2021 IEEE International Conference on Electro Information Technology (EIT)最新文献_第4页

A Survey of Machine Learning Approach to Software Cost Estimation 软件成本估算中的机器学习方法综述

2021 IEEE International Conference on Electro Information Technology (EIT) Pub Date : 2021-05-14 DOI: 10.1109/EIT51626.2021.9491912

Farhad Akhbardeh, H. Reza

引用次数: 2

Teaching Vehicles to Steer Themselves with Deep Learning 用深度学习教学车辆自动驾驶

2021 IEEE International Conference on Electro Information Technology (EIT) Pub Date : 2021-05-14 DOI: 10.1109/EIT51626.2021.9491894

Ian Timmis, Nicholas Paul, C. Chung

{"title":"Teaching Vehicles to Steer Themselves with Deep Learning","authors":"Ian Timmis, Nicholas Paul, C. Chung","doi":"10.1109/EIT51626.2021.9491894","DOIUrl":"https://doi.org/10.1109/EIT51626.2021.9491894","url":null,"abstract":"Traditional approaches for steering a vehicle using machine vision require large amounts of robust hand-crafted software which is both time consuming and expensive. The presented method uses a deep neural network to teach cars to steer themselves without any additional software. We created a labeled dataset for the ACTor (Autonomous Campus TranspORt) electric vehicle by pairing real world images taken during a drive with the associated steering wheel angle. We trained a model end to end using modern deep learning techniques including convolutional neural networks and transfer learning to automatically detect relevant features in the input and provide a predicted output. This means that no traditional hand engineered algorithm features were required for this implementation. We currently use an pretrained inception network on the ImageNet dataset to leverage the high level features learned from ImageNet to the steering problem through transfer learning. We removed the top portion of the network and replaced it with a linear regression node to provide the output. The model is trained end to end using backpropagation. The trained model is integrated with vehicle software on ROS (Robot Operating System) to read image data and provide a corresponding steering angle in real time. The current model achieves 15.2 degree error on average. As development continues the model may replace the current lane centering software and will be used for IGVC Self-Drive competition and campus transportation.","PeriodicalId":162816,"journal":{"name":"2021 IEEE International Conference on Electro Information Technology (EIT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122643772","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

Neural Networks Battery Applications: A Review 神经网络电池应用综述

2021 IEEE International Conference on Electro Information Technology (EIT) Pub Date : 2021-05-14 DOI: 10.1109/EIT51626.2021.9491835

Di Zhu, Gyouho Cho, J. Campbell

{"title":"Neural Networks Battery Applications: A Review","authors":"Di Zhu, Gyouho Cho, J. Campbell","doi":"10.1109/EIT51626.2021.9491835","DOIUrl":"https://doi.org/10.1109/EIT51626.2021.9491835","url":null,"abstract":"Neural network battery applications have drawn tremendous attention. However, recent review papers fail to reflect the popularity of research activities in this area. In addition, neural networks like many other machine learning techniques are data dependent. One neural network architecture may have a much better performance than another architecture in terms of prediction accuracy for a specific application. Therefore, it is crucial to select the neural network architecture based on the available data and the purpose of the application. A review reporting the latest activities regarding neural network battery application is in demand. We selected representative publications from three popular areas: SOC estimation, SOH prediction, and parameter identification. We examined these publications from the aspects such as neural network architectures, inputs, outputs, data requirements, and cell chemistries. We also compared advantages and disadvantages among numerous neural network architectures. Three research trends were found in our study. First, the neural network architecture is getting more and more complex. The complexity comes from either structuring same or different neural networks together or combining the neural network with other techniques. Secondly, more research attention is moving toward the architectures that are suitable for time-dependent applications. For non-RNN architectures, averaged data is used as inputs. Averaging the data allows the past information to be learned by the non-RNN architectures. For RNNs, the past information is carried over by feeding back as either an input or a state. Last, although researchers always try to explore properties other than voltage, current, and temperature, the final selected inputs always have voltage, current and temperature. In addition, voltage is the most important one among these three inputs.","PeriodicalId":162816,"journal":{"name":"2021 IEEE International Conference on Electro Information Technology (EIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126448124","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 Flow and Implementation of an IoT Smart Power Socket 物联网智能电源插座的设计流程与实现

2021 IEEE International Conference on Electro Information Technology (EIT) Pub Date : 2021-05-14 DOI: 10.1109/EIT51626.2021.9491841

C. Mateo, Fernando Almagro, Won-Jae Yi, J. Saniie

引用次数: 0

Security Issues of Mobile Devices: A Survey 移动设备的安全问题:调查

2021 IEEE International Conference on Electro Information Technology (EIT) Pub Date : 2021-05-14 DOI: 10.1109/EIT51626.2021.9491840

Gary Helm, M. Chowdhury

引用次数: 1

Simulation Testbeds and Frameworks for UAV Performance Evaluation 无人机性能评估仿真试验台与框架

2021 IEEE International Conference on Electro Information Technology (EIT) Pub Date : 2021-05-14 DOI: 10.1109/EIT51626.2021.9491882

