bluuebunny/crossref_metadata_2025 huggingface dataset:
Precise and reliable monitoring of electrical grid frequency using PZEM-004T and ADE7753 modules with Arduino
Authors: Kaci Meziane , Salem Merabti , Layate Zakaria , Said Hakim Ait , Amrane Sofiane , Terki Lydia
Published: December 2024

High-quality and precise monitoring of electrical grid frequency is an indispensable and indispensable measure for maintaining the stability and quality of modern energy systems, especially in the context of renewables and smart gird applications. This article will examine the functions of two very high-tech measurement modules PZEM-004T and ADE7753, working with Arduino Uno WiFi Rev2, which will perform real-time frequency monitoring. A detailed comparative analysis has been done, which shows the modules' strengths and limitations in terms of accuracy, integration complexity, cost-effectiveness, and application scope. The PZEM-004T module is the most straightforward, cheap, and simple choice for residential and IoT technologies-based energy management setups, thus giving a sufficient degree of general monitoring tasks. On the other hand, the ADE7753 demonstrates the superior precision that along with advanced functions such as power quality analysis and overload detection guarantees its suitability for the industrial sector that requires strict energy monitoring. The modules have the Arduino boards as the main microcontrollers through which data can be bounced, stored, and displayed on LCD, OLED, or web-based platforms providing remote access via IoT technologies. Through the results, these modules are shown to be adaptable to different energy management needs, which can vary from cost-saving solutions to home automation and high precision in industrial monitoring systems. The plant's goal is to increase the degree of their interconnectivity so that they may be used in smart microgrids where scalability, real-time analytics, and energy optimation will be the drivers.
Existence of solution for a tripled system of fractional hybrid differential equations with laplacie involving Caputo derivatives
Authors: Benallou Mohamed , Beddani Hamid , Beddani Moustafa
Published: December 2024

In this paper, we study the existence of solutions for a tripled system of Fractional hybrid differential equations with nonlocal integro multi point boundary conditions by using the  Laplacian operator of degree p and the  Caputo derivatives, we know that the differential equations with the Laplacian operator appeared for the first  time when Leibenson was attempting to derive an accurate formula to model turbulent flow in the porous medium, in this work we study the case of the Fractional hybrid differential equations who  are the quadratic perturbations of nonlinear differential equations. Dhage and Lakshmikantham [12] discussed the hybrid differential equation They established the existence, uniqueness results, and some fundamental differential inequalities for hybrid differential equations initiating the study of the theory of such systems and proved to utilize the theory of inequalities, its existence of extremal solutions, and comparison results. Hilal and Kajouni [19] have studied boundary fractional hybrid differential equations involving Caputo differential operators, so In this article, we are interested in the existence result of the solution of hybrid nonlinear differential equations. obtained by the hybrid fixed point theorem for a sum of three operators due to Dhage. An illustrative example is presented at the end to show the applicability of the results. To the best of our knowledge, this is the first time where such problem is considered.
The use of carbone fibre composite for strengthening reinforced concrete beams
Authors: Laichaoui Ahmed , Abdessemed Mouloud , Bali Abderrahim , Kenai Said
Published: December 2024

The study of different reinforced concrete structure pathologies helps to understand the main causes of materials as well as structures damage which are mainly due to bad detailing, poor design, and a lack of durability and to the aggressive external actions. Algeria is a country exposed to natural disasters. Thus, damaged buildings need strengthen and repair involving adequate methods and new types of materials. Repairing and strengthening techniques based on carbon fibre reinforced polymers (CFRP) are the new materials characterized by their light weight, high stiffness, ease of placing, efficiency, high tensile strength, reasonable cost and very appreciable overall durability. Bearing in mind the last earthquake (March 18, 2021) which hit Bejaia (Algeria) and caused a lot of damages to buildings and bridges, an important program of repairing has been launched. A study has been carried out in order to examine the effect of the CFRP strengthening of reinforced concrete beams by gluing carbon materials subjected to bending. On the other hand, it is aimed to contribute to develop these techniques based on CFRP for a wide use. These materials could widely be used mainly for seismic retrofit of concrete structures since Algeria as well the whole North Africa is a very active seismic region where many important earthquakes have been recorded. For this purpose, an extensive experimental program has been elaborated and conducted in order to determine the most efficient mode of strengthening of these bearing reinforced concrete structural elements and the effect of these CRRP techniques on the properties and the behaviour of the constitutive materials of these RC beams. The results obtained showed an increase in the bearing capacity together with a reduction in steel and concrete deformations and deflections.
Numerical study of the impact of balcony openings in the vernacular architecture of the Aurès on airflow and thermal comfort
Authors: Redha Attoui , Meriem Abdeldjouad , Nourredine Belghar , Rebai Billel
Published: December 2024

