Pub Date : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009396
K. Dixit, Arti Badhoutiya
Floating photovoltaic (FPV) systems are a new technology that can be used to generate electricity on water bodies. It is crucial to assess the current state and future expectations for technological advancements for solar power generation with value-added solutions, particularly since floating photovoltaic systems have facilities that float on the surface.India, which has a high consumption for energy and a dearth of urban waste land for solar photovoltaic plants, can capture solar energy through the use of floating PV plant technology. To achieve sustainable objectives the establishment of floating solar plants, or solar arrays above floating structures on water bodies, is regularly encouraged by the government.India is among the blessed countries that have around 400 rivers, which are vital to enhancing the livelihood of a sizable population. This paper includes present scenario of solar energy in India along with other leading countries predicting the futuristic possibilities to utilize solar energy in wide. Discussions include the layout of solar cells, connections, power delivery, potential environmental effects, and coastal power management. The configuration of FPV's along with its positive and negative sides are briefly explained here.
{"title":"Emergence of Floating Solar Module Energy Generating Technology","authors":"K. Dixit, Arti Badhoutiya","doi":"10.1109/ICECA55336.2022.10009396","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009396","url":null,"abstract":"Floating photovoltaic (FPV) systems are a new technology that can be used to generate electricity on water bodies. It is crucial to assess the current state and future expectations for technological advancements for solar power generation with value-added solutions, particularly since floating photovoltaic systems have facilities that float on the surface.India, which has a high consumption for energy and a dearth of urban waste land for solar photovoltaic plants, can capture solar energy through the use of floating PV plant technology. To achieve sustainable objectives the establishment of floating solar plants, or solar arrays above floating structures on water bodies, is regularly encouraged by the government.India is among the blessed countries that have around 400 rivers, which are vital to enhancing the livelihood of a sizable population. This paper includes present scenario of solar energy in India along with other leading countries predicting the futuristic possibilities to utilize solar energy in wide. Discussions include the layout of solar cells, connections, power delivery, potential environmental effects, and coastal power management. The configuration of FPV's along with its positive and negative sides are briefly explained here.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130363243","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009511
Jeethu Philip, Venkata Nagaraju Thatha, M. Harshini, I. Haritha, Shruti Patil, B. Veerasekhar Reddy
Recently COVID-19 has become the most discussed topic in different social media platforms like Twitter, Facebook, Instagram etc. As time moves on, lot of messages and videos are posted in social media. As expected, most of the public followed these messages and becomes panic because of lack of information, misinformation about COVID-19 and its impact. This research study proposes a Twitter sentiment analysisbased on the most popular vaccines Covaxin, Covishield, and Pfizer. Most of the people expressed their feelings about vaccines in the twitter. Twitter API authentication is used here to extract the tweets. These extracted tweets are difficult to analyze, hence pre-processing has been done i.e., unstructured data is converted into structured format. After completion of preprocessing, the data is further classified by using Naïve Bayes algorithm. This algorithm performs data classification and divides it into three major classes as positive, negative, and neutral. The result shows that the covaxin yields 48.36% positive, 35.6% negative, and 16.04% neutral, Covishield yields 44.25% positive, 39.67% negative, and 16.08% neutral, Pfizer yields 42.95% positive, 39.45% negative, and 17.6% neutral sentiment.
