2020 27th Conference of Open Innovations Association (FRUCT)最新文献_第4页

Towards a 5G Communication Architecture for the Internet of Musical Things 面向音乐物联网的5G通信架构

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9210980

Marco Centenaro, P. Casari, L. Turchet

引用次数: 10

Problem of Cybersecurity in Context of Medical Information System «Register of Palliative Patients» 医疗信息系统背景下的网络安全问题«姑息病人登记»

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9211033

E. Menshikova, Gennady S. Sigovtsev, Marina Charuta

{"title":"Problem of Cybersecurity in Context of Medical Information System «Register of Palliative Patients»","authors":"E. Menshikova, Gennady S. Sigovtsev, Marina Charuta","doi":"10.23919/fruct49677.2020.9211033","DOIUrl":"https://doi.org/10.23919/fruct49677.2020.9211033","url":null,"abstract":"The project of a special purpose medical information system for use in the field of palliative care “Register of palliative patients” is proposed. The project provides that the system should have the following basic functionality: providing system administration; maintaining a patient register; searching for patient data by specified parameters; maintaining a patient’s medical record including information about prescriptions; searching for prescriptions by specified parameters; generating summary reports and reports for a group of prescriptions. The prototype of the system, presented by its structural-functional and informational models, and its implementation are described. The cybersecurity issues of MISs are analyzed in terms of meeting regulatory requirements. An initial protection level of the «Palliative Patient Register» system was assessed, and the most relevant threats were identified to build a threat model. A scheme for ensuring information security was proposed. A model of data protection in the system based on the exchange of only anonymized personal data between the client and the server is proposed. To do this, we suggest using cryptographic security tools. The General scheme of interaction between the client and server using the REST architecture is described. The possibilities of the Yii framework for implementing the RestFull API are considered.","PeriodicalId":149674,"journal":{"name":"2020 27th Conference of Open Innovations Association (FRUCT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128660334","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

The Influence of Different Stylometric Features on the Classification of Prose by Centuries 不同文体特征对历代散文分类的影响

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9211036

K. Lagutina, N. Lagutina, E. Boychuk, I. Paramonov

引用次数: 6

AI-Based Driving Data Analysis for Behavior Recognition in Vehicle Cabin 基于人工智能的车辆驾驶室行为识别驾驶数据分析

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9211020

Friedrich Lindow, C. Kaiser, A. Kashevnik, A. Stocker

{"title":"AI-Based Driving Data Analysis for Behavior Recognition in Vehicle Cabin","authors":"Friedrich Lindow, C. Kaiser, A. Kashevnik, A. Stocker","doi":"10.23919/fruct49677.2020.9211020","DOIUrl":"https://doi.org/10.23919/fruct49677.2020.9211020","url":null,"abstract":"Driving a vehicle is an indispensable part of their everyday life for many people. However, sometimes this everyday life does not go as expected, as a lot of accidents happen on the public roads, and most of these accidents are due to inattentive driver behavior. Modern driver monitoring systems evaluate driver behavior by means of distinctive sensor technology and, if necessary, indicate undesirable driving behavior. However, many roadworthy vehicles do not have the possibility to implement such systems. Therefore, it seems to be interesting to investigate the implementation of such systems based on commodity hardware, e.g., smartphones, because nowadays almost every driver has a powerful smartphone equipped with many sensors at hand in the vehicle. Furthermore, recent advances in Machine Learning (ML) made it possible to analyze large amounts of data and to generate new outcomes. In this work we discuss how ML can be used for driver behavior recognition by improving an already existing threshold-based driver monitoring system with different ML-based techniques, Neural Networks and Random Forests, and evaluate their performance. We propose to use Microsoft Azure platform to analyze data generated by a Driver Monitoring System (DMS). Our results indicate ML as a useful technique for learning and adapting threshold-based reasoning about individual drivers’ states.","PeriodicalId":149674,"journal":{"name":"2020 27th Conference of Open Innovations Association (FRUCT)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122738173","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: 8

A Deep Learning Approach for Low-Latency Packet Loss Concealment of Audio Signals in Networked Music Performance Applications 网络音乐表演应用中音频信号低延迟丢包隐藏的深度学习方法

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-07-14 DOI: 10.23919/fruct49677.2020.9210988

Prateek Verma, Alessandro Ilic Mezza, C. Chafe, C. Rottondi

{"title":"A Deep Learning Approach for Low-Latency Packet Loss Concealment of Audio Signals in Networked Music Performance Applications","authors":"Prateek Verma, Alessandro Ilic Mezza, C. Chafe, C. Rottondi","doi":"10.23919/fruct49677.2020.9210988","DOIUrl":"https://doi.org/10.23919/fruct49677.2020.9210988","url":null,"abstract":"Networked Music Performance (NMP) is envisioned as a potential game changer among Internet applications: it aims at revolutionizing the traditional concept of musical interaction by enabling remote musicians to interact and perform together through a telecommunication network. Ensuring realistic conditions for music performance, however, constitutes a significant engineering challenge due to extremely strict requirements in terms of audio quality and, most importantly, network delay. To minimize the end-to-end delay experienced by the musicians, typical implementations of NMP applications use uncompressed, bidirectional audio streams and leverage UDP as transport protocol. Being connectionless and unreliable, audio packets transmitted via UDP which become lost in transit are not retransmitted and thus cause glitches in the receiver audio playout. This article describes a technique for predicting lost packet content in real-time using a deep learning approach. The ability of concealing errors in real time can help mitigate audio impairments caused by packet losses, thus improving the quality of audio playout in realworld scenarios.","PeriodicalId":149674,"journal":{"name":"2020 27th Conference of Open Innovations Association (FRUCT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128262906","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: 10

FRUCT 2020 Preface frut 2020前言

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-04-01 DOI: 10.23919/fruct48808.2020.9087404

引用次数: 0