Pub Date : 2024-02-01DOI: 10.53106/199115992024023501002
Zhi Tan Zhi Tan, Zi-Hao Xu Zhi Tan
The key to solve the problem of fine-grained image classification is to find the differentiation regions related to fine-grained features. In this paper, we try to add new network components to the original network and adjust various parameters to try to propose a new fine-grained image classification network. We propose a fine-grained image classification network based on the fusion of asymmetric convolution, convolution and self-attention mechanisms. Firstly, an enhanced module using asymmetric convolution to assist classical convolution proposed to help convolution learn deep features. Secondly, according to the common points of convolution and self-attention mechanism, we invented a fusion module of convolution and self-attention mechanism to improve the learning ability of the network.We integrate these two modules into the residual network and invent a new residual network .Finally, according to the experience, we design a new downsampling layer to adapt to the new component of the attention mechanism and improve the performance of the model. The experiment test on three publicly available datasets, and three methods for comparison. The results show that the new structure can effectively complete the task of fine-grained image classification, and the classification accuracy of different methods and different datasets are significantly improved.
{"title":"ACANet: A Fine-grained Image Classification Optimization Method Based on Convolution and Attention Fusion","authors":"Zhi Tan Zhi Tan, Zi-Hao Xu Zhi Tan","doi":"10.53106/199115992024023501002","DOIUrl":"https://doi.org/10.53106/199115992024023501002","url":null,"abstract":"\u0000 The key to solve the problem of fine-grained image classification is to find the differentiation regions related to fine-grained features. In this paper, we try to add new network components to the original network and adjust various parameters to try to propose a new fine-grained image classification network. We propose a fine-grained image classification network based on the fusion of asymmetric convolution, convolution and self-attention mechanisms. Firstly, an enhanced module using asymmetric convolution to assist classical convolution proposed to help convolution learn deep features. Secondly, according to the common points of convolution and self-attention mechanism, we invented a fusion module of convolution and self-attention mechanism to improve the learning ability of the network.We integrate these two modules into the residual network and invent a new residual network .Finally, according to the experience, we design a new downsampling layer to adapt to the new component of the attention mechanism and improve the performance of the model. The experiment test on three publicly available datasets, and three methods for comparison. The results show that the new structure can effectively complete the task of fine-grained image classification, and the classification accuracy of different methods and different datasets are significantly improved.\u0000 \u0000","PeriodicalId":345067,"journal":{"name":"電腦學刊","volume":"266 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140463055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper introduces a secure and robust zero-watermarking framework that leverages the advantages of zero-watermarking, ensuring non-destructive modification of original images and unlimited capacity. The proposed method enables robust watermark embedding while preserving the original image. It employs a novel feature extraction approach using circular areas based on image radius, enhancing feature resilience. Additionally, applying one-dimensional non-recursive discrete periodized wavelet transform (1-D NRDPWT) converts feature values into phi, contributing to enhanced stability and robustness. Enhanced security is achieved through the use of Shuffle and Pseudo-Random Number Generator (PRNG). Experimental results, evaluated using metrics such as Bit Error Rate (BER) and Normalized Correlation (NC), validate the exceptional performance of this watermarking technique. These findings underscore the framework’s robustness, security, reliability, and integrity against both general and geometric noise attacks, making it a secure and robust solution for modern digital image copyright protection. In summary, our method offers an effective defense against various noise attacks while ensuring the highest watermark quality without compromising the original image. It is a significant advancement in copyright protection applications.