{"title":"Classification of Covid-19 Vaccines tweets using Naïve Bayes Classification","authors":"Jeethu Philip, Venkata Nagaraju Thatha, M. Harshini, I. Haritha, Shruti Patil, B. Veerasekhar Reddy","doi":"10.1109/ICECA55336.2022.10009511","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009511","url":null,"abstract":"Recently COVID-19 has become the most discussed topic in different social media platforms like Twitter, Facebook, Instagram etc. As time moves on, lot of messages and videos are posted in social media. As expected, most of the public followed these messages and becomes panic because of lack of information, misinformation about COVID-19 and its impact. This research study proposes a Twitter sentiment analysisbased on the most popular vaccines Covaxin, Covishield, and Pfizer. Most of the people expressed their feelings about vaccines in the twitter. Twitter API authentication is used here to extract the tweets. These extracted tweets are difficult to analyze, hence pre-processing has been done i.e., unstructured data is converted into structured format. After completion of preprocessing, the data is further classified by using Naïve Bayes algorithm. This algorithm performs data classification and divides it into three major classes as positive, negative, and neutral. The result shows that the covaxin yields 48.36% positive, 35.6% negative, and 16.04% neutral, Covishield yields 44.25% positive, 39.67% negative, and 16.08% neutral, Pfizer yields 42.95% positive, 39.45% negative, and 17.6% neutral sentiment.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115788526","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009347
M. Devi, V. Jyothi, D. Nagajyothi
Automatic pet feeder system is designed which is used to take care of pets such as cat and dog. The pet feeder system can deliver food, water and monitor the motion of the pet. This machine is equipped with a different embedded components which is helpful to feed food and dispense water without any human intervention. Unfortunately, due to their hectic schedules and limited time at work, they have neglected their pets and have left them hungry. This project mainly designed for people for saving their time and energy by feeding their pets on time and monitoring through the designated application. The monitoring has been done because of internet connection has been provided through the gadget so that the user can observe the pet's feeding on the corresponding Thing speak cloud. The Arduino UNO and the server motor are among the machine's novel components, which are employed in a bottle that may endure for a week with electrical connections. The purpose of this is to feed food for pets automatically based on amount of food available and also on time. Consequently, most of this pet feeders on the market are operated manually, and these feeders not even use IoT methods. Users may use this Pet Feeder automatically, eliminating the need to worry about their dogs. Those who love pets will be loving to select this type of machine for their pets at home. By using this type of machine consumer will also be less concerned about leaving their pets for small period, such as when returning to their hometown or working full-time. Finally, especially in the mechanical business, it is an excellent technique to increase and employ top and local users. This is quite helpful for the people who has pet, and it uses latest technology where it encourages Internet of things along with Embedded system as it can be applicable for local industrial petting upgrading.
{"title":"IoT and Cloud-based Automated Pet Care System","authors":"M. Devi, V. Jyothi, D. Nagajyothi","doi":"10.1109/ICECA55336.2022.10009347","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009347","url":null,"abstract":"Automatic pet feeder system is designed which is used to take care of pets such as cat and dog. The pet feeder system can deliver food, water and monitor the motion of the pet. This machine is equipped with a different embedded components which is helpful to feed food and dispense water without any human intervention. Unfortunately, due to their hectic schedules and limited time at work, they have neglected their pets and have left them hungry. This project mainly designed for people for saving their time and energy by feeding their pets on time and monitoring through the designated application. The monitoring has been done because of internet connection has been provided through the gadget so that the user can observe the pet's feeding on the corresponding Thing speak cloud. The Arduino UNO and the server motor are among the machine's novel components, which are employed in a bottle that may endure for a week with electrical connections. The purpose of this is to feed food for pets automatically based on amount of food available and also on time. Consequently, most of this pet feeders on the market are operated manually, and these feeders not even use IoT methods. Users may use this Pet Feeder automatically, eliminating the need to worry about their dogs. Those who love pets will be loving to select this type of machine for their pets at home. By using this type of machine consumer will also be less concerned about leaving their pets for small period, such as when returning to their hometown or working full-time. Finally, especially in the mechanical business, it is an excellent technique to increase and employ top and local users. This is quite helpful for the people who has pet, and it uses latest technology where it encourages Internet of things along with Embedded system as it can be applicable for local industrial petting upgrading.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115799093","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009599
G. B, S. B. V., Vishveshvaran R
India's economy is heavily reliant on agriculture, which is also a significant source of crop production. The livelihood of a sizable portion of India's population depends on yield production. Agriculture-related problems are a current primary concern in the modern era. The primary challenge for agricultural growth is the need to maintain the wellbeing of the plants and the crops. One industry that significantly affects people's lives and the state of the economy is agriculture. Poor management leads to the loss of agricultural products. The most delicate plant leaves are the first to show symptoms of sickness. The use of equipment to anticipate disease has proven to be quicker, less expensive, and more reliable than farmers' traditional method of manual observation. Most often, disease symptoms are visible on the leaves, stems, and fruits. The crop's productivity is impacted by a number of factors. Climate change, insect infestations, and numerous plant diseases are some of the contributing reasons. An automatic detection system is intended to pick up illness signs as they emerge or progress. In the paper, a method for using deep learning and image processing to detect illnesses in leaves is revealed.