This study examines the airflow characteristics of balcony openings in the traditional architecture of the Aurès region, focusing on their role in promoting natural ventilation and ensuring thermal comfort. These balconies, located in Ghoufi, are part of troglodytic homes designed to withstand the harsh arid climate. By utilizing numerical simulations and architectural analysis, the research evaluates the effects of balcony size, shape, and orientation on airflow dynamics and thermal regulation. Results highlight the effectiveness of medium-sized openings in reducing undesirable thermal flows while enhancing natural ventilation, which can reduce energy demand by 15-20%. Additionally, the findings demonstrate the potential of vernacular architectural principles to inspire sustainable design solutions for modern constructions, particularly in arid regions. This work underscores the need for preserving and leveraging traditional design strategies to address contemporary challenges in energy efficiency and ecological construction.
Effect of salt stress on germination of five quinoa varieties (Chenopodium quinoa willd)
Authors: Hichem Aissaoui , Fatima Hiouani , Djamila Madani , Samira Khamkhoum , Khadidja Nouichi
Published: December 2024

This study investigates the impact of salt stress on the germination and early development of five quinoa (Chenopodium quinoa Willd) varieties—GIZA 02, GIZA 01, Q27, Q29, and SANTA MARIA. The objective was to evaluate their tolerance to increasing concentrations of sodium chloride (NaCl), ranging from 0 to 300 mM, in a controlled laboratory setting. By analyzing various germination-related parameters, including germination rate, germination speed, germination kinetics, daily average germination, root and epicotyl lengths, reversibility of salt effects, and reserve mobilization, this research aimed to uncover genetic variability in salinity tolerance among the selected varieties. The findings demonstrate significant differences in the ability of these varieties to withstand salinity. GIZA 02 emerged as the most resilient, consistently maintaining higher germination rates and superior performance across most measured parameters, even under the harshest saline conditions. In contrast, Q29 exhibited the lowest tolerance, with marked reductions in germination and growth metrics. The intermediate performance of GIZA 01, Q27, and SANTA MARIA suggests varying degrees of adaptability to saline environments. This study underscores the potential of GIZA 02 as a highly salt-tolerant quinoa variety, highlighting its suitability for cultivation in saline-prone areas. Conversely, the susceptibility of Q29 emphasizes the need for targeted strategies to improve its tolerance. These findings contribute to a deeper understanding of quinoa's physiological responses to salinity, offering valuable insights for breeding programs aimed at enhancing crop resilience in the face of global soil salinization challenges.
Simplification of probability density function using trapezoidal method in impulsive noise
Authors: Mostari Latifa , Goupil Alban , Taleb-Ahmed Abdelmalik
Published: December 2024

In environments characterized by impulsive noise, the probability density function (pdf) of noise is inaccessible in closed form and can only be obtained through complex numerical computations. This paper introduces a simplified pdf using the trapezoidal method tailored for such noise. To enhance the reliability of these systems, error correction codes such as Low-Density Parity-Check (LDPC) codes are employed. Depending on the decoding algorithm used, these codes utilize the LLR function or the a posteriori probability (APP) function at their input, both of which rely on the pdf of the noise. In our simulations, we demonstrate that LDPC codes using the simplified pdf for LLR calculations with fixed α and γ, specifically with BPSK (Binary Phase Shift Keying) and ASK-4 modulations, can achieve performance in impulsive noise environments comparable to that obtained using the exact pdf.
Unsteady three-dimensional numerical study of mass transfer in tubular PEM fuel cell
Authors: Tamerabet Monsaf , Bensaddek Ali , Tamerabet Yacine , Baira Faycal , Amaroche Zineddine , Khaled Inouri
Published: December 2024

This study investigates the influence of introducing an obstacle within the flow channel of a tubular PEM fuel cell on mass transfer phenomena. A three-dimensional, isothermal, and single-phase model was utilized to capture the complex interactions within the system. The governing equations were discretized using the finite volume method in cylindrical coordinates, employing an implicit time scheme and the power-law approach for spatial discretization to ensure numerical accuracy. To address the computational complexity, the ADI method was applied to simplify the resulting system of algebraic equations, facilitating efficient numerical resolution. A dedicated Fortran program was developed to simulate and analyze the detailed spatial distributions of reactants and water vapor within the fuel cell. The results reveal that the inclusion of obstacles in the flow channels significantly enhances the mass transfer process by improving reactant transport and distribution. This improvement points to a promising strategy for optimizing the performance and efficiency of tubular PEM fuel cells.
Parametric study of an antenna detecting breast cancer
Authors: Bouchouareb Rachida , Amar Koutar Hadj , Berhab Souad
Published: December 2024

