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Deploying large language models in safety-critical domains while migrating to post-quantum cryptographic standards poses...
20/08/2026

Deploying large language models in safety-critical domains while migrating to post-quantum cryptographic standards poses a compounded systems engineering challenge: infrastructure must become privacy-preserving, computa-tionally viable, and quantum-resistant at once. This review examines three frontiers where lattice-based cryptography and large language models converge, applying an evidence-grading scheme that separates established results from conjecture.
For more information, please check: https://ojs.wiserpub.com/index.php/EST/article/view/10357

🌱 Editor's Choice | From Crops to Stronger Sustainable Construction MaterialsCan everyday starches from yam, cassava, an...
18/08/2026

🌱 Editor's Choice | From Crops to Stronger Sustainable Construction Materials

Can everyday starches from yam, cassava, and sweet potato improve the performance of geopolymer materials?

A new study investigates the use of different starch sources as additives in metakaolin-based geopolymer composites, exploring their effects on structure, morphology, and compressive strength.

🔬 The research compares:
• Commercial starch
• Yam starch
• Cassava starch
• Sweet potato starch

The study also shows that the commercial-starch composite developed a more compact and dense microstructure, helping explain its superior mechanical performance.

These findings highlight the potential of agricultural starches as accessible additives for developing stronger and more sustainable geopolymer composites.

📖 Read the full article:
https://doi.org/10.37256/est.5220244500

This study presents a multi technique Explainable AI (XAI) framework for slice level brain tumour classification using M...
18/08/2026

This study presents a multi technique Explainable AI (XAI) framework for slice level brain tumour classification using MRI. A custom CNN was developed and trained on BraTS 2021 FLAIR slices, achieving a slice level test accuracy of 91.24%. To move beyond the “black box” problem, we integrated three complementary XAI methods—Grad CAM, LRP, and SHAP—offering hierarchical explanations from coarse regional localisation to pixel level relevance and quantitative feature contributions. This combined approach proves especially valuable for borderline cases where 2D slices capture only partial tumour views, as each technique resolves ambiguities that single methods leave unclear. By presenting layered, cross validated insights, the framework enhances model transparency and supports clinical decision making. Although quantitative evaluation and multi sequence validation remain future work, this integration demonstrates how thoughtful XAI combination can build trust in AI assisted medical imaging and guide radiologists toward more informed interpretations. Please visit: https://ojs.wiserpub.com/index.php/EST/article/view/9934

This work proposes an architecture that integrates Ethereum blockchain technology and Trusted Ex*****on Environments (TE...
13/08/2026

This work proposes an architecture that integrates Ethereum blockchain technology and Trusted Ex*****on Environments (TEEs), focusing on Intel Software Guard Extensions (SGX). The main motivation is to address existing challenges and limitations in on-chain job ex*****on by smart contracts, proposing a reliable method that ensures the integrity and confidentiality of off-chain processed jobs. The proposed architecture is based on a strategic combination of the blockchain’s smart contract and the TEEs. The smart contract acts as a decentralized coordinator, responsible for job distribution, monitoring the state, and dynamically allocating resources among TEE machines.
For more information, please check: https://ojs.wiserpub.com/index.php/EST/article/view/10397

This study develops an interpretable sales forecasting framework for retail and e-commerce by integrating machine learni...
12/08/2026

This study develops an interpretable sales forecasting framework for retail and e-commerce by integrating machine learning, Explainable AI (XAI), and Necessary Condition Analysis (NCA). Using the Walmart M5 dataset, we benchmarked six models and found that Extra Trees delivered the best performance (RMSE = 1.6183, R² = 0.5852). Beyond prediction, XAI methods (SHAP and Permutation Feature Importance) identified rolling sales averages, product identity, and weekend effects as key drivers. NCA further revealed critical demand thresholds—specific levels of rolling averages and volatility that are necessary for achieving high sales. This ML-XAI-NCA framework thus offers retailers not only accurate forecasts but also actionable, interpretable insights for inventory and pricing decisions.
For more information, please check: https://ojs.wiserpub.com/index.php/EST/article/view/10392

Editor's Choice | Cooling Aluminum: How Size Shapes Heat TransferA new study investigates the cooling kinetics of spheri...
12/08/2026

Editor's Choice | Cooling Aluminum: How Size Shapes Heat Transfer

A new study investigates the cooling kinetics of spherical samples made from different aluminum grades, examining heat transfer through both convection and thermal radiation across a wide temperature range.

The research evaluates aluminum grades A0, A5, A6, AB98, and A5N, focusing on:
🔹 Characteristic cooling times
🔹 Convective and radiative heat transfer mechanisms
🔹 Temperature-dependent heat transfer coefficients
🔹 The influence of sample size on thermophysical behavior
🔹 Differences between spherical and cylindrical specimens

These findings offer useful insights for thermal engineering, materials science, heat treatment, and the design of aluminum-based industrial processes.

