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2022 IEEE 2nd International Conference on Computer Systems (ICCS)最新文献

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The Improvement Breakdown Voltage of GaN on Si Pin Diode by Stepped Sidewall Treated with Fluorine Plasma 氟等离子体台阶侧壁处理提高硅脚二极管GaN击穿电压
2022 IEEE 2nd International Conference on Computer Systems (ICCS) Pub Date : 2022-09-23 DOI: 10.1109/ICCS56273.2022.9988470
Fuchun Jia, Qingyuan Chang, Xiaosheng Chen, Bin Hou, Ling Yang, Xiao-hua Ma
{"title":"The Improvement Breakdown Voltage of GaN on Si Pin Diode by Stepped Sidewall Treated with Fluorine Plasma","authors":"Fuchun Jia, Qingyuan Chang, Xiaosheng Chen, Bin Hou, Ling Yang, Xiao-hua Ma","doi":"10.1109/ICCS56273.2022.9988470","DOIUrl":"https://doi.org/10.1109/ICCS56273.2022.9988470","url":null,"abstract":"In this work, we show a GaN-on-Si quasi vertical PiN diode via the combination of stepped sidewall and fluorine plasma treatment. We achieved a 43.2% increase in breakdown voltage (VBR). Meanwhile, the off-state leakage is greatly reduced. The diode with stepped sidewall treated with fluorine plasma achieved a low specific on-resistance (Ron,sp) of 0.51 mΩ·cm2, and a high Baliga's figure of merit (BFOM) of 0.83 GW/cm2. On the one hand, this work demonstrates the effect of the combination of stepped sidewall and fluorine plasma treatment of GaN-on-Si quasi vertical PiN diode, and on the other hand, shows a broad prospect of GaN on Si PiN diode for power electronics application.","PeriodicalId":382726,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Systems (ICCS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123778170","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 NLP Application of Automated Symptom Information Extraction from TCM Medical Cases 中医病例症状信息自动提取的NLP应用
2022 IEEE 2nd International Conference on Computer Systems (ICCS) Pub Date : 2022-09-23 DOI: 10.1109/ICCS56273.2022.9988199
Cheng Qiang, Du Zhong-min
{"title":"A NLP Application of Automated Symptom Information Extraction from TCM Medical Cases","authors":"Cheng Qiang, Du Zhong-min","doi":"10.1109/ICCS56273.2022.9988199","DOIUrl":"https://doi.org/10.1109/ICCS56273.2022.9988199","url":null,"abstract":"Starting from natural language processing (NLP) technology, we compare the extraction results of TFIDF and Word2vec methods to explore research ideas that are more applicable to automated extraction of symptom information of traditional Chinese medicine (TCM) medical cases, and provide reference for the development of automated analysis of TCM medical cases. On the basis of constructed medical case dictionary, TFIDF and Word2vec methods were used to extract symptoms from heart cases, and the results were compared and analyzed. In medical cases, the onset of patients was often accompanied by palpitations, chest tightness, chest pain, shortness of breath, dizziness and other symptoms, and certain associations between symptoms were also found. The results of experimental evaluation showed that accuracy and recall rates of Word2vec method extraction were higher than those of TFIDF method. Compared with TFIDF method, Word2vec method is more effective when applied to the task of automated symptom information extraction from TCM cases.","PeriodicalId":382726,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Systems (ICCS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114570033","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
Saliency Detection of Logistics Packages Based on Deep Learning 基于深度学习的物流包裹显著性检测
2022 IEEE 2nd International Conference on Computer Systems (ICCS) Pub Date : 2022-09-23 DOI: 10.1109/ICCS56273.2022.9987766
Guanhui Jiang, Weizhong Zhang, Wenshan Wang, Xiaoqi Sun
{"title":"Saliency Detection of Logistics Packages Based on Deep Learning","authors":"Guanhui Jiang, Weizhong Zhang, Wenshan Wang, Xiaoqi Sun","doi":"10.1109/ICCS56273.2022.9987766","DOIUrl":"https://doi.org/10.1109/ICCS56273.2022.9987766","url":null,"abstract":"Aiming at the problem that parcels in the logistics industry cannot be accurately located on the conveyor belt to obtain parcel location information, this paper proposes a parcel saliency detection and location method based on deep learning. Firstly, RGBD (Red-Green-Blue-Depth) images are acquired by depth cameras, and the images are filtered and hole-filled to remove noise and irrelevant information; then they are input to the constructed neural network model for training and testing; finally, the location of parcels in the images is obtained. Test experiments on the parcels on the conveyor belt show that the accuracy of locating the parcel position reaches 96.92% with an mean absolute error of only 0.0141, which can guarantee the accuracy of locating the parcel position and thus facilitate the post-processing of the parcel information. This method has greater research significance and engineering application value for the logistics industry.","PeriodicalId":382726,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Systems (ICCS)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124683884","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