{"title":"Robust Zero-Watermarking by Circular Features and 1-D NRDPWT Transformation","authors":"Hsiu-Chi Tseng Hsiu-Chi Tseng, King-Chu Hung Hsiu-Chi Tseng","doi":"10.53106/199115992024023501008","DOIUrl":"https://doi.org/10.53106/199115992024023501008","url":null,"abstract":"\u0000 This paper introduces a secure and robust zero-watermarking framework that leverages the advantages of zero-watermarking, ensuring non-destructive modification of original images and unlimited capacity. The proposed method enables robust watermark embedding while preserving the original image. It employs a novel feature extraction approach using circular areas based on image radius, enhancing feature resilience. Additionally, applying one-dimensional non-recursive discrete periodized wavelet transform (1-D NRDPWT) converts feature values into phi, contributing to enhanced stability and robustness. Enhanced security is achieved through the use of Shuffle and Pseudo-Random Number Generator (PRNG). Experimental results, evaluated using metrics such as Bit Error Rate (BER) and Normalized Correlation (NC), validate the exceptional performance of this watermarking technique. These findings underscore the framework’s robustness, security, reliability, and integrity against both general and geometric noise attacks, making it a secure and robust solution for modern digital image copyright protection. In summary, our method offers an effective defense against various noise attacks while ensuring the highest watermark quality without compromising the original image. It is a significant advancement in copyright protection applications.\u0000 \u0000","PeriodicalId":345067,"journal":{"name":"電腦學刊","volume":"93 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140469294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.53106/199115992024023501003
Yu Sun Yu Sun, Chen-Wei Feng Yu Sun, Xian-Ling Wang Chen-Wei Feng, Jiang-Nan Yuan Xian-Ling Wang, Lin Zhang Jiang-Nan Yuan
The expansion of 5G and Internet of Things has laid a good foundation for the in-depth research of Internet of vehicles. Low frequency resources are scarce, and Internet of vehicles communication requires extremely high communication rate. Millimeter wave can meet the above two requirements, but its characteristics and the complicated communication conditions of Internet of vehicles make it difficult to combine the two. Overcoming these problems and making beam tracking accurate and steady is a major challenge at present. In this paper, a new extended Kalman filter tracking algorithm is proposed for mmWave V2I scenarios. On the basis of the original algorithm, a threshold prediction update mechanism is added. A new scheme is adopted, which takes position and velocity as tracking variables, and the tracking model is derived for the first time in MIMO 3D scenarios based on this scheme. The model considers the three-dimensional road conditions, including the vehicle deflection motion and the millimeter wave link blocked by large vehicles, which is more suitable for practical application scenarios. The simulation results reveal that the position and velocity tracking scheme is superior to the angle and gain tracking scheme, and the tracking error of the proposed algorithm is lower than that of the algorithms using similar state models. Based on the three-dimensional scene, it considers more realistic situations, and is more consistent with the kinematic characteristics of the vehicle and has more practical significance.
5G 和物联网的发展为车联网的深入研究奠定了良好的基础。低频资源稀缺，车联网通信要求极高的通信速率。毫米波可以满足以上两个要求，但其特性和车联网复杂的通信条件使得两者难以结合。克服这些问题，实现精确稳定的波束跟踪是当前面临的一大挑战。本文针对毫米波 V2I 场景提出了一种新的扩展卡尔曼滤波跟踪算法。在原有算法的基础上，增加了阈值预测更新机制。该算法采用了一种以位置和速度为跟踪变量的新方案，并首次基于该方案推导出了 MIMO 3D 场景下的跟踪模型。该模型考虑了三维路况，包括车辆的偏转运动和毫米波链路被大型车辆阻挡的情况，更适合实际应用场景。仿真结果表明，位置和速度跟踪方案优于角度和增益跟踪方案，且所提算法的跟踪误差低于采用类似状态模型的算法。基于三维场景，考虑的情况更真实，更符合车辆的运动学特性，更具有实用意义。
