CO21 | Viscoelastic testing in inherited bleeding disorders: a cross-sectional comparison between viscoelastic coagulation monitoring (VCM) and rotational thromboelastometry (ROTE...

“…Results: VCM showed significant prolongation of clotting time (CT) and clot-formation time (CFT) and a significant reduction in maximum clot firmness (MCF) in both HA and VWD versus controls (ANOVA p <0.001). …”
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Lithium-Ion Battery Health State Prediction Based on Improved War Optimization Assisted-Long and Short-Term Memory Network by Xiankun Wei, Mingli Mo, Silun Peng

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Metaheuristic Prediction Models for Kerf Deviation in Nd-YAG Laser Cutting of AlZnMgCu1.5 Alloy by Arulvalavan Tamilarasan, Devaraj Rajamani

“…A detailed investigation was conducted to examine the effects of various parameters on kerf deviation. The metaheuristic algorithms (i.e., Giant Trevally Optimizer—GTO; and Zebra Optimization Algorithm—ZOA) were implemented to determine the optimum process parameters for producing the best performance measures. …”
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Low-Complexity Distortionless Techniques for Peak Power Reduction in OFDM Communication Systems by A. Ghassemi, T. A. Gulliver

“…The three most effective distortionless techniques for PAPR reduction are partial transmit sequence (PTS), selective mapping (SLM), and tone reservation (TR). …”
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Torque ripple reduction and increasing of torque per volume for hybrid electrical vehicle by A. Hosseinpour

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Gaining transparency in Uber’s algorithmic management by Jessica Pidoux, Sofia Kypraiou, Paul-Olivier Dehaye

“…Nevertheless, this dependence and the resulting economic losses and gains are passed on to drivers individually as “algorithmic predictability risk”. Indeed, drivers’ data are controlled by Uber to make automated predictions of supply and demand for the benefit of the platform exclusively.…”
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Computational complexity, algorithmic scope, and evolution by Leonhard Sidl, Maximilian Faissner, Manuel Uhlir, Cristian A Velandia-Huerto, Maria Waldl, Hua-Ting Yao, Ivo L Hofacker, Peter F Stadler

“…We use RNA secondary structure prediction as a simple surrogate for developmental programs to demonstrate that the salient features of the genotype–phenotype map remain intact even if ‘simpler’ algorithms are employed that correctly compute the structures only for small subsets of instances, albeit quantitative differences depending on the choice of alternative algorithms can be observed.…”
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Molecular Beacon Sequence Design Algorithm by W. Todd Monroe, Frederick R. Haselton

“…This analysis is carried out using mfold structural predictions along with other free Web-based tools. For smaller laboratories where molecular beacons are not the focus of research, the public domain algorithm described here may be usefully employed to aid in molecular beacon design.…”
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An Antenna Array Sidelobe Level Reduction Approach through Invasive Weed Optimization by Geng Sun, Yanheng Liu, Han Li, Shuang Liang, Aimin Wang, Boyu Li

“…The results show that IWO has a better performance in terms of the accuracy, the convergence rate, and the stability compared with other algorithms for the SLL reductions. Moreover, the electromagnetic simulation results also show that IWO achieves the best performance for the beam pattern synthesis of the antenna arrays in practical conditions.…”
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Algorithm profiling for architectures with dataflow accelerators by Nenad Korolija, Veljko Milutinović, Borko Furht

“…As a result, it is not always obvious whether programming dataflow architectures for certain algorithms is worth the effort needed. Therefore, there is a need for a programmer to be able to predict the outcome of programming for dataflow architectures in terms of accelerating program execution and power savings. …”
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Adaptive dimensionality reduction for neural network-based online principal component analysis. by Nico Migenda, Ralf Möller, Wolfram Schenck

“…While the continuous update of the principal components is widely studied, the available algorithms for dimensionality adjustment are limited to an increment of one in neural network-based and incremental PCA. …”
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Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment by Oluwatobi Adeleke, Obafemi O. Olatunji, Tien-Chien Jen, Iretioluwa Olawuyi

“…This study proposes a hybrid network of adaptive neuro-fuzzy inference system (ANFIS) with genetic algorithm (GA) to predict the higher heating value (HHV) of municipal solid waste (MSW). …”
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QSAR Model for Prediction of some Non-Nucleoside Inhibitors of Dengue Virus Serotype 4 NS5 using GFA-MLR Approach by Samuel Adawara, Gideon Shallangwa, Paul Mamza, Abdulkadir Ibrahim

“…Thus, the model can be used to predict the activity of new chemicals within its applicability domain. …”
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CFD investigation and ANN prediction of heat transfer coefficient for fully developed turbulent air flow around double V-baffle turbulators by Abdulaziz Alasiri, H.E. Fawaz

“…The ANN model demonstrates excellent predictive performance, yielding values close to 1 for R2 and r, along with extremely low values for MSE, MAPE, MSLE, and log-cosh loss (0.01, 0.6 %, 0.001, and 0.01, respectively), demonstrating the ANN model's high predictive accuracy.…”
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Integrated Planning for Shared Electric Vehicle System Considering Carbon Emission Reduction by Xiaohui Sun, Yumei Mi, Askar Ahtam, Zhi Zuo

“…Secondly, a charging demand simulation predictive model framework was designed. Finally, an SEV scheduling model with maximal operating income and minimal scheduling costs as optimization objectives was constructed considering the benefits of carbon emission reduction. …”
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A Comparative Study of Hybrid Adaptive Neuro-Fuzzy Inference Systems to Predict the Unconfined Compressive Strength of Rocks by Annabelle Graham, Emma Scott

“…Performance metrics like R2, RMSE, NMSE, MAE, and n_10 index were used to assess the predictive capability of models, indicating that ANAS with maximum and minimum =3.103, has the most optimal prediction performance for practical applications.…”
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A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy by R. Sudharsan, E. N. Ganesh

Subjects: “…customer churn prediction…”
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A dynamic prediction method for surface mining subsidence based on dynamic probability integral model and Logistic model by Lei HAN, Xinxin QI, Tianjun WANG, Chunmin PEI, Xudong WANG

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Medium and Long Term Wind Power Prediction Based on Graph Convolutional Network and Wind Velocity Differential Fitting by Zihan CHEN, Wei TENG, Xuefeng XU, Xian DING, Yibing LIU

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Extreme high accuracy prediction and design of Fe-C-Cr-Mn-Si steel using machine learning by Hao Wu, Jianyuan Zhang, Jintao Zhang, Chengjie Ge, Lu Ren, Xinkun Suo

“…In this study, a data-driven model combining machine learning (ML), firefly optimization algorithm (FA) and conditional generative adversarial networks (CGANs) were proposed to predict solid solution strengthening theory of Fe-C-Cr-Mn-Si steel. …”
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