Libyan Open University Journal of Applied Sciences (LOUJAS)
The Libyan Open University Journal of Applied Sciences (LOUJAS) (eISSN: 3106-0919) is a distinguished, peer-reviewed scientific journal proudly published by the Libyan Open University. With a commitment to fostering scientific discourse and knowledge dissemination, LOUJAS releases new issues twice a year, ensuring a consistent platform for researchers. Scope and Disciplines LOUJAS is dedicated to covering a wide array of disciplines within the applied sciences. This broad scope allows the journal to publish cutting-edge research from various fields, including but not limited to: Engineering and Technology Environmental Sciences Computer Science and Information Technology Agricultural Sciences Material Science Biotechnology Applied Physics Applied Chemistry Mathematics and Statistics (with applied focus) The journal welcomes original research articles, review papers, and short communications that contribute significantly to their respective fields and have practical applications. Mission and Vision LOUJAS aims to be a leading journal in the region, providing a robust platform for scholarly exchange and the publication of high-quality, impactful research. Its mission is to: Promote scientific research in applied sciences. Facilitate the dissemination of new knowledge and innovations. Support the academic community by offering a rigorous peer-review process. Contribute to the advancement of science and technology, both locally and globally. Connect with LOUJAS You can explore the journal's published articles and learn more about their submission guidelines by visiting their official website: Website: https://oujournals.ly/index.php/LOUJAS For any inquiries, submissions, or general communication, the LOUJAS team can be reached through the following channels: Email: loujas.editor@ou.edu.ly WhatsApp: 00218913426255 LOUJAS stands as a testament to the Libyan Open University's dedication to academic excellence and its role in advancing scientific understanding in the applied sciences.
Functional Classification of Artificial Intelligence Applications within Learning Management Systems: An Analytical Study of Concepts and Applications
This paper presents a conceptual and classificatory analytical study aimed at constructing a functional taxonomy of artificial intelligence applications within Learning Management Systems (LMS) during the period 2020–2025. The study responds to the problem of conceptual confusion and terminological overlap between artificial intelligence, learning analytics, rule-based automation, and personalization. The paper adopts a structured review of evidence and codes “functional features” as the unit of observation into defined categories according to operational definitions and attribution rules based on the “traceable end output” within the LMS environment. This approach produces a single classification table comprising five functional categories: prediction, recommendation, automated assessment, conversational support, and administrative decision support. Each category is linked to expected data inputs and observable outputs, along with explicit rules for managing overlap when more than one function appears within a single feature. The paper concludes that regulating attribution through traceable outputs reduces terminological ambiguity and improves the comparability and descriptive evaluation of artificial intelligence functions within LMS environments, without making causal claims regarding educational impact.
AI in Education, LMS, Functional Taxonomy, Learning Analytics, Educational Automation.
Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
Numerical Study of Triple Pipe Heat Exchanger Using Copper, Steel, and Aluminium of Varying Thicknesses
This study investigates the thermal performance of a triple-pipe heat exchanger constructed with copper, steel, and aluminum pipes of varying wall thicknesses. The analysis focuses on the influence of material properties and thickness on heat transfer efficiency, pressure drop, and overall exchanger effectiveness. Results indicate that copper, owing to its superior thermal conductivity, achieves the highest heat transfer rates. Aluminum provides a favorable compromise between conductivity and structural weight, while steel contributes mechanical strength but exhibits comparatively lower thermal performance. Variations in wall thickness further impact conduction resistance and fluid flow characteristics, underscoring the importance of optimising both material selection and geometric design to enhance exchanger efficiency.
heat exchanger; triple-pipe heat exchanger Efficiency, Optimization, Strategies
"Evaluating the Impact of PCA-Based Dimensionality Reduction on Bitcoin Transaction Forecasting: A Comparative Study of XGBoost, LSTM, and GNN"
Accurate forecasting of Bitcoin dynamics is essential for digital asset management. While existing literature primarily focuses on market price prediction using ensemble and deep learning, this study extends the frontier by analyzing high-dimensional on-chain transaction data. We present a comparative evaluation of XGBoost, LSTM, and Graph Neural Networks (GNN), specifically investigating the impact of Principal Component Analysis (PCA) on model stability. Our findings reveal a 'PCA Paradox': while dimensionality reduction enhances the performance of GNN and LSTM by filtering noise, it marginally reduces the precision of XGBoost. Results show that XGBoost achieves the highest numerical accuracy (RMSE: 0.018), whereas GNN and LSTM provide superior trend stability. This research provides critical insights into feature engineering for blockchain-based financial systems
Bitcoin, Blockchain Transactions, XGBoost, LSTM, Graph Neural Networks (GNN).
