PRER: A patient representation with pairwise relative expression of proteins on biological networks. by Halil İbrahim Kuru, Mustafa Buyukozkan, Oznur Tastan

“…Changes in protein and gene expression levels are often used as features in predictive modeling such as survival prediction. A common strategy to aggregate information contained in individual proteins is to integrate the expression levels with the biological networks. …”
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Elastically induced phase-shift and birefringence in optical fibers [version 2; peer review: 1 approved, 2 approved with reservations] by Piotr T. Chruściel, Elisabeth Steininger, Thomas Mieling

“…Background Light propagation in optical fibers is known to be sensitive to ambient conditions such as changes in temperature and pressure. Building on a model for elastic deformations of optical fiber spools derived in previous work, the induced effects on phase and birefringence are investigated. …”
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Elastically induced phase-shift and birefringence in optical fibers [version 1; peer review: 1 approved, 2 approved with reservations] by Piotr T. Chruściel, Elisabeth Steininger, Thomas Mieling

“…Background Light propagation in optical fibers is known to be sensitive to ambient conditions such as changes in temperature and pressure. Building on a model for elastic deformations of optical fiber spools derived in previous work, the induced effects on phase and birefringence are investigated. …”
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Identification of unknown operating system type of Internet of Things terminal device based on RIPPER by Shichang Xuan, Dapeng Man, Wu Yang, Wei Wang, Jiashuai Zhao, Miao Yu

“…The operating system identification technology based on transmission control protocol/Internet protocol fingerprint library is more complicated than to distinguish the operating system types of unknown fingerprints. In this work, a passive operating system identification method based on RIPPER model is proposed. …”
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六连杆硬顶敞篷机构的设计与研究 by 张晓, 黄强

“…A new type of Stephenson-Ⅲ six-bar linkage for three-piece folding and hard-top convertible roof mechanism is presented.Utilizing vector loop equations and motion generated methods,the analytical expressions of dimension and position of barmembers are solved,and the design parameters are obtained sequentially.Three dimensional model of the mechanismis carried outby usingSolidWorks,and the rationality of the design is confirmed by Working model which is dynamic simulation software.There are some reference value for current design and manufacturing of hard-top convertible roof mechanismwith the research findings.…”
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ViSwNeXtNet Deep Patch-Wise Ensemble of Vision Transformers and ConvNeXt for Robust Binary Histopathology Classification by Özgen Arslan Solmaz, Burak Tasci

“…<b>Methods:</b> We propose ViSwNeXtNet, a novel patch-wise ensemble framework that integrates three transformer-based architectures—ConvNeXt-Tiny, Swin-Tiny, and ViT-Base—for deep feature extraction. Features from each model (12,288 per model) were concatenated into a 36,864-dimensional vector and refined using iterative neighborhood component analysis (INCA) to select the most discriminative 565 features. …”
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Multiclass classification of thalassemia types using complete blood count and HPLC data with machine learning by Muhammad Umar Nasir, Muhammad Zubair, Muhammad Tahir Naseem, Tariq Shahzad, Ahmed Saeed, Khan Muhammad Adnan, Amir H. Gandomi

“…These results are obtained from CBC and HPLC analysis. The analyzed models are K-nearest Neighbor (KNN), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost). …”
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Searching for string bosenovas with gravitational wave detectors by Dawid Brzeminski, Anson Hook, Junwu Huang, Clayton Ristow

“…Abstract We study the phenomenology of a string bosenova explosion in vector superradiance clouds around spinning black holes, focusing on the observable consequences in gravitational wave detectors and accelerometers. …”
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Accurate Indoor Home Location Classification through Sound Analysis: The 1D-ILQP Approach by Umut Erman, Türker Tuncer, Nura Abdullahi, Sengul Dogan, Erhan Akbal

“…The final step of our model involves classification, wherein we employed a range of classifiers, including decision trees, linear discriminant analysis, quadratic discriminant analysis, Naive Bayes, support vector machines, k-nearest neighbor, bagged trees, and artificial neural networks. …”
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Quantum-enhanced beetle swarm optimized ELM for high-dimensional smart grid intrusion detection by Na Cheng, Shuqing Wang, Lihong Zhao, Yan Hu

“…This renders it well-suited for the security monitoring of complex systems such as smart grids. Future work could integrate deep learning techniques to further optimise the model and extend its applications.…”
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Quantitative Prediction of Low-Permeability Sandstone Grain Size Based on Conventional Logging Data by Deep Neural Network-Based BP Algorithm by Hongjun Fan, Xiaoqing Zhao, Zongjun Wang, Zheqing Zhang, Ao Chang

