Penyuluhan dan Pelatihan Penggunaan Obat Tradisional serta Penerapan Hasil Penelitian Tumbuhan Sungkai (Peronema canescens Jack) kepada Masyarakat by Dwisari Dillasamola, Yufri Aldi, Fatma Sri Wahyuni, Hansen Nasif, Yohannes Alen

“…This community service activity aimed to equip individuals with the knowledge and skills to process plants accurately, utilize them appropriately based on the severity of the illness, and avoid any adverse side effects or toxicity. …”
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Real-Time Vehicle Detection Using Cross-Correlation and 2D-DWT for Feature Extraction by Abdelmoghit Zaarane, Ibtissam Slimani, Abdellatif Hamdoun, Issam Atouf

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Budget Politics, Motivation, In Budget Participation, And Local Government Performance In Indonesia by Ernawaty Usman, Sugianto Sugianto, Asri Usman

“…Practical implications emphasize fostering greater budget participation by boosting employee motivation to improve performance. …”
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Comparison of Machine Learning Methods for Predicting Electrical Energy Consumption by Retno Wahyusari, Sunardi Sunardi, Abdul Fadlil

“…The study employs three Machine Learning (ML) models: k-Nearest Neighbors (KNN), Random Forest (RF), and CatBoost. To enhance prediction accuracy, the researchers included a data pre-processing step using min-max normalization. …”
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Performance Comparison of 10 State-of-the-Art Machine Learning Algorithms for Outcome Prediction Modeling of Radiation-Induced Toxicity by Ramon M. Salazar, PhD, Saurabh S. Nair, MS, Alexandra O. Leone, MBS, Ting Xu, PhD, Raymond P. Mumme, BS, Jack D. Duryea, BA, Brian De, MD, Kelsey L. Corrigan, MD, Michael K. Rooney, MD, Matthew S. Ning, MD, Prajnan Das, MD, Emma B. Holliday, MD, Zhongxing Liao, MD, Laurence E. Court, PhD, Joshua S. Niedzielski, PhD

“…Each data set was modeled using 11 commonly employed machine learning algorithms (elastic net, least absolute shrinkage and selection operator [LASSO], random forest, random forest regression, support vector machine, extreme gradient boosting, light gradient boosting machine, k-nearest neighbors, neural network, Bayesian-LASSO, and Bayesian neural network) by randomly dividing the data set into a training and test set. …”
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Prediction and optimization of struvite recovery from wastewater by machine learning by TONG Ying, JIANG Shaojian, KANG Bingyan, LENG Lijian*, LI Hailong

“…The effects of seven process conditions on struvite crystallization were identified. …”
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Enhancing Quantum Information Distribution Through Noisy Channels Using Quantum Communication Architectures by Francisco Delgado

“…Quantum information transmission is subject to imperfections in communication processes and systems. These phenomena alter the original content due to decoherence and noise. …”
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Electricity Consumption, Roads and Their Infrastructure; Strategies to Increase Per Capita Income and Reduce Poverty in East Nusa Tenggara by Dian Anggraeny Rahim, Atik Isniawati

“…However, road infrastructure variables have shown no effect on boosting per capita income or reducing poverty. Formulation of strategies to diminish poverty while augmenting per capita income was conducted through the Analytical Network Process (ANP) analysis tool, involving nine stakeholders and decision-makers within the region.  …”
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Potential of Immunoglobulin A to Prevent Allergic Asthma by Anouk K. Gloudemans, Bart N. Lambrecht, Hermelijn H. Smits

“…This review highlights the latest literature on the role of mucosal IgA in protection against allergic airway disease, the mechanisms described to induce secretory IgA, and the role of (mucosal) dendritic cells in this process. Finally, we discuss how this information can be used to translate into the development of new therapies for allergic diseases based on, or supplemented with, IgA boosting strategies.…”
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A Review of Generative Design Using Machine Learning for Additive Manufacturing by Parankush Koul