Study of Physicochemical Properties and Mineral of Seeds from two date palm cultivars grown in Libya
In the present study, the seeds of two date palm (Phoenix dactylifera L.) cultivars grown in the North (Al-Brince) and the South (Al-Allig) of Libyan were analysed and compared for their chemical, physical properties and macroelements. The following values (Based on dry matter) were obtained for Al- Brince and Allig cultivars, respectively: The seeds constitute about 14.73- 11.16% seed/date fruit weight, the length from 2.4-2.5cm, and the diameter from1.2-1.3cm.The chemical properties of present research consists of moisture 4%, ash1.90% for both samples, protein1.98 -1.10%, total sugar 0.35- 8.27g/100g,crud fiber 52.20 - 34g/100g of date seeds powder (DSP) on dry weight basis (DW). Whereas the mineral analysis of seeds showed higher concentration of K(205.36 – 217.57mg /100 g) followed by P(113.1- 114.1mg/100g), Ba (47.55 – 51.34mg/100g), Na (34.93 – 22.30 mg/100g), Ca (5.89- 1.68 mg/100g), for (Al-Brince) and (Allig) seeds, respectively
Date seeds, Date seeds powder, Physicochemical properties, Macroelements
Integration Between Applied Mathematics and Information Technology
This study aimed to develop an integrative framework that systematically links applied mathematics and information technology in the context of natural resources data analysis. The research was motivated by the observation that many contemporary applications address mathematical and technological aspects separately, leading to partial and less efficient analytical outcomes. A comprehensive approach combining theoretical analysis and practical application was adopted. The study highlighted linear algebra, numerical analysis, and optimization models as fundamental mathematical foundations for analytical modeling. The proposed framework was examined through a multiple linear regression model analyzing the relationship between selected environmental variables and a water quality index.The mathematical model was transformed into an executable algorithm within a numerical analysis environment, and its performance was evaluated using quantitative indicators, including the coefficient of determination, mean squared error, and residual analysis. The results demonstrated strong explanatory power and computational stability, confirming that methodological integration between mathematical formulation and algorithmic implementation enhances modeling efficiency and supports evidence-based decision-making in natural resource applications
Applied Mathematics, Information Technology, Mathematical Modeling, Data Analysis, Natural Resources
Phytochemical Profiling and In Vitro Antimicrobial Potential of Hypericum decaisneanum Coss. Aerial Parts Endemic to Bani Waleed, Libya
The escalating global threat of antimicrobial resistance (AMR) has necessitated the exploration of novel bioactive compounds from medicinal plants. This study was conducted to evaluate the in vitro antimicrobial efficacy and preliminary phytochemical profile of Hypericum decaisneanum Coss., a species endemic to the Bani Waleed region of Libya. Aerial parts of the plant were collected during the flowering season in May 2023. These materials were shade-dried and successively extracted using three solvents of varying polarity: methanol, ethanol, and distilled water via a Soxhlet apparatus. The antimicrobial activity was assessed against a diverse panel of microorganisms, including Gram-positive bacteria (Staphylococcus aureus, Enterococcus faecalis), Gram-negative bacteria (Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae), and the fungal strain Candida albicans using the agar well diffusion assay. Quantitative assessments were performed to determine the minimum inhibitory concentration (MIC) and minimum bactericidal/fungicidal concentration (MBC/MFC) through the broth microdilution method. Results indicated that the methanolic extract exhibited the most potent and broad-spectrum antimicrobial activity. It demonstrated significant inhibition zones against all tested strains, particularly against S. aureus (21.3 ± 0.6 mm) and C. albicans (19.5 ± 0.7 mm). The MIC values for the methanolic extract ranged from 0.312 mg/mL to 2.5 mg/mL, with the lowest MIC observed against S. aureus. The MBC/MFC values were generally equal to or twice the MIC values, suggesting a primarily cidal mode of action. In contrast, the ethanolic extract showed moderate activity, while the aqueous extract was largely ineffective. Phytochemical screening of the methanolic extract revealed a rich presence of tannins, flavonoids, terpenoids, and anthraquinones. Quantitative analysis confirmed high levels of total phenolic content (185.4 ± 5.2 mg GAE/g) and total flavonoid content (112.6 ± 4.1 mg QE/g). These findings validate the potential of H. decaisneanum as a source of natural antimicrobial agents and warrant further bioassay-guided fractionation to isolate specific active principles
Hypericum decaisneanum, antimicrobial activity, medicinal plants, Libya, MIC, MBC, phytochemicals
A study of soil salinity in Wadi Al-Qubeiba and its impact on agricultural activity in the city of Sirte
The study was conducted in the Wadi Al-Qubeiba area, west of the city of Sirte, with the aim of classifying the area's soils according to the American classification of salt-affected lands, The study examined soil salinity and its impact on agricultural activity in the region. The results showed a variation in the region's soils, ranging from non-saline to saline depending on their salt content. Salt concentration values fell within a range of slightly saline soils, which were found in (15) locations in the region, while the remaining locations were classified as saline soils, The results also showed a variation in soil pH values, ranging from (6.9-8.6). From these values, it is clear that the soils in this region are distributed in the range from neutral to alkaline soils, As for the values of the calcium element in the soil of the study area, most of the values were within the normal range, with a noticeable increase in the calcium value in some locations. The results showed that the values of the magnesium element in the soil of the study area were within the normal range, with a noticeable increase in some locations, The sodium values for the soils of the study area were within the normal range, with some locations noting their elevation. The values of the sodium adsorption ratio (SAR) fell within the normal range for most locations in the area, and the values of the exchangeable sodium ratio (ESP%) fell within the normal range in all locations of the study area.
