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Retraction Notice: Capsule Network Model For Detecting Spoofing Attack In The Internet Of Medical Things (Iomt), Iraqi Journal For Computer Science And Mathematics Feb 2026

Retraction Notice: Capsule Network Model For Detecting Spoofing Attack In The Internet Of Medical Things (Iomt), Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF RETRACTION FOR: Alsharaiah, Mohammad A.; Almaiah, Mohammed Amin; Obeidat, Mansour; and Shehab, Rami (2025) ``Capsule Network Model for Detecting Spoofing Attack in the Internet of Medical Things (IoMT),'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 3, Article 35. DOI: https://doi.org/10.52866/2788-7421.1306.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss3/35.

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Retraction Notice: Automated Diagnosis Of Orthopedic Patients With Vertebral Column Disorders Using Advanced Mathematical Modeling, Iraqi Journal For Computer Science And Mathematics Feb 2026

Retraction Notice: Automated Diagnosis Of Orthopedic Patients With Vertebral Column Disorders Using Advanced Mathematical Modeling, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF RETRACTION FOR: Feng, Chen; Sun, Zhenhua; Dai, Xinheng; and Wen, Hongli (2025) ``Automated Diagnosis of Orthopedic Patients with Vertebral Column Disorders Using Advanced Mathematical Modeling,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 3, Article 34. DOI: https://doi.org/10.52866/2788-7421.1304.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss3/34.

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Retraction Notice: Analysis Of Energy Sector Co2 Emanations Using Wavelet-Based Numerical Technique, Iraqi Journal For Computer Science And Mathematics Feb 2026

Retraction Notice: Analysis Of Energy Sector Co2 Emanations Using Wavelet-Based Numerical Technique, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF RETRACTION FOR: R., Yeshwanth and S., Kumbinarasaiah (2025) ``Analysis of Energy Sector CO2 Emanations Using Wavelet-Based Numerical Technique,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 4, Article 2. DOI: https://doi.org/10.52866/2788-7421.1313.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss4/2.

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Retraction Notice: Ai-Driven Flood Prediction, Monitoring, And Warning Systems: Design, Evaluation, And Simulation, Iraqi Journal For Computer Science And Mathematics Feb 2026

Retraction Notice: Ai-Driven Flood Prediction, Monitoring, And Warning Systems: Design, Evaluation, And Simulation, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF RETRACTION FOR: Alkharabsheh, Abdel Rahman A. and Momani, Lina M. (2025) ``AI-Driven Flood Prediction, Monitoring, and Warning Systems: Design, Evaluation, and Simulation,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 4, Article 8. DOI: https://doi.org/10.52866/2788-7421.1337.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss4/8.

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Retraction Notice: Adaptive Crossover And Mutation Mechanisms For Enhanced Lpb Algorithm Performance, Iraqi Journal For Computer Science And Mathematics Feb 2026

Retraction Notice: Adaptive Crossover And Mutation Mechanisms For Enhanced Lpb Algorithm Performance, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF RETRACTION FOR: Ahmed, Abbas M. and Rashid, Tarik A. (2025) ``Adaptive Crossover and Mutation Mechanisms for Enhanced LPB Algorithm Performance,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 3, Article 48. DOI: https://doi.org/10.52866/2788-7421.1323.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss3/48.

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Retraction Notice: Accurate Electrocardiogram Classification Of Heart Disease Using Deep Learning Network, Iraqi Journal For Computer Science And Mathematics Feb 2026

Retraction Notice: Accurate Electrocardiogram Classification Of Heart Disease Using Deep Learning Network, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF RETRACTION FOR: Saleh, Hadeel M.; Ahmed, Sahar Hamad; and Mahmoud, Akeel Sh. (2025) ``Accurate Electrocardiogram Classification of Heart Disease Using Deep Learning Network,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 2, Article 18. DOI: https://doi.org/10.52866/2788-7421.1259.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss2/18.

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Retraction Notice: A Review Of Breast Cancer Histological Image Classification: Challenges And Limitations, Iraqi Journal For Computer Science And Mathematics Feb 2026

Retraction Notice: A Review Of Breast Cancer Histological Image Classification: Challenges And Limitations, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF RETRACTION FOR: Jassam, Israa Faisal; Mukhlif, Abdulrahman Abbas; Nafea, Ahmed Adil; Tharthar, Mustafa Adnan; and Khudhair, Ahmed Isam (2025) ``A Review of Breast Cancer Histological Image Classification: Challenges and Limitations,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 1, Article 1. DOI: https://doi.org/10.52866/2788-7421.1232.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss1/1.

