Genome-wide comparative analysis of variability and population structure between autochthonous Turkish chicken breeds and commercial hybrid lines by Eymen Demir, Bahar Argun Karsli, Demir Özdemir, Umit Bilginer, Huriye Doğru, Sarp Kaya, Veli Atmaca, Nimet Tufan, Ebru Demir, Taki Karsli

“…The negative inbreeding coefficient values occurring due to random mating were observed in DNZ and GRZ chicken breeds, while this value was estimated at 0.118 in the layer hybrid line. …”
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Integrating infiltration processes in hybrid downscaling methods to estimate sub-surface soil moisture by Mo Zhang, Yong Ge, Jianghao Wang

“…This study aims to integrate infiltration processes into downscaling models to predict 1-km multi-layer soil moisture, while comparing performance of nonlinear and linear models, and evaluating RK improvements. …”
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Transfer Kernel Extreme Learning Machine Based on Bidirectional Cross Domain Approximation by Yuanxiao Zeng, Huimin Li, Yanbing Song

“…Kernel extreme learning machine (KELM) not only inherits the high learning efficiency of the traditional extreme learning machine (ELM), but also mitigates the instability caused by random initialization of input layer parameters, thus establishing its success as a machine learning model. …”
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Fault Diagnosis Systems for Robots: Acoustic Sensing-Based Identification of Detached Components for Fault Localization by Woonghee Yeo, Mitsuharu Matsumoto

“…Frequency-domain features were extracted using the Fast Fourier Transform (FFT), and classification was performed using five machine learning models: Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), XGBoost, and Multi-Layer Perceptron (MLP). …”
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Statistical and machine learning models for predicting university dropout and scholarship impact. by Stephan Romero, Xiyue Liao

“…The predictive classifiers evaluated are Lasso regression, generalized additive model, random forest, XGBoost and single-layer neural network. …”
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Predicting the Severity of COVID-19 Respiratory Illness with Deep Learning by Connor Shorten, Taghi M. Khoshgoftaar, Javad Hashemi, Safiya George Dalmida, David Newman, Debarshi Datta, Laurie Martinez, Candice Sareli, Paula Eckard

“…We report train-test performance of a Deep Multi-Layer Perceptron (MLP) to predict the severity of respiratory analysis on a one-hot encoded scale of 5 labels. …”
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Few-shot English text classification method based on graph convolutional network and prompt learning by Yunfei Jin

“…Through random sampling on the three data sets of THUCNews, SHNews and Toutiao, a few-shot training set and a verification set are formed for the experiment. …”
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Tool wear prediction based on XGBoost feature selection combined with PSO-BP network by Zhangwen Lin, Yankun Fan, Jinling Tan, Zhen Li, Peng Yang, Hua Wang, Weiwei Duan

“…In order to solve the problem of input feature selection and parameter selection in BP neural network, a double-layer programming model of input feature and parameter selection is established, which is solved by XGBoost and PSO. …”
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WiFi Indoor Positioning Based on EGA-PF and Fernet Algorithm by Yanchun Wang, Shaoye Sun, Fengjuan Miao, Ying Xia

“…Secondly, the above algorithms reflect the problem of large system variance and unstable results when dealing with too much noise or incomplete data. In this regard, the random sampling and resampling techniques of the particle filtering (PF) algorithm are utilized for secondary optimization of the selection of the GA. …”
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Time to failure prediction for MLCCs: A machine learning approach based on leakage current data by Tianyu Jiang, Jincheng Qin, Faqiang Zhang, Mingcao Li, Xiaolian Yan, Mingsheng Ma, Yongxiang Li, Zhifu Liu

“…The development of modern electronics poses challenges to the long-term reliability of multi-layer ceramic capacitors (MLCCs), especially under extreme conditions. …”
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Quantitative Defect Analysis in CVD‐Grown Monolayer MoS2 via In‐Plane Raman Vibration by Moha Feroz Hossen, Sachin Shendokar, Md. Arifur Rahman Khan, Shyam Aravamudhan

“…The Raman 𝐴1g vibration trend is random, influenced by both restoring force constant and mass. …”
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Certified Robustness of Antenna Selecting Neural Networks for Massive MIMO Wireless Communications by Jaekwon Kim, Hyo-Sang Lim, Kwanghoon Choi

“…Additionally, in our antenna selection setting, we observe that removing monotonic activations in the final layer improves certified robustness.…”
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Enhancing explainability in pacu fish image segmentation using saliency maps and combined explainable AI methods by Juliana da C. Feitosa, Fabrício M. Batista, Juliana C.F. Catharino, Milena V. Freitas, Diogo T. Hashimoto, João Paulo Papa, José Remo F. Brega

“…We compare and evaluate four XAI methods - Grad-CAM, Saliency Map, CNN Filters, and Layer Grad-CAM - using pixel perturbation techniques applied in 100 fish images. …”
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A Comparative Study of Ensemble Machine Learning and Explainable AI for Predicting Harmful Algal Blooms by Omer Mermer, Eddie Zhang, Ibrahim Demir

“…This study employed multiple ensemble ML models, including random forest (RF), deep forest (DF), gradient boosting (GB), and XGBoost, and compared their performance against individual models, such as support vector machine (SVM), decision tree (DT), and multi-layer perceptron (MLP). …”
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EmbryoNet-VGG16 framework for deep learning-based embryo classification with Otsu segmentation by M. Saraniya, J. Anitha Ruth

“…The network contains specialised convolutional layers that identify important quality indicators through the analysis of border characteristics and structural integrity. …”
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Power Adaptation for Optimizing Secrecy Energy Efficiency in NOMA-Enabled Underlay Cognitive Radio Networks and DNN-Based Evaluation by P. P. Hema, A. V. Babu

“…Physical layer security (PLS) has emerged as an innovative security measure for wireless networks, augmenting the prevailing cryptography-based methods. …”
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Separation of Body and Surface Wave Background Noise and Passive Seismic Interferometry Based on Synchrosqueezed Continuous Wavelet Transform by Xiaolong Li, Fengjiao Zhang, Zhuo Xu, Xiangbo Gong

“…Passive seismic interferometry is a technique that reconstructs virtual seismic records using ambient noise, such as random noise or microseisms. The ambient noise in passive seismic data contains rich information, with surface waves being useful for the inversion of shallow subsurface structures, while body waves are employed for deep-layer inversion. …”
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Abundance and co-occurrence of extracellular capsules increase environmental breadth: Implications for the emergence of pathogens. by Olaya Rendueles, Marc Garcia-Garcerà, Bertrand Néron, Marie Touchon, Eduardo P C Rocha

“…Extracellular capsules constitute the outermost layer of many bacteria, are major virulence factors, and affect antimicrobial therapies. …”
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Lightweight CNC digital process twin framework: IIoT integration with open62541 OPC UA protocol by Arivazhagan Anbalagan, Waqir Yusuf Zanhar, Shone George, Marcos Kauffman, Tengfei Long

“…This research introduces a novel, lightweight Digital Process Twin (DPT)-integrated IIoT framework for CNC machining, built on a modular five-layer architecture using the open-source open62541 OPC UA protocol. …”
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Organizational Principles of the Primate Cerebral Cortex at the Single‐Cell Level by Renrui Chen, Pengxing Nie, Liangxiao Ma, Guang‐Zhong Wang

“…By accessing the single‐cell spatial transcriptome of over 25 million neuron cells across the entire macaque cortex, it is discovered that the distribution of neurons within cortical layers is highly non‐random. Strikingly, over three‐quarters of these neurons are located in distinct neuronal clusters. …”
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