Robust DWT-HMM image watermarking algorithm optimized with content-adaptive approach by WANG Chun-tao1, NI Jiang-qun1, HUANG Ji-wu1, ZHANG Rong-yue1, LUO Xi-zhang1

“…A robust watermarking algorithm based on content-adaptive approach was proposed to optimize the tradeoff between robustness and imperceptibility,which was characterized as follows: the entropy masking proposed by Watson etc.was constructed in wavelet domain,which was then used to constitute the integrated HVS model;three different measures,namely,energy,entropy and integrated HVS,for content-adaptive selection were constructed and investigated;repeat-accumulate（RA） code with erasure and error correction was used to tackle the synchronization issue of the exact positions for watermark embedding;and a posteriori DWT-HMM detector was utilized for watermark detection.Simula-tion results show that the proposed content-adaptive watermarking algorithm,under the same imperceptibility,has con-siderable improvement in robustness performance over the traditional one with stochastic approach.…”
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Computerised Method of Multiparameter Optimisation of Predictive Control Algorithms for Asynchronous Electric Drives by Grygorii Diachenko, Serhii Semenov, Katarzyna Marczak, Gernot Schullerus, Ivan Laktionov

“…The study results show that the optimal setting of the algorithmic parameters improves the accuracy of task processing, reduces energy consumption, and reduces computation time. …”
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ImmuProgML: machine learning-based dissection of cancer-immune dynamics during tumor progression to improve immunotherapy by Hanxiao Zhou, Lan Mei, Qianyi Lu, Yakun Zhang, Yue Sun, Caiyu Zhang, Han Jiang, Jiajun Zhou, Xia Li, Yunpeng Zhang, Shangwei Ning

“…While immunotherapy has significantly improved outcomes, current biomarker models lack integration of cancer-immune interactions and progression dynamics. …”
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Optimized Grasshopper Optimisation Algorithm enabled DETR (DEtection TRansformer) model for skin disease classification. by Shakti Kundu, Yogesh Kumar Sharma, Khan Vajid Nabilal, Gopalsamy Venkatesan Samkumar, Sultan Mesfer Aldossary, Shanu Kuttan Rakesh, Nasratullah Nuristani, Arshad Hashmi

“…Hyperparameter tuning using GOA optimizes the critical parameters of the proposed model to improve classification accuracy. After extensive testing on a large dataset of skin disease photos, the optimised DETR model returned an accuracy of at least 99.26%. …”
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Phase Sequence Adjustment Method for Three-Phase Load Imbalance in Station Area Based on Improved Pigeon-inspired Optimization by Mingyue HU, Huifen ZHANG, Shuping MIAO, Fan YANG, Zhenming QU

“…The unbalanced load commutation control strategy is used to establish an optimal commutation mathematical model with the goal of minimizing the three-phase current imbalance on the low-voltage side of the distribution transformers; the adaptive parameters and Cauchy disturbance are introduced to improve the original pigeon-inspired optimization (PIO) algorithm. …”
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Postpartum depression risk prediction using explainable machine learning algorithms by Xudong Huang, Lifeng Zhang, Chenyang Zhang, Jing Li, Chenyang Li

“…Feature selection was performed using LASSO regression and the Boruta algorithm. Eight machine learning algorithms were then employed to construct the prediction models. …”
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Non-Line-of-Sight Location With Gauss Filtering Algorithm Based on a Model of Photon Flight by Yu Ren, Zongliang Xie, Yihan Luo, Shaoxiong Xu, Haotong Ma, Yi Tan

“…To improve the authenticity of the model, the bidirectional reflectance distribution function (BRDF) is used to characterize the scattering process. …”
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Research on Reservoir History Matching Method Based on Real⁃Coded Genetic Algorithm and Connectivity Model by Ainiwaer AILIYAER, Chunli ZHAO, Feng LIU

“…A adaptive selection strategies, crossover, and mutation operations are introduced in this paper to further enhance the algorithm's performance. Application of RGA to the history matching problem in a mechanistic model demonstrates that RGA can effectively improve fitting results and find relatively optimal solutions in a short time. …”
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Model-Free Predictive Control Based on RLS Algorithm for Grid-Forming Inverters With Virtual Synchronous Generator by Min Huang, Huiying Zhang, Kangan Wang, Zhilei Yao, Weimin Wu

“…The implementation of MFPC improves the parameter robustness of the system. Building on this, the improvement schemes of algorithmic parameter initialization, delay compensation and current limiting capability are further investigated. …”
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Model-based estimation of tokamak plasma profiles and physics parameters: algorithm overview and application to ITER by S. Van Mulders, F. Felici, S.C. McIntosh, F. Carpanese, C.E. Contré, R. Coosemans, O. Kudláček, F. Pastore, S.D. Pinches, M. Reisner, O. Sauter

