Quantum Journal of Engineering, Science and Technology
Quantum Journal of Engineering, Science and Technology (QJOEST) is a multi-disciplinary with double-blind peer-reviewed journal publishes across the entire field, to advance our knowledge of our nature world and its various intersections with society. The journal publishes research articles, review articles, short communications, case studies and reports in Engineering, Science and Technology includes engineering, computer sciences, architecture and design, agricultural sciences, biological sciences, chemistry, physics, earth sciences, environmental science, life sciences, mathematics and statistics, as well as sport sciences. Abstract and Indexing: Quantum Journal of Engineering, Science and Technology (QJOEST) are abstracted and indexing in Bielefeld Academic Search Engine (BASE); Google Scholar; Malaysian Journal (MyJurnal); Malaysian Citation Index (MyCite); Neliti; and many more.
IMPACT OF AUGMENTED REALITY AND ICT ON IMPROVEMENT OF TEACHING PRACTICES: AN EXPERIMENTAL STUDY
In a rapidly evolving educational landscape shaped by digital transformation, leveraging augmented reality (AR) within the framework of modern ICT offers a promising avenue for revitalizing traditional pedagogical approaches. This study investigates the impact of AR-enhanced instructional modules on teaching practices and student learning outcomes in a real-world educational setting. Through a quasi-experimental design, two groups of students follow the same curriculum: one receives conventional lessons, while the other experiences AR-augmented content delivered via ICT tools (tablets or smartphones). Quantitative measures of academic performance are complemented by qualitative data capturing student motivation, engagement, and perception of learning. Results reveal that integrating augmented reality with ICT significantly improves both comprehension and retention of complex concepts, while also fostering heightened student enthusiasm and active participation. Teachers involved report greater flexibility in lesson delivery and enhanced interaction dynamics. These findings suggest that AR-based interventions when thoughtfully designed and supported by adequate ICT infrastructure can meaningfully transform teaching practices, making learning more immersive, interactive, and effective. The study concludes with practical recommendations for educators and policymakers aiming to adopt AR-driven pedagogies at scale.
Copyright (c) 2025 FRIDHI ADEL, LARIBI RYM, KOUKI RAHIM, BOUAJILA AHMED https://creativecommons.org/licenses/by/4.0
THE DIGITAL SENTINEL: REVIEW ON FO, RS AND AI FOR PROACTIVE FOOD-WATER NEXUS RISK
The necessity for sustainable food systems dictates a critical move towards proactive, evidence-based Food Safety and Risk Assessment, particularly in the face of escalating environmental threats. The global proliferation of Harmful Algal Blooms (HABs) poses a major, dynamic risk to water security, which rapidly translates into food contamination. Traditional, reactive testing methods are inadequate for managing this emerging hazard. This Perspective article proposes a unified "Digital Sentinel" framework that transforms environmental surveillance into predictive supply chain alerts. The Sentinel operates by fusing two complementary data streams. First, macro-scale environmental monitoring, accomplished through Remote Sensing platforms, provides continuous geospatial tracking and predictive modeling of bloom intensity. Second, this information is validated by micro-scale molecular insights, utilizing Algal Omics technologies (Genomics, Transcriptomics) for high-throughput identification of toxic species and quantification of toxin-producing genes. Hence, the integration of this heterogeneous data is achieved using advanced Big Data analytics and Explainable Artificial Intelligence (XAI). This intelligent layer generates a verifiable, proactive risk score that informs evidence-based regulatory decisions. Thus, the Digital Sentinel strengthens Food Safety, certifies product origin for Food Authenticity, and fully embodies the principles of Foodomics, Digitalization, and the indispensable One Health Model. Hence, the approach is promising and aligns with the direction of digital transformation in food safety and environmental health.
Copyright (c) 2025 MOSTAFA ESSAM EISSA https://creativecommons.org/licenses/by/4.0
ADVANCED MULTIMODAL AI FRAMEWORK FOR ENHANCED DIABETIC RETINOPATHY DIAGNOSIS AND SEVERITY CLASSIFICATION
Diabetic Retinopathy (DR) continues to be a primary cause of visual impairment and blindness among individuals with diabetes globally, affecting millions and underscoring the urgent need for robust, scalable screening mechanisms. This extended study presents an advanced multimodal deep learning framework that synergistically combines fundus photography and Optical Coherence Tomography (OCT) imaging modalities to achieve superior detection and severity grading of DR. By employing a hybrid architecture that integrates Convolutional Neural Networks (CNNs) for spatial feature extraction and Transformers for capturing long-range dependencies in sequential data, the proposed model leverages attention mechanisms to fuse multimodal inputs effectively. Evaluated on benchmark datasets such as EyePACS, IDRiD, and Duke OCT, the framework demonstrates exceptional performance metrics: 98% accuracy, 96% sensitivity, 97% specificity, and an Area Under the Curve (AUC) of 0.99 for binary classification tasks, surpassing existing state-of-the-art approaches. To enhance interpretability, the model incorporates Explainable AI (XAI) techniques, including Gradient-weighted Class Activation Mapping (Grad-CAM), for precise lesion localization. Class imbalance issues are mitigated through sophisticated data augmentation strategies, including Synthetic Minority Over-sampling Technique (SMOTE) and generative adversarial networks (GANs)-based synthesis. This work provides detailed mathematical derivations for custom loss functions, evaluation metrics, and optimization algorithms, accompanied by comprehensive visualizations such as confusion matrices, Receiver Operating Characteristic (ROC) curves, precision-recall curves, and training convergence plots. From a Computer Science Engineering (CSE) perspective, the framework emphasizes computational efficiency, enabling real-time inference on edge devices and potential deployment in resource-constrained environments, thereby reducing healthcare costs and improving accessibility in underserved regions. This extension expands on the original contributions by including in-depth ablation studies, comparative analyses with recent 2025 models, ethical considerations, and deployment strategies.
