Engineering Commons^™

A Deep Learning Model For Accurate Tomato Leaf Disease Identification, Maheen Shahzad, Muhammad Abdullah Javed, Erum Ashraf, Hafiz Ishfaq Ahmad, Sabeen Masood

Turkish Journal of Electrical Engineering and Computer Sciences

Recent advances in machine learning and deep learning have greatly improved how we detect plant diseases, making diagnoses more accurate, faster, and easier to scale. However, many existing solutions depend on large, pretrained models that need powerful hardware, which limits their use in the field, especially in areas with limited resources. To tackle this, we designed a custom lightweight convolutional neural network (CNN) built from scratch using 20,000 carefully selected images from the PlantVillage tomato dataset. Our model uses Squeeze-and-Excitation (SE) blocks and Swish activation functions to boost performance, reaching an accuracy of 97.7% while using far fewer computing resources …

Influence Of Sinr And Noise Variance On Outage Probability For Mimo-Noma System In 5g And Beyond, Sadiq Ur Rehman, Jawwad Ahmed, Muhammad Zubair, Syed Sajjad Hussain Rizvi

Turkish Journal of Electrical Engineering and Computer Sciences

Nonorthogonal multiple access (NOMA) communication presents a promising solution to the limitations of traditional orthogonal multiple access techniques, offering potential improvements in achievable rates. Multiple-input multiple-output (MIMO), when combined with NOMA (MIMO-NOMA), further enhances these benefits by leveraging the diversity advantages of multiple antennas. Looking ahead, the future of wireless communication hinges on deploying heterogeneous networks (HetNets), facilitating the coexistence of various wireless access networks in a hierarchical fashion. However, the advent of 5G and 6G communications brings shorter channel coherence times, rendering channel reciprocity unreliable. Consequently, conventional channel estimation methods relying on uplink (UL) pilots for downlink (DL) transmission …

A Novel Approach To Maximum Weighted Traffic Flow Method For Effective Signal Control, Zülal Hi̇lal Yildiz Budak, Seyi̇t Alperen Çeltek, Aki̇f Durdu

Turkish Journal of Electrical Engineering and Computer Sciences

Traffic signal management is a critical challenge due to its environmental, economic, and public health impacts. The maximum weighted flow method (MaxWeightedFlow) was developed to optimize traffic flow at isolated and coordinated urban intersections. This study proposes a new method, the novel MaxWeightedFlow, which includes two key strategies to enhance the classical approach. The first strategy reduces computational burden by estimating vehicle approach times based on instantaneous speeds, improving real-time performance. The second employs regression analysis to optimize the alpha parameter, representing the vehicle waiting coefficient. The proposed approach, the novel MaxWeightedFlow, was evaluated using real-world traffic data from Kilis, …

Improving Rail System Signaling Efficiency Through Ai-Based Driving Profile Generation: A Comparative Performance Analysis, Mehmet Taci̇ddi̇n Akçay, Abdurrahi̇m Akgündoğdu

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a dataset comprising 3600 discrete operational snapshots (rather than continuous time-series data) derived from real-field operations is used to obtain a high-accuracy driving profile equation using a second-degree Polynomial Regression method. This equation demonstrates the model’s interpretability. The performance metrics obtained with the second-degree polynomial regression model’s equation are as follows: a coefficient of determination (R2) of 0.84, a Pearson Correlation Coefficient of 0.91, and an RMSE of 11.13. These results indicate the effectiveness of artificial intelligence-based approaches in improving the efficiency of the railway signaling system. The same dataset is also utilized with other machine learning …

Single-Valued Neutrosophic Pessimistic Multi-Granulation Rough Set Model Based On (A,B,C)-Cut Relations And Its Applications, Xu-Xi Wu, Hu Zhao, Qiao-Ling Song, Xiong-Wei Zhang