Land assessment, soil salinity, saline soils, sodic soils, suitability of saline soils for agriculture
Effect of Supplementing Drinking Water with Different Levels of (Artemisia annua L.) Extract on Hematological and Biochemical Blood Parameters in Broiler Chickens
This study was conducted in a poultry facility located in Sirte, Libya, to evaluate the effects of supplementing drinking water with different levels of Artemisia annua extract on selected hematological and biochemical parameters of broiler chickens. A total of 108 birds aged 14 days, with an average initial body weight of 530 g, were randomly allocated into three treatment groups, each consisting of three replicates of 12 birds. The control group received no additives, whereas the second and third groups were supplemented with A. annua extract at concentrations of 10 mL/L and 20 mL/L of drinking water, respectively. All birds were fed the same commercial diet throughout the 28‑day experimental period. The results revealed no significant differences (P > 0.05) among treatments in red blood cell count, hemoglobin concentration, platelet count, total white blood cells, neutrophils, eosinophils, or basophils. However, highly significant differences (P < 0.01) were recorded in packed cell volume and monocytes, with the highest values observed in the group receiving 20 mL/L. Lymphocyte counts were highest in the 10 mL/L group. Significant differences (P < 0.05) were also detected in triglycerides, with the highest levels observed in the 20 mL/L group, while the 10 mL/L group exhibited a highly significant increase (P < 0.01) in glucose concentration. The control group showed the highest urea level. No significant differences were observed in total protein, HDL, LDL, cholesterol, albumin, or globulin among treatments. These findings suggest that Artemisia annua extract may influence certain hematological and biochemical variables in broilers, particularly at higher inclusion levels, without adversely affecting major blood constituents.
Artemisia annua, broiler chickens, hematological parameters, biochemical profile, herbal extract
A Comparative Study Between Conventional Power Generation Plants and Renewable Energy Generation Technologies Using Solar (PV) Panels and Wind Energy in Libya
Energy systems in Libya share many of the same characteristics found across developing countries, relying heavily on traditional electricity generation methods such as fossil fuels and natural gas. This dependence results in high electricity costs, significant fuel consumption, and increased pollution and carbon emissions. In recent years, advancements in renewable energy technologies have created an opportunity to address these challenges and enhance the affordability and sustainability of the national energy system. This study highlights the comparison between conventional power generation plants and renewable energy technologies, outlining the advantages and disadvantages of each in order to adopt the most suitable option and incorporate it into future expansion plans to meet the growing demand for energy and reduce the costs of its production and transmission to load centers.
Renewable Energy, Gas Turbine Power Plant, wind power plants, Fuel Consumption
Assessment of Infestation Severity by Scale Insects and Citrus Leafminer and Evaluation of Cultivar Susceptibility in a Citrus Orchard in Qasr Ben Ghashir, Libya
Scale insects and the citrus leafminer are among the major pests affecting citrus productivity and fruit quality in Mediterranean environments, including Libya. This study aimed to evaluate the infestation severity of three scale insect species: California red scale (Aonidiella aurantii), black scale (Chrysomphalus ficus), and purple scale (Lepidosaphes beckii), in addition to the citrus leafminer (Phyllocnistis citrella), on six citrus cultivars (Fresh Lime, Kenyan local, Java, Lime, Kenyan American, and Abu Surra). The study was conducted in an orchard located in Qasr Ben Ghashir (Jefara Plain). Samples were randomly collected by examining 100 leaves and 25 fruits per cultivar from five trees. Infestation percentages were calculated for leaves and fruits. The results showed clear variation among cultivars in infestation levels. The Kenyan local and Fresh Lime cultivars recorded the highest infestation percentages with California red scale (36.8% and 36.6%, respectively), while Abu Surra exhibited complete resistance. The highest citrus leafminer infestation was recorded on Lime and Fresh Lime cultivars (48%). These results reflect genetic differences in cultivar susceptibility and support the use of less susceptible cultivars within integrated pest management programs to reduce reliance on chemical pesticides.