{"title":"Beam Tracking Based on a New State Model for mmWave V2I Communication on 3D Roads","authors":"Yu Sun Yu Sun, Chen-Wei Feng Yu Sun, Xian-Ling Wang Chen-Wei Feng, Jiang-Nan Yuan Xian-Ling Wang, Lin Zhang Jiang-Nan Yuan","doi":"10.53106/199115992024023501003","DOIUrl":"https://doi.org/10.53106/199115992024023501003","url":null,"abstract":"\u0000 The expansion of 5G and Internet of Things has laid a good foundation for the in-depth research of Internet of vehicles. Low frequency resources are scarce, and Internet of vehicles communication requires extremely high communication rate. Millimeter wave can meet the above two requirements, but its characteristics and the complicated communication conditions of Internet of vehicles make it difficult to combine the two. Overcoming these problems and making beam tracking accurate and steady is a major challenge at present. In this paper, a new extended Kalman filter tracking algorithm is proposed for mmWave V2I scenarios. On the basis of the original algorithm, a threshold prediction update mechanism is added. A new scheme is adopted, which takes position and velocity as tracking variables, and the tracking model is derived for the first time in MIMO 3D scenarios based on this scheme. The model considers the three-dimensional road conditions, including the vehicle deflection motion and the millimeter wave link blocked by large vehicles, which is more suitable for practical application scenarios. The simulation results reveal that the position and velocity tracking scheme is superior to the angle and gain tracking scheme, and the tracking error of the proposed algorithm is lower than that of the algorithms using similar state models. Based on the three-dimensional scene, it considers more realistic situations, and is more consistent with the kinematic characteristics of the vehicle and has more practical significance.\u0000 \u0000","PeriodicalId":345067,"journal":{"name":"電腦學刊","volume":"113 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140463864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.53106/199115992024023501006
Chao Wang Chao Wang, Wei Luo Chao Wang, Jia-Rui Zhu Wei Luo, Ying-Chun Xia Jia-Rui Zhu, Jin He Ying-Chun Xia, Li-Chuan Gu Jin He
Visual grounding locates target objects or areas in the image based on natural language expression. Most current methods extract visual features and text embeddings independently, and then carry out complex fusion reasoning to locate target objects mentioned in the query text. However, such independently extracted visual features often contain many features that are irrelevant to the query text or misleading, thus affecting the subsequent multimodal fusion module, and deteriorating target localization. This study introduces a combined network model based on the transformer architecture, which realizes more accurate visual grounding by using query text to guide visual feature generation and multi-stage fusion reasoning. Specifically, the visual feature generation module reduces the interferences of irrelevant features and generates visual features related to query text through the guidance of query text features. The multi-stage fused reasoning module uses the relevant visual features obtained by the visual feature generation module and the query text embeddings for multi-stage interactive reasoning, further infers the correlation between the target image and the query text, so as to achieve the accurate localization of the object described by the query text. The effectiveness of the proposed model is experimentally verified on five public datasets and the model outperforms state-of-the-art methods. It achieves an improvement of 1.04%, 2.23%, 1.00% and +2.51% over the previous state-of-the-art methods in terms of the top-1 accuracy on TestA and TestB of the RefCOCO and RefCOCO+ datasets, respectively.
