In this paper, we investigate the connections between certain spec-tra arising from Fredholm theory of a generalized Drazin invertible bounded linear operator and those of its generalized Drazin inverse. Furthermore, we analyze the transfer of Browder’s theorem and its generalized form from such an operator to its corresponding generalized Drazin inverse. Applications to left, right, and multiplication operators are also presented.

This article presents a linguistic analysis of language dysfluencies produced in exolingual situations. The study is based on a collection of real interactions recorded between Algerian doctors in a university hospital in the country. Following a corpus linguistics approach, the oral data were transcribed according to conventions adapted to spoken language. The description will focus on communication strategies that help manage the production difficulties encountered. The objective of the article is to identify the most frequent markers of disfluencies in the corpus, such as lexical repetitions, interrupted sentences, and terminological confusions. Additionally, it aims to explore whether there is a functional link between these disfluencies and language cooperation strategies, in order to ensure the dynamic of exolingual communication in a linguistic and professional context.

Introduction. A new global maximum power point tracking (GMPPT) control strategy for a solar photovoltaic (PV) system, based on the combination of Takagi-Sugeno (T-S) fuzzy models and an ANFIS, is presented. The novelty of this paper lies in the integration of T-S fuzzy models and the ANFIS approach to develop an efficient GMPPT controller for a PV system operating under partial shading conditions.

Purpose. The new GMPPT control strategy aims to extract maximum power from the PV system under varying weather conditions or partial shading.

Methods. An ANFIS algorithm is used to determine the maximum voltage, which corresponds to the actual maximum power point, based on PV voltage and current. Next, the nonlinear model of the PV system is employed to design the T-S fuzzy controller. A reference model is then derived based on the maximum voltage. Finally, a tracking controller is developed using the reference model and the T-S fuzzy controller. The stability of the overall system is evaluated using Lyapunov's method and is represented through linear matrix inequalities expressions.

The results clearly demonstrate the advantages of the proposed GMPPT-based fuzzy control strategy, showcasing its high performance in effectively reducing oscillations in various steady states of the PV system, ensuring minimal overshoot and a faster response time. In addition, a comparative analysis of the proposed GMPPT controller against conventional algorithms, such as Incremental Conductance, Perturb & Observe and Particle Swarm Optimization, shows that it offers a fast dynamic response in finding the maximum power with significantly less oscillation around the maximum power point.

A human skills framework is a human resource management tool that identifies and describes the set of skills required to fill different positions within an organization. This article helps to identify the knowledge, know-how, and interpersonal skills needed for each role, thereby facilitating talent management and the professional development of employees. By clearly identifying the required skills and adequately training personnel, the framework helps reduce costs related to unexpected breakdowns and emergency interventions, while maximizing equipment availability. A human skills framework is a strategic tool that contributes to optimizing an organization’s human capital, enabling better alignment between available and re

A human skills framework is a human resource management tool that identifies and describes the set of skills required to fill different positions within an organization. This article helps to identify the knowledge, know-how, and interpersonal skills needed for each role, thereby facilitating talent management and the professional development of employees. By clearly identifying the required skills and adequately training personnel, the framework helps reduce costs related to unexpected breakdowns and emergency interventions, while maximizing equipment availability. A human skills framework is a strategic tool that contributes to optimizing an organization’s human capital, enabling better alignment between available and re

