RAPID: Redundancy Analysis With Parallelized and Intelligent Distribution by Younwoo Yoo, Hayoung Lee, Seung Ho Shin, Sungho Kang

“…In modern memory architectures, complex spare structures are essential for improving repair rates. …”
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Enhanced Fault Diagnosis in Milling Machines Using CWT Image Augmentation and Ant Colony Optimized AlexNet by Niamat Ullah, Muhammad Umar, Jae-Young Kim, Jong-Myon Kim

“…A contrast enhancement filter is applied to highlight key features, thereby improving the model’s learning and fault detection capability. The enhanced images are fed into a modified AlexNet model with three residual blocks to efficiently extract both spatial and temporal features from the CWT images. …”
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Design of a reliable and coordinated protection strategy for zonal shipboard power systems by Mehdi Mohammadzamani, Iman Sadeghkhani, Majid Moazzami

“…However, the protection of such systems is a challenging task due to their complex topology and the potential for multiple sources of fault. …”
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Hardware Trojan vulnerability assessment in digital integrated circuits using learnable classifiers by Hadi Jahanirad, Mohammad Fathi

“…The wide range of HT types and related insertion strategies makes the HT detection process very complex. Consequently, developing IC design methodologies that are robust against HT insertion would be of great merit. …”
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Enhancing Road Scene Segmentation With an Optimized DeepLabV3+ by Zhe Ren, Libao Wang, Tianming Song, Yihang Li, Jian Zhang, Fengfeng Zhao

“…These experimental results demonstrate a significant improvement in balancing detection capabilities with real-time performance.…”
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Optimizing Cervical Cancer Diagnosis with Feature Selection and Deep Learning by Łukasz Jeleń, Izabela Stankiewicz-Antosz, Maria Chosia, Michał Jeleń

“…The results demonstrate that optimized feature sets, paired with SVM classifiers, achieve classification performance comparable to those of CNNs while significantly reducing computational complexity. This finding underscores the potential of feature reduction techniques in creating efficient diagnostic frameworks. …”
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Critical Role of Surface Properties in Passive Interstitial Fluid Extraction Using Polymeric Hollow Microneedles for Wearable Diagnostics by Ipek Atay, Emel Yilgör, Gürdeniz Neşer, Taher Abbasiasl, M. Baris Yagci, Iskender Yilgör, Levent Beker

“…Abstract Efficient sampling of dermal interstitial fluid (ISF) is essential for continuous monitoring of biomarkers for early detection and management of chronic diseases. …”
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WORKING ANALYSIS OF SPACE TIME TRELLIS CODE ON WIFI MIMO(2X2) SYSTEM OFDM by Wisnu Broto, Noor Suryaningsih, Adhi Mahendra

“…In addition, the application of Orthogonal Frequency Division Multiplexing (OFDM) on MIMO-STC will more efficiently use bandwidth. The Space-Time Trellis Code (STTC) method is one of the diverse techniques in sending data with complex coding so that coding reinforcement is achieved and applied to the OFDM MIMO system. …”
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Automated classification of epileptic seizures using modified one-dimensional convolution neural network based on empirical mode decomposition with high accuracy by Ibtihal Hassan Elshekhidris, Magdi B. M. Amien, Ahmed Fragoon

“…Therefore, to help with patients' long-term assessment and treatment, an effective automatic detection system is required. Traditional methods of machine learning require step of feature extraction by manual which leads to time consuming, for it we modified in one-Dimensional convolution neural network architecture for features extraction and features dimension reduction for makes the classification low computational complexity and more accurate.Methods: In this study, we did a comparison between three methods for classification: support vector machine, artificial neural network and one-dimensional convolution neural network. …”
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Comparative Analysis of Classifiers for the Assessment of Respiratory Disorders Using Speech Parameters by Poonam Shrivastava, Neeta Tripathi, Bikesh Kumar Singh, Bhupesh Kumar Dewangan

“…The conclusion was that the proposed classifiers may provide an aid in the simple assessment of respiratory disorders utilising speech parameters with high efficiency. In the future, the proposed approach can be evaluated for the detection of specific respiratory disorders such as asthma, COPD, etc.…”
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Histopathological Image Analysis Using Deep Learning Framework by Sudha Rani Vupulluri, Jogendra Kumar Munagala

