bluuebunny/crossref_metadata_2025 huggingface dataset:
The effect of temperature on nickel oxide thin films produced by spray pyrolysis method using a solar oven
Authors: Rouane Azeddine , Gharbi Abderrezak
Published: December 2024

Nickel oxide (NiO) thin films were deposited on glass substrates using spray pyrolysis to study the effect of fabrication temperature on their structural, optical, and electrical properties. Processing temperatures of 350°C, 450°C, and 550°C were used. X-ray diffraction (XRD) revealed cubic crystals with a single-phase structure oriented along the (220) axis. Grain sizes ranged from 8.2 nm to 64.52 nm. Optical band gaps increased from 3.37 eV to 3.57 eV with higher temperatures, while Urbach energy decreased from 362.12 meV to 280.32 meV. Electrical resistivity varied from 316.22 Ω.cm to 1500.14 Ω.cm, and hole concentration from 5.645x1018 cm-3 to 9.987x1018 cm3.
Ability to produce biofilms and antibiotic resistance of coagulase-negative Staphylococci isolated from meat-based street foods
Authors: Boulmaiz Sara , Ammar Ayachi , Bouguenoun Widad
Published: December 2024

Aims: This study investigated the biofilm-producing ability and antibiotic resistance profiles of Coagulase-negative staphylococci (CNS) bacteria isolated from meat-based street foods in Biskra, Algeria. Methods and Results: The study identified 50 CNS isolates, including S. lentus, S. xylosus, S. hominis, S. haemolyticus, S. lugdnensis, and S. capitis, using the Api Staph and Vitek systems. The Vitek method was employed for in vitro antibiotic susceptibility testing, while biofilm formation was evaluated using the Tissue Culture Plate (TCP) and Congo Red Agar (CRA) methods. Results indicated that 64% of the coagulase-negative staphylococci strains exhibited multiple drug resistance, with the highest biofilm formation observed in S. hominis under fed batch mode. Conclusions: The study highlights the high prevalence of multidrug-resistant and biofilm-forming coagulase-negative staphylococci bacteria in meat-based street foods. These bacteria pose a potential health risk, acting as reservoirs for the transmission of antimicrobial-resistant bacteria from food to humans, thereby contributing to the spread of resistan pathogens in the community.
Synthesis, characterization, and theoretical examination of corrosion inhibition properties of anilinesalicylidene Schiff base
Authors: Aicha Bara , Rihana Hadjeb
Published: December 2024

This study investigates the synthesis, characterization, and corrosion inhibition performance of an anilinesalicylidene Schiff base, derived from aniline and salicylaldehyde, as an efficient inhibitor for XC48 steel in acidic environments. The Schiff base was synthesized via both conventional methods and an organic (green) synthesis approach, emphasizing sustainability and reduced environmental impact. Its structure was confirmed using spectroscopic techniques, including FTIR and UV-Vis spectroscopy. Gravimetric analyses were performed to evaluate the inhibitor’s efficiency in 1 M hydrochloric acid, revealing excellent protection against corrosion. Furthermore, a theoretical analysis using Density Functional Theory (DFT) provided insights into the molecular structure's influence on its inhibitory properties. Parameters such as the energy gap, dipole moment, and electronic density distribution were calculated to elucidate the adsorption mechanism on the steel surface. The combined experimental and theoretical findings underline the Schiff base's potential as an eco-friendly and cost-effective corrosion inhibitor for industrial applications.
Energy consumption estimation for a dome greenhouse under different climatic conditions in Algeria
Authors: Kherrour Sofiane , Zarrit Rida , Lebbi Mohamed , Dadda Bachir , Kaci Karim , Bezari Salah , Cherier Mohamed Kamal , Boutina Lyes
Published: December 2024

The ongoing work focuses on studying the dome greenhouse to maintain a suitable temperature for crop environments throughout their growth period by using renewable energy sources to increase the required heat or cool down in cases of extreme heat. To this end, we have studied the effect of the different climates that Algeria has on the amount of energy required by the dome greenhouse to maintain favorable temperatures for crops, utilizing the EnergyPlus simulation tool. The results reveal that the total annual energy delivered to the dome greenhouse reaches its highest value of 14,931.68 kWh in a humid subtropical climate (Tebessa), while its lowest value is 10,396.68 kWh in a hot semi-arid climate (South of Oran). In contrast, to maintain suitable temperatures for growing most crops, the cooling energy (both sensible and latent) provided to the greenhouse in the hot desert climate (Ghardaïa) reached a high percentage of 63.24% of the total annual energy supplied. Meanwhile, the humid subtropical climate has the highest total heating energy at 69.4%. Also, the total cooling energy and total heating energy in the cold semi-arid climate regions (Saida) and the cold desert climate regions (Mecheria) reached 37.35%, 62.65%, and 34.39%, 65.61%, respectively. These percentages are also quite close in both the Mediterranean climate with a hot summer (Algeria) and the hot semi-arid climate. This analysis will provide critical insights into effective greenhouse management strategies tailored to Algeria's diverse environmental contexts, ultimately promoting sustainable agricultural practices.
Thiourea-controlled synthesis of CdS thin films: a study on crystallinity and optical behavior
Authors: Becer Zoubir , Beggas Azzeddine , Ahmim Rachid , Laib Abdellatif
Published: December 2024

