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检索条件"主题词=software algorithms"

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A gaze prediction model based on Vision Transformer and VGG-16

A gaze prediction model based on Vision Transformer and VGG-...

引用

2025 2nd International Conference on algorithms, software Engineering and Network Security (ASENS)

作者： Yidong Hu Li Tong Ying Zeng Yuanlong Gao Bin Yan Zhongrui Li Henan Key Laboratory of Imaging and Intelligent Processing PLA Cyberspace Force Information Engineering University Zhengzhou China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

Currently, most saliency prediction models are stimulus-driven, and the regions they highlight are the salient areas from the machine vision. However, intelligent agents represented by humans can flexibly adjust their visual focus according to task requirements and only pay attention to task-related targets. Eye gaze information, as a concrete manifestation of human visual focus under specific task-driven conditions, can effectively improve the performance of models in corresponding tasks. In this paper, we integrate gaze information and propose a gaze prediction model based on Vision Transformer and VGG-16. This model is designed to predict the human gaze regions in the cross-view matching task from street-view images to aerial-view images. This model uses Vision Transformer to extract the low-level visual features of images and VGG-16 to extract the high-level semantic features of images respectively. It adopts a multi-level feature fusion strategy to strengthen feature representation. In addition, through gaze metric guidance and residual connections, task-related information is effectively introduced to optimize the model performance. Experimental results show that this model achieves competitive results on both self-constructed datasets and public datasets.

关键词： Visualization Computer vision Semantics software algorithms Predictive models Network security Feature extraction Transformers Prediction algorithms software engineering

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Multimodal Fusion for OSA Detection Using Deep Neural Networks

Multimodal Fusion for OSA Detection Using Deep Neural Networ...

引用

2025 2nd International Conference on algorithms, software Engineering and Network Security (ASENS)

作者： Ran Li Peng Zhang Jinru Cai Haojie Quan School of Artificial Intelligence Guangdong Mechanical and Electrical Polytechnic Guangzhou China Faculty of Humanities and Social Sciences Macao Polytechnic University China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

This paper proposes a multimodal recognition method based on snoring sounds and respiratory tract structural variation videos for the auxiliary diagnosis of Obstructive Sleep Apnea Syndrome (OSA). It is important to note that snoring alone is not a definitive indicator of OSA; it is merely one potential symptom that should be considered in conjunction with additional information for a more accurate diagnosis. By integrating data from these two modalities, the diagnostic accuracy and robustness are significantly enhanced. Experimental results demonstrate that the proposed method outperforms single-modality approaches in key performance metrics, including accuracy and recall. This study provides a novel and effective solution for the diagnosis of OSA, offering new insights into the development of advanced diagnostic tools for sleep-related breathing disorders.

关键词： Deep learning Accuracy Soft sensors software algorithms Refining Network security Sleep apnea Robustness Videos software engineering

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OSS License Identification at Scale: A Comprehensive Dataset Using World of Code

OSS License Identification at Scale: A Comprehensive Dataset...

引用

International Mining software Repositories, MSR

作者： Mahmoud Jahanshahi David Reid Adam McDaniel Audris Mockus Department of Electrical Engineering and Computer Science University of Tennessee Knoxville USA

ISBN: (数字)9798331501839

ISBN: (纸本)9798331501846

The proliferation of open source software (OSS) and different types of reuse has made it incredibly difficult to perform an essential legal and compliance task of accurate license identification within the software supply chain. This study presents a reusable and comprehensive dataset of OSS licenses, created using the World of Code (WoC) infrastructure. By scanning all files containing “license” in their file paths, and applying the approximate matching via winnowing algorithm to identify the most similar license from the SPDX and Open Source list, we found and identified 5.5 million distinct license blobs in OSS projects. The dataset includes a detailed project-to-license (P2L) map with commit timestamps, enabling dynamic analysis of license adoption and changes over time. To verify the accuracy of the dataset we use stratified sampling and manual review, achieving a final accuracy of 92.08%, with precision of 87.14%, recall of 95.45%, and an F1 score of 91.11%. This dataset is intended to support a range of research and practical tasks, including the detection of license noncompliance, the investigations of license changes, study of licensing trends, and the development of compliance tools. The dataset is open, providing a valuable resource for developers, researchers, and legal professionals in the OSS community.

关键词： Codes Accuracy Law Reviews Supply chains software algorithms Manuals Licenses Market research Open source software

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Network traffic classification algorithm based on improved ACO-SVR

Network traffic classification algorithm based on improved A...

引用

2025 2nd International Conference on algorithms, software Engineering and Network Security (ASENS)

作者： Yeting Hu Peng Xiong School of Electronic Information Shanghai Dianji University China Kaiserslautern School of Intelligent Manufacturing Shanghai Dianji University China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

This study proposes an improved ACO-SVR algorithm for network traffic classification. The improved ACO algorithm is used to optimize the parameters of SVR model. ACO algorithm dynamically adjusts the parameter search range according to the number of iterations to improve the search accuracy and convergence speed. The heuristic information algorithm is based on the correlation calculation between features and target variables to guide ant search. Experimental results show that this method has significant advantages for classification accuracy and efficiency.