“…Therefore, histologic imaging evaluations must detect breast cancer early. Traditional methods are time-consuming and limit pathologists’ skills. …”
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CerviXpert: A multi-structural convolutional neural network for predicting cervix type and cervical cell abnormalities by Rashik Shahriar Akash, Radiful Islam, SM Saiful Islam Badhon, KSM Tozammel Hossain

“…This study aims to develop CerviXpert, a multi-structural convolutional neural network designed to classify cervix types and detect cervical cell abnormalities efficiently. Methods We introduced CerviXpert, a computationally efficient convolutional neural network model that classifies cervical cancer using images from the publicly available SiPaKMeD dataset. …”
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Improved Hybrid A* Algorithm Based on Lemming Optimization for Path Planning of Autonomous Vehicles by Yong Chen, Yuan Liu, Wei Xu

“…Path planning for autonomous vehicles is a core component of intelligent transportation systems, playing a key role in ensuring driving safety, improving driving efficiency, and optimizing the user experience. To address the challenges of safety, smoothness, and search efficiency in path planning for autonomous vehicles, this study proposes an improved hybrid A* algorithm based on the lemming optimization algorithm (LOA). …”
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Structurally engineered monolithic catalyst for enhanced sunlight-driven degradation of ciprofloxacin in contaminated water systems by Iqra Mazhar, Muhammad Afzaal, Muhammad Altaf, Manzar Sohail, Raja Shahid Ashraf, Abdul-Sattar Nizami

“…The sunlight-assisted photocatalytic degradation efficiency of optimized catalyst exhibited maximum of 78% removal in 70 min, twice the efficiency of pure ZnO/Ni/GF (37%). …”
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Soft, Stretchable, High-Sensitivity, Multi-Walled Carbon Nanotube-Based Strain Sensor for Joint Healthcare by Zechen Guo, Xiaohe Hu, Yaqiong Chen, Yanwei Ma, Fuqun Zhao, Sheng Guo

“…As an assistive device, the accurate monitoring of the user’s joint signals and exoskeleton status using wearable sensors is essential to ensure the efficiency of conducting complex tasks in various scenarios. …”
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Fusion of Visual Attention and Scene Descriptions With Deep Reinforcement Learning for AAV Indoor Autonomous Navigation by Hussein Samma, Ahmed Abubaker, Mubarak Badamasi Aremu, Mohammed Abdel-Nasser, Sami El-Ferik

“…This ensures safe and efficient navigation in complex indoor spaces. The approach was tested in a simulated indoor environment with pedestrians, created using Unreal Engine. …”
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SegAN for Recognition of Caries From 2D-Panoramic X-Ray Images by Parvathaneni Naga Srinivasu, Gorli L. Aruna Kumari, D. Jaya Kumari, Paolo Barsocchi, Akash Kumar Bhoi

“…On the other hand, the discriminator ensures that the output matches realistic segmentation patterns. The SegAN model efficiently handles the local and global contextual information for precise segmentation by considering Pixel-Wise and structural loss measures that assist in better segmentation of complex structures. …”
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Structural and morphological studies of non-covalent functionalization carbon nanotubes wrapped poly(3-hexylthiophene-2,5-diyl) nanocomposites by N. Abdullah, N.M. Nurazzi, I.P. Silverwood, S.K. Matam, S.Z.N. Demon, N.S.N. Sa'aya, N.A. Halim, K.W. Baharin

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Exploring the Determinants of Operational Performance in the Water Supply Sector: A PCA Analysis of Networks, Meters, Raw Water and Operating Costs by Octavia Moise, George Banghiore, Mari-Isabella Stan

“…The water sector is essential for sustainable development, but faces complex challenges arising from climate change, accelerated urbanization, and increasingly stringent economic and environmental demands. …”
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A Systematic Survey of Machine Learning and Deep Learning Models Used in Industrial Internet of Things Security by Ersin Enes Eryılmaz, Erdal Kılıç, Yankı Ertek, Sedat Akleylek

“…IIoT devices vary from sensors to complex industrial robots. Security measures such as patch management, access control, network monitoring, authentication, service isolation, encryption, unauthorized entry detection, and application security are implemented for IIoT networks and devices. …”
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