Pointer meters recognition method in the wild based on innovative deep learning techniques by Jiajun Feng, Haibo Luo, Rui Ming

“…This demonstrates its robustness in real scenarios and provides a new idea for recognizing pointers in low-quality images more efficiently and accurately in complex industrial scenarios.…”
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Unit Size Determination for Exploratory Brain Imaging Analysis: A Quest for a Resolution-Invariant Metric by Jihnhee Yu, HyunAh Lee, Zohi Sternberg

“…Defining an adequate unit size is often crucial in brain imaging analysis, where datasets are complex, high-dimensional, and computationally demanding. …”
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HCAP: Hybrid cyber attack prediction model for securing healthcare applications. by Mohanad Faeq Ali, Mohammed Shakir Mohmood, Ban Salman Shukur, Rex Bacarra, Jamil Abedalrahim Jamil Alsayaydeh, Masrullizam Mat Ibrahim, Safarudin Gazali Herawan

“…However, the existing model's efficiency depends on the diversity of data, which leads to computational complexity issues. …”
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A simple validation and screening method for CRISPR/Cas9-mediated gene editing in mouse embryos to facilitate genetically modified mice production. by Dawid Winiarczyk, Hossein Khodadadi, Paweł Leszczyński, Hiroaki Taniguchi

“…We propose herein an evaluation method (cleavage assay - CA) for CRISPR/Cas9-mediated gene editing in preimplantation mouse embryos that allows us to detect mutants efficiently and later on initiate in vivo production without the extensive number of samples needing to be sent for Sanger sequencing and animal usage. …”
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A Resilient Deep Learning Approach for State Estimation in Distribution Grids With Distributed Generation by Ronald Kfouri, Harag Margossian

“…Results demonstrate that our method efficiently solves the DSSE problem—which cannot be solved using conventional methods—and detects and mitigates bad data, further enhancing the reliability of the state estimation results.…”
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Improved Algorithm for Analysis of DNA Sequences Using Multiresolution Transformation by T. M. Inbamalar, R. Sivakumar

“…Existing digital signal processing (DSP) methods provide less accurate and computationally complex solution with greater background noise. Hence, improvements in accuracy, computational complexity, and reduction in background noise are essential in identification of the protein coding regions in the DNA sequences. …”
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Analysis of digital intelligent financial audit system based on improved BiLSTM neural network by Zhu Xincai

“…Traditional auditing methods have difficulties in detecting various financial issues hidden in massive amounts of data. …”
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Early diagnosis of streptococcus cristatus in blood culture-negative infective endocarditis by capture-based metagenomic next-generation sequencing: a case report by Dong Wang, Hui Wang, Dan Zhang, Xinsheng Yan

“…BackgroundInfective endocarditis (IE) is a life-threatening infectious cardiac condition characterized by therapeutic complexity and high mortality rates, for which precise pathogen identification is critical to guide accurate treatment. …”
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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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Quantifying variability associated with high-resolution respirometry in human permeabilized skeletal muscle fibers by Emily J. Ferguson, Justin Bureau, Tanner Stokes, Danielle Nyman, Joel Seigel, Shivam Gandhi, Luca J. Delfinis, Brendon J. Gurd, Christopher G.R. Perry, Chris McGlory

“…Mean average intra- and inter-biopsy CVs for maximal complex I+II-supported, ADP-stimulated mitochondrial respiration were 11.5 % and 9.7 %, respectively. …”
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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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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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A quantum machine learning framework for predicting drug sensitivity in multiple myeloma using proteomic data by M. Priyadharshini, B. Deevena Raju, A. Faritha Banu, P. Jagdish Kumar, V. Murugesh, Oleg Rybin

“…QSVM employs quantum kernels to map data into a higher-dimensional Hilbert space, so that the model can detect complex patterns in MM drug resistance. qPCA reduces dimensionality without loss of important variance, and thus improves computation efficiency. …”
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Optimized fiducial marker placement using B‐spline surface modeling and graph theory for Cyberknife stereotactic body radiotherapy for superficial tumors by Jing Huang, Xianlong Xiong, Cheng Chen, Yuhan Li, Ruijie Wang, Zhitao Dai

