Engineering Commons^™

A Revenue-Driven Approach For Enhanced Task Utilization In Vehicular Cloud Computing, Ashish Singh Saluja, Satyabrata Das, Sanjib Kumar Nayak, Sohan Kumar Pande

Turkish Journal of Electrical Engineering and Computer Sciences

Vehicular networks support intelligent transportation through vehicle-to-roadside Units (V2R) and vehicle-to-vehicle (V2V) communication but face challenges from dynamic topologies, limited RSU coverage, and bandwidth scarcity, which impact service delivery and revenue. RDA-ITU addresses these challenges by integrating V2R and V2V paradigms to maximize RSU revenue, enhance service availability, and improve system efficiency. It dynamically allocates services based on real-time network conditions and vehicle mobility, leveraging V2V relays to optimize both RSU-direct and cooperative communication. Through extensive simulations, RDA-ITU significantly outperforms four baselines: RBSM, VVMM-U, VVMM-LW, and VVMM-MA. It achieves 81.1% higher total revenue, 154.8% more completed requests, and 103.6% higher …

Resource Constraint Evacuation Route Planning A Capacity-Aware Charge-Encoded State-Space Approach, Praveen Borra

Electronic Theses and Dissertations

Emergency Management Information Systems (EMIS) are defined as a set of tools that assist decision-makers in risk assessment and disaster response for significant multi-hazard threats and disasters. Over the past several decades, EMIS have become increasingly important for understanding, managing, and governing transportation systems during large-scale emergency events. One of the primary objectives of EMIS is to efficiently utilize spatial and network datasets to support evacuation planning, identify critical transportation patterns during emergencies, and allocate resources effectively. However, the increasing complexity and scale of modern transportation systems present significant challenges in developing reliable evacuation planning solutions.

One of the most …

Evolutionary Neural Architecture Search: A Survey, Ferda Nur Özçeli̇k, Mehmet Önder Efe

Turkish Journal of Electrical Engineering and Computer Sciences

Deep Neural Networks (DNNs) have achieved remarkable success across diverse machine learning applications, yet designing effective architectures remains a laborious, expert-driven process. Neural Architecture Search (NAS) was introduced to automate this process, with Evolutionary NAS (ENAS) emerging as one of the most effective and widely adopted NAS paradigms. This survey provides a comprehensive and systematic review of 164 ENAS studies published between 2020 and 2024, categorized according to the specific evolutionary algorithm employed as the search strategy. Unlike prior surveys—which either treat evolutionary methods at a high level or focus on general NAS pipelines—this study is, to the best of …

Cnkg: Harnessing Large Language Models For Cognitive Neuroscience Knowledge Graph Construction, Ali Sarabadani, Kheirollah Rahsepar Fard, Hamid Dalvand

Turkish Journal of Electrical Engineering and Computer Sciences

Textual resources are among the most valuable sources of information in cognitive neuroscience (CN) for understanding and investigating brain activity and cognitive processes. Extracting and constructing knowledge graphs (KGs) from these texts can facilitate medical research by providing deeper insights into neurological diseases and brain function. In recent years, the use of large language models (LLMs) in natural language processing (NLP) has become increasingly widespread, significantly enhancing the extraction of meaningful information from large volumes of text. This study proposes a novel approach for constructing and evaluating a specialized knowledge graph, termed the cognitive neuroscience knowledge graph (CNKG), from scientific …

Robust Variable-Gain Backstepping Control For Nonlinear Systems With Real-Time Application To Induction Motor, Fadi Alyoussef, İbrahi̇m Kaya, Ahmad Akrad, Rabia Sehab, Cristina Morel

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a novel variable-gain mechanism with a minimal number of tuning parameters to enhance the performance of conventional backstepping controllers for nonlinear systems while avoiding singularity and peaking phenomena. The proposed approach is simple, computationally efficient, and well suited for real-time implementation without imposing a significant computational burden. Its effectiveness is validated through real-time experiments conducted using a dSPACE DS1104 controller board and a 7.5-kW induction motor (IM). Simulation results demonstrate that the proposed controller outperforms the conventional backstepping controller. Robustness analyses under variations in stator resistance, load inertia, and viscous friction coefficient reveal substantial reductions in the …

Swindeitvit: A Soft Voting Vision Transformer Ensemble For Accurate And Explainable Solar Panel Fault Detection, Mahe Zabin