Cadmium sulfide (CdS) thin films were synthesized on glass substrates using the chemical bath deposition (CBD) technique to investigate the effects of varying thiourea concentrations on their structural and optical properties. X-ray diffraction (XRD) analysis confirmed a cubic zinc blende structure, with decreasing crystallinity and grain sizes, which reduced from 55.67 nm to 11.34 nm, as thiourea concentration increased. The micro strain and dislocation density showed an increasing trend, with micro strain rising from  to  and dislocation density increasing from  lines/m² to  lines/m², indicating a deterioration in crystalline quality and increased lattice imperfections at higher thiourea concentrations. These structural changes influenced film morphology, reducing grain connectivity and increasing surface disorder. Optical analyses revealed a blue shift in the transmission spectra, higher transmittance, and a band gap widening from 1.80 eV to 1.96 eV, with Urbach energy rising from 0.2 eV to 0.5 eV. The refractive index has been found to decrease with increasing thiourea content. These findings demonstrate that thiourea concentration significantly affects both the structural integrity and optical properties of CdS thin films, highlighting their potential for tailored optoelectronic applications.
Numerical modeling of the impact of an anti-reflective coating layer on a silicon solar cell using PC1D
Authors: Amara Zeyneb , Daikh Ahmed Amine , Benkhedda Amine , Bouazza Marwa , Berkouk Rania , Radja Imane
Published: December 2024

This study presents a numerical simulation of the behavior of three types of solar cells: Si (N⁺)/Si (P), SnO₂/Si (N⁺)/Si (P), and ZnO/Si (N⁺)/Si (P). The research focuses on analyzing the impact of SnO₂ and ZnO window layers on the device's overall performance using the well-known photovoltaic modeling software PC1D. The addition of SnO₂ and ZnO layers, which act as anti-reflective coatings, was carefully evaluated for their influence on the solar cells' key characteristics, including current-voltage (I-V), power-voltage (P-V), and conversion efficiency. Comparative analysis revealed a significant improvement in the performance of the cells incorporating these window layers. Specifically, the SnO₂/Si (N⁺)/Si (P) structure exhibited an efficiency enhancement of 31.41%, while the ZnO/Si (N⁺)/Si (P) structure achieved a further increase, reaching 33.64%. These findings underscore the critical role of anti-reflective coatings in optimizing photovoltaic performance, highlighting their potential for improving the efficiency of silicon-based solar cells in practical applications. This work contributes to the advancement of cost-effective and high-performance solar energy technologies.
Improving thermal resistance of multilayer walls with drinn, sheep wool, and palm fibers: a case study in Ouargla, Algeria
Authors: Necib Hichem , Mosbah Noureddine
Published: December 2024

The reduction of thermal gains in summer and heat loss in winter is ensured through the enhancement of thermal insulation and the thermal inertia of building envelopes. This study aims to exploit local materials from the Saharan region of Algeria, particularly from the Ouargla region, to construct building envelopes with high thermal resistance and inertia at minimal cost. The objective is to evaluate the current insulation methods in Algeria, which primarily use an air gap between two walls, and compare them with local insulating materials such as palm fibers, Drinn, and sheep wool, specifically for hot and arid regions. An experimental setup was designed, comprising two walls: an outer wall with a thickness of 15 cm and an inner wall with a thickness of 10 cm, with a 5 cm air gap in between, resulting in a total multilayer wall thickness of 30 cm. In this experimental study, palm fibers, Drinn, and sheep wool were inserted into the 5 cm gap between the two walls, replacing the conventional air gap. The results demonstrated an improvement in the thermal resistance of the multilayer wall with Drinn, sheep wool, and palm fibers compared to a conventional multilayer wall with an air gap. This improvement was reflected in the reduction of overall heat flux during the 10-hour experiment. The reductions in heat flux for Drinn, sheep wool, and palm fibers were 54.80%, 54.22%, and 25.99%, respectively. Sheep wool and Drinn provided nearly the same reduction in overall heat flux, but due to the higher cost of sheep wool, Drinn emerges as the best insulating material in terms of the insulation efficiency-to-cost ratio.
Leveraging GANs and depth-guided diffusion for improved 3d reconstruction and depth estimation
Authors: Souad Saadi , Brahim Nini , Abdelhak Berkia
Published: December 2024