Citrus, Scale insects, Citrus leafminer, Integrated pest management, Libya
Optimization of Machining Parameters for Minimum Surface Roughness in Turning of Aluminium- Magnesium Alloy Using a 0.4 mm Nose Radius Tool: A Taguchi Approach
This study presents a systematic investigation to optimize the turning parameters in order to minimize surface roughness (Ra) of an Aluminum–Magnesium alloy (Al3Mg) using a CNC turning machine and a cutting tool insert with a 0.4 mm nose radius. The work employs the Taguchi Design of Experiments (DOE) methodology to analyze the effects of three main control factors (cutting speed, feed rate, and depth of cut), each at three levels. An L9 orthogonal array was used to design the experiments. In this study, the “smaller-the-better” signal-to-noise (S/N) ratio was utilized as the performance metric to evaluate surface roughness. Analysis of Variance (ANOVA) was performed to determine the statistical significance and percentage contribution of the turning parameters. The optimal parameter combination for the 0.4 mm nose radius tool was: Cutting Speed (B3) = 900 rpm, Feed Rate (A1) = 0.3 mm/rev, and Depth of Cut (C2) = 1.0 mm. The ANOVA results indicated that feed rate was the most significant contributing factor, accounting for 88.97% of the total variation in surface roughness, followed by cutting speed (4.44%) and depth of cut (3.14%). The predicted surface roughness under optimal conditions was 508.21 µm. This study demonstrates the effectiveness of the Taguchi methodology for process optimization, leading to improved surface roughness with a minimal number of experiments.
Taguchi method; surface roughness; CNC turning; ANOVA; cutting parameters; Aluminum–Magnesium alloy
Secondary Metabolite Profiling and In Vitro Bioefficacy of Retama raetam Extracts Using Bacterial Test Systems
The increasing global concern regarding reduced effectiveness of conventional antimicrobial agents has intensified interest in identifying alternative bioactive resources of natural origin. This study evaluated the phytochemical profile and in vitro bioefficacy of Retama raetam crude extracts using selected bacterial test systems, namely Escherichia coli, Klebsiella spp., Pseudomonas aeruginosa, and Staphylococcus aureus. Aerial parts of the plant were collected from Al-Zawiya, Libya, shade-dried, and extracted using ethanol, methanol, and distilled water through cold maceration. Extraction yield varied according to solvent polarity, with ethanol producing the highest yield. Qualitative phytochemical screening revealed the presence of alkaloids, flavonoids, tannins, terpenoids, and saponins, with a comparatively higher abundance of bioactive constituents detected in the ethanolic extract. Biological response was assessed using the agar well diffusion assay against standardized inocula (0.5 McFarland). The ethanolic extract demonstrated pronounced inhibitory activity, particularly against P. aeruginosa (40 ± 1.2 mm), while moderate inhibition was observed against S. aureus and E. coli. No detectable inhibition was recorded against Klebsiella spp. Statistical analysis using one-way ANOVA confirmed significant differences among extracts (p ≤ 0.05). The observed bioactivity may be attributed to the synergistic action of phenolic compounds and alkaloids capable of influencing bacterial membrane integrity and metabolic pathways. These findings position R. raetam as a promising reservoir of biologically active secondary metabolites and support further quantitative, mechanistic, and minimum inhibitory concentration investigations to clarify its functional potential
Retama raetam, phytochemical screening, antibacterial activity, secondary metabolites, antimicrobial resistance
Physicochemical Parameters of Drinking Water Produced by Small-Scale Desalination Plants and Their Impact on Consumer Safety in Sabratha, Libya.
This study addresses the fundamental nexus between water security and environmental sustainability by examining the physicochemical properties of drinking water and evaluating the operational efficiency of small-scale desalination and filtration plants in Sabratha, Libya. Considering increasing groundwater salinity and deteriorating quality, these plants have emerged as a strategic solution to ensure the sustainability of water supplies. This field study aims to measure the capacity of these systems to remove salts and bacterial contaminants, providing drinking water with balanced physical, chemical, and biological characteristics. The research scope includes analyzing water quality from multiple sources (shallow wells, groundwater, and public distribution networks), with a focus on assessing water used in vital facilities such as hospitals, medical laboratories, and food industries. Preliminary results indicate a wide proliferation of these technologies, accompanied by a remarkable disparity in quality standards and the technologies employed. The study seeks to provide a comprehensive scientific evaluation linking the performance of these plants with standard health criteria, thereby contributing to the enhancement of sustainable water management strategies and the reduction of health risks associated with water pollution in coastal areas.
