Pub Date : 2021-12-22DOI: 10.1109/ICEEE54059.2021.9718786
M. Hasan, M. A. Kashem, Md. Jakirul Islam, Md. Zakir Hossain
Many real-world combinatorial optimization problems (COPs) are NP-hard and challenging to find the optimal solution using classical linear and convex optimization methods. In addition, the computational complexity of these optimization tasks increases exponentially with the increasing number of decision variables. A further difficulty can be also caused by the search space being intrinsically multimodal and non-convex. In such a case, an effective optimization method is required that can cope better with these problem characteristics. Genetic algorithm (GA) is a widely used method for COPs. The original GA and its variants have been used to solve a number of classic discrete optimization problems. Literature shows that the static mutation probability is commonly used for the GA and its variants which cause the imbalance between exploration and exploitation, limiting the performance of GA. To overcome this problem, this research proposes a time-varying mutation operator for GA. In this paper, the balance between exploration and exploitation of the proposed GA has been verified using the benchmark instances of a well-known combinatorial optimization problem i.e., the 0–1 knapsack problem. The numerical results show that the proposed GA can obtain better results with on average a significant number of function evaluations compared to the well-known metaheuristic methods.
{"title":"A Time-varying Mutation Operator for Balancing the Exploration and Exploitation Behaviours of Genetic Algorithm","authors":"M. Hasan, M. A. Kashem, Md. Jakirul Islam, Md. Zakir Hossain","doi":"10.1109/ICEEE54059.2021.9718786","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718786","url":null,"abstract":"Many real-world combinatorial optimization problems (COPs) are NP-hard and challenging to find the optimal solution using classical linear and convex optimization methods. In addition, the computational complexity of these optimization tasks increases exponentially with the increasing number of decision variables. A further difficulty can be also caused by the search space being intrinsically multimodal and non-convex. In such a case, an effective optimization method is required that can cope better with these problem characteristics. Genetic algorithm (GA) is a widely used method for COPs. The original GA and its variants have been used to solve a number of classic discrete optimization problems. Literature shows that the static mutation probability is commonly used for the GA and its variants which cause the imbalance between exploration and exploitation, limiting the performance of GA. To overcome this problem, this research proposes a time-varying mutation operator for GA. In this paper, the balance between exploration and exploitation of the proposed GA has been verified using the benchmark instances of a well-known combinatorial optimization problem i.e., the 0–1 knapsack problem. The numerical results show that the proposed GA can obtain better results with on average a significant number of function evaluations compared to the well-known metaheuristic methods.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"128 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":"128215716","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/ICEEE54059.2021.9718785
Rony Tota, Md. Selim Hossain
In this paper the MUSIC source localization algorithm is applied to the near-field narrowband optimal beamformer to increase its localization accuracy and resolution capability. Optimal beamformer cannot identify closely spaced multiple near-field signals. MUSIC algorithm is an Eigen-decomposition based source localization technique. A three dimensional MUSIC algorithm is used with near-field optimal beamformer to correctly localize the three parameters (range, elevation and azimuthal angle) of multiple sources. The robustness of this proposed beamformer against the white Gaussian noisy environment is also examined. The Root Mean Square Error (RMSE) to localize the multiple near-field targets is also studied. The simulation results show that the MUSIC based optimal beamformer can easily sense the multiple closely spaced sources in the noisy environment with sharper radiation lobe using minimum number of snapshots and sensors.
