Pub Date : 2020-08-01DOI: 10.1109/UCET51115.2020.9205322
S. M. Hamza, H. Ullah, F. A. Tahir
A compact design of ultra-wide band (UWB) log-periodic dipole array (LPDA) antenna printed on FR-4 substrate is presented. The proposed design consists of array of printed dipoles fed by a coaxial cable. The dimensions of the printed dipoles and the spacing between the array elements are optimized by parametric simulations using full wave simulator. The size of the fabricated LPDA antenna is 0.9 $lambda times 0.33 lambda (135 times 50 mm^{2})$. The antenna has a fractional bandwidth of 133% and covers the band from 2.2 GHz to 11 GHz. The antenna exhibits a consistent end-fire radiation patterns over the whole operating band of 2.2-11 GHz with a maximum operating gain of 8.6 dBi.
{"title":"A Miniaturized Printed UWB LPDA Antenna","authors":"S. M. Hamza, H. Ullah, F. A. Tahir","doi":"10.1109/UCET51115.2020.9205322","DOIUrl":"https://doi.org/10.1109/UCET51115.2020.9205322","url":null,"abstract":"A compact design of ultra-wide band (UWB) log-periodic dipole array (LPDA) antenna printed on FR-4 substrate is presented. The proposed design consists of array of printed dipoles fed by a coaxial cable. The dimensions of the printed dipoles and the spacing between the array elements are optimized by parametric simulations using full wave simulator. The size of the fabricated LPDA antenna is 0.9 $lambda times 0.33 lambda (135 times 50 mm^{2})$. The antenna has a fractional bandwidth of 133% and covers the band from 2.2 GHz to 11 GHz. The antenna exhibits a consistent end-fire radiation patterns over the whole operating band of 2.2-11 GHz with a maximum operating gain of 8.6 dBi.","PeriodicalId":163493,"journal":{"name":"2020 International Conference on UK-China Emerging Technologies (UCET)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132068875","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}
Pub Date : 2020-08-01DOI: 10.1109/UCET51115.2020.9205457
I. S. Bayram
Recent advances in communication systems and the proliferation of plug-in electric vehicles (PEVs) hold a promise to support power systems operations with vehicle-togrid (V2G) applications. However, such ancillary services have tight communication requirements (low-latency, high reliability) as the aggregated PEVs need to respond to market signals within seconds and bad communication system performance lead to financial losses. In this paper, we consider a frequency regulation application in which PEVs are charged and discharged according to actual market signals. We assume that a market operator sends signals through 4G/LTE network to an aggregator located at a parking lot, who, as a next step, delivers data packets to electric vehicle supply equipments (EVSEs) via a local Wi-Fi network. In the final phase, each EVSE communicates with PEV battery management unit via power line communications. By adopting communication delay and packet loss profiles from measurement and simulation studies, we examine the impacts of communication system performance on V2G performance. The results show that packet losses significantly lowers precision score, while there is a need for faster networks if multiple aggregators participate at the same time.
