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A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking desired voltage and less energy consumption through investigating and comparing under random current variations with the minimum number of fitness evaluation less than 20 iterations.

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Publication Date
Sat Jan 10 2015
Journal Name
British Journal Of Mathematics & Computer Science
The Use of Gradient Based Features for Woven Fabric Images Classification
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Publication Date
Fri Dec 01 2023
Journal Name
Ieee Antennas And Wireless Propagation Letters
Stabilized and Fast Method for Compressive-Sensing-Based Method of Moments
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Publication Date
Sat May 24 2025
Journal Name
Iraqi Journal For Computer Science And Mathematics
Intrusion Detection System for IoT Based on Modified Random Forest Algorithm
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An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

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Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Low-Distortion MMSE Estimator for Speech Enhancement Based on Hahn Moments
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

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Publication Date
Fri Jun 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Role of Fasting Mimicking Diet in Farnesoid x Receptor for Suppressing Epithelial-to-Mesenchymal Transition, Cell Cycle Progression, and Viability of Prostate Cancer Cells
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The systemic and resistant nature of metastatic castration-resistant prostate cancers (mCRPC) renders it largely incurable even after intensive multimodal therapy. Proliferation, survival, and epithelial-mesenchymal transition (EMT) are three fundamental events that are deeply linked to carcinogenesis.  Hence, it is necessary to find a new combination of several therapies, targeting those vital mechanisms without causing side effects. Significant research works have shown differential low expression of the metabolic Farnesoid X receptor (FXR) in primary and metastatic prostate cancer suggesting their importance in prostate pathogenesis. Obticholic acid (INT 747), a potent FXR agonist is widely used in primary biliary chola

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Publication Date
Thu Dec 01 2022
Journal Name
International Immunopharmacology
Nanovaccines in cancer immunotherapy: Focusing on dendritic cell targeting
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Publication Date
Tue Feb 05 2019
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Anemia Blood Cell localization Using Modified K- Means Algorithm
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Publication Date
Sun Dec 15 2019
Journal Name
Journal Of Baghdad College Of Dentistry
Angiopoietin-2 Immunohistochemical Expression in Oral Squamous cell Carcinoma
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Background: There are various secreted proteins affecting the prognosis of oral squamous cell carcinoma (OSCC) and one of them is Angiopoietin-2(Ang-2) which is thought to have an essential role in the development and progression of the tumor. Aim of the study: This study was conducted to determine the expression of (Ang-2) in (OSCC) to assess its correlations with clinicopathological parameters of the tumor. Material and Methods: 36 formalin- fixed, paraffin- embedded tissue blocks histologically diagnosed as OSCC were examined for Ang-2 immunohistochemical expression semi quantitively. Results: The expression of Ang-2 was significantly associated with histopathological grade (P value=0.023), while there is no significant association wi

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Publication Date
Sat Apr 05 2025
Journal Name
2025 Ieee 4th International Conference On Computing And Machine Intelligence (icmi)
High-Resolution Location Estimation Utilizing Single-Cell Massive MIMO
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