MSSUTop-: Determining the Minimum Scan Scope for UTop- Query over Uncertain Data by Zhibin Zhao, Lan Yao, Ge Yu, Yubin Bao, Zhengbing Ma

“…In this direction, several optimized algorithms have been developed. However, uncertain databases are different in data distributions under different scoring functions, which has significant influence on the performance of the existing optimizing algorithms. …”
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A detailed comparison of analysis processes for MCC-IMS data in disease classification-Automated methods can replace manual peak annotations. by Salome Horsch, Dominik Kopczynski, Elias Kuthe, Jörg Ingo Baumbach, Sven Rahmann, Jörg Rahnenführer

“…We determine which specific algorithmic combinations lead to high AUC values in disease classifications across the different medical application scenarios.…”
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Design Principles for Reinforcement Learning in Congestion Control Environments by Lincoln Kamau Kiarie, Mahsa Derakhshani, Konstantinos G. Kyriakopoulos

“…This paper evaluates different design strategies for developing the state space and how they contribute to learning. …”
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Comparison of digital loudspeaker - equalization techniques by P. Dziechciński

“…On the basis of objective assessments of 32 equalization systems carried out for two stereophonic pairs of loudspeaker systems algorithms yielding the best results for each of the tested filter structures (FIR, IIR, WFIR and WIIR) were selected and evaluated by listening tests. …”
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Implications of variability in triceps surae muscle volumes on peak lower limb muscle forces during human walking. by Christine M Harper, Adam D Sylvester, Patricia Ann Kramer

“…Maximum muscle forces were calculated using inverse dynamics and an algorithm to solve the muscle redundancy problem in the AnyBody Modeling System. …”
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On the electron agyrotropy during rapid asymmetric magnetic island coalescence in presence of a guide field by E. Cazzola, M. E. Innocenti, M. V. Goldman, D. L. Newman, S. Markidis, G. Lapenta

“…We study the departure from isotropic and gyrotropic behavior by means of different robust detection algorithms proposed in the literature. …”
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Analytical Validation of Wrist-Worn Accelerometer-Based Step-Count Methods during Structured and Free-Living Activities by Robert T. Marcotte, Shelby L. Bachman, Yaya Zhai, Ieuan Clay, Kate Lyden

“…Four open-source methods implementing different algorithmic approaches were applied to CPIW data to derive step counts. …”
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Stability indicators in network reconstruction. by Michele Filosi, Roberto Visintainer, Samantha Riccadonna, Giuseppe Jurman, Cesare Furlanello

“…The number of available algorithms to infer a biological network from a dataset of high-throughput measurements is overwhelming and keeps growing. …”
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Epidemiology of Polytrauma at a Teaching Hospital in Northern Ghana: A Cross-Sectional Study by Anwar Sadat Seidu, Abdul Rauf Alhassan, Alexis Dun Bo-ib Buunaaim

“…This study aimed to evaluate the epidemiological profile of polytrauma and outline the distribution of extremity fractures among cases in Northern Ghana. …”
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Development and validation of novel machine learning-based prognostic models and propensity score matching for comparison of surgical approaches in mucinous breast cancer by Chunmei Chen, Jundong Wu, Yutong Fang, Yong Li, Qunchen Zhang

“…Cox analysis and propensity score matching were applied to evaluate survival differences between MBC patients undergoing mastectomy and breast-conserving surgery (BCS). …”
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Comprehensive analysis of IRF8-related genes and immune characteristics in lupus nephritis by Zhibin Yu, Chenghui Zheng, Yilun Wang

“…A diagnostic classifier was built using the RandomForest method to evaluate the diagnostic potential of selected key genes. …”
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Comparative study of IoT- and AI-based computing disease detection approaches by Wasiur Rhmann, Jalaluddin Khan, Ghufran Ahmad Khan, Zubair Ashraf, Babita Pandey, Mohammad Ahmar Khan, Ashraf Ali, Amaan Ishrat, Abdulrahman Abdullah Alghamdi, Bilal Ahamad, Mohammad Khaja Shaik