Neutrosophic Systems with Applications

To address uncertainty in multi-source data, this paper proposes a single-valued neutrosophic pessimistic multi-granulation rough set (P-SVN-MGRS) model based on (a,b,c)-cut relations. In this framework, each neutrosophic relation is characterized by three membership-degree functions: T(x,y), I(x,y), and F(x,y). These functions correspond to truth-membership, indeterminacy, and falsity, respectively. The (α,β,γ)-cut relation employs parameters α,β,γ∈(0,1] as thresholds for the three functions. A pair (x,y) belongs to …

Pythagorean Neutrosophic Mathematical Modelling, M. Kavitha, R. Irene Hepzibah

Neutrosophic Systems with Applications

Survey-based assessments often suffer from ambiguity, inconsistency, and uncertainty, which weaken the reliability of decision-making outcomes. To address these challenges, this study proposes a novel decision-support framework for data fuzzification, ranking, and agility measurement using Pythagorean Neutrosophic Fuzzy Sets (PNFS). The proposed method offers three major advantages: (i) enhanced ability to capture high levels of indeterminacy compared with classical fuzzy and intuitionistic models, (ii) improved ranking accuracy through a newly developed score function and ranking algorithm, and (iii) greater robustness in scenarios involving conflicting, incomplete, or imprecise expert judgments. The framework includes a refined Pythagorean Neutrosophic fuzzification technique, mathematically supported …

Neutrosophic Hankel Transforms And Their Application To Cross-Domain Legislative Integration, Mona Gharib, Mehboob Ali, Ishtiaq Hussain

Neutrosophic Systems with Applications

This paper introduces the Neutrosophic Hankel Transform (NHT) as a novel mathematical framework for modeling systems with radial structure under uncertainty, indeterminacy, and inconsistency. Building upon classical Hankel transforms and neutrosophic logic, we define two complementary realizations: a componentwise transform (NHT–C) that transports uncertainty with the signal, and a kernel-weighted transform (NHT–K) that embeds neutrosophic weights into the integral kernel. We establish linearity, inversion, and Parseval-type relations, and derive operational rules that diagonalize the Bessel radial operator.

To demonstrate utility, we formulate a radial diffusion–reaction model for pollutant concentration in a radialized river cross-section and solve it in closed form …

A Study Of Regular And Irregular Complex Neutrosophic Vague Graphs, Suriyakumar G, V. J. Sudhakar

Neutrosophic Systems with Applications

In this paper, We define the regular complex neutrosophic vague graph and the irregular complex neutrosophic vague graph for this purpose. We specify a node’s degree and total degree in a normal complex neutrosophic vague graph. A few features and theorems of those regular and irregular complex neutrosophic vague graphs are presented. This article defines busy and free nodes in a normal complex neutrosophic vague graph. Also, we describe a regular and irregular complex neutrosophic vague graph with a cycle as the underlying crisp graph.

From Uncertainty To Lucidity: Awareness Neutrosophic Kähler-Einstein Innovative Evaluator Methodological In Era Of Green Artificial Intelligence, Mona Mohamed, Ahmed M. Ali

Neutrosophic Systems with Applications

The rapid development of generative artificial intelligence (Gen AI) is a double-edged sword. On the positive side, Large Language Models (LLMs) of Gen AI as chatbot considered intelligent friend. Due to its potential to stimulate the maturation of ideas and cultivate fundamental general abilities like problem-solving and critical thinking. The advancement of Gen AI continued after that, moving from “chatbots” to “AI agents” that carry out multi-step activities in addition to responding to queries.

Regarding the downside, the terminology of “Red AI” era brought about by generative AI is marked by a performance at any expense that puts pressure on …

A Review Of Routing Attacks In Routing Protocol Over Low-Power And Lossy-Based Iot Networks, Lanka Chris Sejaphala Mr., Vusimuzi Malele Prof, Francis Lugayizi Prof.