Cancer diagnosis often involves a combination of medical tests such as laboratory tests, physical examinations, laboratory tests and medical images such as x-rays, ultrasounds, CT scans and Magnetic resonance imaging (MRIs), radiographic mammography, as well as biopsies to examine suspicious tissue samples [Shah Hussain et all 2022]. However, we see other disadvantages to these methods, such as in radiographic mammography where the high level of ionizing radiation involved in patients is harmful, which can also cause cancer of healthy tissues. In addition, mammography is very painful because of breast compression. If an ultrasound system is used, it is not easy to detect deep or solid cancerous tissue. Although the MRI system provides very high-resolution images of soft tissues, especially for small tumors, these diagnostic procedures are expensive. These limitations stimulate the need for other approaches that can cost-effectively overcome them. Among these methods, we propose the patch antenna, which seems to be the best alternative [Diana L Miglioretti et all 2016].In this paper, the parameters, that we studied, using the High-Frequency Structure Simulator (HFSS) software, are represented in the distance from the breast, the size, the position, and the number of tumors
Wind turbine DFIG stator/rotor open phase diagnosis using FFT and 3-D plot CWT
Authors: Melloul Ahmed , Harbouche Youcef
Published: December 2024

In wind energy systems, doubly-fed induction generators (DFIGs) are widely used because they can produce electricity efficiently and operate over a wide range of wind speeds. However, like all electromechanical systems, DFIGs are prone to failures, one of which is open phase failure. The main objective of this paper is to present new results in the DFIG diagnostic approach for identifying stator and rotor open-phase failures. The approach is based on steady-state stator current analysis, using Fast Fourier Transform (FFT) and wavelets transforms (Continuous Wavelet Transform (CWT) and Discrete Wavelet Transform (DWT)) analysis with 2-D and 3-D approaches respectively.  The effectiveness of the wavelet transform is confirmed by exposing simulation results, which demonstrate its ability to effectively analyze signals across various scales and resolutions. These results highlight how the wavelet transform can overcome traditional limitations associated with other signal processing techniques, such as the inability to provide localized information in both time and frequency domains. This capability is particularly evident in the 3-D time-frequency plot, where the wavelet transform offers a detailed and intuitive representation of the current signal. By capturing transient features and variations in the signal, the wavelet transform allows for a more comprehensive understanding of its underlying characteristics. Consequently, this method proves invaluable in applications such as audio processing, image analysis, and biomedical signal interpretation, where precise localization of features is crucial for accurate analysis and interpretation.
Social relationships via social media and their impact on the nature of family relationships: (a field study on a sample of families in Laghouat city)
Authors: Lahbib Sidahmed Ben , Touhami Mohamed , Ali Bouhkalkhal , Alia Ismail Ben
Published: December 2024

In recent years, the rapid proliferation of social media platforms has significantly altered the dynamics of human interactions, reshaping traditional modes of communication and influencing social structures. Such changes are particularly evident within family relationships, as virtual interactions are increasingly replacing direct communication. This study aims to understand the impact of social relationships through social media on the nature of family relationships. It involves a field study on a sample of families in Laghouat City, where a questionnaire was used to gather data and information from the sample participants. The descriptive method was employed to observe and interpret the phenomenon. The study is primarily guided by the question: How do social media sites affect family relationships? The study arrived at several significant findings: * building social relationships on social media platforms affects the privacy of relationships within the family; * virtual social relationships play a role in forming new styles of family interaction.
Kernel estimation of the copula function under twice censoring
Authors: Boukeloua Mohamed , Toumi Samia , Idiou Nesrine , Fatah Benatia
Published: December 2024

We study the kernel estimation of the copula function of two twice censored random variables. Firstly, we introduce two kernel estimators of the joint distribution function of the two variables of interest. Then, we use these estimators to propose two smoothed estimators of the copula function. We also prove the weak convergence of the proposed estimators to some tight centered Gaussian processes. To prove this convergence, we use the weak convergence of the estimator of the bivariate distribution function under twice censoring. This latter result has been established in a previous paper and it was based on a representation of the product limit estimator of the distribution function as a sum of centered, independent and identically distributed variables. This representation allowed to prove the requested weak convergence. Finally, we illustrate the performances of our estimators through a simulation study. The results of this study show that our estimators have a good quality of estimation.
Performance of Silicon Carbide (SiC) ceramic based total hip arthroplasty, numerical resolution of tensile stresses
Authors: Ridha Harroug Mohammed , Hacene Ameddah , Hammoudi Mazouz
Published: December 2024

This study proposes a novel Ti/SiC metal matrix composite as a potential replacement for traditional metal-on-metal total hip arthroplasty. The primary objective is to address the significant issue of wear, metal debris, and degradation associated with metal-on-metal friction couples. To optimize the composite's mechanical properties, a micromechanical modeling approach was employed. Representative volume elements (RVEs) with various configurations (square, diamond, four fibers, and random) were analyzed to identify the most stress-resistant model. Subsequent finite element analysis was conducted to investigate the influence of different SiC volume fractions (40%, 50%, and 60%) on the stress distribution within the composite. The results indicate that the four-fiber model with a 40% SiC volume fraction exhibits the lowest von Mises stress (8.60 MPa). This finding suggests that this configuration offers the best compromise between mechanical strength and potential for improved biocompatibility, making it a promising candidate for biomechanical joint prosthesis applications.
Environmental feasibility study and its role in achieving sustainable development for construction projects: a study of a sample of relevant authorities in Adrar province
Authors: Abdelkader Yahyaoui , Gasmi Laid , Abderrahmane Brouki , Abdelghani Mouloudi , Kerroumi Fatma Zohra , Ghentioui Yassine , Mohamed Mazouzi
Published: December 2024