Turkish Journal of Electrical Engineering and Computer Sciences

Solar panels are becoming very essential in providing sustainable energy but they are usually affected by defects on the surface like dust, snow, bird droppings, physical damages and electrical faults which interfere with their performance. These faults must be identified accurately and in a timely manner to enhance energy efficiency, lower the maintenance cost, and supplement the traditional manual methods of inspection which are labor-intensive, time-consuming and subject to human errors in judgment. The most common methods, such as traditional CNNs and hybrid architectures tend to be less accurate, less explainable and cannot be properly evaluated to be deployed in …

Enhancement Of Nested Hexagonal Fractal Antenna Performance For Multiband Wireless Applications, Abdelbasset Azzouz, Rachid Bouhmidi, Mohammed Chetioui, Redouane Berber, Ahmed Jamal Abdullah Al-Gburi

Turkish Journal of Electrical Engineering and Computer Sciences

This work focuses on developing a compact multiband antenna to meet the growing demand for versatile and efficient radiating structures in modern wireless communication systems. A hexagonal fractal antenna is proposed and analyzed for applications such as mobile communications, WLAN, industrial, scientific and medical (ISM) bands, Wi-Fi, satellite links, radar systems, and military communications. By iteratively modifying the antenna geometry with larger hexagonal elements, the design enhances multiband behavior and improves key performance parameters including gain, S11, voltage standing wave ratio (VSWR), and radiation characteristics. The antenna is modeled using high-frequency structure simulator (HFSS)® and fabricated on a low-cost 0.8 …

Parameter Optimization Of Dual-Qsg Based Pll For Real-Time Control Of Grid-Connected Ev Chargers, Gaurav Yadav, Sudhanshu Mittal, Vineet Kumar, Sombir Kundu, Praveen Bansal

Turkish Journal of Electrical Engineering and Computer Sciences

Dual-Quadrature Signal Generator (D-QSG) based Phase lock loop (PLL) has been recently proposed to handle the nonideal grid voltage conditions. However, selecting the parameter for D-QSG based controller has been a great challenge, especially for higher-order systems. Inappropriate parameter selection tends to increase settling time both in terms of amplitude as well as harmonics attenuation. Hence, in the proposed work, the main focus is on parameter selection to achieve a faster response. Here, a fourth-order Quasi-Synchronous Generator has been realized by cascading the two nonidentical second order generalized integrators (NISOGIs). Furthermore, the parameters of both the NISOGIs are selected in …

Erratum To “Sgsc-Kko-Lstm: A Deeplearning Classifier Model For Smart Grid” [Turkish Journal Of Electrical Engineering & Computer Sciences 34 (2) 2026 185-213], Samaniba Imchen, Dushmanta Kumar Das

Turkish Journal of Electrical Engineering and Computer Sciences

The first and second authors were incorrectly ordered in the article PDF due to a typesetting error. To rectify this oversight and ensure the accuracy of the published work, the author order have been corrected as follows: 1. Samaniba Imchen – First Author 2. Dushmanta Kumar Das – Second Author

A link to the original article can be found at: https://doi.org/10.55730/1300-0632.4170

Cybersecurity Governance Of Industrial Iot In Sub-Saharan Africa: Policy Gaps, Threat Landscape, And Lessons From Comparative African Contexts, Faztudo Languisse Eng.

Journal of Cybersecurity Education, Research and Practice

The rapid deployment of Industrial Internet of Things (IIoT) systems across Sub-Saharan Africa's extractive, energy, logistics, and agro-industrial sectors has introduced a cybersecurity challenge of growing urgency: industrial networks that were designed for operational efficiency are increasingly exposed to cyber threats for which neither the organizations nor the regulatory frameworks are adequately prepared. This article examines the cybersecurity governance of IIoT systems in a developing African economy, using Mozambique as a primary case study and drawing comparative lessons from South Africa, Rwanda, and Kenya. Through an integrative literature review and documentary analysis of national digital, cybersecurity, and industrial policies, the …

Assessing Computer Vision Based Conflict Detection In Uas Traffic Monitoring Under Secure Communication Constraints, Fadjimata Issoufou Anaroua

Doctoral Dissertations and Master's Theses

The rapid growth of Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) is creating a new low-altitude airspace ecosystem where drones, air taxis, service suppliers, communication networks, sensors, and ground-based monitoring systems must work together safely. Within this ecosystem, UAS Traffic Management (UTM) is expected to provide a digital framework for coordinating operations beyond traditional air traffic control. However, reliable integration also requires resilient monitoring methods that can detect non-cooperative aircraft, protect communication links, and maintain timely situational awareness under real-world constraints.