{"title":"Three Dimentional Multiple Near-field Source Localization Based on MUSIC Algorithm to Increase the Localization Accuracy of Optimal Beamformer","authors":"Rony Tota, Md. Selim Hossain","doi":"10.1109/ICEEE54059.2021.9718785","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718785","url":null,"abstract":"In this paper the MUSIC source localization algorithm is applied to the near-field narrowband optimal beamformer to increase its localization accuracy and resolution capability. Optimal beamformer cannot identify closely spaced multiple near-field signals. MUSIC algorithm is an Eigen-decomposition based source localization technique. A three dimensional MUSIC algorithm is used with near-field optimal beamformer to correctly localize the three parameters (range, elevation and azimuthal angle) of multiple sources. The robustness of this proposed beamformer against the white Gaussian noisy environment is also examined. The Root Mean Square Error (RMSE) to localize the multiple near-field targets is also studied. The simulation results show that the MUSIC based optimal beamformer can easily sense the multiple closely spaced sources in the noisy environment with sharper radiation lobe using minimum number of snapshots and sensors.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"67 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":"134301198","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/ICEEE54059.2021.9718783
Nahin Ul Sadad, Afsana Afrin, Md. Nazrul Islam Mondal
Multiplication is one of the most common operations used in any program. Program working on massively large data always requires high computation power. In the age of big data, conventional general-purpose CPU based on Von Neumann architecture is no longer enough to satisfy high computation demand. Field Programmable Gate Array (FPGA) can perform hardware acceleration of any program. Since multiplier is the slowest component in any hardware accelerator, thus faster and re-configurable multiplier which can handle integers of any size must be implemented on FPGA. In this paper, we implemented both synchronous and asynchronous radix-2 booth multiplier using Verilog HDL on a Xilinx FPGA. We found that simulation time of asynchronous radix-2 booth multiplier is faster than synchronous radix-2 booth multiplier but synchronous radix-2 booth multiplier consumes fewer resources than asynchronous radix-2 booth multiplier.
{"title":"Synchronous and Asynchronous Implementation of Radix-2 Booth Multiplication Algorithm","authors":"Nahin Ul Sadad, Afsana Afrin, Md. Nazrul Islam Mondal","doi":"10.1109/ICEEE54059.2021.9718783","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718783","url":null,"abstract":"Multiplication is one of the most common operations used in any program. Program working on massively large data always requires high computation power. In the age of big data, conventional general-purpose CPU based on Von Neumann architecture is no longer enough to satisfy high computation demand. Field Programmable Gate Array (FPGA) can perform hardware acceleration of any program. Since multiplier is the slowest component in any hardware accelerator, thus faster and re-configurable multiplier which can handle integers of any size must be implemented on FPGA. In this paper, we implemented both synchronous and asynchronous radix-2 booth multiplier using Verilog HDL on a Xilinx FPGA. We found that simulation time of asynchronous radix-2 booth multiplier is faster than synchronous radix-2 booth multiplier but synchronous radix-2 booth multiplier consumes fewer resources than asynchronous radix-2 booth multiplier.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"30 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":"133695524","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/ICEEE54059.2021.9718777
Abir Ebna Harun, Mohammad Ashfak Habib
Urinalysis is a common medical test that can be costly and inconvenient in medical facilities. The use of point-of-care(POC) test devices, smartphones, manifolds, and other additional tools can make urinalysis easier in a home-based environment. In this paper, we are proposing a new system that can be used to performing a laboratory-free urinalysis with the help of a urine test strip and a smartphone device. Our system contains several image pre-processing steps and an artificial neural network mapping model to analyze the color pixels of the urine test strip. By following our proposed solution, the user can acquire an accurate computer vision integrated urinalysis result.
