Pub Date : 2021-12-22DOI: 10.1109/ICEEE54059.2021.9718990
Md. Nazmul Islam, Abdullah Mohammad Tanvirul Hoque, Md. Ahasan Habib
A lots of online courses are other remote education programs are continuing throughout the whole universe as a result of globalization and advancement of modern technology and internet. Examination is a part and parcel of both online and offline education system to evaluate the students took part in the program. In case of online exam numerous techniques were proposed to limit probability of cheating in the examination but no algorithm is available to consider the bandwidth problem for students in low internet speeds. In this paper, a completely new algorithm is designed where the total exam time of the students is dependent on data speed of his device. Moreover, a mock test is arranged with ten students locating different locations to validate the proposed method. The integration of this method with any one high security algorithm will enrich the acceptability of the software to the users.
{"title":"Design and Implementation of Bandwidth Based Time Varying Online Exam","authors":"Md. Nazmul Islam, Abdullah Mohammad Tanvirul Hoque, Md. Ahasan Habib","doi":"10.1109/ICEEE54059.2021.9718990","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718990","url":null,"abstract":"A lots of online courses are other remote education programs are continuing throughout the whole universe as a result of globalization and advancement of modern technology and internet. Examination is a part and parcel of both online and offline education system to evaluate the students took part in the program. In case of online exam numerous techniques were proposed to limit probability of cheating in the examination but no algorithm is available to consider the bandwidth problem for students in low internet speeds. In this paper, a completely new algorithm is designed where the total exam time of the students is dependent on data speed of his device. Moreover, a mock test is arranged with ten students locating different locations to validate the proposed method. The integration of this method with any one high security algorithm will enrich the acceptability of the software to the users.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127317000","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 : 2021-12-22DOI: 10.1109/ICEEE54059.2021.9718890
Farhan Sadaf, S. M. Taslim Uddin Raju, Abdul Muntakim
Offline Handwritten Text Recognition (HTR) is a technique for translating handwritten images into digitally editable text format. Due to the presence of cursive letters, punctuation marks, and compound characters, it is more complex to recognize Bangla handwritten text. Over the years, several approaches to the optical model of the HTR system have been developed, including Hidden Markov Model (HMM) or deep learning techniques such as Convolutional Recurrent Neural Networks (CRNN), and current state-of-the-art Gated-CNN based architectures. Despite this, there are relatively limited works available for Bangla word recognition. In this paper, we introduce an end-to-end system for Bangla word recognition. We used a variety of popular pre-trained CNN architectures, including Xception, MobileNet, and DenseNet, followed by recurrent units such as LSTM or GRU. Furthermore, we experimented with Puigcerver’s CRNN based and Flor’s Gated-CNN based optical model architectulimited works available in Bangla.res. Flor architecture provided the highest recognition rate in our experiment, with a CER of 12.83% and a WER of 36.01%.
{"title":"Offline Bangla Handwritten Text Recognition: A Comprehensive Study of Various Deep Learning Approaches","authors":"Farhan Sadaf, S. M. Taslim Uddin Raju, Abdul Muntakim","doi":"10.1109/ICEEE54059.2021.9718890","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718890","url":null,"abstract":"Offline Handwritten Text Recognition (HTR) is a technique for translating handwritten images into digitally editable text format. Due to the presence of cursive letters, punctuation marks, and compound characters, it is more complex to recognize Bangla handwritten text. Over the years, several approaches to the optical model of the HTR system have been developed, including Hidden Markov Model (HMM) or deep learning techniques such as Convolutional Recurrent Neural Networks (CRNN), and current state-of-the-art Gated-CNN based architectures. Despite this, there are relatively limited works available for Bangla word recognition. In this paper, we introduce an end-to-end system for Bangla word recognition. We used a variety of popular pre-trained CNN architectures, including Xception, MobileNet, and DenseNet, followed by recurrent units such as LSTM or GRU. Furthermore, we experimented with Puigcerver’s CRNN based and Flor’s Gated-CNN based optical model architectulimited works available in Bangla.res. Flor architecture provided the highest recognition rate in our experiment, with a CER of 12.83% and a WER of 36.01%.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120947270","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 : 2021-12-22DOI: 10.1109/ICEEE54059.2021.9718801
Riziya Akter Keya, Abdul Khaleque, K. Shaha, Sumaya Akter, Md. Sarwar Hosen
The electro-absorption modulator is the future of photonic integrated circuits technology. In this paper, a double-layered indium tin oxide based electro-absorption modulator is proposed and analyzed through the finite element method. Double plasmonic layers play an effective role to obtain a compact modulator having 3 dB length of 0.2118 μm with higher figure of merit around 797.60 and high extinction ratio of 14.15 dB/μm at 1550 nm. The device can also show a lower insertion loss of around 0.01774 dB/μm at the same wavelength. Therefore, the proposed plasmonic based modulator could be a better candidate for the optical communication.