Journal of Cybersecurity Education, Research and Practice

Low-power and Lossy IoT Networks (LLNs) comprise physical sensors, processing capability, power, and other technologies to exchange information between systems and devices over the internet. However, these networks are susceptible to routing attacks affecting resources, traffic flow, and topology formation. In the related work, it has been discovered that many previous studies do not consider algorithms and implementation approaches for routing attacks. This research study provides a comprehensive in-depth synthesis insight into the description, effects, and algorithms & implementation of four routing attacks in LLNs i.e., rank, sinkhole, DIS-flooding, and worst parent attacks. The findings of this research study highlight …

An Optimized Hybrid Xgboost-Lstm-Gru Model For Energy Consumption Forecasting In Smart Homes Using Weather Data, Marwah J. Salman, Eman M. El-Gendy, Amira Y. Haikal, Mahmoud M. Saafan

Mansoura Engineering Journal

Energy consumption is increasing every day due to the proliferation of smart homes and smart household appliances, which deplete existing energy resources. Therefore, efficient energy management by accurately predicting energy consumption is critical. In this paper, a hybrid prediction model is proposed to forecast energy consumption in smart homes using weather data. The proposed system follows five steps: data acquisition, data preprocessing, feature selection, prediction, and hyperparameter optimization. In the data acquisition step, all attributes except the weather attributes are removed. The min-max algorithm is then applied to normalize the dataset to a specific scale, preventing the prediction model from …

Optimized Resnet-18 Architecture For Multi-Class Oral Diseases Classification, Ahmed Ahmed

Karbala International Journal of Modern Science

In recent years, the classification of oral diseases has gained significant attention due to its influence on public health and the necessity for early and accurate diagnosis. Traditional diagnosis depends on manual clinical assessment, which can be slow and subjective. An optimized and subsequently quantized model is required to provide a faster and more consistent diagnostic support tool. This paper proposes an optimized ResNet-18 architecture for the classification of six oral diseases. The optimization process is based on removing the Rectified Linear Unit (ReLU), Batch Normalization (BN), and convolutional layers from the base ResNet-18 blocks that contain 128 filters. This …

Merging Terrestrial And Satellite Gravity Data For Africa: A Possibility To Fill-In The Data Gaps, Hussein A. Abd-Elmotaal, Norbert Kuhtreiber

Mansoura Engineering Journal

The major challenge that the IAG Sub-Commission on gravity and geoid in Africa faces is the significantly large gravity data gaps. It is essential to properly tackle this issue for all geodetic applications in Africa due to the large interpolation errors occur at these large gaps. Simple interpolation (using any type of interpolation technique) of the gravity data does not add new information at the large data gaps, and the solution is free there. Global Earth gravity models offer themselves as a possible way to fill-in such large data gaps, provided that they approximate the African gravity field to an …

Model-Based Investigation Of The Influence Of Environmental Conditions On The Energy Supply Of Multirotor Uavs, Morten Roßberg, Hanna Dibbern, Claudia Werner

Journal of Aviation Technology and Engineering

Flight time of unmanned aerial vehicles (UAVs) is limited by available energy, which is affected by the mission profile and external factors, such as environmental conditions. Two main environmental conditions that need to be considered are the impact of wind and ambient temperature on the UAV and its energy supply. The purpose of this study is to examine the effects of wind and ambient temperature to conduct a preliminary evaluation of flight performance and flight limitations. For this reason, three locations in the United States—New York City, Miami, and Fairbanks—are selected and the impact of the considered environmental conditions of …

A Contextual Attention-Based Transformer Model For Enhanced Hate Speech Detection On Twitter, Mira Mansour, Nancy Akoum, Seifedine Kadry

Iraqi Journal for Computer Science and Mathematics

Hate speech on social media poses significant societal challenges, necessitating accurate and context-sensitive automated detection. Traditional machine learning (ML) models typically rely on lexical or superficial features, limiting their ability to capture nuanced or contextually ambiguous expressions of hate speech. Recent transformer-based methods (e.g., RoBERTa) provide improved contextual understanding but often lack explicit mechanisms guiding the model’s attention to critical semantic tokens, thereby reducing interpretability and sensitivity to nuanced linguistic contexts. This paper introduces a novel contextual attention-guided transformer model that explicitly incorporates lexicon-guided attention supervision into RoBERTa fine-tuning, significantly enhancing semantic precision in hate speech detection on Twitter. Evaluations …

