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检索条件"任意字段=Scientific Conference on Mechatronics Engineering and Computer Science"

共 38171 条记录，以下是681-690 订阅

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Software Bug Prediction using Machine Learning 15

Software Bug Prediction using Machine Learning

引用

15th International conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Sathiyaraj, A. Angel, T.G. Ruby Turukmane, Anil V. Ramkumar, D. Guravaiah, Y. Department of Information Technology School of Computing Sathyabama Institute of Science and Technology Tamil Nadu Chennai600 119 India School of Computer Science and Engineering VIT-AP University Inavolu Andhra Pradesh Amaravati522237 India Department of Computer Science and Engineering MJR College of Engineering and Technology Diguvapokulavaripalli Pulicherla Andra Pradesh Chittoor District517214 India

ISBN: (纸本)9798331300579

The entire success of software is impacted by software bug prediction (SBP), a crucial part of the software development and maintenance life cycles. It is necessary to anticipate issues in order to increase the software's dependability, efficiency, and cost. In spite of the fact that a number of methods have been put out in the literature, it is difficult to create a reliable bug prediction model. In this paper, a machine learning (ML) based prediction method for software issues is introduced. Algorithms for guided machine learning that are based on historical data have been used to predict software errors. Two of the classifiers are Support Vector Machine and Naive Bayes (NB). How accurate and useful ML methods can be employed was demonstrated through the evaluation process. Included is the utilization of a comparative measure. © Grenze scientific Society, 2024.

关键词： Prediction models

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Research on the recognition system of visual arc welding 8

Research on the recognition system of visual arc welding

引用

8th IEEE Information Technology and mechatronics engineering conference, ITOEC 2025

作者： Zhang, Mingsheng Gu, Jianyu Li, Qiming Sun, Shiqi Liu, Yu Jiangsu Automation Research Institute Lianyungang222061 China North China Institute of Aerospace Engineering College of Materials Engineering Langfang China

ISBN: (纸本)9798331517915

At present, many domestic scholars and research institutions have studied the laser vision welding seam tracking system. By improving the control strategy of the robot and welding seam tracking system, the processing time is optimized and the real-time response of the welding seam tracking system is promoted. However, the practical application of the research results is not yet satisfactory. This paper carries out an experimental study of vision-based arc weld tracking. Its main content contains welding robot kine matics and control systems, weld image processing technology, right angle weld tracking technology, and so on. The research shows that the feature extraction of arc weld based on vision can be completed and arc weld recognition can be realized. It provides some reference for the application of laser vision welding seam tracking systems in industry. © 2025 IEEE.

关键词： Seam welding

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Research on Illustration Art Design Models Based on Operator-Optimized Genetic Algorithms 2

Research on Illustration Art Design Models Based on Operator...

引用

2nd IEEE International conference on Electrical, Automation and computer engineering, ICEACE 2024

作者： Wang, Bo Guangdong University of Science and Technology Dongguan523000 China

ISBN: (纸本)9798350368208

This paper addresses the challenges of low search efficiency and high complexity associated with standard genetic algorithms in illustration art design. We introduce a new model that integrates operator optimization and clustering-enhanced genetic algorithms. First, we dynamically modify the crossover and mutation probabilities during the genetic algorithm's execution based on population characteristics, which improves search ***, we incorporate the K-medoids algorithm to refine clustering within the genetic framework, utilizing a cost function to assess clustering quality and thereby reduce the algorithm's complexity. Finally, we apply our enhanced genetic algorithm to the design of random illustrations. Simulation results demonstrate that our proposed algorithm achieves higher levels of artistic quality and innovation in illustration art design. © 2024 IEEE.

关键词： Cost functions

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A Study on Short-Term Nowcasting Precipitation Forecasting Methods Based on Radar Echo Maps 8

A Study on Short-Term Nowcasting Precipitation Forecasting M...

引用

8th IEEE Information Technology and mechatronics engineering conference, ITOEC 2025

作者： Liu, Jie Wang, Xingchi G., Zhang Qinghai University Department of Computer Technology and Applications Xining China Qinghai University Qinghai Provincial Laboratory for Intelligent Computing and Application Xining China