{"title":"An Alternate Solution for Smartphone-Based Urinalysis","authors":"Abir Ebna Harun, Mohammad Ashfak Habib","doi":"10.1109/ICEEE54059.2021.9718777","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718777","url":null,"abstract":"Urinalysis is a common medical test that can be costly and inconvenient in medical facilities. The use of point-of-care(POC) test devices, smartphones, manifolds, and other additional tools can make urinalysis easier in a home-based environment. In this paper, we are proposing a new system that can be used to performing a laboratory-free urinalysis with the help of a urine test strip and a smartphone device. Our system contains several image pre-processing steps and an artificial neural network mapping model to analyze the color pixels of the urine test strip. By following our proposed solution, the user can acquire an accurate computer vision integrated urinalysis result.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"1 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":"130336778","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/ICEEE54059.2021.9718787
Shihab Ahammed, Kazi Sazzad Hossen, Ashraful Hossain Howlader
Of late, stanene and germanene having the effect of spin orbital coupling are characterized as a superconductive material at room temperature. These materials have been synthesized and investigated their low thermal conductivity in recent experimental studies. With the purpose of achieving diverse thermal properties, we have modeled and offered germanene/stanene heterobilayer. We have also characterized its in-plane thermal conduction with varying length. For the assessment its thermal properties, we employed a simulation method named reverse non equilibrium molecular dynamics. The nanosheet size in the x direction ranges from 20 to 300 nanometer. The amount of thermal transport of this heterobilayer is predicted to be 19.95 W m−1 K−1 over an unlimited length. In this work, the van der Waals thickness is used to predict this thermal transmission. The length of the nanosheet appears to boost the in-plane heat conduction of the germanene/stanene bilayer. For a better understanding of in-plane thermal conduction, the phonon density of states is determined. The characterization of germanene/stanene nanostructure proposed in this study would give a decent knowledge to make it a promising bilayer for the thermoelectric applications owing to its low thermal conductivity.
近年来，具有自旋轨道耦合效应的硅烯和锗烯在室温下被表征为超导材料。这些材料已被合成，并在最近的实验研究中研究了它们的低导热性。为了获得不同的热性能，我们模拟并提供了锗烯/stanene异质层。我们还描述了它的面内热传导随长度的变化。为了评估其热性能，我们采用了一种称为反向非平衡分子动力学的模拟方法。x方向的纳米片尺寸在20到300纳米之间。该异质层的热输运量预测为19.95 W m−1 K−1，长度不限。在这项工作中，范德华厚度被用来预测这种热传递。纳米片的长度似乎促进了锗烯/烯双分子层的平面内热传导。为了更好地理解面内热传导，确定了态声子密度。本研究提出的锗烯/stanene纳米结构的表征将使其具有良好的知识，使其成为热电应用的有前途的双层材料，因为它的低导热性。
{"title":"Length dependent thermal conduction in germanene/stanene heterobilayer by using molecular dynamics simulations","authors":"Shihab Ahammed, Kazi Sazzad Hossen, Ashraful Hossain Howlader","doi":"10.1109/ICEEE54059.2021.9718787","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718787","url":null,"abstract":"Of late, stanene and germanene having the effect of spin orbital coupling are characterized as a superconductive material at room temperature. These materials have been synthesized and investigated their low thermal conductivity in recent experimental studies. With the purpose of achieving diverse thermal properties, we have modeled and offered germanene/stanene heterobilayer. We have also characterized its in-plane thermal conduction with varying length. For the assessment its thermal properties, we employed a simulation method named reverse non equilibrium molecular dynamics. The nanosheet size in the x direction ranges from 20 to 300 nanometer. The amount of thermal transport of this heterobilayer is predicted to be 19.95 W m−1 K−1 over an unlimited length. In this work, the van der Waals thickness is used to predict this thermal transmission. The length of the nanosheet appears to boost the in-plane heat conduction of the germanene/stanene bilayer. For a better understanding of in-plane thermal conduction, the phonon density of states is determined. The characterization of germanene/stanene nanostructure proposed in this study would give a decent knowledge to make it a promising bilayer for the thermoelectric applications owing to its low thermal conductivity.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"9 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":"121901597","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/ICEEE54059.2021.9718789
S. M. Mahidul Hasan, Md. Rezwanul Ahsan, Md. Dara Abdus Satter
The Internet of things (IoT) is an arising innovation, which changed the industrialization system at a higher level. Staying away from significant catastrophes in the food business or unexpected trivial issues of noticing temperature, humidity, and duct can bring about combined misfortune in food commerce. The main focus of this research has been on how a strategic distance can be maintained from those business misfortunes by incorporating IoT. In food shops, hazardous foods should be kept at a certain level of temperature, humidity, and satisfactory dust level to avert poisoning bacteria. To accomplish the task, IoT-based sensors are used within this research to collect variations of temperature, humidity, and dust level of any hazardous food’s climate and provide required activities with a precise choice. The proposed temperature, humidity, and dust monitoring system has been tested at AJWAH Bake and Pastry shop. The onsite experimental data shows that the system prototype is very effective in observing the food environment and can be utilized at food shops.