This study aims to explore the role of environmental feasibility studies for construction projects in supporting sustainable development. The research first sheds light on the theoretical aspects, presenting the concepts of sustainable development and environmental feasibility studies, along with an overview of construction projects. It then examines the reality of feasibility study application by relevant authorities when assessing construction projects and their impact on supporting sustainable development in the Adrar region. Based on the analysis of 68 questionnaires using SPSS software, the findings reveal a strong positive correlation between the application of environmental feasibility studies for construction projects and sustainable development, with a statistically significant effect estimated at 76%. The study emphasizes the need for training programs for feasibility study practitioners to acquire skills in utilizing various methodologies, particularly quantitative approaches that allow for modeling economic, social, and environmental objectives. Furthermore, it recommends the integration of digitalization and artificial intelligence technologies in feasibility study processes to uncover diverse developmental opportunities in construction projects.
Analysis of the diabetes dataset using a SMOTE machine learning approach
Authors: Abdelaoui Moustapha
Published: December 2024

Diabetes Mellitus affects huge number of people worldwide. Early identification is essential, if we were to limit this huge healthcare problem. The imbalance in class among datasets is a serious concern for machine learning solutions, particularly in generating biased predictions and poor performance for minority classes. The study investigates the effect of SMOTE on performance across multiple machine learning models on diabetes dataset. Before SMOTE, it was found that although the models score satisfactory overall accuracy , yet their average recall and AUC rates were low for the cases with a limited number of samples in the training datasets. In contrast, after applying SMOTE, the changes in recall, precision and the area under the curve noticeably improved, and most of the models met their high-performance classification criteria. There were substantial improvements, in particular, in ensemble and neural networks models. These experiments demonstrate that the synthetic minority over-sampling is efficient in balancing the datasets, thereby giving model robustness and equitable class performance. This study emphasizes the need for pre-processing techniques such as SMOTE for addressing imbalanced data problems in real-life situations.
Numerical study of the effect of using twisted tape and a nanofluid on the thermal performance of a cylindrical-parabolic collector
Authors: Bakhti Fatima Zohra , Benkherbache Souad
Published: December 2024

Cylindro-Parabolic Collector (CPC) is a solar energy technology known for its established role in concentrated solar power systems. Ongoing research aims to improve its thermal efficiency by exploring modifications in the geometry of the absorber tube and using innovative heat transfer fluids. The main objective of this work is to evaluate the combined effects of modifying the absorber tube geometry and using advanced heat transfer fluids on the thermal performance of CPCs. The absorber tube design incorporates twisted tape inserts, which act as turbulators to enhance heat transfer. The heat transfer fluids used include Syltherm 800, a synthetic heat transfer fluid, and Syltherm 800+Cu, a nanofluid that adds copper nanoparticles (φ=1-4% )improved thermal properties. The performance of a collector with a twisted tape turbulator ( CTT) is compared with that of a plain collector tube (PC)  by calculating the Nusselt number (Nu)  and outlet temperature. The findings results indicate a significant enhancement in thermo-hydraulic performance with the twisted tape turbulator and Syltherm 800+Cu nanofluid combination. The twisted tape increases turbulence, improving heat transfer, while the nanofluid enhances the thermal conductivity of the fluid.
Phenolic profiling and antioxidant activity assessment of selected extracts from the leaves of the Algerian endemic plant Anthemis secundiramea (Asteraceae)
Authors: Karima Mellouk , Djawhara Chohra , Azzeddine Charef , Romaissa Amamra , Loubna Ferchichi , Yassira Boutaleb
Published: December 2024

Anthemis secundiramea is an endemic species of the Asteraceae family, native to northeastern Algeria. Despite its unique presence in this region, a comprehensive phytochemical study focusing on its phenolic content has not yet been conducted. In this work, we obtained four leaf extracts of this species using ultrasonic extraction with different solvents.To quantify the phenolic compounds present in the aerial parts (leaves) of Anthemis secundiramea, we conducted several analyses to determine their phenolic composition and antioxidant activity. Two qualitative and quantitative colorimetric methods, employing specific reagents, were used. The results confirmed that this plant is indeed rich in phenolic compounds. Antioxidant activities were evaluated using two different assays: the free radical scavenging test (DPPH) and the ferric reducing antioxidant power test (FRAP).Additionally, the phenolic profiles of the extracts were determined by high-performance liquid chromatography coupled with a diode-array detector (HPLC/DAD). Among the various extracts studied, the methanol/water extract exhibited the highest antioxidant capacity (IC50: 1.42 ± 0.01) and contained the highest levels of total phenols (109.159 ± 12.213 mg GAE/g) and total flavonoids (95.44 ± 3.93 mg QE/g). The HPLC/DAD analysis also revealed that the leaves of Anthemis secundiramea are particularly rich in catechin, cinnamic acid, and coumaric acid.This study highlights the antioxidant potential of Anthemis secundiramea, emphasizing its richness in bioactive compounds. Further exploration is needed to fully understand the role of these bioactive compounds in herbal drug development, potentially paving the way for new natural antioxidant sources.
Enhancing anionic dye removal from aqueous solutions using kaolin-based membranes coated with sol-gel salt chloride film
Authors: Aissat Miloud , Bidaoui Mourad , Chellali Rachid , Belhocine Mohamed , Chaker Yassine
Published: December 2024

