FORECASTING STOCK PRICES FOR MARITIME SHIPPING COMPANY IN COVID-19 PERIOD USING MULTIVARIATE MULTI-STEP MULTI-STEP CONVOLUTIONAL NEURAL NETWORK - BIDIRECTIONAL LONG SHORT-TERM MEMO... by Ahmad GHAREEB, Mihai Daniel ROMAN

“…This study is intended to propose a predictive method based on Multivariate Multi-step convolutional neural network - Bidirectional Long Short-Term Memory (Multivariate Multi-step CNN-BiLSTM) networks in order to forecast the prices of three of the most prominent stocks of big organizations operating in maritime transport. …”
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A computational framework for processing time-series of earth observation data based on discrete convolution: global-scale historical Landsat cloud-free aggregates at 30 m spatial... by Davide Consoli, Leandro Parente, Rolf Simoes, Murat Şahin, Xuemeng Tian, Martijn Witjes, Lindsey Sloat, Tomislav Hengl

“…Processing large collections of earth observation (EO) time-series, often petabyte-sized, such as NASA’s Landsat and ESA’s Sentinel missions, can be computationally prohibitive and costly. Despite their name, even the Analysis Ready Data (ARD) versions of such collections can rarely be used as direct input for modeling because of cloud presence and/or prohibitive storage size. …”
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Utilizing active learning and attention-CNN to classify vegetation based on UAV multispectral data by Sheng Miao, Chuanlong Wang, Guangze Kong, Xiuhe Yuan, Xiang Shen, Chao Liu

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Lightweight visible damage detection algorithm for embedded systems applied to pipeline automation equipment by Jiale Xiao, Lei Xu, Changyun Li, Ling Tang, Guogang Gao

“…This research is designed for low-power, cost-effective and high-performance pipeline defect inspection in embedded systems. …”
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An Approach of Intelligent Compound Fault Diagnosis of Rolling Bearing based on MWT and CNN by Han Tao, Yuan Jianhu, Tang Jian, An Lizhou

“…The experimental results indicates that this method could effectively identify the compound fault of rolling bearing,and the improved method could effectively improve the fault recognition rate and reduce the training cost.…”
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Spherical multigrid neural operator for improving autoregressive global weather forecasting by Yifan Hu, Fukang Yin, Weimin Zhang, Kaijun Ren, Junqiang Song, Kefeng Deng, Di Zhang

“…Although methods such as spherical Fourier neural operator (SFNO) based on spherical harmonic convolution can alleviate these problems, they face the challenge of high computational cost. …”
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Analytic Continual Learning-Based Non-Intrusive Load Monitoring Adaptive to Diverse New Appliances by Chaofan Lan, Qingquan Luo, Tao Yu, Minhang Liang, Wenlong Guo, Zhenning Pan

“…Non-intrusive load monitoring (NILM) provides a cost-effective solution for smart services across numerous appliances by inferring appliance-level information from mains electrical measurements. …”
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EMB-YOLO: A Lightweight Object Detection Algorithm for Isolation Switch State Detection by Haojie Chen, Lumei Su, Riben Shu, Tianyou Li, Fan Yin

“…Firstly, we propose an efficient mobile inverted bottleneck convolution (EMBC) module for the backbone network. …”
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Low-Latency Neural Network for Efficient Hyperspectral Image Classification by Chunchao Li, Jun Li, Mingrui Peng, Behnood Rasti, Puhong Duan, Xuebin Tang, Xiaoguang Ma

“…Based on this, we introduce a split convolution approach that replaces depthwise convolution, resulting in enhanced arithmetic intensity without significant increase in latency. …”
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Bearing Fault Diagnosis in Induction Motors Using Low-Cost Triaxial ADXL355 Accelerometer and a Hybrid CWT-DCNN-LSTM Model by Muhammad Ahsan, Jose Rodriguez, Mohamed Abdelrahem

