Possibilities of magnet-resonance tomography usage while examining patients with reccurent genital prolapse by Banakhevych R.M.

“…Reducing the distance while performing Valsalva samples from cervical pubo-coccygeal line 2-3 cm was seen as second-best result of the operation – 26,7%, questionable form of recurrence was observed in 15,6% of patients. The developed algorithm makes it possible to determine the extent of the procedure and to predict possible intraoperative complications and results of operations, to avoid changes of operation plan, to minimize the risk of recurrence and the need for re-surgery. …”
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IDENTIFICATION OF NOMINAL DYNAMIC CHARACTERISTICS OF AIRCRAFT GAS TEMPERATURE SENSORS by A. F. Sabitov, I. A. Safina

“…The developed method makes it possible to predict the dynamic performance of the specific types of gas temperature sensors in the expected operating conditions.…”
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Short-Term Power Load Forecasting Using Adaptive Mode Decomposition and Improved Least Squares Support Vector Machine by Wenjie Guo, Jie Liu, Jun Ma, Zheng Lan

“…Then, the ILSSVM is presented to predict different power load components, separately. …”
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Simulación del vaciado continuo de perfiles de aceros al carbono de baja aleación//Simulation of the continuous casting of low carbon steel profiles by Yusdel Díaz-Hernández, Alberto Fiol-Zulueta, José Arzola-Ruiz

“…The most outstanding characteristic of the model was the inclusion of complex processes of heat interchange, metal phase changes, distribution of temperatures in the mould, chemical composition of the metal, flow of water in the primary and<br />secondary cooling system and the casting speed. Moreover, the algorithm permitted to predict the behaviour of the process variables in the continuous casting of steel according to its profile and type.…”
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Linking dietary fiber to human malady through cumulative profiling of microbiota disturbance by Xin Zhang, Huan Liu, Yu Li, Yanlong Wen, Tianxin Xu, Chen Chen, Shuxia Hao, Jielun Hu, Shaoping Nie, Fei Gao, Gengjie Jia

“…By leveraging microbiota disturbance similarities, we (1) classified 32 types of dietary fibers into six functional subgroups, revealing correlations with fiber solubility; (2) established associations among 161 diseases, uncovering shared microbiota disturbance patterns that explain disease co‐occurrence (e.g., type II diabetes and kidney diseases) and distinct microbiota patterns that discern symptomatically similar diseases (e.g., inflammatory bowel disease and irritable bowel syndrome); (3) designed a body‐site‐specific microbiota disturbance scoring scheme, computing a disturbance score (DS) for each disease and highlighting the pronounced capacity of Crohn's disease to disturb gut microbiota (DS = 14.01) in contrast with food allergy's minimal capacity (DS = 0.74); (4) identified 1659 fiber‐disease associations, predicting the potential of dietary fiber to modulate specific microbiota changes associated with diseases of interest; (5) established murine models of inflammatory bowel disease to validate the preventive and therapeutic effects of arabinoxylan that notably perturbed the Bacteroidetes and Firmicutes phyla, as well as the Bacteroidetes and Lactobacillus genera, aligning with our model predictions. …”
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Screening for MicroRNA combination with engineered exosomes as a new tool against osteosarcoma in elderly patients by Jiyu Han, Jiyu Han, Zitong Zhao, Yanhong Wang, Yanhong Wang, Tao Yu, Daqian Wan, Daqian Wan

“…Next, we used FunRich software to predict the up-stream transcription factors (TFs) of differentially expressed miRNAs (DE-miRNAs). …”
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A Statistical Approach in Designing an RF-Based Human Crowd Density Estimation System by S. Y. Fadhlullah, Widad Ismail

“…A signal path loss propagation model was also proposed to assist in predicting the human crowd density. The human crowd properties verified by using the statistical approach may offer a new side of understanding and estimating the human crowd density.…”
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The dual-edged potential of AI autonomously defining loss functions by Abbas Ghori

“…Abstract A loss function is one of the key components considered in machine learning as they steer the model toward the optimal performance by quantifying the discrepancy between the predicted outcome and the actual outcome. They predominantly act as guiding principles for any optimization algorithm, thereby influencing both the convergence characteristics as well as the generalization of the model. …”
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Reactor modeling and kinetic parameters estimation for diethylbenzene (DEB) dehydrogenation reactions by M.E zeynali, H. Abedini, H. R. Sadri

