Pub Date : 2020-06-01DOI: 10.1109/incet49848.2020.9154018
Aamer Munaf Shaikh, R. D. Kulkarni, Anupa Sabnis, Mahajan Sagar Bhaskar, Umashankar Subramaniam
A single phase AC-DC converter is extremely important parameter of major sectors of power systems, electronic circuitries, computer power supplies, communication and automation systems. The converter system should be compact, efficient and reliable as it powers the system throughout the year continuously. The power density and performance efficiency of the controlled rectifier circuits are sufficiently enhanced using the next level semiconductor switches like Silicon Carbide (SiC) MOSFET having wide band gap structure. The advantages in the structural properties of the SiC MOSFET device face the challenges in terms of the costing of the device. In this paper a single phase close loop control rectifier with switching device as SiC MOSFET and diodes as Schottky SiC diode is proposed which minimizes the reverse recovery losses of semiconductor switches which gets wipe out. Proposed rectifier is designed for powering the high precision calibration of Direct Current Current Transformer (DCCT) which works on the Hall Effect principle for high DC current measurements of Kilo ampere range. The circuit operational analysis and simulation presented validate the advantages of proposed rectifier in comparison with traditional circuit configuration.
{"title":"Silicon Carbide (SiC) based Constant DC Current Source for DC Current Transformer Calibration","authors":"Aamer Munaf Shaikh, R. D. Kulkarni, Anupa Sabnis, Mahajan Sagar Bhaskar, Umashankar Subramaniam","doi":"10.1109/incet49848.2020.9154018","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154018","url":null,"abstract":"A single phase AC-DC converter is extremely important parameter of major sectors of power systems, electronic circuitries, computer power supplies, communication and automation systems. The converter system should be compact, efficient and reliable as it powers the system throughout the year continuously. The power density and performance efficiency of the controlled rectifier circuits are sufficiently enhanced using the next level semiconductor switches like Silicon Carbide (SiC) MOSFET having wide band gap structure. The advantages in the structural properties of the SiC MOSFET device face the challenges in terms of the costing of the device. In this paper a single phase close loop control rectifier with switching device as SiC MOSFET and diodes as Schottky SiC diode is proposed which minimizes the reverse recovery losses of semiconductor switches which gets wipe out. Proposed rectifier is designed for powering the high precision calibration of Direct Current Current Transformer (DCCT) which works on the Hall Effect principle for high DC current measurements of Kilo ampere range. The circuit operational analysis and simulation presented validate the advantages of proposed rectifier in comparison with traditional circuit configuration.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125161575","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154139
K. R, N. N, Komal Babasab Karangale, M. H, S. Sheela
Blood is an important biological fluid that carries vital nutrients, vitamins, minerals and oxygen to various parts of the body. It helps in actual functioning of the body organs. Blood flow is the amount of blood flowing through arteries or veins of the circulatory system. Impairment in the blood flow is an indicator of various diseases. Hence a simple, fast, accurate and non-invasive blood flow measurement technique is required for early detection of the diseases. This paper proposes a simple, accurate, non-invasive method to measure the blood flow related parameters using Photoplethysmography (PPG). The blood volume through the veins is measured by acquiring the PPG signal from the body and further analysing the signal to measure different parameters like heart rate, oxygen saturation level (SpO2) and the PPG values are further used for building a cuffless blood pressure measuring system using an Artificial Neural Networks (ANN) with the dataset obtained from Medical Information Mart for Intensive Care III (MIMIC III).
{"title":"Photoplethysmography — a Modern Approach and Applications","authors":"K. R, N. N, Komal Babasab Karangale, M. H, S. Sheela","doi":"10.1109/incet49848.2020.9154139","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154139","url":null,"abstract":"Blood is an important biological fluid that carries vital nutrients, vitamins, minerals and oxygen to various parts of the body. It helps in actual functioning of the body organs. Blood flow is the amount of blood flowing through arteries or veins of the circulatory system. Impairment in the blood flow is an indicator of various diseases. Hence a simple, fast, accurate and non-invasive blood flow measurement technique is required for early detection of the diseases. This paper proposes a simple, accurate, non-invasive method to measure the blood flow related parameters using Photoplethysmography (PPG). The blood volume through the veins is measured by acquiring the PPG signal from the body and further analysing the signal to measure different parameters like heart rate, oxygen saturation level (SpO2) and the PPG values are further used for building a cuffless blood pressure measuring system using an Artificial Neural Networks (ANN) with the dataset obtained from Medical Information Mart for Intensive Care III (MIMIC III).","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129243551","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154071
Ayush Jain, A. Bansal, Yogesh Kakde
Generative Adversarial Network is a novel concept for a general purpose solution to Deep Fake Image generation. These networks learn mapping from input image to output image and also assign value in loss function for the same mapping. We demonstrate that this approach is effective to synthesize images from labelled images, and colorizing images, and other tasks. We have investigate performance of three different types of model i.e. simple GAN, DC-GAN, BIG-GAN, which have provided different results with generation of different loss function on the same dataset i.e. Stanford Dogs Dataset. In this paper, we have investigated the performance of models by using inception score and also track the loss function at different stages (epochs).