This paper presents DepthGAN-Enhanced Diffusion, an innovative and sophisticated framework for 2D-to-3D image reconstruction, leveraging state-of-the-art artificial intelligence techniques. By combining Generative Adversarial Networks (GANs), diffusion models, and monocular depth map estimation, the proposed method addresses key challenges in 3D reconstruction, including precise depth estimation, effective handling of occluded regions, and maintaining geometric consistency across complex structures, while ensuring computational efficiency. Comprehensive experiments conducted on prominent datasets, such as ShapeNet and KITTI, highlight the superiority of our approach over existing state-of-the-art methods. DepthGAN-Enhanced Diffusion achieves exceptional performance across commonly used metrics, including Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Chamfer Distance (CD), alongside notable reductions in computational time. These findings emphasize the effectiveness of our framework in balancing both quality and efficiency. Moreover, the versatility of the proposed method makes it well-suited for a broad spectrum of real-world applications, such as autonomous driving, augmented reality (AR), and medical imaging. By enhancing accuracy and computational feasibility, DepthGAN-Enhanced Diffusion offers a transformative solution to 2D-to-3D reconstruction challenges, setting new benchmarks in artificial intelligence-driven image processing across diverse industries.
Influence of dam treated sediment on workability, strength, gas permeability and chlorides diffusion of SCC
Authors: Guerzou Tourkia , Belguesmia Khalil , Belas Nadia , Mebrouki Abdelkader , Safer Omar , Belaribi Omar , Mostefa Fouzia , Amer Adem Ait Mohamed
Published: December 2024

Fine dam sediments are natural wastes resulting from dredging operations, and their valorization is of high interest for environmental issues. This article aims to study the possibility of using the fine sediments dredged from Chorfa dam in Algeria as supplementary cementitious material (SCM). For this purpose, the sediments have been heat-treated and partially replaced cement in self-compacting concrete (SCC) formulation. The SCCs prepared with three different replacement levels of cement with sediment (10, 20 and 30%) were tested at fresh and hardened states. Furthermore, gas permeability and chlorides diffusion were carried out. The results showed that the replacement level of cement with treated sediments in SCC up to 30% was feasible. The compressive strength, gas permeability and chloride diffusion values were dependent on the replacement level of cement with treated sediments.
Membrane strain based finite elements implemented in ABAQUS for static and free vibration analysis
Authors: Messai Abderraouf , Rahmouni Salah , Fortas Lahcene , Belounar Lamine , Merzouki Tarek
Published: December 2024

This study introduces three advanced and robust rectangular finite elements based on the strain approach, designed specifically for the accurate analysis of structural behavior. These elements, denoted as R4BM, SBRIE1, and SBRIE2, have been developed with unique characteristics that make them particularly suited for structural analysis. For the first time, they have been implemented into the commercial finite element software ABAQUS through the user-defined element subroutine (UEL). This integration allows for the evaluation of these elements in both static and free vibration analyses. Each of the proposed elements features two essential external degrees of freedom at each of the four corner nodes, as well as an additional degree of freedom at the central node, ensuring a high level of flexibility and precision in capturing structural responses. The performance of these elements has been thoroughly validated by comparing their results with both analytical solutions and numerical results reported in the literature. The comparative analysis demonstrates that these finite elements exhibit a remarkable combination of high accuracy and computational efficiency. The study underscores the potential of these elements to significantly enhance the accuracy and performance of strain-based finite element analyses within commercial software environments.
Experimental and numerical study of buckling of composite honeycomb sandwich panel subjected to quasi-static indentation
Authors: Mertani Boubekeur Mohammed Bilel , Keskes Boualem , Bentouhami Abderrahmane
Published: December 2024

Light weight high performance sandwich composite structures have been used extensively in various load bearing applications. Experiments have shown that the indentation significantly reduces the load bearing capacity of sandwich composite structure. This work presents a large experimental investigation on honeycomb sandwich plates subjected to quasi-static indentation loading to study their quasi-static indentation behavior. The objective of this work was to understand and ultimately predict the initiation and progression of buckling in this type of composite. Effects of some key parameters on the overall energy absorption behavior and damage of the panels are discussed, such as core material, cell size and indenter geometry. Also, this is to explore the properties of lightweight materials for other applications as to their high-energy absorption ability. It was found that these factors have large influence on the indentation behavior and the buckling of these structures in terms of critical indentation load, indentation at failure and damage area. In meantime, ABAQUS program is used to numerically calculate the corresponding critical buckling loads in case of AHS d = 6.4 mm.
Comparative study of Safranin O adsorption onto biomass-derived activated carbon and commercial activated carbon: isotherm modeling
Authors: Zerhouni Anissa , Attouti Salima , Termoul Mourad , Benallou Mokhtar Benzekri , Bestani Benaouda , Benderdouche Noureddine
Published: December 2024