{"title":"End-to-end Visual Grounding Based on Query Text Guidance and Multi-stage Reasoning","authors":"Chao Wang Chao Wang, Wei Luo Chao Wang, Jia-Rui Zhu Wei Luo, Ying-Chun Xia Jia-Rui Zhu, Jin He Ying-Chun Xia, Li-Chuan Gu Jin He","doi":"10.53106/199115992024023501006","DOIUrl":"https://doi.org/10.53106/199115992024023501006","url":null,"abstract":"\u0000 Visual grounding locates target objects or areas in the image based on natural language expression. Most current methods extract visual features and text embeddings independently, and then carry out complex fusion reasoning to locate target objects mentioned in the query text. However, such independently extracted visual features often contain many features that are irrelevant to the query text or misleading, thus affecting the subsequent multimodal fusion module, and deteriorating target localization. This study introduces a combined network model based on the transformer architecture, which realizes more accurate visual grounding by using query text to guide visual feature generation and multi-stage fusion reasoning. Specifically, the visual feature generation module reduces the interferences of irrelevant features and generates visual features related to query text through the guidance of query text features. The multi-stage fused reasoning module uses the relevant visual features obtained by the visual feature generation module and the query text embeddings for multi-stage interactive reasoning, further infers the correlation between the target image and the query text, so as to achieve the accurate localization of the object described by the query text. The effectiveness of the proposed model is experimentally verified on five public datasets and the model outperforms state-of-the-art methods. It achieves an improvement of 1.04%, 2.23%, 1.00% and +2.51% over the previous state-of-the-art methods in terms of the top-1 accuracy on TestA and TestB of the RefCOCO and RefCOCO+ datasets, respectively.\u0000 \u0000","PeriodicalId":345067,"journal":{"name":"電腦學刊","volume":"49 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140465967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.53106/199115992024023501013
Xue-Meng Du Xue-Meng Du, Ji-Cheng Yang Xue-Meng Du
With the emergence and end of the COVID-19, online learning has become an irreplaceable way of learning. In order to promote the improvement and enhancement of online curriculum resources and increase the learning effect of students, the content of curriculum evaluation is an important reference for the direction of curriculum improvement. Therefore, this article focuses on the student learning feedback of course resources. Firstly, through data collection algorithms, effective evaluation information is crawled, and then based on the collected information, the course evaluation text is annotated and classified, forming a reasonable corpus. Finally, through feature collection and sentiment analysis algorithms, sentiment analysis is performed on the evaluation content, effectively distinguishing between positive and negative evaluations, and guiding teachers to improve the course content.
{"title":"A Text Analysis Method for Student Learning Feedback on Network Teaching Platform Based on Natural Language Processing","authors":"Xue-Meng Du Xue-Meng Du, Ji-Cheng Yang Xue-Meng Du","doi":"10.53106/199115992024023501013","DOIUrl":"https://doi.org/10.53106/199115992024023501013","url":null,"abstract":"\u0000 With the emergence and end of the COVID-19, online learning has become an irreplaceable way of learning. In order to promote the improvement and enhancement of online curriculum resources and increase the learning effect of students, the content of curriculum evaluation is an important reference for the direction of curriculum improvement. Therefore, this article focuses on the student learning feedback of course resources. Firstly, through data collection algorithms, effective evaluation information is crawled, and then based on the collected information, the course evaluation text is annotated and classified, forming a reasonable corpus. Finally, through feature collection and sentiment analysis algorithms, sentiment analysis is performed on the evaluation content, effectively distinguishing between positive and negative evaluations, and guiding teachers to improve the course content.\u0000 \u0000","PeriodicalId":345067,"journal":{"name":"電腦學刊","volume":"99 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140469406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.53106/199115992024023501009
Yu-Hung Hsu Yu-Hung Hsu, Cheng-Hsiu Li Yu-Hung Hsu
Swimming is a sport that relies heavily on motor skills. Inability to maintain adequate bodily balance in water prevents swimmers from remaining afloat and propelling themselves. Due to the difficulty of attaching reflective stickers or LED (light-emitting diode) emitters to the body while adjusting the swimming posture, it is not possible to capture the posture like during a bicycle fitting; the refraction of water also affects the detection of the body’s posture. Addressing the shortcomings, this study developed a low-cost nonhardware posture detection system based on machine-learning models in MediaPipe. The system provides real-time and post analyses of posture angles and posture lines during front crawl swimming, thereby facilitating observation of the relationship between angle at which the arm enters the water and the body horizon. Two participants practicing front crawl were invited to test the proposed system. The experimental results confirmed that the proposed system provides effective detection and analyses of posture lines and angles in swimmers. The study also proposed the algorithm for optimizing posture angle detection to solve the problems of posture line distortion and angle calculation errors that arise when MediaPipe was used to detect a human skeleton above a water line. The system does not require the installation of hardware and is inexpensive to deploy, and it can be widely applied in front crawl swimming lessons to help learners adjust their arm’s entry angle and body horizon to reduce forward drag and increase speed.
