2020 27th Conference of Open Innovations Association (FRUCT)最新文献_第2页

Smart Spaces Middleware: A Requirement-Oriented Overview 智能空间中间件:面向需求的概述

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9211076

Sergey A. Marchenkov, D. Korzun

引用次数: 1

Comparing Statistical Measures for Discovering Emerging Terms in Scopus Publications in the Area of Decision Support in Smart City 比较在智慧城市决策支持领域的Scopus出版物中发现新兴术语的统计方法

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9211000

N. Shilov, Nikolay Teslia

引用次数: 1

Reducing of Bioimpedance Influence on ECG by Correction Filter in Mobile Heart Monitoring System 用校正滤波器降低移动心电监测系统中生物阻抗对心电的影响

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9211026

M. Safronov, A. Kuzmin, O. Bodin, V. Baranov, O. Timokhina, O. Cheban

引用次数: 1

Evolutionary optimization of Drone Trajectories Based on Optimal Reciprocal Collision Avoidance 基于最优互避的无人机轨迹进化优化

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9211037

A. Bojeri, Giovanni Iacca

{"title":"Evolutionary optimization of Drone Trajectories Based on Optimal Reciprocal Collision Avoidance","authors":"A. Bojeri, Giovanni Iacca","doi":"10.23919/fruct49677.2020.9211037","DOIUrl":"https://doi.org/10.23919/fruct49677.2020.9211037","url":null,"abstract":"In recent years, the advent of new hardware and software technologies for navigation and control has made Unmanned Aerial Vehicles (UAVs) ever more autonomous and efficient. As a consequence, it is now possible to have drones moving within complex environments, such as cities or indoor areas. One of the main requirements for intelligent mission planning in such environments is the ability to correctly and efficiently detect and avoid obstacles. For this reason, various libraries have been created for the simulation of UAV navigation in virtual environments, in order to test algorithms for automatic obstacle detection and collision avoidance before deploying the drones in the real world. Usually, the performance of these algorithms depends on various parameters as well as specific application settings. However, while different parameter configurations can be easily tested in simulation, their number can be too large to allow a complete exploration of the parameter space or a manual tuning. Furthermore, a full analytical model of the parameters’ influence on the algorithmic performance can be hard to obtain. Yet, it is extremely important to find their optimal values to allow collision-free navigation. In this direction, we propose here a thorough exploration, based on an Evolutionary Algorithm (EA), of the parameter space of the Optimal Reciprocal Collision Avoidance (ORCA) algorithm. Our results show that the proposed EA is a viable solution for finding optimal parameter settings that can be generalizable to different scenarios characterized by different complexity levels.","PeriodicalId":149674,"journal":{"name":"2020 27th Conference of Open Innovations Association (FRUCT)","volume":"13 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":"130493028","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

Transparent Communication Within Multiplicities 多样性中的透明通信

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9210989

Angelo Fraietta, O. Bown, Sam Ferguson

{"title":"Transparent Communication Within Multiplicities","authors":"Angelo Fraietta, O. Bown, Sam Ferguson","doi":"10.23919/fruct49677.2020.9210989","DOIUrl":"https://doi.org/10.23919/fruct49677.2020.9210989","url":null,"abstract":"The Internet of Musical Things is an emerging field of research that intersects the Internet of Things, humancomputer interaction, ubiquitous music, artificial intelligence, gaming, virtual reality and participatory art through device multiplicity. This paper introduces a paradigm whereby data points and variable parameters can be strategically mapped or bound using aliases, data types and scoping as an alternative to flat address-structured mapping. The ability to send and/or access complex data types as complete entities rather than lists of parameters promotes data abstraction and encapsulation, allowing greater flexibility through modular architecture as underlying data structures can change during the lifestyle or evolution of a computer based composition. Additionally, the facility to define data accessibility, and the ability to reuse human readable names based on a variable’s scope is a common feature of most programming languages. This paradigm has been extended in that scoping a variable can be dynamically bound or addressed to specific objects, class types, devices or globally on an entire network. We describe the evolution of this paradigm through its development via various project requirements.","PeriodicalId":149674,"journal":{"name":"2020 27th Conference of Open Innovations Association (FRUCT)","volume":"1 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":"122114023","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

Human-Machine Collective Intelligence Environment for Decision Support: Conceptual and Technological Design 决策支持的人机集体智能环境:概念与技术设计

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9211077

A. Smirnov, A. Ponomarev

引用次数: 5

Measures of Syntactic Complexity and their Change over Time (the Case of Russian) 句法复杂性的度量及其随时间的变化(以俄语为例)

