Progress in Research on Metal Ion Crosslinking Alginate-Based Gels by Yantao Wang, Zhenpeng Shen, Huili Wang, Zhaoping Song, Dehai Yu, Guodong Li, Xiaona Liu, Wenxia Liu

“…The process of metal ion-induced alginate gelation has been the subject of thorough research over the last few decades. …”
Get full text

Instance structure based multi-label learning with missing labels by Tianzhu CHEN, Fenghua LI, Yunchuan GUO, Zifu LI

“…To address the problem that the existing methods in multi-label learning did not efficiently deal with the problems, the instance structure based multi-label learning scheme with missing labels was proposed.By considering the feature and label structure of instance, the similarity of label vectors were exploit to fill the missing labels and the weight rank loss was exploit to reduce the model bias.Meanwhile, the weight rank loss was also exploit to reduce the model bias.More specially, the manifold structure was capture by forcing the consistency of the geometry similarity of labels and one of the predicted labels.By measuring ranking loss for complete labels and incomplete labels, the relevance of label was distinguish to instance.Experiment results show that the superior performances of the proposed approach compared with the state-of-the-art methods and the accuracy is improved by more than 10% compared with the best comparison scheme under some evaluation criteria.…”
Get full text

A Tri-Attention Neural Network Model-BasedRecommendation by Nanxin Wang, Libin Yang, Yu Zheng, Xiaoyan Cai, Xin Mei, Hang Dai

“…Heterogeneous information network (HIN), which contains various types of nodes and links, has been applied in recommender systems. Although HIN-based recommendation approaches perform better than the traditional recommendation approaches, they still have the following problems: for example, meta-paths are manually selected, not automatically; meta-path representations are rarely explicitly learned; and the global and local information of each node in HIN has not been simultaneously explored. …”
Get full text

Hydrological Process Simulation Based on Statistical Simulation and Data Assimilation by YIN Jian, QIU Yuanhong, OU Zhaofan

“…In order to solve the load capacity calculation and performance optimization by modelparameter calibration, this paper realizes comprehensive optimization of hydrological simulationby taking the Shahe River Basin in North China as the research object and combining thedistributed time-variable gain hydrological model, the response surface provided by PSUADEplatform for parameter optimization, and the ensemble Kalman filtering for error correction & dataassimilation. achieves parameter calibration through using the observation of the outlet flow ofthe basin as the verification data, taking the Nash-Sutcliffe efficiency coefficient, waterbalance coefficient and their comprehensive functions as the evaluation targets, applying thestatistical simulation proxy model of the hydrological model generated by response surface method,performing a sensitivity analysis on the model parameters and reducing the value range, andadopting the global optimization method, and effectively correct the simulation of the runoffprocess in the river basin based on the remote sensing evapotranspiration observation, the ensemble Kalman filtering algorithm and the data assimilation of the hydrological model. …”
Get full text

A A Fingerprint-Based Attendance System for Improved Efficiency by Olayiwola Charles Adesoba, Israel Mojolaoluwa Joseph

“… This paper presents the design and implementation of a fingerprint-based attendance system to address challenges in lecture attendance monitoring in developing countries. …”
Get full text

A Gain-Scheduling PI Control Based on Neural Networks by Stefania Tronci, Roberto Baratti

“…The controller design is based on generic model control (GMC) formalisms and linearization of the neural model of the process. …”
Get full text

Micro-parameter Optimization of Helical Cylindrical Gear based on Romax by Hongfu Xing, Chaohui Yang, Nan Yu, Chao Xu, Jingliang Jiang

“…With the development of technology，the high precision transmission equipment has higher and higher requirements on gear. In the gearbox of main reduction helical cylindrical gear as the research object，by using Romax software，the gearbox model is established，combining the theory of microscopic parameters optimization of cylindrical bevel wheel，the transmission error，distribution of load per unit length of gear tooth surface and the contact spot are taken as the optimization objectives for microscopic gear modification，an omnidirectional modification method combining helical modification and tooth profile modification is proposed. …”
Get full text

Attention-based deep learning for accurate cell image analysis by Xiangrui Gao, Fan Zhang, Xueyu Guo, Mengcheng Yao, Xiaoxiao Wang, Dong Chen, Genwei Zhang, Xiaodong Wang, Lipeng Lai

“…Noisy and redundant signals in cell images impede accurate deep learning-based image analysis. To address these issues, we introduce X-Profiler, a novel HCA method that combines cellular experiments, image processing, and deep learning modeling. …”
Get full text

Efficient and Adaptively Secure Attribute-Based Proxy Reencryption Scheme by Huixian Li, Liaojun Pang

“…Ciphertext-Policy Attribute-Based Proxy Reencryption (CP-ABPRE) has found many practical applications in the real world, because it extends the traditional Proxy Reencryption (PRE) and allows a semitrusted proxy to transform a ciphertext under an access policy to the one with the same plaintext under another access policy. …”
Get full text

