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In the present study, for the first time the machine learning (ML) based refractive index (n) approach is established depends on the density (ρ) parameter of glasses for a dataset of 2000 oxide glasses to predict refractive index of B2O3-CaO-Li2O-Sb2O3 glasses. Density of the investigated glasses varied from 2.56 to 2.97 gm/cm3. The corresponding refractive index was changed from 2.540 to 2.405. The refractive index prediction based on density parameter derived from the density of glasses and constant 'K'. For all M-L techniques including gradient descent (GD), artificial neural network (ANN), and random forest regression (RFR), the density factor is used as an independent variable and the experimental refractive index as a dependent variable. The data set of 10,000 oxide glass samples was employed to forecast density using a variety of machine learning approaches. In comparison to other models, the Random forest regression (RFR) model fitted the glass data with the highest R2 value of 0.949 for refractive index prediction and 0.925 for density prediction. For both the prediction of density and refractive index, the R2 is controlled to 0.932 and 0.9223, respectively. The highest R2 values for refractive index and density prediction were gained when the tanh activation function was used in an artificial neural network (ANN) with varied activation functions. [ABSTRACT FROM AUTHOR]

In the evaluation of a Photovoltaic (PV) system's performance, precise calculation of the system's parameters is essential, as these parameters significantly influence its efficiency across various sunlight intensities, temperature ranges, and distinct load conditions. Addressing the intricate non-linear optimization problem of pinpointing these PV system parameters, the current research adopts a novel metaheuristic optimization approach, called Transit Search (TS). The proposed technique was rigorously tested on a monocrystalline solar panel, which included both single and double-diode model structures. The design of the objective function within this framework aims to diminish the square root of the average squared discrepancies between theoretical and measured current outputs, while remaining within the established parameter bounds. The proficiency of the TS algorithm was highlighted by employing a variety of statistical error indicators, underlining the latter's effectiveness. When pitted against other established optimization algorithms through comparative analysis, TS demonstrated outstanding capabilities, evidently outperforming its contemporaries in the accurate determination of PV system parameters. [ABSTRACT FROM AUTHOR]

In this study, the role of TiO2 on the physica, and optical properties as well as the γ-ray protection features of a set of six glass samples with the chemical formula (65-X)B2O3–15BaO–5Bi2O3–15ZnO–XTiO2, where X = 0–10 mol% in the step of 2% have been investigated. The density (ρ) increased gradually from 3.70 to 3.93 g/cm3 and the molar volume (Vm) reduced from 27.71 to 26.72 cm3/mol as the TiO2 content increased from 0 to 10 mol%. By the inclusion of TiO2 in the glass networks, some absorption bands in the ultraviolet and visible regions are formed. Values of the indirect optical band gaps (Eg) were 2.550, 2.510, 2.470, 2.370, 2.270, and 2.180 eV for Ti-0.0, Ti-2.0, Ti-4.0, Ti-6.0, Ti-8.0, and Ti-10.0 glasses, respectively. The linear refractive index (n0) calculated values varied from 2.515 to 2.631. The linear-attenuation coefficient ( μ) followed the order: Ti-0.0 < Ti-2.0 < Ti-4.0 < Ti-6.0 < Ti-8.0 < Ti-10.0. The sample coded as Ti-10.0 glass sample (highest content of TiO2) has the lowest half (HVL) and tenth (TVL) value layer. Within the investigated energy range of within the range: 51.590–19.480, 50.676–19.722, 50.696–19.833, 50.271–20.012, 49.860–20.193, and 49.460–20.376 for the prepared samples Ti-0.0, Ti-2.0, Ti-4.0, Ti-6.0, Ti-8.0, and Ti-10.0 glasses, respectively. Results confirmed that the suggested titanium bismo-borate glasses can be used in the optical field and as alternative materials for radiation shielding applications. [ABSTRACT FROM AUTHOR]

