A virtual rail train path recognition method based on binocular stereo vision by ZENG Junwei, GENG Li, LU Chenyang, REN Lihui

“…To achieve this, a lane detection model based on Mask R-CNN was developed, incorporating their characteristics such as obvious lane blocks, contour integrity, and unique shape. Meanwhile, a binocular matching algorithm based on multi-target tracking was proposed, addressing the drawbacks of general binocular matching algorithms including substantial computations and deficient ability to match repeated objects. …”
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Robust GNSS/INS Tightly Coupled Positioning Using Factor Graph Optimization with P-Spline and Dynamic Prediction by Bokun Ning, Fang Zhao, Haiyong Luo, Dan Luo, Wenhua Shao

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A method for detecting the rate of tobacco leaf loosening in tobacco leaf sorting scenarios by Yansong Wang, Yansong Wang, Chunjie Zhang, Chunjie Zhang, Mingjie Wu, Mingjie Wu, Ruilin Luo, Lin Lu, Zaiqing Chen, Zaiqing Chen, Lijun Yun, Lijun Yun

“…This was achieved by adding layers for detecting smaller objects and integrating a weighted bi-directional feature pyramid structure to reconstruct the feature fusion network. …”
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Application of a Hybrid Model Based on CEEMDAN and IMSA in Water Quality Prediction by GUO Li-jin, WU Hao-tian

“…Directly removing them could lead to information loss, so outliers were retained. After integrating decomposition, use of entropy, algorithm optimization, and error correction models, eleven comparative experiments were established to evaluate the effectiveness of each optimization method. …”
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Intelligent pattern design using 3D modelling technology for urban sculpture designing by Wei Wan

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GPT-NAS: Neural Architecture Search Meets Generative Pre-Trained Transformer Model by Caiyang Yu, Xianggen Liu, Yifan Wang, Yun Liu, Wentao Feng, Xiong Deng, Chenwei Tang, Jiancheng Lv

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Short-Term Electricity Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Improved Sparrow Search Algorithm–Convolutional Neural Netwo... by Han Qiu, Rong Hu, Jiaqing Chen, Zihao Yuan

“…By the optimization of the ISSA to the parameters of the CNN-BiLSTM model, integrating the prediction results of the reconstructed IMFs in the sub-models can obtain the final prediction result of the data. …”
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Machine-Learning Assisted Prediction of Spectral Power Distribution for Full-Spectrum White Light-Emitting Diode by Jiajie Fan, Yutong Li, Irena Fryc, Cheng Qian, Xuejun Fan, Guoqi Zhang

“…Then, the Back Propagation (BP) and Genetic Algorithm-Back Propagation (GA-BP) NNs are proposed to predict the spectral characteristic parameters of LEDs operated under any usage conditions. …”
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High-performance reconfigurable encryption scheme for distributed storage by Zhihua FENG, Yuxuan ZHANG, Chong LUO, Jianing WANG

“…As the world embraces the digital economy and enters an information society, data has emerged as a critical production factor.The collection, processing, and storage of data have become increasingly prevalent.Distributed storage systems, known for their efficiency, are widely used in various data fields.However, as the scale of data storage continues to expand, distributed storage faces more significant security risks, such as information leakage and data destruction.These challenges drive the need for innovative advancements in big data distributed storage security technology and foster the integration of domestic cryptographic technology with computing storage technology.This work focused on addressing security issues, particularly information leakage, in distributed storage nodes.A dynamic and reconfigurable encryption storage solution was proposed, which considered the requirements for encryption performance and flexibility.A high-performance reconfigurable cryptographic module was designed based on the bio mapping framework.Based on this module, multiple storage pools equipped with different cryptographic algorithms were constructed to facilitate high-performance encryption and decryption operations on hard disk data.The scheme also enabled dynamic switching of cryptographic algorithms within the storage pools.A cryptographic protocol with remote online loading functions for cryptographic algorithms and keys was developed to meet the unified management and convenient security update requirements of reconfigurable cryptographic modules in various storage nodes.Furthermore, the scheme implemented fine-grained data encryption protection and logical security isolation functions based on cryptographic reconstruction technology.Experimental results demonstrate that the performance loss of this scheme for encryption protection and security isolation of stored data is approximately 10%.It provides a technical approach for distributed storage systems to meet the cryptographic application technology requirements outlined in GB/T 39786-2021 “Information Security Technology-Basic Requirements for Cryptography Applications” Level 3 and above in terms of device and computing security, application and data security.…”
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Integrated analysis of single-cell RNA-seq and spatial transcriptomics to identify the lactylation-related protein TUBB2A as a potential biomarker for glioblastoma in cancer cells... by Yifan Xu, Chonghui Zhang, Jinpeng Wu, Pin Guo, Nan Jiang, Chao Wang, Yugong Feng

