Design and analysis of antenna through machine learning for next-generation IoT system by Rachit Jain, R. Ramya, Vandana Vikas Thakare, P. K. Singhal

“…Notably, the CatBoost algorithm demonstrates superior performance, achieving 77.4% accuracy in predicting antenna return loss. …”
Get full text

IMPLEMENTASI METODE RANDOM FOREST DALAM MEMPREDIKSI SINYAL PERGERAKAN SAHAM by MOCH. ANJAS APRIHARTHA, M. HUSNIYADI, TAUFIK NUR ALAM

“…Random forest is a combination algorithm of several decision trees used to solve prediction or classification problems. …”
Get full text

Characterization of the Collagen Extraction Manufacturing Process Using Markov Chains and Artificial Neural Networks by Rosa Trasvina-Osorio, Sergio Alonso-Romero, Juan de Anda-Suarez, Valentin Calzada-Ledesma, Javier Yanez-Mendiola, Luis Fernando Villanueva-Jimenez, Erick Rojas-Mancera

“…In the second stage, the predictive model MCMC-ANN presented a mean square error (MSE) of 0.00171, and a standard deviation (SD) of 0.00133. …”
Get full text

Optimal design of frame structures equipped with viscous dampers using machine learning techniques by Yi Wen, Jianze Wang, Jun Xu, Kaoshan Dai, Yuanfeng Shi, Reza Sharbati

“…The built models achieved an average R2 of 0.955 for the testing dataset, indicating a high level of predictive accuracy. Then, with the target of minimizing seismic responses of the structural system, the developed DP-based optimization algorithm effectively identifies the optimal damper arrangement for the considered three structure cases. …”
Get full text

Delta-radiomics Entropy Based on Tumor Heterogeneity Concept – Response Predictor to Irradiation for Unresectable/recurrent Glioblastoma by Camil Ciprian MIRESTEAN, Roxana Irina IANCU, Dragos Teodor IANCU

“…Radiomics, a new subdomain of artificial intelligence (AI), relies on advanced analysis in high-resolution medical imaging to establish diagnostic, prognostic and predictive models for clinical medicine. The variation of the delta-radiomics parameters analyzed within a tumor volume may be via tumor heterogeneity indirectly correlated with the response to treatment. …”
Get full text

Eecs-fl: energy-efficient client selection for federated learning in AIoT by Yiyang Zhang, Yiming Luo, Tao Yang, Xiaofeng Wu, Bo Hu

“…Experimental results show that incorporating WPT leads to a reduction in unit energy consumption by over 24.54%; while, the proposed algorithm achieves a reduction of over 15.31% compared to random selection. …”
Get full text

Interperiod coherent integration of the received signal with a variable repetition period of the probing signal by S. R. Heister, P. G. Semashko

Get full text

Assessing Similarity Between Datasets Using Vector Representations by А. А. Usatoff, A. M. Nedzved, Guo Jiran

Get full text

Using Machine Learning for Recognition of Alzheimer’s Disease Based on Transcription Information by U. A. Vishniakou, Chu Yue Yu

Get full text

Gas adsorption meets geometric deep learning: points, set and match by Antonios P. Sarikas, Konstantinos Gkagkas, George E. Froudakis

“…Recently, machine learning (ML) pipelines have been established as the go-to method for large scale screening by means of predictive models. These are typically built in a descriptor-based manner, meaning that the structure must be first coarse-grained into a 1D fingerprint before it is fed to the ML algorithm. …”
Get full text

Magnetic resonance imaging of cruciate ligament disorders: current updates by Tanda Yang, Yexin Li, Longtao Yang, Qian Liu

“…AI plays a crucial role in automating radiological estimations and enabling data-driven predictions of future events. Despite the transformative impact of advanced MRI techniques on the analytical and diagnostic algorithms related to cruciate ligament disorders, future efforts are warranted to address challenges such as economic burdens and ethical considerations.…”
Get full text

Multimodal Deep Learning for Android Malware Classification by James Arrowsmith, Teo Susnjak, Julian Jang-Jaccard

“…We synthesise these modalities by combining predictions from convolutional and graph neural networks with a multilayer perceptron. …”
Get full text