Copyright (c) 2025 VIRENDRA KUMAR TIWARI, JITENDRA AGRAWAL, SANJAY BAJPAI, KAVITA KANATHEY https://creativecommons.org/licenses/by/4.0
FORENSIC ANALYSIS OF TEMPORAL INCONSISTENCIES AND METADATA DISCREPANCIES IN CCTV FOOTAGE: A CASE STUDY
The forensic reliability of closed-circuit television (CCTV) footage is central to contemporary criminal investigations; yet temporal irregularities in recorded video often generate disputes regarding authenticity and alleged tampering. This case study critically examines temporal inconsistencies and metadata discrepancies observed in CCTV footage submitted for forensic evaluation, where the primary investigative question concerned potential digital manipulation. Two video clips captured from different camera angles (Cam3 and Cam5) were analysed using Dahua Smart Player Version 4.0.0 through a systematic methodology combining real-time playback, frame-by-frame examination, stopwatch-based time verification, cross-angle synchronization assessment, and metadata analysis. The findings reveal measurable discrepancies between on-screen time progression, real-time measurement, and metadata-reported durations, alongside fluctuating synchronization between camera feeds. However, no visual discontinuities, frame deletions, insertions, or compression artefacts indicative of deliberate tampering were detected. Instead, the anomalies are attributable to technical factors inherent to CCTV systems, including variable bit rate compression, frame rate fluctuations, system clock desynchronization, and recording load constraints. Critically, this study demonstrates that temporal drift and metadata-playback mismatches can arise even in authentic and continuous footage, challenging simplistic assumptions that equate timing irregularities with manipulation. The findings underscore the necessity for forensic practitioners to adopt a holistic, technically informed interpretive framework that integrates system architecture, encoding behaviour, and metadata structure before reaching conclusions on video authenticity. By distinguishing system-induced artefacts from intentional interference, this study contributes to improving the evidentiary assessment of CCTV footage and mitigating the risk of wrongful exclusion or misinterpretation of digital video evidence in judicial proceedings.
Copyright (c) 2025 PRAKHAR PRASOON, MAHESWARI, MUHAMMED ARSHAD, ASHISH KUMAR YADAV https://creativecommons.org/licenses/by/4.0
SILICONE-COATED ALUMINA HOLLOW FIBER MEMBRANES FOR SUSTAINABLE MICROPLASTIC SEPERATION IN WATER SYSTEM
Microplastic (MP) pollution represents a new wave of some of the most devastating environmental stressors, with such an impact on aquatic environment degradation, food chain contamination, and human health. Conventional filtration techniques are ineffective toward smaller MPs; hence there is a dire need for advanced methods of filtration. The present study fabricates and evaluates silicone-coated alumina hollow fiber membranes (AHFMs) by curing temperature variation, membrane configuration variation, and flow rate conditions variation. Contact angle analyses found that the curing at 60°C optimized rapid water interaction and at 70°C gave stable hydrophilicity which can be used for long-term applications. Multi-membrane configurations greatly improve water throughput validating surface area expansion that does not compromise MP separation. Flow rate variations influenced how much volume was collected but did not influence separation efficiency since all tested modules demonstrated complete removal of MPs. This puts a seal on the noticeable increase in durability and antifouling performance of AHFMs with silicone coatings, hence their ability to work perfectly well under diverse hydraulic conditions. The results prove that productivity is actually a function of operative conditions while selectivity lies within the material property as engineered. That places silicone-coated AHFMs as an accessible technology toward community-based purification systems up to industrial wastewater treatment plants. Apart from bringing membrane science one step closer, this study also plays its share in the Sustainable Development Goal 6 by offering an upbeat, resilient, and sustainable technology for mitigating global water contamination by microplastics.
Copyright (c) 2025 NORFAZLIANA ABDULLAH, MUHAMMAD AMMAR FARHAN HASBOLLAH, ANG KEAN HUA https://creativecommons.org/licenses/by/4.0
FRUIT CROP DISEASE CLASSIFICATION USING QUANTUM MACHINE LEARNING: A PILOT STUDY
Crop losses are often caused by factors like plant diseases, nematode attacks, and nutrient deficiencies. The problem is that many of these stresses look alike on the leaves, which makes early detection difficult in the field. In this pilot study, we built and tested part of an AI system that uses leaf photos together with simple soil information to spot crop stress early. Our approach combines MobileNetV2 with a quantum-inspired feature layer, creating a hybrid deep learning model. Trained on about 92379 labeled leaf images, the model was able to tell apart healthy leaves and nematode-infested leaves with strong accuracy. In addition to classification, the system also estimates chlorophyll and key nutrient levels (N, P, K) directly from RGB leaf images, while soil pH values are added manually as an extra input. Looking ahead, we plan to extend this framework with hyperspectral imaging and richer soil data to give more complete insights. The ultimate goal is to create an affordable and scalable decision-support tool that guides farmers with simple “step–check–action” advice to protect yields.
Copyright (c) 2025 ABHISHEK CHANDRAKANT NIKAM, RAHUL BORATE, MASIRA KULKARNI, AAYUSH PATIL, SADAF SHAIKH https://creativecommons.org/licenses/by/4.0
DEVELOPMENT OF ALUMINA HOLLOW FIBER MEMBRANE MODULES FOR EFFECTIVE OIL/WATER SEPARATION
This study critically engages with the context of increasing industrial and urban wastewater challenges where an effective oil-water separation process is considered. In most cases, the traditional gravity separator and centrifuge fail to isolate stable small droplets of oil from water in emulsified form. Alumina hollow fiber membrane modules that this study has undertaken fabrication efforts toward are proposed as one more step further to solve this problem. The hydrophobicity enhanced system shows all promises towards effectively carrying out the separation of oil from water in emulsions. Different membrane configurations tried possible relationships that this work presents between changing the number of membranes and efficiency in separation. Increasing surface area, i.e., an increasing number of fibers, allows more oil recovery but at a cost since fouling will tremendously take place. Even though the membrane could achieve very high separation efficiency, challenges related to operation, especially fouling at high concentrations of oil and the effects due to different flow rates have to be solved when applied on an industrial scale. This brings out the study's view that getting sustainable, cheap, and efficient ways of carrying out the oil-water separation process necessitates the optimization of membrane configurations and operating conditions.