{"title":"Using Machine-Learning Technology to Implement a Nonhardware and Inexpensive Posture Detection System for Analyzing Body Posture Angles in Front Crawl Swimming","authors":"Yu-Hung Hsu Yu-Hung Hsu, Cheng-Hsiu Li Yu-Hung Hsu","doi":"10.53106/199115992024023501009","DOIUrl":"https://doi.org/10.53106/199115992024023501009","url":null,"abstract":"\u0000 Swimming is a sport that relies heavily on motor skills. Inability to maintain adequate bodily balance in water prevents swimmers from remaining afloat and propelling themselves. Due to the difficulty of attaching reflective stickers or LED (light-emitting diode) emitters to the body while adjusting the swimming posture, it is not possible to capture the posture like during a bicycle fitting; the refraction of water also affects the detection of the body’s posture. Addressing the shortcomings, this study developed a low-cost nonhardware posture detection system based on machine-learning models in MediaPipe. The system provides real-time and post analyses of posture angles and posture lines during front crawl swimming, thereby facilitating observation of the relationship between angle at which the arm enters the water and the body horizon. Two participants practicing front crawl were invited to test the proposed system. The experimental results confirmed that the proposed system provides effective detection and analyses of posture lines and angles in swimmers. The study also proposed the algorithm for optimizing posture angle detection to solve the problems of posture line distortion and angle calculation errors that arise when MediaPipe was used to detect a human skeleton above a water line. The system does not require the installation of hardware and is inexpensive to deploy, and it can be widely applied in front crawl swimming lessons to help learners adjust their arm’s entry angle and body horizon to reduce forward drag and increase speed.\u0000 \u0000","PeriodicalId":345067,"journal":{"name":"電腦學刊","volume":"638 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140469543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.53106/199115992024023501001
Lei Wang Lei Wang, Ting-Ting Niu Lei Wang, Wei-Hao Qiao Ting-Ting Niu, Song Cui Wei-Hao Qiao
To address the problem of low localization accuracy in the node localization algorithms of wireless sensor networks (WSN) based on received signal strength indication (RSSI) ranging, a WSN node localization algorithm based on ranging optimization and graph optimization is proposed. In terms of RSSI ranging, the outliers are removed using the Grubbs method, and the data are processed using a moving average smoothing-Gaussian hybrid filter to establish a Bessel function ranging model to reduce the ranging error; in terms of node localization, the signal strength data are employed to construct a distance cost term, a cost function model is built based on these cost terms, and graph optimization is adopted to minimize this function. Then, the node position is estimated to minimize the overall observation error. Simulation results indicate that the proposed algorithm has higher ranging and localization accuracy than existing ranging and localization algorithms, and it can meet the requirements of node localization in large-scale WSN.
{"title":"Wireless Sensor Networks Node Localization Algorithm Based on Range Optimization and Graph Optimization","authors":"Lei Wang Lei Wang, Ting-Ting Niu Lei Wang, Wei-Hao Qiao Ting-Ting Niu, Song Cui Wei-Hao Qiao","doi":"10.53106/199115992024023501001","DOIUrl":"https://doi.org/10.53106/199115992024023501001","url":null,"abstract":"\u0000 To address the problem of low localization accuracy in the node localization algorithms of wireless sensor networks (WSN) based on received signal strength indication (RSSI) ranging, a WSN node localization algorithm based on ranging optimization and graph optimization is proposed. In terms of RSSI ranging, the outliers are removed using the Grubbs method, and the data are processed using a moving average smoothing-Gaussian hybrid filter to establish a Bessel function ranging model to reduce the ranging error; in terms of node localization, the signal strength data are employed to construct a distance cost term, a cost function model is built based on these cost terms, and graph optimization is adopted to minimize this function. Then, the node position is estimated to minimize the overall observation error. Simulation results indicate that the proposed algorithm has higher ranging and localization accuracy than existing ranging and localization algorithms, and it can meet the requirements of node localization in large-scale WSN.\u0000 \u0000","PeriodicalId":345067,"journal":{"name":"電腦學刊","volume":"514 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140468406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.53106/199115992024023501019
Guang-Hua Li Guang-Hua Li, Tian-Hua Lu Guang-Hua Li
The blended teaching mode of “online+offline” has gradually become a widely used teaching mode due to its flexible teaching form and rich and vivid course resources. In the blended teaching mode, this article mainly focuses on how to improve the teaching quality of vocational English courses. Firstly, an analysis was conducted on the learning situation of English courses among vocational college students, including their source structure, learning characteristics, and current development status of English courses. In order to facilitate a structured analysis of students’ learning ability in English courses, a learning ability analysis model for vocational college students was constructed, and a survey questionnaire was designed to analyze their learning behavior and data. Finally, through data analysis, it was found how to use network information resources to improve the quality of English blended learning courses.