This dissertation examines how computer vision can support cooperative monitoring systems such as Remote ID and ADS-B …

Enhanced Intrusion Detection Using Recurrent Neural Networks With Amino Acid Codon Features, Omar Fitian Rashid, Mohammed Ahmed Subhi, Safa Ahmed Abdulsahib, Mohammed Khaleel Hussein, Marwan Ali Albahar

Iraqi Journal for Computer Science and Mathematics

Intrusion Detection Systems (IDS) is the main defense mechanism deployed by the current networks to prevent cyber threats. Recurrent Neural Network (RNN) are also a novel IDS structure that replaces the conventional training and testing mechanism. The strategy encodes network traffic data as biological sequences using amino acid codons in such a fashion that the RNN is capable of effectively analyzing temporal and sequence data patterns. RNN architecture design adopts embedding layers to handle codon representations and Long Short-Term Memory (LSTM) layers to perform sequential data learning, which is followed by a fully connected network to perform classification functions, which …

The Effect Of Ideals In Near Rings With Respect To Zero Divisor And Completely Equiprime Split Graphs, Sarah Hamid Al-Sharifi, Ameer A. J. Al-Swidi

Iraqi Journal for Computer Science and Mathematics

We seek to find several relationships for some of the graphs that were previously studied by us(completely equiprime graph $CEQ_J( N )$) and by other researchers(simple graph $\Gamma $(R)) based on the ideals of the near rings with our new definition, which is the split and non-split of graphs, which determines the consequent priorities in light of that, specifying that according to the properties of the near ring elements and their ideals.

Latent Space Exploration Of Stylegan2-Ada For Fashion Image Synthesis: A Practical Implementation Guide For Moderate-Sized Datasets, Ali H. Shareef, Hajer Ghodhbani, Tarek M. Hamdani, Habib Chabchoub, Adel M. Alimi

Iraqi Journal for Computer Science and Mathematics

\hlThis paper presents the use of StyleGAN2-ADA for fashion image synthesis and editing. We demonstrate that generative adversarial networks (GANs) can generate realistic and diverse fashion images even under moderate data constraints. The model trained on a dataset of 9,000 fashion images achieved a Fréchet Inception Distance (FID) of 10.8, a Garment Structure Accuracy (GSA) of 0.85, a Pattern Continuity Score (PCS) of 0.78, and an Attribute Transfer Accuracy (ATA) averaging 75% across key attributes. These quantitative results confirm the model’s ability to produce high-quality, structurally consistent, and semantically coherent fashion images. Unlike previous studies focusing on …

Explainable Ai In Agriculture: Bridging The Gap Between Technology And Farmer, Jayarekha P, Anitha H M, Sowmya K S, Nalina V, Audithan Sivaraman, Madhu Narasimha

Iraqi Journal for Computer Science and Mathematics

An intelligent and explainable, as well as user-friendly, crop recommendation and yield prediction system is developed to facilitate agricultural decision-making under various tillage methods with the help of Explainable AI. The system utilizes Machine Learning algorithms and calculates yield changes as a relative term with respect to various inputs such as location, month of sowing, years of NT adoption, and soil type using real-time environmental data; accordingly, it recommends crops. The prediction framework, which is based on various regression algorithms, including Linear Regression, Decision Tree, Random Forest, and Gradient Boosting, was trained on the dataset of agronomic and climatic variables. …

Resolution Of Expression Of Concern: Ontology Features-Based Arabic Text Augmentation Using Word2vec, Enas Tariq Khudair, Onsa Lazzez, Mourad Zaied, Tarek M. Hamdani, Ahmed T. Sadiq, Habib Chabchoub, Adel M. Alimi

Iraqi Journal for Computer Science and Mathematics

Editor's Note: This Resolution notice concludes the investigation initiated by the Expression of Concern (DOI: https://doi.org/10.52866/2788-7421.1386) regarding the Original Article (DOI: https://doi.org/10.52866/2788-7421.1302). The publication timeline is as follows: Original Article → Expression of Concern → Resolution.

