using social networks such as Zalo, Facebook, Youtobe, Twitter, and Tiktok of students. The authors used the method of discovery factor analysis (EFA) and tested the research hypothesis by regression analysis, showing that there are factors that affect students' behavior of using social networks, including: usefulness, resource sharing, usage attitudes, etc cognitive control behavior, in which the usefulness factor has the strongest impact on students' intention to use social networks.

[1]. Abbas, J., Aman, J., Nurunnabi, M., Sustainability, S. B.-, & 2019, undefined. (2019). The impact of social media on learning behavior for sustainable education: Evidence of students from selected universities in Pakistan. Mdpi.Com. https://doi.org/10.3390/su11061683
[2]. Ahmed, I., management, T. Q.-A. journal of business, & 2011, undefined. (n.d.). A look out for academic impacts of Social networking sites (SNSs): A student based perspective. Academicjournals.Org. Retrieved September 16, 2024, from https://academicjournals.org/journal/AJBM/article-full-text-pdf/44DE1D921307.pdf
[3]. Akakandelwa, A., & Walubita, G. (2018). Students' social media use and its perceived impact on their social life: a case study of the university of Zambia. https://www.academia.edu/download/61998184/the_effectiveness_of_using_social_media_statements_of_the_problem20200205-90241-x79nz8.pdf
[4]. Al-Bahrani, A., Patel, D., Economics, B. S.-I. R. of, & 2015, undefined. (n.d.). Engaging students using social media: The students' perspective. Elsevier. Retrieved September 16, 2024, from https://www.sciencedirect.com/science/article/pii/S1477388015300025
[5]. Alghizzawi, M., Habes, M., … S. S.-Int. J. Inf. T., & 2019, undefined. (n.d.). The effect of social media usage on students'e-learning acceptance in higher education: A case study from the United Arab Emirates. Academia.Edu. Retrieved September 16, 2024, from https://www.academia.edu/download/61636562/109-495-1-PB20191230-63602-79h3f3.pdf

To address the problem that multi-stop distribution in small-scale logistics scenarios such as campuses and communities often relies on manual experience and suffers from inefficient route arrangement, this paper develops a multi-stop distribution optimization model under vehicle capacity constraints. Based on the geographic coordinates of distribution points, the Haversine formula is used to calculate inter-stop distances, and a 0-1 integer programming model is employed to determine vehicle assignment and visiting sequence, with the minimization of total transportation distance as the objective. A campus distribution case from a university is used for validation......

[1]. Wang, Z. 2021. Logistics System Planning and Design. Beijing: China Machine Press.
[2]. Zhang, J., Li, J. 2022. Urban logistics distribution route optimization based on the Haversine formula. Logistics Technology, 41:8, 132–136.
[3]. Chen, J. 2023. Logistics distance measurement and route optimization model based on geographic coordinates. Computer Engineering and Applications, 59:7, 268–274.
[4]. Hu, Y. Q. 2020. Fundamentals and Applications of Operations Research. Beijing: Higher Education Press.
[5]. Liu, Z. Q. 2023. Application of integer programming in logistics vehicle scheduling. Commercial Economy Research, 12, 105–109.

Ballasted track beds of high-speed railway subgrades in seasonally frozen regions are highly susceptible to performance degradation under the combined actions of train dynamic loads and water-ice phase changes. To address this, a bidirectional two-dimensional coupled discrete element-finite difference (DEM-FDM) numerical model was developed to systematically investigate the dynamic responses and micromechanical mechanisms of the ballast-subgrade system under coupled operational scenarios with varying train speeds (80–200 km/h) and ballast ice contents (0%–30%).......

[1]. Fan Z C 2012 Analysis of vertical dynamic characteristics of elastic long-sleeper ballastless track on simply supported beam bridge Thesis Central South University.
[2]. Wang J J, You R L, Du X G et al 2013 Selection analysis of ballastless track structure in heavy-haul railway tunnel Rail. Constr. 2013 132–6.
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This paper presents a centralized E-Gatepass system designed to optimize administrative operations within educational institutions. The proposed system replaces manual gate pass processes with a digital platform that facilitates structured request handling, real-time approval workflows, and secure monitoring of student movement. It integrates role-based access for faculty, security personnel, and administrators to ensure controlled and transparent operations. Additionally, the system supports resource management through an integrated booking module based on availability constraints. The architecture emphasizes scalability, efficient data processing, and reliable system performance. Experimental evaluation demonstrates improved response time, effective load handling, and high accuracy in request processing, making the system suitable for modern smart campus environments.

