Vol. 21 No. 3 (2025) | Applied Computer Science

Taming complexity: Generative doppelgangers for stochastic data trends in complex industrial manufacturing systems

Richard NASSO TOUMBA, Maxime MOAMISSOAL SAMUEL, Achille EBOKE, Boniface ONDO, Timothée KOMBE

DOI: https://doi.org/10.35784/acs_7202

1-22

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Kidney disease diagnosis based on artificial intelligence/deep learning techniques

Abeer ALSHIHA, Abdalrahman QUBAA

DOI: https://doi.org/10.35784/acs_7241

23-37

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Pulmonary diseases identification: Deep learning models and ensemble learning

Patrycja KWAŚNIEWSKA, Grzegorz ZIELIŃSKI, Paweł POWROŹNIK, Maria SKUBLEWSKA-PASZKOWSKA

DOI: https://doi.org/10.35784/acs_8015

38-58

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A machine learning approach for evaluating drop impact reliability of solder joints in BGA packaging

Venkata Naga Chandana YANAMURTHY, Venu Kumar NATHI

DOI: https://doi.org/10.35784/acs_7340

59-71

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Prediction of remaining useful life and downtime of induction motors with supervised machine learning

Muhammad Dzulfiqar ANINDHITO, SUHARJITO

DOI: https://doi.org/10.35784/acs_7299

72-86

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An ensemble model for maternal health risk classification in Delta State, Nigeria

Oghenevabaire EFEVBERHA-OGODO, Francisca A. EGBOKHARE, Fidelis O. CHETE

DOI: https://doi.org/10.35784/acs_7313

87-98

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Transforming ERP interfaces in production environments: An empirical evaluation using the User Experience Questionnaire

Anna HAMERA

DOI: https://doi.org/10.35784/acs_7625

99-116

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Systematic drift characterization in differential wheeled robot using external VR tracking: Effects of route complexity and motion dynamics

Stanisław Piotr SKULIMOWSKI, Szymon RYBKA, Bartosz TATARA, Michał Dawid WELMAN

DOI: https://doi.org/10.35784/acs_8089

117-136

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Wireless body area networks: A review of challenges, architecture, applications, technologies and interference mitigation for next-generation healthcare

Akeel Abdulraheem THULNOON, Ahmed Mahdi JUBAIR, Foad Salem MUBAREK, Senan Ali ABD

DOI: https://doi.org/10.35784/acs_7355

137-161

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Fuzzy logic in arrhythmia detection: A systematic review of techniques, applications, and clinical interpretability

Nadjem Eddine MENACEUR, Sofia KOUAH, Derdour MEKHLOUF, Khaled OUANES, Meryam AMMI

DOI: https://doi.org/10.35784/acs_7657

162-181

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Enhancing interpretability in brain tumor detection: Leveraging Grad-CAM and SHAP for explainable AI in MRI-based cancer diagnosis

Nasr GHARAIBEH

DOI: https://doi.org/10.35784/acs_7375

182-197

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Noise source analysis of the nitrogen generation system

Grzegorz BARAŃSKI

DOI: https://doi.org/10.35784/acs_8041

198-209

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Archives

Articles

Taming complexity: Generative doppelgangers for stochastic data trends in complex industrial manufacturing systems

Kidney disease diagnosis based on artificial intelligence/deep learning techniques

Pulmonary diseases identification: Deep learning models and ensemble learning

A machine learning approach for evaluating drop impact reliability of solder joints in BGA packaging

Prediction of remaining useful life and downtime of induction motors with supervised machine learning

An ensemble model for maternal health risk classification in Delta State, Nigeria

Transforming ERP interfaces in production environments: An empirical evaluation using the User Experience Questionnaire

Systematic drift characterization in differential wheeled robot using external VR tracking: Effects of route complexity and motion dynamics

Wireless body area networks: A review of challenges, architecture, applications, technologies and interference mitigation for next-generation healthcare

Fuzzy logic in arrhythmia detection: A systematic review of techniques, applications, and clinical interpretability

Enhancing interpretability in brain tumor detection: Leveraging Grad-CAM and SHAP for explainable AI in MRI-based cancer diagnosis

Noise source analysis of the nitrogen generation system