2020 International Conference on Systems, Signals and Image Processing (IWSSIP)最新文献_第3页

Identification and Classification of Corrupted Signals for the Neutrinos Angra Experiment 安格拉中微子实验中干扰信号的识别与分类

2020 International Conference on Systems, Signals and Image Processing (IWSSIP) Pub Date : 2020-07-01 DOI: 10.1109/IWSSIP48289.2020.9145375

M. Migliorini, A. Cerqueira, I. A. Costa, A. Fernandes, G. Lopes, A. S. Lopes, R. Nobrega, I. F. Pains, D. M. Souza, Herman P. Lima Júnior, J. Anjos, P. Chimenti, L. Gonzalez, E. Kemp, I. Pepe, D. Ribeiro, G. Guedes

{"title":"Identification and Classification of Corrupted Signals for the Neutrinos Angra Experiment","authors":"M. Migliorini, A. Cerqueira, I. A. Costa, A. Fernandes, G. Lopes, A. S. Lopes, R. Nobrega, I. F. Pains, D. M. Souza, Herman P. Lima Júnior, J. Anjos, P. Chimenti, L. Gonzalez, E. Kemp, I. Pepe, D. Ribeiro, G. Guedes","doi":"10.1109/IWSSIP48289.2020.9145375","DOIUrl":"https://doi.org/10.1109/IWSSIP48289.2020.9145375","url":null,"abstract":"The Neutrinos Angra Experiment aims at monitoring nuclear plants by detecting antineutrino particles coming out from its fuel burn-up process. The Neutrinos Angra Collaboration developed a fully-equipped detector to accomplish this task. It is currently in operation on the surface and next to the dome of the Angra II nuclear reactor. Selecting antineutrinos events on the surface is a challenge task due to the high level of background noise produced by cosmic ray particles. One of the main parameters used to select antineutrino events is the number of photons acquired by the detector's sensors. This quantity is estimated based on the signals generated at the output of the readout electronics. If any of those signals is corrupted, the estimation fails, compromising the Experiment performance. This work proposes a study of the performance of some classifier algorithms applied to identify corrupted signals for the Neutrinos Angra Experiment. If corrupted signals can be identified, they could go through a recovering process in order to improve the Experiment's events-selection algorithms.","PeriodicalId":406449,"journal":{"name":"2020 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131717567","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 Methodology for Taxi Demand Prediction Using Stream Learning 基于流学习的出租车需求预测方法

2020 International Conference on Systems, Signals and Image Processing (IWSSIP) Pub Date : 2020-07-01 DOI: 10.1109/IWSSIP48289.2020.9145097

David Faial, F. Bernardini, E. M. Meza, Leandro Miranda, J. V. Filho

{"title":"A Methodology for Taxi Demand Prediction Using Stream Learning","authors":"David Faial, F. Bernardini, E. M. Meza, Leandro Miranda, J. V. Filho","doi":"10.1109/IWSSIP48289.2020.9145097","DOIUrl":"https://doi.org/10.1109/IWSSIP48289.2020.9145097","url":null,"abstract":"Intelligent transport support systems have had a major impact on people's urban mobility. In large urban centers, transportation services still need ways to optimize vehicle supply in certain areas, according to the demand in each of them. Optimized distribution of on-demand taxi services can be part of an intelligent urban mobility plan, causing direct impacts on urban traffic, improving transport accessibility, improving safety at taxi standpoints by reduced waiting times, reduce transportation fare etc. Many vehicle-mounted sensors currently generate real-time information that is not used for processing and generating information with value. This paper proposes a Taxi Demand Forecasting methodology using stream machine learning algorithms that tackle concept drift detection on taxi data stream. A real data source made available on the New York open platform feeds a stream learning model, constructed using the Massive Online Analysis (MOA) tool - a framework for data stream mining. The stream model shows promising results in forecasting taxi demand, reaching 78% accuracy. Despite using data from a specific city, the methodology and results of this work can contribute to a more proactive demand management in other cities.","PeriodicalId":406449,"journal":{"name":"2020 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131756880","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

Design of a full polarimetric GPR system for landmine detection 地雷探测全极化探地雷达系统的设计

2020 International Conference on Systems, Signals and Image Processing (IWSSIP) Pub Date : 2020-07-01 DOI: 10.1109/IWSSIP48289.2020.9145096

D. Šipoš, D. Gleich

引用次数: 4

BEM: A Framework based on Business Intelligence, Quality of Experience, and Car Park Management BEM:基于商业智能、体验质量和停车场管理的框架

2020 International Conference on Systems, Signals and Image Processing (IWSSIP) Pub Date : 2020-07-01 DOI: 10.1109/IWSSIP48289.2020.9145442

A. S. Araújo, Bruno Câmara, Flavio Docek, Lucas Gaspar, Yona Lopes

引用次数: 0

Blank Page 空白页

2020 International Conference on Systems, Signals and Image Processing (IWSSIP) Pub Date : 2020-07-01 DOI: 10.1109/iwssip48289.2020.9145386