“…The conversion of DEB and ethylvinyl benzene (EVB) in the reactor was predicted by mathematical modeling and compared with experimental results. …”
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Control strategies for multi-rotor wind turbines by F. Matras, M. Dinhoff Pedersen

“…In contrast to most literature on the topic, the underlying multi-rotor model includes the aerodynamic interactions between rotors. The model predicts that these interactions are central for effective control of multi-rotor wind turbines under some conditions. …”
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Digit recognition using decimal coding and artificial neural network by Toufik Datsi, Khalid Aznag, Ahmed El Oirrak

“…The backpropagation algorithm was used for the training dataset and feed-forward for the testing dataset. …”
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Fuzzy Pheromone Potential Fields for Virtual Pedestrian Simulation by Meriem Mandar, Azedine Boulmakoul

“…Said fields provide virtual pedestrians with better visibility of their surroundings and its various components (goals and obstacles). The predictions provided by the first-order traffic flow theory are confirmed by the results of the simulation. …”
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Identification of plankton habitats in the North Sea by Rene‐Marcel Plonus, Jens Floeter

“…Plankton distributions are closely linked to climate change and shape the seascape for higher trophic levels, so monitoring plankton distributions and defining ecological niches will help to understand and predict ecosystem responses. Here we apply a machine learning autoencoder and a density‐based clustering algorithm to high‐frequency datasets sampled with a ROTV Triaxus in the North Sea. …”
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APOPTOSIS IN CITY SYSTEMS: A BIOMIMETIC APPROACH TO CITY REGENERATION by Stephen Ajadi

“…Aided with streamlined programmatic principles, computational and algorithmic design, city systems are studied in an African context. …”
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Code Generation for Collectible Card Games with Complex APIs by John Licato, Logan Fields, Brayden Hollis

“…Given these practical limitations, is it possible to utilize these massive code-generation LMs to write code compatible with a given API? We develop an algorithm that selects code examples using a smaller LM trained to predict which features of an API are likely to be used in the resulting code, which is a simpler problem than actually generating the code. …”
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Control and readout of a 13-level trapped ion qudit by Pei Jiang Low, Brendan White, Crystal Senko

“…We report on tools we have developed for predicting energy states that are practical for qudit encoding, validated with good agreement with our experimental data. …”
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Optimization Design on Functionally Graded Cem for Trains Based on LPM Model with Calibrated Parameters by Ruixian Qin, Bingzhi Chen

“…The influence of parameters in graded function on interfacial force and peak acceleration is investigated and optimal design parameters are obtained by Nondominated Sorting Genetic Algorithm (NSGA-II). It is concluded that considering the behavior of the carbody can improve the accuracy of LPM in predicting the longitudinal response, and the gradient CEM is a potential energy configuration mode to improve the crashworthiness of the train in a collision.…”
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A numerical framework for simulating fluid-structure interaction phenomena by A. De Rosis, S. de Miranda, C. Burrafato, F. Ubertini

“…The lattice Boltzmann method is used to compute fluid dynamics, while the corotational finite element formulation together with the Time Discontinuous Galerkin method are adopted to predict structure dynamics. The Immersed Boundary method is used to account for the presence of an immersed solid in the lattice fluid background and to handle fluid-structure interface conditions, while a Volume-of-Fluid-based method is adopted to take trace of the evolution of the free surface. …”
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Modelling fatigue induced change in hyperelastic response of SBR/NR blends by Adtihya Nambiar, P. Mythravaruni

“…With the predicted parameters, the tensile test is simulated in ABAQUS incorporating element deletion and the results of the ABAQUS simulation are compared with experimental behaviour and model response. …”
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Multiobjective Optimization System of Extrusion Process Parameters for Targeted Microtubes Based on RSM and NSGA-II by Qingqing Zhang, Guobao Jin, Guanghui Dai

“…Finally, the nondominated sorting genetic algorithm II (NSGA-II) and response surface model (RSM) were mixed to find the optimal parameters of the tube extrusion. …”
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