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Detetion and Prevention of Irrelevent Data Through Data Cleansing

Published online https://doi.org/

Abstract

A file oriented unstructured data collected and transformed into the data warehouse .Two or more records identified separately actually represent same real world entity, detection and prevention to improve data quality. The proposed technique introduces smart tokens of most representative attributes by sorting those tokens identical records are bring into close neighborhood, record duplicates are identified and removed from the data. Clean consistent and non duplicated data loaded into warehouse. The technique is a mile stone for cleaning data as with the explosive amount of data recording it is the need of time that more corrected data to be provided to the data mangers for effective decisions making.

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Current Issue - 2026

MEMS-Based Biosensor Design and Microfabrication for Tear Glucose Sensing

Vol. 13, Issue 03, PP. 22-38, March 2026

Published online https://doi.org/10.5281/zenodo.19124891

ePub PDF

Abstract

Continuous glucose monitoring using smart contact lenses offers a promising non-invasive alternative for diabetes management; however, reliable wireless power delivery and integration of rigid microelectronic components into soft contact lens substrates remain significant engineering challenges. This study presents a battery-free smart contact lens platform integrating MEMS biosensors with a wireless power transfer (WPT) system for real-time tear glucose monitoring. The system employs a near-field communication (NFC) inductive coupling architecture operating at 13.56 MHz, incorporating a miniaturized microcoil embedded within a transparent SU-8/PDMS composite to maintain optical clarity and biocompatibility. A peripheral active-zone integration strategy places electronic components outside the optical region, ensuring unobstructed vision while maximizing power transfer efficiency. The power management module integrates a multi-stage rectifier and a high-efficiency buck–boost converter fabricated on a flexible polyimide substrate, achieving conversion efficiencies exceeding 95%. Experimental evaluation demonstrates a wireless power transfer efficiency of 31.4%, delivering a stable continuous power supply of 30–35 mW suitable for sustained biosensor operation and wireless telemetry. A supercapacitor-based energy buffering system further stabilizes transient load variations during data transmission. To enable reliable integration on curved substrates, a sacrificial-layer flattening technique and compliance-based stress mitigation framework were developed, ensuring mechanical reliability and long-term lens comfort. The proposed architecture establishes a scalable wireless power and integration framework for next-generation wearable biosensing platforms, enabling clinically deployable smart contact lenses for continuous, non-invasive glucose monitoring in diabetic patients.

Author

Fahad Riaz, Longbing Heb, Shaikh Sabieh

Cite

Fahad Riaz, Longbing Heb, Shaikh Sabieh “MEMS-Based Biosensor Design and Microfabrication for Tear Glucose Sensing, Vol. 13, Issue 03, PP. 22-38, March 2026. https://doi.org/10.5281/zenodo.19124891.,

References

[1] J. P. McCulley and W. D. Mathers, “Structure and function of the lacrimal secretory system,” in Ocular Surface Disease: Cornea, Conjunctiva and Tear Film, Elsevier, 2013, pp. 38–51.

[2] B. V. Norm and J. L. Foulks, “The tear film,” in Dry Eye Disease: The Clinician’s Guide to Diagnosis and Treatment, Thieme, 2015, pp. 12–34.

[3] M. Y. Su, J. Z. Ma, H. Zhang, and W. C. Knudtson, “A comparison of tear glucose levels in diabetic and non-diabetic subjects,” Investigative Ophthalmology and Visual Science, vol. 43, no. 12, pp. 3714–3719, 2002.

[4] S. Kallenborn-Gerhardt, A. J. Schilling, P. Atanasov, and J. Kruth, “Non-invasive glucose monitoring using tear glucose sensors,” Diabetes Technology and Therapeutics, vol. 19, no. 3, pp. 180–191, 2017.

[5] J. Y. Lee, J. K. Park, and S. J. Park, “Tear glucose measurement for non-invasive diabetes monitoring,” Journal of Biomedical Optics, vol. 20, no. 4, p. 047001, 2015.

[6] Yildirim, A. Atanasov, J. Gonzales, and R. Bhatia, “Correlation between tear glucose and blood glucose in diabetic patients,” American Journal of Ophthalmology, vol. 167, pp. 35–41, 2016.

[7] R. Markert, U. Staub, and S. Frey, “Temporal dynamics of tear glucose in response to blood glucose changes,” IEEE Transactions on Biomedical Engineering, vol. 68, no. 2, pp. 459–467, 2021.

[8] M. Bao, Y. Gong, X. Zhou, and L. Li, “Real-time kinetic analysis of tear-blood glucose relationship,” Biosensors and Bioelectronics, vol. 165, p. 112413, 2020.

[9] K. C. Park, S. H. Lee, and J. W. Kim, “First-order kinetic modeling of tear glucose response to blood glucose excursions,” Journal of Diabetes Research, vol. 2021, p. 8837416, 2021.