[1] R. Kothawade, D. Bedarkar, R. Naikwadi, R. Arote, and S. Ponnusamy, "Smart Gatepass Solutions," 2024.
[2] D. Bhaskaran, "Leveraging AI for Enhanced Security," 2024.
[3] D. B., D. V., and D. D., "ACE Seminar Hall Booking System," 2024.
[4] S. Pandey, M. Kandpal, A. Rawat, H. C. Upadhyay, A. Mittal, and H. R. Goyal, "Classroom Booking Management System," 2022.
[5] A. Alane, S. Chalikwar, G. Pekam, P. Sarode, and P. Pekam, "Gatepass Generation and Management System Using QR Code," 2022.

The requirement of appropriate divergence measures emerge as they play a vital part in segregation of two likelihood disseminations. The display communication is committed to the presentation of one such divergence measure utilizing Jensen inequality and Shannon entropy and its approval. On basis of the proposed divergence measure, a new dissimilarity measure is presented. Other than building up approval, a few of its major properties are moreover presented. Advance, based on proposed dissimilarity measure ,a new multiple attribute decision making method is presented and is altogether clarified with the assistance of an outlined case. In last paper is briefed with an application of the proposed dissimilarity measure in pattern recognition.

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Agriculture supports the livelihoods of millions of farmers in India; however, crop productivity is increasingly threatened by plant diseases, declining soil fertility, and unsustainable farming practices. Limited access to timely disease diagnosis and scientific soil assessment often compels farmers to rely on excessive use of fertilizers and pesticides, leading to soil degradation, environmental pollution, and increased cultivation costs. A critical issue is the imbalance of essential soil nutrients, particularly nitrogen (N), phosphorus (P), and potassium (K), which significantly influence crop growth, yield quality, and long-term soil sustainability. This study proposes an integrated machine learning-driven......

[1] V. Meshram, K. Patil, V. Meshram, D. Hanchate, and S. D. Ramkteke, "Machine learning in agriculture domain: A state-of-art survey," Artif. Intell. Life Sci., vol. 1, no. October, p. 100010, 2021, doi: 10.1016/j.ailsci.2021.100010.
[2] Y. Tace, M. Tabaa, S. Elfilali, C. Leghris, H. Bensag, and E. Renault, "Smart irrigation system based on IoT and machine learning," Energy Reports, vol. 8, no. May, pp. 1025–1036, 2022, doi: 10.1016/j.egyr.2022.07.088.
[3] M. Tiwari, V. Rathore, and C. Jecklin, "Food Crime: Deterrence of a Potential Money Laundering Typology Through Blockchain and Generative Artificial Intelligence (Gen AI)," Eur. J. Crim. Policy Res., 2025, doi: 10.1007/s10610-025-09641-0.
[4] L. Manning et al., "Artificial intelligence and ethics within the food sector: Developing a common language for technology adoption across the supply chain," Trends Food Sci. Technol., vol. 125, no. April, pp. 33–42, 2022, doi: 10.1016/j.tifs.2022.04.025.
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This study aimed to develop a more accurate and reliable non-invasive blood pressure monitoring system using an enhanced Photoplethysmography (PPG) technique with a real-time feedback loop. The primary problem addressed is the signal distortion caused by noise and motion artifacts, which often compromise the accuracy of conventional monitoring devices. The design method for this research involved a novel approach combining enhanced signal processing techniques with machine learning and control systems. We built a custom Simulink model to simulate a noisy PPG signal, which was then subjected to a series of filtering and smoothing algorithms to improve signal quality. After this, key physiological parameters like heart rate and pulse transit time (PTT) were extracted........

