2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE)最新文献_第8页

Simscape Power Systems Benchmarks for Education and Research in Power Grid Dynamics and Control 电网动力学与控制教育与研究的Simscape电力系统基准

2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE) Pub Date : 2018-05-13 DOI: 10.1109/CCECE.2018.8447645

A. Delavari, I. Kamwa, P. Brunelle

引用次数: 18

A PIR Scheme to Improve the Computation Cost on the Client-Side of Smartphone Applications 一种提高智能手机客户端计算成本的PIR方案

2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE) Pub Date : 2018-05-13 DOI: 10.1109/CCECE.2018.8447708

Maryam Hezaveh, C. Adams

引用次数: 1

Iterative Soft-Decision Decoding of Binary Cyclic Codes Based on Extended Parity-Check Transformation Algorithm 基于扩展奇偶校验变换算法的二进制循环码迭代软判决译码

2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE) Pub Date : 2018-05-13 DOI: 10.1109/CCECE.2018.8447536

O. Babalola, J. Versfeld

引用次数: 2

Enhanced Bad Data Identification in Distribution System State Estimation 配电系统状态估计中不良数据的改进识别

2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE) Pub Date : 2018-05-13 DOI: 10.1109/CCECE.2018.8447843

Adel Tabakhpour, M. Abdelaziz

引用次数: 4

Thermal Effects Analysis of GaN HEMT Power Amplifier Based on LTCC Substrate Integration 基于LTCC衬底集成的GaN HEMT功率放大器热效应分析

2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE) Pub Date : 2018-05-01 DOI: 10.1109/CCECE.2018.8447758

C. Jebali, A. Kouki

引用次数: 1

Solar Forecasting Using Remote Solar Monitoring Stations and Artificial Neural Networks 利用远程太阳监测站和人工神经网络进行太阳预报

2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE) Pub Date : 2018-05-01 DOI: 10.1109/CCECE.2018.8447636

Graeme Vanderstar, P. Musílek, A. Nassif

引用次数: 19

SysMART Indoor Services: A System of Smart and Connected Supermarkets SysMART室内服务:智能互联超市系统

2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE) Pub Date : 2018-05-01 DOI: 10.1109/CCECE.2018.8447626

Omar Raad, Majd Makdessi, Yazan Mohamad, I. Damaj

{"title":"SysMART Indoor Services: A System of Smart and Connected Supermarkets","authors":"Omar Raad, Majd Makdessi, Yazan Mohamad, I. Damaj","doi":"10.1109/CCECE.2018.8447626","DOIUrl":"https://doi.org/10.1109/CCECE.2018.8447626","url":null,"abstract":"Smart gadgets are being embedded almost in every aspect of our lives. From smart cities to smart watches, modern industries are increasingly supporting the Internet-of-Things (IoT). SysMART aims at making supermarkets smart, productive, and with a touch of modern lifestyle. While similar implementations to improve the shopping experience exists, they tend mainly to replace the shopping activity at the store with online shopping. Although online shopping reduces time and effort, it deprives customers from enjoying the experience. SysMART relies on cutting-edge devices and technology to simplify and reduce the time required during grocery shopping inside the supermarket. In addition, the system monitors and maintains perishable products in good condition suitable for human consumption. SysMART is built using state-of-the-art technologies that support rapid prototyping and precision data acquisition. The selected development environment is Lab Viewwith its world-class interfacing libraries. The paper comprises a detailed system description, development strategy, interface design, software engineering, and a thorough analysis and evaluation.","PeriodicalId":181463,"journal":{"name":"2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124778117","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: 7

From Wired to Wireless: Challenges of False Data Injection Attacks Against Smart Grid Sensor Networks 从有线到无线:针对智能电网传感器网络的虚假数据注入攻击的挑战

2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE) Pub Date : 2018-05-01 DOI: 10.1109/CCECE.2018.8447662

Jiachen Liu, F. Labeau

{"title":"From Wired to Wireless: Challenges of False Data Injection Attacks Against Smart Grid Sensor Networks","authors":"Jiachen Liu, F. Labeau","doi":"10.1109/CCECE.2018.8447662","DOIUrl":"https://doi.org/10.1109/CCECE.2018.8447662","url":null,"abstract":"Existing studies on False Data Injection Attacks (FDIAs), a type of stealth attacks against power grids aimed at compromising the system cyber-physical security, have primarily been conducted on wired systems in which state estimation is represented by overdetermined DC power flow models. The emerging trend of Smart Grid (SG) assisted by the widespread deployment of Wireless Sensor Networks (WSNs) for various new functionalities, on the other hand, calls for a review of how some certain well-established premises need to be adjusted in the new context. In addition to related studies based on traditional bus-based systems, certain broad changes brought by the use of WSNs in grid systems will be introduced in this paper. Subsequently, differences in terms of bad data detection (BDD), false data injection attack strategy or physical feasibility of attack methods caused by the shift of scenario will be compared and briefly analyzed. A summary of new or previously overlooked requirements for FDIA studies will then be appended. By presenting a comprehensive review of related studies we will shed light on potential future research directions.","PeriodicalId":181463,"journal":{"name":"2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE)","volume":"775 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126432568","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

A New Hybrid Multilevel Nested Neutral Point Clamped (NNPC) Converter 一种新型混合多级嵌套中性点箝位(NNPC)转换器

2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE) Pub Date : 2018-05-01 DOI: 10.1109/CCECE.2018.8447693

M. Kordic, M. Narimani, Mehdi Alimardani

引用次数: 1

Toward Understanding Hidden Patterns in Human Mobility Using Wi-Fi 利用Wi-Fi了解人类移动的隐藏模式

2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE) Pub Date : 2018-05-01 DOI: 10.1109/CCECE.2018.8447727

Ali Farrokhtala, Y. Chen, Ting Hu, Sipan Ye

{"title":"Toward Understanding Hidden Patterns in Human Mobility Using Wi-Fi","authors":"Ali Farrokhtala, Y. Chen, Ting Hu, Sipan Ye","doi":"10.1109/CCECE.2018.8447727","DOIUrl":"https://doi.org/10.1109/CCECE.2018.8447727","url":null,"abstract":"A reliable model for identifying spatial-temporal regularities in human dynamics is rewarding in many applications such as computer networking and mobile communication. These hidden patterns are inherited from our repeating behaviours with respect to three primary contexts: time, space, and social environments. Thus, selecting a suitable source of sensor data that is scalable, multidimensional, and social network illustrative, can enable us to develop a reliable human mobility model and potentially a prediction system. We first demonstrate that collected Wi-Fi network scans from mobile phone devices share a similar set of characteristics to real-world large-scale networks. One aspect particularly is the long-tailed property of node degree distribution of projection networks. This feature can be interpreted as the robustness of the system against structural changes caused by removing a set of nodes or connections. Then, we transform Wi-Fi events into a tabular data format containing different time granularities and location-tagged information. However, the new data is sparse and difficult to analyze. Thus, we reduce the dimensionality of the data by extracting its structural patterns using the principal components of the new features. Our analysis shows that we can reconstruct the original data with more than 90% accuracy using only a set of top eigenvectors with one-quarter of the original features, while the outliers or the noisy user data are filtered out. Our proposed technique helps to visualize user similarities and behaviour dynamics, and reduce the computation complexity of further analysis.","PeriodicalId":181463,"journal":{"name":"2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130162370","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