{"title":"Performance Analysis of Various Generative Adversarial Network using Dog image Dataset","authors":"Ayush Jain, A. Bansal, Yogesh Kakde","doi":"10.1109/incet49848.2020.9154071","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154071","url":null,"abstract":"Generative Adversarial Network is a novel concept for a general purpose solution to Deep Fake Image generation. These networks learn mapping from input image to output image and also assign value in loss function for the same mapping. We demonstrate that this approach is effective to synthesize images from labelled images, and colorizing images, and other tasks. We have investigate performance of three different types of model i.e. simple GAN, DC-GAN, BIG-GAN, which have provided different results with generation of different loss function on the same dataset i.e. Stanford Dogs Dataset. In this paper, we have investigated the performance of models by using inception score and also track the loss function at different stages (epochs).","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129582878","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154097
Ankit Mishra, V. Dehalwar, Jalpa H. Jobanputra, Mohan Lal Kolhe
The growth of wireless data is the major driving force for an exponential increase in wireless communication. Cognitive Radio is one of the emerging wireless technologies that can be used for smart utility networks. Optimum utilization of the wireless spectrum is the objective of Cognitive Radio. Finding a spectrum hole through intelligent means is essential for the success of Cognitive Radio. Dynamic spectrum allocation is also an efficient technique for spectrum allocation. It will lead to a better spectrum utilization. In this paper, some of the machine learning techniques are used to find a frequency range for dynamic spectrum allocation. Different machine learning techniques such as Logistic Regression, Support Vector Machine, Adaboost Classifier, and Random Forests were used to find spectrum holes in skewed data. Random Forest outperforms all the other models with an accuracy of 91% for determining the spectrum bandwidth (i.e. hole) for Cognitive Radio applications.
{"title":"Spectrum Hole Detection for Cognitive Radio through Energy Detection using Random Forest","authors":"Ankit Mishra, V. Dehalwar, Jalpa H. Jobanputra, Mohan Lal Kolhe","doi":"10.1109/incet49848.2020.9154097","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154097","url":null,"abstract":"The growth of wireless data is the major driving force for an exponential increase in wireless communication. Cognitive Radio is one of the emerging wireless technologies that can be used for smart utility networks. Optimum utilization of the wireless spectrum is the objective of Cognitive Radio. Finding a spectrum hole through intelligent means is essential for the success of Cognitive Radio. Dynamic spectrum allocation is also an efficient technique for spectrum allocation. It will lead to a better spectrum utilization. In this paper, some of the machine learning techniques are used to find a frequency range for dynamic spectrum allocation. Different machine learning techniques such as Logistic Regression, Support Vector Machine, Adaboost Classifier, and Random Forests were used to find spectrum holes in skewed data. Random Forest outperforms all the other models with an accuracy of 91% for determining the spectrum bandwidth (i.e. hole) for Cognitive Radio applications.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124553277","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9153970
V. J. Govindraj, Y. V, Srinidhi V. Bhat, T. K. Ramesh
In this technologically evolving era, with the transition towards a wireless world, security plays a vital role in ensuring the safety. Over the years various methods have been proposed by researchers across the globe which have proven to be successful but have lacked in areas such as security and authentication time. This paper presents an innovative design for a Smart door with the aid of a biometric NFC band and OTP authentication methods which would provide secure and easy access to our homes. Our idea brings forth the opportunity to mitigate the issues faced by these systems by reducing authentication time with the help of a biometric fingerprint sensor and adds an extra layer of security using the help of a local server to generate OTP authentication. This implementation has shown better results and higher performance rate than existing methods.
