Robust and High Accuracy Algorithm for Detection of Pupil Images

Recently, many researchers have tried to develop a robust, fast, and accurate algorithm. This algorithm is for eye-tracking and detecting pupil position in many applications such as head-mounted eye tracking, gaze-based human-computer interaction, medical applications (such as deaf and diabetes patients), and attention analysis. Many real-world conditions challenge the eye appearance, such as illumination, reflections, and occasions. On the other hand, individual differences in eye physiology and other sources of noise, such as contact lenses or make-up. The present work introduces a robust pupil detection algorithm with and higher accuracy than the previous attempts for real-time analytics applications. The proposed circular hough transform with morphing canny edge detection for Pupillometery (CHMCEP) algorithm can detect even the blurred or noisy images by using different filtering methods in the pre-processing or start phase to remove the blur and noise and finally the second filtering process before the circular Hough transform for the center fitting to make sure better accuracy. The performance of the proposed CHMCEP algorithm was tested against recent pupil detection methods. Simulations and results show that the proposed CHMCEP algorithm achieved detection rates of 87.11, 78.54, 58, and 78 according to Świrski, ExCuSe, Else, and labeled pupils in the wild (LPW) data sets, respectively. These results show that the proposed approach performs better than the other pupil detection methods by a large margin by providing exact and robust pupil positions on challenging ordinary eye pictures.     

Theoretical Investigation of Magnetoelectric Coupling in MFe2O4/PbZ0.5T0.5O3/MFe2O4 (M = Ni,Co) Heterostructure

Journal of Superconductivity and Novel Magnetism - Magnetoelectric materials that allow magnetic-field control of electric polarization are promising candidates for high-density data storage and...     

Magnetocaloric Properties of the Perovskite GdCuO3: Monte Carlo Simulation

Journal of Superconductivity and Novel Magnetism - This work aims to examine the magnetocaloric properties of the Perovskite GdCuO3, such as the total magnetization, the susceptibility, and the...     

Impact and visibility of Norwegian,Finnish and Spanish journals in the fields of humanities

Scientometrics - This article analyses the impact and visibility of scholarly journals in the humanities that are publishing in the national languages in Finland, Norway and Spain. Three types of...     

Investigating optical,electrical, and mechanical traits of thiourea admixtured KDP single crystals to explore NLO device applications

The 0.5 and 1 mol% thiourea “mixed” potassium dihydrogen phosphate (KDP) crystals have been developed by conventional slow solution evaporation method. The crystallographic parameters of grown crystals have been determined by employing single crystal X-ray diffraction technique. The functional groups of grown crystals were successfully identified by means of FTIR spectral analysis. The optical transmittance is 79%, 84%, and 89% for KDP, 0.5 mol thiourea mixed KDP, and 1 mol thiourea mixed KDP crystal. The energy band gap (E_g) of KDP, 0.5 mol thiourea mixed KDP, and 1 mol thiourea mixed KDP crystal is 3.71 eV, 3.61 eV, and 3.75 eV, respectively. The Kurtz–Perry test has been employed to determine the SHG efficiency and SHG efficiency of 0.5 and 1 mol thiourea mixed KDP crystal is 2.09 and 2.22 times superior to KDP crystal. Effect of thiourea mixing on hardness properties of KDP crystal have been scrutinized using the Vickers microhardness studies. The frequency dependent dielectric behavior of grown crystals has been analyzed at room temperature.

     

Influence of carbon nanotubes and dispersions of SiC on the physical and mechanical properties of pure copper and copper‐nickel alloy

This paper investigates the physical and mechanical properties of copper‐nickel alloy (at 50 wt.%–50 wt.%) and pure copper, mixed with various types of reinforcement materials such as carbon nanotubes (0.5 wt.%–2 wt.%) as nanoparticles, silicon carbide (1 wt.%–4 wt.%) as microparticles. The acquired composite specimens characteristics were estimated such as microstructure, density, electrical and thermal conductivity, hardness, and compression stress properties to determine the suitable reinforcement percentage that has the best physical and mechanical properties with different main matrix material whether copper‐nickel mechanical alloying or pure copper powder. The micron‐sized silicon carbide and nanosized carbon nanotubes were added to improve the mechanical and physical properties of the composite. The electrical and thermal conductivity of pure copper alloy enhanced compared with the copper‐nickel alloy matrix material. The hardness and compression yield stress of both pure copper and copper‐nickel composites have enhancement values and for copper‐nickel base composites hardness and compression yield stress have enhanced with the most positive enhancement values to examined an optimum percentage of reinforcing material.     

