Pub Date : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007312
S. Zafar, S. Saleem
Recent advances in 5G wireless technologies calls for larger bandwidth, which motivates design engineers and researchers to explore a higher frequency spectrum than the existing one spectrum of below 6 GHz. Millimeter-wave (mm-Wave) is viewed as the most suitable spectrum to satisfy the constraints for 5G and beyond cellular systems. However, it is observed that enabling mm-Wave can bring several issues like path loss, fading, scattering, coverage inadequacy, penetration loss, and signal attenuation problems. Therefore, augmenting the propagation path is important to indicate the behavior of the wireless channel prior to its deployment in the real-world environment. For this reason, we aim to analyze the two most promising mm-Wave frequency bands; 28 GHz and 36 GHz. We have selected the most popular Close-In (CI) & Floating-Intercept (FI) propagation path loss models that helped us to design an urban microcell line of sight (LOS) scenario. Finally, the overall network performance has been investigated by evaluating average user throughput, average cell throughput, cell-edge user throughput, peak user throughput, and spectral capacity. Our results show that the CI model performs much better than the FI model due to its high accuracy, simplicity of implementation, robustness, and single-factor dependency.
{"title":"Propagation Channel Characterization of 28 GHz and 36 GHz Millimeter-Waves for 5G Cellular Networks","authors":"S. Zafar, S. Saleem","doi":"10.1109/ETECTE55893.2022.10007312","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007312","url":null,"abstract":"Recent advances in 5G wireless technologies calls for larger bandwidth, which motivates design engineers and researchers to explore a higher frequency spectrum than the existing one spectrum of below 6 GHz. Millimeter-wave (mm-Wave) is viewed as the most suitable spectrum to satisfy the constraints for 5G and beyond cellular systems. However, it is observed that enabling mm-Wave can bring several issues like path loss, fading, scattering, coverage inadequacy, penetration loss, and signal attenuation problems. Therefore, augmenting the propagation path is important to indicate the behavior of the wireless channel prior to its deployment in the real-world environment. For this reason, we aim to analyze the two most promising mm-Wave frequency bands; 28 GHz and 36 GHz. We have selected the most popular Close-In (CI) & Floating-Intercept (FI) propagation path loss models that helped us to design an urban microcell line of sight (LOS) scenario. Finally, the overall network performance has been investigated by evaluating average user throughput, average cell throughput, cell-edge user throughput, peak user throughput, and spectral capacity. Our results show that the CI model performs much better than the FI model due to its high accuracy, simplicity of implementation, robustness, and single-factor dependency.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115958963","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 : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007311
G. Abbas, J. Gu, M. Asad, V. E. Balas, U. Farooq, I. Khan
Assessing the potential of a wind farm requires looking into how the wind behaves throughout a certain time frame. One of the most popular ways to statistically model wind data is with the Weibull distribution. Estimating two parameters of the Weibull PDF is crucial for a better fit between the PDF and wind speed data. In this study, Weibull distribution parameters for 2019 wind speed data in the Jhimpir region of Pakistan are determined using four analytical techniques: the empirical method (EM), the maximum likelihood method (MLM), the method of moments (MoM), and the energy pattern factor (EPF) approach. Each technique is evaluated using several different metrics, including the root mean squared error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE), and the coefficient of correlation (R). Statistical analyses show that the shape (k) and scale (c) parameters of the Weibull distribution estimated by the EM, MLM, and MoM are quite close to one another compared to the ones obtained by EPF for the available data. The MATLAB environment-based numerical results expressed that the EPF method performed the best in terms of R and RMSE and worst in terms of MAE and MARE.
{"title":"Estimation of Weibull Distribution Parameters by Analytical Methods for the Wind Speed of Jhimpir, Pakistan - A Comparative Assessment","authors":"G. Abbas, J. Gu, M. Asad, V. E. Balas, U. Farooq, I. Khan","doi":"10.1109/ETECTE55893.2022.10007311","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007311","url":null,"abstract":"Assessing the potential of a wind farm requires looking into how the wind behaves throughout a certain time frame. One of the most popular ways to statistically model wind data is with the Weibull distribution. Estimating two parameters of the Weibull PDF is crucial for a better fit between the PDF and wind speed data. In this study, Weibull distribution parameters for 2019 wind speed data in the Jhimpir region of Pakistan are determined using four analytical techniques: the empirical method (EM), the maximum likelihood method (MLM), the method of moments (MoM), and the energy pattern factor (EPF) approach. Each technique is evaluated using several different metrics, including the root mean squared error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE), and the coefficient of correlation (R). Statistical analyses show that the shape (k) and scale (c) parameters of the Weibull distribution estimated by the EM, MLM, and MoM are quite close to one another compared to the ones obtained by EPF for the available data. The MATLAB environment-based numerical results expressed that the EPF method performed the best in terms of R and RMSE and worst in terms of MAE and MARE.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"356 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122804009","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 : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007382
S. Zaman, M. Iqbal, H. Tauqeer, Mohsin Shahzad, Ghulam Akbar
IoT has been deployed in different fields to enhance the quality of human life. However, the IoT has become an appealing source for intruders to penetrate the smart premises of users. As security technology grows, cybercriminals also enable themselves to launch the most sophisticated attacks. Therefore, to maintain the protection of IoT devices, there is need for a responsive security system that can efficiently encounter novel attacks. This paper proposes a security mechanism to tackle cyberattacks by employing Reinforcement Learning (RL). Through RL, we can efficiently detect any ordinary or novel attacks as the RL agent learns by its own without human instructions. So, it educates the algorithm against any sophisticated attack. Dataset UNSW-NB is incorporated to evaluate the performance of the proposed study. The performance and detection rate of the model was enhanced selecting optimal features of the dataset. The proposed RL approach achieves an average accuracy of 97.29%. Results reveal that the proposed study has the potential to be deployed as a security mechanism against cyberattacks.