{"title":"Quantifying the Effects of Communication Network Performance in Vehicle-to-Grid Frequency Regulation Services","authors":"I. S. Bayram","doi":"10.1109/UCET51115.2020.9205457","DOIUrl":"https://doi.org/10.1109/UCET51115.2020.9205457","url":null,"abstract":"Recent advances in communication systems and the proliferation of plug-in electric vehicles (PEVs) hold a promise to support power systems operations with vehicle-togrid (V2G) applications. However, such ancillary services have tight communication requirements (low-latency, high reliability) as the aggregated PEVs need to respond to market signals within seconds and bad communication system performance lead to financial losses. In this paper, we consider a frequency regulation application in which PEVs are charged and discharged according to actual market signals. We assume that a market operator sends signals through 4G/LTE network to an aggregator located at a parking lot, who, as a next step, delivers data packets to electric vehicle supply equipments (EVSEs) via a local Wi-Fi network. In the final phase, each EVSE communicates with PEV battery management unit via power line communications. By adopting communication delay and packet loss profiles from measurement and simulation studies, we examine the impacts of communication system performance on V2G performance. The results show that packet losses significantly lowers precision score, while there is a need for faster networks if multiple aggregators participate at the same time.","PeriodicalId":163493,"journal":{"name":"2020 International Conference on UK-China Emerging Technologies (UCET)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133764732","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}
Pub Date : 2020-08-01DOI: 10.1109/UCET51115.2020.9205373
Lanxin Miao, Xuezhou Guo, H. Abbas, K. Qaraqe, Q. Abbasi
The objective of this research is to develop a longterm risk model for the development of cardiovascular disease (CVD) because of type-2 diabetes (T2D). We use the support vector machine (SVM) and the K-nearest neighbours algorithms on the dataset collected from a longitudinal study called Framingham Heart Study, to develop the prediction models. The dataset was first balanced by the Synthetic Minority Oversampling Technique algorithm. The SVM algorithm was then used to train the model, and after tuning the parameters and training for 1000 times, the average accuracy to correctly predict the prevalence of CVD due to T2D came out as 96.5% and the average recall rate was 89.8%. Similarly, we also applied the KNN algorithm to train the dataset, and the recall rate even reaches 92.9%. The advantages of our model are: 1) it can predict with high accuracy both the risk of development of T2D and CVD simultaneously; 2) it can be used without the expensive and tedious oral glucose tolerance test. The model yielded high-performance results after training on the Framingham Heart Study dataset.
{"title":"Using Machine Learning to Predict the Future Development of Disease","authors":"Lanxin Miao, Xuezhou Guo, H. Abbas, K. Qaraqe, Q. Abbasi","doi":"10.1109/UCET51115.2020.9205373","DOIUrl":"https://doi.org/10.1109/UCET51115.2020.9205373","url":null,"abstract":"The objective of this research is to develop a longterm risk model for the development of cardiovascular disease (CVD) because of type-2 diabetes (T2D). We use the support vector machine (SVM) and the K-nearest neighbours algorithms on the dataset collected from a longitudinal study called Framingham Heart Study, to develop the prediction models. The dataset was first balanced by the Synthetic Minority Oversampling Technique algorithm. The SVM algorithm was then used to train the model, and after tuning the parameters and training for 1000 times, the average accuracy to correctly predict the prevalence of CVD due to T2D came out as 96.5% and the average recall rate was 89.8%. Similarly, we also applied the KNN algorithm to train the dataset, and the recall rate even reaches 92.9%. The advantages of our model are: 1) it can predict with high accuracy both the risk of development of T2D and CVD simultaneously; 2) it can be used without the expensive and tedious oral glucose tolerance test. The model yielded high-performance results after training on the Framingham Heart Study dataset.","PeriodicalId":163493,"journal":{"name":"2020 International Conference on UK-China Emerging Technologies (UCET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133765050","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}
Pub Date : 2020-08-01DOI: 10.1109/UCET51115.2020.9205424
Sagar Suresh Kumar
The spread of COVID-19, which has infected over 10 million people worldwide, entails the need for fast and aggressive testing never like before. As countries look to expanding testing, such test solutions must not only be technically sound, but should also be feasible and convenient for the user. The aim of this paper is to review the emerging tests and technology which can be potentially used to detect and assess the condition of those infected with the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the challenges in their development and use. The paper deals with 1) In vitro diagnostic tests(IVDs),i.e tests that use biological samples like blood and consist of 2 types: nucleic acid tests, which detect the RNA of the virus, and antibody tests which antibodies created by the body in response to the virus. 2) Chest X-Ray and CT scan devices, associated Deep Learning based detection methods and portable devices. 3) Wearable sensors, IoT and telemedicine for remote monitoring of COVID-19 patients to assess their condition, and also of Non-COVID-19 ones to reduce risks of cross-infection.
