Veterinary parasitologists: the time has come to talk about the use of the expressions “Protozoan” and “Protista” by José Reck, Alynne da Silva Barbosa, Huarrison Azevedo Santos, Filipe Dantas-Torres, Marcos Rogério André, George Rego Albuquerque

“…Abstract The classification of eukaryotic organisms has evolved significantly over the past years. …”
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Reweighting and analysing event generator systematics by neural networks on high-level features by Amon Furuichi, Sung Hak Lim, Mihoko M. Nojiri

“…Abstract The state-of-the-art deep learning (DL) models for jet classification use jet constituent information directly, improving performance tremendously. …”
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Determination of Burdur Lake`s Area Changes Using Remote Sensing Techniques by Özümcan Alara Kaya, Gordana Kaplan

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Depression recognition using voice-based pre-training model by Xiangsheng Huang, Fang Wang, Yuan Gao, Yilong Liao, Wenjing Zhang, Li Zhang, Zhenrong Xu

“…Additionally, a small fine-tuning network was used as a classification model to output depression classification results. …”
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Coronary heart disease and the course of newly detected prostate cancer by E. V. Pomeshkin, S. V. Popov, I. N. Orlov, A. I. Bragin-Maltsev, S. A. Pomeshkina, O. L. Barbarash

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An efficient hybrid filter-wrapper method based on improved Harris Hawks optimization for feature selection by Jamshid Pirgazi, Mohammad Mehdi Pourhashem Kallehbasti, Ali Ghanbari Sorkhi, Ali Kermani

“…These factors can negatively impact the performance of classification algorithms, necessitating feature selection before classification. …”
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Representing Aspectual Meaning in Sentence: Computational Modeling Based on Chinese by Hongchao Liu, Bin Liu

“…Currently, there is a lack of resources and methods for the identification and validation of the lexical aspect, and this issue is particularly severe for Chinese. From a computational linguistics perspective, the main reason for this shortage stems from the absence of a verified lexical aspect classification system, and consequently, a gold-standard dataset annotated according to this classification system. …”
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One-Shot Learning from Prototype Stock Keeping Unit Images by Aleksandra Kowalczyk, Grzegorz Sarwas

“…One-shot learning techniques mitigate this issue by enabling classification from a single prototype image per product class, thus reducing data annotation efforts. …”
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Classifying High-Dimensional Patterns Using a Fuzzy Logic Discriminant Network by Nick J. Pizzi, Witold Pedrycz

“…To address this pattern classification issue, we present a technique using an adaptive network of fuzzy logic connectives to combine class boundaries generated by sets of discriminant functions. …”
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Mapping Invasive <italic>Spartina alterniflora</italic> Using Phenological Information and Red-Edge Bands of Sentinel-2 Time-Series Data by Yiwei Ma, Li Zhuo, Jingjing Cao

“…These findings provide insights for selecting suitable classification features for <italic>S. alterniflora</italic> extraction studies and serve as an effective control and management of <italic>S. alterniflora</italic>.…”
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CT-based artificial intelligence system complementing deep learning model and radiologist for liver fibrosis staging by Shuang Zheng, Wenao Ma, Lin Mu, Kan He, Jianfeng Cao, Tiffany Y. So, Lei Zhang, Mingyang Li, Yanan Zhai, Feng Liu, Shunlin Guo, Longlin Yin, Liming Zhao, Lei Wang, Heather H.C. Lee, Wei Jiang, Junqi Niu, Pujun Gao, Qi Dou, Huimao Zhang

“…Additionally, we provided solutions to model generalization and human-machine complementarity issues in multi-classification problems.…”
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Evaluation of novel candidate variations and their interactions related to bipolar disorders: Analysis of GWAS data by Acikel C, Aydin Son Y, Celik C, Gul H

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Making Virtual Learning Environment more intelligent: the problem of software agent’s mental state recognition by Dalia Baziukaitė

“…First, we need to train a software agent to recognize its mental state; and second, we want agent to apply optimal strategy to teach learners when it is in some mental state. The second issue we have discussed in [2]. We propose the agent’s ability to recognise its mental state could be based on the classification result to a particular learner. …”
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Explainable one-class feature extraction by adaptive resonance for anomaly detection in quality assurance. by Hootan Kamran, Dionne Aleman, Chris McIntosh, Tom Purdie

“…The complexity of RT treatment plans, coupled with the aforementioned class imbalance issue, introduces a generalization problem that significantly hinders the efficacy of traditional binary classification approaches. …”
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Efficient tuna detection and counting with improved YOLOv8 and ByteTrack in pelagic fisheries by Yuanchen Cheng, Zichen Zhang, Yuqing Liu, Jie Li, Zhou Fu

“…However, existing manual counting methods suffer from issues such as low accuracy and poor timeliness, highlighting the urgent need for an efficient and automated solution. …”
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Stakeholder Relationships in the Framework of R&D-based Startups: Evidence from Turkey by Elif Kalayci

“…Then, it presents the methodology, classification and analysis of in-depth interviews with the founders of R&D-based startups, which help justify the use of a qualitative approach. …”
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Wave propagation-based tests for concrete piles – an overview by Reham Samaan, Abdelsalaam Mokhtar, Mohamed Saafan, Ahmed Ebid

“…The review highlights significant issues in pile integrity assessment involving the influence of soil conditions, geometric changes, and material variability on test outcomes. …”
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Spatiotemporal characteristics of the apparent optical spectrum in the coastal waters of Leizhou Peninsula and their comparative analysis by Yongze Li, Xia Chai, Fengcheng Guo, Xiong Sun, Zhaohui Cheng, Dongyang Fu, Dazhao Liu, Dazhao Liu

“…IntroductionThe coastal waters of the Leizhou Peninsula, as an important ecological transition zone in the northern South China Sea, face water quality issues that urgently require effective monitoring methods.MethodsBased on data from 188 stations across four seasons from 2020-2024, this study innovatively proposes a quantile statistical classification method based on mean and standard deviation, and compares results with typical bays at similar latitudes globally.ResultsThe research classifies regional water spectral types into four categories: Type I (17.22%) with high reflection narrow peaks at 570 nm; Type II (35.10%) featuring broad peaks at 540-560 nm; Type III (27.81%) showing gentle distribution across 500-570 nm; and Type IV (19.87%) with decreasing reflectance as wavelength increases, peaking around 500 nm.DiscussionResults indicate this region is dominated by mixed turbid waters (Types II and III accounting for 62.91%), providing scientific basis for water quality monitoring, aquaculture planning, algal bloom identification, and marine functional zoning, thus promoting regional marine ecological protection and sustainable resource utilization.…”
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CXR-Seg: A Novel Deep Learning Network for Lung Segmentation from Chest X-Ray Images by Sadia Din, Muhammad Shoaib, Erchin Serpedin

“…Despite progress, these issues highlight the need for improved approaches to overcome segmentation difficulties and enhance diagnostic reliability. …”
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How Predictable Is Electric Vehicle Adoption? Exploring the Broader Role of Renewables in Transportation Using a Data-Driven Approach by Simona-Vasilica Oprea, Adela Bara

“…This study harnesses data from a questionnaire carried out in May 2022 from the Pew Research Center to explore energy sources, climate change issues and factors influencing the adoption of Electric Vehicles (EVs). …”
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