Copyright (c) 2025 NORFAZLIANA ABDULLAH, HASHVININISHA PARAMASIVAM, ANG KEAN HUA https://creativecommons.org/licenses/by/4.0
SENSITIVITY OF SEABED MORPHOLOGY TO HYDRODYNAMIC AND SEDIMENT TRANSPORT PARAMETERS IN TIDAL SYSTEMS
Sediment transport and seabed evolution are key processes influencing the morphology and stability of coastal and estuarine systems. This study uses a one-dimensional (1D) coupled hydrodynamic–sediment transport model to simulate shallow water flow and sediment dynamics in the Kuala Terengganu region. The model integrates the Saint-Venant shallow water equations with the Exner equation for bed evolution and the advection–diffusion equation for suspended sediment concentration. Numerical implementation using the finite volume method ensures mass conservation and numerical stability, allowing accurate representation of flow–sediment feedback. The objectives are: (1) to simulate the temporal evolution of seabed morphology and quantify long-term bed elevation changes; (2) to evaluate the effects of hydrodynamic parameters, particularly tidal range and bed friction coefficient, on sediment entrainment, deposition, and erosion; and (3) to assess the influence of sediment transport parameters, especially the Grass coefficient, on seabed stability and erosion–deposition dynamics. Results show a non-linear decline in bed elevation with a 38% reduction over three years, indicating rapid early sediment mobility followed by stabilization. Increasing tidal range enhances sediment removal, while friction and Grass coefficients govern the transition between erosion and deposition. The findings provide insights for predicting coastal morphological change and improving sediment management.
Copyright (c) 2025 MOHD AZLAN MUSA, MOHAMMAD FADHLI AHMAD, SUNNY GOH ENG GIAP https://creativecommons.org/licenses/by/4.0
BRIDGING THE SKILL GAP: AN INDUSTRY-ACADEMIA TRAINING FOR CIVIL ENGINEERING STUDENTS IN MALAYSIAN POLYTECHNICS
Malaysian Polytechnics, as pivotal Technical and Vocational Education and Training (TVET) institutions, are mandated to produce job-ready graduates for the construction industry. However, a significant misalignment persists between the project management (PM) competencies taught in the Diploma of Civil Engineering and the practical skills demanded by industry. This study investigates this gap by identifying critical PM competencies from an industry perspective, analyzing the current polytechnic curriculum, and developing a strategic framework for alignment. A sequential explanatory mixed-methods design was employed, comprising an industry survey (n=127), a qualitative content analysis of PM syllabi from 15 polytechnics, and a gap analysis. Industry results prioritized practical, site-based competencies: Site Supervision & Safety Management (M=4.85), Quality Control & Assurance (M=4.80), and Scheduling Software Proficiency (M=4.72). In contrast, curriculum analysis revealed a predominant theoretical focus, with insufficient coverage of digital tools (e.g., BIM in 7% of syllabi) and localized standards. The gap analysis was statistically significant (p<0.001) for the top industry-ranked competencies. The study confirms a substantial theory-practice divide and proposes the Polytechnic Industry-Integrated Project Management (PII-PM) Framework, a five-pillar model emphasizing contextualized content, digital skills integration, active learning pedagogy, structured industry collaboration, and a continuous feedback mechanism. This framework provides an actionable roadmap for polytechnics to enhance graduate employability and contribute directly to Malaysia's infrastructure goals.
Copyright (c) 2025 SALIZAWATI KAMARUZZAMAN https://creativecommons.org/licenses/by/4.0
CFD STUDY ON WAVE TRANSMISSION OF SUBMERGED HEMISPHERICAL SHAPED ARTIFICIAL REEF (HASR) BREAKWATER
Coastal erosion is the recession of shorelines and loss of land caused by waves, currents, and wind. Hemispherical Shaped Artificial Reefs (HSAR) can act as submerged breakwaters to mitigate erosion, offering structural protection while enhancing aquatic habitats and biodiversity. Designed to provide shelter for marine life, HSARs combine engineering with ecological benefits. Previous experimental studies on wave transmission over submerged breakwaters were conducted at the Hydraulic and River Engineering Laboratory of Bangladesh University of Engineering and Technology. This study demonstrates wave transmission across HSAR breakwaters using the Volume of Fluid (VOF) method with the Reynolds-Averaged Navier–Stokes (RANS) equations in the FLOW-3D numerical suite. The reefs were modeled using RHINOCEROS 5.0 software. The main objective is to determine wave transmission through numerical simulation. First, the model was validated against experimental results for submerged breakwaters. Further simulations assessed transmission with varying HSAR structural heights and designs. The findings showed close agreement between simulations and experiments, with percentage errors ranging from 4.1% to 16.7%. Results emphasize the significance of structural height in reducing the wave transmission coefficient, K_t. HSARs outperformed thalame breakwaters in transmission reduction, proving beneficial for coastal protection, environmental sustainability, and aquatic life.
Copyright (c) 2025 MOHAMMAD FADHLI AHMAD, MOHD AZLAN MUSA, MUHAMMAD FARIS ROSLAN, MUHAMMAD YUSUF RUSLI, SUNNY GOH ENG GIAP, HANHAN MAULANA, LAMECK FIWA https://creativecommons.org/licenses/by/4.0
CHARCOAL PRODUCTION, ENVIRONMENTAL DEGRADATION AND RURAL-LIVELIHOOD: CRITICAL EVIDENCE FROM COMMUNITY PERCEPTION IN ADAMAWA STATE
Environmental protection in Nigeria and indeed most developing nations has never been a top priority due to the fact that economic losses arisen from environmental degredation especially as a result of charcoal production often occur long after the economic benefits have been realized. Nigeria is among the largest producers and consumers of charcoal worldwide. This has resulted in continued unsustainable harvest of the few remaining trees for charcoal production in Adamawa State, that has led to devastating environmental impacts on the livelihood of the rural poor where most of the inhabitants of these communities relied on this natural resource. Multi stage and purposive sampling techniques were employed in interviewing 172 respondents for this study. Data obtained were analyzed using descriptive and inferential statistics. Results on socio-economic characteristics revealed that majority (62.8%) of the respondents involved in exploiting the trees for charcoal production were males with a mean age of 33 years. Most respondents were married (63.4%) and having a mean household size of 7 individuals and mean annual household income was ₦216,570. Tree species such as Prosopis africana, Anogeisus leiocarpus and Ziziphus mauritiana were frequently exploited having a mean value of 4.7 and 4.6 respectively. The chi-square analysis revealed a significant relationship (P<0.05) between the perceived impacts of charcoal production and gender, age, educational level while marital status, household size, occupation and income of the respondents are not significant (P>0.05) in the study area. Charcoal production has become a lucrative business and major source of income to support rural livelihood.