ISBN: (纸本)9798331517915

Short-To-medium-term precipitation nowcasting aims to predict changes in mesoscale and microscale weather systems, particularly severe convective systems, within 0 to 2 hours. Compared to large-scale weather systems, mesoscale and microscale systems are characterized by their abruptness, complex mechanisms, and short life cycles, making short-term precipitation forecasting a highly challenging field. This study focuses on the Yinchuan region as a case study, processing radar echo data through dimensionality reduction, noise reduction, frame interpolation, and data augmentation to construct datasets suitable for training and testing. The IAM4VPx5 model is employed for forecasting and is compared against traditional spatiotemporal prediction models, including SimVP, ConvLSTM, and ConvGRU. Experimental results demonstrate that the IAM4VPx5 model outperforms SimVP, ConvLSTM, and ConvGRU across multiple metrics, such as Critical Success Index (CSI), Heidke Skill Score (HSS), and Probability of Detection (POD). Additionally, IAM4VPx5 exhibits superior performance in Mean Squared Error (MSE) and Root Mean Squared Error (RMSE). Overall, the IAM4VPx5 model demonstrates exceptional performance compared to SimVP, ConvLSTM, and ConvGRU in various aspects. These results validate the effectiveness and advantages of the IAM4VPx5 model in processing radar echo data, offering an efficient solution for weather radar forecasting. © 2025 IEEE.

关键词： Rain

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Mortality Prediction of Pulmonary Embolism Patients with Deep Learning and XGBoost 4

Mortality Prediction of Pulmonary Embolism Patients with Dee...

引用

4th International conference on Electrical, computer, Communications and mechatronics engineering, ICECCME 2024

作者： Tur, Yalcin Cicek, Vedat Cinar, Tufan Keles, Elif Allen, Bradley D. Savas, Hatice Durak, Gorkem Medetalibeyoglu, Alpay Bagci, Ulas Stanford University Department of Computer Science StanfordCA United States Northwestern University Department of Radiology ChicagoIL United States School of Medicine University of Maryland BaltimoreMD United States

ISBN: (纸本)9798350391183

Pulmonary Embolism (PE) is a serious cardiovascular condition that remains a leading cause of mortality and critical illness, underscoring the need for enhanced diagnostic strategies. Conventional clinical methods have limited success in predicting 30-day in-hospital mortality of PE patients. In this study, we present a new algorithm, called PEP-Net, for 30-day mortality prediction of PE patients based on the initial imaging data (CT) that opportunistically integrates a 3D Residual Network (3DResNet) with Extreme Gradient Boosting (XGBoost) algorithm with patient level binary labels without annotations of the emboli and its extent. Our proposed system offers a comprehensive prediction strategy by handling class imbalance problems, reducing overfitting via regularization, and reducing the prediction variance for more stable predictions. PEP-Net was tested in a cohort of 193 volumetric CT scans diagnosed with Acute PE, and it demonstrated a superior performance by significantly outperforming baseline models (76-78%) with an accuracy of 94.5% (±0.3) and 94.0% (±0.7) when the input image is either lung region (Lung-ROI) or heart region (Cardiac-ROI). Our results advance PE prognostics by using only initial imaging data, setting a new benchmark in the field. While purely deep learning models have become the go-To for many medical classification (diagnostic) tasks, combined ResNet and XGBoost models herein outperform sole deep learning models due to a potential reason for having lack of enough data. © 2024 IEEE.

关键词： Lung cancer

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Enterprise Intranet Threat Intelligence Processing Framework Based on Open Source Community 7

Enterprise Intranet Threat Intelligence Processing Framework...

引用

7th IEEE Information Technology and mechatronics engineering conference, ITOEC 2023

作者： Zeng, Wenjing Lu, Peng Wang, Hao Lou, Fang China Academy of Engineering Physics Institute of Computer Application Mianyang China

ISBN: (纸本)9798350334197

Network attack tactics, techniques, procedures, and IOC are being updated more and more rapidly. Defenders need to obtain such threat intelligence in a timely manner, to identify whether the enterprise intranet is under attack, and take corresponding protective measures. Before the official disclosure of the details of the attack, the open source community often already has users in the discussion of the attack, if we can extract threat intelligence that strong related to the enterprise from the open source community in a timely manner. It will be a great help in monitoring the enterprise intranet. However, new posts are published every day in the open source community, and some of the posts may have nothing to do with network security, and the threat intelligence disclosed in the posts may not be useful to the enterprise intranet. To bridge the gap, we propose EITIP, a framework for automated enterprise intranet threat intelligence processing. EITIP automatically collects new posts from open source community, classifies posts related to cyber security, obtains effective threat intelligence, and keep it updated. To address multiple challenges, EITIP provides: (1) effective threat entities, which can help obtain richer threat intelligence. (2) a method for obtaining strongly correlated threat intelligence on an enterprise intranet. (3) a complete threat intelligence processing framework. © 2023 IEEE.

