Vehicular-Computational Resource Geofencing: Efficient Spatiotemporal Uncertainty Estimation by Ghada Afifi, Bassem Mokhtar

“…According to our evaluation, the service vehicles estimate the spatiotemporal uncertainty and predict the availability of computational resources with up to 99% confidence.…”
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Pixels relationship analysis for extracting building footprints by A. Emelyanov, A. Emelyanov, V. Knyaz, V. Knyaz, V. Kniaz, V. Kniaz, D. Artist

“…This work provides a comprehensive workflow for building extraction and improves their predicted area by regularization the boundaries of buildings. …”
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Inhibition of transcription by dactinomycin reveals a new characteristic of immunogenic cell stress by Juliette Humeau, Allan Sauvat, Giulia Cerrato, Wei Xie, Friedemann Loos, Francesca Iannantuoni, Lucillia Bezu, Sarah Lévesque, Juliette Paillet, Jonathan Pol, Marion Leduc, Laurence Zitvogel, Hugues de Thé, Oliver Kepp, Guido Kroemer

“…Here, we used an established model, built on artificial intelligence to identify, among a library of 50,000 compounds, anticancer agents that, based on their molecular descriptors, were predicted to induce ICD. This algorithm led us to the identification of dactinomycin (DACT, best known as actinomycin D), a highly potent cytotoxicant and ICD inducer that mediates immune‐dependent anticancer effects in vivo. …”
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In Situ Stress Inversion and Distribution Characteristics of Tunnel Based on Numerical Simulation and Neural Network Technology by Pei Zhang

“…Finally, the in situ stress in the study area was predicted. Through the analysis of the in situ stress field in the research target area, the stress boundary conditions are provided for the follow-up study, and the practical basis for the division of the dangerous area of the surrounding rock of the deep and long tunnel is provided.…”
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Channel modeling of molecular communication via free diffusion with multiple receiver by Zhuo SUN, Xu BAO, Jie LIN, Wence ZHANG

“…A coexistence scenario with a point source, a pair of absorbing and transparent receiver was considered, an interference factor was introduced in the proposed channel model based on the receiving molecular probability in the transparent receiver considering the influences of the absorbing receiver on the transparent one.Furthermore, the channel model of point source and transparent receiver had been proposed by using Levenberg-Marquardt algorithm combined with artificial neural network to study and predict channel model parameters.The simulation results not only verify the effectiveness of the proposed channel model, but also show that the peak time of any point in the environment is directly proportional to the square of the distance from the point source to the receiver, and inversely proportional to the molecular diffusion coefficient, and the peak time is not affected by the absorbing receiver in the environment.…”
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Joint optimization of edge computing and caching in NDN by Yu ZHANG, Min CHENG

“…Named data networking (NDN) is architecturally easier to integrate with edge computing as its routing is based on content names and its nodes have caching capabilities.Firstly, an integrated framework was proposed for implementing dynamic coordination of networking, computing and caching in NDN.Then, considering the variability of content popularity in different regions, a matrix factorization-based algorithm was proposed to predict local content popularity, and deep reinforcement learning was used to solve the the problem of joint optimization for computing and caching resource allocation and cache placement policy with the goal of maximizing system operating profit.Finally, the simulation environment was built in ndnSIM.The simulation results show that the proposed scheme has significant advantages in improving cache hit rate, reducing the average delay and the load on the remote servers.…”
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Image colorization based on transformer by Min Xu

“…The encoder primarily extracts features from the input grayscale image, while the decoder utilizes these features alongside the self-attention mechanism and contextual information to predict the corresponding $$a^*$$ and $$b^*$$ chrominance components in CIELAB color space, and combines the channel $$L^*$$ of the input image to achieve image colorization. …”
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An Energy-Domain IR NUC Method Based on Unsupervised Learning by Ting Li, Xuefeng Lai, Sheng Liao, Yucheng Xia

“…This method exploits the inherent physical correlation within the calibration dataset and sets the average predicted energy-domain value of the same blackbody temperature as the learning goal. …”
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Modelling the Shear-Tension Coupling of Woven Engineering Fabrics by F. Abdiwi, P. Harrison, W. R. Yu

“…Finally, the effectiveness of the method is evaluated and shown to provide qualitatively good predictions.…”
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Modelling of organizational and technological operation reliability of excavator sets by O. V. Demidenko, S. M. Kuznetsov, N. E. Alekseev