{"title":"IoT-Cloud-Based Low-Cost Temperature, Humidity, and Dust Monitoring System to Prevent Food Poisoning","authors":"S. M. Mahidul Hasan, Md. Rezwanul Ahsan, Md. Dara Abdus Satter","doi":"10.1109/ICEEE54059.2021.9718789","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718789","url":null,"abstract":"The Internet of things (IoT) is an arising innovation, which changed the industrialization system at a higher level. Staying away from significant catastrophes in the food business or unexpected trivial issues of noticing temperature, humidity, and duct can bring about combined misfortune in food commerce. The main focus of this research has been on how a strategic distance can be maintained from those business misfortunes by incorporating IoT. In food shops, hazardous foods should be kept at a certain level of temperature, humidity, and satisfactory dust level to avert poisoning bacteria. To accomplish the task, IoT-based sensors are used within this research to collect variations of temperature, humidity, and dust level of any hazardous food’s climate and provide required activities with a precise choice. The proposed temperature, humidity, and dust monitoring system has been tested at AJWAH Bake and Pastry shop. The onsite experimental data shows that the system prototype is very effective in observing the food environment and can be utilized at food shops.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"42 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":"124415206","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/ICEEE54059.2021.9719000
Md Abdur Raiyan, S. C. Mohonta
In Brain Computer Interface (BCI), for precise prediction of brain activity, it is important to know which part of the brain is responsible for which activity. Electroencephalography (EEG) signal which conveys the information of such brain activity is recorded using a number of electrodes from all over the skull. In this study, a comparison from a machine learning perspective has been made to investigate which sets of electrodes that mean which part of the brain shows more neural activity during execution or imagination of fist movement. Here, all the preprocessing steps have been done using EEGLAB on MATLAB, and the normalized band powers of five brain rhythms such as alpha, beta, gamma, delta and theta have been used as features. Finally, a supervised machine learning technique – Support Vector Machine (SVM) has been implemented which took those features as input for classification. This study shows that the channel set with more electrodes can distinguish between executed and imaginary fist movement more accurately. Therefore, these findings can be used to understand brain functionality more distinctly and be applied to predict motor movement more precisely in future BCI research.
{"title":"Comparative Study on EEG Based Motor Movement Classification Using Different Sets of Electrode Channels","authors":"Md Abdur Raiyan, S. C. Mohonta","doi":"10.1109/ICEEE54059.2021.9719000","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9719000","url":null,"abstract":"In Brain Computer Interface (BCI), for precise prediction of brain activity, it is important to know which part of the brain is responsible for which activity. Electroencephalography (EEG) signal which conveys the information of such brain activity is recorded using a number of electrodes from all over the skull. In this study, a comparison from a machine learning perspective has been made to investigate which sets of electrodes that mean which part of the brain shows more neural activity during execution or imagination of fist movement. Here, all the preprocessing steps have been done using EEGLAB on MATLAB, and the normalized band powers of five brain rhythms such as alpha, beta, gamma, delta and theta have been used as features. Finally, a supervised machine learning technique – Support Vector Machine (SVM) has been implemented which took those features as input for classification. This study shows that the channel set with more electrodes can distinguish between executed and imaginary fist movement more accurately. Therefore, these findings can be used to understand brain functionality more distinctly and be applied to predict motor movement more precisely in future BCI research.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"106 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":"134343065","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/ICEEE54059.2021.9718776
Md. Farukuzzaman Faruk
Coronavirus illness, commonly abbreviated as COVID-19, has been designated a global pandemic. To prevent the spread of this deadly virus, those who are infected must be quarantined or evacuated. In this situation, a quick and systematic testing toolkit is required. Recent research has discovered that radiography chest CT has significant patterns and attributes that may be utilized to precisely identify COVID-19. A deep learning-based network called ResidualCovid-Net was suggested in this study to identify COVID-19 infestations using CT scans. The proposed ResidualCovid-Net is inspired by the original Resnet architecture. Another barrier in this aspect is clinically distinguishing among COVID-19, pneumonia and normal instances. ResidualCovid-Net was designed to identify anomalies in CT scans that may successfully delineate COVID-19, common pneumonia and normal cases. Gradients weighted class activation maps showed how well the network located anomalies in CT images and demonstrated the network’s generalization ability.
