Related papers: Measuring Thermal Profiles in High Explosives usin…
Power and thermal management are critical components of High-Performance-Computing (HPC) systems, due to their high power density and large total power consumption. The assessment of thermal dissipation by means of compact models directly…
In this paper the methodology and the results of a quasi real-time thermal characterization tool and method for the temperature mapping of circuits and boards based on sensing the infrared radiation will be introduced. With the proposed…
In this paper, a simple algorithm for detailed system-level thermal noise analysis is developed, demonstrated, and verified. This method uses noise-wave theory and noise covariance matrices to cascade noise and scattering parameters of…
In building management, usually static thermal setpoints are used to maintain the inside temperature of a building at a comfortable level irrespective of its occupancy. This strategy can cause a massive amount of energy wastage and…
We develop a neuroevolution-potential (NEP) framework for generating neural network based machine-learning potentials. They are trained using an evolutionary strategy for performing large-scale molecular dynamics (MD) simulations. A…
Convolutional neural networks (CNNs) can potentially provide powerful tools for classifying and identifying patterns in climate and environmental data. However, because of the inherent complexities of such data, which are often…
Context. The gas kinetic temperature (TK) determines the physical and chemical evolution of the Interestellar Medium (ISM). However, obtaining reliable TK estimates usually requires expensive observations including the combination of…
We propose a new method for computing the temperature dependence of the heat capacity in complex molecular systems. The proposed scheme is based on the use of the Langevin equation with low frequency color noise. We obtain the temperature…
Neural network calibration is an essential task in deep learning to ensure consistency between the confidence of model prediction and the true correctness likelihood. In this paper, we propose a new post-processing calibration method called…
The quasi-harmonic Debye approximation has been implemented within the AFLOW and Materials Project frameworks for high-throughput computational science (Automatic Gibbs Library, AGL), in order to calculate thermal properties such as the…
The Infrared Atmospheric Sounding Interferometer (IASI) on board the MetOp satellite series provides important measurements for Numerical Weather Prediction (NWP). Retrieving accurate atmospheric parameters from the raw data provided by…
The materials of surfaces in a room play an important room in shaping the auditory experience within them. Different materials absorb energy at different levels. The level of absorption also varies across frequencies. This paper…
This paper describes the design, implementation, and verification of a test-bed for determining the noise temperature of radio antennas operating between 400-800MHz. The requirements for this test-bed were driven by the HIRAX experiment,…
Enhancing band convergence is an effective way to optimize the thermoelectric (TE) properties of materials. However, the temperature-induced band renormalization is commonly ignored. By employing the recently-developed electron-phonon…
A new analysis method has been developed for measurements of broadband, low-amplitude turbulent electron temperature fluctuations in fusion plasmas using individual radiometer channels of a Correlation Electron Cyclotron Emission (CECE)…
This paper deals with an analytical modeling of heat transfers simulating a new radiation calorimeter operating in a temperature range from -50 {\deg}C to 150 {\deg}C. The aim of this modeling is the evaluation of the feasibility and…
The work presented here applies deep learning to the task of automated cardiac auscultation, i.e. recognizing abnormalities in heart sounds. We describe an automated heart sound classification algorithm that combines the use of…
Delta-T shot noise is activated in temperature-biased electronic junctions, down to the atomic scale. It is characterized by a quadratic dependence on the temperature difference and a nonlinear relationship with the transmission…
Breast cancer diagnosis through thermographic image analysis remains a critical challenge in medical AI, with classical deep learning approaches facing limitations in complex thermal pattern classification tasks. This paper presents a novel…
Recent publications have described a method for stand-off optical detection of explosives using resonant infra-red photothermal imaging. This technique uses tuned lasers to selectively heat small particles of explosive lying on a substrate…