[10] M. Parviz, “Augmented reality in a contact lens,” IEEE Spectrum, vol. 46, no. 9, pp. 30–35, 2009.

Adaptive Gradient-Enhanced PINNs for Numerical Solution of Convection-Diffusion Equation

Vol. 13, Issue 02, PP. 13-21, February 2026

Published online https://doi.org/10.5281/zenodo.18753514

ePub PDF

Abstract

Physics-Informed Neural networks (PINNs) are mesh-free Deep Learning (DL) framework to solve Partial Differential equations (PDEs). This technique embeds physical laws directly into the training process, enabling the solution of forward and inverse problems governed by PDEs. Unlike traditional neural networks, PINNs incorporate the governing equations, initial conditions, and boundary conditions directly into the loss function. Automatic differentiation in PINNs avoids truncation errors and ensures high precision enforcing the governing equations. Despite their advantages, PINNs face several challenges. PINNs struggle to solve Convection-Diffusion Equations (CDEs), particularly at the region where the convection term dominated. To overcome this problem, an extended form of PINNs is discussed here. Adaptive Gradient-enhanced PINNs (AG-PINNs) are extensions of PINNs, where Residual-based Adaptive Refinement (RAR) and the derivatives of the governing equations are also enforced during training. However, adding gradient constraints leads to over-constraining the network, increased computational cost, and inefficient learning in smooth regions. This motivates RAR, which improves the solution accuracy while avoiding over-constraining the neural network in smooth regions. In this paper we discuss convection-diffusion equation with high Péclet number. As Pé increased the convection terms dominated so it become challenging for standard PINNs, to mitigate these challenges AG-PINNs is used. AG-PINNs is better than standard PINNs which is shown in this paper by comparing results of AG-PINNs with standard PINNs technique. This work is carried out through Python Jupiter Notebook in a deepXDE library.

Author

Javeed Ahmad

Cite

Javeed Ahmad “Adaptive Gradient-Enhanced PINNs for Numerical Solution of Convection-Diffusion Equation” International Journal of Engineering Works, Vol. 13, Issue 02, PP. 13-21, February 2026. https://doi.org/10.5281/zenodo.18753514.

References

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[8] X. Yu, K. Lan, J. Wu, Green’s functions, linear second-order differential equations, and one-dimensional diffusion advection models, Studies in Applied Mathematics 147 (1) (2021) 319–362.

[9] M. Raissi, P. Perdikaris, G. E. Karniadakis, Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations, Journal of Computational physics 378 (2019) 686–707.

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Styrene Butadiene Rubber and Plastic Bottle Wastes as Sustainable Materials in Hot Mix Asphalt

Vol. 13, Issue 02, PP. 22-40, February 2026

Published online https://doi.org/10.5281/zenodo.18782799

ePub PDF

Abstract

Environmental concerns associated with waste tires and plastic bottles have driven the adoption of recycling-based modifiers to enhance pavement performance. This study investigates the feasibility of utilizing Styrene–Butadiene Rubber (SBR) and Plastic Bottle Waste (PBW) as sustainable modifiers in Hot Mix Asphalt (HMA). Modified asphalt mixtures were prepared with PBW and SBR contents ranging from 2% to 10% by weight of the Optimum Binder Content (OBC). The performance of conventional and modified mixtures was evaluated using Marshall Stability, rutting resistance, Indirect Tensile Strength (ITS), and microstructural and chemical characterization through Fourier Transform Infrared Spectroscopy (FTIR) and X-ray Diffraction (XRD). Results indicate that a 6% modifier content provides optimum performance enhancement, leading to significant improvements in stability, tensile strength, rut resistance, thermal stability, and stiffness. Microstructural analyses confirmed improved binder–modifier interactions and enhanced material compatibility. Comparatively, SBR demonstrated superior performance improvements over PBW, indicating its higher effectiveness as an asphalt modifier. In addition to mechanical benefits, the incorporation of SBR and PBW offers substantial environmental advantages by reducing landfill disposal and incineration, thereby lowering the associated carbon footprint. Overall, the findings support the use of recycled SBR and PBW as cost-effective, durable, and environmentally sustainable alternatives for producing high-performance asphalt mixtures, contributing to extended pavement service life and sustainable infrastructure development.

Author

Salman Khan, Fazli Karim, Hafiz Adil Shah, Sangeen Khan

Cite

Salman Khan, Fazli Karim, Hafiz Adil Shah, Sangeen Khan “Styrene Butadiene Rubber and Plastic Bottle Wastes as Sustainable Materials in Hot Mix Asphalt” International Journal of Engineering Works, Vol. 13, Issue 02, PP. 22-40, February 2026. https://doi.org/ 10.5281/zenodo.18782799.

