Development and Feasibility Study of HOPE Model for Prediction of Depression Among Older Adults Using Wi-Fi-based Motion Sensor Data: Machine Learning Study by Shayan Nejadshamsi, Vania Karami, Negar Ghourchian, Narges Armanfard, Howard Bergman, Roland Grad, Machelle Wilchesky, Vladimir Khanassov, Isabelle Vedel, Samira Abbasgholizadeh Rahimi

“…We also conduct an explainability analysis to interpret the model’s predictions and identify key features associated with depression classification. …”
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Method of ISSR-marking in the study of genetic diversity of flax varieties by T. A. Bazanov, I. V. Ushapovsky, N. N. Loginova, E. V. Smirnova, P. D. Mikhaylova

“…Detection of amplification products was carried out using electrophoresis in 1.5% agarose gel. …”
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Application of HRCT-based radiomics to predict interstitial lung disease for juvenile dermatomyositis by Lingke Liu, Minfei Hu, Yun Zhou, Fei Zheng, Xiaohui Ma, Li Yang, Yiping Xu, Liping Teng, Bin Hu, Meiping Lu, Xuefeng Xu

“…Results A total of seven radiomics features including the maximum, mean, skewness, and kurtosis features for the First Order Features, the InverseVariance feature for the Gray Level Co-occurrence Matrix (GLCM) Features, the Size Zone NonUniformity Normalized feature for the Gray Level Size Zone Matrix(GLSZM)Features, and the Run Entropy feature for the Gray Level Run Length Matrix (GLRLM) Features were identified. …”
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Quality Control Charts for EWMA with Wavelet Shrinkage: A Simulation Study by Esraa Haydier, Dlshad Saleh, Taha Ali, Bekhal Sedeeq

“…On the other hand, wavelet shrinkage is an effective technique for removing noise from data and identifying deviations while preserving significant signals, thus enhancing the accuracy of the analysis. Alongside using actual data that represents the qualitative feature of children's weights- a crucial indicator for evaluating overall health and early detection of nutritional or health issues- this chart was simulated using MATLAB. …”
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Smart Grid Security: Proactive Prediction of Advanced Persistent Threats by Motahareh Dehghan, Erfan Khosravain

“…Experimental results show that the ProAPT model significantly outperforms traditional machine learning algorithms like Random Forest, Support Vector Machines, and Logistic Regression, achieving 93.8% accuracy, 93.12% precision, 95.2% recall, and 94.15% F1-Score. The feature importance analysis reveals that traffic-related features such as packet size variance and connection duration are crucial in identifying Advanced Persistent Threats. …”
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Comparative metabolic study of planktonic and sessile cells in Salmonella Enteritidis ATCC 13076: Elucidating metabolic pathways driving biofilm formation. by Yuliany Guillín, Claudia Ortiz, William Hidalgo

“…For data processing, XCMS was used for feature detection, retention time, correction and alignment. …”
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Failure State Identification and Fault Diagnosis Method of Vibrating Screen Bolt Under Multiple Excitation of Combine Harvester by Jiaojiao Xu, Tiantian Jing, Meng Fang, Pengcheng Li, Zhong Tang

“…A high-dimensional feature matrix is then constructed utilizing a Gaussian kernel function. …”
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Blockchain Enabled Secure Medical Data Transmission and Diagnosis Using Golden Jackal Optimization Algorithm with Deep Learning by Kiruthikadevi Kulandaivelu, Sivaraj Rajappan, Vijayakumar Murugasamy

“…Next, the diagnostic method includes Bayesian optimization algorithm (BOA) based hyper parameter tuning, deep belief network (DBN)-based classification, and CapsNet-based feature extraction. The empirical analysis of the proposed BGJOA-DLSMTD algorithm has been demonstrated by means of standard medical images and the outcomes underlined the superior achievement of the BGJOA-DLSMTD algorithm.…”
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A Predictive Fault Diagnosis Method for Fire Pump Sliding Bearings Based on the Vision Transformer with Local Mean Decomposition by Huang Yubiao, Chen Ye, Zhang Jiaqing, Yang Yun, Yang Juntao

“…In the proposed method, the vibration signal is first smoothed, and then LMD is used to enhance the quality of frequency-domain signal analysis. Subsequently, leveraging the attention mechanism, self-attention and cross-attention mechanisms, along with a weight-sharing mechanism, are introduced to further extract fault feature information from the signal decomposition diagram. …”
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HASSDE-NAS: Heuristic–Adaptive Spectral–Spatial Neural Architecture Search with Dynamic Cell Evolution for Hyperspectral Water Body Identification by Feng Chen, Baishun Su, Zongpu Jia

“…The accurate identification of water bodies in hyperspectral images (HSIs) remains challenging due to hierarchical representation imbalances in deep learning models, where shallow layers overly focus on spectral features, boundary ambiguities caused by the relatively low spatial resolution of satellite imagery, and limited detection capability for small-scale aquatic features such as narrow rivers. …”
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From Outside to Inside: The Subtle Probing of Globular Fruits and Solanaceous Vegetables Using Machine Vision and Near-Infrared Methods by Junhua Lu, Mei Zhang, Yongsong Hu, Wei Ma, Zhiwei Tian, Hongsen Liao, Jiawei Chen, Yuxin Yang