Logistics Distribution Process Design Based on Stochastic Petri Nets and Big Data Algorithms 基于随机Petri网和大数据算法的物流配送流程设计
2022 IEEE 2nd International Conference on Computer Systems (ICCS) Pub Date : 2022-09-23 DOI: 10.1109/ICCS56273.2022.9987800
Longyang Zhang, Jie Li
{"title":"Logistics Distribution Process Design Based on Stochastic Petri Nets and Big Data Algorithms","authors":"Longyang Zhang, Jie Li","doi":"10.1109/ICCS56273.2022.9987800","DOIUrl":"https://doi.org/10.1109/ICCS56273.2022.9987800","url":null,"abstract":"-Logistics is to distribute goods to corresponding transportation routes according to the demand of goods through warehouse operation, so as to meet customer demand and arrive at the destination on time. The distribution process is the core of the entire logistics system, and its operation speed is directly related to the efficiency of the entire logistics system. In order to improve the distribution efficiency and reduce the transit time, it is necessary to optimize the design of the logistics distribution process. However, the current distribution process is characterized by high cost, low efficiency, and low degree of informatization and labeling, which in turn affects customer satisfaction and enterprise interests. Therefore, aiming at these problems, this paper designs a logistics distribution process based on stochastic Petri net and big data algorithm. Through stochastic Petri net modeling, the distribution process is quantitatively analyzed, the distribution business process model is established and optimized, and the modeling method based on stochastic Petri net is successfully applied to the logistics distribution business process to achieve efficient and low-cost logistics distribution.","PeriodicalId":382726,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Systems (ICCS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124030120","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
Application of Generalized Regression Neural Network and Sarima Model in Prediction of AIDS 广义回归神经网络与Sarima模型在艾滋病预测中的应用
2022 IEEE 2nd International Conference on Computer Systems (ICCS) Pub Date : 2022-09-23 DOI: 10.1109/ICCS56273.2022.9988161
Xixun Zhu, Yanmei Zheng, Yanling Zheng, Jinfeng Ma
{"title":"Application of Generalized Regression Neural Network and Sarima Model in Prediction of AIDS","authors":"Xixun Zhu, Yanmei Zheng, Yanling Zheng, Jinfeng Ma","doi":"10.1109/ICCS56273.2022.9988161","DOIUrl":"https://doi.org/10.1109/ICCS56273.2022.9988161","url":null,"abstract":"Generalized regression neural network (GRNN) is highly fault-tolerant and robust, which is suitable to solve nonlinear problems, and is currently widely used in prediction research. The seasonal autoregressive integrated moving mean model (Sarima) captures the seasonal, periodicity of historical data very well. In order to arouse people's concern about health and keep away from AIDS again, in the study, we applied GRNN and Sarima model to explore the prediction of the incidence and mortality of AIDS Based on historical AIDS data in Guangxi. We established the high-precision Sarima (2,0,1)(1,0,1)12 model and GRNN network with spread 0.4 to predict the numbers of monthly AIDS deaths and reported cases from November 2019 to December 2021. The results of the prediction analysis indicated that if the prevention and control efforts will not be increased, the incidence of AIDS in Guangxi may remain high, and the number of AIDS deaths per month may show an upward trend, which provides early warning and scientific reference for the prevention departments to optimize the allocation of resources in advance.","PeriodicalId":382726,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Systems (ICCS)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115710304","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
Application of DWT-Sigmoid Entropy Feature Parameter Extraction in Gear Fault Diagnosis dwt - s型熵特征参数提取在齿轮故障诊断中的应用