Water treatment through adsorption is widely used to remove organic and inorganic micropollutants. This study aims to evaluate the removal of Safranin O, a cationic dye, using activated carbons derived from marine algae. The performance of these bio-based activated carbons was compared to that of a commercial activated carbon. Adsorption isotherms were modeled using the Langmuir, Freundlich, and Temkin models in both their linear and nonlinear forms. The results were validated through error analyses, including the chi-square (χ²) test and the Average Percentage Error (APE). The maximum adsorption capacities observed were 384.61 mg×g-1 for activated carbon derived from brown algae, 526 mg×g-1 for green algae, and 400 mg×g-1 for the commercial activated carbon. Among the studied models, the linear form I of the Langmuir model and the nonlinear forms of all three models accurately described the adsorption of Safranin O onto the prepared and commercial activated carbons, with correlation coefficients (R²) exceeding 0.90 and low error values.
CMFSM: a framework cloud_mashup based on the concept of free search model for managing data as a service (DaaS)
Authors: Belabed Mourad , Dennai Abdeslem , Salmi Toufik , Khair Younes
Published: December 2024

Given the development of technologies in the Web environment aimed at simplifying the creation, sharing, and use of online resources, and thanks to cloud computing, numerous applications and software systems are designed to meet the complex needs of users while optimizing the use of shared resources and information. This evolution has led to the emergence of various technologies, such as “Mashup”, which allows the integration of different data sets and services on a single web page. This makes cooperation between websites and online services easier. However, this multitude of accessible data presents difficulties, such as the challenge of choosing relevant information due to the large number of online data and search criteria, as well as the lack of semantic tools that influence the quality of the information revealed to develop our Mashup. To solve these problems, we used an model based on cloud Mashup applications that use a free search model (FSM) [1]. By querying DaaS-Cloud (Data as a Service-Cloud) services with the possibility of integrating other Clouds by applying the InterCloud concept, this model, called CMFSM, allows the creation of cloud mashups by leveraging the concepts used in FSM-based search. This service enables users to access a wide range of data sources and improves the relevance of data selection based on specified parameters. And addresses the problem of information poverty in the medical field in case of a rare pathology.
Diagnosis of bearing faults using an advanced feature extraction based on WPT and EEV methods
Authors: Bousseksou Radouane , Bessous Noureddine , Mahmoud Mohamed Metwally
Published: December 2024

Detecting faults in rolling-element bearings can be achieved by monitoring and analyzing various signals such as vibration signal, acoustic noise, and stator current. Frequency spectral analysis using signal processing technique is one of many methods which has been used in fault diagnosis in this field. Other techniques as FFT, MUSIC, ESPRIT, STFT, and DWT are used to detect electrical or mechanical faults in induction motors (IMs). Motor current signature analysis using FFT tool (MCSA-FFT) is the most commonly utilized method. However, it has significant drawbacks, including resolution issues and the limitation of being unsuitable for analyzing non-stationary signals. To address these limitations, a method for analyzing stator current based on the Wavelet Packet Transform (WPT) technique is proposed for detecting this mechanical faults (rolling element bearing faults). The stator current signal is decomposed into nine levels using the Wavelet Packet Decomposition (WPD) method. Subsequently, EEV estimation is applied to the resulting coefficients to identify bearing faults. To confirm the effectiveness of the proposed technique, we examine the performance of a healthy and  faulty motor under both no-load and full-load conditions. The findings indicate that the proposed method is more effective and efficient than traditional approaches.
A systematic study of autoencoder hyperparameters for effective feature learning in image recognition tasks: insights from handwriting dataset
Authors: Soundes Mekki , Ahlam Labdaoui
Published: December 2024

This research investigates the potential of autoencoders to enhance handwritten digit recognition using the MNIST dataset. Autoencoders, with their encoding and decoding mechanisms, effectively capture essential data patterns, making them powerful tools for feature extraction and dimensionality reduction. The study evaluates various autoencoder architectures, including shallow and deep designs, by fine-tuning hyperparameters such as epochs, batch size, and learning rate to optimize model representations and improve recognition performance. Performance is measured using metrics like Mean Squared Error (MSE) and classification accuracy on reconstructed images, providing a comprehensive assessment of the autoencoder’s effectiveness. Comparative experiments reveal the influence of architectural designs and parameter settings on the model’s ability to generalize and accurately recognize digits. Results demonstrate that autoencoders not only enhance recognition accuracy but also provide valuable insights into the dataset’s structure. These findings underscore the importance of unsupervised neural networks in improving practical applications like image recognition. By optimizing architectural and parameter choices, this study contributes to advancements in digit recognition systems and highlights the broader potential of autoencoders in machine learning.
A new combined data-preprocessing and machine learning approach for emotion-based fake news detection
Authors: Mostefai Belkacem , Boutefara Tarek , Khedimallah Nada
Published: December 2024