[1]. Ain, K., Jain, S., Guha, A., & Patra, A. (2021). An Approach to Early Stage Detection of Atherosclerosis using Arterial Blood Pressure Measurements. Biomedical Signal Processing and Control, 68, 102594. https://doi.org/10.1016/j.bspc.2021.102594
[2]. Babadağ, K., &Zaybak, A. (2021). Comparing Intra-arterial, Auscultatory, and Oscillometric Measurement Methods for Arterial Blood Pressure. Florence Nightingale Journal ofNursing, 29(2), 194. https://doi.org/10.5152/FNJN.2021.20029
[3]. Beutel, F., Van Hoof, C., Rottenberg, X., Reesink, K., & Hermeling, E. (2021). Pulse Arrival Time Segmentation into Cardiac and Vascular intervals–Implications for Pulse Wave Velocity and Blood Pressure Estimation. IEEE Transactions on Biomedical Engineering, 68(8), 2810–2820. https://doi.org/10.1109/TBME.2020.3025905
[4]. Calamanti, C., Moccia, S., Migliorelli, L., Paolanti, M., &Frontoni, E. (2019). Learning-based Screening of Endothelial Dysfunction from Photoplethysmographic signals. Electronics, 8(3), 271.
[5]. Cheng, J., Xu, Y., Song, R., Liu, Y., Li, C., & Chen, X. (2021). Prediction of Arterial Blood Pressure Waveforms from Photoplethysmogram Signals via fully Convolutional Neural Networks. Computers in Biology and Medicine, 138, 104877. https://doi.org/10.1016/j.compbiomed.2021.104877

The differentiation between artificial intelligence-generated imagery and authentic photographic representations has emerged as an increasing area of concern. We created MetaScan, a web application to distinguish between these two types of media without utilizing external third-party hardware services or neural networks. Our design philosophy is based on the observation that AI-generated images have forensic signatures in digital file property data primarily as a result of information that is not present. Authentic images include embedded EXIF data, sensor noise attributes......

[1]. Corvi, R., Cozzolino, D., Zingarini, G., Poggi, G., Nagano, K., & Verdoliva, L. (2023). On the detection of synthetic images generated by diffusion models. Proceedings of ICASSP 2023.
[2]. Farid, H. (2009). Image forgery detection. IEEE Signal Processing Magazine, 26(2), 16–25.
[3]. Gragnaniello, D., Mandelli, S., Marra, F., Bestagini, P., Tubaro, S., & Verdoliva, L. (2021). Are GAN generated images easy to detect? A critical analysis of the state-of-the-art. IEEE ICME 2021.
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[5]. Wang, S.-Y., Wang, O., Zhang, R., Owens, A., & Efros, A. A. (2020). CNN-generated images are surprisingly easy to spot... for now. IEEE/CVF CVPR 2020.

The zero field splitting parameters for the Mn2+ doped crystals of LuPO4 are estimated from the superposition model. The obtained parameters are in good agreement with the experimental ones. The experimental conclusion that the Mn2+ ion replaces the Lu3+ site in LuPO4 is supported by theoretical investigation. Using the crystal field parameters derived from the superposition model and the crystal field analysis program, the optical spectra of the crystal are computed by diagonalizing the total Hamiltonian. There is a reasonable match between the calculated and experimental band positions. Thus, the theoretical analysis validates the experimental observations.

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Education plays a vital role in promoting equality, inclusion, and social justice in society. The Indian education system has historically faced challenges related to gender inequality and social exclusion. Many learners, including girls, transgender students, socio-economically disadvantaged groups, and students with disabilities, have encountered significant barriers in accessing quality education. In this context, the National Education Policy 2020 (NEP 2020) represents a major step towards transforming the educational system of India by emphasising equity, inclusiveness, and equal learning opportunities for all. This study examines the vision of NEP 2020 in promoting gender inclusion and social justice and explores how this policy goals can be translated from policy to practice.......

[1]. Ahuja and Chadha (2022), - "Equitable and Inclusive Education": Yojana, a Development Monthly Journal, page no- 32.
[2]. Ministry of Human Resource Development, National Education Policy 2020. https://www.education.gov.in/sites
[3]. Ministry of Education, Government of India, NCFSE report
[4]. Castelino A. and A. Shashkala (2018). Gender, School and Society, published by the Registrar Mangalore University, Mangalagangothri
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