Using the LTO Network Level 1 Blockchain to Automate Inter-Organizational Business Processes by Khrypko Serhii L., Shcherbakov Serhii S.

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Condition Monitoring of Chain Sprocket Drive System Based on IoT Device and Convolutional Neural Network by Sang Kwon Lee, Jiseon Back, Kanghyun An, Sunwon Kim, Changho Lee, Pungil Kim

“…A convolution neural network (CNN) was employed to extract deep features embedded in the images, which are closely related to fault types. …”
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Proposed SmartBarrel System for Monitoring and Assessment of Wine Fermentation Processes Using IoT Nose and Tongue Devices by Sotirios Kontogiannis, Meropi Tsoumani, George Kokkonis, Christos Pikridas, Yorgos Kotseridis

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Air artifact suppression in phase contrast micro-CT using conditional generative adversarial networks by Md Motiur Rahman Sagar, Lorenzo D'Amico, Elena Longo, Irma Mahmutovic Persson, Richard Deyhle Jr, Giuliana Tromba, Sam Bayat, Frauke Alves, Christian Dullin

“…Here, we present a novel workflow based on conditional generative adversarial networks (cGANs) to effectively replace these air artifact regions with generated tissue, which are influenced by the surrounding content. …”
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A Real-Time Video Watermarking Algorithm for Authentication of Small-Business Wireless Surveillance Networks by Shaohui Liu, Daniel Bo-Wei Chen, Long Gong, Wen Ji, Sanghyun Seo

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Optimal graph representations and neural networks for multichannel time series data in seizure phase classification by Alan A. Díaz-Montiel, Richard Zhang, Milad Lankarany

“…Moreover, we show that by leveraging t-SNE, a statistical method for visualizing high-dimensional data, we can analyze how GNN’s influence the iEEG and graph representation embedding space. …”
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CoCoMo: Toward controllable and reliable corrosion monitoring with a wireless sensor network by Guodong Sun, Gaoxiang Yang, Bingbing Guo

“…This article presents a corrosion-monitoring framework, called CoCoMo, based on embedded sensing and wireless networking technologies, aimed at achieving long-term and controllable corrosion monitoring. …”
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AutoTarget: Disease-Associated druggable target identification via node representation learning in PPI networks by Hyunseung Kong, Inyoung Kim, Byoung-Tak Zhang

“…Data from the Therapeutic Target Database (TTD) and DisGeNET were integrated to identify known drug targets and gene-disease associations, respectively. Each protein is embedded into a 128-dimensional vector space, capturing local network structures and enabling the identification of structurally equivalent proteins. …”
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Unknown IoT Device Identification Models and Algorithms Based on CSCL-Siamese Networks and Weighted-Voting Clustering Ensemble by Junhao Qian, Wenyu Zheng, Xulin Lu, Zhihua Li

“…Next, we extract the embedding vectors of unknown IoT devices using the trained CSCL-Siamese network and the embedded vector database. …”
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A comprehensive framework for multi-modal hate speech detection in social media using deep learning by R. Prabhu, V. Seethalakshmi

“…Hence, this research proposes a novel Multi-modal Hate Speech Detection Framework (MHSDF) that combines Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to analyze complex, heterogeneous data streams. …”
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I-MPN: inductive message passing network for efficient human-in-the-loop annotation of mobile eye tracking data by Hoang H. Le, Duy M. H. Nguyen, Omair Shahzad Bhatti, László Kopácsi, Thinh P. Ngo, Binh T. Nguyen, Michael Barz, Daniel Sonntag

“…Abstract Comprehending how humans process visual information in dynamic settings is crucial for psychology and designing user-centered interactions. …”
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Low-Light Image Enhancement Using Deep Learning: A Lightweight Network with Synthetic and Benchmark Dataset Evaluation by Manuel J. C. S. Reis

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Feature extraction and classification of digital rock images via pre-trained convolutional neural network and unsupervised machine learning by Masashige Shiga, Masao Sorai, Tetsuya Morishita, Masaatsu Aichi, Naoki Nishiyama, Takashi Fujii

“…To address this challenge, this study presents a novel approach for the classification and visualization of rock microstructure from micro-computed tomography images, leveraging pre-trained convolutional neural network (CNN) models (AlexNet, GoogLeNet, Inception v3 Net, ResNet, and DenseNet) combined with unsupervised machine learning (USML) techniques principal component analysis, multidimensional scaling, isometric mapping, t-distributed stochastic neighbor embedding (t-SNE), and uniform manifold approximation projection (UMAP)). …”
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Decision-making of drivers following autonomous vehicles: Developing a Bayesian network on the basis of field tests and questionnaire data by Fang Zong, Huan Wu, Meng Zeng, Won Kim, Qiaowen Bai, Yafeng Gong, Ruifeng Duan, Ying Guo

