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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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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Transfer Learning of High-Dimensional Stochastic Frontier Model via Elastic Net by Jiahao Chen, Wenjun Chen, Yunquan Song

“…When the target data is limited, transfer learning improves the accuracy of model estimation and prediction by transferring the source data. When the transferable source is known, a transfer learning algorithm for a high-dimensional stochastic frontier model is proposed based on Elastic Net. …”
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Analysis method of software failure modes in command information system based on complex networks by WANG Bo, JIANG Xuping, JING Huiqian

“…Based on a weighted undirected connected graph, this paper constructs a static model of the complex network for the command information system software, proposes a hierarchical centrality algorithm for the multi-layer neighbor influence of nodes, realizes the prediction of software network fault sources, and mines the fault propagation path based on the ant colony system algorithm. …”
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A clinical scoring system to prioritise investigation for tuberculosis among adults attending HIV clinics in South Africa. by Yasmeen Hanifa, Katherine L Fielding, Violet N Chihota, Lungiswa Adonis, Salome Charalambous, Nicola Foster, Alan Karstaedt, Kerrigan McCarthy, Mark P Nicol, Nontobeko T Ndlovu, Edina Sinanovic, Faieza Sahid, Wendy Stevens, Anna Vassall, Gavin J Churchyard, Alison D Grant

“…<h4>Objective</h4>To develop a diagnostic prediction model for TB, for symptomatic adults attending for routine HIV care, to prioritise TB investigation.…”
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Multi-Sensor Fusion and Machine Learning for Forest Age Mapping in Southeastern Tibet by Zelong Chi, Kaipeng Xu

“…Significant differences in reflectance among different age groups are observed in the 500–1000 nm spectral band, with 100 m resolution PROBA-V data being the most suitable for age prediction. The Random Forest model achieved an overall accuracy of 62% on the independent validation set, with canopy height, L-band radar data, and temperature seasonality being the most important predictors. …”
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A Study on Canopy Volume Measurement Model for Fruit Tree Application Based on LiDAR Point Cloud by Na Guo, Ning Xu, Jianming Kang, Guohai Zhang, Qingshan Meng, Mengmeng Niu, Wenxuan Wu, Xingguo Zhang

“…These results demonstrate that the PLSR model exhibits strong generalization ability, minimal prediction bias, and low average prediction error, offering a valuable reference for precision control of canopy spraying in orchards.…”
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MHOE-DETR: A Ship Detection Method for Small and Fuzzy Targets Based on Satellite Remote Sensing Image Data by Zhuhua Hu, Xiyu Fan, Yaochi Zhao, Wei Wu, Jie Liu

“…The network groups and processes input features in parallel, integrating both low-dimensional and high-dimensional features to alleviate the information bottleneck problem. The prediction head of the model uses the DINO decoder and applies contrastive denoising to remove useless prediction boxes. …”
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