2022 IEEE 2nd International Conference on Computer Systems (ICCS) Pub Date : 2022-09-23 DOI: 10.1109/ICCS56273.2022.9988208
W. Qi, L. Jinhua, Huan Shuaiwei
{"title":"Application of DWT-Sigmoid Entropy Feature Parameter Extraction in Gear Fault Diagnosis","authors":"W. Qi, L. Jinhua, Huan Shuaiwei","doi":"10.1109/ICCS56273.2022.9988208","DOIUrl":"https://doi.org/10.1109/ICCS56273.2022.9988208","url":null,"abstract":"After analyzing the non-stationarity and nonlinear characteristics of gear vibration signals and the problem of fault signal feature extraction, we propose a gear fault classification method based on DWT-sigmoid entropy and BP neural network. The method firstly uses discrete wavelet transform (DWT) to decompose and denoise the vibration signals of four kinds of gear faults and extracts high-frequency and low-frequency coefficients. Then the energy features and singular value features of the high-frequency and low-frequency coefficients are calculated respectively. Secondly, the signal is reconstructed according to the high-frequency coefficients and the low-frequency coefficients. Then the sigmoid entropy feature of the reconstructed signal is calculated. Finally, the five features are fused and input to the BP neural network to classify different faults of gears. Experiments show that the method can effectively perform gear fault classification with an accuracy of up to 100%.","PeriodicalId":382726,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Systems (ICCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124414353","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
Analysis of the Design of Several Modern Programming Languages 几种现代程序设计语言的设计分析
2022 IEEE 2nd International Conference on Computer Systems (ICCS) Pub Date : 2022-09-23 DOI: 10.1109/ICCS56273.2022.9987746
Xudong Wang, Zhimei Zhang
{"title":"Analysis of the Design of Several Modern Programming Languages","authors":"Xudong Wang, Zhimei Zhang","doi":"10.1109/ICCS56273.2022.9987746","DOIUrl":"https://doi.org/10.1109/ICCS56273.2022.9987746","url":null,"abstract":"The design of programming languages has always been an important topic in the field of programming language theory. However, most attention on programming language research focuses on compiler technology, while much less on language design. In this paper, we select multiple modern programming languages (MPLs) and systematically analyzed their designs from an application-oriented view. Concretely, we conduct the evaluation of their programming paradigms, type systems, and language performances based on benchmarking tests. Through these analyses combining theory and practice, the relationship between programming language design and its application scenarios is revealed, and the future developing trend of programming languages can be disclosed.","PeriodicalId":382726,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Systems (ICCS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126759906","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
Resource Deployment and Task Scheduling Based on Cloud Computing 基于云计算的资源部署与任务调度
2022 IEEE 2nd International Conference on Computer Systems (ICCS) Pub Date : 2022-09-23 DOI: 10.1109/ICCS56273.2022.9988014
He Sun
{"title":"Resource Deployment and Task Scheduling Based on Cloud Computing","authors":"He Sun","doi":"10.1109/ICCS56273.2022.9988014","DOIUrl":"https://doi.org/10.1109/ICCS56273.2022.9988014","url":null,"abstract":"Cloud computing is a computing model developed from parallel computing and distributed computing. The rapid development of cloud computing technology not only expands the scale of data in the database, but also consumes a lot of resources for data processing, resulting in huge energy costs. In addition, scheduling policies that do not conform to the actual situation will cause uneven task distribution, cause serious waste of resources, and increase cloud data management operating costs. In cloud computing related research, resource deployment and task scheduling have a great impact on the overall performance of the system. In order to solve the above problems, more and more scholars have conducted in-depth research on this problem. Reduce the energy consumption (EC) of cloud data processing, improve data processing efficiency, propose cloud computing architecture, build resource deployment (RD) model and task scheduling (TS) model on this basis. The usefulness of the model is discussed in depth. Aiming at low EC and high-efficiency