Are Electromyography Data a Fingerprint for Patients with Cerebral Palsy (CP)? by Mehrdad Davoudi, Firooz Salami, Robert Reisig, Dimitrios A. Patikas, Nicholas A. Beckmann, Katharina S. Gather, Sebastian I. Wolf

“…Regarding EMG, a significant reduction was only observed in the ND of the rectus femoris (<i>p</i>-value < 0.001) and soleus (<i>p</i>-value = 0.006). …”
Get full text

THE USE OF INTERACTIVE STUDYING METHODS IN TEACHING OPERATIVE SURGERY AND TOPOGRAPHIC ANATOMY by V.M. Fedorak

“…However, on the ground of current laws it’s totally impossible to obtain cadaveric material and organs of dead people, and strict requirements of Bioethics Commission on the use of animals in education led to a strong reduction of lessons performed on animals. …”
Get full text

Performances Comparison for a Rotating Shaft Suspended by 4-Axis Radial Active Magnetic Bearings via 𝜇-Synthesis, Loop-Shaping Design, and Sub(𝐻)∞with Uncertainties by G. Barbaraci, G. Virzi' Mariotti

“…On contrary PID controller does not depend on angular speed and it can be easily implemented according some simple rules. Predictive control is another interesting controller characterized by a multiple controller operating in different condition in order to get the minimum of cost function, but also in this case the angular speed is introduce for the same reason discussed before.…”
Get full text

Realtime Precise Orbit Determination Technology for LEO Mega-Constellation by Zhen LI, Chuang SHI

“…Supported by GNSS, it analyzed the advantages and disadvantages of solving LEO satellite orbit on the ground or onboard the satellites.The high-fidelity non-conservative force models were applied to the real-time orbit determination algorithm.To separate the kinematic and dynamic orbit determination process had been a great advantage for LEO satellites with much frequent orbital maneuvers.The test results showed that the accuracy of accelerations computed from the radiation pressure and atmospheric drag non-conservation force models were around 5 nm/s².Use the broadcast ephemeris, the real-time orbit determination algorithm could get an accuracy of 0.8 m in the satellites′ positions and 1.1 mm/s accuracy in the satellites′ velocity.When the real-time precise ephemeris of GNSS satellites were provided, the algorithm could get an accuracy of 8 cm in the LEO satellites′ position and 0.1 mm/s in the velocity.The method for real-time orbit determination and orbit prediction in this paper could be used to support the construction of navigation system with the mega-constellations.…”
Get full text

Dynamic Bayesian Network Model for Overhead Power Lines Affected by Hurricanes by Kehkashan Fatima, Hussain Shareef

“…To characterize the stochastic properties of HIF, Monte Carlo simulation (MCS) is employed in conjunction with fragility curves (FC) and the scenario reduction (SCENRED) algorithm. The proposed DBN model evaluates the probability of asset failure and compares the results using stochastic Monte Carlo simulation based on the fragility curve scenario reduction algorithm (FC-MCS-SCENRED) model. …”
Get full text

Occupant-Centric Visual Comfort Assessment and Optimization of Passive Solar Façade Shading Systems through View-Based Analysis of Daylight Glare Probability, View Content, and Spa... by Martin Ivanov, Jun Sato

“…The proposed framework employs an adaptive optimization algorithm that iteratively generates and refines shading device configurations, effectively balancing glare reduction, external visibility, and visual complexity. …”
Get full text

Shape Optimization of Multi-chamber Acoustical Plenums Using the BEM, Neural Networks, and the GA Method by Ying-Chun CHANG, Ho-Chih CHENG, Min-Chie CHIU, Yuan-Hung CHIEN

“…Most researchers have explored noise reduction effects based on the transfer matrix method and the boundary element method. …”
Get full text

Estudio comparativo de técnicas de reducción de ruido en señales industriales mediante Transformada Wavelet Discreta y selección adaptativa del umbral by Antonio Cedeño Pozo Ing., Rafael Trujillo Codorniú Dr.

“…However, we aimed at evaluating their performance for industrial signal noise reduction. In particular, we analyze the behaviour of the Bayes Shrink, Normal Shrink, Modified Shrink, and Neight Shrink methods for the reduction of the Gaussian noise in industrial signals. …”
Get full text