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6th International Symposium on System and Software Reliability, ISSSR 2020

作者： Zhao, Chenyang Wang, Junling Henan University of Technology Key Laboratory of Grain Information Processing and Control Ministry of Education Zhengzhou China Henan University of Technology School of Science Zhengzhou China

ISBN: (数字)9780738104973

ISBN: (纸本)9780738104973

Most of the existing methods cannot deal with the problem of fault-tolerant workflow scheduling in uncertain environment. Therefore, the paper proposes a dynamic workflow scheduling based on autonomic fault-tolerant scheme selection in uncertain cloud environment. In order to make full use of various cloud resources, the tasks that constitute workflow are divided into various types. And a computing capacity fluctuation model based on multiple states and jump points is established to describe the instability of cloud resource. Moreover, an extended fault-tolerant model is built to deal with various computation and transmission faults. Based on the two models and task classification, tasks are firstly assigned statically to appropriate virtual machines, then the fault-tolerant strategies and the actual execution for tasks are automatically adjusted in a dynamic manner. Experiments show that the proposed method can perform effectively in uncertain cloud environment while ensuring fault tolerance. © 2020 IEEE.

关键词： Fault tolerance

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Mathematical Modeling and Comparative Metabolomics Analyses of Interactions between Lactiplantibacillus Plantarum and Morganella Morganii

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SSRN 2024年

作者： Han, Jing Liu, Binkun Lin, Xinping Zhang, Sufang Dong, Liang Ji, Chaofan School of Food Science and Technology Dalian Polytechnic University Dalian116034 China State Key Laboratory of Marine Food Processing and Safety Control Dalian116034 China College of Food Science and Engineering Henan University of Technology Henan Zhengzhou450001 China College of Information Science and Engineering Henan University of Technology Zhengzhou450001 China

Morganella morganii is a spoilage microorganism in fish products that produces harmful biogenic amines. It has been discovered that Lactiplantibacillus plantarum His6 can inhibit the growth of this bacterium. The aim of this study was to quantitatively assess the inhibitory impact of the bioprotective culture Lpb. plantarum His6 on M. morganii YC16 in the matrix (fish and rice) using predictive microbiology models, and elucidate the interaction mechanism through untargeted metabolomics. The mathematical model results showed the inhibition effect of Lpb. plantarum His6 on M. morganii YC16 was dependent on temperature and inoculation concentration. In addition, the simultaneous growth of Lpb. plantarum His6 and M. morganii YC16 could be well simulated with the Lotka-Volterra model. Finally, based on the metabolomics data, it was speculated that Lpb. plantarum His6 may enhance bacteriocin production while reducing the yield of glycerophospholipids and fatty acids associated with outer membrane formation, thereby inhibiting the growth of M. morganii YC16. These findings provide valuable insights into the interaction behavior and mechanism of Lpb. plantarum His6 and M. morganii YC16 in co-culture, facilitating the design of the biopreservation strategies for fish products. © 2024, The Authors. All rights reserved.

关键词： Product design

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A survey on automatic bug fixing 6

A survey on automatic bug fixing

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6th International Symposium on System and Software Reliability, ISSSR 2020

作者： Cao, Heling Meng, Yangxia Shi, Jianshu Li, Lei Liao, Tiaoli Zhao, Chenyang Henan University of Technology Ministry of Education Key Laboratory of Grain Information Processing and Control Zhengzhou China Henan University of Technology College of Information Science and Engineering Zhengzhou China

ISBN: (纸本)9780738104973

To reduce the cost of software debugging, Automatic Bug Fixing (ABF) techniques have been proposed for efficiently fixing and maintaining software, aiming to rapidly correct bugs in software. In this paper, we conduct a survey, analysing the capabilities of existing ABF techniques based on the test case set. We organize knowledge in this area by surveying 133 high-quality papers from 1990 to June 2020 and supplement 57 latest high-quality papers from 2017 to June 2020. This paper shows that existing ABF approaches can be divided into three main strategies: search-based, semantic-based, and template-based. Search-based ABF considers using search strategies, such as genetic programming, context similarity, to change the programs into the correct one. Semantic-based ABF involves symbolic execution and constraint solving, such as satisfiability modulo theories solver, contracts, to fix bugs. Different from the two kinds of theories above, template-based ABF is mainly based on fixing templates, such as other programs, bug reports, to fix bugs. Besides, we provide a summary of the commonly used defect benchmarks and all the available tools that are frequently used in the field of ABF. We also discuss the empirical foundations and argumentation in the area and prospect the trend of future study. © 2020 IEEE.