{"title":"Smart Door Using Biometric NFC Band and OTP Based Methods","authors":"V. J. Govindraj, Y. V, Srinidhi V. Bhat, T. K. Ramesh","doi":"10.1109/incet49848.2020.9153970","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9153970","url":null,"abstract":"In this technologically evolving era, with the transition towards a wireless world, security plays a vital role in ensuring the safety. Over the years various methods have been proposed by researchers across the globe which have proven to be successful but have lacked in areas such as security and authentication time. This paper presents an innovative design for a Smart door with the aid of a biometric NFC band and OTP authentication methods which would provide secure and easy access to our homes. Our idea brings forth the opportunity to mitigate the issues faced by these systems by reducing authentication time with the help of a biometric fingerprint sensor and adds an extra layer of security using the help of a local server to generate OTP authentication. This implementation has shown better results and higher performance rate than existing methods.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121131176","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154075
Meghal Darji, Jaivik Dave, Nadim Asif, Chirag Godawat, Vishal M. Chudasama, Kishor P. Upla
Motorcycle accidents have been rapidly increasing in many countries. The helmet is the main safety equipment of motorcyclists, but many drivers do not use it. Helmets are essential for the safety of a motorcycle rider. Hence, detecting and extracting licence plate of the motorcycle in which riders have not wear helmet becomes a crucial task. Many methods have been proposed to detect and extract the licence plate; however, due to poor video quality and non-uniform illumination, licence plate detection becomes a difficult task. Recently, due to the advancement in graphical processing units (GPUs) and larger datasets, deep learning based models have obtained remarkable performance in the object detection task. One such model is single shot detection (SSD) which classify and detect real-time objects precisely. In this paper, we propose an end-to-end approach for detecting and extracting a licence plate of the motorcycle. Here, we use a MobileNet based SSD model to detect License plates as MobileNet i.e., a light-weight CNN model which is more suitable for mobile and embedded vision applications to obtain fast operation. We also prepare a dataset of Indian motorcycle licence plates which consists of 1524 images to train and validate the SSD model. From experiments, we found that the detection module detects the Indian motorcycle licence plate accurately. Once the License plates are detected, the detected licence plate is extracted and the characters of the extracted licence plate are recognized through optical character recognition (OCR) module.
{"title":"Licence Plate Identification and Recognition for Non-Helmeted Motorcyclists using Light-weight Convolution Neural Network","authors":"Meghal Darji, Jaivik Dave, Nadim Asif, Chirag Godawat, Vishal M. Chudasama, Kishor P. Upla","doi":"10.1109/incet49848.2020.9154075","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154075","url":null,"abstract":"Motorcycle accidents have been rapidly increasing in many countries. The helmet is the main safety equipment of motorcyclists, but many drivers do not use it. Helmets are essential for the safety of a motorcycle rider. Hence, detecting and extracting licence plate of the motorcycle in which riders have not wear helmet becomes a crucial task. Many methods have been proposed to detect and extract the licence plate; however, due to poor video quality and non-uniform illumination, licence plate detection becomes a difficult task. Recently, due to the advancement in graphical processing units (GPUs) and larger datasets, deep learning based models have obtained remarkable performance in the object detection task. One such model is single shot detection (SSD) which classify and detect real-time objects precisely. In this paper, we propose an end-to-end approach for detecting and extracting a licence plate of the motorcycle. Here, we use a MobileNet based SSD model to detect License plates as MobileNet i.e., a light-weight CNN model which is more suitable for mobile and embedded vision applications to obtain fast operation. We also prepare a dataset of Indian motorcycle licence plates which consists of 1524 images to train and validate the SSD model. From experiments, we found that the detection module detects the Indian motorcycle licence plate accurately. Once the License plates are detected, the detected licence plate is extracted and the characters of the extracted licence plate are recognized through optical character recognition (OCR) module.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121272147","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154088
Ravneet Punia, L. Kumar, Mohd. Mujahid, Rajesh Rohilla
COVID-19 is spreading rapidly throughout the world. As of 14 April 2020, 128,000 people died of COVID-19, while 1.99 million cases in 210 countries and territories were reported in 219.747 cases. As the virus spreads at a very high rate, there is a huge shortage of medical testing kits all over the world. The respiratory system is the part of the human body most affected by the virus, so the use of X-rays of the chest may prove to be a more efficient way than the thermal screening of the human body. In this paper, we are trying to develop a method that uses radiology, i.e. X-rays for detecting the novel coronavirus. Along with the paper, we also release a dataset for the research community and further development extracted from various medical research hospital facilities treating COVID-19 patients.