Resolution of Expression of Concern:

The editorial team of the Iraqi Journal for Computer Science and Mathematics has completed a thorough post-publication review of the above-mentioned article, the supporting data, and the authors’ responses to the queries raised. Upon careful assessment, we have determined that the concerns have been addressed and clarified to the satisfaction of the editors.

We have found …

Resolution Of Expression Of Concern: The Innovative Technique For Obtaining The Solutions Of Jeffery Hamel Nano-Fluids Flow Problem, Haedir Abd Alrazak Namoos, Abeer Majeed Jasim

Iraqi Journal for Computer Science and Mathematics

Editor's Note: This Resolution notice concludes the investigation initiated by the Expression of Concern (DOI: https://doi.org/10.52866/2788-7421.1389) regarding the Original Article (DOI: https://doi.org/10.52866/2788-7421.1303). The publication timeline is as follows: Original Article → Expression of Concern → Resolution.

Resolution of Expression of Concern:

The editorial team of the Iraqi Journal for Computer Science and Mathematics has completed a thorough post-publication review of the above-mentioned article, the supporting data, and the authors’ responses to the queries raised. Upon careful assessment, we have determined that the concerns have been addressed and clarified to the satisfaction of the editors.

We have found …

Resolution Of Expression Of Concern: Software Engineering Approach To Enhancing Privacy Protection: Automated Face Blurring Using Deep Learning In Arab Social Media, Yasmin Makki Mohialden, Nadia Mahmood Hussien, Mostafa Abdulghafoor Mohammed

Iraqi Journal for Computer Science and Mathematics

Editor's Note: This Resolution notice concludes the investigation initiated by the Expression of Concern (DOI: https://doi.org/10.52866/2788-7421.1388) regarding the Original Article (DOI: https://doi.org/10.52866/2788-7421.1317). The publication timeline is as follows: Original Article → Expression of Concern → Resolution.

Resolution of Expression of Concern:

The editorial team of the Iraqi Journal for Computer Science and Mathematics has completed a thorough post-publication review of the above-mentioned article, the supporting data, and the authors’ responses to the queries raised. Upon careful assessment, we have determined that the concerns have been addressed and clarified to the satisfaction of the editors.

We have found …

Resolution Of Expression Of Concern: Quantum Machine And Deep Learning For Medical Image Classification: A Systematic Review Of Trends, Methodologies, And Future Directions, Eman A. Radhi, Mohammed Y. Kamil, Mazin Abed Mohammed

Iraqi Journal for Computer Science and Mathematics

Editor's Note: This Resolution notice concludes the investigation initiated by the Expression of Concern (DOI: https://doi.org/10.52866/2788-7421.1387) regarding the Original Article (DOI: https://doi.org/10.52866/2788-7421.1252). The publication timeline is as follows: Original Article → Expression of Concern → Resolution.

Resolution of Expression of Concern:

The editorial team of the Iraqi Journal for Computer Science and Mathematics has completed a thorough post-publication review of the above-mentioned article, the supporting data, and the authors’ responses to the queries raised. Upon careful assessment, we have determined that the concerns have been addressed and clarified to the satisfaction of the editors.

We have found …

Resolution Of Expression Of Concern: Leveraging Machine Learning For Accurate Prediction Of Nba Player Salaries, Ye Cheng, Yan Song, Mingqi Wang

Iraqi Journal for Computer Science and Mathematics

Editor's Note: This Resolution notice concludes the investigation initiated by the Expression of Concern (DOI: https://doi.org/10.52866/2788-7421.1385) regarding the Original Article (DOI: https://doi.org/10.52866/2788-7421.1275). The publication timeline is as follows: Original Article → Expression of Concern → Resolution.

Resolution of Expression of Concern:

The editorial team of the Iraqi Journal for Computer Science and Mathematics has completed a thorough post-publication review of the above-mentioned article, the supporting data, and the authors’ responses to the queries raised. Upon careful assessment, we have determined that the concerns have been addressed and clarified to the satisfaction of the editors.