{"title":"Research on Strategies for Improving the Quality of English Blended Teaching in Vocational Colleges through Network Informatization Resources","authors":"Guang-Hua Li Guang-Hua Li, Tian-Hua Lu Guang-Hua Li","doi":"10.53106/199115992024023501019","DOIUrl":"https://doi.org/10.53106/199115992024023501019","url":null,"abstract":"\u0000 The blended teaching mode of “online+offline” has gradually become a widely used teaching mode due to its flexible teaching form and rich and vivid course resources. In the blended teaching mode, this article mainly focuses on how to improve the teaching quality of vocational English courses. Firstly, an analysis was conducted on the learning situation of English courses among vocational college students, including their source structure, learning characteristics, and current development status of English courses. In order to facilitate a structured analysis of students’ learning ability in English courses, a learning ability analysis model for vocational college students was constructed, and a survey questionnaire was designed to analyze their learning behavior and data. Finally, through data analysis, it was found how to use network information resources to improve the quality of English blended learning courses.\u0000 \u0000","PeriodicalId":345067,"journal":{"name":"電腦學刊","volume":"278 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140464999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.53106/199115992024023501005
Da-Wei Zhou Da-Wei Zhou, Su-Zhen Cao Da-Wei Zhou, Xiao Zhao Su-Zhen Cao, Dan-Dan Xing Xiao Zhao, Zheng Wang Dan-Dan Xing
To solve the problems of existing e-auction protocols such as semi-trustworthiness of outsourced third parties, collusive attacks among participants, unsatisfactory decentralized structure, and inability of public verification, we propose an efficient first-price sealed e-auction protocol under a secure multi-party computational malicious model. First, the protocol combines the additive homomorphism of the ElGamal cryptographic algorithm to achieve a decentralized structure and eliminate the problem of semi-trustworthiness of outsourced third parties; it uses (n, n) threshold encryption and decryption techniques to solve the problem of collusion attacks among participants and uses Hash-based Message Authentication Code (HMAC) technology to achieve public verifiability of auction results. Additionally, the protocol proposes a method to quickly find the maximum value of the data encoding, which can avoid multiple processing of confidential data and thus effectively reduce the number of communication rounds. The combination of zero-knowledge proof and ideal/realistic simulation paradigm proves that the protocol in this paper is resistant to up to n-1 party collusion attacks and satisfies the security of the secure multi-party computational malicious model. Finally, after theoretical analysis and simulation experiments, the protocol not only satisfies higher security performance but also has greater overall operational efficiency.
