Pub Date : 2023-03-03DOI: 10.1109/INOCON57975.2023.10101072
Pratyusha Thogarchety, K. Das
Statistical machine learning models suffer poorly because of class imbalance issue. Real world dataset contains mostly ‘normal’ examples and very few ‘abnormal’ examples and in most of the cases, the primary goal is to identify the abnormal instances. For example, if we want to develop a statistical machine learning model to identify financial fraud using the historical transaction data then we can expect that majority of the data comes from normal/non-fraudulent class, whereas very few examples are fraudulent transactions. Using such imbalanced dataset for training makes machine learning models highly biased towards majority non-fraudulent class. This way, the objective to catch fraudulent transaction instances fails and misclassifying such minority class instances often results in a much higher cost. Hence, a balanced dataset is very much required to train a sound model. Different techniques such as under sampling, oversampling, SMOTE were proposed earlier. In this paper, we propose a novel technique to generate synthetic data using genetic search algorithm. We examined the effectiveness of our proposed algorithm on different datasets and reported in section V.
{"title":"Synthetic Data Generation Using Genetic Algorithm","authors":"Pratyusha Thogarchety, K. Das","doi":"10.1109/INOCON57975.2023.10101072","DOIUrl":"https://doi.org/10.1109/INOCON57975.2023.10101072","url":null,"abstract":"Statistical machine learning models suffer poorly because of class imbalance issue. Real world dataset contains mostly ‘normal’ examples and very few ‘abnormal’ examples and in most of the cases, the primary goal is to identify the abnormal instances. For example, if we want to develop a statistical machine learning model to identify financial fraud using the historical transaction data then we can expect that majority of the data comes from normal/non-fraudulent class, whereas very few examples are fraudulent transactions. Using such imbalanced dataset for training makes machine learning models highly biased towards majority non-fraudulent class. This way, the objective to catch fraudulent transaction instances fails and misclassifying such minority class instances often results in a much higher cost. Hence, a balanced dataset is very much required to train a sound model. Different techniques such as under sampling, oversampling, SMOTE were proposed earlier. In this paper, we propose a novel technique to generate synthetic data using genetic search algorithm. We examined the effectiveness of our proposed algorithm on different datasets and reported in section V.","PeriodicalId":113637,"journal":{"name":"2023 2nd International Conference for Innovation in Technology (INOCON)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124010995","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 : 2023-03-03DOI: 10.1109/INOCON57975.2023.10100997
D. Meena, Aryan Motla, Anuj Majumdar, Aatish Kumar Ghosh
Electric Vehicles are growing faster than the traditional combustion vehicles which are powered by conventional energy resources because of the environmental concern and to attain sustainable development. Formula student is one of the world’s largest student-run competitions. Formula student electric development includes various challenges from both mechanical and electrical fronts. Mechanical parts have their safety standards and measures whereas for electrical front robust safety circuitry must be prepared to reduce the risk of any fatal accident. Generally, Formula student cars are fast and good acceleration, to avoid wheel-to-wheel racing and drag racing or other dangerous stunts, a robust safety circuit Brake system Plausibility Device (BSPD) is designed and tested. This paper discusses the designing, robustness of BSPD devices.