The phenomenon of swelling-shrinkage has gained widespread attention in practice owing to the generation of eroded clayey layers of soil that amplify with global climate change and the seasonal water content. This provokes several serious disorders affecting the stability of nearby constructions and consequently generating human loss. The expansive clayey soils show the phenomena of wetting and drying cycles in their natural state (undisturbed soil). Hence, classical oedometric tests are found to be unable to take into account the thermal behavior of naturally swelling soils; this is proven by the resulting asymptotic volumetric behavior, as well as the steady values of the potential of swelling and shrinkage. The main aim of this experimental analysis is to derive a test that considers the significant effect of temperature. Experimental results of an oedometric approach are represented herein for the purpose of investigating the volumetric and hydric behavior of naturally swelling soil in the region of N’Gaous (Eastern Batna province, Algeria) through drying-wetting paths. Innovative expressions are derived for the direct computations of the swelling-shrinkage potential in terms of water content, appearance time and applied loads. It is of interest to mention that those expressions are applicable to other regions in the world with similar soil geotechnical and chemical characteristics and conditions. The cyclic outputs show that the swelling pressure variation with the appearance time is mainly related to the first cycle of swelling shrinkage; as it exhibits a noticeable increase in the swelling potential with the amplification of applied loads until reaching a state of steadiness. The experimental results demonstrate a high degree of reliability and correlation with the soil behavior. Therefore, the swelling shrinkage potentials are expressed innovatively in equations that help predict the soil behavior in expansive regions in order to enhance the safety of nearby foundations.

The growing need for clean energy has made solar panels an essential solution. However, the nonlinear behavior of photovoltaic (PV) systems under varying weather conditions necessitates advanced control strategies to ensure optimal energy harvesting. This paper presents an enhanced Maximum Power Point Tracking (MPPT) approach that integrates the conventional Perturb and Observe (P&O) method with an Indirect Adaptive Fuzzy Controller (IAFC). While P&O is known for its simplicity, it suffers from steady-state oscillations and slow response during environmental changes. To address these issues, the IAFC adaptively adjusts the perturbation step using a Lyapunov-based rule to improve convergence and minimize power fluctuations. The proposed method achieves Maximum Power Point tracking within less than 0.025 s, compared to 0.05 s for the conventional P&O algorithm. This enhances the credibility of our dynamic performance claim. Specifically, unlike prior fuzzy-P&O hybrids with fixed rule sets, our method leverages Lyapunov-based adaptation to dynamically adjust the control action, improving convergence and robustness under changing conditions. We also included a quantitative metric showing a 75% reduction in power fluctuations compared to conventional P&O. Simulation results under varying sunlight conditions demonstrate fast convergence and improved power stability. The proposed IAFC method clearly outperforms classical P&O in tracking accuracy, responsiveness, and overall energy yield.

This paper compares two approaches for detecting and analyzing acoustic microwaves in piezoelectric materials, specifically in Lithium Niobate (LiNbO3) substrates. The first method focuses on modeling the propagation of acoustic microwaves in piezoelectric structures, utilizing an interdigital transducer (IDT) to excite the electroelastic waves. This method investigates various wave types, such as secondary surface waves, leaky waves, bulk waves, and skimming bulk waves, and applies wavelet transform for efficient detection. Two wavelet functions—Mexican-hat and Morlet—are compared based on their ability to detect acoustic wave singularities, with an emphasis on their efficiency in processing microwave signals. The second method introduces a machine learning approach using support vector machines (SVM) to detect ultrasonic pulses and identify previously undetectable waves. By classifying real and imaginary parts of the coefficient attenuation and acoustic velocity, this method provides more accurate values and facilitates the modeling of ultrasonic pulse propagation. While the wavelet-based approach focuses on signal processing for wave detection, the SVM-based method excels in detecting complex wave patterns that traditional methods may overlook, offering higher precision in ultrasonic pulse modeling and the realization of acoustic microwave devices.

The present work focuses on the experimental characterisation and numerical validation of the in-plane mechanical properties of IM2-12K/Epocast 50-A1 composite for structural damage prediction. Consequently, a series of tensile, compressive, shear, and flexural tests were systematically conducted on specimens prepared with specific lay-up configurations, while the fibre volume fraction was measured using the ashing method. The experimental results demonstrated that the composite under investigation exhibited high tensile strength and stiffness along the fibre direction, moderate compressive properties, and lower shear strength. This behaviour is indicative of anisotropic properties. Moreover, a three-dimensional finite element simulation of the tensile and three-point flexural tests was subsequently conducted, employing a Hashin-based failure initiation criterion. In order to achieve this objective, the key material properties were incorporated into a user-defined material subroutine (VUMAT), thereby enabling the modelling of progressive damage mechanisms, encompassing both fibre and matrix failures. The numerical predictions exhibited excellent agreement with the experimental data, thereby validating both the measured properties and the robustness of the modelling strategy. The present study establishes a validated mechanical dataset and a predictive model, providing a reliable foundation for the design and simulation of the performance of IM2-12K/Epocast 50-A1 in advanced engineering applications.

