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Methodology Metadata-driven Knowledge Production Charac-teristics Identification by Knowledge Retrieval and Mining 7

Methodology Metadata-driven Knowledge Production Charac-teri...

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7th international conference on Data Science and Information Technology, DSIT 2024

作者： Xu, Hao Ge, Linlin Zhang, Yan Jin, Zhenqiang Wang, Mulan Feng, Ke Kang, Zhenyuan Nanjing Institute of Technology School of Management Engineering Nanjing China Nanjing University School of Information Management Nanjing China Nanjing Institute of Technology School of Electrical Power Engineering Shen Guorong College Nanjing China Jiangsu Power Transmission & Transformation Co. Ltd Nanjing China

ISBN: (纸本)9798350384093

the progress of science, technology, and innovation is greatly aided by the advancement, improvement, and use of methodology. Our work developed a Characteristic Recognition Algorithm based on text mining to extract methodology metadata from full-text documents and identify characteristics that are methodologically driven by time trend, dissemination speed, and co-drive. A sample of 5564 publications from the economic and management (E&M) discipline were chosen, from which 9,995 methodological metadata were extracted and classified into 4 categories: model, software & tool (S&T), data, and method & theory (M&T). the co-occurrence trait was revealed using the social network approach. Results indicate that over the past 20 years, the methodology's usage rate has increased, reaching 78.49% in 2019 alone. While S&T, model, and data have slowed down, M&T has the highest usage rate, which is reflected in a continually rising diffusion feature. the outcomes of knowledge creation in E&M exhibit the features of multi-methodology that is frequently driven, including M&T (hypotheses, questionnaire surveys), data (China Statistical Yearbook, wind, and CSMAR), model (double difference and logit), and S&T (SPSS, Amos, LISREL). the process of defining characteristics of approach metadata-driven knowledge production will be applied to different areas as a preliminary investigation, as well as used as training material for the automatic extraction of large-scale corpora. © 2024 IEEE.

关键词： Intelligent Computing Knowledge Production Characteristics Knowledge Retrieval and Mining Methodology driven Social Network Analysis

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Domain-driven Architecture modeling and Rapid Prototyping with Context Mapper 8th

Domain-Driven Architecture Modeling and Rapid Prototyping wi...

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8th international conference on model-driven engineering and software development (modelsward)

作者： Kapferer, Stefan Zimmermann, Olaf Univ Appl Sci Eastern Switzerland OST Oberseestr 10 CH-8640 Rapperswil Switzerland

ISBN: (纸本)9783030674441;9783030674458

Strategic Domain-driven Design (DDD) has become an established practice for system decomposition and service identification in recent years. the trend towards microservices increased the popularity of DDD patterns such as Subdomain, Bounded Context, Aggregate and Context Map. In our previous work, we presented a Domain-Specific Language (DSL) providing a clear and concise interpretation of the DDD patterns and their combinations. As a machine-readable description of DDD, the DSL establishes a foundation for systematic service decomposition and DDD-based architecture descriptions that can be refactored and refined by model transformations. the DSL and supporting tools are implemented in the open source project Context Mapper. In this extended version of our previous paper we enhance the DSL grammar to allow domain-driven designers to prototype applications rapidly: they can specify user stories and/or use cases in the DSL, and model transformations can then derive Subdomains and Bounded Contexts automatically. the Context Mapper tool chain supports the continuous, iterative specification and evolution of Context Maps and other service design artifacts. Our validation activities included prototyping, action research, and case studies. this paper illustrates such a transformation chain on the basis of one of our case studies.

关键词： Domain-driven design Domain-specific language Microservices model-driven software engineering Service-oriented architecture

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Reduction of the Rate of Defective Products in A Metalworking Company, through the Implementation of TPM, 5S And Process Standardization Tools 23

Reduction of the Rate of Defective Products in A Metalworkin...