“…On the basis of the results, we propose some strategies for the traffic management of mixed traffic that are beneficial to traffic efficiency: (1) Improving drivers’ recognition of AVs; (2) embedding the external sensing devices of AVs internally to make them visually similar to HDVs; and (3) establishing dedicated lanes for AVs. …”
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PGTransNet: a physics-guided transformer network for 3D ocean temperature and salinity predicting in tropical Pacific by Song Wu, Senliang Bao, Wei Dong, Senzhang Wang, Xiaojiang Zhang, Chengcheng Shao, Junxing Zhu, Xiaoyong Li

“…In this paper, we proposed PGTransNet, a novel physics-guided transformer network for 3D Ocean temperature and salinity forecasting. …”
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Determining mosquito age using surface-enhanced Raman spectroscopy and artificial neural networks: insights into the influence of origin and sex by Zili Gao, Yuzhen Zhang, Laura C. Harrington, Courtney C. Murdock, Elisabeth Martin, Dalton Manbeck-Mosig, Steve Vetrone, Nicolas Tremblay, Christopher M. Barker, John M. Clark, Lili He, Wei Zhu

“…Performance metrics included accuracy, correlation coefficient (R), and root mean square error (RMSE). t-Distributed stochastic neighbor embedding (t-SNE) visualizations and confusion matrices offered additional model insights into effectiveness. …”
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GRLGRN: graph representation-based learning to infer gene regulatory networks from single-cell RNA-seq data by Kai Wang, Yulong Li, Fei Liu, Xiaoli Luan, Xinglong Wang, Jingwen Zhou

“…The interpretation discussion and the network visualization were conducted. Conclusions The experimental results and case studies illustrate the considerable performance of GRLGRN in predicting gene interactions and provide interpretability for the prediction tasks, such as identifying hub genes in the network and uncovering implicit links.…”
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Direction and velocity kinematic features of point-light displays grasping actions are differentially coded within the action observation network by Settimio Ziccarelli, Antonino Errante, Leonardo Fogassi

“…Previous research showed that the action observation network (AON) may encode some action kinematic features. …”
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Carrier-independent screen-shooting resistant watermarking based on information overlay superimposition by Xiaomeng LI, Daidou GUO, Xunfang ZHUO, Heng YAO, Chuan QIN

“…Financial security, an important part of national security, is critical for the stable and healthy development of the economy.Digital image watermarking technology plays a crucial role in the field of financial information security, and the anti-screen watermarking algorithm has become a new research focus of digital image watermarking technology.The common way to achieve an invisible watermark in existing watermarking schemes is to modify the carrier image, which is not suitable for all types of images.To solve this problem, an end-to-end robust watermarking scheme based on deep learning was proposed.The algorithm achieved both visual quality and robustness of the watermark image.A random binary string served as the input of the encoder network in the proposed end-to-end network architecture.The encoder can generate the watermark information overlay, which can be attached to any carrier image after training.The ability to resist screen shooting noise was learned by the model through mathematical methods incorporated in the network to simulate the distortion generated during screen shooting.The visual quality of the watermark image was further improved by adding the image JND loss based on just perceptible difference.Moreover, an embedding hyperparameter was introduced in the training phase to balance the visual quality and robustness of the watermarked image adaptively.A watermark model suitable for different scenarios can be obtained by changing the size of the embedding hyperparameter.The visual quality and robustness performance of the proposed scheme and the current state-of-the-art algorithms were evaluated to verify the effectiveness of the proposed scheme.The results show that the watermark image generated by the proposed scheme has better visual quality and can accurately restore the embedded watermark information in robustness experiments under different distances, angles, lighting conditions, display devices, and shooting devices.…”
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Efficacy of acupuncture-related therapy for postmenopausal osteoporosis: a systematic review and network meta-analysis based on randomized controlled trials by Bing Deng, Bing Deng, Tiantian Xu, Zilan Deng, Yue Jiang, Li Li, Wankun Liang, Yuewen Zhang, Hongjin Wang, Yunxiang Xu, Guizhen Chen

“…The results of the network meta-analysis revealed that, when compared to conventional Western medication (CWM), multiple acupuncture therapies had a greater impact on the overall clinical effectiveness rate. …”
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