References

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[3] F. Xu, Y. Zhao, and K. Li, “Using waste plastics as asphalt modifier: A review,” Materials, vol. 15, p. 110, 2021.

[4] F. Karim, “Waste cooking oil as sustainable rejuvenator in recycled asphalt pavement,” Technical Journal, vol. 29, no. 3, p. 17, Sep. 2024.

[5] M. Anas and F. Karim, “Plastic bottle waste as a sustainable material in reclaimed asphalt pavement production,” Technical Journal, vol. 30, no. 3, pp. 1–9, Sep. 18, 2025.

[6] D. Hussain, H. Ullah, A. Farooq, D. Farooq, F. Karim, Z. Wang, and J. Huang, “Assessing road safety of the Peshawar–Rawalpindi section of National Highway (N-5) in Pakistan using iRAP,” Periodica Polytechnica Transportation Engineering, vol. 53, no. 4, pp. 371–380, Jul. 8, 2025.

[7] N. Khan, F. Karim, Q. B. A. I. L. Qureshi, S. A. Mufti, M. B. A. Rabbani, M. S. Khan, and D. Khan, “Effect of fine aggregates and mineral fillers on the permanent deformation of hot mix asphalt,” Sustainability, vol. 15, no. 13, p. 10646, Jul. 6, 2023.

[8] F. Karim, S. Iqbal, A. Farooq, H. Ullah, and M. Imran, “Comparing the consensus properties of aggregate sources from KP to Margalla using image analysis,” The Sciencetech, vol. 5, no. 3, pp. 50–69, Aug. 24, 2024.

[9] M. B. Khurshid, N. A. Qureshi, A. Hussain, and M. J. Iqbal, “Enhancement of hot mix asphalt (HMA) properties using waste polymers,” Arabian Journal for Science and Engineering, vol. 44, pp. 8239–8248, 2019.

[10] M. M. BenZair, F. M. Jakarni, R. Muniandy, and S. Hassim, “A brief review: Application of recycled polyethylene terephthalate in asphalt pavement reinforcement,” Sustainability, vol. 13, p. 1303, 2021.

Investigation of Superelasticity of Iron based Shape Memory Alloy

Vol. 13, Issue 01, PP. 07-12, January 2026

Published online https://doi.org/10.5281/zenodo.18242902

ePub PDF

Abstract

Iron-based shape memory alloys (Fe-SMAs) have recently attracted significant attention as cost-effective and mechanically robust alternatives to conventional Ni–Ti alloys for smart structural and engineering applications. This study investigates the superelastic behavior of an iron-based shape memory alloy through systematic mechanical characterization under controlled loading–unloading conditions. Uniaxial tensile tests were conducted to evaluate stress–strain response, reversible strain capacity, critical transformation stresses, and hysteresis behavior associated with stress-induced martensitic transformation and reverse transformation. The influence of cyclic loading on superelastic stability, energy dissipation, and residual strain accumulation was also examined. Microstructural observations were correlated with mechanical responses to elucidate the role of phase transformation mechanisms in governing superelastic performance. The results demonstrate that the investigated Fe-based alloy exhibits pronounced superelasticity with substantial recoverable strain and stable cyclic behavior, highlighting its potential for applications in vibration control, seismic damping, and adaptive structural components. The findings provide fundamental insight into the deformation and recovery mechanisms of Fe-based SMAs and contribute to the development of reliable, large-scale superelastic materials for civil and mechanical engineering systems.

Author

Hamza Kamran, Rana Atta ur Rahman, Ahmed Usman Yasir

Cite

Hamza Kamran, Rana Atta ur Rahman, Ahmed Usman Yasir “Investigation of Superelasticity of Iron based Shape Memory Alloy” International Journal of Engineering Works, Vol. 13, Issue 01, PP. 07-12, January 2026. https://doi.org/10.5281/zenodo.18242902.

References

[1] A. Sato, E. Chishima, K. Soma, and T. Mori, “Shape memory effect in γ to ε transformation in Fe–Mn–Si alloys,” Acta Metallurgica, vol. 30, no. 6, pp. 1177–1183, 1982.
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[6] Z. Dong, S. Kajiwara, T. Kikuchi, and T. Sawaguchi, “Martensitic transformation and superelastic behavior in Fe-based shape memory alloys,” Acta Materialia, vol. 58, no. 3, pp. 935–942, 2010.
[7] T. Sawaguchi, T. Maruyama, Y. Otsuka, and K. Tsuzaki, “Design concept and applications of Fe-based superelastic alloys,” Materials Science and Engineering A, vol. 585, pp. 1–11, 2014.
[8] M. Czaderski, M. Shahverdi, and M. Motavalli, “Iron-based shape memory alloys for prestressing and seismic applications,” Construction and Building Materials, vol. 56, pp. 94–101, 2014.