Copyright (c) 2025 ABDULMOROOF ADEDOTUN, MORUFF SAKA, LUCKY NNYAM, ALEXANDER LINDO DOMINIC https://creativecommons.org/licenses/by/4.0
INVESTIGATION ON LEACHATE TRANSPORT ON GROUNDWATER CONTAMINATION USING VERTICAL ELECTRICAL SOUNDING (VES)
The rapid increase in population has heightened concerns regarding waste disposal, with open dumpsites serving as the primary method of waste management in many areas. This study investigates the geo-electric characteristics and groundwater quality of boreholes situated near an open dumpsite in Ogale Community, Eleme Local Government, Rivers State, Nigeria. Vertical Electrical Sounding (VES) using the Schlumberger configuration was employed to examine the effects of leachate on groundwater contamination, subsurface aquifer protective capacity, and lithological corrosivity. Borehole water samples collected from varying depths (50m, 100m, 150m) and a control location (2000m) revealed that pH, temperature, and dissolved oxygen (DO) exceeded the permissible limits set by the World Health Organization (WHO) and the Nigerian Standard for Drinking Water Quality (NSDWQ). Results indicated high chloride concentrations and microbial contamination, particularly in boreholes closest to the dumpsite. The regression model (R² values of 0.9743, 0.9962, and 0.9981) demonstrated significant metal corrosivity at varying depths. The Water Quality Index (WQI) values (67.7, 67.6, and 68.1) classified the groundwater as poor and unsuitable for drinking. VES analysis confirmed weak to moderate aquifer protective capacity, correlating with increased acidity and microbial presence. Consequently, metal pipes prone to corrosion are unsuitable for water conveyance, and plastic pipes are recommended. The study underscores the necessity for improved waste management practices, including landfill engineering, solid waste recycling, and enhanced environmental sanitation to mitigate groundwater contamination risks.
Copyright (c) 2025 CYPRIAN NDAMZI TOM, JOSEPH EDET, EUNICE NNETE GAM https://creativecommons.org/licenses/by/4.0
Electricity conversion monitoring machine is an electronic device that video display units load voltage and cutting-edge or packs with numerous parameters. But, on the market could be very steeply-priced and now not appropriate for low-price embedded structures. Because the Arduino Uno is widely used for low-price microcontroller boards, smooth programming environment, and open-supply systems for building digital tasks, consequently, this take a look at makes a speciality of Arduino Uno primarily based power conversion monitoring machine with clever automation. This system consists of modern and voltage sensors to reveal and use the PIR sensor to gain the automation, an Arduino Uno microcontroller with wifi module and a liquid crystal show (liquid crystal display) to view the monitored analyzing.To expand this gadget, there are 3 targets to be completed.the connection between enter and output of the sensors must be derived mathematically. The mathematical expression acquired may be demonstrated by means of connecting and disconnecting the circuit with load and tracking the value of output sensors. Then, a whole prototype of the energy conversion monitoring system changed into evolved via connecting the lcd, current and voltage sensors to the Arduino Uno microcontroller and reference to PIR sensor to automate the unit with relay. Think view application is used to tracking the power consumption of the burden this app is open source and by means of soliciting for the personal channel the statistics can included and best seen to legal personal most effective.
Copyright (c) 2025 RADHIKA, IMMANUVEL, DEVARAJ SOMASUNDAR https://creativecommons.org/licenses/by/4.0
PROSPECT IDENTIFICATION USING SEISMIC ATTRIBUTES FOR AN OFFSHORE NIGER DELTA BASIN X FIELD
The offshore Niger Delta Basin "X" field presents significant opportunities for hydrocarbon prospecting; however, effective reservoir characterization remains challenging. This study addresses this challenge by employing a robust combination of seismic attributes, including amplitude, Root Mean Square (RMS) amplitude, variance edge, phase, frequency, and reflector continuity. Utilizing advanced seismic data processing and visualization techniques, the research aims to accurately map structural features, faults, horizons, and potential hydrocarbon traps within the "X" field. The integrated seismic attribute approach enables precise identification of prospective zones by enhancing fault delineation and improving reservoir characterization. The application of the structural smooth attribute significantly increases seismic resolution, allowing for the clear visualization of fault lines and reservoir boundaries, while the variance edge attribute proves instrumental in delineating fault trends and identifying potential trapping mechanisms. Additionally, the construction of 3D fault models using amplitude attributes enhances the interpretation of subsurface features, offering critical insights for targeted well placement. The results reveal two principal faults that align with the reservoir zones, indicating promising areas for detailed hydrocarbon exploration. The findings demonstrate that deploying a multi-attribute seismic analysis provides a cost-effective and reliable method for improving exploration accuracy, optimizing resource allocation, and supporting decision-making in offshore hydrocarbon development.
Copyright (c) 2025 OKECHUKWU FRANK ADIZUA, NNABUIKE GODSPOWER UGWU https://creativecommons.org/licenses/by/4.0
COWPEA HAY AS A PARTIAL SUBSTITUTE FOR CONCENTRATE: EFFECTS ON MILK YIELD AND COMPOSITION
The study was carried out in Yabello Pastoral and Dry Land Agricultural Research Center to investigate the effect of replacement of cowpea (Vigna Unguiculata) for concentrate mix on milk yield and composition in lactating Borana cows fed Rhodes grass hay as a basal diet. Four lactating Borana cows of similar milk yield, body weight and stage of lactation were arranged in 4 x 4 Latin square design. The treatments included offering Rhodes grass hay a basal diet ad libitum with different proportions of concentrate mix and cowpea hay. T1= 100% concentrate mix and 0% cowpea hay (control), T2= 65 % concentrate mix and 20% cowpea hay, T3= 65% concentrate mix and 35% cowpea hay and T4= 50% concentrate mix and 50% cowpea hay. There were no significant differences (P>0.05) in dry matter and nutrient intakes among treatment groups, while milk yield was significantly different (P<0.05) among treatments. The overall mean of daily milk yield was 4.05 kg/day. Cows that were receiving 100% concentrate mix (T1) produced the highest milk yield (4.18 kg/day) followed by cows receiving the diet in which 50% of the concentrate mix was replaced by cowpea hay (T4).Except milk yield, cowpea hay can substitute up to 50% of the concentrate mix without adversely affecting feed intake, nutrient intake and milk composition of lactating Borana cows fed Rhodes grass hay as basal diet. Therefore, to improve their milk production, smallholder farmers can use cowpea hay 50% to replace the concentrate mix in feeding their cows on poor pasture, especially during dry seasons.