{"title":"Double Plasmonic Layered Electro-Absorption Modulator on Silicon Waveguide","authors":"Riziya Akter Keya, Abdul Khaleque, K. Shaha, Sumaya Akter, Md. Sarwar Hosen","doi":"10.1109/ICEEE54059.2021.9718801","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718801","url":null,"abstract":"The electro-absorption modulator is the future of photonic integrated circuits technology. In this paper, a double-layered indium tin oxide based electro-absorption modulator is proposed and analyzed through the finite element method. Double plasmonic layers play an effective role to obtain a compact modulator having 3 dB length of 0.2118 μm with higher figure of merit around 797.60 and high extinction ratio of 14.15 dB/μm at 1550 nm. The device can also show a lower insertion loss of around 0.01774 dB/μm at the same wavelength. Therefore, the proposed plasmonic based modulator could be a better candidate for the optical communication.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123900814","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 : 2021-12-22DOI: 10.1109/ICEEE54059.2021.9718837
Nahin Ul Sadad, Afsana Afrin, Md. Nazrul Islam Mondal
Histogram Equalization is one of the most common algorithms used in image processing applications. Traditional software based histogram equalization using CPU is no longer sufficient for high-computation based real-time image processing applications. To meet high computation demand, image processing operations can be hardware accelerated using Field Programmable Gate Array (FPGA). In this paper, we implemented histogram equalization using Verilog Hardware Description Language (HDL) on Xilinx FPGA for hardware acceleration. The result shows that our FPGA-based histogram equalization is on average 1.5 thousand times faster than traditional software based histogram equalization on CPU.
{"title":"FPGA based Histogram Equalization for Image Processing","authors":"Nahin Ul Sadad, Afsana Afrin, Md. Nazrul Islam Mondal","doi":"10.1109/ICEEE54059.2021.9718837","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718837","url":null,"abstract":"Histogram Equalization is one of the most common algorithms used in image processing applications. Traditional software based histogram equalization using CPU is no longer sufficient for high-computation based real-time image processing applications. To meet high computation demand, image processing operations can be hardware accelerated using Field Programmable Gate Array (FPGA). In this paper, we implemented histogram equalization using Verilog Hardware Description Language (HDL) on Xilinx FPGA for hardware acceleration. The result shows that our FPGA-based histogram equalization is on average 1.5 thousand times faster than traditional software based histogram equalization on CPU.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114954976","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 : 2021-12-22DOI: 10.1109/ICEEE54059.2021.9718838
T. S. Joyeeta, T. K. Roy, M. Sheikh
This research proposes a nonlinear composite excitation controller for synchronous generators (SGs) to improve power system stability. First, the nonlinear model is transformed into a reduced-order model using the nonlinear partial feedback linearization approach. Second, the control signal is produced by applying the reduced-order model to the suggested fast reaching law based-backstepping sliding mode controller (BSMC). Following that, the whole system’s stability is maintained by employing the Lyapunov function theory. Finally, a simulation study with a big disturbance is performed to validate the suggested controller’s theoretical notion. In addition, an existing controller is used to demonstrate the superiority of the proposed controller.