Urban planning plays a critical role in sustainable city development by guiding urban expansion efficiently. In Algeria, the master plan for development and urban planning (PDAU) designates specific areas for city growth, yet the suitability of these areasfor urban extension often remains unassessed using systematic methods. Most PDAU, including the plan for Setif City established in 2016, rely on planning approaches and data that risk becoming outdated due to rapid urban changes and evolving spatial dynamics. As a result, there is a pressing need to critically assess and validate these designated extension zones using updated, objective analytical tools. This study addresses this gap by applying an integrated approach combining Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP) to evaluate land suitability for urban extension in Setif City. Fifteen socio-economic, physical, environmental, and accessibility criteria were applied to assess areas designated in the PDAU. The methodology enables a multi-criteria, data-driven analysis to prioritize zones for sustainable urban growth. About 21.5% of the study area is categorized as very high suitability, and most of these sites are concentrated around the edges of the city.36.7% is classified as high suitability, according to the suitability analysis for future urban expansion. Moderately and poorly suitable areas make up 23.79% and 13% of the total. Merely 5% of the land is deemed to be extremely unsuitable for the extension. The findings support evidence-based urban planning, offering actionable insights for policymakers and urban planners. This study contributes methodologically by demonstrating the effective integration of AHP with GIS in an Algerian context, encouraging replication and further research in similar urban environments.

Wireless sensor networks (WSNs) have recently emerged as a critical technology in various applications, including industrial automation, building monitoring, and military. However, the data generated by these networks are often prone to outliers, which can compromise sensor data quality and reliability. Detecting outliers is paramount to ensure proper network functioning. Traditional detection techniques pose several challenges, such as weak adaptability to the increasing complexity and dynamic environmental changes, limited accuracy, and higher computation costs. To address these challenges, this paper proposes an optimized one-dimensional convolutional neural networks (1D CNN)-based outlier detection approach for WSNs. This approach comprises two key modules: a predictor module and an outlier detector. The predictor module employs a 1D CNN model to forecast forthcoming sensor measurements based on historical data. Bayesian optimization is used to enhance the 1D CNN model’s accuracy. The outlier detector identifies outliers based on the Euclidean distance between the predicted measurements and their corresponding actual values. Experiments on synthetic and real-world datasets reveal that our proposed approach outperforms other existing deep learning-based frameworks in terms of accuracy, F1 score, and false alarm rates.

Introduction/purpose: Algerian natural zeolite (denoted NZ) was modified using hydrochloric acid (HZ) and sodium hydroxide solution (NaZ). This study investigated the impact of acid and alkaline modifications on the adsorption of two cationic textile dyes (BR46 and BY13) from aqueous solutions. Methods: The XRF analysis confirmed that SiO2 is the predominant mineral in all three zeolites. The XRD results revealed that NZ is primarily composed of mordenite, with chabazite and minor quartz content. The MEB-EDX analysis showed slight variations in the Si and Al content for HZ and NaZ, without significantly altering the zeolite’s structure.. The effects of initial dye concentration, contact time and pH were examined in a batch system.

Results: The adsorption on NZ, NaZ and HZ increased with longer contact times, higher initial dye concentrations, and elevated temperatures. Equilibrium was rapidly attained best described using the pseudo-second order kinetic model. Both the Langmuir and the Freundlich isotherm models fit for the adsorption data. Conclusion: The highest dye removal efficiency was observed for NaZ, with 97.62% for BR46 and 98.97% for BY13. The lowest removal rates occurred at pH= 8 for HZ and pH=10 for NZ and NaZ. Adsorption was spontaneous and endothermic.