Copyright (c) 2025 BESHIR HUSSIEN, BIRHANU BEKELE, ADEM KUMBE, ANAF ONETA https://creativecommons.org/licenses/by/4.0
ENHANCING MICROSTRIP PATCH ANTENNA PERFORMANCE THROUGH GENETIC ALGORITHM AND ANFIS OPTIMIZATION
Microstrip patch antennas play an important role in modern wireless communication systems due to their small size, compactness, lightweight, and easy integration into electronic circuits. These types of antennas are widely used in various applications, such as mobile phones, Wi-Fi routers, satellite communications internal systems and radar systems. This paper provides a detailed research study on the improvement and optimization of the measurement of the Aperture Coupled Microstrip Patch Antenna (ACMPA) utilizing a Genetic Algorithm (GA) as well as an Adaptive Neuro-Fuzzy Inference System (ANFIS). The goal is to enhance the total efficiency of the antenna by achieving far better return loss and high directivity coupled with a reduced Voltage Standing Wave Ratio (VSWR). The recommended method includes the usage of GA within the CST software application together with ANFIS within the MATLAB software application to enhance the ACMPA measurements for the procedure at 7.5 GHz. The outcomes show the performance of the recommended antenna measurements in contrast with substitute information in the CST program, verifying the precision as well as the effectiveness of the optimization procedure. This research study offers beneficial insights into the application of innovative optimization methods for the style coupled with the improvement of microstrip patch antennas in contemporary cordless interaction systems.
Copyright (c) 2025 RANA RAAD SHAKER, NOOR RAAD SAADALLAH, SALAH ABDULGHANI ALABADY https://creativecommons.org/licenses/by/4.0
COPPER AND SULFUR CO-DOPED ZNO NANOPARTICLES FOR EFFICIENT SOLAR PHOTOCATALYTIC DEGRADATION OF METHYL ORANGE
In the present study pure ZnO nanoparticles were prepared using a co-precipitation technique. As-prepared ZnO, was used to prepare Cu-doped ZnO, S-doped ZnO, and Cu & S co-doped ZnO nanostructures by simple hydrothermal method. The synthesized materials were characterized employing XRD, FTIR, and UV-visible spectroscopic techniques. The crystallite particle size of pure ZnO (45.7 nm), was highest among the synthesized powders followed by Cu-doped ZnO (43.29 nm), S-doped ZnO (43.4 nm), and Cu & S co-co-doped ZnO (43.19 nm). The UV-visible absorption spectra of aqueous dispersion of synthesized powders revealed that doping Cu and S in ZnO, both contributed synergistically to lowering of band gap energy from 3.27 eV to 2.35 eV. The photocatalytic efficacies of as-synthesized powders under solar irradiation were determined in terms of methyl orange degradation, as a probe. The observed highest photocatalytic degradation (85 %) of 25 mg L-1 dye in aqueous solution within 60 minutes using Cu & S co-doped ZnO load 1.5 gL-1 can be attributed to the lower rate of photo-generated charge carriers’ recombination as well as lowering of band gap energy enabling absorption of more photons in the visible range of solar radiation. Considering the high photocatalytic efficiency of newly synthesized Cu and S co-doped ZnO powder, the same may be recommended for an effective treatment of methyl orange-contaminated wastewater.
Copyright (c) 2025 MENBERU GIDEY, TESFAY WELDERFAEL, OM PRAKASH YADAV https://creativecommons.org/licenses/by/4.0
FORECASTING INDUSTRIAL PH LEVELS: COMPARATIVE STUDY OF SARIMA, REGRESSION TREES AND CONTROL CHART DIAGNOSTICS
Implementation of Statistical Process Control (SPC) techniques in food and beverage industry are crucial to deliver consumable product that meets customer expectations. This study investigated industrial pH forecasting and process stability in a syrup manufacturing facility. We analyzed 1,247 pH observations with three objectives: (1) Quantify instability via control charts, (2) Model pH dynamics using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Classification And Regression Trees (CART), and (3) Develop diagnostic frameworks for unstable processes. Methodologically, Exponentially Weighted Moving Average (EWMA) charts assessed stability; Box-Cox transformed SARIMA (λ=2) with seasonal differencing was used for forecasting; CART identified variable importance. Control charts revealed profound instability: 83.3% of points violated 3σ limits; run tests significant (p<0.001). For SARIMA, (1,0,1)(0,1,1)₁₂ achieved significant parameters (p<0.0001) with improved residual diagnostics versus non-seasonal ARIMA, though minor autocorrelation remained at lag 12 (p=0.003). CART explained training R²=18.86% and test R²=17.93% of pH variation, identifying filling weight and sodium benzoate as key predictors. Crucially, this study demonstrates that forecasting retains diagnostic utility even in unstable environments: SARIMA residuals provide seasonal fingerprints of assignable causes, while CART thresholds guide intervention priorities. SARIMA(1,0,1)(0,1,1)₁₂ demonstrated superior residual properties: eliminated back forecast warnings (present in ARIMA), reduced autocorrelation at lag 24 (p=0.017 vs 0.040), and explicitly modeled 12-period seasonality. While process instability persists, SARIMA provides diagnostic fingerprints of assignable causes through seasonal parameters (SMA₁₂=0.9846, T=513.12) and residual patterns. We conclude that SARIMA offers enhanced short-term forecasting capability, but process intervention remains essential for reliability. The study advocates for integrated instability-informed forecasting combining SARIMA diagnostics, real-time control charts, and expanded sensor deployment.