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Retraction Notice: A Quantum Convolutional Neural Network Approach For Early And Accurate Diagnosis Of Parkinson's Disease, Iraqi Journal For Computer Science And Mathematics Feb 2026

Retraction Notice: A Quantum Convolutional Neural Network Approach For Early And Accurate Diagnosis Of Parkinson's Disease, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF RETRACTION FOR: Ibrahim, Aiesha Mahmoud; Mohammed, Mazin Abed; and Al-Boridi, Omar (2025) ``A Quantum Convolutional Neural Network Approach for Early and Accurate Diagnosis of Parkinson's Disease,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 3, Article 13. DOI: https://doi.org/10.52866/2788-7421.1288.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss3/13.

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Retraction Notice: A Novel Scheme To Optimize Lsb Steganography Based On A Logistic Chaotic Map And Genetic Algorithm, Iraqi Journal For Computer Science And Mathematics Feb 2026

Retraction Notice: A Novel Scheme To Optimize Lsb Steganography Based On A Logistic Chaotic Map And Genetic Algorithm, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF RETRACTION FOR: Laila, Dena Abu; obeidt, Ibrahim Moh'd; Aljaidi, Mohammad; Almaiah, Mohammed Amin; AlBourini, Muneer; Al-Na'amneh, Qais; Samara, Ghassan; Shehab, Rami; and Momani, Khaled (2025) ``A Novel Scheme to Optimize LSB Steganography Based on a Logistic Chaotic Map and Genetic Algorithm,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 2, Article 24. DOI: https://doi.org/10.52866/2788-7421.1265.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss2/24.

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Retraction Notice: A Novel Benchmarking Framework For Selecting The Best Deep Learning Model Diagnosing Covid-19 Based On New Development For Dual Mcdm Methods, Iraqi Journal For Computer Science And Mathematics Feb 2026

Retraction Notice: A Novel Benchmarking Framework For Selecting The Best Deep Learning Model Diagnosing Covid-19 Based On New Development For Dual Mcdm Methods, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF RETRACTION FOR: Salih, Mahmood M.; Muhsen, Yousif Raad; Ahmed, M.A.; Ismael, Reem D.; Shuwandy, Moceheb Lazam; and Al-qaysi, Z.T. (2025) ``A Novel Benchmarking Framework for Selecting the Best Deep Learning Model Diagnosing COVID-19 Based on New Development for Dual MCDM Methods,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 3, Article 2. DOI: https://doi.org/10.52866/2788-7421.1276.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss3/2.

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Retraction Notice: A Group Decision-Making For Selecting Multi-Deep Face Recognition Models, Iraqi Journal For Computer Science And Mathematics Feb 2026

Retraction Notice: A Group Decision-Making For Selecting Multi-Deep Face Recognition Models, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF RETRACTION FOR: Alazzawi, Abdulbasit; Yas, Qahtan M.; and Albayati, Burhan (2025) ``A Group Decision-Making for Selecting Multi-Deep Face Recognition Models,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 2, Article 21. DOI: https://doi.org/10.52866/2788-7421.1262. Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss2/21.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 12, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 12, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 16, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 16, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 20, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 20, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 34, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 34, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 76, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 76, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Bulk Absorber Acoustic Characterization Via The Two-Cavity Impedance Tube Methoda), Anthony Ciletti, Janith Godakawela, Martha Brown, Bhisham Sharma Feb 2026

Bulk Absorber Acoustic Characterization Via The Two-Cavity Impedance Tube Methoda), Anthony Ciletti, Janith Godakawela, Martha Brown, Bhisham Sharma

Michigan Tech Publications

The primary goal of this study is to investigate and refine the two-cavity impedance tube method for acoustic characterization of bulk porous materials, specifically addressing previously unexplained inaccuracies in the prediction of surface impedance and absorption coefficients. Unlike the conventional two-thickness approach, the two-cavity method requires only one sample thickness and involves conducting measurements at various air cavity depths behind the sample. The initial analyses revealed previously unidentified numerical instabilities, resulting in anomalous predictions of sound absorption at specific frequencies. Through systematic investigation and use of calculated data, the numerical origins of these anomalies are uncovered and a practical solution, …

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 11, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 11, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 13, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 13, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 14, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 14, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 15, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 15, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 17, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 17, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 18, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 18, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 23, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 23, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 26, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 26, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 28, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 28, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 30, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 30, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 35, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 35, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 36, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 36, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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Wads 3d Object Detection Dataset (Wads-3d) - Sequence 37, Yiming Yang, Jeremy P. Bos Feb 2026

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 37, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

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