The proliferation of social network platforms, especially post-COVID, has accelerated the spread of fake news, impacting politics, public health, and social stability. This widespread issue undermines trust, polarizes communities, and influences decision-making, highlighting the need for innovative solutions for automatic detection and mitigation. This paper introduces a new combined data-preprocessing and machine learning approach for emotion-based fake news detection. A key focus of the study is the emotional dimension of fake news, identified as a critical factor influencing its propagation on social networks. By analyzing emotional cues embedded in fake news content, the proposed method seeks to detect fake news based on its emotional characteristics. To validate this approach, two machine learning classification methods K-Nearest Neighbors (KNN) and Support Vector Machines (SVM) were tested, achieving accuracy rates of 65% and 70%, respectively. These findings demonstrate the potential of emotional analysis in enhancing fake news detection frameworks and suggest avenues for further refinement and broader application.
Heat treatment effect on the corrosion rate, microstructure and mechanical properties of X60 pipeline steel
Authors: Slimani Assia , Lemmadi Fatima Zohra , Hamdi Ines , Bentrah Hamza
Published: December 2024

In this study, experimental investigations were executed to find the heat treatment effect of two different temperatures (250 °C and 650 °C) on the corrosion rate, microstructure, and mechanical properties of X60 pipeline steel. The obtained results were investigated using diverse instrumental methodologies such as Optical Microscopy, microhardness test, and potentiodynamic polarization measurements. Different microstructure phases appeared in the heat-treated specimens such as fine-grained ferrite, polygonal ferrite, ferrite structure with small islands of pearlite, retained austenite also have been found on this steel. Microhardness test shows that there a change in the hardness of the specimens. The microhardness values increased with increasing from the 250°C and then return to decrease again in 600°C. The polarization tests results show that the corrosion rate of the metal studied during the treatment at 250 and 650 ° C has a minimum value. The best corrosion resistance was obtained from heat treatment at 250°C. The heat treatment can change the mechanical characteristics and corrosion resistance properties of X60 steel.
Calculation of the residual strength of steel-concrete composite columns under standard fire conditions
Authors: Soumia Sekkiou , Moufida Gherdaoui , Ali Mehamdia , Touam Lakhemissi
Published: December 2024

In this paper the fire behaviour of composite columns in  hollow square and circular sections infilled with concrete was studied by the  method of calculation of the EC4 wich is a summation method that uses equations to determine the temperature field and residual strength of composite hollow sections subjected to a conventional fire, and then a comparison was made between residual resistances calculated by this  method and those calculated by a formula from the literature. Calculations have shown that the fire resistance of the columns is very sensitive to the variation of the transverse dimension of the profile and the thickness of the tube. As for the comparison between the fire resistances of square profiles and those of circular sections, it is noted that whatever the area of the section, the resistance of circular profiles is greater than that of square profiles especially during the first hour of fire, and this is because of the large circumference of the square sections compared to the circular ones. And finally the index of  residual resistance calculated by Eurocode 4 (IRREC4) remains lower than that calculated by the literature formula (IRRHan) up to certain values of the section dimension and the buckling length beyond which it will be the opposite.
An efficient genetic algorithm for locating critical failure surfaces in slope stability analysis with limit equilibrium method
Authors: Mennaai Amor , Zatar Abdallah , Hamadi Djamal , Djireb Samir
Published: December 2024

The determination of the critical failure surface in geotechnical field is carried out in the process of evaluating the stability of slopes, embankments, dam, excavations, retaining walls and many others. As in many other studies, the problem of slope stability is analyze by limit equilibrium method (LEM) in homogeneous soil. These methods frequently make it possible to identify the critical circular slip surface (CFS) corresponding to the minimum factor of safety (FOS). Finding the critical slip surface (CFS) and minimum safety factor (FOS) in slope stability analysis can be performed using global optimization metaheuristic techniques. The paper presents a new modified genetic algorithm (MGA), based on Multi-Parametric Convex Crossover (MPCX), to search the critical circular for locating failure surfaces (CFS) and determining the lowest (FOS). The performance of the modified genetic algorithm proposed based on (MPCX), is explored by solving four benchmark applications from the literature. This proposed program converge rapidly to the optimal solution in function of the number of iterations, the results demonstrate that using the approach proposed (MGA) can be applied within the very well result including the analysis of the stability of the slopes, since it presents improved performances compared to the other methods such as grid search and genetic algorithm.
Analyzing gas flow characteristics in a Y-Shaped micro-channel: continuous and discrete regime modeling investigation
Authors: Abdellah Benslimane , Brahim Dennai , Rachid Khelfaoui
Published: December 2024