{"title":"Emerging Technologies and Sensors That Can Be Used During the COVID-19 Pandemic","authors":"Sagar Suresh Kumar","doi":"10.1109/UCET51115.2020.9205424","DOIUrl":"https://doi.org/10.1109/UCET51115.2020.9205424","url":null,"abstract":"The spread of COVID-19, which has infected over 10 million people worldwide, entails the need for fast and aggressive testing never like before. As countries look to expanding testing, such test solutions must not only be technically sound, but should also be feasible and convenient for the user. The aim of this paper is to review the emerging tests and technology which can be potentially used to detect and assess the condition of those infected with the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the challenges in their development and use. The paper deals with 1) In vitro diagnostic tests(IVDs),i.e tests that use biological samples like blood and consist of 2 types: nucleic acid tests, which detect the RNA of the virus, and antibody tests which antibodies created by the body in response to the virus. 2) Chest X-Ray and CT scan devices, associated Deep Learning based detection methods and portable devices. 3) Wearable sensors, IoT and telemedicine for remote monitoring of COVID-19 patients to assess their condition, and also of Non-COVID-19 ones to reduce risks of cross-infection.","PeriodicalId":163493,"journal":{"name":"2020 International Conference on UK-China Emerging Technologies (UCET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123045758","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}
Pub Date : 2020-08-01DOI: 10.1109/UCET51115.2020.9205468
Haolin Fei, M. Rehman
Wearable health monitoring system gain a lot of attraction from the wearable health technology community. Among wearable health devices, smart wrist band is one of the branches that the market invested most of money and there exist varies products aiming at different custom target group such as users who have cardiovascular diseases. However, there has few products that can monitoring heart rate continuously with low power consumption and able to detect the abnormal movement of body which may lead to the diagnosis of early Parkinson’s diseases(PD).This project propose a low-power consumption, customized wrist band with small size and pattern matching ability which help to analysis the abnormal behaviour that many early PD patients have, together with a user end program for data transferring, demonstration and further analysis. Results of the wrist band and user end program are tested, verified and compared, which shows that the wrist band is able to detect heart rate, counting steps and detecting abnormal hand movement, and user end program can properly receive the information from the wrist band and present to the $user$.
{"title":"A Wearable Health Monitoring System","authors":"Haolin Fei, M. Rehman","doi":"10.1109/UCET51115.2020.9205468","DOIUrl":"https://doi.org/10.1109/UCET51115.2020.9205468","url":null,"abstract":"Wearable health monitoring system gain a lot of attraction from the wearable health technology community. Among wearable health devices, smart wrist band is one of the branches that the market invested most of money and there exist varies products aiming at different custom target group such as users who have cardiovascular diseases. However, there has few products that can monitoring heart rate continuously with low power consumption and able to detect the abnormal movement of body which may lead to the diagnosis of early Parkinson’s diseases(PD).This project propose a low-power consumption, customized wrist band with small size and pattern matching ability which help to analysis the abnormal behaviour that many early PD patients have, together with a user end program for data transferring, demonstration and further analysis. Results of the wrist band and user end program are tested, verified and compared, which shows that the wrist band is able to detect heart rate, counting steps and detecting abnormal hand movement, and user end program can properly receive the information from the wrist band and present to the $user$.","PeriodicalId":163493,"journal":{"name":"2020 International Conference on UK-China Emerging Technologies (UCET)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114750872","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}
Pub Date : 2020-08-01DOI: 10.1109/UCET51115.2020.9205375
Zeng Li, Weiheng Sun, Shuhua Xiong, Pradeep Karn, Xiaohai He
Nowadays, the mainstream video coding standard H.265/HEVC has achieved excellent compression performance, but it still can not match the increase of huge amount of data. In order to further optimize intra prediction of HEVC, we proposed an iterative filtering algorithm which combines the characteristics of HEVC intra prediction modes. Proposed algorithm classifies PU into different types by analyzing the characteristics of different intra prediction modes. Through discrete training methods, the coefficients of each type of filters can be obtained. And multiple iterative filtering can make the prediction more accuracy. We further optimize the complexity of the algorithm to make a balance between performance and complexity. Experimental results show that proposed algorithm can achieve better coding performance compared with HEVC baseline algorithm and some latest algorithm.
