The physical substance at high energy level with specific circumstances; tend to behave harsh and complicated, meanwhile, sustaining equilibrium or non-equilibrium thermodynamic of the system. Measurement of the temperature by ordinary techniques in these cases is not applicable at all. Likewise, there is a need to apply mathematical models in numerous critical applications to measure the temperature accurately at an atomic level of the matter. Those mathematical models follow statistical rules with different distribution approaches of quantities energy of the system. However, these approaches have functional effects at microscopic and macroscopic levels of that system. Therefore, this research study represents an innovative of a wireless temperature sensor, which utilizes proton resonance frequency of carbon-13 isotope material. In addition to that, this study also addresses the energy distribution of the particles by selecting an updated appropriate approach that has interesting points of limitation in the number of degree of freedom: (1) thermodynamically limits and (2) theoretical statistical thermodynamics observations. Lastly, the main idea of this paper is to visualize the analysis of temperate in the nanoscale system via statistical thermodynamics approach along with the material characterization of carbon-13 isotope.
This paper presents the Extended State Observer (ESO) based repetitive control (RC) for piezoelectric actuator (PEA) based nano-positioning systems. The system stability is proved using Linear Matrix Inequalities (LMIs), which guarantees the asymptotic stability of the system. The ESObased RC used in this paper has the ability to eliminate periodic disturbances, aperiodic disturbances and model uncertainties. Moreover, ESO can be tuned using only two parameters and the model free approach of ESO-based RC, makes it an ideal solution to overcome the challenges of nano-positioning system control. Different types of periodic and aperiodic disturbances are used in simulation to demonstrate the effectiveness of the algorithm. The comparison studi
... Show MoreBinary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin
... Show MoreA medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un
... Show MoreEarly detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med
... Show MoreThe mechanical properties and microstructure of hot-rolled steel are critical in determining its performance in industrial applications, particularly when exposed to elevated temperatures. This study examines the effects of varying temperatures and soaking times on these properties through a series of controlled experiments. The primary objective was to optimize the key response parameters, including tensile strength, yield strength, and elongation, by analyzing the influence of temperature and time. A full factorial design approach was used, applying the desirability function theory to explore all possible combinations and identify optimal processing conditions. The experimental results showed that the soaking time played a critica
... Show MoreMany researchers tried to prevent or reduce moisture damage and its sensitivity to temperature to improving the performance of hot mix asphalt because it is decreasing the functional and structural life of fixable pavement due to the moisture damage had exposed to it.
The main objective of this study is to inspect the effect of (fly ash “3%, 6%, 12%”, hydrated lime”5%, 10%, 20%” and silica fumes”1%, 2%, 4%) referring to previous research by the net weight asphalt cement as a modified material on the moisture and temperature sensitivity of hot mix asphalt. This was done using asphalt from AL-Nasiria refinery with penetration grade 40-50, nominal maximum size (12.5) mm (surface course) of aggregate and on
... Show MoreWarm dark matter (WDM) models offer an attractive alternative to the current cold dark matter (CDM) cosmological model. We present a novel method to differentiate between WDM and CDM cosmologies, namely, using weak lensing; this provides a unique probe as it is sensitive to all of the “matter in the beam,” not just dark matter haloes and the galaxies that reside in them, but also the diffuse material between haloes. We compare the weak lensing maps of CDM clusters to those in a WDM model corresponding to a thermally produced 0.5 keV dark matter particle. Our analysis clearly shows that the weak lensing magnification, convergence, and shear distributions can be used to distinguish