{"title":"A Backstepping Sliding Mode Controller Design for Synchronous Machine Excitation Systems for Enhancing the Transient Stability","authors":"T. S. Joyeeta, T. K. Roy, M. Sheikh","doi":"10.1109/ICEEE54059.2021.9718838","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718838","url":null,"abstract":"This research proposes a nonlinear composite excitation controller for synchronous generators (SGs) to improve power system stability. First, the nonlinear model is transformed into a reduced-order model using the nonlinear partial feedback linearization approach. Second, the control signal is produced by applying the reduced-order model to the suggested fast reaching law based-backstepping sliding mode controller (BSMC). Following that, the whole system’s stability is maintained by employing the Lyapunov function theory. Finally, a simulation study with a big disturbance is performed to validate the suggested controller’s theoretical notion. In addition, an existing controller is used to demonstrate the superiority of the proposed controller.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117081953","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}
A brain tumor is a severe disease that can be fatal and significantly impacts one’s quality of life. The traditional method of identifying tumors relies on physicians, which is time-consuming and prone to errors, putting the patient’s life in jeopardy. Identifying the classes of brain tumors is difficult due to the high anatomical and spatial diversity of the brain tumor’s surrounding region. An automated and precise diagnosis approach is required to treat this severe disease effectively. Deep learning technology, such as CNN, can be used to diagnose various tumor types in the early stages of their development using brain MRI. In this study, a deep transfer learning framework based on VGG-19 is introduced to accurately detect three common kinds of tumors from brain MRI. There are primarily two phases to the suggested framework. The VGG-19 frozen part is the first phase, while the modified neural style classification part is the second phase. With certain modified techniques, the class imbalance impact within the MRI dataset and the generalization error issue during the training process were also resolved. The proposed model has a 94% classification accuracy and a 94% F1-score.
{"title":"Deep Transfer Learning Based Multi-Class Brain Tumors Classification Using MRI Images","authors":"Mrinmoy Mondal, Md. Farukuzzaman Faruk, Nasif Raihan, Protiva Ahammed","doi":"10.1109/ICEEE54059.2021.9719003","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9719003","url":null,"abstract":"A brain tumor is a severe disease that can be fatal and significantly impacts one’s quality of life. The traditional method of identifying tumors relies on physicians, which is time-consuming and prone to errors, putting the patient’s life in jeopardy. Identifying the classes of brain tumors is difficult due to the high anatomical and spatial diversity of the brain tumor’s surrounding region. An automated and precise diagnosis approach is required to treat this severe disease effectively. Deep learning technology, such as CNN, can be used to diagnose various tumor types in the early stages of their development using brain MRI. In this study, a deep transfer learning framework based on VGG-19 is introduced to accurately detect three common kinds of tumors from brain MRI. There are primarily two phases to the suggested framework. The VGG-19 frozen part is the first phase, while the modified neural style classification part is the second phase. With certain modified techniques, the class imbalance impact within the MRI dataset and the generalization error issue during the training process were also resolved. The proposed model has a 94% classification accuracy and a 94% F1-score.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124806513","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 : 2021-12-22DOI: 10.1109/ICEEE54059.2021.9718796
Sadia Enam, M. Rana
This paper presents conventional shaped (rectangular elliptical, and circular) textile antennas performance and SAR analysis with and without human body tissue model (HBTM) at 2.45 GHz. The antenna design involved a coaxial probe feeding technique and fabric substrates (wash cotton, curtain cotton, and polycot) of 3 mm thickness. At 2.45 GHz WLAN band, both for OFF body and ON body, circular antenna with curtain cotton presents an overall superior performance in terms of return loss (−60.9995 dB and −52.423 dB), VSWR (1.0018 and 1.0048), peak directivity (8.969 dBi and 8.825 dBi), gain (7.391 dBi and 7.109 dBi), and radiation efficiency (69.81% and 68.07%) maintaining a bandwidth (BW) of 108.2 MHz and 107.4 MHz at −10dB. The antennas are also analyzed in close proximity (2 mm away) to a three-layered (skin, fat, and muscle) flat body phantom to determine the Specific Absorption Rate (SAR). The SAR recorded for circular MPA (curtain cotton) is 0.0293 W/kg< 2 W/kg averaged over 10g tissue. The overall simulation is done using CST Microwave Studio software. The proposed antenna is considered to be an effective antenna for on body wireless communication.