“…Nondestructive testing is reasonably used for image processing and pattern recognition, and can meet the identification and grading of single features and fusion features in production. Through the summary and analysis of the fruits and vegetable grading technology in the past five years, the results show that the accuracy of machine vision for fruits and vegetable size grading is 70–99.8%, the accuracy of external defect grading is 88–95%, and the accuracy of NIR and hyperspectral internal detection grading is 80.56–100%. …”
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Providing contexts for classification of transients in a wide-area sky survey: An application of noise-induced cluster ensemble by Tossapon Boongoen, Natthakan Iam-On, James Mullaney

“…Initial works based on the feature-based approach design this detection as imbalance classification, where a data-level method can be used to resolve the difference in cardinality between classes. …”
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Xenes-based QCM sensors: exploring borophene and silicene for humidity sensing by Ahmet Gulsaran, Bersu Bastug Azer, Gamze Gursu, Cihat Tasaltin, Nevin Tasaltin, Dogu Ozyigit, A.-Reum Kim, Boxin Zhao, Michael A. Pope, Mustafa Yavuz

“…Abstract Borophene and silicene, two novel members of the Xene family, feature high surface reactivity and stability suitable for sensing applications. …”
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Distributed denial-of-service (DDoS) on the smart grids based on VGG19 deep neural network and Harris Hawks optimization algorithm by Abdurahim Alhashmi, H. Idwaib, Selçuk Alparslan Avci, Javad Rahebi, Raheleh Ghadami

“…The suggested approach uses the robust feature extraction capability of VGG19-DNN for network traffic pattern analysis to detect abnormal traffic flows indicative of DDoS attacks. …”
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A Novel THz Differential Spectral Clustering Recognition Method Based on t-SNE by Tie-Jun Li, Chih-Cheng Chen, Jian-jun Liu, Gui-fang Shao, Christopher Chun Ki Chan

“…Comparative experiments indicate that our model can judge the existence of sample defect features or not through spectrum clustering, as a predetection process for image analysis.…”
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Multiclass skin lesion classification and localziation from dermoscopic images using a novel network-level fused deep architecture and explainable artificial intelligence by Mehak Arshad, Muhammad Attique Khan, Nouf Abdullah Almujally, Areej Alasiry, Mehrez Marzougui, Yunyoung Nam

“…Abstract Background and objective Early detection and classification of skin cancer are critical for improving patient outcomes. …”
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Effective Identification of Variety and Origin of Chenpi Using Hyperspectral Imaging Assisted with Chemometric Models by Hangxiu Liu, Youyou Wang, Yiheng Wang, Jingyi Wang, Hanqing Hu, Xinyi Zhong, Qingjun Yuan, Jian Yang

“…Feature wavelength selection strategies, such as CARS, simplified the model complexity while maintaining a classification performance comparable to that of the full-spectrum models. …”
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Automated diagnosis of respiratory diseases from lung ultrasound videos ensuring XAI: an innovative hybrid model approach by Arefin Ittesafun Abian, Mohaimenul Azam Khan Raiaan, Asif Karim, Sami Azam, Nur Mohammad Fahad, Niusha Shafiabady, Kheng Cher Yeo, Friso De Boer

“…The DSS, incorporating Layer Class Activation Mapping (LayerCAM) and heatmaps, improved interpretability and reliability, and PDF graphs facilitated precise decision-making by identifying feature boundaries. The DSS facilitates clinical marker analysis, and the validation by using the proposed algorithms highlights its impact on a reliable diagnosis outcome.DiscussionOur proposed methodology could assist radiologists in accurately detecting and comprehending the patterns of respiratory disorders.…”
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Explainable Machine Learning in the Prediction of Depression by Christina Mimikou, Christos Kokkotis, Dimitrios Tsiptsios, Konstantinos Tsamakis, Stella Savvidou, Lillian Modig, Foteini Christidi, Antonia Kaltsatou, Triantafyllos Doskas, Christoph Mueller, Aspasia Serdari, Kostas Anagnostopoulos, Gregory Tripsianis

“…Additionally, a genetic algorithm (GA) was utilized for feature selection and SHAP (SHapley Additive exPlanations) for interpreting the contributions of each employed feature. …”
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Enhancing wheat flour origin traceability by using laser-induced breakdown spectroscopy and Raman spectroscopy by Minghui Gu, Chao Liu, Hansong Huang, Xin Zhang, Jiguo Li, Qingbin Jiao, Liang Xu, Mingyu Yang, Xin Tan

“…First, a hybrid feature selection method, termed ANOVA-Sine Cosine Algorithm (AVSCA), was developed by integrating analysis of variance (ANOVA) with the Sine Cosine Algorithm (SCA) to extract spectral fingerprint information of wheat flour. …”
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