ENHANCING CYBERSECURITY OF SMART CITY WATER DISTRIBUTION SYSTEMS USING BLOCKCHAIN AND PBFT CONSENSUS MECHANISM
This paper investigates cybersecurity attack models and defense strategies for water distribution systems (WDS) in smart city environments. As water infrastructure becomes increasingly digitized, it faces sophisticated cyber threats that could compromise system integrity and operational reliability. This study presents a systematic analysis of two prevalent attack vectors Denial of Service (DoS) and Man in the Middle (MITM) attacks and evaluates blockchain based defense mechanisms against these threats. Through experimental simulation using the C-town WDS model with 953 timestamp data points, we assess the vulnerability of water systems and the effectiveness of six consensus mechanisms: Proof of Work (PoW), Proof of Trust (PoT), Proof of Authority (PoA), Proof of Vote (PoV), Proof of Authentication (PoAuth), and Practical Byzantine Fault Tolerance (PBFT). The research quantifies attack impacts and demonstrates the superior resilience of PBFT, which achieved an 82.5% defense rate against DoS attacks and an 82.7% defense rate against MITM attacks, significantly outperforming alternative approaches. Furthermore, PBFT exhibited exceptional recovery capabilities with 71.1% recovery after DoS attacks and 89.3% recovery following MITM attacks. These findings provide valuable insights for implementing robust security frameworks that can maintain water system integrity even under sophisticated attack conditions.
Copyright (c) 2025 AMINA ALAJWARY, FIRAS ALSHARBATY https://creativecommons.org/licenses/by/4.0
ENVIRONMENTAL SUSTAINABILITY OF RURAL WASTEWATER-TREATMENT PLANTS VIA LIFE-CYCLE ASSESSMENT WITH EMPHASIS ON CONSTRUCTED WETLANDS
Sustainability plays a pivotal role in environmental engineering and management. Life Cycle Assessment (LCA) serves as a valuable methodology for evaluating the environmental footprint of products, services, or processes throughout their life cycles. LCA offers a quantitative approach and aids in identifying strategies that address environmental challenges rather than merely transferring them. It proves particularly relevant for assessing the sustainability and design of wastewater treatment systems. This study employs the LCA framework to compare various wastewater treatment options suitable for small, decentralized areas. Specifically, the focus lies on evaluating the constructed wetland (CW) within the wastewater treatment (WWT) system across its three main phases: construction, operation, and decommissioning. The investigation examines the impact on diverse environmental categories such as abiotic depletion, global warming, ozone layer depletion, human toxicity, freshwater aquatic ecotoxicity, marine aquatic ecotoxicity, terrestrial ecotoxicity, photochemical oxidation, acidification, and eutrophication, adhering to LCA standards. Findings reveal that natural wastewater treatment methods exhibit lower environmental footprints due to their reduced resource requirements. However, the construction phase of the CW emerges as the primary contributor to most impact categories, accounting for 89% of the overall impact. Notably, marine aquatic ecotoxicity ranks as the most significant impact category, while ozone layer depletion and photochemical oxidation potentials exhibit minimal values.
Copyright (c) 2025 ABDUL WAHED AHMADI, NILGUN BALKAYA https://creativecommons.org/licenses/by/4.0
ADVANCING QUANTUM DOT-SENSITIZED SOLAR CELLS: TRANSITION METAL-SULFIDE-BASED COUNTER ELECTRODES FOR HIGH-EFFICIENCY AND STABLE PHOTOVOLTAICS
Quantum dot-sensitized solar cells (QDSSCs) represent a leading-edge innovation within third-generation photovoltaic systems, owing to the unique light-harvesting capabilities of quantum dots (QDs), including multiple exciton generation, tunable band gaps, and high absorption coefficients. Despite their potential for achieving power conversion efficiencies (PCE) beyond those of conventional solar technologies, challenges remain; particularly in the stability and performance of counter electrodes (CEs). Platinum (Pt), while efficient, suffers from catalytic degradation in polysulfide electrolytes, limiting its suitability for QDSSC applications. This review explores the use of transition metal sulfides (TMS), such as NiS, CoS, Cu₂S, and PbS, as alternative CE materials due to their abundance, low cost, and promising electrocatalytic properties. Emphasis is placed on their compatibility with polysulfide electrolytes, structural stability, and ability to enhance interfacial charge transfer, which directly impacts overall device performance. The paper also discusses the synthesis techniques employed, chemical bath deposition and successive ionic layer adsorption and reaction, and how they influence the morphology, adhesion, and efficiency of the CEs. Among the materials reviewed, nickel sulfide-based electrodes stand out due to their low charge transfer resistance, high Jsc values, and excellent long-term operational stability. Composite materials such as NiS/PbS and Cu₂S/graphene hybrids show synergistic effects, enhancing both catalytic performance and mechanical durability. By identifying and evaluating viable alternatives to noble metals, this study underscores the critical role of CE materials in advancing QDSSC technology toward scalable, efficient, and cost-effective solar energy solutions.
Quantum Dot-Sensitized Solar Cells (QDSSCs)
Copyright (c) 2025 LAYLA HAYTHOOR KHARBOOT, KOLEOLA EBENEZER OJAOMO https://creativecommons.org/licenses/by/4.0
MECHANICAL BEHAVIOUR OF ANISOTROPIC FOLIATED ROCKS: IMPLICATIONS FOR TUNNEL STABILITY AND DESIGN
Understanding the mechanical behavior of anisotropic rocks is critical for the design and stability of underground structures, particularly in tunneling and deep excavation projects. This study investigates the effects of anisotropy on the strength, deformation, and failure mechanisms of foliated metamorphic rocks such as phyllite, schist, and gneiss using a combination of laboratory techniques, including triaxial compression tests, Unconfined Compressive Strength (UCS) tests, point load tests, and petrographic analysis. The results reveal a strong dependency of rock strength on bedding orientation. At 0° and 90° to foliation, rocks exhibited higher compressive strength, whereas at intermediate angles (particularly β=30°–45°), strength significantly decreased and failure became more pronounced. Triaxial testing showed that the influence of confining pressure was more effective at lower bedding angles, diminishing at steeper ones, indicating dominant anisotropic behavior. Petrographic analysis confirmed that mineral composition, particularly the presence of mica, along with microcracks and voids, plays a substantial role in weakening rock structure at certain orientations. Point load tests supported UCS findings and offered a practical means of estimating strength anisotropy. Crack propagation patterns also varied with loading angles, with brittle failure dominating at higher angles and shear failure observed along foliation planes at lower angles. This study underscores the necessity of accounting for anisotropy in geomechanical modeling and engineering design to ensure the structural integrity of subsurface constructions.