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9th international conference on Industrial and Business engineering, ICIBE 2023

作者： Yalico-Luciano, Ronald Herrada-Gálvez, Jesus Castro-Rangel, Percy Peruvian University of Applied Sciences Peru

ISBN: (纸本)9798400708824

Currently in Peru, there are metal-mechanic companies that present deficiencies and problems in their production processes. One of these problems is the high rate of defective products, since most of them exceed the average percentage (1.60%) of defective products in total production. To all this, a company was selected for the investigation of a case study, where it was possible to identify that it presented problems with respect to the rates of defective products since, between the months between the years 2021 and 2022, the average percentage of defective products amounted to 9.91%. this problem generated an economic impact of $35,000.00, causing a considerable decrease in the company's profits. For this reason, in this investigation a continuous improvement model (PDCA) was carried out, applying 5S tools, Process Standardization, Autonomous Maintenance and Planned Maintenance, to reduce the high rate of defective products. For the development and validation of the model proposed in the case study, a pilot test and a simulation were carried out in the Arena software, obtaining as a result a reduction in the rate of defective products from 9.91% to 2.43%, an increase in the level of compliance of 5S from 48% to 76%, a decrease in standard time from 135.17 min to 95.45 min, and an increase in OEE from 53.0% to 69.30%. © 2023 ACM.

关键词： software testing

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A Novel Family of Queuing Network models for Self-adaptive Systems 8th

A Novel Family of Queuing Network Models for Self-adaptive S...

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8th international conference on model-driven engineering and software development (modelsward)

作者： Arcelli, Davide Univ Laquila Dept Informat Engn Comp Sci & Math Via Vetoio 1 I-67100 Laquila Italy

A Self-adaptive System (SaS) consists of an autonomic manager which is able to adapt the system9;s behavior by operating on a managed sub-system that perceives and affects the environment through its sensors and ac... 详细信息

ISBN: (纸本)9783030674441;9783030674458

A Self-adaptive System (SaS) consists of an autonomic manager which is able to adapt the system's behavior by operating on a managed sub-system that perceives and affects the environment through its sensors and actuators, respectively. Self-adaptation may occur at different levels, devising a number of knobs that the autonomic manager can properly regulate in order to produce actuation in response to environment sensing. this paper is an extension of our previous work introducing a generalized QN model that allows performance modeling and assessment of SaSs. We here extend previous work by defining modeling patterns and controller selection policies to conform to during the instantiation of the generalized model, resulting into a novel family of QN models aimed at representing the different parts of the system and the dynamics occurring over and among them. A controlled experiment addressing a realistic SaS for emergency handling shows that, by adhering to the defined patterns and controller selection policies, QN models behave as expected, and that the latter can be immersed into a performance optimization context that opens to the development of automated solutions to support the identification of efficient system configurations.

关键词： Self-adaptive systems software architecture modeling patterns Performance Queuing networks SMAPEA QNs

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A Multi-model Reviewing Approach for Production Systems engineering models 8th

A Multi-Model Reviewing Approach for Production Systems Engi...

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8th international conference on model-driven engineering and software development (modelsward)

作者： Rinker, Felix Waltersdorfer, Laura Schueller, Manuel Biffl, Stefan Winkler, Dietmar Tech Univ Wien Christian Doppler Lab Secur & Qual Improvement Pr Vienna Austria Tech Univ Wien Inst Informat Syst Engn Vienna Austria

ISBN: (纸本)9783030674441;9783030674458

Background. In Production Systems engineering (PSE) models, which describe plants, represent different views on several engineering disciplines (such as mechanical, electrical and software engineering) and may contain up to 10,000s of instance elements, such as concepts, attributes and relationships. Validating these models requires an integrated multi-model view and the domain expertise of human experts related to individual views. Unfortunately, the heterogeneity of disciplines, tools, and data formats makes it hard to provide a technology-independent multi-model view. Aim. In this paper, we aim at improving Multi-model Reviewing (MMR) capabilities of domain experts based on selected model visualisation methods and mechanisms. Method. We (a) derive requirements for graph-based visualisation to facilitate reviewing multi-disciplinary models;(b) introduce the MMR approach to visualise engineering models for review as hierarchical and linked structures;(c) design an MMR software prototype;and (d) evaluate the prototype based on tasks derived from real-world PSE use cases. For evaluation purposes we compare capabilities of the MMR prototype and a text-based model editor. Results. the MMR prototype enabled performing the evaluation tasks in most cases considerable faster than the standard text-based model editor. Conclusion. the promising results of the MMR approach in the evaluation context warrant empirical studies with a wider range of domain experts and use cases on the usability and usefulness of the MMR approach in practice.