The melt-quenching method was used to manufacture newly synthesized glasses with a nominal composition of 60B2O3 – 20CaO – 15ZnO – 5Li2O – xEu2O3: 0 (Eu-0.0) ≤ x ≤ 0.5 (Eu-0.5) mol%. The structural, physical, FTIR, UV–visible spectra, and mechanical properties of the synthesized Eu-x glasses are examined. XRD results verified the amorphous condition of proposed glasses. The density (ρ) of the prepared glasses increased from 3.231 to 3.338 g cm−3, but in contrast, the molar volume (VM) decreased from 20.643 to 20.506 cm3 mol−1 with increasing Eu3+ ions. FTIR spectroscopy illustrated absorbance peaks appear around 393 and 464 nm, which indicates the presence of electronic states in the wide band gap of glass matrix. These peaks are attributed to the 5L6 and 5D2 electronic states of Eu3+ ions. UV–visible measurements showed an improvement in optical absorbance and a decrease in optical energy gap. The Eu3+ ions mol% doping into the proposed glasses results in generating photoluminescence glasses, which is attributed to the 5D0 → 7F1, 5D0 → 7F2, 5D0 → 7F3, and 5D0 → 7F4 electronic transitions of Eu3+ ions. Thus, the emission spectra due to the 393 nm excitation results in the appearance of emission peaks at 593 (orange), 617 (strong red), 653 (red), and 698 (red) nm. The Poisson's ratio (σ) of Eu-x glasses is decreased from 0.3927 to 0.3903 as the molar fraction of Eu3+ ions is increased from 0.0 to 0.5 mol%. The thermodynamic properties of the glassy network are hidden in the Gibbs free energy (G) which started at 33.56 and ended at 33.72 kJ.cm−3 at low and high Eu3+ ions content mol%. Furthermore, all elastic moduli increased linearly with molar increment of Eu3+ ions in the molecular structure of the proposed glassy network. [ABSTRACT FROM AUTHOR]

Four glasses of cadmium lead-borate glasses with nominal compositions of (75-X)B2O3–XPbO–5Na2O–10CdO–10ZnO: X = 5 (BPNCZPb-5), 10 (BPNCZPb-10), 15 (BPNCZPb-15), and 20 (BPNCZPb-20) mol% were fabricated using the well-known melt quenching route.The role of B2O3/PbO substitution on the physical properties and γ-ray shielding factors have been evaluated via MCNP simulation code and PhX software in the γ-energy range of 0.015: 15 MeV. The density (ρ) and molar volume (Vm) of the examined glasses grows systematically from 4.82 to 5.664 g/cm3 and from 18.88 to 22.02 cm3/mol as the PbO content increases from 5 to 20 mol% in the glass network. The oxygen molar volume (OMV) increased following the observation of an opposing the oxygen packing density (OPD) trend. The obtained values of simulated linear-absorption coefficient (µ) were in decent agreement with the values calculated by PhX software with a maximum relative differences, φ = of 4.497%. The simulated µ values drop from 127.981 to 0.130 cm−1 for BPNCZPb-5, from 189.241 to 0.158 cm−1 for BPNCZPb-10, from 243.308 to 0.180 cm−1 for BPNCZPb-15, and from 299.755 to 0.206 cm−1 for BPNCZPb-20 at photon energy range from 0.015: 15 MeV. At 0.5, 5, and 10 MeV, the µ of the BPNCZPb-X glasses have higher values than those of concretes. The BPNCZPb-20 glass sample possessed the lowest half- (HVL) and tenth- (TVL) value layers. The radiation protection efficiency (RPE) values reduced from ≈ 100.000% at 0.015 for all BPNCZPb-X glass samples to 6.305% (BPNCZPb-5), 7.587% (BPNCZPb-10), 8.626% (BPNCZPb-15), and 9.777% (BPNCZPb-20), respectively at gamma-ray energy 15 MeV. Results confirm that the suggested samples can be applied as alternative materials for radiation safety applications. [ABSTRACT FROM AUTHOR]

Breast cancer is one of the major threats that attack women around the world. Its detection and diagnosis in the early stages can greatly improve care efficiency and reduce mortality rate. Early detection of breast cancer allows medical professionals to use less intrusive treatments, such as lumpectomies or targeted medicines, improving survival rates and lowering morbidity. This study developed a breast cancer segmentation system based on an improved version of the U-Net 3+ neural network. Various optimizations were applied to this architecture to improve the localization and segmentation performance. An evaluation of different state-of-the-art networks was performed to improve the performance of the proposed breast cancer diagnosis system. Various experiments were carried out on the INbreast Full-Field Digital Mammographic dataset (INbreast FFDM). The results obtained demonstrated that the proposed model achieved a dice score of 98.47%, which is a new state-of-the-art segmentation finding, showcasing its efficiency in detecting breast cancer from mammography images with the possibility of implementation for real applications. [ABSTRACT FROM AUTHOR]