关键词： Automatic bug fixing Emplate-based Search-based Semantic-based Software debugging

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Tcgfusion: A Network for Pet-Mri Fusion Based on Gan and Transformer

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SSRN 2022年

作者： Fan, Chao Chen, Zhixiang Lin, Hao Wang, Xiao School of Artificial Intelligence and Big Data Henan University of Technology Henan Province Zhengzhou City China School of Information Science and Engineering Henan University of Technology Henan Province Zhengzhou City China Key Laboratory of Grain Information Processing and Control Ministry of Education Henan Province Zhengzhou City China

We provide an end-to-end unsupervised training model called TCGFusion: a network for PET-MRI fusion based on GAN and transformer. We set the generator to a dual-path layout to assure the gathering of both global and detailed image information. To guarantee the coarse scale picture extraction and prevent the high computational cost, the global path T-Path utilizes Grid-former (a residual grid transformer structure). The detailed path C-Path is DenseNet, and its multi-cascade structure captures image details well. Additionally, we set up a dual adversarial mechanism between the fused image and the source image, creating a dual discriminator to determine the distribution of structural similarity between the fused result and the source image, and using patch-SSIM to reinforce the semantic constraints between them and promote the image details. According to our extensive studies on public datasets, medical image fusion demonstrate the superiority of our TCGFusion compared to the state-of-the-art image fusion algorithms. © 2022, The Authors. All rights reserved.

关键词： Semantics

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Dfe-Net: Dual-Branch Feature Extraction Network for Enhanced Segmentation in Skin Lesion

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SSRN 2022年

作者： Fan, Chao Yang, Litao Lin, Hao Qiu, Yingying School of Artificial Intelligence and Big Data Henan University of Technology Henan Province Zhengzhou City China Key Laboratory of Grain Information Processing and Control Ministry of Education Henan Province Zhengzhou City China School of Information Science and Engineering Henan University of Technology Henan Province Zhengzhou City China

Skin lesion segmentation is a critical method for extracting pathological information from dermoscopy images, which is of great significance for lesion location, recognition, monitoring and treatment. Due to the varied sizes of lesions, different forms and colors, and blurring boundaries, the present detection methods are unable to accurately anticipate local features, which has an impact on the segmentation accuracy. Therefore, the Dual-branch Feature Extraction Network (DFE-Net) is suggested in this paper. We designed two types of encoders based on the Transformer and Efficient Channel Attention (ECA) module, one for extracting the global feature and another for the local feature, before fusing and decoding. Simultaneously, the skip connections from the Enhanced ECA Feature Extraction Modules to decoders are designed to reduce feature loss during decoding, this will restore the boundaries and local features to the greatest extent possible. We test the model on three publicly available skin lesion datasets: PH2, ISIC-2016, and ISIC-2018. The results show that our model is superior to other previous methods, and the segmentation characteristics are more accurate representations of the actual lesion. © 2022, The Authors. All rights reserved.

关键词： Feature extraction

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Topic Embedded Representation Enhanced Variational Wasserstein Autoencoder for Text Modeling 5

Topic Embedded Representation Enhanced Variational Wasserste...

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5th IEEE International Conference on Electronics technology, ICET 2022

作者： Xiang, Zheng Liu, Xiaoming Yang, Guan Liu, Yang Zhongyuan University of Technology School of Computer Science Zhengzhou China Henan Key Laboratory on Public Opinion Intelligent Analysis Zhengzhou China Key Laboratory of text processing and image understanding Zhengzhou China Xidian University State Key Laboratory of Integrated Services Networks Xi'an China Shandong University Key Lab of Cryptologic Technology and Information Security Ministry of Education Xi'an China

ISBN: (纸本)9781665485081

Variational Autoencoder (VAE) is now popular in modeling and language generation tasks, which need to pay attention to the diversity of generation results. The existing models are insufficient in capturing the built-in relationships between topic representation and sequential words. At the same time, there is a massive contradiction between the commonly used simple Gaussian prior and the actual complex distribution of languages. To address the above problems, we introduce a hybrid Wasserstein Autoencoder (WAE) with Topic Embedded Representation (TER) for modeling. TER is obtained through an embedding-based topic model and can capture the dependencies and semantic similarities between topics and words. In this case, the learned latent variable has rich semantic knowledge with the help of TER and is easier to explain and control. Our experiments show that our method is competitive with other VAEs in modeling. © 2022 IEEE.

关键词： Semantics

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Multidirection Update-Based Multiobjective Particle Swarm Optimization for Mixed No-Idle Flow-Shop Scheduling Problem

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Complex System Modeling and Simulation 2021年第3期1卷 176-197页

作者： Wenqiang Zhang Wenlin Hou Chen Li Weidong Yang Mitsuo Gen the College of Information Science and Engineering Henan University of Technologyand also with Henan Key Laboratory of Grain Photoelectric Detection and ControlZhengzhou 450001China the Fuzzy Logic Systems Institute Fukuoka 820-0067Japanand also with Tokyo University of ScienceTokyo 162-8601Japan

The Mixed No-Idle Flow-shop Scheduling Problem(MNIFSP)is an extension of flow-shop scheduling,which has practical significance and application prospects in production *** improve the efficacy of solving the complicated multiobjective MNIFSP,a MultiDirection Update(MDU)based Multiobjective Particle Swarm Optimization(MDU-MoPSO)is proposed in this *** the biobjective optimization problem of the MNIFSP with minimization of makespan and total processing time,the MDU strategy divides particles into three subgroups according to a hybrid selection *** subgroup prefers one convergence *** subgroups are individually close to the two edge areas of the Pareto Front(PF)and serve two objectives,whereas the other one approaches the central area of the PF,preferring the two objectives at the same *** MDU-MoPSO adopts a job sequence representation method and an exchange sequence-based particle update operation,which can better reflect the characteristics of sequence differences among *** MDU-MoPSO updates the particle in multiple directions and interacts in each direction,which speeds up the convergence while maintaining a good distribution *** experimental results and comparison of six classical evolutionary algorithms for various benchmark problems demonstrate the effectiveness of the proposed algorithm.

