An optimized deterministic concurrency control approach for geo-distributed transaction processing on permissioned blockchains by Zhibo Han, Zeshun Peng, Gang Wang, Minghe Yu, Xiaohua Li, Yanfeng Zhang, Ge Yu

“…Traditional concurrency control algorithms, such as locking-based protocols, usually suffer from performance degradation due to heavy transaction coordination overheads. …”
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Enhanced medical image segmentation using novel level set evolution and efficient optimization by Samad Wali, Adil Jhangeer, Ariana Abdul Rahimzai, Samina Samina, Mudassar Imran

“…Unlike prior edge-based algorithms, which frequently fail with noisy images and have large computing costs, our method incorporates an improved edge indicator term into the level set architecture, considerably improving performance on degraded images. …”
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Bio-Inspired Object Detection and Tracking in Aerial Images: Harnessing Northern Goshawk Optimization by Agnivesh Pandey, Rohit Raja, Sumit Srivastava, Krishna Kumar, Manoj Gupta, Chanyanan Somthawinpongsai, Aziz Nanthaamornphong

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A novel swarm intelligence-based approach for solving optimal power flow problems in modern power systems by Haewon Byeon, Wajdi Alghamdi, Munni Evin, M. Sucharitha, D. David Neels Ponkumar, A. Prakash, J. Sunil

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ML-RASPF: A Machine Learning-Based Rate-Adaptive Framework for Dynamic Resource Allocation in Smart Healthcare IoT by Wajid Rafique

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A hybrid BOA-SVR approach for predicting aerobic organic and nitrogen removal in a gas-liquid-solid circulating fluidized bed bioreactor by Shaikh Abdur Razzak, Nahid Sultana, S.M. Zakir Hossain, Muhammad Muhitur Rahman, Yue Yuan, Mohammad Mozahar Hossain, Jesse Zhu

“…The downer of a GLSCFB bioreactor provided experimental data on TKN, NH4-N, NO3-N, and TCOD removal. The hybrid optimal intelligence algorithm (BOA-SVR) has improved model accuracy across multiple domains by combining BOA and SVR. …”
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Securing and optimizing optical transmission in quantum wells using OAM and advanced modulation techniques by Muhammad Ahmad, Zhiping Wang, Ming Fang, Zhixiang Huang, Guoda Xie

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Measurement of Mobile Switching Centres Throughput in GSM Network Integrating Sliding Window Algorithm with a Single Server Finite Queuing Model by Dinaker Babu Bollini, Mannava Muniratnam Naidu, Mallikharjuna Rao Nuka

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Data enhanced iterative few-sample learning algorithm-based inverse design of 2D programmable chiral metamaterials by Zhao Zeyu, You Jie, Zhang Jun, Du Shiyin, Tao Zilong, Tang Yuhua, Jiang Tian

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Optimal Allocation of Gas Supply Reliability in Natural Gas Pipeline System Based on Exterior Penalty Function Method by Yueqi LIU, Lei HOU, Shuaishuai TANG, Huai SU, Xingtao LI

“…Optimal allocation of gas supply reliability is an important part of gas supply reliability of natural gas pipeline system.In order to study the optimal allocation scheme of gas supply reliability with the lowest cost,a cost function model based on the gas supply capacity of the pipeline system was constructed.To address the limitation of traditional intelligent optimization algorithms (e.g.…”
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Quantum-enabled topological optimization of distributed energy storage for resilient black-start operations by Yinchi Shao, Yu Gong, Xiaoyu Wan, Xianmiao Huang, Shanna Luo, Yuntao Cao, Tao Zhang

“…By integrating quantum annealing algorithms, the framework efficiently addresses the combinatorial complexity of large-scale ESS placement and dispatch, outperforming traditional heuristic and classical optimization techniques in both computational speed and solution quality. …”
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Fusion of transfer learning with nature-inspired dandelion algorithm for autism spectrum disorder detection and classification using facial features by G. Elangovan, N. Jagadish Kumar, J. Shobana, M. Ramprasath, Gyanendra Prasad Joshi, Woong Cho

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Deep Learning‐Guided Urban Climate Risk Mitigation Through Optimal Spatial Allocation of Green and Cool Roofs by JiHyun Kim, Suyeon Choi, Mahdi Panahi, Hocheol Seo, Yeonjoo Kim

“…These indices were used to test four deep learning algorithms: UNet, UNet++, UNet3+, and Multi‐ResUNet. …”
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Application of Machine Learning for Adaptive Trajectory Control of UAVs Under Uncertainty by Alexander S. Ermilov, Olga A. Saltykova

“…Parameters such as system adaptability, trajectory correction accuracy, and stability under challenging conditions are studied to assess the accuracy and efficiency of the proposed algorithms. The study also investigates the impact of computational power limitations on the real-time performance of algorithms. …”
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Intelligent algorithm-based model for predicting mass transfer performance in CO2 absorption within a rotating packed bed by Wei Zhang, Hao Chen, Ke Huang, Xing Shu, Cheng Fu, Bin Huang

“…Using dimensional analysis, key factors are transformed into dimensionless numbers, which are then input into models integrating least squares support vector machine (LSSVM) with genetic algorithm (GA), particle swarm optimization (PSO), and a hybrid GA-PSO (HGAPSO). …”
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Technological advances and the use of IoT in monitoring Diaphorina citri in citrus cultivation by Eduardo Goiano da Silva, Franciely da Silva Ponce, Silvia Graciele Hulse de Souza

“…The integration of IoT facilitates the early detection of D. citri and the continuous monitoring of their populations, improving the response to pest outbreaks and optimizing the use of insecticides. Systems based on AIoT (Artificial Intelligence of Things) and computer vision have demonstrated high accuracy in identifying and occurring pests, allowing for fast and efficient management. …”
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A Novel LSTM Architecture for Automatic Modulation Recognition: Comparative Analysis With Conventional Machine Learning and RNN-Based Approaches by Sam Ansari, Soliman Mahmoud, Sohaib Majzoub, Eqab Almajali, Anwar Jarndal, Talal Bonny

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Bat optimization of hybrid neural network-FOPID controllers for robust robot manipulator control by Bashra Kadhim Oleiwi, Mohamed Jasim, Ahmad Taher Azar, Ahmad Taher Azar, Saim Ahmed, Saim Ahmed, Ahmed Redha Mahlous, Ahmed Redha Mahlous

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Optical multilayer thin film structure inverse design: From optimization to deep learning by Taigao Ma, Mingqian Ma, L. Jay Guo

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An interpretable machine learning model based on computed tomography radiomics for predicting programmed death ligand 1 expression status in gastric cancer by Lihuan Dai, Jinxue Yin, Xin Xin, Chun Yao, Yongfang Tang, Xiaohong Xia, Yuanlin Chen, Shuying Lai, Guoliang Lu, Jie Huang, Purong Zhang, Jiansheng Li, Xiangguang Chen, Xi Zhong

“…SHapley Additive exPlanations (SHAP) were used to interpret the optimal model and visualize the decision-making process for a single individual. …”
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