“…The vibration data, recorded using an low-cost ADXL355 accelerometer, was preprocessed by converting the one-dimensional (1D) signals into two-dimensional (2D) images using Continuous Wavelet Transform (CWT). …”
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Precision Enhanced Bioactivity Prediction of Tyrosine Kinase Inhibitors by Integrating Deep Learning and Molecular Fingerprints Towards Cost-Effective and Targeted Cancer Therapy by Fatma Hilal Yagin, Yasin Gormez, Cemil Colak, Abdulmohsen Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

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Deep Learning Framework for Oil Shale Pyrolysis State Recognition Using Bionic Electronic Nose by Yuping Yuan, Xiaohui Weng, Yuheng Qiao, Xiaohu Shi, Zhiyong Chang

“…Abstract Real-time monitoring of the pyrolysis state of oil shale is crucial for precisely controlling heating temperature and duration, which can significantly reduce extraction costs. However, due to the complexity of in-situ environments, this task is highly challenging and remains one of the key technological barriers in in-situ mining. …”
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Improved deep learning method and high-resolution reanalysis model-based intelligent marine navigation by Zeguo Zhang, Zeguo Zhang, Zeguo Zhang, Liang Cao, Liang Cao, Liang Cao, Jianchuan Yin, Jianchuan Yin, Jianchuan Yin

“…Key components include: (1) IPCA preprocessing to reduce dimensionality and noise in 2D wind field data; (2) depthwise-separable convolution (DSC) blocks to minimize parameters and computational costs; (3) multi-head attention (MHA) and residual mechanisms to improve spatial-temporal feature extraction and prediction accuracy. …”
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ZoomHead: A Flexible and Lightweight Detection Head Structure Design for Slender Cracks by Hua Li, Fan Yang, Junzhou Huo, Qiang Gao, Shusen Deng, Chang Guo

“…Second, Detail Enhanced Convolution (DEConv) replaces traditional convolution kernels, and shared convolution is adopted to reduce redundant structures, which enhances the ability to capture details and improves the detection performance for small objects. …”
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GLN-LRF: global learning network based on large receptive fields for hyperspectral image classification by Mengyun Dai, Tianzhe Liu, Youzhuang Lin, Zhengyu Wang, Yaohai Lin, Changcai Yang, Riqing Chen

“…In the decoder phase, to further extract rich semantic information, we propose a multi-scale simple attention (MSA) block, which extracts deep semantic information using multi-scale convolution kernels and fuses the obtained features with SimAM. …”
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Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attenti... by Santosh Prabhakar Agnihotri, Mandar Padmakar Joshi

“…The methodology combines a Dandelion optimizer algorithm (DOA) for servo motor parameter optimization and an Attention pyramid convolution neural network (APCNN) (APCNN) for system behavior prediction. …”
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HCT-Det: A High-Accuracy End-to-End Model for Steel Defect Detection Based on Hierarchical CNN–Transformer Features by Xiyin Chen, Xiaohu Zhang, Yonghua Shi, Junjie Pang

“…This structure combines window-based self-attention (WSA) blocks to reduce computational overhead and parallel residual convolutional (Res) blocks to enhance local feature continuity. …”
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A Multivariate Spatiotemporal Feature Fusion Network for Wind Turbine Gearbox Condition Monitoring by Shixian Dai, Shuang Han, Xinjian Bai, Zijian Kang, Yongqian Liu

“…SCADA data, due to their easy accessibility and low cost, have been widely applied in wind turbine gearbox condition monitoring. …”
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Novel Custom Loss Functions and Metrics for Reinforced Forecasting of High and Low Day-Ahead Electricity Prices Using Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM)... by Ziyang Wang, Masahiro Mae, Takeshi Yamane, Masato Ajisaka, Tatsuya Nakata, Ryuji Matsuhashi

“…To implement this, we integrate these custom loss functions into a Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model, augmented by an ensemble learning approach and multimodal features. …”
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Analysis of the criteria selection problem in diversification models by Анна Бакурова, Алла Савранська, Еліна Терещенко, Дмитро Широкорад, Марк Шевчук

“… The digitalization of the economy reduces the cost of doing business by automating the relevant processes, but any transformation creates new risks and economic instability. …”
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