Elucidating structure-property correlations in ferroelectric Hf0.5Zr0.5O2 films using variational autoencoders by Kévin Alhada-Lahbabi, Brice Gautier, Damien Deleruyelle, Grégoire Magagnin

“…We further demonstrate a VAE-based inverse design approach to optimize P-V loop features, enabling the tailored design of device-specific key performance indicators (KPIs), including coercive field, remanent polarization, and loop area. …”
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An Adaptive Convolutional Neural Network With Spatio-Temporal Attention and Dynamic Pathways (ACNN-STADP) for Robust EEG-Based Motor Imagery Classification by Aaqib Raza, Mohd Zuki Yusoff

“…However, existing classification models face limitations such as inter-subject variability, lack of generalizability, high computational demands, low signal-to-noise ratios, and inefficient feature extraction, which impede their robustness and accuracy. …”
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Analysis of Electromagnetic Characteristics of Outer Rotor Type BLDC Motor Based on Analytical Method and Optimal Design Using NSGA-II by Tae-Seong Kim, Jun-Won Yang, Kyung-Hun Shin, Gang-Hyeon Jang, Cheol Han, Jang-Young Choi

“…This approach transforms the operating point on the B–H curve to facilitate accurate modeling in a 2D framework, overcoming traditional analysis limitations. …”
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Abnormal events detection using spatio-temporal saliency descriptor and fuzzy representation analysis by R. Tino Merlin, R. Karthick, A. Aalan Babu, G. Vennira Selvi, D. Usha, R. Nithya

“…Though several approaches have been used in the field still many problems remain to get the abnormal events detection accuracy. Moreover, many feature representations have limited capability to describe the content since several research works applied hand craft features, this type of feature can work in limited problems. …”
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MD-Former: Multiscale Dual Branch Transformer for Multivariate Time Series Classification by Yanling Du, Shuhao Chu, Jintao Wang, Manli Shi, Dongmei Huang, Wei Song

“…Current approaches emphasize modeling multiscale relationships over time. However, the Multivariate Time Series (MTS) also exhibits multiscale cross-channel relationships. …”
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Inverse power XLindley distribution with statistical inference and applications to engineering data by Amal S. Hassan, Najwan Alsadat, Christophe Chesneau, Mohammed Elgarhy, Mohamed Kayid, Suleman Nasiru, Ahmed M. Gemeay

“…Essential characteristics and features of our study include quantiles, moments, inverse moments, probability-weighted moments, incomplete moments, and inequality measures. …”
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Insulator discharge severity assessment algorithm based on RDIDSNet by Cheng Chi, Li Keyu, Yanhui Meng, Yang Yang, JiNing Zhao, Shaotong Pei, Haosen Sun

“…Firstly, LDConv is introduced to replace the convolution of the backbone network part of the network feature extraction, which effectively realizes the enhancement of the feature extraction ability of the algorithm in the case of model lightweighting; and then ACMix attention mechanism is introduced, which realizes better focusing of the model on the target with a very small performance loss; and finally, Shape-IoU is introduced to replace the loss function of the CIoU, which effectively improve the detection accuracy of the algorithm. …”
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Predicting Financial Distress through Ranking Working Capital Management Components Using Random Forest Algorithm by Pouya Sadeghi, Daryush Farid, Hamid Reza Mirzaei, Abolfazl Dehghani

“…These scores, being close to 1, suggested that the model's estimations were performed with a high degree of accuracy.The analysis of the relative importance of each working capital management component in achieving this 85% accuracy rate revealed some key insights. …”
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AD-VAE: Adversarial Disentangling Variational Autoencoder by Adson Silva, Ricardo Farias

“…Deep learning techniques have shown promising results in recent years using VAE and GAN, with approaches such as patch-VAE, VAE-GAN for 3D Indoor Scene Synthesis, and hybrid VAE-GAN models. However, in Single Sample Per Person Face Recognition (SSPP FR), the challenge of learning robust and discriminative features that preserve the subject’s identity persists. …”
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Structure of Small and Medium-Sized Business: Results of Total Statistic Observations in Russia by Iuliia S. Pinkovetskaia, Igor V. Balynin