关键词： multiobjective optimization Particle Swarm Optimization(PSO) Mixed No-Idle Flow-shop Scheduling Problem(MNLFSP) multidirection update

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A detection method for granary storage states based on a support vector machine and domain knowledge

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Acta Agriculturae Scandinavica, Section B — Soil & Plant Science 2021年第1期71卷 45-51页

作者： Dexian Zhang Cong Cheng Miao Zhang a College of Information Science and Engineering Henan University of Technology Zhengzhou People’s Republic of Chinab Key Laboratory of Grain Information Processing and Control Ministry of Education Henan University of Technology Zhengzhou People’s Republic of China

ABSTRACTFormulae display:?Mathematical formulae have been encoded as MathML and are displayed in this HTML version using MathJax in order to improve their display. Uncheck the box to turn MathJax off. This feature requires Javascript. Click on a formula to *** detection of granary storage states is an important technology to ensure national food security. In view of distribution characteristics of bottom pressure, this study theoretically explored a relationship between detected value of bottom pressure of granaries and granary storage states through the technologies, such as integrated learning and nonlinear regression. On this basis, this research built layout models of single-ring pressure sensors on the bottom of granaries and proposed a detection method for granary storage states based on domain knowledge of statistics of bottom pressure in granaries. The experiment demonstrates that the detection method for granary storage states based on a support vector machine (SVM) and domain knowledge shows high detection accuracy and low requirements for sensor performance and low detection cost. Therefore, it can meet the needs of remote online detection of granary storage states usually used.

关键词： Detection of granary storage state support vector machine domain knowledge detection accuracy food security

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Review of Outlier Detection Algorithms Based on grain Storage Temperature Data

Review of Outlier Detection Algorithms Based on Grain Storag...

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2020 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2020

作者： Liu, Tingfeng Gao, Hui Wu, Jianjun College of Information Science and Engineering Henan University of Technology Zhengzhou China Key Laboratory of Grain Information Processing and Control College of Information Science and Engineering Henan University of Technology Ministry of Education Zhengzhou China

ISBN: (纸本)9781728170046

Outliers may be objectively existing data generated by mechanisms different from most data, and have related laws and certain research value. Outliers have been widely used in recent years, including financial fraud, cyber fraud, and abnormal weather warnings. Traditional outlier detection algorithms such as statistical-based outlier detection, cluster-based outlier detection, deviation-based outlier detection, distance-based outlier detection, density-based outlier detection, etc., but there are many shortcomings in the traditional outlier detection algorithms. Outlier detection algorithms based on information entropy, outlier detection algorithms based on spectral clustering, etc. have gradually appeared. Because in practice, traditional outlier detection algorithms cannot perform good detection applications on high-dimensional data, spatial data, and time series data, so they are performed for high-dimensional outlier detection, space outlier detection, and time series outlier detection. Dedicated research. How to improve the effectiveness, scalability and space-time efficiency of the algorithm will be the future research direction. © 2020 IEEE.

关键词： Anomaly detection

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A QoE Evaluation and Adaptation Method for Multi-player Online Games 14th

A QoE Evaluation and Adaptation Method for Multi-player Onli...

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14th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2021

作者： Wang, Zaijian Guo, Wei Zhao, Le Yang, Weidong Mao, Shiwen Li, Zhipeng The School of Physics and Electronic Information Anhui Normal University Anhui Wuhu241002 China The Key Laboratory of Grain Information Processing and Control at Henan University of Technology Ministry of Education Henan Zhengzhou450001 China Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States Anhui Province Key Laboratory of Optoelectric Materials Science and Technology School of Physics and electronic information Anhui Normal University Wuhu241002 China

ISBN: (纸本)9783030898137

To evaluate the performance of multi-player online games (MPOGs) (e.g., the online Chinese poker game), this paper presents a novel Effective Quality of Experience (EQoE) concept that considers the interaction among multiple players. A novel QoE evaluation and adaptation method is proposed utilizing EQoE. Specifically, the proposed method assigns different weights to different players according to their roles in the multi-player online poker game. Some players with a lower weight are willing to reduce their own QoE to save network resources for players with a higher weight in order to keep the game going under poor network conditions. Our simulation study demonstrates the feasibility of the proposed QoE evaluation and adaptation method. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Quality control

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