Non-destructive assessment of hemp seed vigor using machine learning and deep learning models with hyperspectral imaging by Damrongvudhi Onwimol, Pongsan Chakranon, Kris Wonggasem, Papis Wongchaisuwat

“…To simplify the analysis and reduce computational complexity, a subset of key spectral wavelengths was selected using a successive projection algorithm. …”
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Spatially optimized allocation of water and land resources based on multi-dimensional coupling of water quantity, quality, efficiency, carbon, food, and ecology by Yingbin Wang, Haiqing Wang, Jiaxin Sun, Peng Qi, Wenguang Zhang, Guangxin Zhang

“…These enhancements enable the algorithm to explore the solution space more efficiently when addressing complex multi-objective problems to validate the effectiveness and practicality of the COM-WL model, we selected the Daan Irrigation District as the study area. …”
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A review on atomically modified materials by atomic layer deposition for wastewater treatment by Asif Jan, Melike Begum Tanis-Kanbur, Luuk C. Rietveld, Sebastiaan G.J. Heijman

“…ALD enables nanoscale engineering of materials, offering unprecedented control over surface chemistry, pore structure, and functional properties for improved wastewater treatment efficiency. This review critically examines the advancements in ALD-modified membranes and adsorbents for industrial wastewater treatment, highlighting how ALD enhances adsorption kinetics and selectivity in adsorbents, improves hydrophilicity and antifouling behavior in polymeric membranes, and enhances chemical and mechanical stability in ceramic membranes. …”
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ITap: Index Finger Tap Interaction by Gaze and Tabletop Integration by Jeonghyeon Kim, Jemin Lee, Jung-Hoon Ahn, Youngwon Kim

“…The primary purpose of this research is to enhance interaction efficiency, reduce user fatigue, and improve accuracy in gaze-based object selection tasks, particularly in complex and cluttered XR environments. …”
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Knee injury prevention via personalized exercise using EDAS method and Sugeno Weber operator under complex q rung orthopair fuzzy data by ShiJie Zhang, Chuxin Sima, TaiFu Hou

“…The complex q-rung orthopair fuzzy set (C-qROFS) is a prevailing tool for managing ambiguity by combining satisfactory, dissatisfactory, and complex phase data. …”
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BiSeNeXt: a yam leaf and disease segmentation method based on an improved BiSeNetV2 in complex scenes by Bibo Lu, Yanjun Lu, Di Liang, Jie Yang

“…Additionally, the FLOPs and total number of parameters of the proposed method require only 11.81% and 7.81% of DeepLabV3+, respectively.DiscussionTherefore, the proposed method can efficiently and accurately extract yam leaf spots in complex scenes, providing a solid foundation for analyzing yam leaves and diseases.…”
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Vitamin-herbal flour from Rhaponticum carthamoides in the diets of dairy cows by Nikolay A. Morozkov, Lyudmila S. Terentyeva, Elena V. Sukhanova, Vladimir A. Voloshin

“…The experiment was carried out according to the generally accepted method with the selection of analog pairs. The cows of the control group received a feeding ration consisting of feeds available at the dairy complex. …”
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Presenting a model for determining the level of technological complexity of research and development activities in knowledge-based companies (case study: companies based in Golesta... by Gholamali shahmoradi, Taghi Torabi, Reza Radfar, Mohammadhasan Cheraghali

“…Then, during three stages of coding (open, central and selective), the influential factors in determining the level of complexity were identified and the research model was formed. …”
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Energy efficient adaptive clustering with QoS-aware CBRP and grey wolf optimization clustering algorithm for mobile ad-hoc network (MANET) by Minal Patil, Manish Chawhan, Roshan Umate, Abhishek Madankar, Bhumika Neole

“…Moreover, the cluster definition protocol (CBRP) has been developed to improve the efficiency of determination by organizing the structure itself as a group and selecting CHs for internal communication and between effective groups. …”
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Biohybrid ZnCr-LDH/Spirogyra algae composite for selective adsorption from multi-dye anionic mixtures: Toward enhanced removal of direct yellow by Alfan Wijaya, Nur Ahmad, Laila Hanum, Elda Melwita, Yulizah Hanifah, Aldes Lesbani