“…To enhance the computational efficiency, a kd‐tree spatial indexing structure was integrated with graph theory, specifically the Bron–Kerbosch algorithm for maximal clique detection. …”
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Tip optofluidic immunoassay: Evaluating COVID-19 antibody protection with 1 μL fingertip blood by Xiaotian Tan, Yujuan Chai, Ruihan Li, Binmao Zhang, Hao Li, Jie Zhang, Tianen Zhu, Weishu Wu, Lixiang An, Shi Hu, Bin Yang, Li Wang, Zhenqiu Cao, Hongjiu Zhang, Peng Wang, Lingling Yu, Shan Yin, Xingyu Li, Fei Shao, Jianheng Huang, Jinze Li, Fan Yang, Chao Zhao, Jiajia Guo, Lin Zeng, Dong Liang, Zhengting Zou, Hairong Zheng, Xudong Fan, Liangzhi Xie, Yunlong Cao, Hui Yang

“…TOI achieves a broad dynamic range (3–4 orders of magnitude), high signal-to-noise ratio (∼10,000), and excellent sensitivity for immunoglobulin G (IgG) detection. A renovated version of the rapid in vitro inhibition assay (RIVIA) is incorporated to evaluate neutralizing antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with greater speed and cost-efficiency. …”
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Smart Clove Oil Distillation System using IoT and Ultrasonic Sensors by Ihwana As'ad, Andi Muhammad Rahmatullah, Syahrul Mubarak Abdullah, Fahmi Fahmi, Hariani Ma'tang Pakka, Andiyan Andiyan

“…Furthermore, the modular container design promotes gravity-assisted separation, enhancing energy efficiency and reducing mechanical complexity. The remote monitoring feature allows users to access real-time data on fluid levels and system status, ensuring reliable operation with minimal manual supervision. …”
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Recent Advances in Black Silicon Surface Modification for Enhanced Light Trapping in Photodetectors by Abdulrahman Alsolami, Hadba Hussain, Radwan Noor, Nourah AlAdi, Nada Almalki, Abdulaziz Kurdi, Thamer Tabbakh, Adnan Zaman, Salman Alfihed, Jing Wang

“…We also explore the impact of BSi on the emerging applications in silicon (Si)-based photodetectors, showcasing their potential for pushing the boundaries of light-trapping efficiency. Throughout this review, we critically evaluate the trade-offs between fabrication complexity and performance enhancement, providing valuable insights for future development in this rapidly evolving field. …”
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A Robotic grinding station based on an industrial manipulator and vision system. by Guoyang Wan, Guofeng Wang, Yunsheng Fan

“…The measurements indicate that this system can work stably and efficiently, and the experimental results demonstrate the high accuracy and high efficiency of the proposed method. …”
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APPLICATION OF HYBRID MEMETIC ALGORITHM IN OPTIMAL CONTROL NONLINEAR STOCHASTIC SYSTEMS WITH INCOMPLETE FEEDBACK PROBLEMS by A. V. Panteleev, V. N. Panovskiy

“…Several alternative forms of parametrization are considered: in the form of expansion by Legendre polynomials system and in the form of cosine-waves. The efficiency of the proposed algorithms was analyzed by means of created software complex. …”
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Classification of pulmonary diseases from chest radiographs using deep transfer learning. by Muneeba Shamas, Huma Tauseef, Ashfaq Ahmad, Ali Raza, Yazeed Yasin Ghadi, Orken Mamyrbayev, Kymbat Momynzhanova, Tahani Jaser Alahmadi

“…In clinical practice, diagnosing pulmonary diseases using chest radiographs is challenging due to Overlapping and complex anatomical Structures, variability in radiographs, and their quality. …”
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