{"title":"Development of Brake System Plausibility Device of an FSAE Race Car","authors":"D. Meena, Aryan Motla, Anuj Majumdar, Aatish Kumar Ghosh","doi":"10.1109/INOCON57975.2023.10100997","DOIUrl":"https://doi.org/10.1109/INOCON57975.2023.10100997","url":null,"abstract":"Electric Vehicles are growing faster than the traditional combustion vehicles which are powered by conventional energy resources because of the environmental concern and to attain sustainable development. Formula student is one of the world’s largest student-run competitions. Formula student electric development includes various challenges from both mechanical and electrical fronts. Mechanical parts have their safety standards and measures whereas for electrical front robust safety circuitry must be prepared to reduce the risk of any fatal accident. Generally, Formula student cars are fast and good acceleration, to avoid wheel-to-wheel racing and drag racing or other dangerous stunts, a robust safety circuit Brake system Plausibility Device (BSPD) is designed and tested. This paper discusses the designing, robustness of BSPD devices.","PeriodicalId":113637,"journal":{"name":"2023 2nd International Conference for Innovation in Technology (INOCON)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124614363","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 : 2023-03-03DOI: 10.1109/INOCON57975.2023.10101110
S. Patil, Y. M. Patil, S. B. Patil
An extremely useful mechanism in the agriculture industry for efficient crop production is spraying activities. The current spray methods are inefficient. Spraying at a variable pace is the best option in this case. The size of the tree canopy must be accurately estimated in order to spray pesticides at variable rates. Due of the diverse growing structures and different plant sizes, it is difficult. Trees are seen to have a variety of shapes and dimensions throughout the growth seasons. It is vital to take into account elements like tree height, width, diameter, and total canopy volume in order to assess this alteration. The amount of a tree’s canopy is calculated in this study utilizing ultrasonic sensors, controller and a spraying mechanism is constructed in proportion to the volume of that plant. The ultrasonic sensor, controller and spraying mechanism are all part of the system. With the aid of sensors, geometrical properties of the tree are identified. A series of experiments were carried out on samples of plants with various sizes and forms. For plant sample applications, liquid pesticide savings were greater than a traditional application. Results demonstrated no discernible difference between tree canopy volumes estimated by ultrasound sensor and by person. The procedures for variable rate spraying techniques in orchards are presented in this article. The study of the creation of cost-effective precision spraying techniques using sensor technology is the major contribution of this work. Out of all of these strategies, this study will assist in selecting and designing the most effective and affordable way for a precision sprayer.
{"title":"Development of Cost-Effective Precision Spraying Techniques Using Sensor Technology","authors":"S. Patil, Y. M. Patil, S. B. Patil","doi":"10.1109/INOCON57975.2023.10101110","DOIUrl":"https://doi.org/10.1109/INOCON57975.2023.10101110","url":null,"abstract":"An extremely useful mechanism in the agriculture industry for efficient crop production is spraying activities. The current spray methods are inefficient. Spraying at a variable pace is the best option in this case. The size of the tree canopy must be accurately estimated in order to spray pesticides at variable rates. Due of the diverse growing structures and different plant sizes, it is difficult. Trees are seen to have a variety of shapes and dimensions throughout the growth seasons. It is vital to take into account elements like tree height, width, diameter, and total canopy volume in order to assess this alteration. The amount of a tree’s canopy is calculated in this study utilizing ultrasonic sensors, controller and a spraying mechanism is constructed in proportion to the volume of that plant. The ultrasonic sensor, controller and spraying mechanism are all part of the system. With the aid of sensors, geometrical properties of the tree are identified. A series of experiments were carried out on samples of plants with various sizes and forms. For plant sample applications, liquid pesticide savings were greater than a traditional application. Results demonstrated no discernible difference between tree canopy volumes estimated by ultrasound sensor and by person. The procedures for variable rate spraying techniques in orchards are presented in this article. The study of the creation of cost-effective precision spraying techniques using sensor technology is the major contribution of this work. Out of all of these strategies, this study will assist in selecting and designing the most effective and affordable way for a precision sprayer.","PeriodicalId":113637,"journal":{"name":"2023 2nd International Conference for Innovation in Technology (INOCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128380871","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 : 2023-03-03DOI: 10.1109/INOCON57975.2023.10101366
Reshma Banu, G. F. A. Ahammed, G. Divya, V. D. Reddy, Nuthanakanti Bhaskar, M. Kanthi
The basic purpose of sentiment analysis is to determine how someone feels when they comment or express their feelings or emotions. Positive, neutral, and negative emotions are the three categories into which emotions are divided. Everyone will use and apply this analysis on social media; online; everyone expresses their opinions by clicking on the like, remark, or share buttons. Using the Random Forest, SVM, and Nave Bayes algorithms, the Twitter tweets in this study were identified as positive or negative, with F1-Scores of 0.224, 0.410, and 0.702, respectively, and accuracy values of 50%, 52%, and 73%.