In the last decade, there has been a significant rise in the level of attention given to the examination of gas flow, specifically the flow of compressed gas across extended channels. This study examines the gas flow in a microchannel shaped like the letter "Y" while assuming a steady state regime. The primary objective is to investigate the impact of channel widths on the flow characteristics of several gases, including air, hydrogen, argon, and nitrogen. This study enhances the developing field of microfluidics by offering a detailed investigation of gas flow in a Y-shaped microchannel. The discoveries not only deepen our comprehension of the underlying principles that govern the dynamics of gases at a small scale, but also have practical consequences for enterprises aiming to optimise processes, boost efficiency, and progress technologies that rely on accurate control of gas flow. Moreover, the study investigates the impact of reducing size on the Knudsen number, which characterises the flow pattern, as well as the influence of temperature and channel width on the shift between various flow patterns for each of the gases being studied. Additionally, the collision dynamics of argon particles in microchannel flow are investigated using the Monte Carlo method. The increased interest in microchannel is fuelled by the prospective uses of these channels in several industries, spanning from sophisticated manufacturing to energy conversion technologies. Examining gas flow in microchannel is vital for enhancing processes in microfabrication, fuel cell technology, and other applications that need accurate management of gas transport.
Atomic solutions of some fractional partial differential equations
Authors: Hammou Asma
Published: December 2024

We offer a comprehensive example to showcase the atomic solution method for finding all possible atomic solutions to specific fractional partial differential equations, which are often difficult to solve with traditional methods like separation of variables. This approach is based on principles from tensor product theory in Banach spaces and the properties of atomic operators. By representing the solution as a tensor product of two functions, the method allows for a more efficient and structured way of solving these equations. This example highlights how the atomic solution method can overcome the limitations of conventional techniques, providing a clearer pathway to identifying solutions that may be otherwise elusive. Through this approach, we demonstrate the potential of atomic operators and tensor product theory to simplify the resolution of complex fractional partial differential equations, broadening the range of solvable problems in this field. Mathematics Subject Classification (2010). 35E99, 47B01.
Application of wavelet transform for wind energy generator diagnostic
Authors: Batoun Bachir , Merabet Houri , Chaker Abdelkader , Assia Hamza
Published: December 2024

In this paper, we propose a method for monitoring a wind energy generator using wavelet transform, aiming to enhance fault detection and localization capabilities. This method involves applying wavelet transform to analyze the stator and rotor currents, enabling the identification and precise localization of faults that may arise during operation. The wavelet transform, known for its ability to process non-stationary and transient signals, is particularly suited to capturing the dynamic behavior of electrical currents in wind energy systems. After a detailed presentation of the fundamental characteristics and advantages of the wavelet transform in fault analysis, we focus on implementing specific algorithms, namely those of Morley, Gabor, and Wigner-Ville. These algorithms are applied to classify various types of faults affecting the stator and rotor currents, providing a comprehensive diagnostic framework. The proposed approach not only contributes to early fault detection but also aids in minimizing downtime and improving the overall reliability and efficiency of wind energy generators.
Enhancing power grid observability through optimal PMU placement using the salp swarm algorithm
Authors: Souhaib Remha , Mosbah Laouamer , Khaled Miloudi , Abdelkader Mahmoudi , Azzeddine Bengharbi Abdelkader
Published: December 2024

The Phasor Measurement Unit (PMU) is a state-of-the-art device that substantially enhances the full monitoring and control of power systems. Renowned for their high precision, PMUs utilize sophisticated time synchronization techniques that enable the accurate measurement of voltages at specific buses, as well as the phase angles of currents in the lines that connect to those buses. This study proposes an innovative methodology that utilizes the Salp Swarm Algorithm (SAA) to optimize PMU placement, ensuring comprehensive system observability. The optimization approach aims to minimize the number of PMUs required, thereby reducing deployment costs while maintaining effective system monitoring. The proposed (SSA) algorithm has been validated through testing on three IEEE standard benchmark systems, specifically the 9-bus, 14-bus, and 30-bus networks. Simulation results indicate that the optimal PMU placement achieved with this approach guarantees effective observability of system states. In addition, the methodology has been applied to a real-world power network in Algeria, consisting of 114 buses, further demonstrating its robustness in ensuring full system observability.
A Y-Design formal modeling framework for RESTful APIs-Based E-Learning system development
Authors: Mostefai Belkacem , Bousbia Nabila , Boutefara Tarek , Hammia Abderrahmane , Dhelim Sahraoui , Balla Amar
Published: December 2024

A current trend in software engineering is the model-driven software engineering approach, which emphasizes the use of formal models in the design phase to streamline the development process. The Unified Modeling Language (UML) has emerged as a widely adopted open-standard modeling approach. This paper introduces a Y-Design Formal Modeling Framework tailored for the efficient design and development of RESTful web service-based e-learning systems. Rooted in the 2-Track Unified Process (2TUP), the Y-Design framework structures the design process into three stages, each strategically employing selected UML diagrams: a functional stage focusing on capturing and modeling user requirements, a technical stage addressing architectural needs and defining system components, and a design-integration stage that harmonizes both tracks into a unified system. The feasibility and effectiveness of the proposed framework are validated through the implementation of a typical e-learning system, demonstrating its potential to streamline design while ensuring robust and scalable solutions for modern distributed systems. The proposed framework emphasizes agility and coherence, making it particularly suited for e-learning projects requiring modularity and efficient reuse of common e-learning users' required services.
Real Random Number Generation by Chemical Reactions Based on Quantum Wave Equation
Authors: Gençoğlu Muharrem Tuncay , Genç Tuncay
Published: December 2024