关键词： Intranets

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Automatic Pricing And Replenishment Decision of Vegetable Products 8

Automatic Pricing And Replenishment Decision of Vegetable Pr...

引用

8th IEEE Information Technology and mechatronics engineering conference, ITOEC 2025

作者： Yang, Qin Wang, Yuqing Deng, Kaiying Deng, Jingwei Northwest Minzu University School of Mathematics and Computer Science Lanzhou China

ISBN: (纸本)9798331517915

In this paper, the 2023 China Higher Education Cup National College Students Mathematical Contest in Modeling is used as the theme to study the automatic pricing and replenishment decisions of vegetable products. Because the shelf life of vegetable products in fresh supermarkets is relatively short, and the quality will deteriorate with the increase of sales time, most vegetable varieties cannot be sold the next day if they are not sold on the same day. This requires a reasonable and efficient analysis and identification system, and builds a model based on the category of dishes sold, the sales volume, and the total sales, and generates automatic pricing and replenishment decisions. In this paper, linear regression, kendall consistency test, cost-plus pricing (P=c × (1+r)) method, and genetic algorithm are used to establish a mathematical model to obtain automatic pricing and replenishment decisions. © 2025 IEEE.

关键词： Sensitivity analysis

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The Feature Selection Strategy of Few-shot Learning Based on Causal Inference

The Feature Selection Strategy of Few-shot Learning Based on...

引用

2022 International conference on mechatronics engineering and Artificial Intelligence, MEAI 2022

作者： Zhang, Jining Zhu, Xiaodong Liu, Yuanning Software Engineering Jilin University Jilin Province Changchun132000 China Computer Science and Technology Jilin University Jilin Province Changchun132000 China

ISBN: (纸本)9781510663169

Statistical learning methods require large-scale data to make the significant generalized probability and observation error close to each other. Few-shot learning can alleviate this situation, but it cannot break through the limitations of statistical learning methods. The training model only depends on the correlation between data distributions. There may be potential risks in applying these models to decision-making in the natural environment. This paper studies feature selection in small sample regression analysis based on AutoMPG and MOP The performance of the two datasets on the regression task is first verified through three classical regression analysis models. Then, through the causal inference method, this paper analyzes the causal effect of the relationship between the features in the dataset and finds that two groups of features do not have a causal relationship. Finally, by setting up a simulation environment, this paper illustrates the potential risks of not considering the causal effect in feature selection. © 2023 SPIE.

关键词： Feature Selection

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Comparative Analysis of Decision Tree with Existing Approaches for Improving Prediction Performance 15

Comparative Analysis of Decision Tree with Existing Approach...

引用

15th International conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Pathan, Shabana Sharma, Sanjeev Kumar Department of Computer Science & Engineering Oriental University M.P Indore India Department of Computer Science and Engineering Oriental Institute of Science and Technology M.P Bhopal India

ISBN: (纸本)9798331300579

Data mining has applications for a wide range of enterprises, including those in the banking, telecommunications, energy, medical, marketing, and finance industries. The real-world situations involve noisy, unpredictable, ambiguous, and untrustworthy data, which further muddies the waters. During the information-gathering process, uncertainty arises in various application domains and is comprised of measurement errors, outdated information (data staleness), and repeated entries of the same type. This could lead to the prediction model performing poorly. The suggested method uses Deep Learning to control the uncertainty in the dataset before building Decision Tree models for categorization. This study compares two proposed approaches for decision tree optimization with the state-of-the-art approaches based on F1 score, accuracy, precision, recall, and evaluation parameters. © Grenze scientific Society, 2024.

关键词： Prediction models

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Detection of Ethereum Smart Contracts Vulnerabilities Over Blockchain

Detection of Ethereum Smart Contracts Vulnerabilities Over B...

引用

2023 International conference on Electrical, computer, Communications and mechatronics engineering, ICECCME 2023

作者： Prasad, Baddepaka Ramachandram, Sirandas Osmania University Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350322972

Smart contracts are a widely researched topic due to their crucial role in blockchain technology. Ethereum, one of the most popular blockchain platforms, utilizes Solidity code for creating secure and transparent transactions through smart contracts. Etherscan provides an extensive collection of Solidity code for Ethereum smart contracts. However, smart contract vulnerabilities can lead to significant financial losses for contract holders. To address this issue, a comprehensive dataset containing numerous defects was collected from etherscan and smartbug-wild. This paper is Proposed a Mathematical model to effectively detect and analyze all possible vulnerabilities with high accuracy, providing an efficient solution for improving smart contract security and ensuring the integrity and reliability of blockchain transactions. © 2023 IEEE.

关键词： Smart contract

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