Water Security, Sustainability, Desalination Sustainability, Drinking Water Quality, Microbial Disinfection, Sabratha City
Calibration of Radiation Detectors for Monitoring and Decontamination of Radioactive Surface Contamination
This study presents a systematic approach for managing radioactive surface contamination and evaluating the effectiveness of decontamination procedures. The methodology involves the calibration of three distinct radiation detectors: Monitor E, Monitor S, and NE BP1/4, followed by the identification of the contamination source. Instrumental monitoring was integrated with smear testing to assess the efficacy of surface decontamination. This was performed by wiping the contaminated areas with specialized filter papers and measuring the residual radioactivity. The results demonstrated successful surface decontamination; subsequently, the generated radioactive waste was collected and disposed of in compliance with established radiological safety guidelines. Waste disposal procedures were initiated once the total accumulated activity reached the regulatory limit of 370 kBq, as determined by the filter paper measurements.
Surface Radioactive Contamination, Decontamination, Radiation Monitoring, Smear Test, Radioactive Waste, Detector Calibration
Chemical and Microbiological Analysis of Groundwater After a Major Flood Event in Darna City
This study evaluates the impact of severe flooding caused by Storm Daniel on groundwater quality in Derna city. Groundwater samples from five wells were collected immediately after the flood and analyzed for physical, chemical, and microbiological parameters. Wells 1 and 2 were located within the flooded area, while Wells 3, 4, and 5 were nearby but were not submerged. The results indicate that the pH values of groundwater samples ranged from 7.17 to 7.61, remaining within the permissible limits set by both national (Libyan standards, 2008) and international (WHO guidelines, 2003) water quality standards. Total Dissolved Solids (TDS) levels were generally within acceptable limits, except in Wells 1 and 2. The highest TDS concentration was recorded in Well 2 at 1837 mg/L, followed by 1147 mg/L in Well 1. Electrical Conductivity (EC) values exceeded the permissible limit of 1400 µS/cm in several wells. The highest EC value was recorded in Well 2 at 3675 µS/cm. The concentrations of cations (Mg²⁺, Ca²⁺, and Na⁺) were mostly within allowable limits. However, sodium levels exceeded the standards in some samples. Among anions, sulfate (SO₄²⁻) and chloride (Cl⁻) concentrations were notably elevated, especially in Wells 1 and 2, exceeding both national and international permissible limits. The total bacterial count per milliliter detected in the well water revealed the presence of bacteria in Wells 1 and 2. Notably, water from these wells was found to be unfit for drinking.
The Potential of Exploiting Renewable Energy in Libya Using the Strengths, Weaknesses, Opportunities, and Threats (SWOT) Analysis Model
The utilization of renewable energy constitutes a primary global strategy to overcome future energy challenges and secure a sustainable supply. Libya faces chronic power outages that adversely affect electricity consumers. Currently, electricity generation relies heavily on fossil fuels, contributing to significant environmental risks and climate change. Conversely, Libya possesses abundant renewable resources due to its strategic location within the "Sun Belt". This study aims to assess the feasibility of adopting renewable energy in Libya using the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis framework. The findings indicate that key strengths include Libya's strategic geographical location and its substantial solar and wind energy potential. However, significant weaknesses involve political and investment instability, continued fossil fuel subsidies, and administrative corruption. Consequently, the transition to renewables should be encouraged by leveraging opportunities for regional and international integration.
Simulation of BER Performance for BPSK and QPSK over SISO and SIMO (1×2, 1×4) Systems for Image Transmission under Flat Fading Channel Conditions
This study presents a detailed simulation-based analysis of Bit Error Rate (BER) performance for Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK) modulation schemes, focusing on their application in image transmission over wireless communication systems. The performance evaluation is conducted over both Single-Input Single-Output (SISO) and Single-Input Multiple-Output (SIMO) configurations, specifically 2 and 1×4 antenna systems, under the influence of flat fading channel conditions. The primary objective is to assess how the introduction of receive diversity via multiple antennas impacts the robustness and efficiency of data transmission. The study replicates realistic wireless channel conditions by employing a flat Rayleigh fading model, allowing for an accurate evaluation of modulation performance in fading environments. Simulation results indicate that SIMO systems, particularly those with higher diversity orders (e.g., 1×4), exhibit significantly improved BER performance compared to SISO systems. Both BPSK and QPSK show enhanced resilience to channel impairments when used with multiple receive antennas. While BPSK demonstrates superior error performance in severe fading conditions, QPSK offers higher spectral efficiency with a moderate trade-off in BER. Furthermore, the study examines the degradation of image quality as a function of channel fading severity, offering practical insights for the design of reliable wireless image transmission systems.
