2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)最新文献_第4页

Filters in Michálek's Fuzzy Topological Spaces Michálek模糊拓扑空间中的过滤器

2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO) Pub Date : 2019-05-01 DOI: 10.1109/iccairo47923.2019.00016

F. Lupiáñez

引用次数: 0

Developing a System Dynamics Model for Creating a Learning Sustainable Mobility Culture 建立一个系统动力学模型来创造一个学习可持续的流动文化

2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO) Pub Date : 2019-05-01 DOI: 10.1109/ICCAIRO47923.2019.00037

George Papageorgiou, G. Demetriou

{"title":"Developing a System Dynamics Model for Creating a Learning Sustainable Mobility Culture","authors":"George Papageorgiou, G. Demetriou","doi":"10.1109/ICCAIRO47923.2019.00037","DOIUrl":"https://doi.org/10.1109/ICCAIRO47923.2019.00037","url":null,"abstract":"This paper examines the concepts of learning and diffusion within the context of sustainable mobility and urban development. A System Dynamics (SD) model is proposed, which investigates plausible strategies that can change the mindsets of people towards active mobility. Treating the learning process as a diffusion control process for changing mindsets, is central to the development of the model. Specifically, awareness strategies are investigated as well as introducing Information and Communication Technology (ICT) in a computer simulated environment. The simulation results show that changing mindsets requires time in order to go through the process of knowledge, persuasion, decision, implementation and confirmation which is influenced by the formulated strategies. Carrying out a sensitivity analysis on the various parameters, it was revealed that for changing mindsets effectively, an awareness strategy should be reinforced with the use of an ICT strategy at specific time intervals, during the diffusion process. Optimization on minimizing the required time for developing a sustainable mobility culture is carried out. Such results would be of great use for policy makers interested to promote sustainable mobility such as walking, since their decisions can be tested prior to implementation.","PeriodicalId":297342,"journal":{"name":"2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114553267","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

BioPortal Ontologies Integration with SNOMED CT, RxNORM & GO Datasets 生物门户本体与SNOMED CT, RxNORM和GO数据集的集成

2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO) Pub Date : 2019-05-01 DOI: 10.1109/ICCAIRO47923.2019.00034

Artemis Chaleplioglou, S. Papavlasopoulos, M. Poulos

{"title":"BioPortal Ontologies Integration with SNOMED CT, RxNORM & GO Datasets","authors":"Artemis Chaleplioglou, S. Papavlasopoulos, M. Poulos","doi":"10.1109/ICCAIRO47923.2019.00034","DOIUrl":"https://doi.org/10.1109/ICCAIRO47923.2019.00034","url":null,"abstract":"BioPortal, the open repository of biomedical ontologies, represents one of the most popular portals for both researchers and practitioners in the Linked Data environment. The BioPortal ontologies contain concepts, relationships, rules and functions to infer the knowledge from various data resources. Solutions of complex biomedical queries is based on the interplay between three types of ontologies: (i) clinical, modelled by SNOMED CT, (ii) pharmacological, modelled by RxNORM, and (iii) genetic, modelled by GO. To explore the degree of integration of BioPortal Ontologies with SNOMED CT, RxNORM and GO ontologies, we collected the BioPortal links and analyzed their connections by descriptive statistics, graphical analysis and agglomerative hierarchical clustering. Whilst nearly all the BioPortal ontologies share links with SNOMED CT, only a quarter out of total share links with RxNORM and only a third out of total share links with GO. A fraction of 3.5% of BioPortal ontologies share links with both RxNORM and GO. Cluster analysis revealed the pattern of ontologies relationships with respect to their links to the SNOMED CT, RxNORM and GO triptych. The NIH, cell biology, pharmacology and chemistry, medical diagnostic and procedure, as well as bibliographic ontologies are clustering together into different subgroups. Collectively, our data suggest, the need for development or enrichment of ontologies connecting all three SNOMED CT, RxNORM and GO. We proposed the usefulness of cluster analysis of linked data to facilitate the selection of closely related ontologies for reuse by the developers.","PeriodicalId":297342,"journal":{"name":"2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134406609","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

Design and Performance Comparison of CNN Accelerators Based on the Intel Movidius Myriad2 SoC and FPGA Embedded Prototype 基于Intel Movidius Myriad2 SoC与FPGA嵌入式样机的CNN加速器设计与性能比较

2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO) Pub Date : 2019-05-01 DOI: 10.1109/ICCAIRO47923.2019.00030

A. Kyriakos, E. Papatheofanous, Bezaitis Charalampos, Evangelos Petrongonas, D. Soudris, D. Reisis

引用次数: 4

Finding the Shortest Paths in Izmir Map by Using Slime Molds Images 利用黏菌图像在伊兹密尔地图上找到最短路径