关键词： Multi-disciplinary engineering visualisation Production systems engineering model-driven engineering Domain-specific modeling model review model quality assurance

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Anti-DDoS Attacks Strategy of SDN Data Plane with Data Augmentation Based on P4 25

Anti-DDoS Attacks Strategy of SDN Data Plane with Data Augme...

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25th IEEE international conferences on High Performance Computing and Communications, 9th international conference on Data Science and Systems, 21st IEEE international conference on Smart City and 9th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Zhang, Wenxiu Jing, Shan Zhao, Chuan School of Information Science and Engineering University of Jinan Jinan China Quan Cheng Laboratory Jinan China

ISBN: (纸本)9798350330014

As software Defined Networking (SDN) becomes increasingly prevalent, the risk of Distributed Denial of Service (DDoS) attacks targeting SDN also grows. Specifically, the SDN data plane, consisting of simple forwarding devices, is more susceptible to DDoS attacks launched by malicious actors. these attacks can impose tremendous load on the SDN, potentially leading to its complete collapse in severe cases. the traditional SDN architecture based on the OpenFlow Protocol falls short in meeting the requirements for programming the data plane. To address this challenge and improve the flexibility of SDN architectures, the Programming Protocol-Independent Packet Processors (P4) has emerged. However, existing solutions, primarily based on Statistical Learning, Machine Learning, and Deep Learning, require further enhancement in terms of accuracy, complexity, and latency. In this study, we utilize the P4 language to implement a programmable data plane and propose the P4-CACNN model for detecting and defending against DDoS attacks on the data plane. Firstly, we employ an appropriate attention mechanism to enhance the processing of incoming traffic. Subsequently, the data is fed into a discriminator consisting of a Convolutional Neural Network (CNN) to classify whether it constitutes attack traffic. Experimental results demonstrate that our proposed model achieves a remarkable 98.99% accuracy in detecting DDoS attacks on the SDN data plane, while maintaining low latency. © 2023 IEEE.

关键词： Denial-of-service attack

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the Smart Grid Simulation Framework: model-driven engineering Applied to Cyber-Physical Systems 8th

The Smart Grid Simulation Framework: Model-Driven Engineerin...

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8th international conference on model-driven engineering and software development (modelsward)

作者： Oudart, David Cantenot, Jerome Boulanger, Frederic Chabridon, Sophie Inst Polytech Paris SAMOVAR Telecom SudParis Paris France EDF R&D Palaiseau France Univ Paris Saclay CNRS Cent Supelec LRI Paris France

ISBN: (纸本)9783030674441;9783030674458

Smart grids are complex systems for which simulation offers a practical way to evaluate and compare multiple solutions before deployment. However, the simulation of a Smart Grid requires the development of heterogeneous models corresponding to electrical, information processing, and telecommunication behaviors. these heterogeneous models must be linked and analyzed together in order to detect the influences on one another and identify emerging behaviors. We apply model-driven engineering to such cyber-physical systems combining physical and digital components and propose SGridSF, the Smart Grid Simulation Framework, which automates tasks in order to ensure consistency between different simulation models. this framework consists mainly of a domain specific language for modeling a cosimulation unit, called CosiML for Cosimulation modeling Language, a domain specific language for modeling the functional architecture of a Smart Grid, called SGridML for Smart Grid modeling Language, and a tool implementing different transformation rules to generate the files and scripts for executing a cosimulation. Finally, we illustrate the use of SGridSF on the real use case of an islanded grid implementing diesel and renewable sources, battery storage and intelligent control of the production. We show the sequencing of automatic generation tasks that minimizes the effort and the risk of error at each iteration of the process.

关键词： Cosimulation FMI IT MDE Smart grid Cyber-physical system

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CopyFormer: A Transformer Text Generation model combined with Pointer Network 23

CopyFormer: A Transformer Text Generation model combined wit...