In this research, a clay product called Kaolin KT2 from Tamazert was utilized to create porous ceramic membrane supports for treating polluted water. The membrane supports underwent various investigations. They were made using the casting method in plaster molds and then enhanced with a thin functional layer through the sol-gel method to reduce the pore size to around 0.2 μm. The gel synthesis method was inspired by the Pechini method, which involves replacing expensive polymer precursors with more cost-effective metal salts. The ceramic membranes were tested for removing Indigo Carmine Anionic Dye (ICAD) under a filtration pressure of 3 bar for a three-hour cycle. The results showed that the membrane exhibited a high rejection rate of 90% for the anionic dye after the deposition of a thin film. The ceramic membrane was characterized using various techniques including ATD-ATG, XRD, XRF, FTIR, AAN, and SEM imaging. These characterization methods provided detailed insights into the microstructure, chemical composition, and demonstrated excellent mechanical strength and chemical stability, thus rendering it suitable for industrial use.
Effect study of the probability of error on the frozen bit positions in polar codes
Authors: Souillah Hadjer , Abderrahmane Lahcen Hadj , Imine Belkacem , Ali-Pacha Adda
Published: December 2024

Polar codes are a channel coding technique designed to achieve the symmetric capacity of a binary input discrete memoryless channel (BI-DMC). Constructing polar codes involves selecting the most reliable channels from a set of polar sub-channels, which are linear combinations of the original channel outputs . This paper examines the relationship between error probability and the positions of frozen bits in polar codes, considering different channel models, including the Binary Erasure Channel (BEC), Binary Symmetric Channel (BSC), and Additive White Gaussian Noise (AWGN) channel, while maintaining a constant code length. The study aims to understand how variations in error probability affect the reliability of sub-channels. These variations, in turn, influence the position of the frozen bits, which play a crucial role in the encoding process. By exploring these factors, the research seeks to optimize polar codes for different communication scenarios, enhancing performance by gaining a deeper understanding of how error probabilities and frozen bit positions interact across various channel conditions.
Investigations of Secondary Metabolites and antioxidant activity of methanolic, ethanolic and acetonic extracts of lichen (Xantoria parietina L.) from Northestern Algeria
Authors: Souria Bendeddouche Mansouria , Lahouaria Labga , Ouafia Liamani , Benouis Khedidja , Yahia Khelef , Abdelhamid El Haci Imad , Meriem Belarbi , Ibtissem Benghalem
Published: December 2024

This study aims to evaluate Xantoria parietina (L.), a plant indigenous to north-western Algeria. We analyzed ethanolic (EE), methanolic (ME) and acetonic (EE) extracts obtained from the thalli and apothecia of this plant. Our main focus was on secondary metabolites, specifically polyphenols, flavonoids, condensed and hydrolysable tannins. We additionally assessed their antioxidant characteristics. The Folin-Ciocalteu method was employed to quantify the polyphenol content, while the DPPH (2,2-diphenyl-1-picrylhydrazyl) reduction and FRAP (ferric ion-reducing power) tests were utilized to assess the free radical scavenging activity. The findings show that the methanolic and ethanolic extracts exhibited the highest concentration of polyphenols with 27.839 mg EAG/g (EE) and 27.55 mg EAG/g (ME). The results also indicated significant antioxidant activities in the DPPH compared to ascorbic acid and FRAP assay.In addition, the acetone extract of X. parietina exhibited a significant tannin content of 420.33 mg EC/g of condensed tannins, whereas the ethanolic extract displayed a lower content of 0.187 mg EC/g. This underscores the substantial presence of tannins in the plant. Analyses by high-performance liquid chromatography (HPLC) confirmed the presence of quercetin, gallic acid, chlorogenic acid, catechin narenginin. The findings suggest that X. parietina is a notable source of polyphenols, which are compounds recognized for their antioxidant characteristics.
Integration and interoperability of connected electrical sensors in the Internet Of Things (IoT) for smart healthcare
Authors: Khalef Rostom , Moulahcene Fateh , Tourqui Djamel Eddine , Merazga Ammar
Published: December 2024

