Unveiling connectivity patterns of railway timetables through complex network theory and Infomap clustering. by Fabio Lamanna, Michele Prisma, Giorgio Medeossi

“…Comparative analysis of the two scenarios highlights improvements in physical infrastructure and travel time efficiency by 2033, while also identifying areas where service frequency distribution and transfer effectiveness may require further optimization. …”
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Adaptive rumor propagation and activity contagion in higher-order networks by Yafang Dong, Liang’an Huo, Matjaž Perc, Stefano Boccaletti

“…We also apply a sequential quadratic programming algorithm to optimize the parameters of our model and validate its accuracy and applicability on real-world data. …”
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Skip-Connected CNN Exploiting BNN Surrogate for Antenna Modelling by Yubo Tian, Jinlong Sun, Zhiwei Zhu

“…The combination of evolutionary algorithms with full-wave electromagnetic (EM) simulation software is an effective method for antenna optimal design. …”
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Client grouping and time-sharing scheduling for asynchronous federated learning in heterogeneous edge computing environment by Qianpiao MA, Qingmin JIA, Jianchun LIU, Hongli XU, Renchao XIE, Tao HUANG

“…., edge heterogeneity, data Non-IID, and communication resource constraints, a grouping asynchronous federated learning (FedGA) mechanism was proposed.Edge nodes were divided into multiple groups, each of which performed global updated asynchronously with the global model, while edge nodes within a group communicate with the parameter server through time-sharing communication.Theoretical analysis established a quantitative relationship between the convergence bound of FedGA and the data distribution among the groups.A time-sharing scheduling magic mirror method (MMM) was proposed to optimize the completion time of a single round of model updating within a group.Based on both the theoretical analysis for FedGA and MMM, an effective grouping algorithm was designed for minimizing the overall training completion time.Experimental results demonstrate that the proposed FedGA and MMM can reduce model training time by 30.1%～87.4% compared to the existing state-of-the-art methods.…”
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A hybrid unsupervised machine learning model with spectral clustering and semi-supervised support vector machine for credit risk assessment. by Tao Yu, Wei Huang, Xin Tang, Duosi Zheng

“…The effectiveness, efficiency, and robustness of the proposed TSC-SVM model are demonstrated through various real-world applications. The proposed algorithm is anticipated to expand the customer base for financial institutions while reducing economic losses.…”
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Robust Mainlobe Interference Suppression Based on Joint Oblique Projection for Dual Polarization Conformal Array by Chao Liu, Xiaoyuan Zhang, Junjie Qian, Lei Zhang

“…In this paper, a robust mainlobe interference suppression algorithm is proposed in a space-polarization joint domain based on a dual-polarized conformal array. …”
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A framework for detecting and predicting highway traffic anomalies via multimodal fusion and heterogeneous graph neural networks. by Shaowei Sun, Mingzhou Liu

“…To address these limitations, we propose a framework based on multimodal deep fusion and heterogeneous graph neural networks (HGNNs), incorporating an Ensemble Contrastive Pessimistic Likelihood Estimation (CPLE) algorithm to optimize performance. The framework integrates static and dynamic traffic data, such as video images, traffic flow, vehicle speed, and tunnel weather conditions. …”
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Computing mutual similarity of 3D human faces in nearly linear time. by Radek Ošlejšek, Petra Urbanová, Jiří Sochor

“…Our solution utilizes properties of facial scan geometry to optimize individual steps. Moreover, the algorithm deals with possible holes and other artifacts in polygonal meshes automatically. …”
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Benthos-DETR: a high-precision efficient network for benthic organisms detection by Weibo Rao, Gang Chen, Yifei Zhang, Jue Cang, Shusen Chen, Chenyang Wang

“…Through a series of experimental analyses, it was evident that the performance of the Benthos-DETR network surpasses existing target detection algorithms, achieving an optimal equilibrium between high recognition precision and a trim network scale.…”
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Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia by Fangmin Zhong, Fangyi Yao, Zihao Wang, Jing Liu, Bo Huang, Xiaozhong Wang