Introduction purpose: As population growth and industrial expansion continue, surface freshwater reservoirs such as dams have become increasingly vital due to their accessibility and ease of treatment. However, the quality of these water sources has significantly deteriorated, primarily due to the discharge of domestic and industrial wastewater. The proliferation of extensive algal blooms has led to significant challenges in maintaining drinking water quality and raised concerns about public health. This study investigates the impact of various water sources on the physicochemical quality of an Algerian dam over four seasons (December 2020 – October 2021) and explores the factors influencing the occurrence of cyanobacterial blooms to better understand and manage this excessive growth.

Methods: Physicochemical properties and algal composition of the dam water were analyzed monthly to determine nutrient sources and environmental factors affecting cyanobacterial proliferation. Results: The analysis revealed that the Timgad stream and Reboua valley are notable sources of nutrient enrichment. Elevated temperatures and high nutrient loads, particularly total phosphorus (TP), in Timgad dam water facilitate the proliferation of blue-green algae. Additionally, limited nitrogen content favors the dominance of nitrogen-fixing cyanobacteria such as Aphanizomenon and Oscillatoria. The study also highlights that the low flow rate and high nutrient load of the Timgad stream create favorable conditions for cyanobacterial growth. Conclusions: Nutrient inputs, temperature, and hydrological conditions significantly influence cyanobacterial blooms. Understanding these factors is crucial for implementing effective water management strategies to reduce algal proliferation and protect freshwater quality.

This article presents a quantitative and qualitative analysis of causal markers in scientific articles published in France and Algeria. Based on two corpora drawn from Synergie France and Synergie Algérie, the study examines the frequency, distribution, and functions of connectors such as car, donc, puisque, and parce que. The results reveal a common core of markers but distinct preferences:  French authors favor a structured and diversified argumentative style, while Algerian writers adopt a more explicit and pedagogical approach. These differences reflect contrasting academic traditions and highlight the didactic importance of causal markers in the teaching of scientific writing.

The aim of the present study is to examine the way in which The Daily Telegraph portrays migrants as ‘Others’ by employing a discourse and power dynamics perspective. It attempts to identify and analyse the predominant discursive strategies, social context implications and power dynamics that the newspaper employs to represent this group of individuals. The study uses a descriptive qualitative research approach, along with critical discourse analysis, adopting Fairclough’s three-dimensional framework as a research instrument for analysis. This framework allows for a thorough analysis of the text, and its social context. Consequently, the results gained from the examination, revealed that the Daily Telegraph used various discursive strategies to construct migrants as others in a negative way, employing metaphor, hyperbole, and othering strategies. As regards the discursive practices, social context implications and power dynamics at play, the study showed that migrants are believed to be an uncontrollable "other" that necessitates border control. The marginalisation and exclusion of migrants from the holding society were frequently the result of the recurrent use of negative stereotypes by the daily Telegraph. It is possible that this will lead to unfair policies and the maintenance of power relationships by making these migrants seem different or dangerous.

 Ensuring the safety and health of assembly line workers is critical to increasing productivity and preventing accidents. This research presents a real-time monitoring system that combines computer vision (AI), wearable Internet of Things (IoT) devices, and cloud-based technologies to detect worker fatigue and health risks. The system calculates eye aspect ratio (EAR) and mouth aspect ratio (MAR) to identify fatigue symptoms such as eye closure and yawning, while wearable IoT devices monitor physiological parameters such as heart rate (HR) and blood oxygen saturation (SpO₂) to detect potential health issues. Alerts are automatically triggered based on pre-defined thresholds, allowing for immediate intervention. All data is processed in real-time with input from wearables and computer vision, and transmitted to a cloud platform for analysis, reporting and storage. This integration of AI-powered computer vision, wearable IoT and cloud connectivity ensures continuous monitoring and provides actionable insights to supervisors, improving workplace safety and operational efficiency. The results of the study demonstrate the effectiveness of this innovative system in identifying fatigue and health issues, reducing accidents and promoting a safer working environment. By using the latest technology, the proposed solution addresses the urgent need for advanced safety measures in demanding work environments.

