Financial Sustainability of the Russian Higher Education Institutions: Quantitative Analysis by D. A. Endovitsky, V. V. Korotkikh, A. V. Krivosheev

“…Non-parametric methods for data analysis and machine learning.Results. We proposed two groups of working hypothesis. …”
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Adaptive sensing scheme using naive Bayes classification for environment monitoring with drone by Yao-Hua Ho, Yu-Te Huang, Hao-Hua Chu, Ling-Jyh Chen

“…Our results show that the naive Bayes classification–enhanced adaptive return-to-home sensing scheme is able to avoid oscillation in sensing and guarantees return-to-home feature while behaving more cost-effective in parameter tuning than the other machine learning–based approaches.…”
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Secure and Privacy Enhanced Gait Authentication on Smart Phone by Thang Hoang, Deokjai Choi

“…These traditional systems are mostly based on pattern recognition and machine learning algorithms, wherein original biometric templates or extracted features are stored under unconcealed form for performing matching with a new biometric sample in the authentication phase. …”
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A new model for lung cancer prediction based on differential evolution algorithm and effective feature selection by Amid Khatibi Bardsiri

“…By using advanced machine learning techniques and optimization algorithms, early prediction and diagnosis of this disease can be achieved. …”
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Automated identification of bulk structures, two-dimensional materials, and interfaces using symmetry-based clustering by Thea Denell, Lauri Himanen, Markus Scheidgen, Claudia Draxl

“…Because SBC is not a machine learning-based method, it requires no prior training. …”
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Review of Recent Advances in Predictive Maintenance and Cybersecurity for Solar Plants by Younes Ledmaoui, Adila El Maghraoui, Mohamed El Aroussi, Rachid Saadane

“…It also highlights the Internet of Things (IoT), machine learning (ML), and deep learning (DL), which are all incorporated into solar panel predictive maintenance. …”
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A Bibliometric Analysis on Federated Learning by Ersin Namlı, Yusuf Sait Türkan, Mesut Ulu, Ömer Algorabi

“…The emergence of FL as a novel machine-learning approach and the volume of relevant papers and studies now call for a thorough investigation of FL. …”
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Hybrid Deep Learning Techniques for Improved Anomaly Detection in IoT Environments by Hanan Abbas Mohammad

“…Hence, a number of researchers are attempting to build an intrusion detection system utilizing machine learning and deep learning algorithms. In this work, a novel attack detection model is proposed by superimposing Whale Optimization Algorithm and Bidirectional Long Short-Term Memory (WB-LSTM) together. …”
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Drug discovery and mechanism prediction with explainable graph neural networks by Conghao Wang, Gaurav Asok Kumar, Jagath C. Rajapakse

“…The unprecedented development of machine learning and deep learning algorithms has expedited the drug response prediction research. …”
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A Roadway Safety Sustainable Approach: Modeling for Real-Time Traffic Crash with Limited Data and Its Reliability Verification by Zhenzhou Yuan, Kun He, Yang Yang

“…Finally, the applicability of machine learning and statistical methods to low precision data set was compared. …”
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Investigations on tool wear behavior in turning AISI 304 stainless steel: An empirical and neural network modeling approach by Satish Chinchanikar, Mahendra Gadge

“…An ANN was modeled using a feedforward backpropagation machine learning technique. In this study, a higher prediction accuracy of 0.9975 was achieved with ANN model as compared to the empirical model. …”
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Using Burstiness for Network Applications Classification by Hussein Oudah, Bogdan Ghita, Taimur Bakhshi, Abdulrahman Alruban, David J. Walker

“…This paper proposes a novel flow statistical-based set of features that may be used for classifying applications by leveraging machine learning algorithms to yield high accuracy in identifying the type of applications that generate the traffic. …”
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Naive Bayes-Guided Bat Algorithm for Feature Selection by Ahmed Majid Taha, Aida Mustapha, Soong-Der Chen

“…Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
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An Explainable Stacked Ensemble Model for Static Route-Free Estimation of Time of Arrival by Sören Schleibaum, Jörg P. Müller, Monika Sester

“…To solve the underlying hard computational problem with high precision, machine learning (ML) models for ETA are the state of the art. …”
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Characterizing mutation-treatment effects using clinico-genomics data of 78,287 patients with 20 types of cancers by Ruishan Liu, Shemra Rizzo, Lisa Wang, Nayan Chaudhary, Sophia Maund, Marius Rene Garmhausen, Sarah McGough, Ryan Copping, James Zou

“…Leveraging the large number of identified predictive mutations, we developed a machine learning model to generate a risk score for response to immunotherapy in patients with advanced non-small cell lung cancer (aNSCLC). …”
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Deep Learning Algorithms and Multicriteria Decision-Making Used in Big Data: A Systematic Literature Review by Mei Yang, Shah Nazir, Qingshan Xu, Shaukat Ali

“…The research finds novel means to make the decision support system for the problems of big data using multiple criteria in integration with machine learning and artificial intelligence approaches.…”
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A Systematic Literature Review on Defense Techniques Against Routing Attacks in Internet of Things by Lanka Chris Sejaphala, Vusimuzi Malele, Francis Lugayizi

“…., Secure-Protocol, conventional Intrusion Detection Systems (IDS), and Machine Learning (ML)-based. This systematic literature review explores 39 published papers in the domain of defense techniques against routing attacks in RPL-based IoT. …”
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Effectiveness of the Spatial Domain Techniques in Digital Image Steganography by Rosshini Selvamani, Yusliza Yusoff

“…In addition to using statistics as a foundation, convolution neural networks (CNN), generative adversarial networks (GAN), coverless approaches, and machine learning are all used to construct steganographic methods. …”
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Barriers and Enablers of AI Adoption in Human Resource Management: A Critical Analysis of Organizational and Technological Factors by Mitra Madanchian, Hamed Taherdoost

“…Change aversion, data security worries, and integration expenses are major roadblocks, but strong digital leadership, company culture, and advancements in NLP and machine learning are key enablers. This paper presents a complex analysis that questions the common perception of AI as only disruptive by delving into the relationship between power dynamics, corporate culture, and technology infrastructures. …”
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Multi-GPU Development of a Neural Networks Based Reconstructor for Adaptive Optics by Carlos González-Gutiérrez, María Luisa Sánchez-Rodríguez, José Luis Calvo-Rolle, Francisco Javier de Cos Juez

“…The Complex Atmospheric Reconstructor based on Machine Learning (CARMEN) is an algorithm based on artificial neural networks, designed to compensate the atmospheric turbulence. …”
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