A. F. Gochuyeva^*, Kh. Kh. Hashimov, I. Y. Bayramov

Chalcogenide Letters, Vol.20, No.4, pp. 285-291, 2023, DOI:10.15251/CL.2023.204.285

Abstract The photoelectret effect in composite heterostructures consisting of polar (fluorinecontaining) and non-polar (polyolefins) polymers - high density polyethylene (HDPE), low density polyethylene (LDPE), F42, F2-ME and the inorganic phase A^II B^VI (CdS, ZnS) has been studied. It has been established that the difference in photoelectret potentials in a given volume share of the inorganic phase mainly depends on the polarity of the polymer matrix. A possible mechanism of the photoelectret effect formed under the combined action of a strong electric field and light in these composites. It has been experimentally established that the potential barrier formed More >

D. Dekhil^a,*, H. Guessas^a, A. Nouri^a, S. Ullah^b

Chalcogenide Letters, Vol.20, No.8, pp. 549-558, 2023, DOI:10.15251/CL.2023.208.549

Abstract SnS thin films were synthesized using the spray pyrolysis method and then annealed at 350, 400, and 450°C. According to the crystallographic analysis, the obtained SnS thin films crystallized in the polycrystalline orthorhombic system. The grains measured 47, 66, and 37 nm for the samples annealed at 350, 400, and 450°C, respectively. SEM and AFM images indicate that the samples’ surfaces were completely covered. Thus, the grains of SnS nanostructures have a granular-like shape and vary in size depending on the annealing temperatures. The transmittance measurement shows that annealing the sample at 400 °C extends… More >

O. V. Iaseniuc^*, M. S. Iovu

Chalcogenide Letters, Vol.20, No.10, pp. 725-731, 2023, DOI:10.15251/CL.2023.2010.725

Abstract In the present work some nanostructured quaternary chalcogenides of the As-S-Sb-Te sys tem have been investigated by a photoelectric method. The spectral distribution of steady state photocurrent I_ph=(λ) and the relaxation curves of photocurrent I_ph=(t) were registered at positive and negative polarity of the applied voltage to the top Al illuminated electrode. In the spectral distribution of steady-state photocurrent, for the amorphous thin films As_1.17S_2.7Sb_0.83Te_0.40, As_1.04S_2.4Sb_0.96Te_0.60, As_0.63S_2.7Sb_1.37Te_0.30, and As_0.56S_2.4Sb_1.44Te_0.60 in the wavelength range λ=0.50÷0.92 mm (2.48÷1.35 eV) some maxima were detected, which are the result of the presence of binary clusters As₂S₃, Sb₂S₃ and Sb₂S₃. The photo voltaic method was used More >

RABIRANJAN MURMU^a,b, DEBASHIS ROY^a, HAREKRUSHNA SUTAR^b

Journal of Polymer Materials, Vol.40, No.3-4, pp. 125-139, 2023, DOI:10.32381/JPM.2023.40.3-4.1

Abstract A one dimensional isothermal model is proposed by modelling the kinetics of methanol transport at anode flow channel (AFC), membrane and cathode catalyst layer of direct methanol fuel cell (DMFC). Analytical model is proposed to predict methanol cross-over rate through the electrolyte membrane and cell performance. The model presented in this paper considered methanol diffusion and electrochemical oxidation at the anode and cathode channels. The analytical solution of the proposed model was simulated in a MATLAB environment to obtain the polarization curve and leakage current. The effect of methanol concentration on cell voltage and leakage More >

Dazhi Wang^*, Pengyi Pan, Bowen Niu

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1535-1555, 2023, DOI:10.32604/cmc.2023.042286 - 29 November 2023

Abstract The permanent magnet eddy current coupler (PMEC) solves the problem of flexible connection and speed regulation between the motor and the load and is widely used in electrical transmission systems. It provides torque to the load and generates heat and losses, reducing its energy transfer efficiency. This issue has become an obstacle for PMEC to develop toward a higher power. This paper aims to improve the overall performance of PMEC through multi-objective optimization methods. Firstly, a PMEC modeling method based on the Levenberg-Marquardt back propagation (LMBP) neural network is proposed, aiming at the characteristics of… More >