New strategy for gastrointestinal protection based on gaseous mediators application by O. N. Sulaieva, J. L. Wallace

“…To assess protective mechanisms and efficacy of gaseous mediators based antiinflammatory therapy. Key points. Nowadays there are no reasonable and effective methods of prevention and treatment of NSAID-induced intestinal lesions. …”
Get full text

Research Progress of Synthesis and Modification Methods Based on Dynamic Substructures by Jintao Su, Bangdong Wang

Get full text

Calibration verification for stochastic agent-based disease spread models. by Maya Horii, Aidan Gould, Zachary Yun, Jaideep Ray, Cosmin Safta, Tarek Zohdi

“…In this work, we develop a stochastic agent-based disease spread model to act as a testing environment as we test two calibration methods using simulation-based calibration, which is a synthetic data calibration verification method. …”
Get full text

Study on PON Based LTE Small Cell Backbaul Tecbnology by Min Cao, Ming Jiang, Chengbin Shen, Tao Zeng

“…Those key technologies related to PON based LTE small cell backhaul and their implementations were discussed. …”
Get full text

Optimal Control of Renewable Resources Based on the Effective Utilization Rate by Rui Wu, Zhengwei Shen, Fucheng Liao

Get full text

Real-World Experience with Dolutegravir-Based Two-Drug Regimens by Douglas Ward, Moti Ramgopal, David J. Riedel, Cindy Garris, Shelly Dhir, John Waller, Jenna Roberts, Katie Mycock, Alan Oglesby, Bonnie Collins, Megan Dominguez, James Pike, Joseph Mrus

“…Background. Dolutegravir-based 2-drug regimens (DTG 2DRs) are now accepted as alternatives to 3-drug regimens for HIV antiretroviral treatment (ART); however, literature on physician drivers for prescribing DTG 2DR is sparse. …”
Get full text

Network Representation Based on the Joint Learning of Three Feature Views by Zhonglin Ye, Haixing Zhao, Ke Zhang, Zhaoyang Wang, Yu Zhu

“…Big Data Mining and Analytics…”
Get full text

A Lightweight AI-Based Approach for Drone Jamming Detection by Sergio Cibecchini, Francesco Chiti, Laura Pierucci

“…The future integration of drones in 6G networks will significantly enhance their capabilities, enabling a wide range of new applications based on autonomous operation. However, drone networks are particularly vulnerable to jamming attacks, a type of availability attack that can disrupt network operation and hinder drone functionality. …”
Get full text

Aura phenomenon: a proposal for an etiology-based clinical classification by Umberto Pensato, Andrew M. Demchuk, Jens P. Dreier, Kevin C. Brennan, Simona Sacco, Michele Romoli

“…Main body We propose the following terminology and etiology-based clinical classification for the aura phenomenon: (i) Migrainous Aura (when the etiology is migraine), (ii) Non-migrainous Aura (when there is an alternative etiology), (iii) Aura of uncertain clinical etiology (when etiology is unclear), and (iv) Migrainous Infarction (a typical migrainous aura in a patient with migraine with aura associated with an infarction in a corresponding anatomical brain region). …”
Get full text

Slope Deformation Prediction Based on IVDF-SVR Coupling Model by HOU Taiping, YANG Qiandong, LU Xuefeng, JIANG Lei, WU Anjie, HUANG Xiuyin

“…Given the shortcomings of improved variable-dimension fractal in the fitting and prediction of fractal dimensions,this paper proposes a fractal prediction model based on the coupling of the improved variable-dimension fractal (IVDF) theory and the support vector regression (SVR) machine theory,namely the IVDF-SVR coupling model.The model uses the SVR machine theory to fit and predict the fractal dimension sequence in the original improved variable-dimension fractal model.This paper takes the slope displacement monitoring data of Maoping Landslide as an example and selects the dimensioned segmented ln(r)-ln(S1) curve of the cumulative sum sequence as the fractal parameter curve of the prediction model.The IVDF model is utilized to calculate the segmented fractal dimension of each curve,and slope displacement is predicted.Then,the IVDF-SVR coupling model is used for another round of calculation and prediction.The prediction results show that the IVDF-SVR coupling model makes full use of the self-similarity in the fractal theory so that the prediction model has strong noise resistance.Moreover,by incorporating the self-learning ability in the SVR theory,it enables data fitting and prediction under small samples and nonlinear conditions.These advantages provide the proposed model with a favorable prediction length,high prediction accuracy,and ultimately a bright application prospect.…”
Get full text

Monte Carlo Based Personalized PageRank on Dynamic Networks by Zhang Junchao, Chen Junjie, Jiancheng Song, Rong-Xiang Zhao

“…In this paper, we design a Monte Carlo-based incremental method for Personalized PageRank computation. …”
Get full text