A User-Centric Smart Library System: IoT-Driven Environmental Monitoring and ML-Based Optimization with Future Fog–Cloud Architecture by Sarkan Mammadov, Enver Kucukkulahli

“…Environmental factors—including air quality, sound, temperature, humidity, and lighting—were monitored using microcontrollers and image processing. User feedback was collected via surveys and incorporated into models trained using Logistic Regression, Decision Trees, Random Forest, Support Vector Machine (SVM), K-Nearest Neighbors (KNNs), Extreme Gradient Boosting (XGBoost), and Naive Bayes. …”
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Analysing and Forecasting the Energy Consumption of Healthcare Facilities in the Short and Medium Term. A Case Study by Ali Koç, Serap Ulusam Seçkiner

“…The increasing trend in energy consumption of these facilities and the process of selecting an energy supplier from the open market requires reliable and robust energy forecasting studies. …”
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Phase-Aligned Physical-Layer Network Coding in Visible Light Communications by Xun Guan, Qing Yang, Taotao Wang, Calvin Chun-Kit Chan

“…In this paper, we propose to employ physical-layer network coding (PNC) in the VLC system to increase its throughput by boosting the data transmission at the relay node. We design a unified PNC–VLC framework that includes both the physical-layer signal processing algorithm and the medium access control method. …”
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A Robust and Efficient Machine Learning Framework for Enhancing Early Detection of Android Malware by Fandi Kurniawan, Deris Stiawan, Darius Antoni, Mohd Yazid Idris, Rahmat Budiarto

“…Six machine learning algorithms Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), Naive Bayes, AdaBoost, and Gradient Boosting are used to identify malicious behavior in APK files. …”
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Harnessing microalgae as a bioresource for nutraceuticals: advancing bioactive compound exploration and shaping the future of health and functional food innovation by Anjuman Ayub, Farida Rahayu, Aniswatul Khamidah, Sri Satya Antarlina, Kasma Iswari, Khojin Supriyadi, Elya Mufidah, Anjuvan Singh, Chirag Chopra, Atif Khurshid Wani

“…Despite these issues, ongoing progress in biotechnology, AI-based process optimization, and strain improvement offers promising solutions to make microalgae production more efficient and commercially viable. …”
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Planar chlorination engineering induced symmetry-broken single-atom site catalyst for enhanced CO2 electroreduction by Shengjie Wei, Jiexin Zhu, Xingbao Chen, Rongyan Yang, Kailong Gu, Lei Li, Ching-Yu Chiang, Liqiang Mai, Shenghua Chen

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Exploring immune-inflammation markers in psoriasis prediction using advanced machine learning algorithms by Li Yang, Shixin He, Li Tang, Xiao Qin, Yan Zheng

“…Subsequently, nine classification algorithms were developed using the processed training set, including random forest, neural networks, XGBoost, k-nearest neighbors, gradient boosting, logistic regression, naïve Bayes, AdaBoost, and SVMs. …”
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Effects of <i>Fructus Aurantii</i> Extract on Growth Performance, Nutrient Apparent Digestibility, Serum Parameters, and Fecal Microbiota in Finishing Pigs by Haiqing Gan, Qian Lin, Yecheng Xiao, Qiyu Tian, Chao Deng, Renjie Xie, Hongkun Li, Jiajie Ouyang, Xingguo Huang, Yang Shan, Fengming Chen

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Revolutionizing Management Accounting: The Role of Artificial Intelligence in Predictive Analytics, Automated Reporting, and Decision-Making by Milos Pavlovic, Cedomir Gligoric, Filip Zdravkovic, Danijela Pavlovic

“…Results: The findings reveal that AI greatly enhances predictive analytics by boosting model accuracy and swiftly processing large datasets. …”
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Early Detection of Congenital Heart Diseases among Infants Using Artificial Neural Network Algorithm by Lucy Ifeyinwa Ezigbo, Anthony Kwubeghari, Francis Okoye