{"title":"An Iterative Filtering Algorithm for HEVC Intra Prediction Combined with Prediction Mode Characteristics","authors":"Zeng Li, Weiheng Sun, Shuhua Xiong, Pradeep Karn, Xiaohai He","doi":"10.1109/UCET51115.2020.9205375","DOIUrl":"https://doi.org/10.1109/UCET51115.2020.9205375","url":null,"abstract":"Nowadays, the mainstream video coding standard H.265/HEVC has achieved excellent compression performance, but it still can not match the increase of huge amount of data. In order to further optimize intra prediction of HEVC, we proposed an iterative filtering algorithm which combines the characteristics of HEVC intra prediction modes. Proposed algorithm classifies PU into different types by analyzing the characteristics of different intra prediction modes. Through discrete training methods, the coefficients of each type of filters can be obtained. And multiple iterative filtering can make the prediction more accuracy. We further optimize the complexity of the algorithm to make a balance between performance and complexity. Experimental results show that proposed algorithm can achieve better coding performance compared with HEVC baseline algorithm and some latest algorithm.","PeriodicalId":163493,"journal":{"name":"2020 International Conference on UK-China Emerging Technologies (UCET)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125090688","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}
Pub Date : 2020-08-01DOI: 10.1109/UCET51115.2020.9205465
M. Xiao, S. Gong, X. Zheng, Yunjiang Jin
In this work, p-Ge/GaAs hetero-epitaxy was studied by MOCVD and a p-Ge/i-GaAs/n-GaAs photodetector structure was fabricated aiming at 1.3, 1.55 $mu$m photodetection. The photo-response spectra indicate that the prepared device has quite good performance on dark current and signal on/off ratio, suggesting promising application in optical fiber communication.
{"title":"1.3, 1.55 μm photodetector based on Ge/GaAs hetero-integration prepared by MOCVD","authors":"M. Xiao, S. Gong, X. Zheng, Yunjiang Jin","doi":"10.1109/UCET51115.2020.9205465","DOIUrl":"https://doi.org/10.1109/UCET51115.2020.9205465","url":null,"abstract":"In this work, p-Ge/GaAs hetero-epitaxy was studied by MOCVD and a p-Ge/i-GaAs/n-GaAs photodetector structure was fabricated aiming at 1.3, 1.55 $mu$m photodetection. The photo-response spectra indicate that the prepared device has quite good performance on dark current and signal on/off ratio, suggesting promising application in optical fiber communication.","PeriodicalId":163493,"journal":{"name":"2020 International Conference on UK-China Emerging Technologies (UCET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120953551","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}
Pub Date : 2020-08-01DOI: 10.1109/UCET51115.2020.9205422
Salaheddin Hosseinzadeh, N. Ramzan, M. Yousefi, K. Curtis, H. Larijani
A practical investigation of LoRaWAN’s (longrange wide area network) propagation in an urban and semiurban environment is demonstrated and analyzed in this article. Measured data is analyzed to understand the attributes of LoRa, including: effective propagation range, chirp spread spectrum (CSS) modulation and spreading factor (SF). This analysis provides a better understanding of these attributes. In addition, a comparison was made with propagation models to benchmark and observe the impact of clutter, environment and structures in practice. For this purpose, log-distance, COST.W.I models were used. An average increase of 5.5 dB was observed on the received signal strength due to a higher spreading factor. This translated into a range extension of approximately 500 m in practice. Outcome of this study provides an insight of LoRa’s propagation in metropolitan environments, and facilitates the network planning in similar scenarios.