{"title":"A Survey on Deep Learning Prediction Techniques for Plant Contagion","authors":"G. B, S. B. V., Vishveshvaran R","doi":"10.1109/ICECA55336.2022.10009599","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009599","url":null,"abstract":"India's economy is heavily reliant on agriculture, which is also a significant source of crop production. The livelihood of a sizable portion of India's population depends on yield production. Agriculture-related problems are a current primary concern in the modern era. The primary challenge for agricultural growth is the need to maintain the wellbeing of the plants and the crops. One industry that significantly affects people's lives and the state of the economy is agriculture. Poor management leads to the loss of agricultural products. The most delicate plant leaves are the first to show symptoms of sickness. The use of equipment to anticipate disease has proven to be quicker, less expensive, and more reliable than farmers' traditional method of manual observation. Most often, disease symptoms are visible on the leaves, stems, and fruits. The crop's productivity is impacted by a number of factors. Climate change, insect infestations, and numerous plant diseases are some of the contributing reasons. An automatic detection system is intended to pick up illness signs as they emerge or progress. In the paper, a method for using deep learning and image processing to detect illnesses in leaves is revealed.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124460582","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009358
A. V. Kumar, G. Vyshnavi, P. Harshini, Papareddy Sushanth Reddy
A quick growth of information sharing and transferring has been observed recently. Everything is getting digitized, and everyone requires a simple and straightforward method. As a result, the number of fake documents generated for job applications is increasing, and checking all the documents manually is not a good option as it takes a lot of time. Therefore, digitizing documents is becoming an increasingly popular option for companies and individuals as it is the most secure and least time-consuming way of verifying documents. As Blockchain is a decentralized system that guarantees the protection of data kept in it, this article proposes a solution based on Federated Blockchain technology that allows specific organizations to submit candidates' original documents. It validates the student's submitted document hash value by comparing the existing cryptographic hash in the Blockchain. SHA-512 is used to generate the hash values for the documents. This technique is incredibly efficient, consumes less time, and is less expensive to execute all types of verifications.
{"title":"A Blockchain-based Document Verification Model in Freshers Hiring Process","authors":"A. V. Kumar, G. Vyshnavi, P. Harshini, Papareddy Sushanth Reddy","doi":"10.1109/ICECA55336.2022.10009358","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009358","url":null,"abstract":"A quick growth of information sharing and transferring has been observed recently. Everything is getting digitized, and everyone requires a simple and straightforward method. As a result, the number of fake documents generated for job applications is increasing, and checking all the documents manually is not a good option as it takes a lot of time. Therefore, digitizing documents is becoming an increasingly popular option for companies and individuals as it is the most secure and least time-consuming way of verifying documents. As Blockchain is a decentralized system that guarantees the protection of data kept in it, this article proposes a solution based on Federated Blockchain technology that allows specific organizations to submit candidates' original documents. It validates the student's submitted document hash value by comparing the existing cryptographic hash in the Blockchain. SHA-512 is used to generate the hash values for the documents. This technique is incredibly efficient, consumes less time, and is less expensive to execute all types of verifications.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"274 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134450384","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009285
S. S., T. Sheela, T. Muthumanickam
Now-a-davs Internet of Things (IoT) is used in various real-time applications, Including smart health monitoring. The existing health monitoring system can only collect the basic information about heat. heartbeat. and BP (Blood Pressure). This research study proposes an effective examination of patient's brain signals and detect the health status of the patient in real time. The main objective of the proposed study is to provide a proper optimized value about the mentally challenged patients by collecting the data information from brain signals with 24 channels and study the body parameters through each EEG (Electroencephalography) signal channel. Here, the collected data is pre-processed by using Machine Learninz (ML) tools and Neural Networks (NN) with Python programming language, By collecting the data information from brain signals with EEG sensors, an optimized value and solution can be provided to the patients suffering from Cerebral Palsy (CP). The collected data is then stored in a cloud storage platform and it can be accessed from any remote location. The stored data is then collected and filtered by using PCA techniques and further the Artifact siznals (Noise) are removed to diagnose seizures by Identifying brain signal parameters (Alpha, Beta, Delta and Theta). Further, a novel model has been designed by using python programming languaze for training the machine with a maximum number of datasets in order to check accuracy and predict the seizure levels of any CP patient. Neural Network (NN) algorithms were applied here by using python programming language in order to check the percentage error in the data processing mechanism. Once the data is analyzed with the proposed model it suggests the CP patient for Tentative Treatment.