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A Novel Method for Inverting Deep-Sea Sound-Speed Profiles Based on Hybrid Data Fusion Combined with Surface Sound Speed by Qiang Yuan, Weiming Xu, Shaohua Jin, Xiaohan Yu, Xiaodong Ma, Tong Sun

“…The artificial lemming algorithm (ALA) is introduced to optimize the inversion of empirical orthogonal function (EOF) coefficients, enhancing global search efficiency while avoiding local optimization. …”
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Computer-economical optimization method for solving inverse problems of determining electrophysical properties of objects in eddy current structroscopy by V. Ya. Halchenko, R. V. Trembovetska, V. V. Tychkov

“…The method for determining the electrophysical properties of objects is based on homogeneous designs of experiments, surrogate optimization with the accumulation of apriori knowledge about them in metamodels with nonlinearly reduced dimensionality. Originality. Integration of multiple capabilities in the surrogate model that combine the advantages of high-performance computing and optimization algorithms in the factor space reduced by the Kernel PCA (Principal Component Analysis) method. …”
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GRL-ITransformer: An Intelligent Method for Multi-Wind-Turbine Wake Analysis Based on Graph Representation Learning With Improved Transformer by Kang Han, Li Xu

“…After that, the data driven method is employed to update the parameters, and the superiority of GRL-ITransformer is highlighted by analyzing and comparing with the existing five classical intelligent algorithms (belongs to four categories). The comprehensive results show that GRL-ITransformer has excellent performance in wind turbine wake field prediction and reconstruction, and always possesses the lowest error for a series of error evaluation indexes among all models.…”
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Robust Current Sensing in Rectangular Conductors: Elliptical Hall-Effect Sensor Array Optimized via Bio-Inspired GWO-BP Neural Network by Yue Tang, Jiajia Lu, Yue Shen

“…This work bridges bio-inspired algorithms and adaptive sensing hardware, offering a systematic solution to mechanical deformation-induced errors in high-density power systems.…”
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Multiclass semantic segmentation for prime disease detection with severity level identification in Citrus plant leaves by P. Dinesh, Ramanathan Lakshmanan

“…The significance of this proposed RSL Linked-Transnet model lies in its integration of hierarchical feature extraction, global context modeling via transformers, and precise feature reconstruction, ensuring superior segmentation accuracy and robustness. …”
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Redefining IoT networks for improving energy and memory efficiency through compressive sensing paradigm by S. Balamurali, M. Kathirvelu, SatheeshKumar Palanisamy, Ines Hilali Jaghdam

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Short-Term Power Load Prediction of VMD-LSTM Based on ISSA Optimization by Shuai Wu, Huafeng Cai

“…The Improved Sparrow Search Algorithm (ISSA), which integrates piecewise chaotic mapping into population initialization to augment the global exploration capability, is employed to fine-tune LSTM hyperparameters, thereby enhancing the prediction precision. …”
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Real-time prediction of port water levels based on EMD-PSO-RBFNN by Lijun Wang, Shenghao Liao, Sisi Wang, Jianchuan Yin, Ronghui Li, Jingyu Guan

“…Addressing the spatial variability, temporal dynamics, and non-linearity characteristics of port water levels, a hybrid prediction scheme was proposed, which integrates empirical mode decomposition (EMD) with a radial basis function neural network (RBFNN), optimized using the particle swarm optimization (PSO) algorithm. …”
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Proposal of a new classification scheme for periocular injuries by Devi Prasad Mohapatra, Friji Meethale Thiruvoth, Ravi Kumar Chittoria, S. Dinesh Kumar, Sudhanva Hemant Kumar, Senthil Kumar, Preethitha Babu, Elan Kumar

“…Based on the classification scheme and review of existing literature, an algorithm is presented to facilitate repair and reconstruction.…”
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OTFS-based ISAC for active channel sensing and low-altitude multi-target detection by CHEN Jiabin, WANG Chaowei, PANG Mingliang, YAN Shuai, XU Lexi, JIANG Fan, ZHANG Junyi

“…Additionally, the convergence of the proposed algorithm is also validated to be overhead saving.…”
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