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Enhanced reactivity and electron efficiency of nanoscale zero-valent iron for nitroaromatic compounds reduction through modification with anthraquinone-2-carboxylic acid by Yuxin Li, Shiqi Yang, Zihan Liu, Yiyang Pan, Pengfei Zhang, Zhiqiu Qu, Chao Shan

“…Humic substances (HS) modification favors the reactivity of nanoscale zero-valent iron (nZVI) for water decontamination from nitro-compounds like nitrobenzene (NB), whereas the structural complexity of HS hinders the elucidation of its mechanism. …”
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EnsembleXAI-Motor: A Lightweight Framework for Fault Classification in Electric Vehicle Drive Motors Using Feature Selection, Ensemble Learning, and Explainable AI by Md. Ehsanul Haque, Mahe Zabin, Jia Uddin

“…RFE-CV is found to be very effective in feature selection and helps to construct a lightweight and cost-effective ensemble voting model for enhancing fault diagnosis for EV Drive Motors, overcoming its unsatisfactory transparency, accuracy, and computational efficiency. …”
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A Machine Learning Model for Predicting Breast Cancer Recurrence and Supporting Personalized Treatment Decisions Through Comprehensive Feature Selection and Explainable Ensemble Le... by Lee TF, Shiau JP, Chen CH, Yun WP, Wuu CS, Huang YJ, Yeh SA, Chen HC, Chao PJ

“…However, traditional risk prediction models often lack accuracy and do not fully capture the complexity of patient data.This study developed an ensemble learning model to predict breast cancer recurrence more accurately by integrating LASSO feature selection and multiple machine learning models. …”
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Development of New Electricity System Marginal Price Forecasting Models Using Statistical and Artificial Intelligence Methods by Mehmet Kızıldağ, Fatih Abut, Mehmet Fatih Akay

“…Overall, this study presents a novel and comprehensive approach tailored for complex electricity markets, significantly enhancing predictive reliability by incorporating economic indicators and sophisticated feature selection methods.…”
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Evaluating the Performance of Machine Learning Classifiers for Network Intrusion Detection: A Comparative Study Using the UNSW-NB15 Dataset by Iwan Handoyo Putro

“…It is because of their growing adoption and complexity of cyber-attacks. Therefore, protecting network infrastructures and identifying malicious behavior becomes a necessity. …”
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Features of the Methods of Training Physical Exercises by Victor BUFTEA

“…Certainly, this information can lead to the selection of the most relevant methodological sequences, the correct application of which can contribute to streamlining the learning process of any technical structure and any content. …”
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DenseNet-FPA: Integrating DenseNet and Flower Pollination Algorithm for Breast Cancer Histopathology Image Classification by Musa Adamu Wakili, Harisu Abdullahi Shehu, Mahdi Abdollahi, Badamasi Imam Ya'u, Md Haidar Sharif, Huseyin Kusetogullari

“…While histopathological image analysis plays a key role in breast cancer diagnosis, the complexity and heterogeneity of these images present significant challenges. …”
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A multistrategy improved hunger games search algorithm by Qiu Yihui, Zhang Xinqiang, Li Ruoyu, Li Dongyi, Xia Feihan

“…Moreover, a binary variant, BMHGS_V3, using sigmoid transformation, attains an average classification accuracy of 92.3% on ten UCI datasets for feature selection tasks. The proposed MHGS algorithm provides a novel and effective framework for solving complex optimization problems, demonstrating significant theoretical and practical value in the field of computational intelligence.…”
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A Novel Approach to Pine Nut Classification: Combining Near-Infrared Spectroscopy and Image Shape Features with Soft Voting-Based Ensemble Learning by Yueyun Yu, Xin Huang, Danjv Lv, Benjamin K. Ng, Chan-Tong Lam

“…This study proposes a novel near-infrared (NIR) spectral feature selection algorithm, termed the improved binary equilibrium optimizer with selection probability (IBiEO-SP), which incorporates a dynamic probability adjustment mechanism to achieve efficient feature dimensionality reduction. …”
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Rough Set Theory and Soft Computing Methods for Building Explainable and Interpretable AI/ML Models by Sami Naouali, Oussama El Othmani

“…This study introduces a novel framework leveraging Rough Set Theory (RST)-based feature selection—MLReduct, MLSpecialReduct, and MLFuzzyRoughSet—to enhance machine learning performance on uncertain data. …”
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