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9th international conference on Computing and Artificial Intelligence, ICCAI 2023

作者： Ma, Xingyu Lu, Songfeng Liu, Hu Zhou, Xianjing Feng, Bingyan School of Software & Engineering Huazhong university of Science and Technology Wuhan430074 China School of Cyber Science & Engineering Huazhong university of Science and Technology Wuhan430074 China Shenzhen Huazhong University Science and Technology Research Institute Shenzhen518057 China Wuhan Zhuoer Information Technology Co. Ltd Wuhan430040 China

ISBN: (纸本)9781450399029

Industrial Internet Research Institute Wuhan Huazhong Numerical Control Co., ***, 430074, China In the Pointer Generation Network, the model uses the attention mechanism in Seq2Seq [1]to selectively point to the text that needs to be copied, thus effectively alleviating the problem of out of vocabulary (OOV). However, Seq2Seq has some defects, so Google proposed a new Encoder-Decoder architecture Transformer [2], to replace the traditional Seq2Seq. this paper proposes a Pointer Generation Network model based on Transformer, which can effectively improve the generation ability of the model by using the powerful model of Transformer combined with Pointer Generation Network. In addition, considering that the Pointer Generation Network does not effectively use the relevant information in the input sequence, this paper selectively combines the information in the input sequence to the Decoder, so as to improve the effect of the model. Finally, experiments on Similar Text Generation tasks verify the effectiveness of the method. © 2023 Copyright held by the owner/author(s).

关键词： Decoding

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Regression in Estimation of software Attributes: A Systematic Literature Review 9

Regression in Estimation of Software Attributes: A Systemati...

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9th international conference in software engineering Research and Innovation (CONISOFT)

作者： Gonzalez-Hernandez, Saarayim Sanchez-Garcia, Angel J. Cortes-Verdin, Karen Carlos Perez-Arriaga, Juan Univ Veracruzana Fac Estadist & Informat Xalapa Veracruz Mexico

ISBN: (纸本)9781665443616

software estimation is a fundamental activity in the software development process, since it is possible to predict the number of defects, size, effort, among other attributes. With this, it is possible to improve the quality of the product and process. To predict quantitative values, it is common to use Regression model mechanisms, although each model adjusts to a specific behavior of the data. In this work, a Systematic Literature Review is carried out based on the Kitchenham and Charters guide, to know the different types of Regression that have been used in the software estimates. In addition, it seeks to know those attributes that are estimated and those that function as independent variables. Simple Linear Regression, Multiple Linear Regression and Logistic Regression were the most used, although other types of regression were found that can be further explored. Finally, the attributes that work as predictor variables were categorized, where the attributes of effort, lines of code and use cases were the most frequent.

关键词： Regression software estimation Systematic Literature Review

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Classification Algorithms for software Defect Prediction: A Systematic Literature Review 9

Classification Algorithms for Software Defect Prediction: A ...

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9th international conference in software engineering Research and Innovation (CONISOFT)

作者： Jose Hernandez-Molinos, Ma Sanchez-Garcia, Angel J. Erandi Barrientos-Martinez, R. Univ Veracruzana Fac Estadist & Informat Xalapa Veracruz Mexico Univ Veracruzana Inst Invest Inteligencia Artificial Xalapa Veracruz Mexico

ISBN: (纸本)9781665443616

Within software engineering, it is essential to build quality software. An obstacle to the after mentioned are the defects that can be found in any phase of software development. that is why the area of software defect prediction emerged, in which different algorithms have already been evaluated, studied, and proposed. the objective of this paper is to carry out a Systematic Literature Review, to know which are the classification algorithms that help to predict software defects. In the same way, it is intended to know the features, metrics and what has been the precision of the classification algorithms for software defect prediction. this paper shows that the most widely used classifiers to predict defects are Naive Bayes and Random Forest, while those that show the best results are Naive Bayes and Boosting. Finally, it is highlighted that Precision and Recall are the most used metrics for model validation.

关键词： software defect prediction classifier metrics precision

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