关键词： Support vector machines Resistance Accuracy Heuristic algorithms software algorithms Telecommunication traffic Robustness Classification algorithms Standards software engineering

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Smart Voice Signature: A Machine Learning Approach to Speaker Identification

Smart Voice Signature: A Machine Learning Approach to Speake...

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International Conference on Computer and Communications Technologies (ICCCT)

作者： Shafiul Islam Mazumder Md Tanzid Mollah Labiba Tahia Tawsif Mustasin Rafin Nafiun Al Amin N M SaifKabir Fahim Islam Farhan Md Tanvir Chowdhury Department of Computer Science and Engineering American International University Dhaka Bangladesh Department of Computer Science and Technology Algoma University Brampton Canada Department of Electrical and Electronic Engineering BRAC University Dhaka Bangladesh Department of Computer Science and Engineering BRAC University Dhaka Bangladesh Department of Computer Science and Engineering East West University Dhaka Bangladesh

ISBN: (数字)9798331537579

ISBN: (纸本)9798331537586

Speaker identification is recognizing individuals based on their unique vocal characteristics. This paper explores the enhancement of speaker identification systems through machine learning techniques, focusing on Mel-Frequency Cepstral Coefficients (MFCC) for feature extraction and the application of K-Nearest Neighbors (K-NN) and Decision Tree algorithms using the ‘Weka’ software tool. This study aims to develop a robust system valuable in forensic science, security, and other areas where verifying an individual's claimed identity based on their voice is crucial. By leveraging these sophisticated algorithms, the system enhances the accuracy and efficiency of voice-based identity verification. This research seeks to improve the precision of speaker recognition. It aims to enhance the visualization tools that aid in analyzing voice data, thus facilitating a more intuitive understanding of the results. This integration of advanced machine learning techniques with practical visualization enhancements is expected to broaden the applicability of speaker identification technologies, making them more effective in diverse real-world environments where quick and reliable identification is needed. Through this study, the system is anticipated to contribute significantly to security and forensic analysis, providing a dependable method for identity confirmation in various applications.

关键词： Technological innovation Machine learning algorithms Accuracy Forensics software algorithms Data visualization Machine learning Transforms Tagging Reliability

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Artificial Intelligence-Based Solar Power Generation Prediction and Analysis

Artificial Intelligence-Based Solar Power Generation Predict...

引用

Sustainable Energy Technologies and Computational Intelligence (SETCOM), International Conference on

作者： Niraj H. Patel Prakruti Shah Siddharth Joshi Electrical and Electronics Engineering Department Navrachana University Vadodara India Electrical Engineering Department Pandit Deendayal Energy University Gandhinagar India

ISBN: (数字)9798331520540

ISBN: (纸本)9798331520557

Integration of renewable energy sources with the conventional grid is the key way to sustain the world with the limited conventional sources and also open the door to the green energy system. Solar, wind, hydro and many more are the renewable energy sources connected with the grid; however, its optimization is one of the crucial aspects as the input to these sources is variable and intermittent in nature. This paper deals with the prediction of solar power plant located at Ahmedabad. The simulation work has been carried out with System Advisor Model (SAM) software. Various parameters like temperature, solar irradiance and generated output power have been analysed through this study. Various Artificial Intelligence (AI) algorithms, Linear regression (LR) model, artificial neural network (ANN) model, support vector machines (SVM) model, random forest (RF) model, gradient boosting (GB) models has been simulated, analysed and compared in results w.r.t the root means square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and correlation coefficient (CC) and fond that for small amount of the power plant data provided here, ANN and SVM fits best as they provide 1 to 10 % error as compared to rest of all errors. CC gives result 1 except SVM algorithm and LR model provides linear relations.

关键词： Support vector machines Analytical models software algorithms Linear regression Artificial neural networks Predictive models Prediction algorithms Boosting Data models Root mean square

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Research and Application of Personalized Recommendation Algorithm Based on Deep Learning Network

Research and Application of Personalized Recommendation Algo...

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2025 2nd International Conference on algorithms, software Engineering and Network Security (ASENS)

作者： Zhigang Zhu City Institute Dalian University of Technology Dalian China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

In today's digital age, information technology has made great progress, which has promoted the explosive growth of global data volume, and the problem of information overload has become increasingly serious. Faced with massive data information, users rely heavily on personalized recommendation algorithms to screen out the content that really meets their interests and needs. However, the traditional personalized recommendation algorithm needs to build user portraits with a large number of user behavior data, so that there are obvious shortcomings in dealing with data sparseness, cold start and other issues, which further affects the accuracy of the recommendation effect. In this regard, based on the actual needs, this paper will deeply explore the application feasibility of artificial intelligence and artificial neural network in this field, and propose a brand-new personalized recommendation algorithm model combined with deep learning network to solve the challenges faced by traditional recommendation algorithms. Practice has proved that the personalized recommendation model refers to CNN-LSTM to process diverse original information to obtain rich semantic features, and at the same time, it uses attention mechanism to obtain the attention vectors of users and projects. The user and project feature vectors generated by the combination of the two effectively improve the overall expressive ability of the model, which is beneficial to capture the interactive information between features and improve the accuracy of recommendation results.

