2021 International Symposium on Electrical, Electronics and Information Engineering最新文献_第7页

On the Impact of Emotions on the Detection of False Information 论情绪对虚假信息检测的影响

2021 International Symposium on Electrical, Electronics and Information Engineering Pub Date : 2021-02-19 DOI: 10.1145/3459104.3459150

Paolo Rosso, Bilal Ghanem, Anastasia Giahanou

引用次数: 0

Collaborative Filtering Recommendation Algorithm Based on Similarity of Co-Rating Sequence 基于协同评级序列相似性的协同过滤推荐算法

2021 International Symposium on Electrical, Electronics and Information Engineering Pub Date : 2021-02-19 DOI: 10.1145/3459104.3459180

Xiaoyu Liu, Shuqing Li

引用次数: 2

Multistep Forecasting of New COVID-19 Cases Based on LSTMs Using Bayesian Optimization 基于贝叶斯优化lstm的新冠肺炎多步预测

2021 International Symposium on Electrical, Electronics and Information Engineering Pub Date : 2021-02-19 DOI: 10.1145/3459104.3459116

Tianqian Chen, Shuyu Chen, Shan Mei, Shuqi An, Xiaohan Yuan, Yuwen Lu

{"title":"Multistep Forecasting of New COVID-19 Cases Based on LSTMs Using Bayesian Optimization","authors":"Tianqian Chen, Shuyu Chen, Shan Mei, Shuqi An, Xiaohan Yuan, Yuwen Lu","doi":"10.1145/3459104.3459116","DOIUrl":"https://doi.org/10.1145/3459104.3459116","url":null,"abstract":"The multistep prediction of new Corona Virus Disease (COVID-19) cases plays a vital role during the epidemic control period, and the Long Short-Term Memory (LSTM) based time series analysis model is the most frequently used among many prediction methods. But whether it is the cumulative error of the multistep prediction or the instability of the new case data of the COVID-19 make the performance of LSTM in this task not so good. In this paper, we selected three countries with more severe COVID-19 epidemics—India, Russia, and Chile, to predict new cases in the next 15 days with different multistep LSTM network models, and use Bayesian Optimization to explore the optimal hyperparameter space. The results show that: a) the performance of Recursive Prediction LSTM is the best (Mean Absolute Percentage Error, MAPE was reduced to 14.88%, 6.46%, and 16.31% for the three countries respectively), Encoder Decoder LSTM is second (15.52%, 19.61%, 19.87%), and the effect of vector output LSTM is the worst (23.55%, 26.82%, 19.57%); b) there are obvious extremely poor areas in the hyperparameter space, and the Bayesian Optimizer can focus on the good areas to avoid cost of tuning parameters based on bad hyperparameters; c) the data of new cases of COVID-19 in different countries have great differences in the hyperparameter expectations for the model. The bad area of hyperparameters and different expectations are likely to be one of the reasons why the COVID-19 data of different countries is hard to train jointly.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133849853","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

Improving Consumer Experience for Medical Information Using Text Analytics 使用文本分析改善医疗信息的消费者体验

2021 International Symposium on Electrical, Electronics and Information Engineering Pub Date : 2021-02-19 DOI: 10.1145/3459104.3459182

P. Karmalkar, H. Gurulingappa, Justna Muhith, Shikha Singhal, Gerard Megaro, F. Buchholz

{"title":"Improving Consumer Experience for Medical Information Using Text Analytics","authors":"P. Karmalkar, H. Gurulingappa, Justna Muhith, Shikha Singhal, Gerard Megaro, F. Buchholz","doi":"10.1145/3459104.3459182","DOIUrl":"https://doi.org/10.1145/3459104.3459182","url":null,"abstract":"Detecting language nuances from unstructured data could be the difference in serving up the right Google search results or using unsolicited social media chatter to tap into unexplored customer behavior (patients and HCPs). However, as an established science, there is a slow adoption of NLP and Text Analytics in healthcare sector for analysis of unstructured textual data originating from customer interactions. One of the key areas of our exploration is the Medical Information function within our organization. We receive a significant amount of medical information inquires in the form of unstructured data through multiple communication channels. The current system of gathering insights takes significant time and effort – as information must be manually tagged and classified limiting the ability to drive insights and trends efficiently and in a timely manner. These limitations mean subject matter experts must spend time manually deducing insights and aligning with medical affairs – time that could be better spent elsewhere. Therefore, this article presents an approach using NLP & Text Analytics to generate valuable insights from unstructured medical information inquiries. The system automatically extracts key phrases, medical terms, themes, sentiments as well as leverages unsupervised statistical modeling for two-level categorization of inquiries. Results of NLP when analyzed with the aid of visual analytics tool highlighted non-obvious insights indicating the value it can generate to influence product strategies.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115195370","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 Tensor Formalism for Computer Science 计算机科学的张量形式化

2021 International Symposium on Electrical, Electronics and Information Engineering Pub Date : 2021-02-19 DOI: 10.1145/3459104.3459152