We have found …

Resolution Of Expression Of Concern: Improving Road Safety Through Multimodal Deep Learning For Driver Drowsiness Detection, Hadel A. Hussain, Mohammed A. Subhi, Ahmed S. Al Tmeme, Ahmed D. Radhi, Marwan Ali Albahar

Iraqi Journal for Computer Science and Mathematics

Editor's Note: This Resolution notice concludes the investigation initiated by the Expression of Concern (DOI: https://doi.org/10.52866/2788-7421.1384) regarding the Original Article (DOI: https://doi.org/10.52866/2788-7421.1330). The publication timeline is as follows: Original Article → Expression of Concern → Resolution.

Resolution of Expression of Concern:

The editorial team of the Iraqi Journal for Computer Science and Mathematics has completed a thorough post-publication review of the above-mentioned article, the supporting data, and the authors’ responses to the queries raised. Upon careful assessment, we have determined that the concerns have been addressed and clarified to the satisfaction of the editors.

We have found …

Resolution Of Expression Of Concern: Improved Harmony Search Algorithm For Sdn Controller Placement, Yousra Abdul Alsahib S. Aldeen, Ahmed T. Sadiq, Abeer E. Abed, Omar F. Hussain, Syed Hamid Hussain Madni

Iraqi Journal for Computer Science and Mathematics

Editor's Note: This Resolution notice concludes the investigation initiated by the Expression of Concern (DOI: https://doi.org/10.52866/2788-7421.1382) regarding the Original Article (DOI: https://doi.org/10.52866/2788-7421.1249). The publication timeline is as follows: Original Article → Expression of Concern → Resolution.

Resolution of Expression of Concern:

The editorial team of the Iraqi Journal for Computer Science and Mathematics has completed a thorough post-publication review of the above-mentioned article, the supporting data, and the authors’ responses to the queries raised. Upon careful assessment, we have determined that the concerns have been addressed and clarified to the satisfaction of the editors.

We have found …

Resolution Of Expression Of Concern: Exact Solutions Of M-Fractional Complex Ginzburg-Landau Equation Via Two Analytical, Nematollah Kadkhoda, Mojtaba Baymani, Maad M. Mijwil, Mostafa Abotaleb

Iraqi Journal for Computer Science and Mathematics

Editor's Note: This Resolution notice concludes the investigation initiated by the Expression of Concern (DOI: https://doi.org/10.52866/2788-7421.1381) regarding the Original Article (DOI: https://doi.org/10.52866/2788-7421.1267). The publication timeline is as follows: Original Article → Expression of Concern → Resolution.

Resolution of Expression of Concern:

The editorial team of the Iraqi Journal for Computer Science and Mathematics has completed a thorough post-publication review of the above-mentioned article, the supporting data, and the authors’ responses to the queries raised. Upon careful assessment, we have determined that the concerns have been addressed and clarified to the satisfaction of the editors.

We have found …

Resolution Of Expression Of Concern: Artificial Intelligence In Education: Mathematics Teachers’ Perspectives, Practices And Challenges, Mohammad A. Tashtoush, Yousef Wardat, Rommel Al Ali, Shoeb Saleh

Iraqi Journal for Computer Science and Mathematics

Editor's Note: This Resolution notice concludes the investigation initiated by the Expression of Concern (DOI: https://doi.org/10.52866/2788-7421.1379) regarding the Original Article (DOI: https://doi.org/10.52866/ijcsm.2024.05.01.004). The publication timeline is as follows: Original Article → Expression of Concern → Resolution.

Resolution of Expression of Concern:

The editorial team of the Iraqi Journal for Computer Science and Mathematics has completed a thorough post-publication review of the above-mentioned article, the supporting data, and the authors’ responses to the queries raised. Upon careful assessment, we have determined that the concerns have been addressed and clarified to the satisfaction of the editors.

We have found …

Resolution Of Expression Of Concern: A Lightweight U-Net Model For Accurate Skin Lesion Segmentation, Fallah H. Najjar, Karrar A. Kadhim, Farhan Mohamed, Mohd Shafry Mohd Rahim, Asniyani Nur Haidar Abdullah

Iraqi Journal for Computer Science and Mathematics

Editor's Note: This Resolution notice concludes the investigation initiated by the Expression of Concern (DOI: https://doi.org/10.52866/2788-7421.1378) regarding the Original Article (DOI: https://doi.org/10.52866/2788-7421.1230). The publication timeline is as follows: Original Article → Expression of Concern → Resolution.

