Clinical Evaluation of a Rapid Reciprocal-Flow PCR Assay and Real-Time PCR Assay with Quenching Probe for Detection of <i>Mycobacterium tuberculosis</i> Complex by Kosuke Kosai, Keisuke Matsumoto, Takahisa Ishikawa, Yasuhide Kawamoto, Norihiko Akamatsu, Kenji Ota, Fujiko Mitsumoto-Kaseida, Norihito Kaku, Hiroo Hasegawa, Koichi Izumikawa, Hiroshi Mukae, Katsunori Yanagihara

“…This study investigated the diagnostic efficiencies of two assays for the detection of <i>Mycobacterium tuberculosis</i> complex: (1) the reciprocal-flow real-time polymerase chain reaction (PCR)-based GeneSoC assay and (2) the real-time PCR based GENECUBE MTB assay with quenching probe. …”
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Simulation of Patch Field Effect in Space-Borne Gravitational Wave Detection Missions by Mingchao She, Xiaodong Peng, Li-E Qiang

“…This paper presents a novel boundary element partitioning and octree-based simulation algorithm to address these limitations, enabling efficient simulation of both electrostatic and geometric impacts of patch fields with low spatiotemporal complexity (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>n</mi><mo>)</mo></mrow></semantics></math></inline-formula>). …”
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GA4RF: An Effective Fall Detection System Through Optimizing Random Forest Hyperparameters Using Genetic Algorithm With Mobile Sensor Data by Ha-Nam Nguyen, Hong-Lam Le, Ngo-Thi-Thu-Trang, Duc-Nhan Nguyen

“…Additionally, we select a chromosome structure focusing on three hyperparameters to effectively narrow the search space, reducing computational complexity while maintaining high detection performance. …”
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Fast recursive algorithm for implementation of MIMO ZF-SIC detection by Zuo-liang YIN, Xing-peng MAO, Qin-yu ZHANG, Nai-tong ZHANG

“…To reduce the complexity of the zero-forcing(ZF)detection with successive interference cancellation(SIC)in a Vertical Bell Labs layered space-time(V-BLAST)systems,a computationally efficient recursive algorithm was proposed.A fast implementation of the proposed algorithm was developed and its complexity was analyzed in detail.Theoretical analysis and simulations demonstrate significant advantages of the proposed algorithm over the fast recursive algorithm (FRA)on complexity,practicability and storage requirements.Moreover,its performance on symbol error rate(SER)is close to optimal under practical conditions.These advantages make the proposed algorithm more efficient and practical.…”
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Multi-Feature Fusion-Based Speech Disorder Classification Using MobileNetV3-EfficientNetB7, Linformer-Performer, and SHAP-Aware XGBoost by Abdul Rahaman Wahab Sait, Suresh Sankaranarayanan, P. Gouthaman

“…Traditional speech disorders (SD) detection relies on subjective analysis, resulting in inconsistent outcome. …”
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Anomaly Detection in Industrial Machine Sounds Using High-Frequency Features and Gate Recurrent Unit Networks by Thi-Thu-Huong Le, Andro Aprila Adiputra, Jiwon Yun, Howon Kim

“…Detecting anomalies in industrial sound is critical for maintaining operational efficiency, preventing costly equipment failures, and ensuring workplace safety. …”
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The coupling of a high-efficiency aerosol collector with electrospray ionisation–Orbitrap mass spectrometry as a novel tool for real-time chemical characterisation of fine and ultr... by Y.-S. Lau, Z. Ristovski, B. Miljevic

“…The proposed setup consists of a custom-built high-efficiency aerosol collector (HEAC) used to collect aerosol samples into a working fluid and an electrospray ionisation (ESI) Orbitrap mass spectrometer (MS) for the subsequent chemical analysis of the liquid sample. …”
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Refined Monitoring of Water Bodies in Built-Up Areas and Analysis and Evaluation of Water Color Characteristics in Complex Urban Backgrounds by Bin Li, Yong Xie, Zui Tao, Wen Shao, Gan Qin

“…With the rapid construction and development of cities in China, urban water environment changes and water quality monitoring face increasingly complex challenges. Water body extraction in complex urban settings is susceptible to environmental disturbances, reducing monitoring accuracy and efficiency. …”
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A new three-dimensional mesh modeling method for geological bodies containing complex faults in geological engineering by Wenli Gao, Xinming Lu, Shengzhe Hou, Tianyu Zhang, Wenting Liu