2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO) Pub Date : 2019-05-01 DOI: 10.1109/ICCAIRO47923.2019.00039

Tayfun Topuzoglu, G. Köktürk, D. Altun, A. Şendemir, Ozge Andic Cakır, A. Tokuç, Feyzal Ozkaban

引用次数: 0

Attention-Based Curiosity in Multi-Agent Reinforcement Learning Environments 多智能体强化学习环境中基于注意的好奇心

2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO) Pub Date : 2019-05-01 DOI: 10.1109/ICCAIRO47923.2019.00035

Marton Szemenyei, Patrik Reizinger

引用次数: 6

Adaptive Forecasting Techniques Applied to Short Time Wind Speed Forecasting 自适应预报技术在短时风速预报中的应用

2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO) Pub Date : 2019-05-01 DOI: 10.1109/ICCAIRO47923.2019.00027

S. Pappas

{"title":"Adaptive Forecasting Techniques Applied to Short Time Wind Speed Forecasting","authors":"S. Pappas","doi":"10.1109/ICCAIRO47923.2019.00027","DOIUrl":"https://doi.org/10.1109/ICCAIRO47923.2019.00027","url":null,"abstract":"Climate change and the increased level of power demand has led to a growing electrical energy production from renewable sources, such as wind power. The main problem associated with wind power production is the nature of the wind speed which is random and non linear. This is a reason why wind speed forecasting is a difficult but crucial task, since its accuracy plays a significant role in achieving reliable and autonomous power production and at the same time contributes in surpassing a series problems, of economic and technical nature. In this study real data is used and the performance of three different techniques for adaptive short term wind speed forecasting are evaluated. The first method combines the multimodel partitioning filter (MMPF) implementing extended Kalman filters (EKF) with Support Vector Machines (SVM), the second is a hybrid method of MMPF and Genetic Algorithms (G.A) and the last method implements an artificial multilayer layer feed-forward neural network (ANN). It should be noted that the first two techniques having the structure presented in this work, have never been tested before on short term wind speed prediction. The results indicate that all three methods are reliable, however the combination of MMPF and SVM provides a more accurate wind speed forecasting. Therefore, the proposed method strengthens the prediction precision, and becomes a significant tool for efficient grid planning.","PeriodicalId":297342,"journal":{"name":"2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122114963","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 Bayesian Artificial Neural Networks for Modeling the Dependence of Nickel-Based Superalloys' Ultimate Tensile Strength on Their Chemical Composition 应用贝叶斯人工神经网络模拟镍基高温合金抗拉强度随化学成分的变化规律

2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO) Pub Date : 2019-05-01 DOI: 10.1109/ICCAIRO47923.2019.00018

D. Tarasov, O. Milder, A. Tyagunov

{"title":"Application of Bayesian Artificial Neural Networks for Modeling the Dependence of Nickel-Based Superalloys' Ultimate Tensile Strength on Their Chemical Composition","authors":"D. Tarasov, O. Milder, A. Tyagunov","doi":"10.1109/ICCAIRO47923.2019.00018","DOIUrl":"https://doi.org/10.1109/ICCAIRO47923.2019.00018","url":null,"abstract":"Nickel-based superalloys are unique high-temperature materials with complex doping, used, in particular, in gas-turbine engines. These materials exhibit excellent resistance to mechanical and chemical degradation. The main service property of the alloy is its heat resistance, which is expressed, in particular, by the ultimate tensile strength (UTS). When determining the service life of a superalloy product, the developers investigate only certain combinations of temperature parameters and exposure time. The availability of data on the properties of alloys over the entire range of temperatures and time exposures would greatly expand the possibilities of alloys application and would allow more accurate assessment and comparison of alloys. We applied the Bayesian regularized artificial neural network to simulate the missing UTS values for more than 300 well-known superalloys. Network input parameters are the chemical composition and tensile test conditions. Special data pre-processing and a developed learning algorithm significantly reduced the model prediction error. Comparison of the predicted and experimental data showed excellent convergence. A model check was performed on a test data set (10 alloys), which was combined from samples that were not involved in network training.","PeriodicalId":297342,"journal":{"name":"2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128299717","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 Generic Multi-Service Cloud-Based IoT Operational Platform - EMULSION 基于云的通用多业务物联网运营平台——EMULSION

2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO) Pub Date : 2019-05-01 DOI: 10.1109/ICCAIRO47923.2019.00024

Ivan Ganchev, Zhanlin Ji, M. O'Droma

引用次数: 8

Dynamic Mixture Ratio Model 动态混合比模型

2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO) Pub Date : 2019-05-01 DOI: 10.1109/ICCAIRO47923.2019.00023

Marko Ruman, M. Kárný

引用次数: 3