2020 31st Irish Signals and Systems Conference (ISSC)最新文献_第3页

Polar code performance with Doppler shifts and reflections in Rayleigh fading for Industrial channels 工业信道中具有多普勒频移和瑞利衰落反射的极码性能

2020 31st Irish Signals and Systems Conference (ISSC) Pub Date : 2020-06-01 DOI: 10.1109/ISSC49989.2020.9180204

Y. Samarawickrama, V. Cionca

{"title":"Polar code performance with Doppler shifts and reflections in Rayleigh fading for Industrial channels","authors":"Y. Samarawickrama, V. Cionca","doi":"10.1109/ISSC49989.2020.9180204","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180204","url":null,"abstract":"Industry 4.0 has created a strong pull for wireless communications. Industrial applications have tight communication constraints putting them in the class of Ultra Reliable, Low Latency Communication (URLLC). Polar codes have recently become a primary contender for satisfying URLLC requirements. Their performance is heavily dependent on the channel state and with industrial environments presenting extreme conditions with highly dynamic radio channels, obtaining high reliability from polar codes is challenging. Pilot Assisted Transmission allows channel estimation and can improve the reliability of polar codes in fading channels. However a detailed analysis of the impact of the channel dynamics and PAT scheme on the polar code performance is not available. This paper models the industrial radio channel as a Rayleigh channel affected by Doppler shift and delay spread. We evaluate the channel estimation and Bit Error Rate improvements that can be achieved using PAT with variable pilot interval. We detail the behaviour of polar codes subjected to Doppler shift and delay spread. Finally, we investigate the trade-off between reliability and maximum achievable data rate based on PAT interval and code rate. The existence of a trade-off indicates scope for optimization of PAT parameters depending on channel conditions.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129150538","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

Generative Augmented Dataset and Annotation Frameworks for Artificial Intelligence (GADAFAI) 面向人工智能的生成增强数据集和注释框架(GADAFAI)

2020 31st Irish Signals and Systems Conference (ISSC) Pub Date : 2020-06-01 DOI: 10.1109/ISSC49989.2020.9180200

P. Corcoran, Hossein Javidnia, Joseph Lemley, Viktor Varkarakis

引用次数: 0

Dynamic Countermeasure Knowledge for Intrusion Response Systems 入侵响应系统的动态对策知识

2020 31st Irish Signals and Systems Conference (ISSC) Pub Date : 2020-06-01 DOI: 10.1109/ISSC49989.2020.9180198

Kieran Hughes, K. Mclaughlin, S. Sezer

{"title":"Dynamic Countermeasure Knowledge for Intrusion Response Systems","authors":"Kieran Hughes, K. Mclaughlin, S. Sezer","doi":"10.1109/ISSC49989.2020.9180198","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180198","url":null,"abstract":"Significant advancements in Intrusion Detection Systems has led to improved alerts. However, Intrusion Response Systems which aim to automatically respond to these alerts, is a research area which is not yet advanced enough to benefit from full automation. In Security Operations Centres, analysts can implement countermeasures using knowledge and past experience to adapt to new attacks. Attempts at automated Intrusion Response Systems fall short when a new attack occurs to which the system has no specific knowledge or effective countermeasure to apply, even leading to overkill countermeasures such as restarting services and blocking ports or IPs. In this paper, a countermeasure standard is proposed which enables countermeasure intelligence sharing, automated countermeasure adoption and execution by an Intrusion Response System. An attack scenario is created on an emulated network using the Common Open Research Emulator, where an insider attack attempts to exploit a buffer overflow on an Exim mail server. Experiments demonstrate that an Intrusion Response System with dynamic countermeasure knowledge can stop attacks that would otherwise succeed with a static predefined countermeasure approach.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132424713","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

Investigating Supervised Machine Learning Techniques for Channel Identification in Wireless Sensor Networks 无线传感器网络中信道识别的监督机器学习技术研究

2020 31st Irish Signals and Systems Conference (ISSC) Pub Date : 2020-06-01 DOI: 10.1109/ISSC49989.2020.9180209

George D. O’Mahony, Philip J. Harris, Colin C. Murphy

{"title":"Investigating Supervised Machine Learning Techniques for Channel Identification in Wireless Sensor Networks","authors":"George D. O’Mahony, Philip J. Harris, Colin C. Murphy","doi":"10.1109/ISSC49989.2020.9180209","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180209","url":null,"abstract":"Knowledge of the wireless channel is pivotal for wireless communication links but varies for multiple reasons. The radio spectrum changes due to the number of connected devices, demand, packet size or services in operation, while fading levels, obstacles, path losses, and spurious (non-)malicious interference fluctuate in the physical environment. Typically, these channels are applicable to the time series class of data science problems, as the primary data points are measured over a period. In the case of wireless sensor networks, which regularly provide the device to access point communication links in Internet of Things applications, determining the wireless channel in operation permits channel access. Generally, a clear channel assessment is performed to determine whether a wireless transmission can be executed, which is an approach containing limitations. In this study, received in-phase (I) and quadrature-phase (Q) samples are collected from the wireless channel using a software-defined radio (SDR) based procedure and directly analyzed using python and Matlab. Features are extracted from the probability density function and statistical analysis of the received I/Q samples and used as the training data for the two chosen machine learning methods. Data is collected and produced over wires, to avoid interfering with other networks, using SDRs and Raspberry Pi embedded devices, which utilize available open-source libraries. Data is examined for the signal-free (noise), legitimate signal (ZigBee) and jamming signal (continuous wave) cases in a live laboratory environment. Support vector machine and Random Forest models are each designed and compared as channel identifiers for these signal types.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131565493","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