{"title":"Trustworthy Communication Channel for the IoT Sensor Nodes Using Reinforcement Learning","authors":"S. Zaman, M. Iqbal, H. Tauqeer, Mohsin Shahzad, Ghulam Akbar","doi":"10.1109/ETECTE55893.2022.10007382","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007382","url":null,"abstract":"IoT has been deployed in different fields to enhance the quality of human life. However, the IoT has become an appealing source for intruders to penetrate the smart premises of users. As security technology grows, cybercriminals also enable themselves to launch the most sophisticated attacks. Therefore, to maintain the protection of IoT devices, there is need for a responsive security system that can efficiently encounter novel attacks. This paper proposes a security mechanism to tackle cyberattacks by employing Reinforcement Learning (RL). Through RL, we can efficiently detect any ordinary or novel attacks as the RL agent learns by its own without human instructions. So, it educates the algorithm against any sophisticated attack. Dataset UNSW-NB is incorporated to evaluate the performance of the proposed study. The performance and detection rate of the model was enhanced selecting optimal features of the dataset. The proposed RL approach achieves an average accuracy of 97.29%. Results reveal that the proposed study has the potential to be deployed as a security mechanism against cyberattacks.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129048071","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 : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007202
Mudassar Ayub, Kaleem Ullah, Muhammad Jawad Khan, Hassan Farooq, A. Khan
Brain is the most important organ in the human body. The effects of brain impairment are wide ranging and include cognition, fatigue, sleep issues, headaches, dizziness, impaired self-awareness, clinical depression, attention and concentration problems, epilepsy, struggle in making decisions and many more. The objective of this paper is to the efficacy of noninvasive neuro modulatory technique Transcranial direct current stimulation (tDCS) in the estimation of brain cognitive state improvement using changes in small electrical brain voltages recorded by Electroencephalogram (EEG). Event related De synchronization (ERDs) is applied to the Motor Imagery Period (MIP) and Rest Period (RP) of pre stimulation and post stimulation EEG data of ten subjects. Common Spatial Pattern (CSP) is used for feature extraction and Linear Discrimination Analysis (LDA) a machine learning model is applied on these features for classification. The results suggest a decrease of contralateral ERDs oscillatory activity related to an event as per the hypothesis in anodal post stimulation than pre stimulation across all channels for six subjects. Further LDA applied on CSP proved that the classification accuracy between Motor imagery period (MIP) and the Rest period (RP) after the stimulation therapy is higher than the Pre stimulation Motor Imagery period (MIP) and Rest period (RP).