{"title":"Performance Analysis of Textile Antennas for Body Worn Application","authors":"Sadia Enam, M. Rana","doi":"10.1109/ICEEE54059.2021.9718796","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718796","url":null,"abstract":"This paper presents conventional shaped (rectangular elliptical, and circular) textile antennas performance and SAR analysis with and without human body tissue model (HBTM) at 2.45 GHz. The antenna design involved a coaxial probe feeding technique and fabric substrates (wash cotton, curtain cotton, and polycot) of 3 mm thickness. At 2.45 GHz WLAN band, both for OFF body and ON body, circular antenna with curtain cotton presents an overall superior performance in terms of return loss (−60.9995 dB and −52.423 dB), VSWR (1.0018 and 1.0048), peak directivity (8.969 dBi and 8.825 dBi), gain (7.391 dBi and 7.109 dBi), and radiation efficiency (69.81% and 68.07%) maintaining a bandwidth (BW) of 108.2 MHz and 107.4 MHz at −10dB. The antennas are also analyzed in close proximity (2 mm away) to a three-layered (skin, fat, and muscle) flat body phantom to determine the Specific Absorption Rate (SAR). The SAR recorded for circular MPA (curtain cotton) is 0.0293 W/kg< 2 W/kg averaged over 10g tissue. The overall simulation is done using CST Microwave Studio software. The proposed antenna is considered to be an effective antenna for on body wireless communication.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122812220","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 : 2021-12-22DOI: 10.1109/ICEEE54059.2021.9718575
Sancoy Barua, N. Mohammad
In order to meet the increasing growth of energy demand, incorporation of renewable resources appears to be a viable solution. With the increase of renewable integration, a big challenge is to handle these intermittent resources in a smart way. An effective approach can be the optimal management of energy of Solar PV panels and energy storage besides the main utility. In this research, an optimization method is employed to manage variable load demand to minimize the overall electricity bill of residential house over a period of 24 hours. Optimization approach schedules the energy resources and decides, when to use grid or cut it off, depending on the availability of solar power, state-of-charge (SOC) of ESS and dynamic electricity tariffs. The impact of using smart energy management system (EMS), is tested by executing three different plausible cases. To verify and validate the real time behaviors of the model, optimization results are compared with the static electricity tariffs and a substantial cost reduction is observed.
{"title":"Optimization-based Energy Management System to Minimize Electricity Bill for Residential Customer","authors":"Sancoy Barua, N. Mohammad","doi":"10.1109/ICEEE54059.2021.9718575","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718575","url":null,"abstract":"In order to meet the increasing growth of energy demand, incorporation of renewable resources appears to be a viable solution. With the increase of renewable integration, a big challenge is to handle these intermittent resources in a smart way. An effective approach can be the optimal management of energy of Solar PV panels and energy storage besides the main utility. In this research, an optimization method is employed to manage variable load demand to minimize the overall electricity bill of residential house over a period of 24 hours. Optimization approach schedules the energy resources and decides, when to use grid or cut it off, depending on the availability of solar power, state-of-charge (SOC) of ESS and dynamic electricity tariffs. The impact of using smart energy management system (EMS), is tested by executing three different plausible cases. To verify and validate the real time behaviors of the model, optimization results are compared with the static electricity tariffs and a substantial cost reduction is observed.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131540418","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 : 2021-12-22DOI: 10.1109/ICEEE54059.2021.9718798
Tania Akter, M. Ali
Autism is a set of complicated developmental disorders marked by social skills impairments, communication difficulties (verbal and nonverbal), and recurring behavior. Autistic children are frequently alienated as a result of these impairments. Rapid recognition of autism can help to establish a treatment strategy and lessen the burden on sufferers. As a result, effective methods to early diagnosis and treatment for ASD are necessary. The toddler, child, adolescent, and adult screening datasets are collected in this study and separated according to gender (male and female). By using random oversampling (ROS), these datasets are balanced. Next, different classifiers are applied to both the primary and balanced datasets. The MLP classifier produced the best results, and the hyperparameter for it was tuned to improve autism identification rate. However, the experimental outcome for the female dataset is better than the male dataset. The shapely adaptive explanation (SHAP) method is also employed to assess the significant features of male and female.