Copyright (c) 2025 GAUTAM HARKHANI, MANISH SHAH, ALPA SHAH, SHALINI SINGH https://creativecommons.org/licenses/by/4.0
COMPARATIVE STUDY ON BEHAVIOUR OF GEOCELL REINFORCED PAVEMENT
Infrastructure has become a major force for national development. Therefore, the development of ground improvement technology for weak subgrade composition has become an important goal in geotechnical engineering applications. Geosynthetics is one of the ground improvement techniques to improve bearing capacity of problematic subgrade soil. Geocell, the cell matrix expands to create radial stress and provide stability to the subgrade composition soil. In the past few years, the use of geocells and other methods to improve the properties of problematic soil, especially in pavement and foundation engineering, has been investigated. This paper focuses on presenting parameters such as increased bearing capacity, decreased settlement and increased stiffness when reinforcing various types of collapsible soils by addressing laboratory tests and field investigations for geocell configuration and highlights their advantages in various applications and future research. Research shows that geocells can improve the properties of problematic subgrade soil, making it suitable for many engineering applications.
Copyright (c) 2025 ANJALI GUNDALIYA, ALPA SHAH, MANISH SHAH https://creativecommons.org/licenses/by/4.0
INNOVATIVE MODELLING OF SOIL PHYSICOCHEMICAL PROPERTIES FOR PREDICTING HYDRAULIC CONDUCTIVITY IN ABIA STATE
Understanding the relationship between soil physicochemical properties and water movement is essential for optimizing agricultural productivity, resource management, and environmental sustainability. This study models the physicochemical properties and hydraulic conductivity (K) of soils in Abia State, Nigeria, using Response Surface Methodology (RSM). Focusing on three senatorial districts: Abia North, Abia Central, and Abia South; the research examines how soil texture, physical structure, and chemical composition influence hydraulic conductivity at varying depths (1-15 cm, 16-25 cm, and 26-35 cm). The study covers different soil types, including Ferralitic, Hydromorphic, and Alluvial soils, with a focus on improving irrigation, fertilizer application, and erosion control. Field sampling was conducted systematically across selected agricultural zones, resulting in 27 composite soil samples. These samples were analyzed for physical properties such as sand, silt, clay, bulk density, porosity, particle density, and hydraulic conductivity. Chemical properties examined included nitrogen (N₂), organic carbon (OC), calcium (Ca), magnesium (Mg), potassium (K), sodium (Na), and phosphorus (P). Laboratory analyses adhered to standardized methods, and data were processed using RSM to understand variable interactions and predict hydraulic conductivity. The results revealed significant spatial and vertical variations in soil characteristics. Sand was dominant in the topsoil, averaging 61.24%, while clay content increased with depth, particularly in Ferralitic soils of Abia South. Silt content remained relatively constant. Bulk density increased with depth, ranging from 1.12 to 1.82 g/cm³, while porosity decreased, indicating soil compaction. The models demonstrated high predictive accuracy (R²>0.85), confirming that soil texture, structure, and organic content significantly influence hydraulic conductivity. High organic carbon improved K in sandy soils but was less effective in clay-rich layers unless supplemented by calcium or porosity.
Copyright (c) 2025 JOSEPH EDET, CYPRIAN NDAMZI TOM, ISIGUZO EDWIN AHANEKU, UKACHI ETOAMAIHE, CHARLES UGOCHUKWU ORJI, EUNICE NNETE GAM https://creativecommons.org/licenses/by/4.0
SUSTAINABILITY OF WATER SUPPLY SYSTEMS UNDER CONDITIONS OF NEGATIVE ACTION NATURAL AND MAN-MADE PHENOMENA
This analyzes the sustainability of water supply systems under the effects of natural and anthropogenic factors. In theoretical terms, probability-based quantitative models will here be developed to serve stability assessment needs for water supply systems at different levels. This paper proposes a general scheme for assessing the stability of centralized water supply systems in its physical, technological, technical, and institutional aspects. The results indicate that continuous availability of water should be achieved to meet increasing demand together with environmental degradation and climate change. The findings provide an imperative test on how far the present system can go toward sustainability in supplying water in regions characterized by scarcity and improving it. An integrated approach to resource management is designed here after destabilizing factors such as pollution and infrastructure inadequacy are assessed. Results shall guide the formulation of programs on how to better manage water and ensure sustainability in the long run of a water supply system. Findings from this study are imperative for policymakers, urban planners, and environmental managers who plan an appropriate intervention concerning issues pertaining to global challenges where scarcity of water resources exists.
Copyright (c) 2025 NIKOLENKO ILYA VIKTOROVICH, MELNIKOVA NATALIA SERGEEVNA https://creativecommons.org/licenses/by/4.0
ENERGY FORECASTING MODELS FOR POWER AND TELECOMMUNICATION INFRASTRUCTURES: A SYSTEMATIC REVIEW
Energy demand for power and telecommunication infrastructures has risen in recent years owing to technological advancements. The downtimes caused by an inadequate energy supply to critical infrastructure pose a great risk to daily activities. Hence, knowledge of future energy demands is pertinent to minimizing losses and operational costs, while ensuring consistent and reliable services. This article comprehensively reviews different models for predicting energy requirements by power and telecommunication infrastructure. The findings reveal that, while traditional models such as linear regression are simple to implement, models utilizing machine learning (ML) and deep learning (DL) techniques demonstrate superior performance in predicting energy consumption, yielding more precise outcomes. It has also shown that ML and DL models, including long short-term memory (LSTM), convolutional neural networks (CNN), Gated Recurrent Units (GRU), and hybrid architectures, are particularly effective for handling the complexities of long-term forecasting and adaptive systems. Thus, this current study offers valuable insights for academia, researchers, and energy personnel in network planning of the power and telecommunication industries to improve energy efficiency and cost management by analyzing historical data, identifying complex patterns, enabling real-time adaptations, and accurately forecasting their energy requirements. Researchers can also build upon the identified gaps to enhance the existing models and improve productivity.