引用次数: 0

Interpretability of Machine Learning Models: Application for Lawsuits Prediction in the Energy Sector 机器学习模型的可解释性:在能源部门诉讼预测中的应用

2020 International Conference on Systems, Signals and Image Processing (IWSSIP) Pub Date : 2020-07-01 DOI: 10.1109/iwssip48289.2020.9145141

A. B. Cavalcante

引用次数: 1

Comparing the Degeneration of the Corpus Callosum by Magnetic Resonance Images 胼胝体退行性变的磁共振影像比较

2020 International Conference on Systems, Signals and Image Processing (IWSSIP) Pub Date : 2020-07-01 DOI: 10.1109/IWSSIP48289.2020.9145454

A. Falco, A. Conci

引用次数: 0

Mask Overlaying: a Deep Learning Approach for Individual Optic Cup Segmentation from Fundus Image 掩模叠加:一种基于眼底图像的光学杯分割的深度学习方法

2020 International Conference on Systems, Signals and Image Processing (IWSSIP) Pub Date : 2020-07-01 DOI: 10.1109/IWSSIP48289.2020.9145459

Arthur Azevedo Lima, Alana C. de Carvalho Araújo, A. C. M. Lima, J. A. Sousa, J. Almeida, A. Paiva, G. B. Junior

引用次数: 2

Analysis of Non-Conformity in Flexible Pipe through Data Mining from Image Bank 基于图像库数据挖掘的柔性管道不合格分析

2020 International Conference on Systems, Signals and Image Processing (IWSSIP) Pub Date : 2020-07-01 DOI: 10.1109/IWSSIP48289.2020.9145256

C. Teixeira, Simone Vasconçelos Silva, A. Neto

{"title":"Analysis of Non-Conformity in Flexible Pipe through Data Mining from Image Bank","authors":"C. Teixeira, Simone Vasconçelos Silva, A. Neto","doi":"10.1109/IWSSIP48289.2020.9145256","DOIUrl":"https://doi.org/10.1109/IWSSIP48289.2020.9145256","url":null,"abstract":"To make possible the exploration of oil and natural gas in maritime waters, it is necessary to develop high technology to support the projects of drilling and exploration of submarine wells. One of the equipment that enables offshore exploration is the flexible pipes. Considering the high cost and complexity of the flexible pipe manufacturing process, the objective of this work is to analyze the effect of the occurrence of whitening stress identified as bleaching observed in the polymeric material known as Polyfluoride of Vinylidene (PVDF), which is used in the manufacture of inner liner layers in flexible pipes. The proposed methodology is to develop a prediction model based on classification, which evaluates the whitening bleaching by extracting knowledge from an image database. Through the proposed methodology, the most relevant parameters associated with the study problem that can define classification rules areidentified. As a result, some relationships between some characters, fruits of image data extraction and product characteristics were identified through decision trees. The conclusion is that these relationships provides support for decision making when peformed by a domain expert.","PeriodicalId":406449,"journal":{"name":"2020 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127223152","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

Energy Reconstruction Performance in the ATLAS Tile Calorimeter Operating at High Event Rate Conditions Using LHC Collision Data 利用大型强子对撞机碰撞数据在高事件速率条件下运行的ATLAS瓷砖量热计的能量重构性能

2020 International Conference on Systems, Signals and Image Processing (IWSSIP) Pub Date : 2020-07-01 DOI: 10.1109/IWSSIP48289.2020.9145451

J. Marin

{"title":"Energy Reconstruction Performance in the ATLAS Tile Calorimeter Operating at High Event Rate Conditions Using LHC Collision Data","authors":"J. Marin","doi":"10.1109/IWSSIP48289.2020.9145451","DOIUrl":"https://doi.org/10.1109/IWSSIP48289.2020.9145451","url":null,"abstract":"The discovery of particles that shape our universe pushes the scientific community to increasingly build sophisticated equipments. Particle accelerators are one of these complex machines that put known particle beams on a collision course at speeds close to that of light. The Large Hadron Collider (LHC) is the world's largest and most powerful beam collider, operating with 13 TeV of energy collision and 25 ns of bunch-crossing interval. ATLAS is the largest LHC experiment, comprising several subsystems which provide data fusion to reconstruct each collision. When collisions occur, subproducts are produced and measured by the calorimeter system, which absorbs these subproducts. Typically, a high-energy calorimeter is highly segmented, comprising thousands of dedicated readout channels. The present work evaluates the performance of two cell energy reconstruction algorithms that operate in the ATLAS Tile Calorimeter (TileCal): the baseline algorithm OF2 (Optimal Filter) and COF (Constrained Optimal Filter), which was recently proposed to deal with the signal superposition (pile-up) that is, increscent, present in LHC operation. In order to evaluate the energy estimation efficiency, real data acquired during the nominal LHC operation at high luminosity condition were used. The statistics from the energy estimation is employed to compare the performance achieved by each method. The results show that the COF method presents a better performance than the OF2 method, pointing out benefits from using this alternative estimation method.","PeriodicalId":406449,"journal":{"name":"2020 International Conference on Systems, Signals and Image Processing (IWSSIP)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114141706","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