{"title":"Cognitive Improvement Estimation using EEG Imaging after tDCS Therapy","authors":"Mudassar Ayub, Kaleem Ullah, Muhammad Jawad Khan, Hassan Farooq, A. Khan","doi":"10.1109/ETECTE55893.2022.10007202","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007202","url":null,"abstract":"Brain is the most important organ in the human body. The effects of brain impairment are wide ranging and include cognition, fatigue, sleep issues, headaches, dizziness, impaired self-awareness, clinical depression, attention and concentration problems, epilepsy, struggle in making decisions and many more. The objective of this paper is to the efficacy of noninvasive neuro modulatory technique Transcranial direct current stimulation (tDCS) in the estimation of brain cognitive state improvement using changes in small electrical brain voltages recorded by Electroencephalogram (EEG). Event related De synchronization (ERDs) is applied to the Motor Imagery Period (MIP) and Rest Period (RP) of pre stimulation and post stimulation EEG data of ten subjects. Common Spatial Pattern (CSP) is used for feature extraction and Linear Discrimination Analysis (LDA) a machine learning model is applied on these features for classification. The results suggest a decrease of contralateral ERDs oscillatory activity related to an event as per the hypothesis in anodal post stimulation than pre stimulation across all channels for six subjects. Further LDA applied on CSP proved that the classification accuracy between Motor imagery period (MIP) and the Rest period (RP) after the stimulation therapy is higher than the Pre stimulation Motor Imagery period (MIP) and Rest period (RP).","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126098404","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 : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007241
Aeshna Tanveer, Nimra Afzaal, S. Murawwat, Sabaina Aleem, Fatima Sayeda
This research explores modelling, design, and control of quadcopters, focusing on mitigating flight performance errors that compensate the performance of Unmanned Aerial Vehicles (UAVs) performance. It also explores a mathematical model for simulation and a control of rotary-wing UAV systems. Moreover, it describes a design methodology for a micro-sized UAV in CAD software. Adaptive control techniques are then used to design four sub-controllers of UAVs named Altitude Control, Roll, Pitch, and Yaw. It is basically a remodeling of classical Model Reference Adaptive Control (MRAC) scheme, which is named Hybrid MRAC, ensuring a better rise time performance than classical MRAC. The controllers are then analyzed in the presence of disturbances to prove that adaptive controllers are more robust to external disturbances than non-adaptive ones. Lastly for state estimation, an Extended Kalman Filter (EKF) is applied to account for real-world sensor noises that further degrade the performance of UAV
{"title":"Mitigating Flight Performance Errors in UAVs through Hybrid MRAC controller","authors":"Aeshna Tanveer, Nimra Afzaal, S. Murawwat, Sabaina Aleem, Fatima Sayeda","doi":"10.1109/ETECTE55893.2022.10007241","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007241","url":null,"abstract":"This research explores modelling, design, and control of quadcopters, focusing on mitigating flight performance errors that compensate the performance of Unmanned Aerial Vehicles (UAVs) performance. It also explores a mathematical model for simulation and a control of rotary-wing UAV systems. Moreover, it describes a design methodology for a micro-sized UAV in CAD software. Adaptive control techniques are then used to design four sub-controllers of UAVs named Altitude Control, Roll, Pitch, and Yaw. It is basically a remodeling of classical Model Reference Adaptive Control (MRAC) scheme, which is named Hybrid MRAC, ensuring a better rise time performance than classical MRAC. The controllers are then analyzed in the presence of disturbances to prove that adaptive controllers are more robust to external disturbances than non-adaptive ones. Lastly for state estimation, an Extended Kalman Filter (EKF) is applied to account for real-world sensor noises that further degrade the performance of UAV","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121893637","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 : 2022-10-27DOI: 10.1109/etecte55893.2022.10007365
{"title":"Front Cover Page","authors":"","doi":"10.1109/etecte55893.2022.10007365","DOIUrl":"https://doi.org/10.1109/etecte55893.2022.10007365","url":null,"abstract":"","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122484299","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 : 2022-10-01DOI: 10.1109/etecte55893.2022.10007325
{"title":"Half Title Page","authors":"","doi":"10.1109/etecte55893.2022.10007325","DOIUrl":"https://doi.org/10.1109/etecte55893.2022.10007325","url":null,"abstract":"","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116119519","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 : 2022-01-01DOI: 10.1109/ETECTE55893.2022.10007322
Muhammad Aitsam
Data privacy has been a significant issue for many decades. Several techniques have been developed to make sure individuals' privacy but still, the world has seen privacy failures. In 2006, Cynthia Dwork gave the idea of Differential Privacy which gave strong theoretical guarantees for data privacy. Many companies and research institutes developed differential privacy libraries, but in order to get differentially private results, users have to tune the privacy parameters. In this paper, we minimized these tunable parameters. The DP-framework is developed which compares the differentially private results of three Python based differential privacy libraries. We also introduced a new very simple DP library (GRAM - DP), so that people with no background in differential privacy can still secure the privacy of the individuals in the dataset while releasing statistical results in public.
{"title":"Differential Privacy Made Easy","authors":"Muhammad Aitsam","doi":"10.1109/ETECTE55893.2022.10007322","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007322","url":null,"abstract":"Data privacy has been a significant issue for many decades. Several techniques have been developed to make sure individuals' privacy but still, the world has seen privacy failures. In 2006, Cynthia Dwork gave the idea of Differential Privacy which gave strong theoretical guarantees for data privacy. Many companies and research institutes developed differential privacy libraries, but in order to get differentially private results, users have to tune the privacy parameters. In this paper, we minimized these tunable parameters. The DP-framework is developed which compares the differentially private results of three Python based differential privacy libraries. We also introduced a new very simple DP library (GRAM - DP), so that people with no background in differential privacy can still secure the privacy of the individuals in the dataset while releasing statistical results in public.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125819642","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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