Bit Error Rate (BER), Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK), Single-Input Single-Output (SISO), Single-Input Multiple-Output (SIMO), Flat Fading Channel, Image Transmission
Design and Performance Comparison of Bowtie and Bowtie-Slot Antennas for 10-GHz 6G Wireless Applications
In this paper, a compact bowtie antenna is presented. The evaluation of this design, including simulation and performance optimization, was conducted for operation at 10 GHz to support 6G wireless communication systems. The proposed antenna was implemented on a low relative permittivity substrate Duroid with a thickness of 1.27 mm, selected for its low dielectric loss and stable performance at millimeter-wave frequencies. A modified bowtie geometry is employed to enhance impedance matching, extend operational bandwidth, and improve radiation efficiency in the 8–12 GHz spectrum. Full-wave electromagnetic simulations are conducted using ANSYS HFSS to validate the antenna’s return loss, gain, radiation pattern, and surface current distribution. Results demonstrate that the optimized bowtie structure achieves broadband operation with return loss below –10 dB around the 10 GHz resonance, making it a suitable candidate for compact 6G front-end devices, high-speed sensing, and short-range high-capacity links.
millimeter-wave; Bowtie antenna; high gain; Ansys HFSS
Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0
Adsorption of Acetic Acid onto Activated Carbon from Barley Husks, Eggshells, and Silica Gel: Isotherm and Thermodynamic Analysis
This study investigated the efficiency of three distinct low-cost adsorbents—activated carbon prepared from barley husks (ACB), eggshell powder (ESP), and commercial silica gel (SG)—for the removal of acetic acid from aqueous solutions. The research included optimizing the preparation conditions (e.g., carbonization temperature for ACB) and evaluating key operational parameters such as adsorbent dosage, contact time, initial acid concentration, and solution temperature. Experimental findings demonstrated that eggshell powder (ESP) exhibited the highest adsorption efficiency and capacity among the materials tested. The equilibrium contact time was consistently reached in approximately 30 minutes for all adsorbents. Kinetic analysis indicated that the adsorption data fit well with the Pseudo-Second-Order model. Thermodynamic analysis revealed that the process on ACB was endothermic (favorable at high temperatures), while it was exothermic (favorable at low temperatures) for both ESP and SG. Furthermore, the equilibrium data were successfully modeled using both the Langmuir and Freundlich isotherm models.
Adsorption, Acetic Acid, Activated Carbon, Barley Husks, Eggshell Powder, Silica Gel, Langmuir Isotherm, Freundlich Isotherm, Thermodynamics
Applications of matrices in big data analysis: Modeling user behavior in digital systems
This applied study aims to implement matrix-based techniques on real-world data to model user behavior in digital systems. The study was conducted on large-scale data extracted from an e-commerce platform comprising more than 100,000 users and 50,000 products. Non-negative Matrix Factorization (NMF) and similarity matrices were employed to analyze browsing and purchasing patterns. A predictive model based on principal component analysis of matrices was developed to forecast users’ future behavior. The applied results demonstrated a predictive accuracy of 87.3% in anticipating user preferences and 82.1% in forecasting purchasing behavior. Furthermore, a recommendation system based on matrix analysis was developed, achieving a 34% improvement in click-through rate compared to traditional systems. This study provides a practical and applicable framework for leveraging matrix techniques in big data analysis for organizations and enterprises.
Big Data, Matrices, User Behavior, Applied Study, Recommendation Systems
A Mathematical Analysis of the Lucas Sequence and its Relationship to Prime Number Properties and the Silver Ratio in Light of Number Theory
This study presents a mathematical analysis of the Lucas sequence and its relationship to prime number testing algorithms and the silver ratio within the framework of number theory. It aims to highlight the unique numerical properties of this sequence and explore the patterns inherent in its terms and their numerical convergence. The study employs a descriptive-analytical approach, drawing on theoretical sources and specialized textbooks. Computer programs such as Mathematica and MATLAB were used to analyze the behavior of the sequence's terms and observe their convergence towards the silver ratio. The procedures included numerical and graphical analysis of a sample of terms and linking the results to the principles of number theory to test for the emergence of prime numbers and extract patterns.The results showed that the Lucas sequence possesses precise numerical properties, and that some of its terms include prime numbers that can be utilized in developing prime-testing algorithms. The study also demonstrated that its terms gradually converge towards the silver ratio and exhibit recurring numerical patterns of mathematical and applied significance. The study recommended expanding future research on the Lucas sequence and linking it to deeper applications in cryptography and computer science, along with conducting comparative studies with similar sequences to enhance theoretical and applied understanding.
Lucas sequence, prime numbers, number theory, mathematical analysis of sequences, silver ratio
Deriving contour lines from digital elevation models using Geographic Information Systems (ArcGIS software)
Extracting contour lines from Digital Elevation Models (DEM) is considered one of the most important applications of topographic analysis in Geographic Information Systems (GIS), as these lines provide an accurate representation of the Earth's surface shape and characteristics. ArcGIS relies on advanced spatial analysis tools to convert digital elevation data into contour lines that represent different elevations in a graduated manner. Free Digital Elevation Model (DEM) elevation data obtained through satellite imagery is one of the most important sources of information about the nature of the terrain, as this data enables the derivation of contour lines (equal elevations), which are of great significance in many fields. Furthermore, most GIS software programs have the capability to deal with this data and generate contour maps. This research aims to utilize free SRTM Digital Elevation Model data and convert it into contour lines (equal vertical intervals/levels) with minimal cost, the fastest time, and a specified accuracy.
