Welcome to Volume 3, Issue 1 of NIJES. This regular issue features pioneering theoretical and experimental contributions across deep learning optimization, smart grid reliability, advanced structural materials, and IoT edge security. All articles are licensed under CC BY 4.0 and indexed with persistent Crossref DOIs.
DOI Prefix: 10.5281/nijes.2026.01
4 Papers Published
International Authors
Original Research
Feb 18, 2026 • pp. 1–14
Dr. Rajiv Ramanathan, Prof. Elena Rostova, and Dr. Marcus Weber
Automated inspection of high-voltage electrical substations demands robust, low-latency computer vision algorithms capable of detecting thermal anomalies and insulation degradation under varying weather conditions. In this paper, we propose a lightweight deep residual framework with spatial-temporal attention mechanisms trained on multispectral infrared telemetry datasets.
DOI: 10.5281/nijes.2026.0101
342 Downloads
1,180 Views
Review Paper
Feb 10, 2026 • pp. 15–32
Dr. Sarah Jenkins, Dr. Vikramaditya Rao, and Prof. Chen Wei
The construction sector is undergoing a paradigm shift towards low-embodied-carbon binders to mitigate Portland cement emissions. This critical review investigates the synthesis, curing thermodynamics, and mechanical durability of alkali-activated slag-fly ash geopolymers across civil implementations.
DOI: 10.5281/nijes.2026.0102
518 Downloads
1,940 Views
Original Research
Jan 28, 2026 • pp. 33–46
Dr. Ahmed Farouk, Dr. Lisa Nguyen, and Prof. Rajesh K. Sharma
Emerging quantum computing architectures pose a critical threat to classical public-key cryptography widely deployed across IoT networks. This paper presents a provably secure, lightweight mutual authentication protocol founded on Module Learning With Errors (M-LWE).
DOI: 10.5281/nijes.2026.0103
412 Downloads
1,420 Views
Industrial Case Study
Jan 15, 2026 • pp. 47–58
Ing. Klaus Meyer, Dr. Hiroshi Tanaka, and Prof. Marcus Becker
Weight reduction in aerospace structural components directly translates to fuel efficiency. Utilizing selective laser melting additive manufacturing and SIMP topology optimization, a Ti-6Al-4V engine mounting bracket was redesigned achieving a 38.6% mass reduction.
DOI: 10.5281/nijes.2026.0104
289 Downloads
990 Views
