A Mobile LiDAR-Based Deep Learning Approach for Real-Time 3D Body Measurement by Yongho Jeong, Taeuk Noh, Yonghak Lee, Seonjae Lee, Kwangil Choi, Sujin Jeong, Sunghwan Kim

“…This research, however, utilizes 3D depth information to enhance both accuracy and efficiency. By employing HRNet-based keypoint detection and transfer learning through deep learning, the precise locations of body parts are identified and combined with depth maps to automatically calculate body circumferences. …”
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Epitope-imprinted biomaterials with tailor-made molecular targeting for biomedical applications by Youlu Diao, Jia Gao, Yue Ma, Guoqing Pan

“…Additionally, we discuss the application of epitope-imprinted materials in the recognition and detection of peptides, proteins, and cells. Despite these advancements, challenges such as template complexity, imprinting efficiency, and scalability remain. …”
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Proactive Complaint Management in Public Sector Informatics Using AI: A Semantic Pattern Recognition Framework by Marco Esperança, Diogo Freitas, Pedro V. Paixão, Tomás A. Marcos, Rafael A. Martins, João C. Ferreira

“…The digital transformation of public services has led to a surge in the volume and complexity of informatics-related complaints, often marked by ambiguous language, inconsistent terminology, and fragmented reporting. …”
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Multi-material 3D printed smart floor tiles with triboelectric energy generation and security monitoring by Shidhin Mappoli, Kalyan Ghosh, Martin Pumera

“…The MMP-TENG is integrated with electronics to showcase its capability for remote monitoring in smart home settings to detect real-time fall detection and security monitoring. …”
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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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GPU Ray Tracing for the Analysis of Light Deflection in Inhomogeneous Refractive Index Fields of Hot Tailored Forming Components by Pascal Kern, Max Brower-Rabinowitsch, Lennart Hinz, Markus Kästner, Eduard Reithmeier

“…Although hybrid components are key to meeting modern technical requirements and saving resources, they exhibit complex shrinkage behavior due to differing thermal expansion coefficients. …”
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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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Image quality evaluation of imaging skins, a novel stretchable X-ray detector for intraoperative tumour imaging by Solène Dietsch, Harry Allan, Lukas Lindenroth, Robert Moss, Agostino Stilli, Danail Stoyanov

“…In addition, we examined how the stretching capabilities of these detectors influenced the image quality. Our imaging detection stack demonstrated consistent linearity across various fabrication parameters with the coefficient of determination ( $$R^2$$ ) more than 0.99998, showing that the silicone elastomer does not affect the conversion of the X-ray into light. …”
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Convolutional block attention gate-based Unet framework for microaneurysm segmentation using retinal fundus images by C. B. Vanaja, P. Prakasam

“…However, because of the complex background and varied lighting factors, it is challenging to recognize microaneurysms in fundus images automatically. …”
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Assessment of the applicability of multi-satellite precipitation products on the Loess Plateau over the past four decades by Rui Liu, Liu Yang, Zhengguo Shi, Mengdao Xing

“…The findings indicate that the CPC is the most suitable product for inverting daily precipitation on the LP, with the highest correlation coefficient of 0.774 between CPC and observations, and the highest Probability of Detection of 0.667. …”
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