resource allocation tasks, a TS algorithm based on improved particle swarm optimization (PSO) algorithm is proposed to further improve the performance of cloud computing systems. The experimental results show that the resource deployment and task scheduling model constructed in this paper can consume bad particles, maximize resource utilization, and reduce the EC of cloud computing (CC) systems after being optimized by particle swarm optimization. Compared with the traditional PSO algorithm, the improved PSO algorithm in this paper can effectively avoid the problem of user query resource allocation lag, improve the task execution efficiency, and enhance the stability of the CC system.","PeriodicalId":382726,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Systems (ICCS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124901670","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: 1
A Novel Demand Response Potential Assessment Method for Industrial Users 一种新的工业用户需求响应潜力评估方法
2022 IEEE 2nd International Conference on Computer Systems (ICCS) Pub Date : 2022-09-23 DOI: 10.1109/ICCS56273.2022.9988549
Shaofeng Guan, Huidan Zhuo, Kuangli Yang
{"title":"A Novel Demand Response Potential Assessment Method for Industrial Users","authors":"Shaofeng Guan, Huidan Zhuo, Kuangli Yang","doi":"10.1109/ICCS56273.2022.9988549","DOIUrl":"https://doi.org/10.1109/ICCS56273.2022.9988549","url":null,"abstract":"Power companies or load aggregators can reasonably call demand-side resources through accurate user demand response potential assessment, which can improve the effect of demand response implementation and reduce the load peak-to-valley difference of the power system. Therefore, based on Gaussian process regression, this paper proposes a demand response potential evaluation method for industrial users with large power consumption and strong load regularity. A feature extraction model of industrial user interruptible load based on time series decomposition algorithm, a demand response user willingness model and an industrial user demand response potential evaluation model based on Gaussian process regression are established. Finally, the actual demand response data of a local industrial user is compared with the proposed demand response potential evaluation method. The results show that the proposed method can more accurately evaluate the demand response potential of industrial users, and reasonably call the industrial user resources on the demand side for power companies or load aggregators.","PeriodicalId":382726,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Systems (ICCS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121794426","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
Recovering Multi-frame Incomplete Path Tracing Images Using Tensor Completion 利用张量补全恢复多帧不完整路径跟踪图像
2022 IEEE 2nd International Conference on Computer Systems (ICCS) Pub Date : 2022-09-23 DOI: 10.1109/ICCS56273.2022.9988436
Ping Liu, Hangyu Ji
{"title":"Recovering Multi-frame Incomplete Path Tracing Images Using Tensor Completion","authors":"Ping Liu, Hangyu Ji","doi":"10.1109/ICCS56273.2022.9988436","DOIUrl":"https://doi.org/10.1109/ICCS56273.2022.9988436","url":null,"abstract":"This paper presents a novel method to recover missing pixels in multi-frame incomplete path tracing images using tensor completion. Matrix completion and compressed sensing provide screen space solutions to recover missing pixels from sparsely rendered path tracing images, providing efficient previsualization. Path tracing is often used to generate an animated sequence of images, which then requires an efficient previsualization that is coherent across multiple frames to avoid temporal noise in the final video. We present a novel numerical method to construct a tensor structure using multiple path tracing images followed by tensor completion, which coherently recovers missing pixels avoiding temporal noise. Our numerical method avoids complex procedures when building a low rank tensor for tensor completion, which previously required complex initialization and similar patch finding steps across nearby frames. Our method shows promising results and outperforms recent matrix completion based methods in both visual quality and performance.","PeriodicalId":382726,"journal":{"name":"2022 IEEE 2nd International Conference on Computer Systems (ICCS)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122406463","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
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