“…AI integration with existing production processes is also vital to real-time manufacturing optimization—further increasing overall operational effectiveness. …”
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An assessment of graduates skills gap for sustainable employability during the 4IR in Bangladesh by Md Jahangir Alam, Shiblee Noman, Md Nurul Islam Mujib, Wasik Sajid Khan

“…The Fourth Industrial Revolution (4IR) leads global transformation through technological advancements, streamlining labor processes, and boosting productivity. This study explores the emerging employment sectors in Bangladesh for graduates, such as data science, artificial intelligence, and e-commerce management, in the context of the 4IR. …”
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The Influence of the Role-Playing Method on the Arabic Speaking Skills of Students at Al-Ghuraba Islamic Boarding School, Dompu. by Muhammad Ardiansyah, R Taufiqurrochman, Nur Hasaniyah

“…These findings suggest that the role-playing method fosters a more active and communicative learning environment, while also boosting students’ confidence in practical Arabic usage. …”
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How Inflation and its Uncertainty Affect Stock Returns: Insights from Borsa Istanbul by Emre Akyurt, Durmuş Çağrı Yıldırım, Ömer Esen

“…In particular, a rise in inflation uncertainty has a stronger impact on boosting stock returns than a rise in inflation itself. …”
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An 8-bit Digitally-controlled Low NF VGA for 5G Millimeter-wave Beamforming in 65 nm CMOS Technology by Sid Ahmed Tedjini, Sonia Salhi

“…In this paper, a linear-in-dB digitally controlled variable gain low-noise amplifier (D-VGLNA) designed in 65 nm CMOS process for the 5G mm-wave phase-array subsystem is presented. …”
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Design and prediction of high optical density photovoltaic polymers using machine learning-DFT studies by Aljaafreh Mamduh J., Hassan Abrar U.

“…The results show that extra gradient boosting regressor and random forest regressor are the best-performing models among all the tested ML models, whose good R-squared (R 2) values reveal their prediction accuracy. …”
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TECHNOLOGICAL ADVANCES IN ELECTROPLATING: ARTIFICIAL INTELLIGENCE TO PREDICT ZINC COATING THICKNESS ON SAE 1008 LOW CARBON STEELS by Luciano M. L. de Oliveira, Fabiana L. da Silva, Paulo R. Janissek, Juliano C. Toniolo

“…Statistical analysis and supervised machine learning algorithms, including multivariate regression, random forest, and extreme gradient boosting (XGBoost), were employed to develop prediction models. …”
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AI-Militarization in South Asia: A Comparative Analysis by Summar Iqbal Babar, Malaika Sarwar

“…Analyzing these developments within the Revolution in Military Affairs (RMA) theoretical framework, the study focuses on how AI-driven technologies are rearranging asymmetric warfare capabilities, boosting intelligence operations, and affecting decision-making processes under military frameworks. …”
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Research on the Pricing Model of B2B Data Transactions and Its Nature for a Single Industrial Chain by Weiqing Zhuang, Hanyu Yu, Morgan C. Wang

“…In particular, pricing strategies in the industrial chain’s data trading process critically influence the cooperation and market competitiveness of upstream and downstream enterprises. …”
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Improved phase prediction of high-entropy alloys assisted by imbalance learning by Libin Zhang, Chang-Seok Oh, Yoon Suk Choi

“…In this work, an extensive database by collecting experimental data from published literature was constructed, and the key features affecting the phase formation of HEAs were filtered out by performing a three-step feature selection process. Then, extreme gradient boosting (XGB) models were constructed to categorize phase structures of HEAs with high accuracies. …”
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Political Sentiment Analysis of Persian Tweets Using CNN-LSTM Model by Mohammad Dehghani, Zahra Yazdanparast

“…Sentiment analysis is the process of identifying and categorizing people’s emotions or opinions regarding various topics. …”
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