{"title":"Impact of Spreading Factor on LoRaWAN Propagation in a Metropolitan Environment","authors":"Salaheddin Hosseinzadeh, N. Ramzan, M. Yousefi, K. Curtis, H. Larijani","doi":"10.1109/UCET51115.2020.9205422","DOIUrl":"https://doi.org/10.1109/UCET51115.2020.9205422","url":null,"abstract":"A practical investigation of LoRaWAN’s (longrange wide area network) propagation in an urban and semiurban environment is demonstrated and analyzed in this article. Measured data is analyzed to understand the attributes of LoRa, including: effective propagation range, chirp spread spectrum (CSS) modulation and spreading factor (SF). This analysis provides a better understanding of these attributes. In addition, a comparison was made with propagation models to benchmark and observe the impact of clutter, environment and structures in practice. For this purpose, log-distance, COST.W.I models were used. An average increase of 5.5 dB was observed on the received signal strength due to a higher spreading factor. This translated into a range extension of approximately 500 m in practice. Outcome of this study provides an insight of LoRa’s propagation in metropolitan environments, and facilitates the network planning in similar scenarios.","PeriodicalId":163493,"journal":{"name":"2020 International Conference on UK-China Emerging Technologies (UCET)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121255763","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}
Pub Date : 2020-08-01DOI: 10.1109/UCET51115.2020.9205461
Mu Jia, Shaoxuan Li, J. Kernec, Shufan Yang, F. Fioranelli, O. Romain
As the number of older adults increases worldwide, new paradigms for indoor activity monitoring are required to keep people living at home independently longer. Radar-based human activity recognition has been identified as a sensing modality of choice because it is privacy-preserving and does not require end-users compliance or manipulation. In this paper, we explore the robustness of machine learning algorithms for human activity recognition using six different activities from the University of Glasgow dataset recorded with an FMCW radar. The raw radar data is pre-processed and represented using four different domains, namely, range-time, range-Doppler amplitude and phase diagrams, and Cadence Velocity Diagram. From those, salient features can be extracted and classified using Support Vector Machine, Stacked AutoEncoder, and Convolutional Neural Networks. The fusion of handcrafted features and features from CNN is applied to get the best scheme of classification with over 96% accuracy.
{"title":"Human activity classification with radar signal processing and machine learning","authors":"Mu Jia, Shaoxuan Li, J. Kernec, Shufan Yang, F. Fioranelli, O. Romain","doi":"10.1109/UCET51115.2020.9205461","DOIUrl":"https://doi.org/10.1109/UCET51115.2020.9205461","url":null,"abstract":"As the number of older adults increases worldwide, new paradigms for indoor activity monitoring are required to keep people living at home independently longer. Radar-based human activity recognition has been identified as a sensing modality of choice because it is privacy-preserving and does not require end-users compliance or manipulation. In this paper, we explore the robustness of machine learning algorithms for human activity recognition using six different activities from the University of Glasgow dataset recorded with an FMCW radar. The raw radar data is pre-processed and represented using four different domains, namely, range-time, range-Doppler amplitude and phase diagrams, and Cadence Velocity Diagram. From those, salient features can be extracted and classified using Support Vector Machine, Stacked AutoEncoder, and Convolutional Neural Networks. The fusion of handcrafted features and features from CNN is applied to get the best scheme of classification with over 96% accuracy.","PeriodicalId":163493,"journal":{"name":"2020 International Conference on UK-China Emerging Technologies (UCET)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129818607","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}
Pub Date : 2020-08-01DOI: 10.1109/UCET51115.2020.9205473
Y. Shukrinov, I. Rahmonov, A. E. Botha, A. Plecenik, Dragos Angel
We investigate the $varphi$0 Josephson junction, which demonstrates a rich variety of dynamical states determined by the parameters of the Josephson junction and intermediate ferromagnetic layer, as well as by the value of the dc-bias current. Results of magnetization dynamics simulation at fixed value of bias current and results of FFT analysis are presented. We discuss how the superconducting current interacts with the different magnetization components.
{"title":"Magnetization Dynamics Features in the SFS φ0 Josephson Junction","authors":"Y. Shukrinov, I. Rahmonov, A. E. Botha, A. Plecenik, Dragos Angel","doi":"10.1109/UCET51115.2020.9205473","DOIUrl":"https://doi.org/10.1109/UCET51115.2020.9205473","url":null,"abstract":"We investigate the $varphi$0 Josephson junction, which demonstrates a rich variety of dynamical states determined by the parameters of the Josephson junction and intermediate ferromagnetic layer, as well as by the value of the dc-bias current. Results of magnetization dynamics simulation at fixed value of bias current and results of FFT analysis are presented. We discuss how the superconducting current interacts with the different magnetization components.","PeriodicalId":163493,"journal":{"name":"2020 International Conference on UK-China Emerging Technologies (UCET)","volume":"419 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128914861","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}
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