Istanbul Technical University
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Lützhöft, M. and Earthy, J. (eds.) (2024) Human-Centred Autonomous Shipping
No full texthttps://doi.org/10.1007/s13437-025-00386-
Numerical analysis of dusty hybrid nanofluid flow in a porous medium under LTNE conditions in the impacts of thermophoresis and gravity-buoyancy forces
No full texthttps://doi.org/10.1615/jpormedia.202505611
Long Short‐Term Memory (LSTM)‐Based Modeling of Negative Bias Temperature Instability (NBTI) in 40 nm MOSFETs
No full textABSTRACTBias temperature instability (BTI) is a time‐based degradation mechanism that causes serious damage to the performance of analog and digital integrated circuits. The increasingly probabilistic nature of this phenomenon renders machine learning‐based modeling approaches more advantageous, as they can deliver more accurate results in that context compared to analytical methods. In this paper, the Long Short‐Term Memory (LSTM) method, a time‐series approach, has been adopted to model BTI in 40 nm CMOS p‐type metal‐oxide‐semiconductor field‐effect transistors (MOSFETs). The aging model has been established by training the experimental data collected from a dedicated test chip. A bi‐directional LSTM structure has been employed in model generation. Mean‐square error (MSE) results indicate that the model can be effectively utilized in interpolation exercises where the test data falls within the same interval as the training data, with great accuracy. Moreover, the model has yielded promising outcomes in extrapolation exercises where the test data lies outside the defined training range. This property potentially qualifies the proposed approach for time‐to‐market and cost‐reduction efforts.https://doi.org/10.1002/jnm.7005
Abundance and Distribution of Organic Pollutants in Soils and Sediments of Mt. Vechernyaya, East Antarctica
No full textAbstract This study aims to determine the abundance and distribution of organic pollutants in the coastal areas of Mt. Vechernyaya (Enderby Land, East Antarctica). For this purpose, soil and sediment samples were collected from the vicinity of the old Soviet field base and lakes. The field studies were conducted within the 14th Belarusian Antarctic Expedition between January and February 2022. The collected samples were analyzed for 16 polycyclic aromatic hydrocarbons (PAH), 7 polychlorinated biphenyls (PCB), and 11 organochlorine pesticides (OCP) by GC–MS/MS. Particle size distributions and total organic carbon levels of the samples were determined to evaluate the measured pollutant concentrations. The total PAH, PCB and OCP levels measured in the samples were 6.0–92 µg/kg, 25–422 ng/kg and 2.3–1383 ng/kg, respectively. The results pointed out petrogenic PAH sources for lake sediment while pyrolytic sources were estimated for soil samples due to the use of fossil fuels in generators. While detected PCBs may originate from local sources due to legacy use, OCPs have been suggested to reach from the mainland by long-range atmospheric transport. The measured levels will provide a baseline which will help to monitor possible future changes in the region.https://doi.org/10.1007/s11270-025-07944-
Novel DT-assisted Vehicular Task Offloading for Cloud, Edge, and Hybrid Deployments
No full texthttps://doi.org/10.1109/tvt.2025.362081
Design of Ultra Wideband Power Divider/Combiner and Comparison on Results of Measurement and Simulation based on EM Solver Methods
No full texthttps://doi.org/10.1109/smacd65553.2025.11092080https://doi.org/10.1109/SMACD65553.2025.1109208
Unexplored regions in teleparallel f ( T ) gravity: Sign-changing dark energy density
No full texthttps://doi.org/10.1103/1xd4-k91
Prediction and visualization of charge shape and ball trajectory in tumbling mills: a python-based tool for liner design and operational optimizations
No full textTumbling mills are critical in mineral processing due to their high energy consumption and impact on downstream processes. The mining industry accounts for 1.7% of global energy consumption, with comminution responsible for approximately 25% of this usage. Mill performance is largely governed by charge shape and media trajectory, which are significantly influenced by liner design and wear conditions. However, existing tools provide limited capabilities for combined analysis of these critical parameters. This study introduces a Python-based tool that integrates the Morrell C model for charge shape prediction with Powell's model for media trajectory calculation, offering comprehensive visualization of mill dynamics. The tool's effectiveness was demonstrated through two case studies on an 8-meter SAG mill: first optimizing initial liner design parameters and then adapting operating parameters to compensate for liner wear over a six-month period. Results show how the tool enables proactive operational adjustments based on visualized trajectory changes, helping maintain optimal grinding efficiency throughout the liner lifecycle. This integrated approach to design and operational optimization contributes to improved energy efficiency, extended liner life, and more sustainable mineral processing practices.https://doi.org/10.37190/ppmp/20453
Design of a Tracking System for Monitoring the Performance of Cosmetic Products Sold in Pharmaceutical Channels
No full texthttps://doi.org/10.1007/978-3-031-83611-4_3
PnP-Based 6DoF Pose Estimation with Marker Tracking and CFD Simulation Comparison
No full texthttps://doi.org/10.1109/siu66497.2025.1111231