{"title":"Sentiment Analysis for Real-Time Micro Blogs using Twitter Data","authors":"Reshma Banu, G. F. A. Ahammed, G. Divya, V. D. Reddy, Nuthanakanti Bhaskar, M. Kanthi","doi":"10.1109/INOCON57975.2023.10101366","DOIUrl":"https://doi.org/10.1109/INOCON57975.2023.10101366","url":null,"abstract":"The basic purpose of sentiment analysis is to determine how someone feels when they comment or express their feelings or emotions. Positive, neutral, and negative emotions are the three categories into which emotions are divided. Everyone will use and apply this analysis on social media; online; everyone expresses their opinions by clicking on the like, remark, or share buttons. Using the Random Forest, SVM, and Nave Bayes algorithms, the Twitter tweets in this study were identified as positive or negative, with F1-Scores of 0.224, 0.410, and 0.702, respectively, and accuracy values of 50%, 52%, and 73%.","PeriodicalId":113637,"journal":{"name":"2023 2nd International Conference for Innovation in Technology (INOCON)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128724535","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 : 2023-03-03DOI: 10.1109/INOCON57975.2023.10101168
Shradhanand Dahiya, M. Garg, Kumar Sourabh Mani
Light Emitting Diode (LED) technology has emerged as a better alternative to conventional lighting options like incandescent lamps, CFLs, etc. It has various advantages over conventional alternatives, e.g., better efficiency, longer life, multi-colored light, fast dimming capabilities, etc. LED driver circuits are adapted to supply power to LED loads. When LEDs are supplied through the AC mains, they are required to operate at a power factor near unity, creating a need for power factor correction (PFC) in the driver circuit. Also, the driver circuit should maintain a constant voltage at the load terminal such that a flicker-free operation of the LED is obtained. Buck-boost PFC configuration, derived from the basic buck-boost converter when operated in the discontinuous current conduction mode has inherent power factor correction property. This simplifies the control of the configuration to only a single voltage control loop. Active Disturbance Rejection Control (ADRC) is based on the control law implemented with the help of estimated states which are estimated with the help of an Extended State Observer (ESO). This work is focused on extending the concept of linear ADRC (LADRC) to buck-boost PFC based LED driver circuit and to evaluate its performance.
{"title":"Linear Active Disturbance Rejection Control of Buck-boost PFC based LED Driver Circuit","authors":"Shradhanand Dahiya, M. Garg, Kumar Sourabh Mani","doi":"10.1109/INOCON57975.2023.10101168","DOIUrl":"https://doi.org/10.1109/INOCON57975.2023.10101168","url":null,"abstract":"Light Emitting Diode (LED) technology has emerged as a better alternative to conventional lighting options like incandescent lamps, CFLs, etc. It has various advantages over conventional alternatives, e.g., better efficiency, longer life, multi-colored light, fast dimming capabilities, etc. LED driver circuits are adapted to supply power to LED loads. When LEDs are supplied through the AC mains, they are required to operate at a power factor near unity, creating a need for power factor correction (PFC) in the driver circuit. Also, the driver circuit should maintain a constant voltage at the load terminal such that a flicker-free operation of the LED is obtained. Buck-boost PFC configuration, derived from the basic buck-boost converter when operated in the discontinuous current conduction mode has inherent power factor correction property. This simplifies the control of the configuration to only a single voltage control loop. Active Disturbance Rejection Control (ADRC) is based on the control law implemented with the help of estimated states which are estimated with the help of an Extended State Observer (ESO). This work is focused on extending the concept of linear ADRC (LADRC) to buck-boost PFC based LED driver circuit and to evaluate its performance.","PeriodicalId":113637,"journal":{"name":"2023 2nd International Conference for Innovation in Technology (INOCON)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127270136","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 : 2023-03-03DOI: 10.1109/INOCON57975.2023.10100991
M. Hossen, T. Ahmad, Ntivuguruzwa Jean De La Croix
Our information is constantly under threat when transmitted through public networks. So, research to keep information secret has been carried out. Mainly, steganography, which consists of hiding data in digital media, receives much attention. Existing steganographic systems identified the need to improve performance by reducing a tradeoff between the peak signal-to-noise ratio (PSNR) and bits per pixel (BPP). In this paper, we propose a new steganographic scheme to embed the bits of secret messages in a digital image’s pixels. Our method expands the differences between the neighbouring pixels for secret data concealment. We group the pixels in blocks of size $1times 3$, and two of the three pixels of the block are candidates to hold the secret bit. We also propose extracting the hidden data to validate our data concealment scheme. To extract the secret data, we also arrange the neighbouring pixels into blocks of three and use their differences, and a modulus function, based on pixels identified carrying the secret data based on the key generated during data concealment. To evaluate the performance of our scheme, we consider the PSNR and the BPP as metrics. The experimental results showed better performance over the existing methods with 68.7790 dB for the PSNR and 0.1562 BPP.
