A New Multiphase Soft Segmentation with Adaptive Variants by Hongyuan Wang, Fuhua Chen, Yunmei Chen

“…Second, we develop a bidirection projected primal dual hybrid gradient (PDHG) algorithm for iterations of membership functions. Third, we also develop a novel algorithm for explicitly computing the projection from RK to simplex ΔK-1 for any dimension K using dual theory, which is more efficient in both coding and implementation than existing projection methods.…”
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A Decision-Making Model for Self-Driving Vehicles Based on Overtaking Frequency by Mengyuan Huang, Shiwu Li, Mengzhu Guo, Lihong Han

“…First, a self-driving vehicle and surrounding vehicles are compared in terms of the overtaking frequency (OTF), and an OTF-based driving state evaluation algorithm is proposed considering the future driving efficiency. …”
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Customer service complaint work order classification based on matrix factorization and attention multi-task learning by Yong SONG, Zhiwei YAN, Yukun QIN, Dongming ZHAO, Xiaozhou YE, Yuanyuan CHAI, Ye OUYANG

“…The automatic classification of complaint work orders is the requirement of the digital and intelligent development of customer service of communication operators.The categories of customer service complaint work orders have multiple levels, each level has multiple labels, and the levels are related, which belongs to a typical hierarchical multi-label text classification (HMTC) problem.Most of the existing solutions are based on classifiers to process all classification labels at the same time, or use multiple classifiers for each level, ignoring the dependence between hierarchies.A matrix factorization and attention-based multi-task learning approach (MF-AMLA) to deal with hierarchical multi-label text classification tasks was proposed.Under the classification data of real complaint work orders in the customer service scenario of communication operators, the maximum Top1 F1 value of MF-AMLA is increased by 21.1% and 5.7% respectively compared with the commonly used machine learning algorithm and deep learning algorithm in this scenario.It has been launched in the customer service system of one mobile operator, the accuracy of model output is more than 97%, and the processing efficiency of customer service agent unit time has been improved by 22.1%.…”
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A Fast Imaging Technique Applied to 2D Electrical Resistivity Data by Raffaele Martorana, Patrizia Capizzi

“…In the past some modifications to the back-projection algorithm, as well as the use of filtering techniques for the sensitivity matrix were proposed. …”
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Application in Feature Extraction of AE Signal for Rolling Bearing in EEMD and Cloud Similarity Measurement by Long Han, Chengwei Li, Liqun Shen

“…Due to the powerful ability of EEMD algorithm in noising, it is usually applied to feature extraction of fault signal of rolling bearing. …”
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Forest Fire Smoke Video Detection Using Spatiotemporal and Dynamic Texture Features by Yaqin Zhao, Zhong Zhou, Mingming Xu

“…The performance of smoke video detection algorithm is often influenced by some smoke-like objects such as heavy fog. …”
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In the Search of Fundamental Inner Bond Strength of Solid Elements by Maziar Sahba Yaghmaee, Reza Riahifar

“…Therefore, in order to study the effect of the nature of metallic bond on their physico-chemical properties, we first tried to investigate and introduce a mathematical model for transforming the bulk molar cohesion energy into microscopic bond strengths between atoms. Then an algorithm for estimating the nature of bond type including the materials properties and lattice scale “cutoff” has been proposed. …”
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A hybrid Harris Hawks Optimization with Support Vector Regression for air quality forecasting by Essam H. Houssein, Meran Mohamed, Eman M. G. Younis, Waleed M. Mohamed

“…Additionally, we contrast our methodology with recently created models that have been published in the literature, such as the Grey Wolf Optimizer (GWO), Salp Swarm Algorithm (SSA), Henry Gas Solubility Optimization (HGSO), Barnacles Mating Optimizer (BMO), Whale Optimization Algorithm (WOA), and Manta Ray Foraging Optimization (MRFO). …”
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Application of Surface Roughness Analysis on Micro–Computed Tomographic Images of Bone Erosion: Examples Using a Rodent Model of Rheumatoid Arthritis by Matthew D. Silva, Jason Ruan, Elizabeth Siebert, Anneli Savinainen, Bruce Jaffee, Lisa Schopf, Sudeep Chandra

“…The main advantage of such an algorithm is demonstrated in the preclinical drug study of rat CIA with methotrexate treatment, indicating the immediate utility of this approach in drug development studies.…”
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Squat Motion of a Humanoid Robot Using Three-Particle Model Predictive Control and Whole-Body Control by Hongxiang Chen, Xiuli Zhang, Mingguo Zhao

