ACCELERATED ITERATIVE RECONSTRUCTION OF PHANTOM «ROZI» BY OS-SART METHOD USING ORDERED SUBSET PROJECTIONS by S. A. Zolotarev, M. M. Mieteeg, A. N. Al-Nadfa

“…One of the popular approaches used to increase the rate of convergence of these algorithms is to perform a correction of the current approximation of the reconstructed object on subsets of the projection data. …”
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SA Sorting: A Novel Sorting Technique for Large-Scale Data by Mohammad Shabaz, Ashok Kumar

“…Sorting is defined as an arrangement of data or records in a particular logical order. A number of algorithms are developed for sorting the data. The reason behind developing these algorithms is to optimize the efficiency and complexity. …”
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Cell on Wheels-Unmanned Aerial Vehicle System for Providing Wireless Coverage in Emergency Situations by Hazim Shakhatreh, Khaled Hayajneh, Khaled Bani-Hani, Ahmad Sawalmeh, Muhammad Anan

“…We utilize the exhaustive search (ES) and particle swarm optimization (PSO) algorithms to solve the optimization problem. The effectiveness of the proposed algorithms is validated using simulation results.…”
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MARS: An Educational Environment for Multiagent Robot Simulations by Marco Casini, Andrea Garulli

“…Undergraduate robotics students often find it difficult to design and validate control algorithms for teams of mobile robots. This is mainly due to two reasons. …”
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Online Bayesian Data Fusion in Environment Monitoring Sensor Networks by Yang Dingcheng, Wang Zhenghai, Xiao Lin, Zhang Tiankui

“…Evaluations based on real sensor data show that significant gain can be achieved by the proposed algorithms in environment monitoring sensor networks compared with channel-unaware algorithms.…”
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Deep Learning- and Word Embedding-Based Heterogeneous Classifier Ensembles for Text Classification by Zeynep H. Kilimci, Selim Akyokus

“…The ensemble of base classifiers includes traditional machine learning algorithms such as naïve Bayes, support vector machine, and random forest and a deep learning-based conventional network classifier. …”
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An Overview of Application of Machine Learning Models in Urban Flood Simulation and Forecasting by CHEN Zeming, FANG Xuhong, LI Jiaye, WANG Mengyao, CHEN Aifang, YIN Ling

“…Additionally, this paper also focused on the research on urban flood simulation and forecasting models based on machine learning algorithms published in the recent five years, summarized the technical processes for urban flood simulation and forecasting models based on machine learning algorithms, and proposed several current technological bottlenecks and potential solutions. …”
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Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning by Spyridon Chavlis, Panayiota Poirazi

“…Abstract Artificial neural networks (ANNs) are at the core of most Deep Learning (DL) algorithms that successfully tackle complex problems like image recognition, autonomous driving, and natural language processing. …”
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Facial expression recognition based on adaptation of the classifier to videos of the user by E.N. Churaev, A.V. Savchenko

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Towards the Development of a Cloud Computing Intrusion Detection Framework Using an Ensemble Hybrid Feature Selection Approach by Noah Oghenefego Ogwara, Krassie Petrova, Mee Loong Yang

“…The ensemble includes FS algorithms of three different types (filter, wrapper, and embedded algorithms). …”
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The Use of Machine Learning Methods in Road Safety Research in Poland by Anna Borucka, Sebastian Sobczuk

“…The aim of this study was to develop mathematical models based on ML algorithms describing road safety in Poland. First, variables with the strongest impact on safety were extracted. …”
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Prediction of Winter Wheat Parameters with Planet SuperDove Imagery and Explainable Artificial Intelligence by Gabriele De Carolis, Vincenzo Giannico, Leonardo Costanza, Francesca Ardito, Anna Maria Stellacci, Afwa Thameur, Sergio Ruggieri, Sabina Tangaro, Marcello Mastrorilli, Nicola Sanitate, Simone Pietro Garofalo

“…Different machine learning (ML) algorithms were trained and compared using spectral band data and calculated vegetation indices (VIs) as predictors. …”
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Vision-based manipulation of transparent plastic bags in industrial setups by F. Adetunji, F. Adetunji, A. Karukayil, A. Karukayil, P. Samant, P. Samant, S. Shabana, S. Shabana, F. Varghese, F. Varghese, U. Upadhyay, U. Upadhyay, R. A. Yadav, R. A. Yadav, A. Partridge, E. Pendleton, R. Plant, Y. R. Petillot, Y. R. Petillot, M. Koskinopoulou, M. Koskinopoulou

“…Tracking algorithms and depth-sensing technologies are integrated to enable 3D spatial awareness during pick-and-place operations. …”
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Forecasting insect abundance using time series embedding and machine learning by Gabriel R. Palma, Rodrigo F. Mello, Wesley A.C. Godoy, Eduardo Engel, Douglas Lau, Charles Markham, Rafael A. Moral

“…We pre-processed the data using our newly proposed approach and more straightforward approaches commonly used to train learning algorithms. We evaluate the performance of the selected algorithms by looking at the Pearson correlation and Root Mean Squared Error obtained using one-step-ahead forecasting. …”
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Estimation of minimum miscible pressure in carbon dioxide gas injection using machine learning methods by Ali Akbari, Ali Ranjbar, Yousef Kazemzadeh, Fatemeh Mohammadinia, Amirjavad Borhani

“…Input data for these algorithms include CO2, H2S, N2, C1, C2, C3, C4, C5, C6, C7+, MWC5+, MWC7+, T, alongside vol/int. …”
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Enhancing palm precision agriculture: An approach based on deep learning and UAVs for efficient palm tree detection by Yosra Hajjaji, Wadii Boulila, Imed Riadh Farah, Anis Koubaa

“…We are currently investigating deep-learning-based object detection algorithms and remote sensing (RS) technologies to enhance industry efficiency. …”
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Prediction of Future Terrorist Activities Using Deep Neural Networks by M. Irfan Uddin, Nazir Zada, Furqan Aziz, Yousaf Saeed, Asim Zeb, Syed Atif Ali Shah, Mahmoud Ahmad Al-Khasawneh, Marwan Mahmoud

“…The performance of the DNN is compared with NN and the three machine learning algorithms, and it is demonstrated that the performance in DNN is more than 95% in terms of accuracy, precision, recall, and F1-Score, while ANN and traditional machine learning algorithms have achieved a maximum of 83% accuracy. …”
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SIGNAL FILTERING FOR SUDDEN SENSOR FAILURES BASED ON RECURRENT LEAST SQUARES METHOD by V. M. Artemiev, A. O. Naumov, L. L. Kokhan

“…It allows to design simple filtering algorithms with failure detection and to realize filter structure reorganization providing filter functionality.…”
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Optimization problems for construction foundations by Rimantas Belevičius, Saulius Valentinavičius

“…Solutions of a number of problems demonstrate the validity of proposed algorithms. …”
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Units in families of totally complex algebraic number fields by L. Ya. Vulakh

“…Multidimensional continued fraction algorithms associated with GLn(ℤk), where ℤk is the ring of integers of an imaginary quadratic field K, are introduced and applied to find systems of fundamental units in families of totally complex algebraic number fields of degrees four, six, and eight.…”
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