Muhammad Usman Ghani Khan¹, Abid Mehmood², Mourad Elhadef², Shehzad Ashraf Chaudhry^2,3,*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2225-2249, 2023, DOI:10.32604/cmc.2023.038303 - 29 November 2023

Abstract The proliferation of deluding data such as fake news and phony audits on news web journals, online publications, and internet business apps has been aided by the availability of the web, cell phones, and social media. Individuals can quickly fabricate comments and news on social media. The most difficult challenge is determining which news is real or fake. Accordingly, tracking down programmed techniques to recognize fake news online is imperative. With an emphasis on false news, this study presents the evolution of artificial intelligence techniques for detecting spurious social media content. This study shows past,… More >

AMGAD M. RABIE^*

BIOCELL, Vol.47, No.10, pp. 2133-2139, 2023, DOI:10.32604/biocell.2023.030057 - 08 November 2023

Abstract Despite the global decline in the severity of the coronavirus disease 2019 (COVID-19) cases, the disease still represents a major concern to the relevant scientific and medical communities. The primary concern of drug scientists, virologists, and other concerned specialists in this respect is to find ready-to-use suitable and potent anticoronaviral therapies that are broadly effective against the different species/strains of the coronaviruses in general, not only against the current and previous coronaviruses (e.g., the recently-appeared severe acute respiratory syndrome coronavirus 2 “SARS-CoV-2”), i.e., effective antiviral agents for treatment and/or prophylaxis of any coronaviral infections, including More > Graphic Abstract

Zhaoan Wang¹, Shaoping Xiao^1,*, Cheryl Reuben², Qiyu Wang², Jun Wang²

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 285-297, 2023, DOI:10.32604/cmc.2023.044366 - 31 October 2023

Abstract This paper presents designing sequence-to-sequence recurrent neural network (RNN) architectures for a novel study to predict soil NOx emissions, driven by the imperative of understanding and mitigating environmental impact. The study utilizes data collected by the Environmental Protection Agency (EPA) to develop two distinct RNN predictive models: one built upon the long-short term memory (LSTM) and the other utilizing the gated recurrent unit (GRU). These models are fed with a combination of historical and anticipated air temperature, air moisture, and NOx emissions as inputs to forecast future NOx emissions. Both LSTM and GRU models can… More >

Maryam Bukhari¹, Sadaf Yasmin¹, Sheneela Naz², Mehr Yahya Durrani¹, Mubashir Javaid³, Jihoon Moon⁴, Seungmin Rho^5,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1251-1279, 2023, DOI:10.32604/cmc.2023.040329 - 31 October 2023

Abstract Effective smart healthcare frameworks contain novel and emerging solutions for remote disease diagnostics, which aid in the prevention of several diseases including heart-related abnormalities. In this context, regular monitoring of cardiac patients through smart healthcare systems based on Electrocardiogram (ECG) signals has the potential to save many lives. In existing studies, several heart disease diagnostic systems are proposed by employing different state-of-the-art methods, however, improving such methods is always an intriguing area of research. Hence, in this research, a smart healthcare system is proposed for the diagnosis of heart disease using ECG signals. The proposed… More >

T. M. Nithya^1,*, R. Umanesan², T. Kalavathidevi³, C. Selvarathi⁴, A. Kavitha⁵

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2537-2547, 2023, DOI:10.32604/iasc.2022.028804 - 11 September 2023

Abstract Big data analytics is a popular research topic due to its applicability in various real time applications. The recent advent of machine learning and deep learning models can be applied to analyze big data with better performance. Since big data involves numerous features and necessitates high computational time, feature selection methodologies using metaheuristic optimization algorithms can be adopted to choose optimum set of features and thereby improves the overall classification performance. This study proposes a new sigmoid butterfly optimization method with an optimum gated recurrent unit (SBOA-OGRU) model for big data classification in Apache Spark. More >