“…TP-MPC is utilized to optimize the rough planning’s reference trajectory, while WBC is employed to follow the optimized trajectory. The algorithm is tested through simulations of a humanoid robot performing continuous squatting motions. …”
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PERFORMANCE DEGRADATION ASSESSMENT OF ROLLING BEARING BASED ON SINGLE RING THEOREM IN RANDOM MATRIX THEORY by SHAN Qiang, NI GuangXian, WANG Heng

“…A rolling bearing performance degradation assessment algorithm based on single ring theorem in the random matrix theory is proposed to solve the problem that the traditional feature extraction algorithm is not sufficient to extract the useful information of the bearing under the industrial big data environment, and the constructed index is difficult to effectively characterize the bearing degradation process. …”
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A Hybrid Ant Colony Optimization for Dynamic Multidepot Vehicle Routing Problem by Haitao Xu, Pan Pu, Feng Duan

“…Experimental results show that the HACO algorithm is feasible and efficient to solve DMDVRP.…”
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Evaluation of Land Use Change Trends Using Landscape Measurements (Case Study: Pakdasht City) by Alireza Thernasab, Leila Ebrahimi, Ameneh Haghzad, Mehrdad Ramezan Por

“…These images were classified in ENVI 5.3 software based on the maximum likelihood algorithm. Then the accuracy of the maps obtained from the maximum likelihood algorithm was estimated. …”
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Fuzzy Semiactive Vibration Control of Structures Using Magnetorheological Elastomer by Xuan Bao Nguyen, Toshihiko Komatsuzaki, Yoshio Iwata, Haruhiko Asanuma

“…However, the fuzzy semiactive algorithm presented here is able to produce the sufficient applied current and thus viscoelastic force is desirably produced. …”
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A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica by Xin Zou, Wen Long Yue

“…By taking Adelaide Central Business District (CBD) in South Australia as a case, the Bayesian network structure was established by integrating K2 algorithm with experts’ knowledge, and Expectation-Maximization algorithm that could process missing data was adopted to conduct the parameter learning in Netica, thereby establishing the Bayesian network model for the causation analysis of road accidents. …”
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Laboratory Evaluation of Time-Domain Reflectometry for Bridge Scour Measurement: Comparison with the Ultrasonic Method by Xinbao Yu, Xiong Yu

“…TDR method, with the developed analysis algorithm, yields information on the river properties such as the electrical conductivity of river water and the density of sediments. …”
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A Study on the Prediction of House Price Index in First-Tier Cities in China Based on Heterogeneous Integrated Learning Model by Yaqi Mao, Yonghui Duan, Yibin Guo, Xiang Wang, Shen Gao

“…Secondly, with the goal of improving accuracy, diversity, and generalization ability, the types of base learners as well as metalearners are determined, and the parameters of the base learners are optimized using the grey wolf optimization algorithm to produce the GWO-stacking model, and the experimental results from four datasets demonstrate that the model has high prediction accuracy. …”
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A multi-source threat intelligence confidence value evaluation method based on machine learning by Hansheng LIU, Hongyu TANG, Mingxia BO, Jianfeng NIU, Tianbo LI, Lingxiao LI

“…During the collection process of multi-source threat intelligence,it is very hard for the intelligence center to make a scientific decision to massive intelligence because the data value density is low,the intelligence repeatabil-ity is high,and the ineffective time is very short,etc.Based on those problems,a new multi-source threat intelligence confidence value evaluation method was put forward based on machine learning.First of all,according to the STIX intelligence standard format,a multi-source intelligence data standardization process was designed.Secondly,ac-cording to the characteristic of data,14 characteristics were extracted from four dimensions of publishing time,source,intelligence content and blacklist matching degree to be the basis of determining the intelligence reliability.After getting the feature encoding,an intelligence confidence value evaluation model was designed based on deep neural network algorithm and Softmax classifier.Backward propagation algorithm was also used to minimize recon-struction error.Last but not least,according to the 2 000 open source marked sample data,k-ford cross-validation method was used to evaluate the model and get an average of 91.37% macro-P rate and 84.89% macro-R rate.It was a good reference for multi-source threat intelligence confidence evaluation.…”
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Modelling a Coupled Thermoelectromechanical Behaviour of Contact Elements via Fractal Surfaces by G. Mazzucco, F. Moro, M. Guarnieri

“…In this way the micromechanical model allowed for an upgraded contact algorithm in terms of effective contact area and thermal and electrical contact conductivities. …”
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Robust Fractional Low-Order Multiple Window STFT for Infinite Variance Process Environment by Haibin Wang, Changshou Deng, Junbo Long, Youxue Zhou

“…The performance of the traditional cross-term reduction algorithm is compromised, sometimes yielding incorrect results under the infinite variance process environment. …”
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