In this work, the role of insertion cobalt(II) on the physical properties, dielectric spectroscopy, and photon attenuation parameters of the prepared glasses 25NaF-10ZnO-(65-x)B2O3-xCoO-0.6Y2O3: x = 0.0 (Co-0.0) ≤ x ≤ 0.5 (Co-0.5) mol% has been investigated. The amorphous state of samples verified via the XRD measurements. The density (ρ) ∈ [2.9824, 3.0058 g.cm−3]. The molar volume (Vm) ∈ [21.868, 21.715 cm3.mol−1] as an increase of CoO from 0.0 to 0.5 mol% in the glass network. Dielectric spectroscopy of borate glass loaded with varying cobalt content was investigated throughout frequency range from 50 to 5 MHz. The recorded dielectric constant at 3 kHz was enhanced from 14.4 to 17.8 by cobalt doping. The dependency of tangent loss (tan δ) for all investigated glasses on frequency is normal behavior with dielectric relaxation which is enhanced and shifted by cobalt doping. At the photon energy (E = 0.015 MeV), the mass-attenuation-coefficient (MAC) values were 10.192, 10.246, 10.300, 10.354, and 10.408 cm2/g for the samples Co-0.0, Co-0.1, Co-0.2, Co-0.30, Co-0.4, and Co-0.5, respectively. These MAC values are corresponding to as increment of 0.216 cm2/g between the low and high CoO contents presented in the glass samples. Values of half value layer (HVL) of all proposed specimens were more significant than that of RS-360 and RS-520 commercial glasses. Results confirmed that the suggested glasses are suitable for radiation attenuation. [ABSTRACT FROM AUTHOR]

In this study, a bald eagle optimizer (BEO) is used to get optimal parameters of the fractional-order proportional-integral-derivative (FOPID) controller for load frequency control (LFC). SinceBEOtakes only a very short time in finding the optimal solution, it is selected for designing the FOPID controller that improves the system stability and maintains the frequency within a satisfactory range at different loads. Simulations and demonstrations are carried out using MATLAB-R2020b. The performance of the BEOFOPID controller is evaluated using a two-zone interlinked power system at different loads and under uncertainty of wind and solar energies. The robustness of the BEO-FOPID controller is examined by testing its performance under varying system time constants. The results obtained by the BEOFOPID controller are compared with those obtained by BEO-PID and PID controllers based on recent metaheuristics optimization algorithms, namely the sine-cosine approach, Jaya approach, grey wolf optimizer, genetic algorithm, bacteria foraging optimizer, and equilibrium optimization algorithm. The results confirm that the BEO-FOPID controller obtains the finest result, with the lowest frequency deviation. The results also confirm that the BEOFOPID controller is stable and robust at different loads, under varying system time constants, and under uncertainty of wind and solar energies. [ABSTRACT FROM AUTHOR]

Groundwater (GW) quality evaluation includes a variety of biological, chemical and physical parameters. The fundamental problem with water quality assessment is the difficulty with which a large number of parameters are evaluated. If all criteria have been used to evaluate the quality of GW, then computational difficulty will certainly increase. In this paper, a new hybrid three-stage assessment approach based on Feature Extraction Algorithm (FEA), standard deviation (SD) and Complex Proportional Assessment Method (COPRAS) was proposed. In the first stage the redundant criteria for GW quality assessment is removed using FEA. Secondly, the weights of the reduct parameters are evaluated based on SD. Finally, GW sites are ranked using (COPRAS). Sixteen GW samples were gathered from several GW wells. The collected samples were investigated for 12 various physicochemical water quality criteria to evaluate GW quality. The results reveal that sulfates (SO4), nitrate (NO3), Fluorides (F), sodium (Na), and Escherichia coli (E. coli) are the main parameters for GW quality assessment. Furthermore, the optimal concentrations of physicochemical parameters: (SO4), (NO3), (F), (Na), and (E. coli) are 18.9(mg/L), 8.18(mg/L), 0.222(mg/L), 21(mg/L), 1.9(MPN/100mL), respectively, with 40 WQI.The suggested approach is compared to three MCDM methods to validate the performance of the proposed methodology. The assessment results gained by the FEA combined with COPRAS and SD significantly minimize computational difficulty, reasonable and accurate. The approach presented in this study improves the system for evaluating GW quality. [ABSTRACT FROM AUTHOR]