“…In this work, a model-based estimation algorithm is proposed to improve real-time and post-shot estimation of tokamak plasma profiles. …”
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Log-Viterbi algorithm applied on second-order hidden Markov model for human activity recognition by Yang Sung-Hyun, Keshav Thapa, M Humayun Kabir, Lee Hee-Chan

“…Therefore, this approach maximizes the probability of activity recognition with improved accuracy and reduced time complexity. We compared our proposed algorithm among other famous probabilistic models such as Naïve Bayes, condition random field, hidden Markov model, and hidden semi-Markov model using three datasets in the smart home environment. …”
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Design of an evolutionary model for international trade settlement based on genetic algorithm and fuzzy neural network. by Jiaqing Huang, Yang Liu, Miaomiao Tu, Osama Sohaib

“…This study proposes a hybrid model-Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)-to enhance bank risk identification within this context. …”
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A model for placing electric vehicle charging stations in megapolis based on the sparrow search algorithm by Sizhuo Du, D. V. Kapski

“…First, the main factors of placing electric vehicle charging stations are analyzed from different points of view, a multi-purpose model for choosing the address of the charging station is built, an algorithmic model is proposed to improve the sparrow search algorithm as the basis for a specific solution method, and finally, the effect of applying the model and solution method is verified by analyzing examples. …”
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Hybridization of Machine Learning Algorithms and an Empirical Regression Model for Predicting Debris-Flow-Endangered Areas by Xiang Wang, Mi Tian, Qiang Qin, Jingwei Liang

“…Results show that compared with the three individual machine-learning models, hybridization of machine-learning algorithms and the empirical model results in R2, RMSE, and MAE improved by 70.5%, 32.9%, and 41.1%, respectively. …”
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Priority Load Management for Improving Supply Reliability of Critical Loads in Healthcare Facilities Under Highly Unreliable Grids by Ndukwe Henry Ibiam, Fadi Kahwash, Jubaer Ahmed

“…It was found that the priority-based algorithm improved the reliability served to the most critical loads at the expense of the least critical. …”
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Last-Mile Shuttle Planning for Improving Bus Commuters’ Travel Time Reliability: A Case Study of Beijing by Weibin Kou, Jiayu Wang, Yanxi Liu, Chenxu Li

“…This study proposes a multiobjective mixed integer nonlinear programming model for a last-mile shuttle service to improve bus commuters’ travel time reliability. …”
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YOLOv7-DWS: tea bud recognition and detection network in multi-density environment via improved YOLOv7 by Xiaoming Wang, Xiaoming Wang, Zhenlong Wu, Guannan Xiao, Guannan Xiao, Chongyang Han, Cheng Fang

“…Secondly, a new loss function WiseIoU is proposed for the loss function in YOLOv7, which improves the accuracy of the model. Finally, we evaluate different attention mechanisms to enhance the model’s focus on key features.Results and discussionThe experimental results show that the improved YOLOv7 algorithm has significantly improved over the original algorithm in all evaluation indexes, especially in the RTea(+6.2%) and mAP@0.5 (+7.7%). …”
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Predictive modeling of adolescent suicidal behavior using machine learning: Key features and algorithmic insights by Priya Metri, Swetta Kukreja

“…This review highlights existing gaps in cross-cultural generalization and calls for the development of interpretable and hybrid models for improved risk prediction.This review aims to conduct a comprehensive examination of the etiological factors contributing to the development of suicidal thoughts in students, with the goal of enabling early detection through the application of AI and machine learning techniques.This paper aims to review the current state-of-the-art, highlight the limitations, and emphasizes the need to shift toward hybrid and ensemble deep learning models, which have shown early promise but lack extensive analysis in current literature.…”
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Models and Algorithms of Conflict Detection and Scheduling Optimization for High-Speed Train Operations Based on MPC by Zhihui Wang, Yonghua Zhou, Deng Liu

“…Compared with the general-speed railway transportation, the high-speed railway transportation requires a timely and automatic adjustment capability in the centralized traffic control (CTC) system. In order to improve the capability, this paper mainly explores the models and algorithms of conflict detection and scheduling optimization of high-speed train operations. …”
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Algorithm Comparison and Evaluation of GAN Models Based on Image Transferring from Desert to Green Field by Zhenyu Liu, Hongjun Li

“…In order to improve the rendering efficiency of image style transformation and increase the variety of renderings, we can build an algorithm for automatically generating style images based on machine learning. …”
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