RWA-BFT: Reputation-Weighted Asynchronous BFT for Large-Scale IoT by Guanwei Jia, Zhaoyu Shen, Hongye Sun, Jingbo Xin, Dongyu Wang

“…This paper introduces RWA-BFT, a reputation-weighted asynchronous Byzantine Fault Tolerance (BFT) consensus algorithm designed to address the scalability and performance challenges of blockchain systems in large-scale IoT scenarios. …”
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The Neural Frontier of Future Medical Imaging: A Review of Deep Learning for Brain Tumor Detection by Tarek Berghout

“…Some models integrate with Internet of Things (IoT) frameworks or federated learning for real-time diagnostics and privacy, often paired with optimization algorithms. However, the adoption of eXplainable AI (XAI) remains limited, despite its importance in building trust in medical diagnostics. …”
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Optimization of high-dimensional expensive multi-objective problems using multi-mode radial basis functions by Jiangtao Shen, Xinjing Wang, Ruixuan He, Ye Tian, Wenxin Wang, Peng Wang, Zhiwen Wen

“…Abstract Numerous surrogate-assisted evolutionary algorithms are developed for multi-objective expensive problems with low dimensions, but scarce works have paid attention to that with high dimensions, i.e., generally more than 30 decision variables. …”
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Monitoring Population Phenology of Asian Citrus Psyllid Using Deep Learning by Maria Bibi, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Muhammad Irfan Khan, Shouket Zaman Khan, Casper Shikali Shivachi, Asad Anees

“…In the current study, several prediction models were developed based on regression algorithms of machine learning to monitor different phenological stages of Asian citrus psyllid to predict its population about different abiotic variables (average maximum temperature, average minimum temperature, average weekly temperature, average weekly relative humidity, and average weekly rainfall) and biotic variable (host plant phenological patterns) in citrus-growing regions of Pakistan. …”
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In-Depth Learning Layout and Path Optimization of Energy Service Urban Distribution Sites under e-Commerce Environment by Kun Wang, Ki-Hyung Bae

“…This paper fully considers the characteristics of the network operation mode of the energy service city distribution site and establishes an optimization model for the location selection and vehicle routing of the distribution center with the lowest total system cost under the simultaneous delivery service mode; based on the hierarchical solution strategy, a combination of deep learning is designed. Algorithms mainly include two-stage hybrid heuristic algorithm of cluster analysis, maximum coverage and genetic algorithm; simulation analysis is conducted to verify the effectiveness of the model and algorithm by data simulation, finally get the integrated optimization plan of distribution center location and routing, and put forward the operation strategy through the result expansion analysis. …”
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Predicting Olympic Medal Trends for Southeast Asian Countries Using the Facebook Prophet Model by Bagus Al Qohar, Yulizchia Malica Pinkan Tanga, Putri Utami, Maylinna Rahayu Ningsih, Much Aziz Muslim

“…However, low-performance regression algorithms are the main problems with prediction. By integrating custom seasonality with the Facebook-Prophet prediction model, this study aims to increase the accuracy of Olympic prediction. …”
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Condition Recognition of High-Speed Train Bogie Based on Multi-View Kernel FCM by Qi Rao, Yan Yang, Yongquan Jiang

“…Furthermore, the condition recognition rate of MvKFCM is higher than that of single-view and four other multiple-view clustering algorithms.…”
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Statistical assessment of interrelationship of marriage and divorces to fertility by A. B. Sinelnikov, O. A. Zolotareva, M. D. Khabib

“…A number of indicators complement the traditional methodology of marriage and divorce tables calculation. The algorithms for obtaining the indicators proposed for implementation (in particular, the cumulative marriage rate of divorcees, the level of divorces compensation by legal remarriages, etc.) have been prescribed, and their estimations have been made, which substantiates the scientific significance of the study. …”
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Effects of Single Nucleotide Polymorphism Marker Density on Haplotype Block Partition by Sun Ah Kim, Yun Joo Yoo

“…With decreasing sampling ratio down to 20% of the original SNP markers, the total number of haplotype blocks decreases and the length of haplotype blocks increases for all algorithms. When we examined the marker-independence of the haplotype block locations constructed from the datasets of different density, the results using below 50% of the entire SNP markers were very different from the results using the entire SNP markers. …”
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Perspectives on Soft Actor–Critic (SAC)-Aided Operational Control Strategies for Modern Power Systems with Growing Stochastics and Dynamics by Jinbo Liu, Qinglai Guo, Jing Zhang, Ruisheng Diao, Guangjun Xu