关键词： Deep learning Accuracy Attention mechanisms software algorithms Semantics Prediction algorithms Vectors Classification algorithms Convolutional neural networks Artificial intelligence

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Research on image encryption algorithm based on hyper chaotic Lorenz system and wavelet transform

Research on image encryption algorithm based on hyper chaoti...

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2025 2nd International Conference on algorithms, software Engineering and Network Security (ASENS)

作者： Zhaojun Han Yujie Zhang Wenru Wang Zhenqi Wen Xubin Ma Zihao Li Xuebin Ren Yuheng Lu School of Information Science and Engineering Dalian Polytechnic University Dalian China Department of Basic Education Dalian Polytechnic University Dalian China Dalian Gongxingda Information Technology Co. Ltd. Dalian China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

In this paper, a color image encryption algorithm based on hyper chaotic Lorenz system and discrete wavelet transform is proposed. The algorithm generates a chaotic sequence using a four-dimensional hyper chaotic Lorenz system and encrypts the image by combining with a two-dimensional Haar wavelet transform. The randomness and security of the image are effectively enhanced by wavelet decomposition, chaotic sequence encryption and bitwise dissimilarity operation. The experimental results show that the encrypted image has a uniform histogram, the information entropy is close to the ideal value of 8, and the correlation of adjacent pixels is significantly reduced, which can effectively resist the information entropy attack and correlation analysis attack. The algorithm performs well in terms of security, randomness and efficiency, and provides a reliable solution for the secure storage and transmission of image data.

关键词： Correlation Statistical analysis software algorithms Resists Encryption Discrete wavelet transforms software reliability Information entropy Secure storage software engineering

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Design of Fault Diagnosis System for Wind Power Gearbox Based on Labview

Design of Fault Diagnosis System for Wind Power Gearbox Base...

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Advanced algorithms and Control Engineering (ICAACE), International Conference on

作者： Shili Yang Yan Lu School of Electrical Engineering Shanghai DianJi University Shanghai China

ISBN: (数字)9798331535087

ISBN: (纸本)9798331535094

Given the continuous growth of wind power generation, the reliability and stability of wind turbine gearboxes have become pivotal areas of research. Due to the inclement climatic conditions and the challenges associated with maintenance, wind turbine gearboxes are susceptible to failures, which in turn impacts the overall operational efficiency of the turbines. This paper proposes a gearbox fault diagnosis system, which is designed using Labview software. Initially, a comprehensive analysis of the gearbox's critical components is conducted, encompassing gears, rotors, and rolling bearings. The paper then goes on to implement the fault simulation and diagnosis functions of the gearbox using Labview software, together with a series of effective software development strategies. The experimental results demonstrate the system's capacity to accurately simulate the actual operating conditions of the gearbox under various fault conditions and to successfully diagnose the types of faults that occur. This diagnosis system enhances the accuracy of fault detection and provides reliable data support for the maintenance of wind turbine gearboxes. Furthermore, the system's flexibility and scalability ensure its adaptability to the future diagnosis of a broader range of faults, providing valuable references for enhancing safety and efficiency in the wind power industry.

关键词： Fault diagnosis Vibrations Scalability software algorithms Wind power generation software Real-time systems Wind turbines Maintenance Monitoring

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Porting C++containers based on domestic heterogeneous platforms

Porting C++containers based on domestic heterogeneous platfo...

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Computer Applications and Information Technology (ISCAIT), International Symposium on

作者： Xueyuan Li Guangyu Ding Mengzhi Han Unit: Zhengzhou University Zhengzhou China Unit:Shuguang Information Industry (Beijing) Co. Ltd Beijing China

ISBN: (数字)9798331542856

ISBN: (纸本)9798331542863

With the development of the times, the demand for high-performance computing power is also increasing, and heterogeneous computing collaborative parallel computing has become an important development direction of computing technology. In recent years, domestic heterogeneous platforms have flourished, and it is of great significance to transplant and develop suitable algorithms and software for the architecture of domestic heterogeneous platforms. The C++Standard Template Library (STL) is an important component of the C++programming language, providing a series of universal and reusable template classes and functions that can help developers better develop software. In terms of STL heterogeneous porting, the progress of domestic heterogeneous platforms lags far behind NVIDIA, which hinders the development of heterogeneous computing in China. Therefore, this article migrates commonly used containers in STL to broaden the adaptation range of domestic heterogeneous software. By porting several iconic containers, a solution for container heterogeneous porting is proposed, providing a reference method for STL heterogeneous porting. The final experiment showed that compared to non heterogeneous operations, this scheme significantly improves the performance of heterogeneous porting of containers in large data volumes. At the same time, it also has a huge improvement in the performance of internal operation functions of containers compared to the original STL parallel operation method.

关键词： software algorithms Containers Parallel processing Writing Libraries software Heterogeneous networks Organ transplantation Information technology Standards

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