Copyright (c) 2025 TOLULOPE ERINOSHO, KAMOLI AMUSA, ABDULTAOFEEK ABAYOMI, FATAI KAZEEM, IMHADE OKOKPUJIE https://creativecommons.org/licenses/by/4.0
CIRCULAR HORIZONS: NAVIGATING THE PATH TO SUSTAINABLE PROSPERITY
The circular economy (CE) is emerging as a transformative framework for sustainable development, challenging the conventional linear model of "take-make-waste." This study critically examines the evolution and practical implementation of CE, focusing on three core areas: Circular Design, Industrial Symbiosis, and Grassroots Empowerment. By leveraging case studies from diverse regions, including Latin America, Europe, and Asia, the research highlights how innovative practices and strategic business models are reshaping industries towards sustainability. CE principles such as designing for longevity, maximizing resource efficiency, and fostering community-driven initiatives demonstrate their potential to minimize environmental impacts while enhancing economic resilience. This investigation also addresses critical challenges, including technological limitations, policy fragmentation, and socio-economic disparities, which hinder widespread adoption. The research underscores the importance of cross-sector collaboration and policy alignment to effectively embed CE practices into mainstream economic activities. By integrating sustainable design, collaborative industrial ecosystems, and community empowerment, CE offers a viable pathway toward a resilient and sustainable future. This study contributes to the ongoing discourse by providing actionable insights and strategic recommendations for stakeholders seeking to transition from traditional economic models to more circular and regenerative systems.
Copyright (c) 2025 SHARIEF UDDIN KHAN, SUHAIL ABDULLAH MALIK, BASHIR AHMAD DAR https://creativecommons.org/licenses/by/4.0
AN INSIGHT INTO THE ANTIBACTERIAL ACTIVITY OF COPPER DOPED GRAPHITIC CARBON NITRIDE COMPOSITE
The synthesis and doping of graphitic carbon nitride (g-C3N4) with copper (ii) chloride dihydride (CuCl2.2H2O) to the corresponding copper doped graphitic carbon nitride (Cu-g-C3N4) composite and also the application of the as-synthesized composite as an antibacterial agent is described. The graphitic carbon nitride (g-C3N4) was synthesized from melamine via condensation and then converted to copper doped graphitic carbon nitride (Cu-g-C3N4) by treatment with different percentage (5%, 10% and 20%) of the metal precursor to obtained Cu-g-C3N4. The resultant composite was characterized using XRD, FTIR, and FESEM. The antibacterial assay of the composite was assessed against the standard laboratory strains of Staphylococcus aureus (gram +ve), Salmonella typhi (gram –ve), Escherichia Coli (gram –ve) and Streptococcus pyogenes (gram +ve) using well diffusion method. The as-synthesized composite shows a good antibacterial activity against the test organisms (gram +ve and gram –ve) with zone of inhibition ranging between 2-21 mm. The results were found to be appreciable when compared with that of the standard antibiotic (Ampicillin). These indicate that the as-synthesized composites have good potentials for developing new antibiotics which will help in reducing healthcare costs and mortality rate due to resistance of bacteria to already manufactured drugs.
Copyright (c) 2025 IBRAHIM MUHAMMAD, ABUBAKAR ISAH, JAMILU USMAN https://creativecommons.org/licenses/by/4.0
GROWTH OF CANDIDA ALBICANS ON MODIFIED MEDIA BASED ON COOWBEANS (VIGNA UNGUICULATA L. WALP)
One fungus that can cause infection is Candida albicans. Supporting examinations to confirm the diagnosis can be carried out by growing the fungus in fungal growth media. The abundance of natural resources can be used as substitute raw materials for growth media for microorganisms. Cowpea is a natural ingredient that contains quite high nutrients, is widely available, easy to cultivate, has a fast harvest time, and is relatively affordable. This research aimed to determine the growth and morphology of Candida albicans on modified cowpea media. The method used was laboratory experimental and five variations were made to differ in the amount of cowpea added, namely 5 g (F1), 10 g (F2), 15 g (F3), 20 g (F4), 25 g (F5). The research showed that Candida albicans fungus grew on the modified cowpea media. The morphology of Candida albicans colonies in all cowpea-modified media formulations is characterized by smooth round colonies, yellowish white with a characteristic yeast odor. Candida albicans fungi in F1, F2 and F3, produce blastospores. Candida albicans fungi in F4 and F5 produce blastospores, pseudohyphae, and chlamydospores. Cowpea-modified media can be used as an alternative growth medium for Candida albicans, the best seen from its morphology is F5 with the addition of 25 g of cowpea.
Copyright (c) 2025 MAKHABBAH JAMILATUN, SEPTI DEA MAWARNI, WAWAN SOFWAN ZAINI https://creativecommons.org/licenses/by/4.0
ASSESSMENT OF SIX EVAPOTRANSPIRATION MODELS FOR UMUAHIA LOCAL GOVERNMENT AREA, ABIA STATE
Penman-Monteith (PM), Priestly Taylor (PT), Blaney-Morin Nigeria (BMN), Jensen-Haise (JH), Hargreaves-Samani (HS) and Thornthwaite (TH) models were used to estimate Reference Evapotranspiration (RET) for Umuahia, in South-Eastern Nigeria from 1997to 2017. The Penman-Monteithmodel was chosen as a standard for evaluating the other five empirical models. Good correlation was found between the RET values, estimated by each of the five radiation and temperature based models and the Penman-Monteith model, although there were some discrepancies. The mean annual RET estimated by the Penman-Monteith model as the standard tool for Umuahia was found to be 1041.0mm. While the mean annual RET estimated by other five models were found to be 579.3mm, 1487.7mm, 513.7mm, 1543.3mm and 1367.7mm, respectively. Conversely, the weather parameters influencing this station were found to be high due to the flatness of the terrain. In addition, from the statistical regression analysis, Priestly Taylor (PT) had the highest T-scores and lowest Root Mean Square Error (RMSE), in the ranking the Thornthwaite, Blaney-Morin and Hargreaves-Samani predicted best among the five models in the station. Good correlation was found by the temperature based models when evaluated RET with data for Umuahia Station. The Penman-Monteith estimates was used to develop correction factors for the three models that predicted best in the station for their potential use in the areawithout sensitive error. This was done in order to achieve accurate and reliable evapotranspiration estimate.
Copyright (c) 2025 CYPRIAN NDAMZI TOM, JOSEPH ANTIGHA EDET, EMMANUEL TEGA EROKARE, NGOZI FAITH UDENZE https://creativecommons.org/licenses/by/4.0