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9211027

Tatiana Y. Sherstinova, Evgenia Ushakova, Aleksey Mel'nik

{"title":"Measures of Syntactic Complexity and their Change over Time (the Case of Russian)","authors":"Tatiana Y. Sherstinova, Evgenia Ushakova, Aleksey Mel'nik","doi":"10.23919/fruct49677.2020.9211027","DOIUrl":"https://doi.org/10.23919/fruct49677.2020.9211027","url":null,"abstract":"Syntactic complexity is an important feature of any text, both written and oral. The information about syntactic complexity is crucial for successful solution of many practical NLP tasks starting from intellectual understanding of texts and ending with automatic machine translation. Because of this, syntactic complexity and its measures are in the center of attention of NLP developers. Thus far, quite a series of different measures of syntactic complexity have been developed; in this paper, it is proposed to consider 10 syntactic measures that have been proposed for syntactic stylometric analysis. The pilot experiment described in this paper was made on automatic syntactic text annotation made by UDPipe syntactic parser, which was manually corrected. In our approach, particular attention is paid to the analysis of stability of certain measures of syntactic complexity and the analysis of their variation. Thus, we try to evaluate, which syntactic properties of Russian texts may be considered as inherent for the language as a whole, and which of them undergo some changes. To achieve this task, we analyze the corpus of Russian literary texts for three decades. Due to their high stylistic variability, texts of fiction may be considered as excellent data for assessing different levels of complexity. The obtained results show the effectiveness of different measures for estimating text syntactic complexity and revealing their correlation.","PeriodicalId":149674,"journal":{"name":"2020 27th Conference of Open Innovations Association (FRUCT)","volume":"1 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":"129292563","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: 6

Comparative Assessment of Data Augmentation for Semi-Supervised Polyphonic Sound Event Detection 半监督复调声事件检测中数据增强的比较评价

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9211023

L. Delphin-Poulat, R. Nicol, C. Plapous, K. Peron

{"title":"Comparative Assessment of Data Augmentation for Semi-Supervised Polyphonic Sound Event Detection","authors":"L. Delphin-Poulat, R. Nicol, C. Plapous, K. Peron","doi":"10.23919/fruct49677.2020.9211023","DOIUrl":"https://doi.org/10.23919/fruct49677.2020.9211023","url":null,"abstract":"In the context of audio ambient intelligence systems in Smart Buildings, polyphonic Sound Event Detection aims at detecting, localizing and classifying any sound event recorded in a room. Today, most of models are based on Deep Learning, requiring large databases to be trained. We propose a CRNN system exploiting unlabeled data with semi-supervised learning based on the “Mean teacher” method, in combination with data augmentation to overcome the limited size of the training dataset and to further improve the performances. This model was submitted to the challenge DCASE 2019 and was ranked second out of 58 systems submitted. In the present study, several conventional solutions of data augmentation are compared: time or frequency shifting, and background noise addition. It is shown that data augmentation with time shifting and noise addition, in combination with class-dependent median filtering, improves the performance by 9%, leading to an event-based F1-score of 43.2% with DCASE 2019 validation set. However, these tools rely on a coarse modelling (i.e. random variation of data) of intra-class variability observed in real life. Injecting acoustic knowledge into the design of augmentation methods seems to be a promising way forward, leading us to propose strategies of physics-inspired modelling for future work.","PeriodicalId":149674,"journal":{"name":"2020 27th Conference of Open Innovations Association (FRUCT)","volume":"50 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":"131757819","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

Towards a Retrospective One-Class Oriented Approach to Parents Detection in Social Media 社交媒体中家长检测的回溯性单班导向方法

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9211021

Alexander Egorov, T. Sokhin, N. Butakov

{"title":"Towards a Retrospective One-Class Oriented Approach to Parents Detection in Social Media","authors":"Alexander Egorov, T. Sokhin, N. Butakov","doi":"10.23919/fruct49677.2020.9211021","DOIUrl":"https://doi.org/10.23919/fruct49677.2020.9211021","url":null,"abstract":"Social media is the source of data for different purposes: advertisement, social study, human recruiting. However, usually, we are limited to readily available, structured information: age, gender, education, occupation. We have to work with unstructured data such as texts related to a user if we want to extract more complex, implicit features. We show the case of complex user analysis in social media using textual data. The task we solve is detecting parents on social networks. Our approach works with content that is not generated by a user, but with the content, the user was interested in implicitly - the user liked, or explicitly - the user subscribed to a group, where the content was published. In this paper, we compare classification methods for the task of parents detection on social media. Using mentioned above user’s likes and other information it is required to estimate chances if a user has got a child or children already or not. This task is an example of positive-unlabeled learning: data from social networks and media may contain explicit signals about users’ parenthood but there is no ground to make a backward conclusion. It can be considered as a case of look-a-like modelling or in other words a one-class classification problem. We propose a retrospective approach that can exploit data from social media to allow building a binary classifier. We compare both these approaches and conclude that the retrospective approach albeit requiring more efforts to be implemented may yield better results. This approach may be useful in similar tasks having look-a-like problem statement.","PeriodicalId":149674,"journal":{"name":"2020 27th Conference of Open Innovations Association (FRUCT)","volume":"35 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":"129602601","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

Flexible Charging Using Edge Computing 使用边缘计算灵活收费

2020 27th Conference of Open Innovations Association (FRUCT) Pub Date : 2020-09-01 DOI: 10.23919/fruct49677.2020.9211025

E. Pencheva, I. Atanasov, D. Velkova

引用次数: 0