Design of nodes importance assessment method for complex network based on neighborhood information by Xing LI, Jie ZHAN, Baoquan REN, Siqi ZHU

“…Accurate identification of influential nodes in complex networks is crucial for network management and network security.The local centrality method is concise and easy to use, but ignores the topological relationship between neighboring nodes and cannot provide globally optimal results.A node importance assessment method was proposed to correlate the node edge relationship and topology, which firstly applied the H-index and information entropy to assess the nodes, then combined the structural holes of the nodes with the structural characteristics of the nodes, and took into account the attribute of “bridging” while focusing on the node’s own quality and the amount of information about the neighboring nodes.The algorithm was validated by simulating the propagation process using the SIR model, and the Kendall correlation coefficient, complementary cumulative distribution function and propagation influence were applied to validate the validity and applicability of the method.Comparison of the experimental results on six real network datasets shows that the proposed method is more accurate than the traditional centrality methods in identifying and ordering the key nodes in the network.…”
Get full text

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. …”
Get full text

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. …”
Get full text

Design and Analysis of Parallel Adjusting Equipment of Vertical Drilling by Zhou Bin, Zeng Yishan, Zi Bin

“…Focusing on the current limited vertical adjustment technique of large-scale drillings,a 6-DOF parallel adjustment equipment with 12 inputs is designed for the working condition of vertical drilling.The equipment mechanism consists of 6branched chains with redundancy which are symmetrical in structure.Each of the chains is composed by a compound of rotate joint and a compound of spherical joint,while the two pairs are connected by two prismatic pairs.The modal analysis is carried out on the body which is based on ANSYS software,first six order frequency distribution and modal vibration mode,and along the X、Y、Zdirection of the displacement frequency response about the moving platform are got.The analysis consequence shows that the most sensitive of external forces to the moving platform is 46 Hz frequency.Otherwise,the working space of the 6-DOF platform is obtained by using the 3-D searching algorithm.The results have significant meanings in the further research on the correlation between the parameters and the whole mechanism,as well as the optimization of the parameter.…”
Get full text

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. …”
Get full text

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.…”
Get full text

Saliency Detection via Fusing Color Contrast and Hash Fingerprint by Yin Lv, Xuanrui Zhang, Yong Wang

“…Besides, another saliency map that enhances the salient region while restraining the background is also generated through hash fingerprint matching. …”
Get full text

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.…”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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.…”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text