Random Number Generators are software or hardware components that allow the production of unpredictable number sequences without any pattern or relationship between them. Various studies have been conducted with different techniques regarding RNG. In these studies, the difficulties of random number generation and the high cost negatively affect the efficiency of the developed generators. Many different methods have been used in real random number generation, and even quantum random number generators have been developed to make predictability difficult. Quantum Random Number Generators; are a tepe of generator based on the laws of Quantum physics instead of classical physics. In photonic-based RNG, random numbers are generated after various software and hardware operations by utilizing the uncertainty of photons. This study, it is aimed to develop a true random number generator using chemical reactions that have not been studied before. Data was produced by using sensors and other hardware elements together, the values produced were taken as seed values and assigned as input to the algorithm used in generating random numbers, and true random numbers were produced and these numbers were tested in detail with known test methods.
Comparative Analysis of Policy Effect Evaluation of New-energy Vehicle Industry in China and the U.S.
Authors: Xue Mengqi , Yuan Zefeng
Published: December 2024

Against fluctuations in the global automotive market, the electric vehicle (EV) industry has demonstrated a positive development trend overall. China has become a leader in battery production and related infrastructure construction, while the United States, though ranking third, also holds an important position. This paper analyzes the effects of government-led policies and market-driven policies on the electric vehicle policies of China and the United States. It explains how the industries and policies of the two countries interact. By analyzing the current state of the industries in both countries and their different policy preferences in terms of fiscal policy, infrastructure allocation, and other dimensions, the following conclusions can be drawn. Firstly, compared to the incoherent central policies and decentralized local policies lacking central authority in the U.S. electric vehicle industry, China's top-down long-term policies lead to a more consistent and efficient development of its electric vehicle industry. This article concludes that China's strong authoritative and consistent policies in the electric vehicle industry play an important role in maintaining its leading position in the global electric vehicle industry.
Policy Responses to Aging and Chronic Diseases in China: Control and Insights
Authors: Ren Shiyi
Published: December 2024

China is one of the countries with the most rapid changes in population structure worldwide. Chronic diseases among China's aging population have emerged as a significant public health challenge, given the massive population and high aging rate. The incidence of chronic diseases among the elderly is increasing and often involves multiple coexisting diseases, thereby contributing to an increased social and economic burden. This paper highlights the health dilemma faced by China's aging population and provides an overview of their current state regarding chronic diseases. Three key points for the formulation of chronic disease management and prevention policies in China's aging society are proposed, while also drawing on specific measures from Japan to provide insights for developing effective health policies in China's future aging society.
A comparative study of urban and rural aging systems in China
Authors: Jin Yige
Published: December 2024

The paper contrasts the urban elderly care system and the rural geriatric care system in China and evaluates the differences concerning the quality of life of the elderly. The study shows that elderly care facilities in urban areas are more developed. There is greater involvement from the government and a variety of community care services whereas in the rural facilities’ elderly population relies predominantly on family care and insufficient skilled nursing and medical facilities. Employed both qualitative and quantitative methods, this paper explains disparities in resource allocation, service provision, and policy implementation between urban and rural areas of China and provides recommendations to enhance elder care in the rural regions of China. The research also recognizes other countries experience and it utilizes resource dependency and social equity theory to explain and enhance equality-based policies in the provision of elder care.
The Cultivation of Environmental Awareness of College Students: A Public Policy Perspective
Authors: Wu Zhonghan
Published: December 2024

As environmental problems around the world become more and more obvious and people's awareness is improving, people are gradually becoming more and more aware of environmental protection. The role of education in environmental awareness cannot be ignored. Environmental protection education is one of the key research topics today. Therefore, the research topic of this paper is the cultivation of environmental awareness of college students: a public policy perspective. This study found that China already has many policies on environmental education and these policies have good prospects and far-reaching benefits for the future. College students should actively learn about environmental protection and spread relevant knowledge. At the same time, college students should also take the initiative to abide by relevant regulations on campus and participate in relevant activities. This study has clarified the status of environmental awareness cultivation in Chinese universities to a certain extent and provides a reference for future related research.
Take India as an example to explore the role of media in policy communication
Authors: Zou Yijun
Published: December 2024