“…The formation of NETs is impaired in acute myeloid leukemia (AML), which can result in immunodeficiency and increased susceptibility to infection.MethodsThe gene set variation analysis (GSVA) algorithm was employed for the calculation of NET score, while the consensus clustering algorithm was utilized to identify molecular subtypes. …”
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EDT-MCFEF: a multi-channel feature fusion model for emergency department triage of medical texts by Tao Lin, Shiming Yi

“…However, traditional triage methods frequently depend on human judgment, which is susceptible to high subjectivity and low efficiency.MethodsTo address these issues, this paper presents a novel emergency department triage algorithm. The proposed EDT-MCFEF (Emergency Triage Algorithm Based on Multi-Channel Feature Extraction and Fusion) addresses numerous shortcomings of conventional triage methodologies. …”
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Minimization of Resource Consumption with URLLC Constraints for Relay-Assisted IIoT by Yujie Zhao, Tao Peng, Yichen Guo, Yijing Niu, Wenbo Wang

“…In this work, the packet error probability (PEP) and blocklength allocation across two-hop links are jointly optimized to minimize total blocklength (resource consumption) while satisfying reliability, latency, and throughput requirements. …”
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Denoising of acoustic emission signals from rock failure processes through ICEEMDAN combined with multiple criteria and wavelet transform by Tao Wang, Weiwei Ye, Liyuan Liu, Zhihui Zhao, Wei Huang

“…The peak frequency range is unaffected before and after optimization, while the main amplitude reduction is concentrated in the high-frequency range. …”
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A Model‐Independent Strategy for the Targeted Observation Analysis and Its Application in ENSO Prediction by Weixun Rao, Youmin Tang, Yanling Wu, Xiaojing Li

“…Sensitive experiments show that while number of data sets reaches 12, a robust optimal observational array is obtained. …”
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Computational design exploration of rocket nozzle using deep reinforcement learning by Aagashram Neelakandan, Arockia Selvakumar Arockia Doss, Natrayan Lakshmaiya

“…Additionally, the use of the Single-Step Proximal Policy Optimization (SSPPO) algorithm enhances the exploration of nozzle geometries by maximizing aerodynamic performance while balancing computational efficiency. …”
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Fast and fair split computing for accelerating deep neural network (DNN) inference by Dongju Cha, Jaewook Lee, Daeyoung Jung, Sangheon Pack

“…To address these issues, we formulate an optimization problem to determine one or two split points that minimize inference latency while ensuring fair offloading among MDs. …”
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Effective feature selection based HOBS pruned- ELM model for tomato plant leaf disease classification. by M Amudha, K Brindha

“…Firstly, an Elephant Herding Optimization (EHO) algorithm selects pertinent features for classification tasks. …”
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A Blockchain-Based Architecture of Web3.0: A Comprehensive Decentralized Model With Relay Nodes, Unique IDs and P2P by Hyunjoo Yang, Sejin Park

“…When faced with malicious requests, the system significantly reduces verification latency to an average of 0.0106 ms, ensuring rapid rejection and preserving network stability, while legitimate requests are processed efficiently with an average latency of 0.4125 ms.Experiments comparing latency-based and random-based relay selection methods across various network configurations (public-public, public-private, private-private) demonstrate that latency-based selection optimizes connection setup times in low-latency environments, while random-based selection provides robust performance in complex network scenarios. …”
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Distributed blockchain assisted secure data aggregation scheme for risk-aware zone-based MANET by V R. Sugumaran, E. Dinesh, R. Ramya, Elangovan Muniyandy

“…Data aggregation is secured through a Two-Step Secure (STS) method and Elliptic Curve Cryptography (ECC), while optimal routing is achieved using the Improved Elephant Herd Optimization (IEHO) algorithm. …”
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Hybrid energy storage systems for photovoltaic storage microgrids power allocation and capacity determination based on adaptive Savitzky-Golay filtering and VMD-DTW by Zengqiang Ma, Zejia Zhou, Tianming Mu, Cheng Wen

“…An enhanced dung beetle optimization algorithm is employed to optimize this model, enabling adaptive parameter adjustments in SG filtering. …”
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