{"title":"IoT Enabled Health Monitoring System using Machine Learning Algorithm","authors":"S. S., T. Sheela, T. Muthumanickam","doi":"10.1109/ICECA55336.2022.10009285","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009285","url":null,"abstract":"Now-a-davs Internet of Things (IoT) is used in various real-time applications, Including smart health monitoring. The existing health monitoring system can only collect the basic information about heat. heartbeat. and BP (Blood Pressure). This research study proposes an effective examination of patient's brain signals and detect the health status of the patient in real time. The main objective of the proposed study is to provide a proper optimized value about the mentally challenged patients by collecting the data information from brain signals with 24 channels and study the body parameters through each EEG (Electroencephalography) signal channel. Here, the collected data is pre-processed by using Machine Learninz (ML) tools and Neural Networks (NN) with Python programming language, By collecting the data information from brain signals with EEG sensors, an optimized value and solution can be provided to the patients suffering from Cerebral Palsy (CP). The collected data is then stored in a cloud storage platform and it can be accessed from any remote location. The stored data is then collected and filtered by using PCA techniques and further the Artifact siznals (Noise) are removed to diagnose seizures by Identifying brain signal parameters (Alpha, Beta, Delta and Theta). Further, a novel model has been designed by using python programming languaze for training the machine with a maximum number of datasets in order to check accuracy and predict the seizure levels of any CP patient. Neural Network (NN) algorithms were applied here by using python programming language in order to check the percentage error in the data processing mechanism. Once the data is analyzed with the proposed model it suggests the CP patient for Tentative Treatment.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131680226","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009093
Rama Krishna Peddarapu, Sofia Ameena, S. Yashaswini, Nadipelli Shreshta, Muppidi PurnaSahithi
The varying customer requirements and interests often result in subscription cancellation. Hence, running a subscription business necessitates an accurate churn forecasting model as even a minor change will result in a significant impact. If the seller is not informed that the customer is about to cancel the subscription, no action will be taken to retain them. As a result, this research study attempts to design and develop a churn prediction model to predict a subscription cancellation and provide incentives for that particular subscriber to stay back. This results in significant cost savings and generate an additional revenue source for any online business. The primary goal of this research work is to analyze different models for predicting the active churners with high accuracy. In existing systems, the service providers track down the clients before they leave in order to solve this problem. This study has compared the well-known machine learning techniques to solve the problem and also predict the results in a more accurate way.
{"title":"Customer Churn Prediction using Machine Learning","authors":"Rama Krishna Peddarapu, Sofia Ameena, S. Yashaswini, Nadipelli Shreshta, Muppidi PurnaSahithi","doi":"10.1109/ICECA55336.2022.10009093","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009093","url":null,"abstract":"The varying customer requirements and interests often result in subscription cancellation. Hence, running a subscription business necessitates an accurate churn forecasting model as even a minor change will result in a significant impact. If the seller is not informed that the customer is about to cancel the subscription, no action will be taken to retain them. As a result, this research study attempts to design and develop a churn prediction model to predict a subscription cancellation and provide incentives for that particular subscriber to stay back. This results in significant cost savings and generate an additional revenue source for any online business. The primary goal of this research work is to analyze different models for predicting the active churners with high accuracy. In existing systems, the service providers track down the clients before they leave in order to solve this problem. This study has compared the well-known machine learning techniques to solve the problem and also predict the results in a more accurate way.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132258786","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009434
Sindhuja R, S. K, P. E., P. S
In recent years, classical inverters such as the H-bridged cascaded multilevel inverter, flying capacitor, and flying capacitor multilevel inverter have contributed in electric vehicle and non-conventional energy applications. Due to higher switching and conduction losses, as well as a greater number of power switches and driver circuits, conventional multilevel inverters do not achieve the highest performance. To obtain higher performance while reducing power losses and total harmonic distortion, individual switches are controlled by logic gates. In this proposed work, one of the inverters is considered symmetrical voltage another is asymmetrical voltage for implementing these effective topologies. The proposed single-phase seven-level voltage output and current for both symmetric and asymmetric multilevel inverters are employed to test the intended computation. The MATLAB/Simulink tool is used to implement and investigate the various parameters of proposed topologies.