This paper investigates how utilizing the Internet of Things (IoT) for real-time monitoring and predictive analytics in smart healthcare is revolutionizing patient care. The IoT allows for the constant tracking of a patient's symptoms, vital signs, and general health via linked devices, including electrical sensors, wearables, and smart medical equipment. This real-time data flow enables proactive therapies and early detection of potential health concerns, providing clinicians with a continuous, accurate picture of a patient's state. Additionally, combining IoT data with predictive analytics enhances healthcare decision-making. This allows for the detection of patterns and the forecasting of patient outcomes using both historical and real-time data. In order to decrease the chance of problems or hospital readmissions, predictive models can notify healthcare practitioners of changes in a patient's health trajectory. This allows for prompt modifications to treatment plans. As the Internet of Things (IoT) and predictive analytics develop further, smart healthcare solutions have the potential to optimize the allocation of resources while simultaneously reducing healthcare costs and improving patient outcomes and the quality of care. Patients and providers alike will benefit from this shift because it will pave the way for a healthcare system that is more responsive, data-driven, and connected. In this, we focus on the design and implementation of an intelligent healthcare room based on the Internet of Things (IoT). The system primarily consists of microcontrollers (ESP32 board and Arduino board) and sensors. Additionally, the "Blynk" platform facilitated this interaction. This innovation promises to improve critical care management by automating and improving the medication administration process based on individual patients' needs.
Static creep behavior of asphalt concrete modified by rubber crumb
Authors: Hadidane Hocine , Djebbari Zina
Published: December 2024

Asphalt concrete (AC), is a sensitive material compared to other configurations used in civil engineering. Therefore scientists and engineers are constantly trying to improve the performance of asphalt pavements. Modification of the asphalt binder is one approach taken to improve pavement performance. Nowadays, there are different materials that have been employed to reinforce asphalt concrete. Furthermore, fibers and rubber waste are two important examples used for this purpose. The objective of this study to evaluate the static creep behaviour of bituminous concrete modified by rubber crumb inserted in the aggregate of mixtures. The experimental design for this study included the use of different percentages of rubber crumb (0%, 1,5%, 3%, 4,5% and 6%), the mixtures performances already evaluated by the tests (Marshall and Duriez). The tests results indicated that the addition of rubber crumb was show advantages compared to the conventional mixture. However, the excess quantity of this last reduced the resistance of modified mixtures.
Exploring the historical development and architectural changes of the El Mechouar Monument in Tlemcen using 3D visualizations
Authors: Zahira Seddiki
Published: December 2024

The study investigates the historical evolution and architectural transformations of El Mechouar Monument in Tlemcen, a site of immense cultural significance that has undergone numerous changes over centuries. These transformations reflect the dynamic interplay of cultural, political, and structural influences that have shaped its architecture. Using a multidisciplinary approach combining historical analysis, architectural modeling, and advanced simulation techniques, the research aims to reconstruct the monument's development with precision. By examining historical documents, detailed architectural plans, and archaeological evidence, the project identifies key phases of structural and functional adaptation. The integration of 3D visual narratives provides an innovative perspective on the spatial organization and architectural intricacies of the site, enabling a deeper understanding of its historical context. This methodology not only enhances historical interpretation but also contributes significantly to heritage preservation by creating an accessible digital archive. Ultimately, the study addresses critical gaps in documenting El Mechouar’s legacy and supports efforts to safeguard its historical value.
Local linear estimation of a conditional hazard function under random censorship: strong consistency with convergence rates
Authors: Gagui Abdelmalek
Published: December 2024

This paper explores the estimation of a conditional hazard function for a scalar response variable conditioned on a random predictor within a semi-metric space. Utilizing a local linear estimator, we address the challenges posed by censored and -mixing dependent data. The proposed method combines nonparametric functional data analysis techniques to estimate the conditional density and cumulative distribution functions. We establish almost sure convergence rates under specific regularity conditions, contributing to the theoretical understanding of hazard function estimation in complex data structures. Our methodology is validated through extensive simulations, where functional data are generated and subjected to censorship. The performance of the local linear estimator is benchmarked against the k-nearest neighbors approach using Mean Squared Error (MSE) as the evaluation metric. Results demonstrate that the local linear estimator consistently outperforms traditional methods, providing more accurate and reliable estimates even under complex dependencies. The findings underscore the potential of local linear estimation in addressing the intricate challenges of censored and dependent functional data. This study advances the scope of survival analysis by offering a robust and efficient tool for hazard function estimation in high-dimensional, dependent data contexts.
Practical inverter design and control: implementation strategies and performance analysis
Authors: Mansour Zegrar , Houari Zerhouni M’hamed , Zohra Zerhouni Fatima , Nouh Zegrar
Published: December 2024

