High-confidence assessment of functional impact of human mitochondrial non-synonymous genome variations by APOGEE. by Stefano Castellana, Caterina Fusilli, Gianluigi Mazzoccoli, Tommaso Biagini, Daniele Capocefalo, Massimo Carella, Angelo Luigi Vescovi, Tommaso Mazza

“…Since these tools proved to be rather incongruent, we have designed and implemented APOGEE, a machine-learning algorithm that outperforms all existing prediction methods in estimating the harmfulness of mitochondrial non-synonymous genome variations. …”
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Identification of Clusters in a Population With Obesity Using Machine Learning: Secondary Analysis of The Maastricht Study by Maik JM Beuken, Melanie Kleynen, Susy Braun, Kees Van Berkel, Carla van der Kallen, Annemarie Koster, Hans Bosma, Tos TJM Berendschot, Alfons JHM Houben, Nicole Dukers-Muijrers, Joop P van den Bergh, Abraham A Kroon, Iris M Kanera

“…To identify a subset of distinct, minimally redundant, predictive variables, we used the statistically equivalent signature algorithm. …”
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Sepsis-Associated Acute Kidney Disease Incidence, Trajectory, and Outcomes by Hsiu-Yin Chiang, Chih-Chia Liang, Ya-Luan Hsiao, Uyen-Minh Le, Yi-Ching Chang, Pei-Shan Chen, David Ray Chang, I-Wen Ting, Hung-Chieh Yeh, Chin-Chi Kuo

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Characteristics of gut and lung microbiota in patients with lung masses and their relationship with clinical features by Yanping Yang, Jiacheng Shen, Sulan Wei, Maosong Ye, Xing Zhao, Jian Zhou, Lin Tong, Jie Hu, Yuanlin Song, Shengdi Wu, Nuo Xu

“…For differentiating benign and malignant masses, the combination of Megasphaera and norank_p__Saccharibacteria in BALF demonstrated superior predictive performance, with an AUC reaching 0.8 (95% CI 0.59-1). …”
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Machine learning-based radiomics for differentiating lung cancer subtypes in brain metastases using CE-T1WI by Xueming Xia, Wei Du, Qiheng Gou

“…The models’ performance was evaluated using receiver operating characteristic (ROC) analysis and area under the curve (AUC) calculations, complemented by additional metrics such as accuracy, specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV).ResultsA total of 833 radiomic features were extracted from the ROIs. …”
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Digital Transformation in the Context of European Union’s Green Deal by Bertoncelj, Andrej

“…Both concepts have one thing in common, that is smart technologies, which is predicted to exponentially increase in market value and scope with time. …”
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Secure and efficient batch authentication scheme based on dynamic revocation mechanism in space information network by Yinghui ZHANG, Lingyun HU, Yixin LI, Jianting NING, Dong ZHENG

“…A secure and efficient batch authentication scheme based on dynamic revocation mechanism was proposed for the problem of cross-domain authentication of a large number of mobile users in space information networks.Early key negotiation was achieved by predicting the satellite trajectory and updating the session key in real time.Algorithms were designed for a single as well as a large number of mobile terminals to perform signing and verification, which effectively reduce the computational burden of satellites.Cuckoo filters were adopted by the new scheme to achieve dynamic revocation and malicious access control of mobile terminals.Finally, under the Diffie-Hellman assumption, the proposed scheme was proved to be resistant to replay and man-in-the-middle attacks based on a random oracle model and automated validation of internet security protocols and applications.Security goals such as traceability and revocability were achieved by the scheme, thus improving the efficiency of transmission and computation by more than 80% and 20%, respectively, compared with the existing optimal scheme.…”
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Enhanced pixel-level detection of food regions using a self-attention mechanism by Takuya Futagami

“…This study aims to increase the accuracy of pixel-level detection of food regions extraction algorithms based on saliency detection, which predicts noticeable image areas that are attractive to the human eye. …”
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Analysis of Dynamic Transaction Fee Blockchain Using Queueing Theory by Koki Inami, Tuan Phung-Duc

“…The processing fee varies significantly depending on other transactions; it is difficult to predict the fee, and it may be significantly high. …”
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Smart Manufacturing through Machine Learning: A Review, Perspective, and Future Directions to the Machining Industry by A. S. Rajesh, M. S. Prabhuswamy, Srinivasan Krishnasamy