{"title":"A Reconfigurable Multilevel Inverters with Minimal Switches for Battery Charging and Renewable Energy Applications","authors":"Sindhuja R, S. K, P. E., P. S","doi":"10.1109/ICECA55336.2022.10009434","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009434","url":null,"abstract":"In recent years, classical inverters such as the H-bridged cascaded multilevel inverter, flying capacitor, and flying capacitor multilevel inverter have contributed in electric vehicle and non-conventional energy applications. Due to higher switching and conduction losses, as well as a greater number of power switches and driver circuits, conventional multilevel inverters do not achieve the highest performance. To obtain higher performance while reducing power losses and total harmonic distortion, individual switches are controlled by logic gates. In this proposed work, one of the inverters is considered symmetrical voltage another is asymmetrical voltage for implementing these effective topologies. The proposed single-phase seven-level voltage output and current for both symmetric and asymmetric multilevel inverters are employed to test the intended computation. The MATLAB/Simulink tool is used to implement and investigate the various parameters of proposed topologies.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134305801","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009057
Sneha M S, B. Yamuna, Karthi Balasubramanian
Polar codes are highly channel efficient with minimum hardware complexity with increasing code length, making them one of the most favorable error-correcting codes. There exist many architectures for both encoding and decoding of polar codes. In this paper a modified partially parallel polar encoder architecture is proposed. The registers that are used for inducing the parallelism in the architecture are replaced with pulsed latches, making the whole architecture low power and area efficient. The synthesis and simulation of the proposed architecture is carried out in Xilinx ISE for (16,k), (32,k) and (64,k) polar codes. Results show that the proposed architecture leads to an average reduction of 50% and 45% in power and gate count respectively.
{"title":"A Modified Partially Parallel Polar Encoder Architecture","authors":"Sneha M S, B. Yamuna, Karthi Balasubramanian","doi":"10.1109/ICECA55336.2022.10009057","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009057","url":null,"abstract":"Polar codes are highly channel efficient with minimum hardware complexity with increasing code length, making them one of the most favorable error-correcting codes. There exist many architectures for both encoding and decoding of polar codes. In this paper a modified partially parallel polar encoder architecture is proposed. The registers that are used for inducing the parallelism in the architecture are replaced with pulsed latches, making the whole architecture low power and area efficient. The synthesis and simulation of the proposed architecture is carried out in Xilinx ISE for (16,k), (32,k) and (64,k) polar codes. Results show that the proposed architecture leads to an average reduction of 50% and 45% in power and gate count respectively.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132675340","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009628
P. S. Kumar, S. Sudha, P. Das, D. Pradeep, S. J, K. Vijaipriya
Fruits are an excellent source of nutrients and minerals. They have a high concentration of antioxidants and flavonoids, which are beneficial to one's health. Pomegranates have a high potential in preventing cell damage, boosting our immunity, helping with smooth digestion, fighting type-2 diabetes, keeping vital parameters in check and are seen to be effective inthe prevention of cancers. India is considered the largest producer of excellent varieties of pomegranates and thus the quality analysis in the export operation of pomegranates is highly concerned. Grading of pomegranates is very necessary for post-harvest management and is performed based on the external appearance like attractive colours, texture, size and shape which decides the standard of the fruit. Manual grading can be done which requires human operation and consumes more time. Hence quality assessment of pomegranates can be done using Machine Learning(ML) which is highly efficient. The process of feature extraction yields accurate results and can be done quickly. ML technology improves accuracy and efficiency and has improved user experience. The review paper proposes an efficient ML approach for pomegranate quality analysis using Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP) feature extraction methods. K-Nearest Neighbour (KNN) and Naive Bayes (NB) algorithms are implemented in the designed model using both sets of feature extractors and the result illustrates that the LBP + NB model performs with better efficiency and greater accuracy.
{"title":"Pomegranate Quality Analysis and Classification Using Feature Extraction and Machine Learning","authors":"P. S. Kumar, S. Sudha, P. Das, D. Pradeep, S. J, K. Vijaipriya","doi":"10.1109/ICECA55336.2022.10009628","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009628","url":null,"abstract":"Fruits are an excellent source of nutrients and minerals. They have a high concentration of antioxidants and flavonoids, which are beneficial to one's health. Pomegranates have a high potential in preventing cell damage, boosting our immunity, helping with smooth digestion, fighting type-2 diabetes, keeping vital parameters in check and are seen to be effective inthe prevention of cancers. India is considered the largest producer of excellent varieties of pomegranates and thus the quality analysis in the export operation of pomegranates is highly concerned. Grading of pomegranates is very necessary for post-harvest management and is performed based on the external appearance like attractive colours, texture, size and shape which decides the standard of the fruit. Manual grading can be done which requires human operation and consumes more time. Hence quality assessment of pomegranates can be done using Machine Learning(ML) which is highly efficient. The process of feature extraction yields accurate results and can be done quickly. ML technology improves accuracy and efficiency and has improved user experience. The review paper proposes an efficient ML approach for pomegranate quality analysis using Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP) feature extraction methods. K-Nearest Neighbour (KNN) and Naive Bayes (NB) algorithms are implemented in the designed model using both sets of feature extractors and the result illustrates that the LBP + NB model performs with better efficiency and greater accuracy.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114785620","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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