“…This strategy transforms the integration of complex three-dimensional models into a triangulation problem for simple two-dimensional polygons, ensuring topologically consistent and computationally efficient merging. …”
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TWO-PARAMETER IRT MODEL APPLICATION TO ASSESS PROBABILISTIC CHARACTERISTICS OF PROHIBITED ITEMS DETECTION BY AVIATION SECURITY SCREENERS by A. K. Volkov, D. V. Aidarkin, A. K. Volkov

“…The main drawback is the complexity of ICAO recommendations implementation concerning taking into account of shadow x-ray image complexity factors during preparation and evaluation of prohibited items detection efficiency by aviation security screeners. …”
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Hybrid Deep Learning Approach for Accurate Detection and Multiclass Classification of Broken Conductor Faults in Power Distribution Systems by Firas Saadoon Mohammed Al-Jumaili, Mustafa Onat

“…The developed CVNN framework was built with TensorFlow&#x2019;s Sequential API, which provided efficient computing of complex-valued inputs and weights and, thus, the proper handling of the intricate signals often encountered in power systems. …”
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GhostConv+CA-YOLOv8n: a lightweight network for rice pest detection based on the aggregation of low-level features in real-world complex backgrounds by Fei Li, Yang Lu, Qiang Ma, Shuxin Yin, Rui Zhao

“…Deep learning models for rice pest detection often face performance degradation in real-world field environments due to complex backgrounds and limited computational resources. …”
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Prediction of sediment-water partition coefficients for pesticides in real river based on energy lattice points by Zhoubing Huang, Zhenqin Zhao, He Yu, Lu Sun, Dali Sun, Jianzhong Cheng, Qinghai Zhang, Chaoxuan Liao

“…Predicting the sorption coefficients of pesticides in the real environment is a complex and challenging task. …”
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Cross-attention swin-transformer for detailed segmentation of ancient architectural color patterns by Lv Yongyin, Yu Caixia

“…Traditional approaches, including convolutional neural networks (CNNs) and standard transformer-based models, have achieved significant success; however, they often face challenges in capturing fine-grained details and maintaining efficiency across diverse datasets. These methods struggle with balancing precision and computational efficiency, especially when dealing with complex patterns and high-resolution images.MethodsTo address these limitations, we propose a novel segmentation model that integrates a hierarchical vision transformer backbone with multi-scale self-attention, cascaded attention decoding, and diffusion-based robustness enhancement. …”
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Ecological network construction and community resilience analysis of nocturnal birds: a case study of Hangzhou City, Zhejiang Province, China by Yang Jin, Mingkan Zhang, Danying Yan, Kun Li, Chao Zhou, Xi Chen

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Orthogonal Frequency Division Multiplexing With Generalized Joint Index Modulation by Zeng Hu, Yanke Che, Jing Wang, Xuhong Peng, Chaobo He, Dehuan Wan, Yun Liu, Ting Wu

“…In this paper, we propose a generalized joint OFDM-IM scheme, which performs joint modulation on multiple subsubblocks divided from a subblock, to achieve higher spectral efficiency (SE) and lower complexity for both modulation and detection processes. …”
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A fuzzy-optimized multi-level random forest (FOMRF) model for the classification of the impact of technostress by Gabriel James, Ifeoma, David, John, Samuel, Enefiok, Imeh Umoren, Ubong Etuk, Aloysius, Anietie, Saviour, Chikodili

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Reliability and Quality of Complex Systems by S.M. Gerashchenko, A.D. Semenov, S.I. Gerashchenko, N.V. Goryachev, I.M. Rybakov

A Novel Approach to Classify Brain Tumor with an Effective Transfer Learning based Deep Learning Model by Hafiz Muhammad Tayyab Khushi, Tehreem Masood, Arfan Jaffar, Sheeraz Akram

“…We need an autonomous, intelligent system to detect brain cancers early and accurately. This study proposes a pre-trained EfficientNetb4 model with an adjusttable learning rate and custom callback to efficiently classify tumors. …”
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A comparative study of neural network pruning strategies for industrial applications by Amirhossein Douzandeh Zenoozi, Laura Erhan, Antonio Liotta, Lucia Cavallaro

“…IntroductionIn recent years, Deep Learning (DL) and Artificial Neural Networks (ANNs) have transformed industrial applications by providing automation in complex tasks such as anomaly detection and predictive maintenance. …”
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