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

Implementing wearable sensor technology for the determination of a biomarker profile for cancer-related fatigue 实施可穿戴传感器技术，用于确定癌症相关疲劳的生物标志物概况

2020 31st Irish Signals and Systems Conference (ISSC) Pub Date : 2020-06-01 DOI: 10.1109/ISSC49989.2020.9180194

N. Akhtar, M. Kelly, William N. Scott, J. Connolly

{"title":"Implementing wearable sensor technology for the determination of a biomarker profile for cancer-related fatigue","authors":"N. Akhtar, M. Kelly, William N. Scott, J. Connolly","doi":"10.1109/ISSC49989.2020.9180194","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180194","url":null,"abstract":"Cancer Related Fatigue (CRF) is a well-recognised symptom of malignant breast disease and may affect up to 70% of those undergoing therapy or deemed to be in remission. The condition is frequently subject to unpredictable recurrence that can result in unavoidable and unforeseen detriment to quality of life. Moreover, management of the condition can place significant financial burden on health and social care facilities. CRF is distinct from normal tiredness which may be resolved by periods of sleep or rest. Customers' extensive use of wearable technologies has contributed to the evolution of clinical trial procedures and, as a result, health data can also be obtained using wearables [1]. New technologies have the potential to improve data accuracy and timeliness, improve efficiency and increasing patient engagement in the clinical trial process Medical quality tracking devices are already supporting patient care in several clinical areas [1]. The main aim of this study is to define an accurate fatigue baseline for individuals diagnosed with breast cancer to determine potential relationships between possible fatigue markers, measurable daily activity and individual perceptions of fatigue.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"384 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":"123956475","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

Gender Classification using Twitter Text Data 使用Twitter文本数据进行性别分类

2020 31st Irish Signals and Systems Conference (ISSC) Pub Date : 2020-06-01 DOI: 10.1109/ISSC49989.2020.9180161

Pradeep Vashisth, Kevin Meehan

{"title":"Gender Classification using Twitter Text Data","authors":"Pradeep Vashisth, Kevin Meehan","doi":"10.1109/ISSC49989.2020.9180161","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180161","url":null,"abstract":"Increasingly content sharing websites such as social media have become very popular in many countries across the world. Classifying the gender of a person based on these short messages is an interesting research area that could benefit legal investigation, forensics, marketing analysis, advertising and recommendation. This research will explore the use of Natural Language Processing (NLP) techniques and tweets in a gender classification system. This investigation will compare multiple techniques such as Bag of Words (Term Frequency - Inverse Document Frequency), Word Embedding (W2Vec, GloVe) and traditional Machine Learning techniques (Logistic Regression, Support Vector Machine and Naïve Bayes) in this context. A new dataset has been generated to be used as part of this study comprising of the user gender and associated tweets. This dataset was developed due to the unavailability of any public standard dataset with the volume required to perform this investigation. The results have determined that the traditional Bag of Words model did not provide any significant results in classification. However, word embedding models have significantly performed better using multiple machine learning techniques. Therefore, the word embedding models have been proven to be the most effective technique in classifying gender based on twitter text data.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"11 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":"127212712","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: 15

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

Derivation of E-model Equipment Impairment Factors for Narrowband and Wideband Opus Codec Using the Instrumental Method 用仪器法推导窄带和宽带工作码编解码器的e型设备损伤因子

2020 31st Irish Signals and Systems Conference (ISSC) Pub Date : 2020-06-01 DOI: 10.1109/ISSC49989.2020.9180160

Mohannad Al-Ahmadi, P. Počta, H. Melvin

{"title":"Derivation of E-model Equipment Impairment Factors for Narrowband and Wideband Opus Codec Using the Instrumental Method","authors":"Mohannad Al-Ahmadi, P. Počta, H. Melvin","doi":"10.1109/ISSC49989.2020.9180160","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180160","url":null,"abstract":"Real-time multimedia applications like Web realtime communication WebRTC support a wide range of codecs, from the standard narrowband up to fullband codecs. The IETF standardized Opus codec is the default codec utilized by WebRTC speech and audio applications, by supporting a wide range of bitrates. In current best effort networks, network impairments such as packet loss, delay and jitter affect the quality of VoIP. To assess the impact of such impairments in order to estimate the quality experienced by the end users of speech applications, the E-model standardized in ITU-T Rec. G.107 can be used. In this paper we derive codec-specific parameters required by the E-model to estimate the quality degradation in speech applications deploying narrowband and wideband Opus codec, namely the equipment impairment factor Ie and packet loss robustness factor Bpl. We followed the ITU-T methods designed for this purpose and share the results arising from all the experiments covering all the narrowband and wideband Opus codec conditions. The derived values make it possible to integrate the E-model in realtime communication applications including WebRTC to assess the quality experienced by the end user.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"23 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":"131353980","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

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