{"title":"Data Hiding Scheme using Difference Expansion and Modulus Function","authors":"M. Hossen, T. Ahmad, Ntivuguruzwa Jean De La Croix","doi":"10.1109/INOCON57975.2023.10100991","DOIUrl":"https://doi.org/10.1109/INOCON57975.2023.10100991","url":null,"abstract":"Our information is constantly under threat when transmitted through public networks. So, research to keep information secret has been carried out. Mainly, steganography, which consists of hiding data in digital media, receives much attention. Existing steganographic systems identified the need to improve performance by reducing a tradeoff between the peak signal-to-noise ratio (PSNR) and bits per pixel (BPP). In this paper, we propose a new steganographic scheme to embed the bits of secret messages in a digital image’s pixels. Our method expands the differences between the neighbouring pixels for secret data concealment. We group the pixels in blocks of size $1times 3$, and two of the three pixels of the block are candidates to hold the secret bit. We also propose extracting the hidden data to validate our data concealment scheme. To extract the secret data, we also arrange the neighbouring pixels into blocks of three and use their differences, and a modulus function, based on pixels identified carrying the secret data based on the key generated during data concealment. To evaluate the performance of our scheme, we consider the PSNR and the BPP as metrics. The experimental results showed better performance over the existing methods with 68.7790 dB for the PSNR and 0.1562 BPP.","PeriodicalId":113637,"journal":{"name":"2023 2nd International Conference for Innovation in Technology (INOCON)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127407007","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 : 2023-03-03DOI: 10.1109/INOCON57975.2023.10101312
R. Barreto, Jose Cornejo, R. Palomares, Jorge A. Cornejo, Juan Carlos Suárez-Quispe, Mariela Vargas, Cristián Valenzuela, J. C. Chávez, Julio Valdivia
The research line of Controlled Environment Agriculture (CEA) in the Division of Biomechatronics and Life Support Systems at the Center of Space Emerging Technologies (C-SET) developed a multi-collaborative study in order to present a micro-literature review of the innovative synergistic connection between mechatronics technologies and space agriculture, which consists of to collect information about the latest developments in this field. At the same time, this review targets to showcase the challenges and solutions to achieve a sustainable source of food for future astronauts for long-term spaceflight travels or colonizing other celestial bodies. Said solutions could be applied to the colonization of places such as the Moon and Mars, that already have research concerning their regolith. This work addresses and classifies the relevant studies in terms of applications, materials, and advances. Moreover, identify ongoing challenges and discuss future requirements for agriculture outside the Earth. Finally, this is the first research conducted in Latin America that summarizes the historical data related to plants in space.