Numerical Solution Of A Coupled Nonlinear Dynamic Problem Of Thermoviscoelasticity, Abdali Abdukarimov, Ibodat Turabekovna Khaldybaeva, Askarova Shamshetdinovna Ayjamal

Technical science and innovation

This paper presents a numerical solution of a coupled nonlinear dynamic problem of thermoviscoelasticity. A Duffing-type oscillator with temperature-dependent properties is used to model nonlinear hereditary deformable systems. After specifying the temperature dependences of the elastic modulus 𝐸 and viscosity parameter 𝜂 and introducing dimensionless variables, the problem is reduced to a system of nonlinear integro-differential equations. A numerical procedure for solving this system is developed, and representative examples are computed. The results are presented in graphical form for various values of the governing parameters.

Pengujian High Fidelity Prototipe Media Pembelajaran Interaktif Bahasa Inggris Dengan Gamifikasi Menggunakan User Experience Questionare, Adhitya Prastyadi, Meizano Muhammad Ardhi, Daniel Rinaldi, Margaretha Karolina Sagala

Jurnal Sosial Humaniora Terapan

Abstract

Testing a Hi-Fi Prototype of Interactive English Learning Media with Gamification Using UEQ

This study aims to test and evaluate the User Experience (UX) quality of a High-Fidelity prototype for interactive English learning media integrating gamification elements. The research is motivated by the low English proficiency and motivation among Indonesian students, and the potential of digital media and gamification to enhance learning engagement. Inspired by the success of the Duolingo application, this prototype was designed to create an enjoyable and effective learning experience. A quantitative research methodology was employed, involving high school students as participants selected via purposive sampling. …

Exploring The Role Of Occupational Therapy In The Delivery Of Trauma-Informed Services To Hospital-Based Clients Ot, Frank Czuba

Journal of Applied Disciplines

Hospitalization can traumatize clients and impact overall health outcomes, leading to increased hospital readmission rates and resulting in a negative impact for both clients and providers. Limited information exists regarding how hospital-based occupational therapists evaluate and address trauma, even though incorporating trauma-informed principles into professional practice can enhance the occupational therapy process. The study explored the comprehension and perceived significance of trauma-informed tenets among occupational therapists delivering services in hospital-based settings. A quantitative research study with an exploratory design was implemented to explore how occupational therapists (OT) understand and utilize trauma-informed practices with their clients in a hospital setting. An …

The Impact Of Natural Cavities On Mining Feasibility In Brazil: Dilemma Between The Sustainability Of Mining Operations And The Environment, Tiago Leite, Felipe Souza, Mariana Silva, Iuri Brandi, Hernani De Lima

Journal of Sustainable Mining

Due to the legislation on natural underground cavities in Brazil, mineral reserves have been blocked, causing a great dilemma between the sustainability of the mineral activity and the preservation of cavities. This study presented an analysis of the evolution of the federal cave legislation, pointing out the main gains and contribution to the theme, in which the importance in the Brazilian scenario of the publication in 2017 of Normative Instruction N° 01, which updated the procedures for the definition of these “other forms of compensation” to the irreversible negative impact on cavities with a high degree of relevance. In this …

Multivariate Stochastic Mine Scheduling Targeting Stationary Grades Considering Risk Uncertainty And Hierarchical Variables, Augusto A. T. Toledo, Joao F. C. L. Costa, Diego M. Marques, Luciano N. Capponi

Journal of Sustainable Mining

In short-term mine planning for deposits characterized by multiple variables, sequential diglines are generated with an emphasis on maintaining consistent grade distributions across mining periods. This research integrates an array of mineral variables, including deleterious elements, to facilitate the establishment of excavation geometries that enable precise grade and volume control within operational production zones. Through the systematic application of geostatistical analysis coupled with process optimization, geological risks associated with grade uncertainties are minimized, and an optimized operational sequence for the extraction of mineral blocks is pursued. The main point of this approach is maintaining grade distributions aligned with the historical …

An Innovative Implicit Modeling Technique To 3d Deposit Modeling: A Case Study Of The Chromite Mine, Ali Can Ozdemir Ozdemir, Yavuz Tore