“…In this paper, the sensitivity logging parameters of median rock grain size are optimized for low permeability sandstone reservoirs using principal component analysis obtained the grain size direction correlation curves (DEN, CNL,GR, and RD) in the study area, and the corresponding loss and activation functions are selected based on the learning characteristics of the nonlinear mapping of the logging data and the BP neural network to ensure that overfitting occurs. The best model was obtained by using decision tree, support vector machine, shallow and deep neural networks to model the median rock grain size and predict neighboring wells, and a comparative analysis showed that for the problem of predicting the median rock grain size in low-permeability sandstone reservoirs, the deep neural network improved significantly over the shallow one and was much stronger than other machine learning methods. …”
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CubicPat: Investigations on the Mental Performance and Stress Detection Using EEG Signals by Ugur Ince, Yunus Talu, Aleyna Duz, Suat Tas, Dahiru Tanko, Irem Tasci, Sengul Dogan, Abdul Hafeez Baig, Emrah Aydemir, Turker Tuncer

“…To achieve classification and explainable results, a new XFE model was developed, incorporating a novel feature extraction function called Cubic Pattern (CubicPat), which generates a three-dimensional feature vector by coding channels. …”
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A New Method of 3D Facial Expression Animation by Shuo Sun, Chunbao Ge

“…Secondly, through using the method of principle component analysis (PCA), we generate the parameter sets of eigen-ERI space, which will rebuild reasonable expression ratio image. Then we learn a model with the support vector regression mapping, and facial animation parameters can be synthesized quickly with the parameters of eigen-ERI. …”
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Hyperspectral estimation of mercury content of soil in Oasis city in arid zones of China by Qing Zhong, Mamattursun Eziz, Mireguli Ainiwaer, Rukeya Sawut, Maorui Hou

“…The novel contribution of this work is to construct hyperspectral inversion model which can accurately estimate the Hg content of urban soils in arid zones. …”
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Long Short-Term Memory-Enabled Electromyography-Controlled Adaptive Wearable Robotic Exoskeleton for Upper Arm Rehabilitation by S. M. U. S. Samarakoon, H. M. K. K. M. B. Herath, S. L. P. Yasakethu, Dileepa Fernando, Nuwan Madusanka, Myunggi Yi, Byeong-Il Lee

“…Conventional machine learning (ML) models, including K-Nearest Neighbor Regression (K-NNR), Support Vector Regression (SVR), and Random Forest Regression (RFR), were compared with neural network approaches, including Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) to determine the best ML model for the ROM angle prediction. …”
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Combining miRNA concentrations and optimized machine-learning techniques: An effort for the tomato storage quality assessment in the agriculture 4.0 framework by Seyed Mohammad Samadi, Keyvan Asefpour Vakilian, Seyed Mohamad Javidan

“…Moreover, research has shown that conventional machine-learning methods do not exert enough performance in predicting treatments applied to plants by having miRNA concentrations. In this work, using basic machine-learning methods and their optimization via meta-heuristic algorithms, the storage period, storage temperature, and mechanical loading during storage in tomatoes have been predicted by having miRNA concentrations as model inputs. …”
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GRE²-MDCL: Graph Representation Embedding Enhanced via Multidimensional Contrastive Learning by Quanjun Li, Weixuan Li, Xiya Zheng, Junhua Zhou, Wenming Zhong, Xuhang Chen, Chao Long

“…Graph representation learning aims to preserve graph topology when mapping nodes to vector representations, enabling downstream tasks like node classification and community detection. …”
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Enhancing Fake Review Detection Using Linguistic Exaggeration, BERT Embeddings, and Fuzzy Logic by Mohammed Ennaouri, Ahmed Zellou

“…The core objective of this work is to develop a hybrid model that combines interpretable handcrafted linguistic cues with deep semantic features for more accurate, robust, and accurate fake review detection. …”
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Bayesian-Optimized Multi-Task Gaussian Process Regression With Composite Kernels for Soybean Oil Futures Forecasting by Hui-Dong Yin, Yi-Yang Li

“…Traditional econometric models and machine learning approaches often struggle with non-stationary data and uncertainty quantification, while existing Gaussian process applications in agricultural markets remain underexplored. …”
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Application of Hyperspectral Image for Monitoring in Coastal Area with Deep Learning: A Case Study of Green Algae on Artificial Structure by Tae-Ho Kim, Jee Eun Min, Hye Min Lee, Kuk Jin Kim, Chan-Su Yang

“…A certain area of the image was used as learning data to create classification models for three classes. The classification models were created from one machine-learning (support vector machine, SVM) and two deep-learning models (convolutional neural network, CNN; and dense convolutional network, DenseNet). …”
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