Peak to average power ratio reduction techniques based on chirp selection for single and multi‐user orthogonal chirp division multiplexing system by Vincent Savaux

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Uncertainty estimation with prediction-error circuits by Loreen Hertäg, Katharina A. Wilmes, Claudia Clopath

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Graph Neural Networks for Link Prediction by Alina Lazar

“…Graph Neural Networks (GNNs) belong to a class of deep learning methods that are specialized for extracting critical information and making accurate predictions on graph representations. Researchers have been striving to adapt neural networks to process graph data for over a decade. …”
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A Deterministic Approach to Earthquake Prediction by Vittorio Sgrigna, Livio Conti

“…Unfortunately, up to now, what is lacking is the demonstration of a causal relationship (with explained physical processes and looking for a correlation) between data gathered simultaneously and continuously by space observations and ground-based measurements. …”
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Conformational ensembles for protein structure prediction by Jiaan Yang, Wen Xiang Cheng, Peng Zhang, Gang Wu, Si Tong Sheng, Junjie Yang, Suwen Zhao, Qiyue Hu, Wenxin Ji, Qiong Shi

“…The P53_HUMAN as a well-known protein and LEF1_HUMAN and Q8GT36_SPIOL as typical disordered proteins are token as the benchmark to evaluate the predicted outcomes. The results demonstrated an effective algorithm and biological meaningful process well to predict protein multiple conformation structures.…”
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Prediction and data curation in digital humanitarianism by Gianluca Iazzolino, Nimesh Dhungana

“…We argue that while there is no such thing as a “humanitarian dataset”, there are contested processes of datafied humanitarian knowledge production that are situated in specific contexts. …”
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Comorbidity as an interdisciplinary problem: prediction capability by M. M. Tlish, Zh. Yu. Naatyzh, T. G. Kuznetsova

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In Silico Pharmacological Prediction of Substituted Aminonitriles by Bianca Araújo Fernandes Veras, Pamela Isabel Japura Huanca, Igor de Sousa Oliveira, Rafael Trindade Maia, Helivaldo Diogenes da Silva Souza, Sávio Benvindo Ferreira

“…Aminonitriles are heterocyclic compounds commonly used as intermediates in the synthesis of various compounds, but which have versatility in physiological processes, with peculiar characteristics and high biological value that still need to be investigated with greater avidity. …”
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Event Prediction Using Spatial–Temporal Data for a Predictive Traffic Accident Approach Through Categorical Logic by Eleftheria Koutsaki, George Vardakis, Nikos Papadakis

“…For this reason, the initial forecasting applications process data for specific situations, in terms of number and characteristics, while, at the same time, having the possibility to respond to different situations, e.g., an application that predicts a pandemic can also predict a central phenomenon, simply by using different data types. …”
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Diabetes Mellitus Disease Prediction and Type Classification Involving Predictive Modeling Using Machine Learning Techniques and Classifiers by B. Shamreen Ahamed, Meenakshi S. Arya, S. K. B. Sangeetha, Nancy V. Auxilia Osvin

“…The Diabetes prediction process can be further improvised by identifying the type a person is being affected by and the probability of the occurrence of the related diseases. …”
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Predictive Modeling of Surface Subsidence Considering Different Environmental Risk Zones by Yunsong Li, Yongjun Qin, Liangfu Xie, Yangchun Yuan, Jie Ran

“…Adopt four different noise reduction algorithms for data noise reduction on the raw data of the monitoring points at the intervals of different risk zones, and combine the time series prediction as well as the deep learning prediction method to get the prediction model for environmental risk zoning based on the environmental risk zoning. …”
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Model predictive control for energy efficient AC motor drives: An overview by Muhammad Bilal Shahid, Weidong Jin, Muhammad Abbas Abbasi, Abdul Rashid Bin Husain, Hafiz Mudassir Munir, Mannan Hassan, Aymen Flah, Ahmed Saad Eddine Souissi, Thamer A. H. Alghamdi

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Model Predictive Control of Demagnetization Vibration in Permanent Magnet Synchronous Motor by Wantai Liu, Bifeng Zhou

“…This article proposes a new nonlinear processing method combined with model predictive control (MPC) to study the demagnetization vibration problem of permanent magnet synchronous motors (PMSMs). …”
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Possibilities and Limitations of the Use of Hydrogen in Different Metallurgical Sectors by Casper van der Eijk, Halvor Dalaker, Jafar Safarian

“…Moreover, hydrogen shows promise in other metal production processes as well. One application involves utilizing hydrogen for effective selective reduction copper from copper slags with a low amount of iron being reduced. …”
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Machine learning-driven predictive modeling of mechanical properties in diverse steels by Movaffaq Kateb, Sahar Safarian

“…This study highlights the feasibility of using small, realistic datasets to develop effective ML models for predicting mechanical properties in steel design. The methodology can also be readily extended to investigate processing-property relationships in other systems, offering a versatile approach for advancing materials science through data-driven techniques.…”
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Improving Data Quality with Advanced Pre-Processing of MWD Data by Alla Sapronova, Thomas Marcher

“…In geotechnical engineering, an accurate prediction is essential for the safety and effectiveness of construction projects. …”
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SUPPLEMENTS TO THE PROBLEM OF ENERGY CONSUMPTION IN REDUCING LIGNOCELLULOSES BIOMASS SIZE TO PRODUCE ENERGY by Raluca SFÎRU, Petru CARDEI, Cornelia MURARU-IONEL, Vergil MURARU

“…The results of this article are starting points for a systemic approach to this biomass processing process. A first systematization is fixing 13 parameters that are included in the model of the biomass size reduction phenomenon. …”
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Unsupervised hypernymy directionality prediction using context terms by Thushara Manjari Naduvilakandy, Hyeju Jang, Mohammad Al Hasan

“…Hypernymy directionality prediction is an important task in Natural Language Processing (NLP) due to its significant usages in natural language understanding and generation. …”
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Method of load balancing for computer cluster of data processing center by N. Yu. Bratchenko, V. P. Mochalov, I. S. Palkanov

“…The fractal properties of network traffic are the rationale for the possibility of prediction, allow with a fairly high probability to predict the appearance of bursts and drops in its activity at certain time intervals, identify periods of possible overload of servers and network equipment, and make it possible to develop methods for effective planning and distribution of tasks within the data center, ensuring a statistically uniform loading its functional elements. …”
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METHOD OF LOAD BALANCING FOR COMPUTER CLUSTER OF DATA PROCESSING CENTER by N. Yu. Bratchenko, V. P. Mochalov, I. S. Palkanov

“…The fractal properties of network traffic are the rationale for the possibility of prediction, allow with a fairly high probability to predict the appearance of bursts and drops in its activity at certain time intervals, identify periods of possible overload of servers and network equipment, and make it possible to develop methods for effective planning and distribution of tasks within the data center, ensuring a statistically uniform loading its functional elements. …”
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