Isolation and Identification of Bacteria Causing UrinaryTract Infections and Their Antibiotic Sensitivity Pattern at Mohammad Almoghariaf Hospital in Ajdabiya
Urinary tract infections represent a significant health concern, leading to elevated morbidity rates in both men and women. The objective of the current study was to isolate and identify various bacterial agents responsible for UTIs. A total number amount to 200 urine samples from at suspected urinary tract infection in the age group 1 year to 105 years old were collected from patients at Mohammed Almogariaf hospital during August to October 2024. Bacterial isolates identified in this study included Staphylococcus aureus, Escherichia coli, Staphylococcus epidermidis, Klebsiella pneumoniae, Pseudomonas spp., and Streptococcus spp. The results demonstrated a higher prevalence of urinary tract infections (UTIs) among females, with an infection rate of 82.26%, compared to 18.43% in males. Furthermore, the data indicated that the incidence of UTIs was significantly greater in the female population. The study also assessed the antibiotic sensitivity profiles of the isolated bacterial strains, revealing variations in susceptibility to different antibiotics.
AI-Enhanced Semantic IoT Framework for Smart City Management Information Systems
Rapid advances in the Internet of Things (IoT) and artificial intelligence (AI) have transformed smart city management, but the resulting data deluge challenges traditional Management Information Systems (MIS). Conventional data-centric networks struggle with bandwidth and latency constraints, while smart city MIS requires real-time, context-aware insights. This paper proposes an integrated conceptual framework that combines semantic communications and AI-driven data analytics to enhance MIS in IoT-enabled smart cities. The framework uses semantic encoding at the IoT edge to transmit meaningful context rather than raw data, and employs AI models for decision support. We simulate a representative smart-city use case (traffic monitoring), implementing the proposed framework in an edge-cloud environment. Key contributions include the design of the semantic-AI MIS architecture and a replicable simulation scenario. In experiments, our approach improved decision accuracy by ~15% and reduced data transmission by ~20% compared to a baseline MIS using raw data. These results demonstrate that semantic-aware AI processing can significantly alleviate network load while enhancing analytical performance. The findings have practical implications for scalable smart city MIS, suggesting new directions for AI and communication co-design. Our study bridges gaps in current research by integrating semantic communication concepts with AI in organizational decision systems.
Transforming Human Resource Management with Artificial Intelligence in Recruitment, Performance, and Retention
This paper examines how artificial intelligence (AI) is reshaping human resource management (HRM) across recruitment, performance evaluation, and retention. Motivated by the trade-offs between hiring speed and quality and the high costs of employee turnover, this study reviews the latest evidence on AI’s impact. We trace the evolution of AI use in HR (screening, matching, interviews, onboarding, performance tracking, attrition prediction) and frame it through theories such as resource-based view, human capital, signaling, and socio-technical systems. A conceptual framework maps an end-to-end AI-enabled talent pipeline and links AI to outcomes (efficiency, hire quality, diversity, retention) while considering risks (fairness, privacy, explainability) and governance (human oversight). Using a systematic narrative review (2015-2025) and case examples (e.g. Unilever’s AI hiring, IBM’s attrition model), we synthesize results on time-to-hire, candidate funnels, quality-of-hire, and retention metrics. Key findings include evidence of faster hires and cost savings (Unilever: 90% time reduction, £1M savings) but also limitations in demonstrating improved long-term retention. Public sentiment is wary: many Americans oppose AI making final hiring decisions, though some see AI as more consistent. We analyze regulatory and ethical issues: “high-risk” classification under the EU AI Act (2024) imposes duties on data quality, bias audits, transparency; new U.S. rules (NYC LL144) require bias impact ratios; and live litigation (Workday class action) signals compliance risks (Reuters., 2024). An implementation guide recommends target use-cases, data/model pipelines, oversight processes, and ROI study designs aligned with NIST and ISO standards. We discuss trade-offs (speed vs fairness, predictiveness vs explainability), strategic implications for HR leaders, and identify research gaps in longitudinal outcomes, causal methods, and fairness optimization.