{"title":"Efficient First-price Sealed E-auction Protocol Under Secure Multi-party Computational Malicious Model","authors":"Da-Wei Zhou Da-Wei Zhou, Su-Zhen Cao Da-Wei Zhou, Xiao Zhao Su-Zhen Cao, Dan-Dan Xing Xiao Zhao, Zheng Wang Dan-Dan Xing","doi":"10.53106/199115992024023501005","DOIUrl":"https://doi.org/10.53106/199115992024023501005","url":null,"abstract":"\u0000 To solve the problems of existing e-auction protocols such as semi-trustworthiness of outsourced third parties, collusive attacks among participants, unsatisfactory decentralized structure, and inability of public verification, we propose an efficient first-price sealed e-auction protocol under a secure multi-party computational malicious model. First, the protocol combines the additive homomorphism of the ElGamal cryptographic algorithm to achieve a decentralized structure and eliminate the problem of semi-trustworthiness of outsourced third parties; it uses (n, n) threshold encryption and decryption techniques to solve the problem of collusion attacks among participants and uses Hash-based Message Authentication Code (HMAC) technology to achieve public verifiability of auction results. Additionally, the protocol proposes a method to quickly find the maximum value of the data encoding, which can avoid multiple processing of confidential data and thus effectively reduce the number of communication rounds. The combination of zero-knowledge proof and ideal/realistic simulation paradigm proves that the protocol in this paper is resistant to up to n-1 party collusion attacks and satisfies the security of the secure multi-party computational malicious model. Finally, after theoretical analysis and simulation experiments, the protocol not only satisfies higher security performance but also has greater overall operational efficiency.\u0000 \u0000","PeriodicalId":345067,"journal":{"name":"電腦學刊","volume":"1300 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140466850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.53106/199115992024023501015
Xuan Zhao Xuan Zhao, Bo Shen Xuan Zhao, Maojie Zhang Bo Shen, Ying Liu Maojie Zhang, Guohua Shi Ying Liu, Peng Zhao Guohua Shi, Zhiyuan Zhang Peng Zhao
Deterministic scheduling technology is of great significance for the real-time and deterministic transmission of industrial wireless network data. In view of the fact that the industrial wireless network data stream itself has priority classification attribute, this paper, based on multi-channel time-division multiple access (TDMA) technology, analyzes link conflict delay and channel contention delay caused by high priority data stream to low priority data stream, and performs scheduling preprocessing on the network, so as to eliminate the network with unreasonable parameters, and feedback to the network manager. For preprocessed networks, the scheduling algorithm prioritizes the allocation of time slots and channel resources for links of high priority data streams, while for data streams belonging to the same priority class, a scheduling scheme based on Maximum Proportional Conflict and Deadline First (MPC-D) is proposed. Under the premise of meeting schedulability conditions, time slots and channel resources are allocated sequentially according to the proportional conflict deadline values of each link, from largest to smallest. The experimental results show that the proposed scheduling algorithm can achieve a high network scheduling success rate.
{"title":"Deterministic Scheduling Algorithm Based on Proportional Conflict and Deadline in Industrial Wireless Networks","authors":"Xuan Zhao Xuan Zhao, Bo Shen Xuan Zhao, Maojie Zhang Bo Shen, Ying Liu Maojie Zhang, Guohua Shi Ying Liu, Peng Zhao Guohua Shi, Zhiyuan Zhang Peng Zhao","doi":"10.53106/199115992024023501015","DOIUrl":"https://doi.org/10.53106/199115992024023501015","url":null,"abstract":"\u0000 Deterministic scheduling technology is of great significance for the real-time and deterministic transmission of industrial wireless network data. In view of the fact that the industrial wireless network data stream itself has priority classification attribute, this paper, based on multi-channel time-division multiple access (TDMA) technology, analyzes link conflict delay and channel contention delay caused by high priority data stream to low priority data stream, and performs scheduling preprocessing on the network, so as to eliminate the network with unreasonable parameters, and feedback to the network manager. For preprocessed networks, the scheduling algorithm prioritizes the allocation of time slots and channel resources for links of high priority data streams, while for data streams belonging to the same priority class, a scheduling scheme based on Maximum Proportional Conflict and Deadline First (MPC-D) is proposed. Under the premise of meeting schedulability conditions, time slots and channel resources are allocated sequentially according to the proportional conflict deadline values of each link, from largest to smallest. The experimental results show that the proposed scheduling algorithm can achieve a high network scheduling success rate.\u0000 \u0000","PeriodicalId":345067,"journal":{"name":"電腦學刊","volume":"65 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140466532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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