Resolution of Expression of Concern:
The editorial team of the Iraqi Journal for Computer Science and Mathematics has completed a thorough post-publication review of the above-mentioned article, the supporting data, and the authors’ responses to the queries raised. Upon careful assessment, we have determined that the concerns have been addressed and clarified to the satisfaction of the editors.
We have found …

A Hybrid Densenet121-Inceptionv3 Model For Multi-Output Race And Gender Classification, Maiwan Bahjat Abdulrazzaq, Mayyadah Ramiz Mahmood, Sardar Hasen Ali, Azar Abid Salih

Iraqi Journal for Computer Science and Mathematics

This research proposes and validates a novel Hybrid DenseNet121-InceptionV3 architecture for robust multi-output demographic classification from facial images, with a focus on optimizing both time efficiency and parameter utilization. The model was trained on a curated subset of the UTKFace dataset comprising 4,000 images, balanced across four racial groups with equal gender distribution. Our hybrid approach processes images through parallel feature extractors, strategically combining DenseNet121's parameter-efficient feature reuse with InceptionV3's multi-scale analysis capabilities. This architectural synergy achieves superior performance while maintaining computational efficiency. Through rigorous 3-fold cross-validation, the hybrid model demonstrated significant advantages in accuracy and training time, achieving 98.35% …

Design And Fpga Deployment Of Quantized Convolutional Spiking Neural Networks For Ecg Arrhythmia Classification, Olamilekan Banjo

Electronic Theses and Dissertations

Wearable ECG monitors enable continuous cardiac surveillance, yet most remain limited to basic heart rate metrics or coarse atrial fibrillation detection, relying on cloud-based analysis that introduces latency, connectivity dependence, and battery drain. Deploying advanced multi-class arrhythmia classification directly on-device is constrained by the tight memory, power, and computational budgets of wearable hardware. This dissertation presents a Quantized Convolutional Spiking Neural Network (QCSNN) for real-time ECG arrhythmia detection on edge hardware, developed across three progressive phases.

Phase 1 introduces a separately trained two-stage QCSNN architecture — a binary classifier cascaded with a four-class classifier — trained directly via surrogate gradient …

Design And Implementation Of Cyber Risk Management In The Indonesian Aviation Sector Based On Nist Csf And Iso/Iec 27002:2022, Annisa Aulia Budianti Qurota'aini, Ira Rosianal Hikmah, Yulial Hikmah

Jurnal Vokasi Indonesia

As technology usage increases, cyberspace in Indonesia has developed significantly, including in Vital Information Infrastructure (VII) sectors such as aviation. However, this advancement introduces potential cyber threats that can disrupt operations. This research aims to design a systematic cyber risk management framework for a navigation authority within the Indonesian aviation sector using the National Institute of Standards and Technology Cybersecurity Framework (NIST CSF) as the primary standard. This research also utilizes national aviation regulations, Center for Internet Security Controls (CIS Controls) v8.0, and ISO/IEC 27002:2022 as supporting frameworks. The research employs a qualitative descriptive approach, gathering data through field observations, …

A Machine-Learning-Based Systematic Framework For Modeling Compression And Recompression Indices For Florida Soils, Michael Morales

Doctoral Dissertations and Master's Theses

This thesis develops a machine-learning framework for estimating the compression index and the recompression index of Florida soils from routinely measured index properties, and reports two studies that build it. Consolidation settlement design requires both indices, and both are obtained from the incremental-loading oedometer test, which occupies a specimen for one to two weeks; the index tests that accompany it are complete within hours. Empirical correlations have filled that interval since the 1950s, but their coefficients are calibrated on specific soil populations and transfer poorly between regions. The first study analyzes 376 consolidation tests compiled for the Florida Department of …

Enhancing Virtual Reality Cockpit Procedure Training With Haptic Feedback, Christian K. Jaedicke

Doctoral Dissertations and Master's Theses

Pilot training is time-consuming and costly, and not all phases require full-flight simulators or actual aircraft. Virtual reality (VR) offers a potential means to reduce cost and duration while supporting practical cockpit procedure training. While prior research in the VR domain suggests that providing haptic feedback can support training of muscular control and increase perceived immersion, it remains unclear whether haptic feedback improves spatial cognition in an unfamiliar VR environment. This study examined whether haptic feedback and cockpit complexity affected response time and position error under limited-visibility, time-constrained conditions in a VR cockpit environment (i.e., a quasi-blindfold cockpit check).

Grounded …