📖 Read the full article:
https://doi.org/10.37256/est.5220244117

Deep learning has significantly improved the performance of semantic segmentation in high-resolution imagery and compute...
11/08/2026

Deep learning has significantly improved the performance of semantic segmentation in high-resolution imagery and computer vision tasks. However, standard segmentation models treat all pixel-wise predictions equally, despite the fact that predictions close to the decision boundary are inherently uncertain. This limitation often leads to unstable classifications and increased false positives or false negatives in complex scenes. In this paper, we propose a practical uncertainty-aware semantic segmentation refinement framework that explicitly handles decisionboundary ambiguity through an empirical routing mechanism through a Confusion Zone mechanism. Instead of forcing a binary decision for all pixels, predictions whose probability scores fall within a predefined interval [τlow, τhigh] are marked as uncertain and redirected to a secondary refinement module that exploits additional spatial features and local context before assigning a final label. More detailed information, please visit:
https://ojs.wiserpub.com/index.php/EST/article/view/10368

🌍 Empowering Rural Healthcare Through Reliable Solar Energy SolutionsReliable electricity is essential for healthcare de...
06/08/2026

🌍 Empowering Rural Healthcare Through Reliable Solar Energy Solutions

Reliable electricity is essential for healthcare delivery, particularly in emergency situations where power interruptions can directly affect critical services. In many rural regions, limited access to stable electricity remains a significant barrier to healthcare infrastructure development.

The research article, “Design and Implementation of a Charge Controller for Solar PV Systems for Emergency Situations in Health Facilities in Rural Areas of Uganda,” introduces a practical renewable energy solution designed to improve power reliability in rural healthcare settings.

The study presents the development of a Solar Charge Controller System (SCCS) that:

🔹 Regulates solar panel power generation and battery charging
🔹 Prevents battery overcharging and excessive discharge
🔹 Protects electrical systems from overload and overvoltage conditions
🔹 Maintains performance under low sunlight conditions
🔹 Provides an affordable and sustainable emergency power solution

Experimental testing demonstrates the effectiveness of the system, achieving an average efficiency of 96.52% during an eight-day evaluation period.

This research highlights how appropriately designed solar technologies can strengthen healthcare resilience, expand energy access, and support sustainable development in regions where grid electricity remains limited.

The proposed SCCS represents an important step toward combining renewable energy innovation with public health infrastructure, offering valuable insights for engineers, policymakers, and development organizations.

📄 Explore the full article:
https://doi.org/10.37256/est.5220244153

This study by Sheykhaleslami and Maleki (Sharif University of Technology) numerically investigates seismic force transfe...
05/08/2026

This study by Sheykhaleslami and Maleki (Sharif University of Technology) numerically investigates seismic force transfer in steel floor diaphragms—prefabricated joists (PJS), open-web joists (OWSJ), and composite decks (CSD)—using SAP2000 and nonlinear ABAQUS models. The critical finding: when positive shear connection between slab and collector beams is absent, a "diaphragm core" forms, forcing perimeter joists to act as unintended collectors and increasing axial demands by 1.5–6× over conventional design assumptions. For OWSJ systems, joist-seat welds became vulnerable; for CSD, shear connectors significantly improved ductility. The study recommends conservative diaphragm response factors (Rₛ ≤ 1) when direct load paths are not provided. These results challenge routine modeling practices and offer practical guidance for safer, more realistic seismic design of steel floor systems. Please visit: https://ojs.wiserpub.com/index.php/EST/article/view/10207

🔬 Editor's Choice | Optimizing Laser Welding Performance Through Beam Oscillation ControlLaser welding has become a key ...
04/08/2026

🔬 Editor's Choice | Optimizing Laser Welding Performance Through Beam Oscillation Control

Laser welding has become a key technology for manufacturing industries requiring high precision, strength, and reliability—especially when joining advanced materials such as 304L stainless steel.

A new experimental and modeling study investigates how different laser beam oscillation patterns influence weld quality and mechanical performance.

The research examines:
✅ Effects of laser power and welding speed on joint performance
✅ Comparison of sinusoidal, square, and triangular beam oscillation patterns
✅ Taguchi L9 experimental design for process optimization
✅ ANOVA and regression modeling for predictive analysis
✅ Influence of oscillation patterns on microhardness and tensile strength

The findings show that beam oscillation patterns play a critical role in determining weld properties, with square and sinusoidal patterns achieving improved microhardness compared with triangular patterns.

This study provides valuable guidance for optimizing laser welding processes in industrial applications, supporting stronger, more reliable, and precisely engineered welded structures.

📖 Read the full article:
https://doi.org/10.37256/est.5220244307

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