{"title":"ResidualCovid-Net: An Interpretable Deep Network to Screen COVID-19 Utilizing Chest CT Images","authors":"Md. Farukuzzaman Faruk","doi":"10.1109/ICEEE54059.2021.9718776","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718776","url":null,"abstract":"Coronavirus illness, commonly abbreviated as COVID-19, has been designated a global pandemic. To prevent the spread of this deadly virus, those who are infected must be quarantined or evacuated. In this situation, a quick and systematic testing toolkit is required. Recent research has discovered that radiography chest CT has significant patterns and attributes that may be utilized to precisely identify COVID-19. A deep learning-based network called ResidualCovid-Net was suggested in this study to identify COVID-19 infestations using CT scans. The proposed ResidualCovid-Net is inspired by the original Resnet architecture. Another barrier in this aspect is clinically distinguishing among COVID-19, pneumonia and normal instances. ResidualCovid-Net was designed to identify anomalies in CT scans that may successfully delineate COVID-19, common pneumonia and normal cases. Gradients weighted class activation maps showed how well the network located anomalies in CT images and demonstrated the network’s generalization ability.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"132 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":"131481226","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/ICEEE54059.2021.9718802
Tasnim Irtifa Chowdhury, M. Mowla
Recently, fifth generation (5G) wireless standard is entering into the implementation stage with some of the initial design concepts and ideas. The 5G standard triangle is designed for supporting enhanced mobile broadband, massive machine type communication, and ultra reliable communication for the users. One of the major inclusions of this design targets is to provide internet to the huge small devices with low power, Internet of Things (IoT). In this direction, 5G technology has started to ensure IoT connectivity for the next generation users. The single clustering approach does not ensure the high throughput with low block error rate. In this paper, we have used the facilities of 5G to design a novel multi-clustered 5G network for IoT applications. A systematic analysis of the network is performed using well-suited UMa (urban-macro), and UMa3D (urban-macro-3-dimensional) path-loss models, for femto cell (FC) and pico cell (PC) configurations. Our investigation shows the superior performances of signal-to-interference-noise ratio (SINR), and throughput for UMa3D and pico cell configuration than their counterpart. We also find stable throughput over a wide range of users for the same configuration through maintaining insignificant block error rate (BLER) difference. Therefore, the proposed network seems very promising for practical implementation.