This study investigates the fatigue degradation and crack propagation in the locking mechanism of PET bottle blow molding machines, focusing on the impact of elliptical cracks on the mechanism’s performance and longevity. The locking mechanism, which plays a vital role in securing the mold during the blow molding process, is subjected to repeated loading, making it susceptible to fatigue damage. Using a combination of finite element analysis (FEA) and experimental methodologies, we examine the stress distribution, deformation, and displacement in the mechanism under operational loads. The study identifies the most stressed component and models the behavior of an elliptical crack located at the center of this component. A stress intensity factor (K) of 3.7553 MPa.mm-0.5 is found, indicating significant risk in the crack region. Fatigue analysis using Goodman’s law predicts a service life of one million cycles with a safety factor of 2.08. These findings highlight the need for targeted design and maintenance strategies to enhance the reliability and durability of PET blow molding machines.

This paper investigates the relationship between the extended spectrum of a bounded linear operator and its group inverse. We also establish a connection between the extended spectrum of the bounded linear operator and that of its Drazin inverse. As part of our analysis, we prove the following equality: σext((BA)D) = σext((AB)D), where (BA)D and (AB)D represent the Drazin inverses of BA and AB, respectively. 2020 Mathematics Subject Classification. 35K15; 35K55; 35K65; 35B40. Key words and phrases. extended spectrum; operator group inverse; Drazin inverse.

III-V-based materials are widely used for multi-junction solar cell applications due to their large band gap, allowing them to absorb a significant amount of light and increase the output power. Among the III-V materials, AlGaAs is a promising candidate for the top cell due to its tunable band gap. However, the growth of AlGaAs often leads to the formation of DX-centers, resulting in low material quality and limiting the reported efficiencies of AlGaAs cells to mostly below 18.7%. Research in this field has primarily focused on single and multi-variable parameter sweep methods to optimize the conversion efficiency of solar cells. While effective, these techniques can be time-consuming, especially when only the final result matters and their accuracy diminishes as the number of layers in the cell increases. To address these challenges, we proposed a metaheuristic method based on Real Coded Genetic Algorithm (RCGA) to optimize the solar cell. By hybridizing MATLAB and Atlas SILVACO, we developed an efficient code. The effectiveness of the utilized modeling framework is evaluated by comparing its predictions to experimental results, revealing a strong correspondence between the two. The obtained results were compared to those achieved using conventional parameter sweep methods. Our optimized solar cell achieved an efficiency of 26.08% under the AM1.5 spectrum. The findings demonstrate that a multi-dimensional optimization using the RCGA approach, combined with the Atlas SILVACO simulator, can be effectively employed to optimize semiconductor devices, offering a more robust alternative to existing methods.

This study presents the development and validation of a hybrid cutting force prediction model for ball end milling of aluminum 7075-T6 alloy. The model combines a mechanistic approach with a specific cutting force coefficient (Ks=850 N/mm²) sourced from experimental literature. Cutting forces in the x, y, and z directions are predicted by integrating differential force components with tool geometry and machining parameters. Experimental validation was performed under dry conditions at a spindle speed of 15,000 rpm. In the x-direction, the simulated force was 162.4 N versus an experimental force of 215.4 N; in the y and z-directions, predicted values (65.2 N and 25.3 N) closely matched experimental forces (74.3 N and 28.2 N), respectively. The corresponding mean absolute errors were 18.2% (x), 4.5% (y), and 3.3% (z). The higher error in the x direction highlights limitations in modeling tangential force dynamics, while the y and z predictions align closely with experimental data. Leveraging the experimentally derived Ks, the proposed model offers a practical tool for optimizing machining processes in the aerospace sector, with potential for further refinement in tangential force modeling.