Performance Augmentation of Base Classifiers Using Adaptive Boosting Framework for Medical Datasets by Durr e Nayab, Rehan Ullah Khan, Ali Mustafa Qamar

“…We conducted a comprehensive experiment to assess the efficacy of twelve base classifiers with the AdaBoost framework, namely, Bayes network, decision stump, ZeroR, decision tree, Naïve Bayes, J-48, voted perceptron, random forest, bagging, random tree, stacking, and AdaBoost itself. …”
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ESA CCI Soil Moisture Assimilation in SWAT for Improved Hydrological Simulation in Upper Huai River Basin by Yongwei Liu, Wen Wang, Yuanbo Liu

“…Besides, the efficiency of DA is deteriorated by the dense forest coverage and the complex topography conditions of the basin. …”
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Monitoring Population Phenology of Asian Citrus Psyllid Using Deep Learning by Maria Bibi, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Muhammad Irfan Khan, Shouket Zaman Khan, Casper Shikali Shivachi, Asad Anees

“…Multiple linear regression, random forest regressor, and deep neural network approaches were compared to predict population dynamics of Asian citrus psyllid. …”
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Determination of the Properties of Medium-Density Fiberboards Produced Using Urea-Formaldehyde Resins Modified with Boron Compounds by Recai Arslan, Ebru Karaçay, Derya Maraşlıoğlu, Bilge Aslan Tanrıverdi, Ebru Fırat, Ayhan Tozluoğlu, Halil İbrahim Uğraş, Zeki Candan

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Identification of therapeutic targets for Alzheimer’s Disease Treatment using bioinformatics and machine learning by ZhanQiang Xie, YongLi Situ, Li Deng, Meng Liang, Hang Ding, Zhen Guo, QinYing Xu, Zhu Liang, Zheng Shao

“…By integrating differential gene expression analysis, weighted gene co-expression network analysis, Mfuzz clustering, single-cell RNA sequencing, and machine learning algorithms including LASSO regression, SVM-RFE, and random forest, five hub genes related to AD, including PLCB1, NDUFAB1, KRAS, ATP2A2, and CALM3 were identified. …”
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Biosphere Reserves in the Southwest of Ethiopia by Semegnew Tadese, Teshome Soromessa, Tesefaye Bekele, Brhane Meles

“…Forests that have a wide ecological gradient, diversity, and significant cover are confined in the southwestern part vis-à-vis other parts of Ethiopia, while the country is fronting biodiversity losses. …”
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FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images. by Nicholas T Gigliotti, Justin Lee, Emily H Mang, Giancarlo R Zambrano, Mitra L Taheri

“…Presented here is a new machine learning-based workflow for the analysis of microscopy images named FIRM (Feature Identification from Raw Microscopy) that uses a random forest classifier to identify ECM features of interest and generate binary segmentation masks for quantification with ImageJ-FIJI. …”
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IDENTIFIKASI TUMBUHAN EPIFIT BERDASARKAN CIRI MORFOLOGI DAN ANATOMI BATANG DI HUTAN PERHUTANI SUB BKPH KEDUNGGALAR, SONDE DAN NATAH by Mega Tri Suwila

“…The purpose of this action research is to improve the competence learning material digestive systeForests cover a lot of land vegetation, tropical rainforest is one of them, a lot of diversity tumbuahn that inhabit tropical rain forests. …”
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Hybrid MCDM-FMEA Model for Process Optimization: A Case Study in Furniture Manufacturing by Kristina Klarić, Ivana Perić, Karla Vukman, Fran Papić, Miljenko Klarić, Petra Grošelj

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Feeding Patterns and Xenomonitoring of Trypanosomes among Tsetse Flies around the Gashaka-Gumti National Park in Nigeria by Solomon Ngutor Karshima, Idris A. Lawal, Oluseyi Oluyinka Okubanjo

“…We identified 10 T. brucei, 3 T. congolense savannah, 2 T. congolense forest, and 2 mixed infections among the 13 pools made from the 27 flies positive for trypanosomes with light microscopy. …”
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Environmental influences on chorusing patterns in an Australian tropical savanna frog community by Sheryn Brodie, Slade Allen‐Ankins, Lin Schwarzkopf

“…We described the chorusing patterns of each species over two wet seasons at three breeding sites, and used conditional random forest analysis to investigate the influence of various environmental factors. …”
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Research on noise-induced hearing loss based on functional and structural MRI using machine learning methods by Minghui Lv, Liping Wang, Ranran Huang, Aijie Wang, Yunxin Li, Guowei Zhang

“…The support vector machine (SVM), random forest (RF) and logistic regression (LR) algorithms, were used to establish the classification model for NIHL. …”
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Applying Sewage Sludge to Eucalyptus grandis Plantations: Effects on Biomass Production and Nutrient Cycling through Litterfall by Paulo Henrique Müller da Silva, Fabio Poggiani, Jean Paul Laclau

“…In most Brazilian cities sewage sludge is dumped into sanitary landfills, even though its use in forest plantations as a fertilizer and soil conditioner might be an interesting option. …”
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Comprehensive dataset from high resolution UAV land cover mapping of diverse natural environments in Serbia by Bojana Ivošević, Nina Pajević, Sanja Brdar, Rana Waqar, Maryam Khan, João Valente

“…Our method compares the efficacy and accuracy of object-based image analysis (OBIA) combined with random forest and convolutional neural networks (CNN) for land cover classification. …”
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Three-Rooted Permanent Mandibular First Molars: A Meta-Analysis of Prevalence by Nyan M. Aung, Kyaw K. Myint

“…The proportions of the prevalence of three-rooted permanent mandibular first molars were presented in the forest plots by random effect model. The calculation was performed with MetaXL version 5.3. …”
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Breaking the Barriers for Women Participation in Agroforestry in the Context of AfCFTA by Patrick Opoku, Awonlimali Kenneth Ali, Peter Ampadu-Daaduam, Dorothy Asare Akoto

“…The study found out that Taungya farming, home garden, and forest farming were the types of agroforestry systems carried out by women in the study area. …”
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Singleton-based species names and fungal rarity: Does the number really matter? by Jonathan Cazabonne, Allison K. Walker, Jonathan Lesven, Danny Haelewaters

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Modeling and Solving Multi-Objective Path Planning Problem for Cooperative Cable-Suspended Load Transportation Considering the Time Variable Risk by Amir Arslan Haghrah, Sehraneh Ghaemi, Mohammad Ali Badamchizadeh

“…To demonstrate the efficiency of the proposed model and algorithm, three case studies inspired by a fire incident in a forest park have been conducted, and the results have been compared with those of seven other well-known algorithms.…”
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ML-Based Quantitative Analysis of Linguistic and Speech Features Relevant in Predicting Alzheimer’s Disease by Tripti Tripathi, Rakesh Kumar

“…The characteristics are subsequently used to educate five machine learning algorithms, namely k-nearest neighbors (KNN), decision tree (DT), support vector machine (SVM), XGBoost, and random forest (RF). The effectiveness of every algorithm is assessed through a 10-fold cross-validation. …”
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Design Study for a Quasisynchronous CDMA Sensor Data Collection System: An LEO Satellite Uplink Access Technique Based on GPS by Yijun Chen, Sheng Ding, Zhouchen Xie, Zhuangping Qi, Xuwen Liang

“…With the development of the LEO satellite communication technology, highly dependable wireless communication and sensor data collection using LEO satellites have been getting much attention for emergency, marine research, and forest fire disaster in the remote region. The satellite system is expected to have the following features: rapid production, low cost, and fast construction of the satellite network. …”
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