2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID)最新文献

Analysis of Discharge Parameters Influenced by Electrode Velocity Based on LSTM Prediction Model 基于LSTM预测模型的电极速度对放电参数影响分析

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9995944

X. He, Fangming Ruan, Lan Yin, Yanli Chen, Yaru Yang, Xiao Wang

{"title":"Analysis of Discharge Parameters Influenced by Electrode Velocity Based on LSTM Prediction Model","authors":"X. He, Fangming Ruan, Lan Yin, Yanli Chen, Yaru Yang, Xiao Wang","doi":"10.1109/ASID56930.2022.9995944","DOIUrl":"https://doi.org/10.1109/ASID56930.2022.9995944","url":null,"abstract":"Relationships were discussed in this work between discharge current and electrode moving speed, ionization coefficient, field strength, gas pressure, temperature, humidity and other factors. Gas flow distribution around electrode, according to Bernoulli's law in aerodynamics, was analyzed during the electrode moving toward the target. Mechanism was explained on forming of local part low vacuum in the discharge gap. Two sub-processes of gas ionization avalanche process and surface electronic emission process were used to describe small gap discharge. With Paschen's law, analysis of influence was performed on discharge current by electrode moving speed toward the target. Experiments were conducted many times based on test platform of electrostatic discharge electrode moving speed effect, while experiment data were recorded. Long Short-Term Memory network (LSTM) model was used to train and learn experimental data, predicted peak value of discharge current at different electrode moving speeds and rise time. The experimental results show that there is a strong correlation between the electrode moving speed and the peak discharge current, while there is a certain correlation between the electrode moving speed and the current rise time, but it is relatively weak. The research results maybe have some reference significance for the proposal and formulation of non-contact electrostatic discharge standards.","PeriodicalId":183908,"journal":{"name":"2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129517282","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}

引用次数: 0

An Optimized Method for Large-Scale Pre-Training in Symbolic Music 符号音乐大规模预训练的优化方法

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9995766

Shike Liu, Hongguang Xu, Ke Xu

{"title":"An Optimized Method for Large-Scale Pre-Training in Symbolic Music","authors":"Shike Liu, Hongguang Xu, Ke Xu","doi":"10.1109/ASID56930.2022.9995766","DOIUrl":"https://doi.org/10.1109/ASID56930.2022.9995766","url":null,"abstract":"A better understanding of music can effectively improve the performance of music recommendation or generation. Although it has been confirmed that simply using the training method of the BERT model has strong ability in the field of symbolic music, the performance of BERT still has significant potential to be improved. In this paper, we mainly focus on the BERT model and propose a method to enhance its performance in the symbolic music domain. In order to mitigate the problem of information leakage between adjacent music tokens in pre-training, we propose a masking strategy that optimizes pre-training by corrupting data in a novel mechanism. Furthermore, the pre-training datasets used in our work cover both classical and popular music, which can provide a more comprehensive knowledge of different sorts of music, where a dynamic masking strategy is also employed to make full use of the data. We evaluate our improved model on four downstream tasks, including the melody extraction, velocity prediction, composer classification, and emotion classification. Experiments demonstrate that our proposed method has better music understanding ability than the baselines.","PeriodicalId":183908,"journal":{"name":"2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128991681","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}

引用次数: 0

Intelligent Recognition of the Ultrasound Standard Plane of the Fetal Cranial Brain with the FCB-Net FCB-Net对胎儿颅脑超声标准平面的智能识别

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9996076

Pang Zeng, Weifeng Yu, Zhonghua Liu, Yong Diao, Peizhong Liu

{"title":"Intelligent Recognition of the Ultrasound Standard Plane of the Fetal Cranial Brain with the FCB-Net","authors":"Pang Zeng, Weifeng Yu, Zhonghua Liu, Yong Diao, Peizhong Liu","doi":"10.1109/ASID56930.2022.9996076","DOIUrl":"https://doi.org/10.1109/ASID56930.2022.9996076","url":null,"abstract":"Ultrasound images can be acquired in real-time and quickly, and also have the advantage of being low cost and no radiation. Currently, ultrasound is widely used in clinical diagnosis. With the development of ultrasound, it is slowly becoming an essential part of the imaging examinations in obstetrics. Fetal cranial ultrasound plays a vital role in assessing fetal growth and development, decreasing the rate of birth defects, monitoring pregnancy, and assessing clinical diagnosis. Due to its ability to visualize the internal structures of the fetal cranial brain in standard planes, fetal cranial ultrasound is also essential in screening for fetal structural abnormalities. However, the conventional approach relies primarily on the ultrasound doctor to do the work manually, which is a time-consuming and laborious process. This paper proposed a convolutional neural network, FCB-Net, for recognition of the ultrasound standard plane of the fetal cranial brain. There are 5361 fetal intracranial ultrasound images collected, and they were randomly divided into 4258 for model training and 1103 for testing the performance of the model. The experiments have shown that our proposed FCB-Net has the best recognition performance for the fetal cranial brain, and the accuracy of FCB-Net has reached 91.66%.","PeriodicalId":183908,"journal":{"name":"2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114555662","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}