“…With this method it is possible to form a sample and calculate the basic parameters of the samples of construction machinery’s operation on any object. This will allow predicting for certain the period of construction and installation works at the design stage of construction. …”
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LOGIC SIMULATION OF LIFE SUPPORT SYSTEM COMPONENT IN REAL TIME by A. S. Marchenko, A. B. Sulin

“…The article proposed the use of simulation methods for evaluating the effectiveness of a stepped fan engine speed control while maintaining the air flow volume in the set boundaries of the «fan-filter» system. A detailed algorithm of the program made on the basis of an Any Logic software package. …”
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Imaging in Patients with Merkel Cell Carcinoma by Elisabeth Enzenhofer, Philipp Ubl, Christian Czerny, Boban M. Erovic

“…Accurate assessment of nodal involvement in patients with MCC predicts significantly overall outcome (Smith et al., 2012 and Ortin-Perez et al., 2007). …”
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Clinical Pathways Guided by Remotely Monitoring Cardiac Device Data: The Future of Device Heart Failure Management? by Joanne K Taylor, Fozia Zahir Ahmed

“…As standalone diagnostic tools, individual physiological metrics and algorithm-based systems have demonstrated utility in predicting future events, but the integration of remote monitoring data with existing clinical care pathways for device HF patients is not well described. …”
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Exploration for the physical origin and impact of chemical short-range order in high-entropy alloys: Machine learning-assisted study by Panhua Shi, Zhen Xie, Jiaxuan Si, Jianqiao Yu, Xiaoyong Wu, Yaojun Li, Qiu Xu, Yuexia Wang

“…In this study, we introduced a set of interpretable ML workflows and determined the best algorithm (kernel ridge regression (KRR)) for predicting the atomic stress in HEAs, which can deepen the understanding of the formation mechanism of CSRO. …”
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Identification method of roof rock interface based on response characteristics of drilling parameters by LI Dianshang, LIU Cancan, WANG Chuanbing, REN Bo, REN Shuai, KANG Zhipeng

“…On-site tests yielded 0.04m of average error in predicting the position of the coal rock interface. …”
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Potential Herb-Drug Interactions Among Elderly Nursing Home Residents in Romania by Hanna Sebesi, László István Bába, Melinda Kolcsár, Zsolt Gáll, Soma Dávid

“…AIM: Our study investigates the algorithm-predicted HDIs during herb-drug coadministration among elderly patients in nursing homes in a Romanian sample. …”
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Efficient Detection of Mind Wandering During Reading Aloud Using Blinks, Pitch Frequency, and Reading Rate by Amir Rabinovitch, Eden Ben Baruch, Maor Siton, Nuphar Avital, Menahem Yeari, Dror Malka

“…A voice activity detection (VAD) technique was also used to recognize human speech. The algorithm achieved 76% accuracy in predicting mind wandering during specific text segments, demonstrating the feasibility of using noninvasive physiological indicators. …”
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Advancing a machine learning-based decision support tool for pre-hospital assessment of dyspnoea by emergency medical service clinicians: a retrospective observational study by Wivica Kauppi, Henrik Imberg, Johan Herlitz, Oskar Molin, Christer Axelsson, Carl Magnusson

“…The gradient boosting algorithm had the overall best performance, with excellent calibration of the predictions, and consistently showed higher sensitivity to detect SAE than the other methods. …”
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Reconstructing the regulatory programs underlying the phenotypic plasticity of neural cancers by Ida Larsson, Felix Held, Gergana Popova, Alper Koc, Soumi Kundu, Rebecka Jörnsten, Sven Nelander

“…Here we present “single-cell regulatory-driven clustering” (scregclust), a method that reconstructs cellular regulatory programs from extensive collections of single-cell RNA sequencing (scRNA-seq) data from both tumors and developing tissues. The algorithm efficiently divides target genes into modules, predicting key transcription factors and kinases with minimal computational time. …”
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Neural network technologies for forecasting and controlling electricity consumption in energy systems by the genetic method by Nikolay K. Poluyanovich, Oleg V. Kachelaev, Marina N. Dubyago, Talia Hernandez Falcón

“…The authors have developed the neural network models and carried out the study to find the optimal structure of a neural network, and the influence of specified neural networks hyperparameters on the error in predicting power consumption. The developed management methodology and technologies are applied in the structure of the software modeling system to manage the regional energy system of autonomous consumers. …”
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