Cyber-security considerations for domestic-level automated demand-response systems utilizing public-key infrastructure and ISO/IEC 20922 使用公钥基础设施和ISO/IEC 20922的国内级自动化需求响应系统的网络安全考虑

2020 31st Irish Signals and Systems Conference (ISSC) Pub Date : 2020-06-01 DOI: 10.1109/ISSC49989.2020.9180208

John Hastings, D. Laverty, A. Jahic, D. Morrow, P. Brogan

引用次数: 1

Multi-step ahead wind power forecasting for Ireland using an ensemble of VMD-ELM models 利用VMD-ELM模型集合对爱尔兰的风力发电进行超前多步预测

2020 31st Irish Signals and Systems Conference (ISSC) Pub Date : 2020-06-01 DOI: 10.1109/ISSC49989.2020.9180155

J. M. González-Sopeña, V. Pakrashi, Bidisha Ghosh

引用次数: 5

Practical Implementation of APTs on PTP Time Synchronisation Networks 点到点时间同步网络上apt的实际实现

2020 31st Irish Signals and Systems Conference (ISSC) Pub Date : 2020-06-01 DOI: 10.1109/ISSC49989.2020.9180157

Waleed Alghamdi, M. Schukat

引用次数: 3

Methodology for Building Synthetic Datasets with Virtual Humans 用虚拟人构建合成数据集的方法

2020 31st Irish Signals and Systems Conference (ISSC) Pub Date : 2020-06-01 DOI: 10.1109/ISSC49989.2020.9180188

Shubhajit Basak, Hossein Javidnia, Faisal Khan, R. Mcdonnell, M. Schukat

引用次数: 5

Reduced Complexity Approach for Uplink Rate Trajectory Prediction in Mobile Networks 移动网络上行速率轨迹预测的降低复杂度方法

2020 31st Irish Signals and Systems Conference (ISSC) Pub Date : 2020-06-01 DOI: 10.1109/ISSC49989.2020.9180156

G. Nikolov, M. Kuhn, A. Mcgibney, Bernd-Ludwig Wenning

引用次数: 1

Implementing Pattern Recognition and Matching techniques to automatically detect standardized functional tests from wearable technology 实现模式识别和匹配技术，自动检测可穿戴技术的标准化功能测试

2020 31st Irish Signals and Systems Conference (ISSC) Pub Date : 2020-06-01 DOI: 10.1109/ISSC49989.2020.9180174

Vini Vijayan, Nigel McKelvey, J. Condell, P. Gardiner, J. Connolly

{"title":"Implementing Pattern Recognition and Matching techniques to automatically detect standardized functional tests from wearable technology","authors":"Vini Vijayan, Nigel McKelvey, J. Condell, P. Gardiner, J. Connolly","doi":"10.1109/ISSC49989.2020.9180174","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180174","url":null,"abstract":"Wearable sensor technology is often used in healthcare environments for monitoring, diagnosis and recovery of patients. Wearable sensors can be used to detect movement throughout measurement of standardized functional tests, which are considered part of the assessment criteria for Activities of Daily Living (ADL). The volume of data collected by sensors for long term assessment of ambulatory movement can be very large in tuple size since they may contain detailed 3-D sensor information. Extracting recorded movement data corresponding to standardized functional tests from an entire data set is complex and time consuming. This paper examines whether standardized functional tests can be automatically detected from long term data collected by wearable technology devices using Artificial Intelligence (AI) techniques. The current research work is aligned with clinical trial data generated by patients who are suffering from Axial Spondylo Arthritis (axSpA). These datasets contain Inertial Measurement Unit (IMU) values corresponding to individual patient functional tests for axSpA. Rotation angles with respect to each functional test are plotted against time. Individual movements that form part of a functional test are constructed for training and testing the AI system. Individual movement patterns are split into training and testing data inputs and are used to train the Neural Network (NN) system and to estimate overall prediction accuracy of the NN system. NN model is trained in such a way that the learned system can predict new functional test patterns with respect to the trained data and it is compared with expected data set and returned the accuracy of prediction. Once the semi supervised learning phase of AI system has successfully finished with adequate amount of data, it is capable for automatically detect gait and posture changes of patients at home.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116513503","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