{"title":"Predicting Autism Spectrum Disorder Based On Gender Using Machine Learning Techniques","authors":"Tania Akter, M. Ali","doi":"10.1109/ICEEE54059.2021.9718798","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718798","url":null,"abstract":"Autism is a set of complicated developmental disorders marked by social skills impairments, communication difficulties (verbal and nonverbal), and recurring behavior. Autistic children are frequently alienated as a result of these impairments. Rapid recognition of autism can help to establish a treatment strategy and lessen the burden on sufferers. As a result, effective methods to early diagnosis and treatment for ASD are necessary. The toddler, child, adolescent, and adult screening datasets are collected in this study and separated according to gender (male and female). By using random oversampling (ROS), these datasets are balanced. Next, different classifiers are applied to both the primary and balanced datasets. The MLP classifier produced the best results, and the hyperparameter for it was tuned to improve autism identification rate. However, the experimental outcome for the female dataset is better than the male dataset. The shapely adaptive explanation (SHAP) method is also employed to assess the significant features of male and female.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"708 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116106433","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 : 2021-12-22DOI: 10.1109/ICEEE54059.2021.9718857
Md. Hasibul Islam, Kusum Tara, H. Rahman, A. K. Sarkar
Human heart is one of the most complex structures of human body deals with unique and indispensable functionality to keep humans alive. Judgment of heart’s efficacy often relies on to what extent sympatho-vagal balance prevails and keeps the heart beating. This work deals with a two-approach-based solution to assess the secretion of acetylcholine (ACh) and norepinephrine (NE) inside heart’s myocardial cell during R-peak formation. Approach-I deals with formation of ECG peak, generation of action potential, and details of ACh and NE secretion inside myocardial cell. Approach-II analyzes and processes obtained cardiac signals in order to find out features necessary to define cardiac condition. Their combined analysis ends up refuting the assessing process with Respiratory sinus arrhythmia (RSA), Cardiac autonomic balance (CAB), and Cardiac autonomic regulation (CAR) in the range respectively of 0.04±0.025, −15.96±1.38, and 16.08±1.37 for NE predominance and 0.086±0.015, −14.63±0.333, and 14.76±0.33 for ACh predominance inside heart’s myocardial cell.
{"title":"An Approach to Assess ACh and NE Secretion inside Heart’s Myocardial Cell during R-peak Formation","authors":"Md. Hasibul Islam, Kusum Tara, H. Rahman, A. K. Sarkar","doi":"10.1109/ICEEE54059.2021.9718857","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718857","url":null,"abstract":"Human heart is one of the most complex structures of human body deals with unique and indispensable functionality to keep humans alive. Judgment of heart’s efficacy often relies on to what extent sympatho-vagal balance prevails and keeps the heart beating. This work deals with a two-approach-based solution to assess the secretion of acetylcholine (ACh) and norepinephrine (NE) inside heart’s myocardial cell during R-peak formation. Approach-I deals with formation of ECG peak, generation of action potential, and details of ACh and NE secretion inside myocardial cell. Approach-II analyzes and processes obtained cardiac signals in order to find out features necessary to define cardiac condition. Their combined analysis ends up refuting the assessing process with Respiratory sinus arrhythmia (RSA), Cardiac autonomic balance (CAB), and Cardiac autonomic regulation (CAR) in the range respectively of 0.04±0.025, −15.96±1.38, and 16.08±1.37 for NE predominance and 0.086±0.015, −14.63±0.333, and 14.76±0.33 for ACh predominance inside heart’s myocardial cell.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121296381","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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