MODELING OF UNDERGROUND STRUCTURES SUBJECTED TO EARTHQUAKE BY COMBINING 1D FREE-FIELD AND 2D PSEUDO-STATIC ANALYSES by Tereza Poklopová, Veronika Pavelcová, Tomáš Janda, Michal Šejnoha

“…The initial stage of calculation is concerned with the design of computational model and subsequent analysis of the actual excavation process. …”
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Binary phase-only gallium oxide diffractive optical element for beam shaping by Wei Jia, Steve Blair, Berardi Sensale-Rodriguez

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VP_TT: A value propagation based equivalence checker for testability transformations by Ramanuj Chouksey, Sachin Kumar Maddheshiya, Chandan Karfa

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Secure healthcare data management using multimodal image fusion and dual watermarking by Harendra Singh, Maroti Deshmukh, Lalit Kumar Awasthi

“…It employs Laplacian redecomposition to fuse MRI and SPECT/PET images, creating a host image for embedding Aadhaar card image and a computed hash value. The embedding process integrates lifting wavelet transform, Hessenberg decomposition, and singular value decomposition to balance imperceptibility and robustness. …”
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Applying Software Metrics to RNN for Early Reliability Evaluation by Hao Zhang, Jie Zhang, Ke Shi, Hui Wang

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Enhancing atom mapping with multitask learning and symmetry-aware deep graph matching by Maryam Astero, Juho Rousu

“…This makes our method a promising advancement for computational chemistry and related fields.…”
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Bearing Remaining Useful Life Prediction Based on AdCNN and CWGAN under Few Samples by Junfeng Man, Minglei Zheng, Yi Liu, Yiping Shen, Qianqian Li

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Homogenization of Heterogeneous Tissue Scaffold: A Comparison of Mechanics, Asymptotic Homogenization, and Finite Element Approach by Z. Fang, C. Yan, W. Sun, A. Shokoufandeh, W. Regli

“…Derivations and formulations of mechanics, homogenization, and finite element approach as they relate to tissue engineering are described. The process for the development of a computational algorithm, finite element implementation, and numerical solution for calculating the effective mechanical properties of porous tissue scaffolds are also given. …”
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Overcoming Class Imbalance in Incremental Learning Using an Elastic Weight Consolidation-Assisted Common Encoder Approach by Engin Baysal, Cüneyt Bayılmış

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UAV Swarm Confrontation Using Hierarchical Multiagent Reinforcement Learning by Baolai Wang, Shengang Li, Xianzhong Gao, Tao Xie

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An adaptive feature fusion strategy using dual-layer attention and multi-modal deep reinforcement learning for all-media similarity search by Jin Yue, Jiayun Lang, Rui Feng

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Towards Automated Frequency Response Analysis of Power Transformers with Deep Learning by Micah Phillip, Arvind Singh, Craig J. Ramlal

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AMC: Adaptive Learning Rate Adjustment Based on Model Complexity by Weiwei Cheng, Rong Pu, Bin Wang

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Low-temperature pulsed-light assembly of nanoparticle silver ink by Atef Abu-Ageel, Virginia Ayres, Abigail Vanderberg, John Albrecht

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Coordinated TSO-DSO operational planning for congestion management in day-ahead and real-time markets by Ali Esmaeel Nezhad, Toktam Tavakkoli Sabour, Ravindra P. Joshi

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Multi-Domain Indoor Dataset for Visual Place Recognition and Anomaly Detection by Mobile Robots by Piotr Wozniak, Tomasz Krzeszowski, Bogdan Kwolek

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Siamese Denoising Autoencoders for Enhancing Adversarial Robustness in Medical Image Analysis by Jaesung Shim, Kyuri Jo

“…Deep learning models have achieved groundbreaking results in computer vision; however, their vulnerability to adversarial examples persists. …”
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An overview of the activation functions used in deep learning algorithms by Mete Çelik, Kemal Adem, Serhat Kılıçarslan

“…Also, in deep learning algorithms, activation functions have been developed by taking into account features such as performing the learning process in a healthy way, preventing excessive learning, increasing the accuracy performance, and reducing the computational cost. …”
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An Improved SLIC Superpixel Segmentation Algorithm Combined with FPGA Technology by HAN Jianhui, LZhi qiang

“…In view of the large amount of calculations, complexity of algorithm and the implementation is slow The paper combines superpixel segmentation technology with FPGA parallel processing technology, and puts forward a method to realize the image segmentation algorithm on FPGA platform SLIC is a kind of fast image segmentation algorithm SLIC has a lot of improvements in efficiency, costing and segmentation results compared with traditional image segmentation algorithm On the basis of the principle of SLIC segmentation algorithm, we made a further improvement algorithm by optimizing the operation and extracting a small number of pixels of the original image to reduce computational complexity Finally, the last of the original image segmentation was achieved by K nearest neighbor classification process We completed the algorithm design on FPGA platform The simulation results show that the improved algorithm has a better segmentation results and the processing speed has about 40% promotion And the improved algorithm has a higher realtime performance…”
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Light weight encryption technique: a cellular automaton based approach for securing health records by Shamama Anwar, Prashant Pranav, Supreeti Kamilya

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