Investigating the dynamics and uncertainties in portfolio optimization using the Fourier-Millen transform. by Muhammad Hilal Alkhudaydi, Aiedh Mrisi Alharthi

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Dynamic Path Planning of Unknown Environment Based on Deep Reinforcement Learning by Xiaoyun Lei, Zhian Zhang, Peifang Dong

“…Pygame module in PYTHON is used to establish dynamic environments. Considering lidar signal and local target position as the inputs, convolutional neural networks (CNNs) are used to generalize the environmental state. …”
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Denoising of Brillouin Gain Spectrum Images for Improved Dynamic Measurements of BOTDR by Bo Li, Ningjun Jiang, Xiaole Han

“…However, the accuracy and reliability of the measurements are often limited by the noise in the sensor signals. Dynamic measurement of BOTDR requires small averaging number and fast measurement, and hence noise reduction is more significant in dynamic measurement. …”
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Data-Driven Carbon Emission Dynamics Under Ship In-Port Congestion by Weiyu Liu, Bowei Xu, Junjun Li

“…This study quantifies in-port emission dynamics for four cargo ship types (container, liquid bulk, dry bulk, and general cargo) using an operational phase-specific emission accounting model. …”
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Dynamic Ensemble Selection for EEG Signal Classification in Distributed Data Environments by Małgorzata Przybyła-Kasperek, Jakub Sacewicz

“…This study presents a novel approach to EEG signal classification in distributed environments using dynamic ensemble selection. In scenarios where data dispersion arises due to privacy constraints or decentralized data collection, traditional global modelling is impractical. …”
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Deep learning for prediction and classifying the dynamical behaviour of piecewise-smooth maps by Vismaya V S, Bharath V Nair, Sishu Shankar Muni

“…This paper explores novel ways of predicting and classifying the dynamics of piecewise smooth maps using various deep learning models. …”
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Dynamic Optimization of Recurrent Networks for Wind Speed Prediction on Edge Devices by Laeeq Aslam, Runmin Zou, Ebrahim Shahzad Awan, Sayyed Shahid Hussain, Muhammad Asim, Samia Allaoua Chelloug, Mohammed A. ELAffendi

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ADEPNET: A Dynamic-Precision Efficient Posit Multiplier for Neural Networks by Aditya Anirudh Jonnalagadda, Uppugunduru Anil Kumar, Rishi Thotli, Satvik Sardesai, Sreehari Veeramachaneni, Syed Ershad Ahmed

“…Its properties- tapered precision and high dynamic range, allow a smaller size posit to almost match the performance of a much larger size floating-point in representing decimals. …”
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A Novel 3D Convolutional Neural Network-Based Deep Learning Model for Spatiotemporal Feature Mapping for Video Analysis: Feasibility Study for Gastrointestinal Endoscopic Video Cla... by Mrinal Kanti Dhar, Mou Deb, Poonguzhali Elangovan, Keerthy Gopalakrishnan, Divyanshi Sood, Avneet Kaur, Charmy Parikh, Swetha Rapolu, Gianeshwaree Alias Rachna Panjwani, Rabiah Aslam Ansari, Naghmeh Asadimanesh, Shiva Sankari Karuppiah, Scott A. Helgeson, Venkata S. Akshintala, Shivaram P. Arunachalam

“…To reduce computational complexity, a (2 + 1)D convolution is used in place of full 3D convolution. …”
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Research on Multi-Step Prediction of Pipeline Corrosion Rate Based on Adaptive MTGNN Spatio-Temporal Correlation Analysis by Mingyang Sun, Shiwei Qin