“…Another highly performing algorithm is the use of Extreme Gradient Boosting (XGB) which achieved an accuracy of 92.00%. …”
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Quantum limits of parameter estimation in long-baseline imaging by Aqil Sajjad, Michael R. Grace, Saikat Guha

“…Telescope systems with distributed apertures are a well-established approach for boosting resolution in astronomical imaging. However, theoretical limits on quantitative imaging precision, and the fundamentally best possible mode-sorting, beam-combining, and detection schemes to use with such arrays, remain largely unexplored. …”
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ASSESSMENT OF TRAINING NEEDS OF COCOA FARMERS IN BENDE LOCAL GOVERNMENT AREA OF ABIA STATE, SOUTH EAST NIGERIA by Chioma Udo NWAOBIALA, Ikechukwu NDUKWE, Oji EKUMANKAMA

“…The study recommends review of Land Use Act of 1990, increased extension contact and training and re-training of farmers on pesticide and fungicide usage for boosting cocoa production in the study area.…”
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Yield of Protein Crystallization from Metastable Liquid–Liquid Phase Separation by Shamberia Thomas, Joel A. Dougay, Onofrio Annunziata

“…Preparative protein crystallization is regarded as an economically sustainable protein purification alternative to chromatography in biotechnological downstream processing. However, protein crystallization is a not-well-understood process that is usually slow and poorly reproducible. …”
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Building Safer Social Spaces: Addressing Body Shaming with LLMs and Explainable AI by Sajedeh Talebi, Neda Abdolvand

“…Fine-tuned Psycho-Robustly Optimized BERT Pretraining Approach (Psycho-RoBERTa), pre-trained on psychological texts, excels (accuracy: 0.98, F1-score: 0.994, AUC: 0.990), surpassing models like Extreme Gradient Boosting (XG-Boost) (accuracy: 0.972) and Convolutional Neural Network (CNN) (accuracy: 0.979) due to its contextual sensitivity. …”
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A hybrid approach for pattern recognition and interpretation in age-related false memory by Noorbakhsh Amiri Golilarz, Elias Hossain, Shahram Rahimi, Hossein Karimi

“…IntroductionAging is associated with a decline in essential cognitive functions such as language processing, memory, and attention, which significantly impacts the quality of life in later years. …”
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Applications of Machine Learning Algorithms in Geriatrics by Adrian Stancu, Cosmina-Mihaela Rosca, Emilian Marian Iovanovici

“…The most studied algorithms in research articles are Random Forest, Extreme Gradient Boosting, and support vector machines. They are preferred due to their performance in processing incomplete clinical data. …”
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The role of personalization in influencing digital trust and impulse buying in e-commerce by David R. Hayrapetyan, Syuzi H. Darbinyan

“…This transforms consumers behavior, increasing their engagement, but at the same time boosting the risks of manipulative influence. In this regard, it seems relevant to analyze how personalization affects the formation of digital trust and consumer behavior. …”
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Digital technology adoption and farm household income in ethnic minority areas: evidence from Xinjiang, China by Yan Tang, Lizhi Tang

“…Specifically, digital adoption reduces reliance on traditional labor inputs in agricultural production, boosting agricultural incomes while increasing the likelihood of non-farm employment, thereby promoting income diversification. …”
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An Automatic Modulation Recognition Algorithm Based on Time–Frequency Features and Deep Learning with Fading Channels by Xiaoya Zuo, Yuan Yang, Rugui Yao, Ye Fan, Lu Li

“…Automatic modulation recognition (AMR) stands as a crucial core technology within the realm of signal processing and perception, playing a significant part in harsh electromagnetic environments. …”
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New hybrid features extracted from US images for breast cancer classification by Gigi Tăbăcaru, Simona Moldovanu, Dan Munteanu, Marian Barbu

“…Abstract Artificial intelligence (AI), and image processing fields play a vital role in classifying benign and malignant breast cancer (BC). …”
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