“…One such subclass of artificial intelligence is machine learning, which uses a computer system for making predictions and performing definite tasks without any use of specific instructions to enhance the quality of the product, and rate of production, and to optimize the processes and parameters in machining operations. …”
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A Gaussian Process Latent Variable Model for Subspace Clustering by Shangfang Li

“…Moreover, it can directly predict the new samples by introducing a back constraint in the model, thus being more suitable for big data learning tasks such as analysis of chaotic time series and so on. …”
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A Framework for Determining the Big Five Personality Traits Using Machine Learning Classification through Graphology by null Samsuryadi, Rudi Kurniawan, Julian Supardi, null Sukemi, Fatma Susilawati Mohamad

“…These results indicated that the proposed framework can be well applied to predict the personality of the Big Five model through handwriting analysis features.…”
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Teaching deep networks to see shape: Lessons from a simplified visual world. by Christian Jarvers, Heiko Neumann

“…We design simple, artificial image datasets in which shape, color, and texture features can be used to predict the image class. By training networks from scratch to classify images with single features and feature combinations, we show that some network architectures are unable to learn to use shape features, whereas others are able to use shape in principle but are biased towards the other features. …”
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The influence of eye model parameter variations on simulated eye-tracking outcomes by Joshua Fischer, David van den Heever, Johan van der Merwe

“…This study investigated the influence that variations in eye model parameters have on the ability of simulated data to predict real-world eye-tracking outcomes. The real-world experiments performed by two pertinent comparative studies were replicated in a simulated environment using a high-complexity stochastic eye model that includes anatomically accurate distributions of eye biometry parameters. …”
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Probabilistic Operation of the Microgrids Including Active Loads and Distributed Generation Constrained to Flexibility and Reliability Indices by Hosein Hasan Shahi, Mehdi Nafar, Mohsen Simab

“…The proposed strategy attempts to provide the minimum expected operating cost for the MG, power sources, predicted pollutant emission, and expected energy not-supplied (EENS) because of an N − 1 event considering different applications. …”
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Neural mechanisms for the attention-mediated propagation of conceptual information in the human brain. by David Acunzo, Damiano Grignolio, Clayton Hickey

“…We find that variance in the amplitude of N2pc-an event-related potential (ERP) component closely linked to selective attention-predicts the emergence of conceptual information in a network including prefrontal, posterior parietal, and anterior insular cortex. …”
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Dynamic Simulation and Comprehensive Quantitative Evaluation of Rural Tourism Core Competitiveness Based on Neural Network by Shiyuan Gan

“…This paper first designs the neural network algorithm model, then analyzes the dynamic simulation model and comprehensive quantitative analysis, and then uses the artificial neural network algorithm to analyze and predict the core competitiveness of rural tourism. …”
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Random k conditional nearest neighbor for high-dimensional data by Jiaxuan Lu, Hyukjun Gweon

“…The k nearest neighbor (kNN) approach is a simple and effective algorithm for classification and a number of variants have been proposed based on the kNN algorithm. …”
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METHOD OT DATA AND KNOWLEDGE PROCESSING IN INTERNET WITH CIPHERING SUPPORT by V. A. Vishniakov, D. S. Borodaenko

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Simultaneous Determination of Caffeine and Taurine in Energy Drinks by FT-MIR Spectroscopy Coupled with Multivariate Analysis by Marcela González-Vázquez, Ofelia Gabriela Meza-Márquez, Tzayhri Gallardo-Velázquez, Guillermo Osorio-Revilla, José Luis Velázquez Hernández, Maylet Hernández-Martínez

“…The taurine and caffeine content in the 50 samples ranged between 0 and 69.51 mg/100 mL and 14.92 and 1126.17 mg/100 mL, respectively. The best prediction model was obtained with the partial least squares (PLS1) algorithm; for taurine, the following values were obtained: determination coefficient of calibration (Rc2) = 0.9999, standard error of calibration (SEC) = 0.15, determination coefficient of validation (Rv2) = 0.9997, and standard error of prediction (SEP) = 0.16; for caffeine, Rc2 = 0.9999, SEC = 0.26, Rv2 = 0.9999, and SEP = 0.32. …”
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