Journal of Sustainable Mining

The location of an orebody known to show regional variability in space is determined only through 3D geological modeling. A reliable 3D orebody model must be obtained to ensure resource efficiency and sustainability in the mining industry. In addition, 3D geological modeling has become indispensable in intelligent mining, smart mining, and mining 4.0. In previous years, explicit methods were widely used for 3D geological modeling. However, the validity of geological models produced with these methods has been debated. It has been understood that they are inadequate in modeling vein-type mineralizations with complex geometry in particular. For this reason, implicit modeling …

A Review Study Of The Relationship Between Coal Fly Ash Characteristics And The Presence Of Rare Earth Metals From Steam Power Plants In Indonesia, Muhammad F. Shafiyurrahman, Shofa Rijalul Haq, Nurkhamim Nurkhamim, Ade Kurniawan, Rofa D Bulopa, Rizki Khoiriah Nasution

Journal of Sustainable Mining

The establishment of a coal mining downstream ecosystem focused on a sustainable and environmentally friendly economy is an important goal for many countries. One strategic step in achieving this goal is the utilization of coal fly ash (CFA) waste as a secondary source of rare earth elements (REE). The use of CFA provides a solution to the environmental and health challenges resulting from mining primary sources. Prior to developing REE extraction technology, CFA characterization must be conducted. Therefore, this study addresses the relationship between CFA characteristics and the presence of REE. Based on the ASTM C618-12 standard, CFA in Indonesia …

Integrated Optimization Of Underground Mine Ventilation Using Hardy Cross, Monte Carlo Simulations, And Machine Learning Techniques: A Step Toward Sustainable Mining, Hussein A. Saleem

Journal of Sustainable Mining

Underground mine ventilation is crucial for ensuring worker safety, air quality, and operational efficiency. Effective optimization of ventilation systems reduces energy consumption, enhances airflow distribution, and minimizes risks associated with harmful gases and fire hazards. This study proposed an integrated framework combining the Hardy Cross (HC) method, Monte Carlo (MC) simulations, and machine learning (ML) techniques to optimize the ventilation system at the Jabal Sayid mine in Saudi Arabia. The HC method was employed to provide deterministic baseline airflow calculations, while the MC simulations accounted for uncertainties in resistance values and environmental conditions, generating probabilistic distributions of key parameters. Among …

Study On Visualization Simulation And System Dynamic Optimization Of The Ore Drawing Process In Mine Chutes, Liang Juan, Zhu Quanjie, Hao Yingnan, Quan Zhongxue, Zhang Zhiwu, Liu Xiaohuic, Ouyang Zhihua

Journal of Sustainable Mining

The ore release process in metal mine chutes is a critical part of the mining operation. Based on the urgent demand for intelligent mining construction, this paper proposes a visualization simulation and dynamic optimization method for the mine chute ore release process using the open-source programs Python and Blender. The main research content includes: designing the simulation method and model for the ore release process, including the main control program, process subprograms, etc.; proposing a visualization simulation method for the mine chute ore release process based on Blender, studying the impact of ore shape and size on ore release efficiency, …

Assessment Of Heavy Metal Contamination In Surface Water Near Tailings Dam, Gera Techane Mengistu, Tesema Kebede, Enatfenta Melaku, Engdasew Temere

Journal of Sustainable Mining

Elevated levels of heavy metals in surface water can lead to the degradation of water quality, especially in mining areas where tailing dams are sources of heavy metal pollution. This study focuses on evaluating the concentrations of heavy metals in surface water near the Legadembi tailings dams. The mean concentrations (in µg/L) of various heavy metals including: arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), molybdenum (Mo), nickel (Ni), lead (Pb), antimony (Sb), selenium (Se), thallium (Tl), uranium (U), vanadium (V), tungsten (W), zinc (Zn), and zirconium (Zr) were determined: 79.7, 0.15, 162.3, 0.66, 18.1, 0.01, …

Intrinsically Safe Pneumatic Seismic Source For Controlled Rock Mass ,Monitoring And Imaging In Underground Mining, Przemysław Sierodzki, Leszek Remiorz, Mateusz Ćwiękała, Krzysztof Krawiec