“…First, pipeline monitoring points are modeled as graph nodes to construct the pipeline corrosion spatio-temporal information graph, with corrosion rate and auxiliary features (selected through feature correlation analysis) forming node attributes. Then, a dynamic adjacency matrix is adaptively learned to capture hidden spatial dependencies, while temporal convolution modules extract multi-scale temporal patterns, and the node sequences with integrated corrosion features are input into the adaptive MTGNN for prediction. …”
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Gearbox Fault Diagnosis Under Noise and Variable Operating Conditions Using Multiscale Depthwise Separable Convolution and Bidirectional Gated Recurrent Unit with a Squeeze-and-Exc... by Xiaoteng Ma, Kejia Zhai, Nana Luo, Yehui Zhao, Guangming Wang

“…To address these limitations, this study proposes a novel fault diagnosis framework that integrates multiscale depthwise separable convolution, bidirectional gated recurrent units, and a squeeze-and-excitation attention mechanism. …”
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An Approach to Predicting Urban Carbon Stock Using a Self-Attention Convolutional Long Short-Term Memory Network Model: A Case Study in Wuhan Urban Circle by Zhi Zhou, Xueling Wu, Bo Peng

“…This paper introduces a long- and short-term memory network algorithm called the Self-Attention Convolutional Long and Short-Term Memory Network (SA-ConvLSTM). …”
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Propagation of Blood Function Errors to the Estimates of Kinetic Parameters with Dynamic PET by Yafang Cheng, İmam Şamil Yetik

“…Mathematical modeling of the tissue of interest in dynamic PET can be simplified using compartment models as a linear system where the time activity curve of a specific tissue is the convolution of the tracer concentration in the plasma and the impulse response of the tissue containing kinetic parameters. …”
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Chinese Tone Recognition Based on 3D Dynamic Muscle Information by JianRong Wang, Li Wan, Ju Zhang, Qiang Fang, Fan Yang, Jing Hu

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3D Micro-Expression Recognition Based on Adaptive Dynamic Vision by Weiyi Kong, Zhisheng You, Xuebin Lv

“…Inspired by circular convolution networks, this paper innovatively proposes an adaptive dynamic micro-expression recognition algorithm based on self-supervised learning, namely MADV-Net. …”
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Dynamic Calibration and Validation of an Accelerometer Force Balance for Hypersonic Lifting Models by Prakash Singh, Sharad Trivedi, Viren Menezes, Hamid Hosseini

“…Calibration and validation of the balance were carried out by a convolution technique using hammer pulse test and surface pressure measurements. …”
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An Improved Scene Adaptive PRM Path Planning Algorithm by YANG Jingzhao, WANG Chao, ZHANG Yu

“…Firstly, the risk fusion cost map is established based on the multi-factor environment scene, the scene adaptive PRM probabilistic road map is constructed through the mechanisms of Gaussian convolution adaptive sampling, nonlinear probability enhancement and secondary sampling strategy, and the local planner is utilized to dynamically update the weights of the probabilistic road map, so as to realize the optimized search of global low-risk cost paths. …”
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Application of deep learning in cloud cover prediction using geostationary satellite images by Yeonjin Lee, Seyun Min, Jihyun Yoon, Jongsung Ha, Seungtaek Jeong, Seonghyun Ryu, Myoung-Hwan Ahn

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Identification of Ion-kinetic Instabilities in Hybrid-PIC Simulations of Solar Wind Plasma with Machine Learning by Viacheslav M. Sadykov, Leon Ofman, Scott A. Boardsen, Yogesh, Parisa Mostafavi, Lan K. Jian, Kristopher Klein, Mihailo Martinović

“…Analysis of ion-kinetic instabilities in solar wind plasmas is crucial for understanding energetics and dynamics throughout the heliosphere, as evident from spacecraft observations of complex ion velocity distribution functions (VDFs) and ubiquitous ion-scale kinetic waves. …”
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DMA-Net: Dynamic Morphology-Aware Segmentation Network for Remote Sensing Images by Chao Deng, Haojian Liang, Xiao Qin, Shaohua Wang

“…To address these limitations, we propose DMA-Net, a Dynamic Morphology-Aware Segmentation Network built on an encoder–decoder architecture. …”
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