[9] M. Shahverdi, M. Czaderski, and M. Motavalli, “Superelastic behavior of Fe-based shape memory alloys for civil engineering applications,” Journal of Materials in Civil Engineering, vol. 32, no. 6, pp. 04020131, 2020.
[10] Y. Wang, H. Peng, X. Liu, and Y. Wen, “Compression superelasticity and energy dissipation capacity of Fe-Mn-Si-based shape memory alloys,” Materials & Design, vol. 197, pp. 109220, 2021.
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Neural Network based Portable Spectrometer for Fluid Classification

Vol. 13, Issue 01, PP. 01-06, January 26

Published online https://doi.org/10.5281/zenodo.18183364

ePub PDF

Abstract

The spectrometer, a powerful analytical instrument, plays a vital role in the fields of Chemistry, Material Sciences, Biochemistry, and Physics by allowing researchers to test, discover, and measure the spectral content of various fluids. This paper details the development of a portable, lightweight, cost-effective spectrometer device, which incorporates artificial intelligence for fluid classification. In a practical application, milk is used as the test fluid, with different qualities achieved by introducing controlled impurities. The spectrometer collected spectral data using a camera sensor, and the dataset is subsequently randomized and divided into training and testing data. Employing a range of machine learning algorithms and neural networks, the device accurately predicts the class of the fluid. The integration of optical components and microcontrollers facilitated model deployment. Notably, this device provides real-time fluid classification and displays results on an Organic LED. Beyond milk, its versatility allows for quality analysis of various fluids containing impurities, such as gasoline, human blood, and saliva. Remarkably compact at 70 x 70 x 50 mm and lightweight at 0.2 kilograms, the device had achieved an impressive average accuracy of 93.45 percent. It stands out for its ease of use, recharge ability, accuracy, and cost effectiveness compared to traditional spectrophotometers, positioning it as a valuable tool in the realm of scientific research and quality assessment.

Author

Hassan Nawazish Rasool, Muhammad Zeb

Cite

Hassan Nawazish Rasool, Muhammad Zeb “Neural Network based Portable Spectrometer for Fluid Classification” Internationa, Vol. 13, Issue 01, PP. 01-06, January 2026. https://doi.org/10.5281/zenodo.18183364.,

References

[1] Mettler Toledo GmbH, “UV / VIS Spectrophotometry,” Mettler-Toledo Int., no. September 2015, p. 56, 2021, [Online]. Available: https://www.mt.com/es/es/home/library/guides/laboratory- division/1/uvvis-spectrophotometry-guide-applications fundamentals.html

[2] F. Sánchez Rojas, C. Bosch Ojeda, and J. M. Cano Pavón, “Spectrophotometry | biochemical applications,” Encycl. Anal. Sci., no. April, pp. 205–213, 2019, doi: 10.1016/B978-0-12-409547- 2.00501-1.

[3] P. Carpentier, A. Royant, J. Ohana, and D. Bourgeois, “Advances in spectroscopic methods for biological crystals. 2. Raman spectroscopy,” J. Appl. Crystallogr., vol. 40, no. 6, pp. 1113–1122, 2007, doi: 10.1107/S0021889807044202.

[4] R. A. Ahmadi, F. Hasanvand, G. Bruno, H. A. Rudbari, and S. Amani, “Synthesis, spectroscopy, and magnetic characterization of copper(II) and cobalt(II) complexes with 2-amino-5-bromopyridine as ligand,” Russ. J. Coord. Chem. Khimiya, vol. 39, no. 12, pp. 867–871, 2013, doi: 10.1134/S1070328413110018.

[5] K. Laganovska et al., “Portable low-cost open-source wireless spectrophotometer for fast and reliable measurements,” HardwareX, vol. 7, p. e00108, 2020, doi: 10.1016/j.ohx.2020.e00108.

[6] J. Riu, G. Gorla, D. Chakif, R. Boqué, and B. Giussani, “Rapid analysis of milk using low-cost pocket-size NIR spectrometers and multivariate analysis,” Foods, vol. 9, no. 8, 2020, doi: 10.3390/foods9081090.

[7] J. A. Diaz-Olivares, I. Adriaens, E. Stevens, W. Saeys, and B. Aernouts, “Online milk composition analysis with an on-farm near-infrared sensor,” Comput. Electron. Agric., vol. 178, no. September, p. 105734, 2020, doi: 10.1016/j.compag.2020.105734.

[8] L. L. Monteiro, P. Zoio, B. B. Carvalho, L. P. Fonseca, and C. R. C. Calado, “Quality Monitoring of Biodiesel and Diesel/Biodiesel Blends: A Comparison between Benchtop FT-NIR versus a Portable Miniaturized NIR Spectroscopic Analysis,” Processes, vol. 11, no. 4, 2023, doi: 10.3390/pr11041071.

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