Hybrid Tidal-Wave Systems with Advanced Materials for Efficient and Durable Renewable Ocean Energy
Hybrid marine energy systems combine wave and tidal converters to increase capacity factor and smooth power output by exploiting complementary ocean resources. Advanced composite and corrosion-resistant materials are critical for durable platforms and structures in harsh marine environments. This paper presents a conceptual design scaffold for a semi-submersible hybrid wave-tidal platform. A broad literature review covers hybrid device concepts, modeling methods, materials, testing facilities, and research trends. Hybridization examples such as mechanical rectifier systems and combined-platform converters are discussed with diagrams. Composite materials (carbon/glass fiber-reinforced polymers) enable lightweight, stiff structures with high corrosion resistance. Corrosion protection using barrier coatings and cathodic systems is reviewed. A case study site (e.g. North Scotland) is characterized by example tide speeds (~1.0 m/s spring, ~0.5 m/s neap) and wave power (∼30 kW/m). Conceptual designs include component sizing tables and platform schematics (Figure 4.1) inspired by published designs. Modeling workflow (hydrodynamics → FSI → structure → fatigue → electrical) and test plan (scale model tests in a circular basin with controlled waves and currents) are outlined. FloWave tank (25 m diameter) is cited as a facility enabling combined wave-current testing. Example results from literature (TIWAG prototype and simulations) illustrate power output benefits. Economic analysis templates (CAPEX, OPEX, LCOE) are provided with literature cost estimates. This comprehensive design framework, fully referenced with figures and tables, supports future research on robust hybrid tidal-wave energy systems.
Global Trends in Electric Vehicle Charging Demand and Infrastructure Development
Over the past decade, electric vehicle (EV) adoption has surged globally, driving a sharp increase in charging infrastructure demand. This paper reviews the worldwide growth of EV markets and the corresponding expansion of charging networks. We analyze recent data on EV stocks and sales, and document how public and private chargers have proliferated. For example, global EV stocks rose from ~1.5 million in 2018 to over 15 million by 2024. Public charging points have more than doubled since 2022, exceeding 5 million by end-2024 (International Energy Agency., 2025). The study examines regional patterns - China hosts about 65% of chargers added since 2020, Europe and North America are expanding rapidly, and emerging markets like India and Latin America are accelerating growth. It also surveys technical and policy factors: fast-charging technology improvements, smart-grid integration, and government incentives. Challenges such as high deployment costs, grid impacts, and uneven charging access are discussed. Practical data sources and case studies (e.g., smart charging experiments) illustrate real-world demand management and usage patterns. We highlight that balancing charger rollout with EV uptake is critical; globally there are on average ~10 EVs per public charger, a ratio that varies widely by country. To meet future demand, coordinated planning, standards, and investment will be needed.
From Transition to Transformation: A Comparative Engineering Study of Hybrid and Electric Vehicles
This study compares hybrid (HEV/PHEV) and battery electric (BEV) vehicles using measured data. We aggregate chassis dynamometer tests of EVs and HEVs, large-scale field charging/usage records, and controlled battery aging experiments. Using statistical comparisons (e.g. median differences, regressions, nonparametric tests), we analyze energy use (Wh/mi, mpg), real-world PHEV electric-drive shares, charging-session delays, and battery capacity fade. Key findings include that EVs consume far less energy per mile than HEVs on test cycles, even after normalizing for mass. Real PHEV drivers use electric mode only ~40-50% of miles on average, well below EPA utility-factor assumptions. Charging sessions are dominated by handshaking overhead (e.g. cable checks ~7 s median). Battery aging data show capacity loss accelerates at high temperature and current, implying the need for robust thermal management. Our results inform powertrain design (e.g. maximize regenerative braking, right-size motors/batteries) and policy (e.g. set realistic PHEV credits, improve charging infrastructure reliability).
Fair and Transparent AI for Hiring: Evaluating Resume-Job Matching, Bias Mitigation, and Human-in-the-Loop Auditing
Automated hiring systems promise efficiency but risk perpetuating bias. We examine resume-job matching using embedding models and fairness audits. We reproduce a CareerBERT-style shared-embedding model trained on the ESCO taxonomy and a large job ads corpus. We compare it to TF-IDF and SBERT baselines, measuring retrieval utility (MRR, Recall@k) on an ESCO/EURES-derived dataset. We then apply IBM’s AIF360 fairness toolkit to evaluate demographic parity, equalized odds, and error-rate metrics across protected groups. We experiment with pre-processing (Reweighing), in-processing (Adversarial Debiasing), and post-processing (Reject Option) interventions. In simulation, we find typical trade-offs: e.g., reweighing can reduce selection-rate disparities by ~10-20 pts at the cost of a few percentage points drop in Recall@10, while adversarial training maintains utility but only partially closes gap. We implement a prototype HR auditing dashboard with group metrics and example rationales. In a human evaluation, auditors preferred the fair-re-ranked shortlist in X% of cases (p<0.05) and reported higher perceived equity. All code, data splits, and figures are released for reproducibility.