“…To tackle the limitations of existing control approaches that require full-system models with accurate parameters and conduct real-time extensive sensitivity-based analyses in handling the growing uncertainties, this paper presents a novel data-driven control framework using reinforcement learning (RL) algorithms to train robust RL agents from high-fidelity grid simulations for providing immediate and effective controls in a real-time environment. …”
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Stochastic Optimal Selection and Analysis of Allowable Photovoltaic Penetration Level for Grid-Connected Systems Using a Hybrid NSGAII-MOPSO and Monte Carlo Method by Ali Abubakar, Reindorf Nartey Borkor, Peter Amoako-Yirenkyi

“…Five cutting-edge multiobjective optimization algorithms were implemented and compared using hypervolume metric, execution time, and nonparametric statistical analysis to obtain a quality solution. …”
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Recent Advancements in Deep Learning Frameworks for Precision Fish Farming Opportunities, Challenges, and Applications by Gaganpreet Kaur, Nirmal Adhikari, Singamaneni Krishnapriya, Surindar Gopalrao Wawale, R. Q. Malik, Abu Sarwar Zamani, Julian Perez-Falcon, Jonathan Osei-Owusu

“…The technical specifics of DL approaches used in smart fish farming which includes data and algorithms as well as performance was also examined. …”
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Deep Learning Automated System for Thermal Defectometry of Multilayer Materials by A. S. Momot, R. M. Galagan, V. Yu. Gluhovskii

“…Three neural network modules are used for automated data processing, each of which performs one of the tasks: defects detection and classification, determination of the defect depth and thickness. The software algorithms and user interface for interacting with system are programmed in the NI LabVIEW development environment.Experimental studies on samples made of multilayer fiberglass have shown a significant advantage of the developed system over using traditional methods for analyzing thermal testing data. …”
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Structural Health Monitoring of Precast Concrete Box Girders Using Selected Vibration-Based Damage Detection Methods by Zhengjie Zhou, Leon D. Wegner, Bruce F. Sparling

“…A box girder removed from a dismantled bridge was used to evaluate the ability of five different VBDD algorithms to detect and localize low levels of spalling damage, with a focus on using a small number of sensors and only the fundamental mode of vibration. …”
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Gradient pooling distillation network for lightweight single image super-resolution reconstruction by Zhiyong Hong, GuanJie Liang, Liping Xiong

“…Thus, there is a pressing demand to devise efficient super-resolution algorithms. To address this issue, we propose a gradient pooling distillation network (GPDN), which can enable the efficient construction of a single image super-resolution system. …”
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Research on noise-induced hearing loss based on functional and structural MRI using machine learning methods by Minghui Lv, Liping Wang, Ranran Huang, Aijie Wang, Yunxin Li, Guowei Zhang

“…The support vector machine (SVM), random forest (RF) and logistic regression (LR) algorithms, were used to establish the classification model for NIHL. …”
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Real-Time Adaptive Content-Based Synchronization of Multimedia Streams by Imad H. Elhajj, Nadine Bou Dargham, Ning Xi, Yunyi Jia

“…Testing adaptive content-based and adaptive time-based synchronization algorithms remotely between the American University of Beirut and Michigan State University showed that the proposed method outperforms the traditional synchronization method. …”
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A novel ensemble model for fall detection: leveraging CNN and BiLSTM with channel and temporal attention by Sarita Sahni, Sweta Jain, Sri Khetwat Saritha

“…Despite the proliferation of machine learning and deep learning algorithms for fall detection, their efficacy remains hampered by resilience, robustness, and adaptability challenges across varied input scenarios. …”
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CBSBS: A classification-based size-based scheduling and its application in industrial network by Zhiqiang He, Yongjun Lin

“…Least attained recent service optimizes the queuing algorithm by applying historical accumulation factor and decay cycle factor. …”
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Intelligent Injection Molding on Sensing, Optimization, and Control by Peng Zhao, Jianfeng Zhang, Zhengyang Dong, Junye Huang, Hongwei Zhou, Jianzhong Fu, Lih-Sheng Turng

“…Finally, conclusions are drawn to discuss future research directions and technologies, as well as algorithms worthy of being explored and developed.…”
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