Journal of Sustainable Mining

This article explores the technical principles of pneumatic seismic sources, focusing on their application in underground mining operations, including environments prone to fire hazards. It introduces an intrinsically safe pneumatic seismic source as a cost-effective solution for quasi-continuous seismic excitation, useful for detecting stress concentrations in mining settings. These stress concentrations are identified through anomalies in seismic wave velocity, which may indicate potentially hazardous deformations in the rock mass. The developed system enables fully remote operation from the surface and integrates with a seismic monitoring system to capture high-resolution waveforms. The study provides an overview of the pneumatic system’s technical …

Investigating Frozen Paste Surface Disposal As A Climate Change Adaptation Strategy: Case Study Of Mont-Wright Mine, Khalil Hashem, Agus P. Sasmito, Laxmi Sushama, Ferri Hassani, Mehrdad Kermani

Journal of Sustainable Mining

The mining industry faces evolving challenges in adapting to the impacts of climate change. Among these challenges is the management of tailings. This study focuses on investigating surface disposal of non-cemented paste tailings, particularly the effect of water content, freeze-thaw cycles (FTC, defined as freezing the sample to –20°C and thawing it to +20°C), and ambient temperature on the mechanical characteristics and thermophysical properties of paste tailings. The potential for maintaining non-cemented tailings in a frozen state year-round is also investigated through field-scale numerical simulations. Experiment results of thermophysical properties of tailings with water content, freeze-thaw cycles and ambient temperatures …

Continuous Sorption Of Ionic Dyes Onto Nanoporous Faujasite Zeolite And The Regeneration Of The Adsorbent, Frederick O. Oshomogho, Miracle Aisosa Omorogieva

BAU Journal - Science and Technology

This study evaluates the efficiency of synthesized faujasite zeolite in the continuous removal of methylene blue from water and tests the reusability of the regenerated adsorbent. Faujasite Zeolite was synthesized from locally available aluminosilicate clay in Edo State using standard methods documented in the literature. XRF analysis affirmed the elemental composition, showing high levels of silica and alumina, which increased its adsorption capacity. SEM images depicted a crystal-clear structure with an octahedral shape and visible micro-pores on the surface. TGA showed effective thermal stability below 300 ºC, with a 10% weight loss between 28.59 ºC and 300 ºC. BET analysis …

Toward Sustainable Water Security: A Novel Assessment And Recharge Strategy For North Bekaa Plain, Rida Tadmouri, Amin Shaban, Mohamad Soliman

BAU Journal - Science and Technology

The demand for water in the northern Bekaa Plain is of utmost significance, especially given the substantial portion of land dedicated to irrigated agriculture. Additionally, the region experiences population growth, further exacerbating the water supply challenge. Understanding the groundwater potential zones and identifying appropriate recharge areas are crucial steps towards sustainable water resource management. The study focuses on reaching the best solutions for the study area, by utilizing advanced Geographic Information System (GIS) tools, including overlying slope, rainfall, lithology, attitude, soil, fracture, and stream maps, a Groundwater Potential (GWP) map was generated using ArcGIS. This map serves as a valuable …

Numerical Investigation Of Heat Transfer And Aero-Acoustic Response In Deep Cavity Flows Using Urans Simulations, Abdul Hamid Jabado, Ali Hammoud, Bilal El Zohbi, Bilal Taher, Hassan Assoum

BAU Journal - Science and Technology

This paper presents a numerical study to investigate a deep cavity flow, in order to better understand the underlying mechanisms involved in it, such as flow dynamics, heat transfer, and aeroacoustics. A 2-D Unsteady Reynolds Averaged Navier Stokes model (URANS) was implemented using an SST k-ω turbulence closure simulated over a rectangular deep cavity. Previous experimental results were used to validate the numerical results, to confirm the accuracy of the flow field patterns reproduced. Both controlled and uncontrolled cases were analyzed. Heat transfer was also investigated on both configurations, showing the effect of cavity geometry and inlet conditions on heat …