J. S. Gill, Mahdi Saeedi Velashani, Jordan Wolf, Jonathan Kenney, M. R. Manesh, N. Kaabouch

引用次数: 4

Finite Element Simulation of Inkjet Printed Flexible Parallel Plate MIM Capacitors on Polyimide Film 聚酰亚胺薄膜上喷墨印刷柔性平行板MIM电容器的有限元模拟

2021 IEEE International Conference on Electro Information Technology (EIT) Pub Date : 2021-05-14 DOI: 10.1109/EIT51626.2021.9491846

Moriom R. Momota, Ankita Mohapatra, B. Morshed

{"title":"Finite Element Simulation of Inkjet Printed Flexible Parallel Plate MIM Capacitors on Polyimide Film","authors":"Moriom R. Momota, Ankita Mohapatra, B. Morshed","doi":"10.1109/EIT51626.2021.9491846","DOIUrl":"https://doi.org/10.1109/EIT51626.2021.9491846","url":null,"abstract":"As the potential usage of flexible electronics inkjet printing (IJP) is rapidly growing in flexible electronics, we present a Finite Element Analysis (FEA) with electrostatic modeling of a Metal-Insulator-Metal (MIM) type parallel plate capacitor using COMSOL Multiphysics designed for application in flexible electronic circuits. In this study, silver was used as the conductive metal parallel plates and Poly(4-vinylphenol) (PVP) was used as the insulator material. We compared our simulated result with IJP parallel plate capacitors where the bottom and top plate was printed with JS B40 silver ink and dielectric layer was printed with PVP dielectric ink. We also compared our simulation results with ideal calculated capacitance values. Our simulated results are promising and matched closely with the calculated and experimental results from fabricated capacitances. We demonstrated the change of capacitance due to variance of design parameters, such as, the area of the capacitance. Our printed IJP capacitors provided us the capacitance in the range of 8.8 pF to 467 pF for capacitor area 1 to 36 mm, while the simulated capacitance range was recorded between 9 pF to 455 pF. For four coat PVP the minimum and maximum capacitance obtained from simulations were 13.3 pF and 455 pF for capacitor area 1 mm2 and 36 mm2 respectively. The simulated capacitances with six coat PVP were 9 pF and 310 pF for 1 mm2 and 36 mm2 capacitor area respectively. For flexible electronics devices like body-worn sensors, IJP electronic components will be significant in near future and this paper lays the key foundation for that endeavor.","PeriodicalId":162816,"journal":{"name":"2021 IEEE International Conference on Electro Information Technology (EIT)","volume":"69 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126974669","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: 3

Threat Assessment for avoiding collsions with perpendicular vehicles at Intersections 在交叉路口避免与垂直车辆碰撞的威胁评估

2021 IEEE International Conference on Electro Information Technology (EIT) Pub Date : 2021-05-14 DOI: 10.1109/EIT51626.2021.9491879

Ishan Tyagi

引用次数: 1

Applications of Machine Learning in Fintech Credit Card Fraud Detection 机器学习在金融科技信用卡欺诈检测中的应用

2021 IEEE International Conference on Electro Information Technology (EIT) Pub Date : 2021-05-14 DOI: 10.1109/EIT51626.2021.9491903

Francisco Lacruz, J. Saniie

引用次数: 1

Comparison of data mining algorithms in remote sensing using Lidar data fusion and feature selection 基于激光雷达数据融合和特征选择的遥感数据挖掘算法比较

2021 IEEE International Conference on Electro Information Technology (EIT) Pub Date : 2021-05-14 DOI: 10.1109/EIT51626.2021.9491878

Papia F. Rozario, Rahul Gomes

{"title":"Comparison of data mining algorithms in remote sensing using Lidar data fusion and feature selection","authors":"Papia F. Rozario, Rahul Gomes","doi":"10.1109/EIT51626.2021.9491878","DOIUrl":"https://doi.org/10.1109/EIT51626.2021.9491878","url":null,"abstract":"Application of data mining techniques defines the basis of land use classification. Even though multispectral images can be very accurate in classifying land cover categories, using spectral reflectivity alone sometimes fails to distinguish between landcover types that share similar spectral signatures such as forest and wetlands. The problem aggravates owing to interpolation of neighbourhood pixel values. In this paper, we present a comparison of four classification and clustering algorithms and analyze their performance. These algorithms are applied both on spectral reflectivity values alone and along with Lidar data fusion. Experiments were performed in the Carlton County of Minnesota. Accuracy estimation was conducted for all models. Experiments indicate that accuracy increases when Lidar data is used to complement the spectral reflectivity values. Random Forest Classification and Support Vector Machines yield good results consistently due to their ensemble learning methods and the ability to represent non-linear relationship in the dataset, respectively. Maximum likelihood shows significant improvement with Lidar data fusion and ISODATA clustering approach has the lowest accuracy rate.","PeriodicalId":162816,"journal":{"name":"2021 IEEE International Conference on Electro Information Technology (EIT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121262172","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