{"title":"Space Agriculture and Mechatronic Technologies: Micro-Review and Multi-Collaborative Study","authors":"R. Barreto, Jose Cornejo, R. Palomares, Jorge A. Cornejo, Juan Carlos Suárez-Quispe, Mariela Vargas, Cristián Valenzuela, J. C. Chávez, Julio Valdivia","doi":"10.1109/INOCON57975.2023.10101312","DOIUrl":"https://doi.org/10.1109/INOCON57975.2023.10101312","url":null,"abstract":"The research line of Controlled Environment Agriculture (CEA) in the Division of Biomechatronics and Life Support Systems at the Center of Space Emerging Technologies (C-SET) developed a multi-collaborative study in order to present a micro-literature review of the innovative synergistic connection between mechatronics technologies and space agriculture, which consists of to collect information about the latest developments in this field. At the same time, this review targets to showcase the challenges and solutions to achieve a sustainable source of food for future astronauts for long-term spaceflight travels or colonizing other celestial bodies. Said solutions could be applied to the colonization of places such as the Moon and Mars, that already have research concerning their regolith. This work addresses and classifies the relevant studies in terms of applications, materials, and advances. Moreover, identify ongoing challenges and discuss future requirements for agriculture outside the Earth. Finally, this is the first research conducted in Latin America that summarizes the historical data related to plants in space.","PeriodicalId":113637,"journal":{"name":"2023 2nd International Conference for Innovation in Technology (INOCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130084293","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 : 2023-03-03DOI: 10.1109/INOCON57975.2023.10101125
Barsha Biswas, R. Yadav
Around 38% of land in the world is used for agriculture and the whole world is completely dependent on agriculture. So, that’s why good crop yield is very important to get high agricultural output. A single disease in a plant can lower crop yield. So, to maintain a high agricultural output, we need to detect disease at the early stage so that the agricultural output should be maintained. There are multiple ways to detect plant disease like detecting a plant disease by using the naked eye by hiring an expert, or by using Artificial Intelligence (AI). By using AI, it takes less time to detect plant disease as compared to detecting using the naked eye. Deep Learning (DL), the sub-branch of AI gives an accurate result as compared to the other sub-branches of AI. In DL, Convolutional Neural Network or CovNet is the latest and revolutionary algorithm to perform this task. An apple tree disease detection model, based on Multilayer CNN, is presented in the paper. To train the proposed Multilayer CNN model, the data is collected from FGVC8 dataset from Plant Pathology 2021, a Kaggle Competition which is supported by the “Cornell Initiative for Digital Agriculture Decision Trees, Logistic Regression, and Random Forests are machine learning algorithms that are compared with the performance of the proposed model. This study shows that the proposed model outperforms Machine Learning algorithms with the accuracy of 91%, Precision of 89%, Recall of 85% and F1-Score of 88.34%.
世界上大约38%的土地用于农业，整个世界完全依赖农业。所以，这就是为什么好的作物产量对获得高农业产量非常重要。一种病害就能降低作物产量。因此，为了保持较高的农业产量，我们需要在早期发现疾病，这样才能保持农业产量。检测植物病害的方法有很多种，比如聘请专家用肉眼检测植物病害，或者使用人工智能(AI)。与肉眼检测相比，使用人工智能检测植物病害所需的时间更短。与人工智能的其他分支相比，人工智能的分支深度学习(DL)给出了准确的结果。在深度学习中，卷积神经网络或CovNet是执行这项任务的最新和革命性的算法。提出了一种基于多层CNN的苹果树病害检测模型。为了训练所提出的多层CNN模型，数据收集自Plant Pathology 2021的FGVC8数据集，该数据集是由“康奈尔数字农业倡议”(Cornell Initiative for Digital Agriculture)支持的Kaggle竞赛，决策树、逻辑回归和随机森林是与所提出模型的性能进行比较的机器学习算法。本研究表明，该模型的准确率为91%，精密度为89%，召回率为85%，F1-Score为88.34%，优于机器学习算法。
{"title":"Multilayer Convolutional Neural Network Based Approach to Detect Apple Foliar Disease","authors":"Barsha Biswas, R. Yadav","doi":"10.1109/INOCON57975.2023.10101125","DOIUrl":"https://doi.org/10.1109/INOCON57975.2023.10101125","url":null,"abstract":"Around 38% of land in the world is used for agriculture and the whole world is completely dependent on agriculture. So, that’s why good crop yield is very important to get high agricultural output. A single disease in a plant can lower crop yield. So, to maintain a high agricultural output, we need to detect disease at the early stage so that the agricultural output should be maintained. There are multiple ways to detect plant disease like detecting a plant disease by using the naked eye by hiring an expert, or by using Artificial Intelligence (AI). By using AI, it takes less time to detect plant disease as compared to detecting using the naked eye. Deep Learning (DL), the sub-branch of AI gives an accurate result as compared to the other sub-branches of AI. In DL, Convolutional Neural Network or CovNet is the latest and revolutionary algorithm to perform this task. An apple tree disease detection model, based on Multilayer CNN, is presented in the paper. To train the proposed Multilayer CNN model, the data is collected from FGVC8 dataset from Plant Pathology 2021, a Kaggle Competition which is supported by the “Cornell Initiative for Digital Agriculture Decision Trees, Logistic Regression, and Random Forests are machine learning algorithms that are compared with the performance of the proposed model. This study shows that the proposed model outperforms Machine Learning algorithms with the accuracy of 91%, Precision of 89%, Recall of 85% and F1-Score of 88.34%.","PeriodicalId":113637,"journal":{"name":"2023 2nd International Conference for Innovation in Technology (INOCON)","volume":"160 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128974319","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 : 2023-03-03DOI: 10.1109/INOCON57975.2023.10101343
Silpakesav Velagaleti
This paper discusses the design of a Bank locker system. Three different versions of a Bank Locker Security (BLS) System is designed and observed the power consumption at different process corners and different supply voltages. The simulations are measured at 27o C temperature. The power consumption is observed at the supply voltage from 600mV to 1. 2V. The power consumption is less with slow-slow (SS) process corner at 66 MHZ and 200 MHz respectively. This BLS is designed using 45nm CMOS technology.