Inverters are devices that convert electrical energy from DC to AC. They come in all shapes and sizes, ranging from low-power functions such as powering a PC back-up to powering a building during a power outage. Inverters come in many varieties, differing in price, power, efficiency, and application. Inverters can be single-phase or three-phase depending on the desired application. For each of them, there are two types of control: Full-wave control: the output signal is at the switching frequency and is generally close to a square signal. This type of inverter is used when the shape of the alternating signal is not essential.  PWM (Pulse Width Modulation) control: this type of control allows the generation of a wave which, after filtering the switching, is sinusoidal with variable amplitude and frequency. This type of inverter is used to generate an alternating signal close to a sinusoid. This work is the design and implementation of a single-phase bridge inverter that can be used for static converters. The switch control is managed by a PIC and will cover all types of possible controls. The energy source can be a photovoltaic generator. To calculate the switching angles and store them in memory areas, a computer medium is used as a control tool. For this, we have chosen the PIC18F452 microcontroller. The latter was chosen based on its technical performance, its ease of implementation and its availability on the market. The experimental results are presented.
Dynamic optimization strategy to enhance the efficiency of photovoltaic system
Authors: Houari Zerhouni M’hamed , Mansour Zegrar , Tarik Benmessaoud Mohamed , Zohra Zerhouni Fatima , Nouh Zegrar
Published: December 2024

Our present work exploits the potential of photovoltaic energy: abundant wealth of Algeria and aims to improve the use of photovoltaic solar panels PPV. Directly associating photovoltaic panels with a given load sometimes limits their good exploitation. With this in mind, this present work is interested in developing and understanding one of the ways to exploit this inexhaustible energy. Indeed, a lack of optimization generates a system often presenting failures in efficiency and therefore poor exploitation of PPV. This work therefore aims to develop a technique to draw the best power from PPV. The technique is: the implementation of the dynamic topology method of PV panels to optimize their use given a fixed number of PPV. The developed method determines the best assembly of the PV field by adjusting the connections between its panels, in order to minimize losses in the system. The interest is to maximize the exploitation of photovoltaic cells. This optimal assembly of PPV is for any load, at real operating conditions. The results found are presented.
Aplicação de ferramentas de gestão da produção em uma indústria metalúrgica de Sertãozinho
Authors: Oliveira João Daniel de Souza , Santos Paulo Samuel Pereira dos , Bonette Luiz Rodrigo
Published: December 2024

A aplicação de ferramentas de gestão da produção, como a Análise da Causa Raiz (ACR) e o 5W2H, mostrou-se eficaz na identificação e mitigação de gargalos no processo produtivo de uma indústria metalúrgica em Sertãozinho. O estudo, baseado em dados coletados ao longo de 90 dias, revelou possibilidades de melhorias para alinhar a capacidade efetiva com a capacidade realizada, otimizando o uso de recursos. A ACR facilitou a compreensão das causas subjacentes aos problemas, enquanto o 5W2H forneceu uma estrutura clara para planejar ações corretivas. Propostas como a implementação de manutenção preditiva e revisões no planejamento produtivo foram essenciais para reduzir paradas não planejadas, melhorar a eficiência operacional e garantir maior confiabilidade no processo produtivo. Os resultados destacam a relevância dessas ferramentas para promover um fluxo produtivo mais ágil e reduzir desperdícios, assegurando a competitividade no mercado. A pesquisa reafirma que o uso estratégico dessas metodologias pode levar ao aprimoramento contínuo dos processos industriais, proporcionando ganhos significativos em eficiência e produtividade. Assim, conclui-se que o Plano de Ação proposto tem o potencial de gerar melhorias sustentáveis e consolidar a gestão eficaz na indústria metalúrgica.
Hybridation of ResNet 50 and a customized CNN using transfert learning for pneumonia detection in CXR images
Authors: Monsif Boughenama , Mohammed Beladgham , Soumia Kerrache
Published: December 2024

In this paper, to categorize and detect Pneumonia desease from a collection of chest X-ray picture samples, we propose a deep learning technique based on object detection, convolutional neural networks, and transfer learning. The proposed model is a hybridation  of to models the pre-trained model (ResNet -50) and our designed architecture. The Guangzhou Women and Children's Medical Center in Guangzhou, China provided the chest X-ray  dataset used in this study. There are 5,000 samples in the data set, with 1,583 healthy samples and 4,273 pneumonia samples). Preprocessing techniques such as Bilateral Equalization was also used  to improve accuracy. Due to the imbalance of the data set, we adopted some training techniques to improve the learning process of the samples. This network achieved over 99% accuracy due to the proposed architecture that is based on a combination of two models. The pre-trained ResNet 50 as feature extractor and our designed convolutional neural network (CNN).
Assessment of lead contamination in Kohl available on the algerian market
Authors: Sellami Seifeddine , Lifa Said , Tebboub Omar , Zaamouche Fares , Zeghouan Ouahida , Gasmi Salim
Published: December 2024