“…The materiality of structural changes was carried out on the basis of the Ryabtsev index. Modeling the differentiation of the values of the number of employees per enterprise was based on the development of density normal distribution functions. …”
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A Deep Reinforcement Learning Framework for Adaptive Resiliency Enhancement in Smart Power Grids by Boyu Wang, Aliasghar Baziar, Mohammad Reza Askari

“…The proposed framework features a two-layered control architecture that models grid states, actions, and rewards to enable continuous, real-time adaptive control of distributed energy resources, microgrids, and control centers. …”
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OPTIMIZATION OF COMMODITY STOCKS THE ENTERPRISE BY MEANS OF HML-FMR CLUSTERING by I.GI. Britchenko, M. G. Bezpartochnyi

“…Economic-mathematical modeling is applied and graphically shown the difference in the formation of commodity resources by various features of HML-FMR clustering. …”
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Improved Energy Efficient Anytime Optimistic Algorithm for PEGASIS to Extend Network Lifetime in Homogeneous and Heterogeneous Networks by Tadele A. Abose, Venumadhav Tekulapally, Samuel T. Daka, Diriba C. Kejela, Alemayehu E. Duguma, Desalegn T. Degaga

“…The proposed algorithm demonstrates a 40% improvement across all evaluated features compared to existing algorithms.…”
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Three‐Way Equal Filtering Power Divider for Modern Communication Systems by Augustine O. Nwajana, Rose Paul

“…This design includes theoretical calculations, circuit modeling, microstrip layout design, and electromagnetic (EM) simulations. …”
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Alternate encoder and dual decoder CNN-Transformer networks for medical image segmentation by Lin Zhang, Xinyu Guo, Hongkun Sun, Weigang Wang, Liwei Yao

“…However, the unique characteristics of many lesion tissues often lead to poor performance and most previous models failed to fully extract effective local and global features. …”
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Sonic Affinity and Aesthetic Metamorphosis: The Nineteenth Century as a Turning Point in the History of Musical Thought by Javier Campos Calvo-Sotelo

“…Technological innovations had a decisive impact on the creation, performance, and perception of music. The orchestra grew unstoppable, the piano doubled in power and possibilities compared to its predecessors, metronome and pianola became universal, and cultured compositions developed previously unthinkable features and complexity. …”
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Harnessing quantum power: Revolutionizing materials design through advanced quantum computation by Zikang Guo, Rui Li, Xianfeng He, Jiang Guo, Shenghong Ju

“…We introduce the loop framework for QUBO‐empowered materials design, including constructing high‐quality datasets that capture critical material properties, employing tailored computational methods for precise material modeling, developing advanced figures of merit to evaluate performance metrics, and utilizing quantum optimization algorithms to discover optimal materials. …”
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Variational Methods in Optical Quantum Machine Learning by Marco Simonetti, Damiano Perri, Osvaldo Gervasi

“…The selected dataset is a set of 2D points creating two interleaved semicircles and is based on a 2D binary classification generator, which aids in evaluating the performance of particular methods. The two coordinates of each unique point, <inline-formula> <tex-math notation="LaTeX">$x_{1}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$x_{2}$ </tex-math></inline-formula>, serve as the features since they present two disparate data sets in a two-dimensional representation space. …”
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A Comprehensive Content-Based Recommendation System for Programming Problems Through Multi-Faceted Code Analysis by Daniel M. Muepu, Yutaka Watanobe, Md. Faizul Ibne Amin

“…Compared with collaborative filtering models on the same dataset, the CBRS achieved stronger performance in diversity-focused metrics, supporting more engaging and meaningful learning experiences.…”
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A comprehensive analysis through Mendelian randomization of immunological markers and sphingolipid metabolism by Dunpeng Yang, Wentian Zhang, Qibin Wang

“…Single-cell profiling revealed significant differential expression of six genes (APCDD1L, CNTNAP4, GNG13, KIRREL2, LINC00628, and LIPK) between normal and tumor tissues. Machine learning models constructed from these findings demonstrated robust predictive performance in both TCGA and GEO datasets. …”
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