Jon Bratseth, H. Pettersen, L. Solbakken

{"title":"A Tensor Formalism for Computer Science","authors":"Jon Bratseth, H. Pettersen, L. Solbakken","doi":"10.1145/3459104.3459152","DOIUrl":"https://doi.org/10.1145/3459104.3459152","url":null,"abstract":"Over recent years, tensors have emerged as the preferred data structure for model representation and computation in machine learning. However, current tensor models suffer from a lack of a formal basis, where the tensors are treated as arbitrary multidimensional data processed by a large and ever-growing collection of functions added ad hoc. In this way, tensor frameworks degenerate to programming languages with a curiously cumbersome data model. This paper argues that a more formal basis for tensors and their computation brings important benefits. The proposed formalism is based on 1) a strong type system for tensors with named dimensions, 2) a common model of both dense and sparse tensors, and 3) a small, closed set of tensor functions, providing a general mathematical language in which higher level functions can be expressed. These features work together to provide ease of use resulting from static type verification with meaningful dimension names, improved interoperability resulting from defining a closed set of just six foundational tensor functions, and better support for performance optimizations resulting from having just a small set of core functions needing low-level optimizations, and higher-level operations being able to work on arbitrary chunks of these functions, as well as from better mathematical properties from using named tensor dimensions without inherent order. The proposed model is implemented as the model inference engine in the Vespa big data serving engine, where it runs various models expressed in this language directly, as well as models expressed in TensorFlow or Onnx formats.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124004183","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

Investigation on the Application of Structural Noise Bearing Capability Analysis Method in Airborne Radar Equipment 结构噪声承载能力分析方法在机载雷达设备中的应用研究

2021 International Symposium on Electrical, Electronics and Information Engineering Pub Date : 2021-02-19 DOI: 10.1145/3459104.3459107

Z. Gu, Zhigang Qin

引用次数: 0

Design and Evaluation of a Privacy-preserving Supply Chain System Based on Public Permissionless Blockchain 基于公共许可的隐私保护供应链系统设计与评价[j]

2021 International Symposium on Electrical, Electronics and Information Engineering Pub Date : 2021-02-19 DOI: 10.1145/3459104.3459155

Takio Uesugi, Yoshinobu Shijo, M. Murata

{"title":"Design and Evaluation of a Privacy-preserving Supply Chain System Based on Public Permissionless Blockchain","authors":"Takio Uesugi, Yoshinobu Shijo, M. Murata","doi":"10.1145/3459104.3459155","DOIUrl":"https://doi.org/10.1145/3459104.3459155","url":null,"abstract":"Securing the traceability of products in a supply chain is an urgent issue. Recently, supply-chain systems that use a blockchain have been proposed. In these systems, the blockchain is used as a common database shared among supply chain parties to secure the integrity and reliability of distribution information such as ownership transfer records. These systems thus secure a high level of traceability in the supply chain. Considering future scalability of supply chains, public permissionless blockchain (PPBC) is a promising approach. In this approach, however, distribution information that should be kept private is made public since the information recorded in PPBC can be read by anyone. We therefore propose a method for preserving privacy while securing traceability in a supply chain system using PPBC. The proposed method preserves privacy by concealing distribution information via encryption. In addition, the proposed method ensures distribution among legitimate supply chain parties while concealing their blockchain addresses by using zero-knowledge proofs.We implement the proposed method on Ethereum smart contracts and verify the system behavior. The results show that the proposed method works as expected, and that system usage cost per distribution party is at most 2.2 × 106 gas units in terms of blockchain transaction fees.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128882211","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: 4

Multiscale Diversity Index for RUL Analysis with Bernstein Polynomial Neural Networks Bernstein多项式神经网络RUL分析的多尺度多样性指数

2021 International Symposium on Electrical, Electronics and Information Engineering Pub Date : 2021-02-19 DOI: 10.1145/3459104.3459188

M. Landauskas, L. Saunoriene, M. Ragulskis

引用次数: 0

Exploring the Integration of Blockchain Technology and IoT in a Smart University Application Architecture 探索区块链技术与物联网在智慧大学应用架构中的融合

2021 International Symposium on Electrical, Electronics and Information Engineering Pub Date : 2021-02-19 DOI: 10.1145/3459104.3459153

Siphamandla Mjoli, N. Dlodlo

{"title":"Exploring the Integration of Blockchain Technology and IoT in a Smart University Application Architecture","authors":"Siphamandla Mjoli, N. Dlodlo","doi":"10.1145/3459104.3459153","DOIUrl":"https://doi.org/10.1145/3459104.3459153","url":null,"abstract":"The ecosystem inherent within currently deployed Internet of Things (IoT) systems is that of low-powered devices equipped with sensors that consume data. The data these devices collect is then stored in use-case specific applications, which are connected through application layer gateways that allow these devices to connect to third party cloud storage platforms for further processing. This stratified architecture has created data silos that introduce complexities such as limited user control and lack of solicitation regarding the usage of user data. The constant proliferation of IoT devices deployed in smart cities which include smart university campus (SUC) has resulted in the need for the development of IoT architecture models which are data-centric. In this paper a blockchain- based architecture model, and specifically, the distributed ledger inherent within the Ethereum blockchain, combined with the Proof Of Authority (POA) consensus mechanism, are proposed as a potential solution to developing a proof of concept architecture model that is data-centric. The proposed architecture model will be tested against with application specific use-cases in a simulated environment within the context of a SUC which is subsumed by a smart city.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":" 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113950932","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 Elastic Blockchain IoT-based Intelligent Edge-Fog Collaboration Computing Platform 基于弹性区块链物联网的智能边缘雾协同计算平台

2021 International Symposium on Electrical, Electronics and Information Engineering Pub Date : 2021-02-19 DOI: 10.1145/3459104.3459178

M. Muneeb, Su-Chong Joo, Gyu-Sung Ham, Kwangman Ko

引用次数: 0