Survei Penelitian Metode Kecerdasan Buatan untuk Mendeteksi Ancaman Teknologi Serangan Siber by Eza Yolanda Fitria, Kusprasapta Mutijarsa

“…Teknik dan metode baru machine learning dan deep learning terus dikembangkan oleh banyak peneliti untuk menangani serangan siber. …”
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A multimodal Transformer Network for protein-small molecule interactions enhances predictions of kinase inhibition and enzyme-substrate relationships. by Alexander Kroll, Sahasra Ranjan, Martin J Lercher

“…The Python code provided can be used to easily implement and improve machine learning predictions involving arbitrary protein-small molecule interactions.…”
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AutoML based workflow for design of experiments (DOE) selection and benchmarking data acquisition strategies with simulation models by Xukuan Xu, Donghui Li, Jinghou Bi, Michael Moeckel

“…This paper introduces a workflow for conducting DOE comparative studies using automated machine learning. Based on a practical definition of model complexity in the context of machine learning, the interplay of systematic data generation and model performance is examined considering various sources of uncertainty: this includes uncertainties caused by stochastic sampling strategies, imprecise data, suboptimal modeling, and model evaluation. …”
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An embedded intrusion detection and prevention system for home area networks in advanced metering infrastructure by Sahar Lazim Qaddoori, Qutaiba Ibrahim Ali

“…Also, it uses two machine learning models to detect the abnormality in periodic and daily data metering respectively. …”
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Classification of Melanoma Cancer Using Deep Convolutional Neural Networks by Emrah Dönmez, Ali Güneş

“…This study investigates the application of machine learning techniques to diagnose skin lesions, focusing on differentiating between benign moles and malignant melanoma. …”
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Short-Term Prediction of Traffic State for a Rural Road Applying Ensemble Learning Process by Arash Rasaizadi, Seyedehsan Seyedabrishami, Mohammad Saniee Abadeh

“…Results show that the OL model as an ensemble learning model outperforms machine learning models, and its accuracy is equal to 80.03 percent. …”
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A Novel Approach to Face Verification Based on Second-Order Face-Pair Representation by Qiang Hua, Chunru Dong, Feng Zhang

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USING ARTIFICIAL INTELLIGENCE (AI) AND DEEP LEARNING TECHNIQUES IN FINANCIAL RISK MANAGEMENT by Joseph Olorunfemi AKANDE

“…Recent advancements in machine learning, particularly deep learning, offer significant potential for improving the efficiency and effectiveness of risk management systems. …”
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USING ARTIFICIAL INTELLIGENCE (AI) AND DEEP LEARNING TECHNIQUES IN FINANCIAL RISK MANAGEMENT by Joseph Olorunfemi AKANDE

“…Recent advancements in machine learning, particularly deep learning, offer significant potential for improving the efficiency and effectiveness of risk management systems. …”
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An Intrusion Detection System Based on Deep Learning and Metaheuristic Algorithm for IOT by Bahman Sanjabi, Mahmood Ahmadi

“…They are trained in machine learning and deep neural network learning to detect attack patterns. …”
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A data-driven methodology for the classification of different liquids in artificial taste recognition applications with a pulse voltammetric electronic tongue by Jersson X Leon-Medina, Leydi J Cardenas-Flechas, Diego A Tibaduiza

“…Particularly, in the latter, machine learning techniques are useful in data analysis and have been used to solve classification and regression problems. …”
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Exploring the vulnerability in the inference phase of advanced persistent threats by Qi Wu, Qiang Li, Dong Guo, Xiangyu Meng

“…However, models using machine learning methods lack robustness because it can be attacked easily by adversarial examples. …”
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Ensemble Classifiers for Arabic Sentiment Analysis of Social Network (Twitter Data) towards COVID-19-Related Conspiracy Theories by Abdullah Al-Hashedi, Belal Al-Fuhaidi, Abdulqader M. Mohsen, Yousef Ali, Hasan Ali Gamal Al-Kaf, Wedad Al-Sorori, Naseebah Maqtary

“…This study proposes a machine learning model to analyze the Arabic tweets from Twitter. …”
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A New Preprocessing Method for Diabetes and Biomedical Data Classification by Sarbast CHALO, İbrahim Berkan AYDİLEK

“…Several different types of machine learning classifiers, such as KNN, J48, RF, and DT, were utilized in the experimental findings of biological datasets. …”
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Application of Feature Selection Based on Elastic Network and Random Forest in the Evaluation of Sports Effects by Lina Ren, Shen Cao

“…With the rapid development of data mining and machine-learning technology and the outbreak of big sports data mining development challenges, sports data mining cannot simply use data statistical methods such as how to combine machine learning and data mining technology for effective mining and analysis of sports data, to provide useful advice for public physical exercise, and this is an urgent need to study. …”
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Prediction of Sonic Log Values Using a Gradient Boosting Algorithm in the 'AB' Field by Rasif Nahari, Utama Widya, Ardhya Garini Sherly, Fitri Indriani Rista, Pratama Novian Putra Dhea

“…To address missing data, machine learning algorithms, like gradient boosting, provide an effective solution. …”
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An in‐depth study of the effects of methods on the dataset selection of public development projects by Can Cheng, Bing Li, Zengyang Li, Peng Liang, Xu Yang

“…The results show that (1) to select PDPs or DPDPs with a high precision, the base line method is the best with precision of 0.877 (PDPs) and 0.831 (DPDPs); (2) to select PDPs or DPDPs with a high F‐measure, the machine learning methods are the best, with F‐measure of 0.817 (PDPs) and 0.789 (DPDPs); (3) existing sample selection strategies can be combined with the machine learning methods, and the precision of selecting PDPs can be increased by 6.39%–41.33% and the precision of selecting DPDPs can be can be increased by 35.50%–269.02%.…”
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DETECTION OF KERATOCONUS DISEASE DEPENDING ON CORNEAL TOPOGRAPHY USING DEEP LEARNING by Aseel Abdulhasan Hashim, Mahdi Mazinani

“…The pre-processed data is then fed into Machine Learning(ML) algorithms and Convolutional Neural Network(CNN) models, by which the four corneal maps were analyzed. …”
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Nonlinear Autoregressive Neural Network for Antimicrobial Waste Water Treatment by Anwer Mustafa Hilal, Mashael M. Asiri, Shaha Al-Otaibi, Faisal Mohammed Nafie, Amal Al-Rasheed, Mohammed Rizwanullah, Ishfaq Yaseen, Abdelwahed Motwakel

“…This research used machine learning (ML) techniques to generate general adsorption forecasting model for sulfamethoxazole (SMX) and tetracycline (TC) on CBM. …”
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Artificial Intelligence in Identifying Patients With Undiagnosed Nonalcoholic Steatohepatitis by Onur Baser, Gabriela Samayoa, Nehir Yapar, Erdem Baser

“…We performed a claims data analysis using a machine learning algorithm. To build our model, the study population was randomly divided into an 80% training subset and a 20% testing subset and tested and trained using a cross-validation technique. …”
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