Efficient joint resource allocation using self organized map based Deep Reinforcement Learning for cybertwin enabled 6G networks by Nivetha A, Preetha KS

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Comprehensive analysis of arc methods of 3D printing of metal products: assessment of the efficiency and prospects of using TIG as a heat source by Andrii Horbenko, Constantine Zvorykin

“… In recent years, additive technologies have become increasingly important for the production of parts with complex geometries, enabling the rapid and efficient creation of objects with different shapes and configurations in industrial sectors such as medicine, aerospace and construction. …”
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Sponge-like Modified White-Rot Fungi Adsorbent for Rapid Removal of Pb(II) and Cd(II) from Solution: Selective Performance and Mechanistic Insights by Chunxiao Wang, Zhirong Chen, Nana Wang, Jianqiao Wang, Runshen He, Yu Chen, Haerfosai Nuhu, Hang Chen, Zhixuan Lin, Minqi Fan, Mingdong Chang

“…Mechanistic analyses (XRD, FTIR, and XPS) revealed that removal occurs via ion exchange, complexation, and precipitation, forming stable compounds like PbS/CdS and PbCO₃/CdCO₃. …”
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Genotype Selection from Azide-Induced Rice Mutants Using Multitrait Genotype–Ideotype Distance Index (MGIDI): Unveiling Promising Variants for Yield Improvement by S. M. Abdullah Al Mamun, Nasrin Akter Ivy, Mohammad Ashik Iqbal Khan, Sayda Rehana, Mst. Sabiha Sultana, Sanjoy Kumar Adhikary, Md. Monirul Islam

“…The estimated heritability and genetic advance indicated that nearly all traits had a high level of heritability and followed a complex pattern of inheritance. The strong correlations observed between grain yield and flag leaf length, branch panicle−1, grain panicle−1, 100-grain weight, straw yield hill−1, and harvest index indicate that prioritizing these traits during selection could substantially improve other desirable characteristics. …”
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Data-driven non-intrusive reduced order modelling of selective laser melting additive manufacturing process using proper orthogonal decomposition and convolutional autoencoder by Shubham Chaudhry, Azzedine Abdedou, Azzeddine Soulaïmani

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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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A reagent-free, fouling-resistant electrochemical multifunctional peptide sensor for highly sensitive and rapid detection of Alzheimer's disease biomarkers by Yajing Ji, Xueqin Li, Xiumin Li, Xiaochun Hu, Wei Cong, Honggang Hu, Siyao Liu, Yan Chen

“…This study presents a novel, efficient, and rapid strategy for detecting Aβ aggregates in human serum without complex pre-processing and provides practical support for the early clinical diagnosis of AD.…”
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An ensemble agglomerative hierarchical clustering algorithm based on clusters clustering technique and the novel similarity measurement by Teng Li, Amin Rezaeipanah, ElSayed M. Tag El Din

“…Hierarchical Clustering (HC) is recognized as an efficient unsupervised approach to unlabeled data analysis. …”
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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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