Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques by Yadigar Imamverdiyev, Elshan Baghirov, John Chukwu Ikechukwu

“…Utilizing the CIC-MalMem-2022 dataset, the effectiveness of decision trees, gradient-boosted trees, logistic Regression, random forest, and LightGBM in identifying obfuscated malware was evaluated. …”
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UAV-Multispectral Based Maize Lodging Stress Assessment with Machine and Deep Learning Methods by Minghu Zhao, Dashuai Wang, Qing Yan, Zhuolin Li, Xiaoguang Liu

“…The results indicate that the Random Forest (RF) model outperforms the other four ML algorithms, achieving an overall accuracy (OA) of 89.29% and a Kappa coefficient of 0.8852. …”
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Influences of Sampling Design and Model Selection on Predictions of Chemical Compounds in Petroferric Formations in the Brazilian Amazon by Niriele Bruno Rodrigues, Theresa Rocco Barbosa, Helena Saraiva Koenow Pinheiro, Marcelo Mancini, Quentin D. Read, Joshua Blackstock, Edwin H. Winzeler, David Miller, Phillip R. Owens, Zamir Libohova

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AI-powered IoT and UAV systems for real-time detection and prevention of illegal logging by Montaser N.A. Ramadan, Mohammed A.H. Ali, Shin Yee Khoo, Mohammad Alkhedher

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Development and Validation of DIANA (Diabetes Novel Subgroup Assessment tool): A web-based precision medicine tool to determine type 2 diabetes endotype membership and predict indi... by Viswanathan Baskar, Mani Arun Vignesh, Sumanth C Raman, Arun Jijo, Bhavadharini Balaji, Nico Steckhan, Lena Maria Klara Roth, Moneeza K Siddiqui, Saravanan Jebarani, Ranjit Unnikrishnan, Viswanathan Mohan, Ranjit Mohan Anjana

“…Its performance was compared with an algorithm determined based on conditional pre-determined cut-offs and weights for each clinical feature [age at diagnosis, BMI, waist, HbA1c, Serum Triglycerides, HDL-Cholesterol, (C-peptide fasting, C-peptide stimulated) - optional. …”
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Certainty of Linear Interrelation of Technical and Economic Parameters of Power Units of 300 МWt Thermal Power Stations by E. M. Farhadzadeh, A. Z. Muradaliyev, T. K. Rafiyeva, A. A. Rustamova

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Ensemble machine learning for predicting academic performance in STEM education by Aklilu Mandefro Messele

“…To tackle these issues, our research focused on developing a predictive model for STEM students using advanced ensemble machine learning algorithms. …”
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Rapid and accurate multi-phenotype imputation for millions of individuals by Lin-Lin Gu, Hong-Shan Wu, Tian-Yi Liu, Yong-Jie Zhang, Jing-Cheng He, Xiao-Lei Liu, Zhi-Yong Wang, Guo-Bo Chen, Dan Jiang, Ming Fang

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The Efficiency of Complex Differential Treatment of the Patients with Systemic Lupus Erythematous Considering the Features of Bone Tissue Structure Remodeling by Abrahamovych U., Tsyhanyk L., Abrahamovych O., Farmaha M., Romaniuk O.

“…The evaluation of the application forms of LQ proves this fact. A general score of the patients of research group has increased up to 37.93 % versus 3.19 % for the women of research group, the same has a complex objective evaluation of the results of treatment by the doctors and researchers: the patients out of research group experienced a positive result of treatment more often while the ones out of comparison group -satisfactory and negative. …”
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Mortality impact, risks, and benefits of general population screening for ovarian cancer: the UKCTOCS randomised controlled trial by Usha Menon, Aleksandra Gentry-Maharaj, Matthew Burnell, Andy Ryan, Jatinderpal K Kalsi, Naveena Singh, Anne Dawnay, Lesley Fallowfield, Alistair J McGuire, Stuart Campbell, Steven J Skates, Mahesh Parmar, Ian J Jacobs

“…The volunteers were placed into one of three groups at random: The blood test group contained 50,640 women who had yearly CA125 blood tests. …”
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SVM-Based Spectrum Mobility Prediction Scheme in Mobile Cognitive Radio Networks by Yao Wang, Zhongzhao Zhang, Lin Ma, Jiamei Chen

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The application of blockchain with a comparative approach and its impact on risk, flexibility and internal control evaluation by mohammadsadegh aminipoor, HamidReza GholamniaRoshan, azadeh kiapour, Iman Dadashi

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Predicting climate-driven shift of the East Mediterranean endemic Cynara cornigera Lindl by Heba Bedair, Heba Bedair, Yehia Hazzazi, Asmaa Abo Hatab, Marwa Waseem A. Halmy, Mohammed A. Dakhil, Mohammed A. Dakhil, Mubaraka S. Alghariani, Mubaraka S. Alghariani, Mari Sumayli, A. El-Shabasy, Mohamed M. El-Khalafy

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Differentiation of Soybean Genotypes Concerning Seed Physiological Quality Using Hyperspectral Bands by Izabela Cristina de Oliveira, Dthenifer Cordeiro Santana, Victoria Toledo Romancini, Ana Carina da Silva Cândido Seron, Charline Zaratin Alves, Paulo Carteri Coradi, Carlos Antônio da Silva Júnior, Regimar Garcia dos Santos, Fábio Henrique Rojo Baio, Paulo Eduardo Teodoro, Larissa Ribeiro Teodoro

“…The experiment was conducted during the 2021/2022 harvest at the Federal University of Mato Grosso do Sul in a randomized block design with four replicates and 10 F3 soybean populations (G1, G8, G12, G15, G19, G21, G24, G27, G31, and G36). …”
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A toolkit for quantifying individual response to herbal extracts in metabolic and inflammatory stress by Soo-yeon Park, Oran Kwon, Tim van den Broek, Jildau Bouwman, Ji Yeon Kim

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Incorporating food plant distributions as important predictors in the habitat suitability model of sumatran orangutan (Pongo abelii) in Gunung Leuser National Park, Indonesia by Salmah Widyastuti, Wanda Kuswanda, M. Hadi Saputra, Hendra Helmanto, Nunu Anugrah, U. Mamat Rahmat, Rudianto Saragih Napitu, Andrinaldi Adnan, Iskandarrudin

“…Using machine learning algorithms—support vector machine, random forest, boosted regression trees, and maximum entropy—along with an ensemble model, seven important food plants, including Ixora insularum and Calamus manan, were identified as critical predictors of habitat suitability. …”
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What are new opportunities for clinical practice the VERIFY study opens and which values for native diabetes patients? Joint conclusion on the advisory board results. November 6, 2... by Marina V. Shestakova, Mikhail B. Antsiferov, Alexander S. Ametov, Gagik R. Galstyan, Tatiana Y. Demidova, Alexey V. Zilov, Tatiana N. Markova, Nina A. Petunina, Natalya A. Chernikova, Minara S. Shamkhalova

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Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

“…The texts of these 290 articles were studied, and finally 149 articles related to the selected topic and the literature and background of this research were used. In fact, the general goal and main question of this research was to model the innovation process centered on artificial intelligence, was carried out successfully with a very low model error during the test. …”
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Wearable sensor-based fall detection for elderly care using ensemble machine learning techniques by Ch Gangadhar, P Pavithra Roy, R. Dinesh Kumar, Janjhyam Venkata Naga Ramesh, S. Ravikanth, N. Akhila

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