{"title":"Design of a novel multi-clustered 5G network for IoT applications","authors":"Tasnim Irtifa Chowdhury, M. Mowla","doi":"10.1109/ICEEE54059.2021.9718802","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718802","url":null,"abstract":"Recently, fifth generation (5G) wireless standard is entering into the implementation stage with some of the initial design concepts and ideas. The 5G standard triangle is designed for supporting enhanced mobile broadband, massive machine type communication, and ultra reliable communication for the users. One of the major inclusions of this design targets is to provide internet to the huge small devices with low power, Internet of Things (IoT). In this direction, 5G technology has started to ensure IoT connectivity for the next generation users. The single clustering approach does not ensure the high throughput with low block error rate. In this paper, we have used the facilities of 5G to design a novel multi-clustered 5G network for IoT applications. A systematic analysis of the network is performed using well-suited UMa (urban-macro), and UMa3D (urban-macro-3-dimensional) path-loss models, for femto cell (FC) and pico cell (PC) configurations. Our investigation shows the superior performances of signal-to-interference-noise ratio (SINR), and throughput for UMa3D and pico cell configuration than their counterpart. We also find stable throughput over a wide range of users for the same configuration through maintaining insignificant block error rate (BLER) difference. Therefore, the proposed network seems very promising for practical implementation.","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":"126561493","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/ICEEE54059.2021.9718797
Shehan Irteza Pranto, Rahad Arman Nabid, Ahnaf Mozib Samin, Nabeel Mohammed, F. Sarker, M. N. Huda, K. Mamun
The research study presents an architecture of HumanRobot Interaction (HRI) based Artificial Conversational Entity integrated with speaker recognition ability to avail modern healthcare services. Due to the Covid-19 pandemic, the situation has become troublesome for health workers and patients to visit hospitals because of the high risk of virus dissemination. To minimize the mass congestion, our developed architecture would be an appropriate, cost-effective solution that automates the reception system by enabling AI-based HRI and providing fast and advanced healthcare services in the context of Bangladesh. The architecture consists of two significant subsections: Speaker Recognition and Artificial Conversational Entities having Automatic Speech Recognition in Bengali, Interactive Agent, and Text-to-Speech-synthesis. We used MFCC features as the linguistic parameters and the GMM statistical model to adapt each speaker’s voice and estimation and maximization algorithm to identify the speaker’s identity. The developed speaker recognition module performed significantly with 94.38% average accuracy in noisy environments and 96.27% average accuracy in studio quality environments and achieved a word error rate (WER) of 42.15% from RNN based Deep Speech 2 model for Bangla Automatic Speech Recognition (ASR). Besides, Artificial Conversational Entity performs with an average accuracy of 98.58% in a small-scale real-time environment.
{"title":"Human-Robot Interaction in Bengali language for Healthcare Automation integrated with Speaker Recognition and Artificial Conversational Entity","authors":"Shehan Irteza Pranto, Rahad Arman Nabid, Ahnaf Mozib Samin, Nabeel Mohammed, F. Sarker, M. N. Huda, K. Mamun","doi":"10.1109/ICEEE54059.2021.9718797","DOIUrl":"https://doi.org/10.1109/ICEEE54059.2021.9718797","url":null,"abstract":"The research study presents an architecture of HumanRobot Interaction (HRI) based Artificial Conversational Entity integrated with speaker recognition ability to avail modern healthcare services. Due to the Covid-19 pandemic, the situation has become troublesome for health workers and patients to visit hospitals because of the high risk of virus dissemination. To minimize the mass congestion, our developed architecture would be an appropriate, cost-effective solution that automates the reception system by enabling AI-based HRI and providing fast and advanced healthcare services in the context of Bangladesh. The architecture consists of two significant subsections: Speaker Recognition and Artificial Conversational Entities having Automatic Speech Recognition in Bengali, Interactive Agent, and Text-to-Speech-synthesis. We used MFCC features as the linguistic parameters and the GMM statistical model to adapt each speaker’s voice and estimation and maximization algorithm to identify the speaker’s identity. The developed speaker recognition module performed significantly with 94.38% average accuracy in noisy environments and 96.27% average accuracy in studio quality environments and achieved a word error rate (WER) of 42.15% from RNN based Deep Speech 2 model for Bangla Automatic Speech Recognition (ASR). Besides, Artificial Conversational Entity performs with an average accuracy of 98.58% in a small-scale real-time environment.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"43 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":"126436271","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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