{"title":"An Integrated Security System for Bank Lockers Using Gated D-Latch","authors":"Silpakesav Velagaleti","doi":"10.1109/INOCON57975.2023.10101343","DOIUrl":"https://doi.org/10.1109/INOCON57975.2023.10101343","url":null,"abstract":"This paper discusses the design of a Bank locker system. Three different versions of a Bank Locker Security (BLS) System is designed and observed the power consumption at different process corners and different supply voltages. The simulations are measured at 27o C temperature. The power consumption is observed at the supply voltage from 600mV to 1. 2V. The power consumption is less with slow-slow (SS) process corner at 66 MHZ and 200 MHz respectively. This BLS is designed using 45nm CMOS technology.","PeriodicalId":113637,"journal":{"name":"2023 2nd International Conference for Innovation in Technology (INOCON)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125406535","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 : 2023-03-03DOI: 10.1109/INOCON57975.2023.10101101
Liu Nan, Zheng Wulue, Yuan Wenjun, Zhang Xin, Chen Daxuan, Luo Kai
Beidou technology is used to identify the position of a station and its position relative to other stations. Beidou system can be applied to the acceptance of overhead transmission lines, so that when the new lines are completed, we can judge whether there are any obstacles between them. In the process of infrastructure acceptance, new technologies should be applied to replace existing technologies. The application of Beidou technology in overhead transmission lines is a new technology developed in China, which can be used to replace the satellite communication system currently used for mobile communication. The application of Beidou technology in overhead transmission lines refers to the use of satellite positioning system (GPS) to locate underground power cables or other buried structures at a certain distance from overhead transmission lines. This method can be used to locate underground power cables or other buried structures at a certain distance from overhead transmission lines. The method is to use GPS signals transmitted by satellites orbiting around the equator of the earth at an altitude of about 2.
{"title":"Application of Beidou technology in infrastructure acceptance of overhead transmission lines","authors":"Liu Nan, Zheng Wulue, Yuan Wenjun, Zhang Xin, Chen Daxuan, Luo Kai","doi":"10.1109/INOCON57975.2023.10101101","DOIUrl":"https://doi.org/10.1109/INOCON57975.2023.10101101","url":null,"abstract":"Beidou technology is used to identify the position of a station and its position relative to other stations. Beidou system can be applied to the acceptance of overhead transmission lines, so that when the new lines are completed, we can judge whether there are any obstacles between them. In the process of infrastructure acceptance, new technologies should be applied to replace existing technologies. The application of Beidou technology in overhead transmission lines is a new technology developed in China, which can be used to replace the satellite communication system currently used for mobile communication. The application of Beidou technology in overhead transmission lines refers to the use of satellite positioning system (GPS) to locate underground power cables or other buried structures at a certain distance from overhead transmission lines. This method can be used to locate underground power cables or other buried structures at a certain distance from overhead transmission lines. The method is to use GPS signals transmitted by satellites orbiting around the equator of the earth at an altitude of about 2.","PeriodicalId":113637,"journal":{"name":"2023 2nd International Conference for Innovation in Technology (INOCON)","volume":"356 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123105174","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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