Insights into the Electrochemical Behavior of Manganese Oxides as Catalysts for the Oxygen Reduction and Evolution Reactions: Monometallic Core-Shell Mn/Mn3O4

Overcoming the sluggish electrode kinetics of both oxygen reduction and evolution reactions (ORR/OER) with non-precious metal electrocatalysts will accelerate the development of rechargeable metal-air batteries and regenerative fuel cells. The authors investigated the electrochemical behavior and ORR/OER catalytic activity of core-porous shell Mn/Mn₃O₄ nanoparticles in comparison with other manganese dioxides (β- and γ-MnO₂), and benchmarked against Pt/C and Pt/C-IrO₂. Under reversible operation in O₂-saturated 5 M KOH at 22 °C, the early stage activity of core-shell Mn/Mn₃O₄ shows two times higher ORR and OER current density compared to the other MnO₂ structures at 0.32 and 1.62 V versus RHE, respectively. It is revealed that Mn(III) oxidation to Mn(IV) is the primary cause of Mn/Mn₃O₄ activity loss during ORR/OER potential cycling. To address it, an electrochemical activation method using Co(II) is proposed. By incorporating Co(II) into MnO_x, new active sites are introduced and the content of Mn(II) is increased, which can stabilize the Mn(III) sites through comproportionation with Mn(IV). The Co-incorporated Mn/Mn₃O₄ has superior activity and durability. Furthermore, it also surpassed the activity of Pt/C-IrO₂ with similar durability. This study demonstrates that cost-effective ORR/OER catalysis is possible.     

Combined experimental and TDDFT computational studies of the optical and electrical characteristic of luminol films-doped TiO2 with 9.027% power conversion efficiency

Journal of Materials Science: Materials in Electronics - In this study, the spectrophotometric analysis was applied to check the optical properties of undoped [LO]TF and doped Luminol films with...     

Effect of pre-deposition annealing on physical properties of CZTSSe thin films deposed by RF-sputtering based on nanoparticles synthesized by solvothermal technique

This work aims to highlight the beneficial effect of annealing of Cu₂ZnSn(S,Se)₄ (CZTSSe) nanoparticles (NPs) on the properties of the obtained films by RF-magnetron sputtering at room temperature (RT) and at 200 °C. The CZTSSe targets used for the deposition are obtained using nanoparticles synthesized by solvothermal technique. It is denoted that the elemental composition of thin films becomes independent of the growth temperature in the case of annealed CZTSSe NPs. The optical investigation gives that the gap energy is ranging between 1.26 and 1.40 eV with an Urbach’s energy between 100 and 200 meV. By using the Wemple and Didominico model to analyze the refractive index spectra, we have identified common oscillator energy for all CZTSSe thin films and dispersion energy ranging from 2.63 to 5.81 eV. CZTSSe thin films obtained by means of annealed NPs exhibit higher dielectric constant and refractive index. The dispersion of different parameters with experimental conditions is analyzed via a common relationship that illustrates the linear dependence of n₀, E_d, ε_s, and ε_L on the square of the valence difference (ΔZ). The conductivity spectra are deduced, and a theoretical model was identified to fit the permittivity spectra. The obtained results are promising for solar cell applications.

     

A review on the design and optimization of antennas using machine learning algorithms and techniques

This paper presents a focused and comprehensive literature survey on the use of machine learning (ML) in antenna design and optimization. An overview of the conventional computational electromagnetics and numerical methods used to gain physical insight into the design of the antennas is first presented. The major aspects of ML are then presented, with a study of its different learning categories and frameworks. An overview and mathematical briefing of regression models built with ML algorithms is then illustrated, with a focus on those applied in antenna synthesis and analysis. An in‐depth overview on the different research papers discussing the design and optimization of antennas using ML is then reported, covering the different techniques and algorithms applied to generate antenna parameters based on desired radiation characteristics and other antenna specifications. Various investigated antennas are sorted based on antenna type and configuration to assist the readers who wish to work with a specific type of antennas using ML.