The aim of this study is to assess the lead concentration in kohl sold in various regions of Algeria, due to its widespread use, which represents a potential source of lead exposure, particularly concerning for newborns and children who are more vulnerable to its toxic effects. Given that there is no standard composition for this traditional cosmetic, which is typically based on stibnite and galena, we analyzed 15 kohl samples with varying textures and origins using Flame Atomic Absorption Spectroscopy (FAAS). The results revealed the presence of lead in all samples, with concentrations ranging from 1.25 to 326 mg/kg. This variation raises concerns regarding the compliance of these products with current regulatory standards. In conclusion, none of the analyzed samples meet the legal standards for lead content, highlighting the need to reassess the health risks associated with the use of this traditional product.
First-principles calculations of the properties of CsXO2 materials (X = Cu, Ag and Au) in orthorhombic phase
Authors: Boukhari Ammar , Amari Rabie , Allali Djamel , Benrezgua Elhadj , Terchi Smail , Deghfel Bahri
Published: December 2024

The structural, electronic, optical, and elastic properties of CsXO₂ (X = Cu, Ag, Au) compounds have been systematically studied using first-principles density functional theory. These materials crystallize in an orthorhombic structure with space group Cmcm (No. 63), and their lattice parameters (a, b, and c) increase progressively from Cu to Au, influenced by the X atomic size. Elastic constant calculations confirm their mechanical stability, with Pugh’s ratio (B/G) identifying these compounds as ductile. Electronic structure analysis reveals that CsXO₂ compounds exhibit indirect semiconducting behavior, with conduction band minima located at the T point and valence band maxima at the Γ point in the Brillouin zone. This band alignment is crucial for understanding their electronic properties and tailoring them for specific applications. The optical properties of CsXO₂ vary significantly with their electronic structures. An increase in bandgap correlates with a shift of absorption intensities to higher energies and a decrease in static dielectric constants and refractive indices. Additionally, their transparency at photon energies above 22 eV highlights their potential for applications in optoelectronics and photonics. These findings provide valuable insights into the structure-property relationships of CsXO₂ and underscore their potential for advanced technological applications.
Improved copper(II) extraction from aqueous solutions using di-2-ethylhexyl phosphoric acid and MIBK
Authors: Ghebghoub Fatima , Labed Nadjoua , Barkat Djamel
Published: December 2024

In the present work, the synergistic extraction of copper(II) from sulfate media with di(2-ethylhexyl) phosphoric acid (D2EHPA) and methylisobutylkétone (MIBK) in chloroform at 25 °C, has been carried out. , with a focus on how pH, extractant concentration and diluent selection affect the extraction process. The extracted species in the organic phase have been found to be CuL2.2HL and CuL2. In the presence of MIBK, the extraction of copper by D2EHPA in the system chloroform-water (Na2SO4) showed that synergy effect increase with the concentration of the synergistic reagent. The results indicate that the synergistic effect is a result of the cooperative interactions between the D2EHPA /MIBK molecules, which improve phase stability, reduce metal-ion competition, and enhance the formation of metal-complexes. The potential for optimizing metal separation processes in hydrometallurgical operations, particularly for the recovery of rare and precious metals, is also highlighted in this paper, which compares the extraction performance of the D2EHPA-MIBK system to conventional single-agent extraction methods.
Integration of a product in a two-dimensional Fredholm integral equation with a weakly singular kernel
Authors: Dahmane Raouia Ben , Kaboul Hanane , Mokhtari Zouhir
Published: December 2024

This study highlights the feasibility of solving the Fredholm integral equation in cases where its kernel exhibits weak singularity, a challenging scenario that often arises in mathematical and physical applications. The primary objective of our research is to obtain a highly accurate solution, with a particular focus on two-dimensional cases. Addressing such equations requires careful consideration of the requisite mathematical conditions and the development of robust methods capable of handling the inherent complexities. In our previous work, we successfully demonstrated the effectiveness of the product integration method for solving the Fredholm equation in one-dimensional cases. This success served as the foundation and motivation to extend our approach to higher dimensions, where the complexity of the problem increases significantly. By adapting and refining the product integration method, we aim to achieve similar levels of accuracy and reliability in two-dimensional scenarios. Furthermore, the study introduces a practical application to showcase the utility of our approach. Before presenting this application, we rigorously prove the convergence of the approximate solution, ensuring that the methodology provides consistent and reliable results. This combination of theoretical analysis and practical demonstration underscores the robustness of our approach and its potential to address a wide range of problems involving weakly singular Fredholm integral equations in higher dimensions.
Predicting overhead temperature in distillation column by N-CARARMA model
Authors: Zouai Mohamed , Aggoun Lakhdar , Chetouani Yahya
Published: December 2024

In this paper, a non-linear controlled autoregressive autoregressive moving average (N-CARARMA) model was developed using extended least square algorithm (ELS) and extended stochastic gradient algorithm (ESG) to predict the evolution of the overhead temperature of a distillation column system. The model parameters were estimated and verified by taking input and output data from the separation unit under nominal operating conditions. Three criteria of models selection: Akaike’s Information Criterion (AIC), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency (NSE) are used to estimate the prediction performance of the N-CARARMA model. Using real experimental data, it is showed that the best structure of the proposed model can be used to describe the overhead temperature at different nominal operating conditions.