引用次数: 0

A SPA Countermeasure for Hardware Implementation of SM2 Algorithm SM2算法硬件实现的SPA对策

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9995777

Zhanzhan Chen, Liji Wu, Zhenhui Zhang, Dehang Xiao, Xiangmin Zhang, Yan Liu

引用次数: 0

Performance and Security Enhancement Solutions for Positron Emission Tomography Medical Hardware 正电子发射断层扫描医疗硬件的性能和安全性增强解决方案

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9995986

Zhuoheng Ran, Haosen Yu

引用次数: 0

Design and Implementation of Data Navigator for Heterogeneous Multi-Core System 异构多核系统数据导航器的设计与实现

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9995747

Hu Ge, Y. Song, Duoli Zhang, Zhen-cheng Chen, Yan Ma

引用次数: 0

Safe Deep Reinforcement Learning Based on Sample Value Evaluation 基于样本值评估的安全深度强化学习

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9996075

Rongjun Ye, Hao Wang, Huan Li

{"title":"Safe Deep Reinforcement Learning Based on Sample Value Evaluation","authors":"Rongjun Ye, Hao Wang, Huan Li","doi":"10.1109/ASID56930.2022.9996075","DOIUrl":"https://doi.org/10.1109/ASID56930.2022.9996075","url":null,"abstract":"In recent years, deep reinforcement learning has combined the advantages of reinforcement learning and deep learning, and has made great progress in decision-making tasks. However, the training of deep reinforcement learning requires frequent interactions between the agent and the environment and repeated experiments. Adversaries have chances to poison the sample data collected by the agent by attacking the experimental environment in the training process, thereby bringing security risks and serious consequences to the training process of reinforcement learning. This work is committed to addressing the security risks in the field of deep reinforcement learning. However, this work improves the algorithm from the perspective of sample data filtering, and improves the security performance of deep reinforcement learning algorithm. There are two contributions in this work: one is to defend against adversarial attacks against deep reinforcement learning through cluster analysis and sample value evaluation; the other is to propose a deep reinforcement learning algorithm based on sample value evaluation on the basis of deterministic strategy gradient algorithm. The algorithm uses the clustering method to classify the sample pool, and measures the contribution value and security risk of the sample to the model training through the sample value evaluation. The classic game experiments show that the proposed algorithm is safe and effective. It reduces the threat of the agent falling into the adversarial sample attack and improves the training performance of deep reinforcement learning.","PeriodicalId":183908,"journal":{"name":"2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126596741","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}

引用次数: 0

A Floating-Point Unit Architecture Based on SweRV EH1 Core 基于SweRV EH1内核的浮点单元体系结构

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9995796

Zhen Lei, Fan Cai, Jianyang Zhou, Zichao Guo

引用次数: 1

An Improved SAMP Channel Estimation Method via Compressed Sensing for MIMO-OFDM Systems 一种基于压缩感知的MIMO-OFDM系统SAMP信道估计方法

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9995751

Weiqiang Chen, Mingjie Zhuang

引用次数: 0

Design of 64-Bit High-Performance Embedded Processor Supporting RISC-V B-Extension 支持RISC-V b扩展的64位高性能嵌入式处理器设计

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9995771

Ziqin Meng, Yunrui Zhang, Jianyang Zhou, Zichao Guo

{"title":"Design of 64-Bit High-Performance Embedded Processor Supporting RISC-V B-Extension","authors":"Ziqin Meng, Yunrui Zhang, Jianyang Zhou, Zichao Guo","doi":"10.1109/ASID56930.2022.9995771","DOIUrl":"https://doi.org/10.1109/ASID56930.2022.9995771","url":null,"abstract":"With the continuous development of IoT technology, edge computing and high-performance computing are being merged. Compared with 32-bit processors, 64-bit processors have obvious advantages in processing some large data sets and high-precision numerical computing tasks. At the same time, as an open-source instruction set, RISC-V has highly concise instruction coding and flexible modular expansion, which is very suitable for the implementation of embedded processors. In this paper, we refer to the micro-architecture of the open-source 32-bit RISC-V processor SweRV EH1 and design a 64-bit embedded processor that supports the RV64IMCB instruction set. We adopt the instruction set self-checking test scheme based on riscv-tests to complete the functional verification of the processor and carry out the FPGA prototype verification on the Xilinx KC705 hardware platform. Compared with the 32-bit SweRV EH1, the Dhrystone performance improved by 32.3% on 64-bit processors with B-extension. The experiment shows that implementing the B-extension in a 64-bit processor can bring a 28.8% increase in Dhrystone performance and an 11.8% increase in CoreMark performance with an additional area overhead of 8.4%.","PeriodicalId":183908,"journal":{"name":"2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115314102","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}

引用次数: 2