This paper examines the role of media in the dissemination and implementation of public policy in India. Through an analysis of various media platforms, including television, newspapers, and social media, the study explores how the media influences public perception and understanding of government policies. The paper highlights the dual role media plays in both promoting policies and holding the government accountable by fostering public debate and scrutiny. Key case studies, such as the Digital India initiative, demonstrate how effective media engagement can lead to increased policy awareness and citizen participation. However, the study also identifies significant challenges, including media bias, the spread of misinformation, and unequal access to media in rural areas. These issues can hinder the successful communication of policies and undermine trust in government efforts. The paper concludes by stressing the need for media reform, greater media literacy, and improved infrastructure to ensure that public policy dissemination reaches all sectors of society and remains accurate and unbiased. This research underscores the critical role media plays in shaping democratic governance and public policy outcomes in India.
Geographical Indications in Vietnam: Protecting Cultural Heritage and Promoting Economic Growth
Authors: Thanh Van Doan Vu
Published: December 2024

For millennia, Vietnam's identity has been deeply rooted in its agricultural prowess, which it considers the backbone of its economic framework. The country's unique geographical positioning, coupled with its distinct weather patterns, has blessed it with a cornucopia of agricultural produce. These products are not only varied in kind but also renowned for their rich flavors and exquisite taste. Recognizing the importance of these products, the Vietnamese government has turned to Geographical Indications (GIs), a facet of Intellectual Property (IP) law, as a strategic tool to preserve the nation's cultural heritage and stimulate economic development. GIs are a form of IP that identifies a product as originating from a specific region, where its qualities are due to that region's unique geographical features. This article delves into the case of Phu Quoc fish sauce, a quintessential example of how IP law, through the use of GIs, has safeguarded and promoted Vietnamese agricultural products. Phu Quoc fish sauce, with its distinctive taste and production process deeply tied to the island's environment, has gained international recognition and protection. The GI status not only protects the product from imitation but also adds value, ensuring that the authentic product's reputation and the region's cultural identity are preserved. This legal framework has become a catalyst for economic growth, as it encourages sustainable farming practices and supports local communities, while also ensuring that the unique flavors of Vietnam's agriculture reach global markets with authenticity and pride.
Application of Communication Effectiveness Theory to Fitness Bloggers' Social Media Communication - A Study of Audience Changes in Health Perceptions and Behaviour
Authors: Liu Likai
Published: December 2024

With the popularity of social media, fitness bloggers have become important figures in the dissemination of health information. Based on communication effect theory, this paper investigates the influence of fitness bloggers on audience health perception and behaviour on social media. By analyzing the origin and development of communication effects theory, its main schools and key concepts, and its evolution in the new media environment, the study explores the interactivity and fragmentation of social media communication, the role and influence of fitness bloggers, and the match between platforms and fitness content. It is found that fitness bloggers effectively enhance their audience's health perceptions, stimulate positive health attitudes, and motivate changes in health behaviours through personalized and interactive content design. In particular, the bloggers' long-term interactions and incentives had a significant impact on the sustained change of audience behaviour. In addition, the interactive model of communication effects and audience behaviour change reveals the dynamic relationship among perception, attitude and behaviour. Although this study provides valuable insights into the communication effects of fitness bloggers, it still suffers from a limited sample scope and insufficient data support. Future research should expand the sample scope and incorporate more interdisciplinary theories to further validate and optimize fitness bloggers' information dissemination strategies.
Revitalizing Lakers’ Home Game Attendance: Challenges, Strategies, and Future Directions
Authors: Zhong Chiyuen
Published: December 2024

From 2020 to 2024, attendance at the Lakers' home arena diminished as a result of the epidemic. The objective of this study was to examine the causes contributing to this situation and propose feasible remedies to resolve this issue for the Lakers. This study employs qualitative analysis and case study methodologies to identify attendance difficulties, examine possible constraints encountered by the Lakers, and determine the reasons for the reduction. The research will then provide solutions to each specific problem. The investigation revealed that a potential decrease in the impact of the all-star player could be a contributing factor, which could potentially be addressed by acquiring another exceptional player. Secondly, insufficient imaginative advertising may result in diminished attendance; nevertheless, creating a mascot might serve as a feasible remedy. Ultimately, evolving consumer behaviors adversely impact the Lakers' attendance; hence, the Lakers should prioritize stadium advertising. This research aims to offer advice to the Lakers' management or marketer regarding the decline in attendance at their home arena.
Unraveling the Diagnostic Challenge: A Case Report on Disruptive Mood Dysregulation Disorder
Authors: Godiawala Shreya , Parikh Minakshi , Kumar Rajesh
Published: December 2024

The DSM-5 diagnostic criteria for disruptive mood dysregulation disorder (DMDD) require outbursts that are grossly out of proportion to the situation. These temper outbursts present with verbal rages or physical aggression towards people or property and are inappropriate for the child’s developmental level. Temper outbursts occur, on average, three or more times per week, with variations in mood between outbursts. Symptoms must be exhibited before age 10 years, be present for at least 12 months, and be present within at least two settings.