“…However, no comprehensive survey has been conducted on integrated IoT- and computing-based systems that deploy deep learning for disease detection. This study evaluated different machine learning and deep learning algorithms and their hybrid and optimized algorithms for IoT-based disease detection, using the most recent papers on IoT-based disease detection systems that include computing approaches, such as cloud, edge, and fog. …”
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dmQAR: Mapping Metacognition in Digital Spaces onto Question–Answer Relationship by Brittany Adams, Nance S. Wilson, Gillian E. Mertens

“…In response to the nonlinear, multimodal, and algorithmically curated nature of online texts, the dmQAR Framework scaffolds purposeful metacognitive questioning to support comprehension, evaluation, and critical engagement. …”
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The effect of lipid accumulation product and its interaction with other factors on hypertension risk in Chinese Han population: A cross-sectional study. by Jian Song, Yingying Zhao, Sumei Nie, Xue Chen, Xuesen Wu, Jing Mi

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Designing and Interpreting a Mathematical Programming Language by Hüseyin Pehlivan

“…To illustrate the use of the language with code samples, several mathematical algorithms that include calculations on different sequences of numbers, are programmed and interpreted.…”
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Experimental verification of a methodology for Monte Carlo modeling of multileaf collimators using the code Geant4 by Alex Cristóvão Holanda de Oliveira, José Wilson Vieira, Miriam Zarza Moreno, Fernando Roberto Andrade Lima

“…Among the many algorithms developed for evaluation of dose distributions in radiotherapy, the Monte Carlo methods provide more realistic results. …”
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Automatic identification of clinically important Aspergillus species by artificial intelligence-based image recognition: proof-of-concept study by Chi-Ching Tsang, Chenyang Zhao, Yueh Liu, Ken P. K. Lin, James Y. M. Tang, Kar-On Cheng, Franklin W. N. Chow, Weiming Yao, Ka-Fai Chan, Sharon N. L. Poon, Kelly Y. C. Wong, Lianyi Zhou, Oscar T. N. Mak, Jeremy C. Y. Lee, Suhui Zhao, Antonio H. Y. Ngan, Alan K. L. Wu, Kitty S. C. Fung, Tak-Lun Que, Jade L. L. Teng, Dirk Schnieders, Siu-Ming Yiu, Susanna K. P. Lau, Patrick C. Y. Woo

“…In this proof-of-concept study, using 2813, 2814 and 1240 images from four clinically important Aspergillus species for training, validation and testing, respectively; the performances and accuracies of automatic Aspergillus identification using colonial images by three different convolutional neural networks were evaluated. …”
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Binary Chaotic White Shark Optimizer for the Unicost Set Covering Problem by Pablo Zúñiga-Valenzuela, Broderick Crawford, Felipe Cisternas-Caneo, Eduardo Rodriguez-Tello, Ricardo Soto, José Barrera-Garcia, Fernando Lepe-Silva

“…This study introduces a binary White Shark Optimizer (WSO) enhanced with V3 transfer functions, elitist binarization, and chaotic maps. To evaluate algorithm performance, we employ the Relative Percentage Deviation (RPD), which measures the percentage difference between the obtained solutions and optimal values. …”
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SpeakerNet for Cross-lingual Text-Independent Speaker Verification by Hafsa HABIB, Huma TAUSEEF, Muhammad Abuzar FAHIEM, Saima FARHAN, Ghousia USMAN

“…The emergence of machine learning algorithms provides an easy and economical solution to authentication problems. …”
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Advancements in Multi-Objective Optimization for Planning and Management of Multi-Energy Systems by Marco Tangi, Alessandro Amaranto

“…The work presented herein aims to develop modelling frameworks to explore of configurations of Multi-energy systems according to non-comparable objectives and extract trade-off solutions through optimization algorithms. Three different methodologies are presented, integrating the single-objective configuration model CALLIOPE with multi-objective algorithms for exploring the decision space. …”
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