{"title":"Computer Vision and Radiology for COVID-19 Detection","authors":"Ravneet Punia, L. Kumar, Mohd. Mujahid, Rajesh Rohilla","doi":"10.1109/incet49848.2020.9154088","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154088","url":null,"abstract":"COVID-19 is spreading rapidly throughout the world. As of 14 April 2020, 128,000 people died of COVID-19, while 1.99 million cases in 210 countries and territories were reported in 219.747 cases. As the virus spreads at a very high rate, there is a huge shortage of medical testing kits all over the world. The respiratory system is the part of the human body most affected by the virus, so the use of X-rays of the chest may prove to be a more efficient way than the thermal screening of the human body. In this paper, we are trying to develop a method that uses radiology, i.e. X-rays for detecting the novel coronavirus. Along with the paper, we also release a dataset for the research community and further development extracted from various medical research hospital facilities treating COVID-19 patients.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"46 13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126843488","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 : 2020-06-01DOI: 10.1109/INCET49848.2020.9154176
Geetanjali Rohilla, Dinesh Mathur, U. Ghanekar
Peripheral Component Interconnect (PCI) Express is a modern, high performance, point to point, general purpose input output interconnect communication protocol. PCI Express supersedes other legacy buses and provides higher bandwidth which makes it ideal choice for many applications. It provides layered architecture which contains three separate layers. Information flows among these layers in terms of packets. PCI Express Gen5.0 is a latest protocol which provides data rate of 32GT/s per lane and backward compatible with previous releases of PCI Express specifications Gen4.0(16GT/s), Gen3.0(8GT/s), Gen2.0 (5GT/s) and Gen1.1 (2.5GT/s). This presented paper performs the verification of the PCI Express Gen5.0 transactions between MAC (Media Access Layer) and PHY (Combination of SerDes & Physical Sub-block (Physical Media Attachment Layer)) layers of PCIe Gen5.0 physical layer. The RTL of PCI Express Gen5.0 is designed in SystemVerilog language and for the verification purpose, the methodology used is Universal Verification Methodology. Simulation results show the efficacy of the proposed procedure which are shown in Synopsys Discovery Visual Environment tool successfully.
{"title":"Functional Verification of MAC-PHY Layer of PCI Express Gen5.0 with PIPE Interface using UVM","authors":"Geetanjali Rohilla, Dinesh Mathur, U. Ghanekar","doi":"10.1109/INCET49848.2020.9154176","DOIUrl":"https://doi.org/10.1109/INCET49848.2020.9154176","url":null,"abstract":"Peripheral Component Interconnect (PCI) Express is a modern, high performance, point to point, general purpose input output interconnect communication protocol. PCI Express supersedes other legacy buses and provides higher bandwidth which makes it ideal choice for many applications. It provides layered architecture which contains three separate layers. Information flows among these layers in terms of packets. PCI Express Gen5.0 is a latest protocol which provides data rate of 32GT/s per lane and backward compatible with previous releases of PCI Express specifications Gen4.0(16GT/s), Gen3.0(8GT/s), Gen2.0 (5GT/s) and Gen1.1 (2.5GT/s). This presented paper performs the verification of the PCI Express Gen5.0 transactions between MAC (Media Access Layer) and PHY (Combination of SerDes & Physical Sub-block (Physical Media Attachment Layer)) layers of PCIe Gen5.0 physical layer. The RTL of PCI Express Gen5.0 is designed in SystemVerilog language and for the verification purpose, the methodology used is Universal Verification Methodology. Simulation results show the efficacy of the proposed procedure which are shown in Synopsys Discovery Visual Environment tool successfully.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125478086","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154021
Trisha, I. Ali
In the past few years, there has been an exponential growth of Diabetes which is also known as the silent killer [1] and become a major concern for health in our society [2]. The ophthalmologists are looking for methods through which they can easily and automatically detect whether a person is affected by Diabetes or not, instead of spending extensive time on finding it out manually [3]. If they are able to have an early-stage detection of this disease, they can control its severity to a great extent [5]–[8]. The eye can be a vital organ for the detection of diabetes since it is among the fundamental organs which get affected at the earliest stage [9]–[15]. Therefore, analyzing the retina of the eye can act as a gateway for automatically detecting Diabetic Retinopathy (DR). Therefore, we have tried to provide a technique via which, we can effortlessly and efficiently find out whether a person is affected by diabetes or not so that the patient can start the further treatments without wasting their time by going through long and tedious processes of various manual tests for detection of DR [16]–[20]. In order to detect DR, it is important to pinpoint three important regions of the eye. In this paper, we have tried to localize these three important regions of retina that is the Outer Boundary of Retina, the Optic Disk, and the Macula.
{"title":"Intensity Based Optic Disk Detection for Automatic Diabetic Retinopathy","authors":"Trisha, I. Ali","doi":"10.1109/incet49848.2020.9154021","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154021","url":null,"abstract":"In the past few years, there has been an exponential growth of Diabetes which is also known as the silent killer [1] and become a major concern for health in our society [2]. The ophthalmologists are looking for methods through which they can easily and automatically detect whether a person is affected by Diabetes or not, instead of spending extensive time on finding it out manually [3]. If they are able to have an early-stage detection of this disease, they can control its severity to a great extent [5]–[8]. The eye can be a vital organ for the detection of diabetes since it is among the fundamental organs which get affected at the earliest stage [9]–[15]. Therefore, analyzing the retina of the eye can act as a gateway for automatically detecting Diabetic Retinopathy (DR). Therefore, we have tried to provide a technique via which, we can effortlessly and efficiently find out whether a person is affected by diabetes or not so that the patient can start the further treatments without wasting their time by going through long and tedious processes of various manual tests for detection of DR [16]–[20]. In order to detect DR, it is important to pinpoint three important regions of the eye. In this paper, we have tried to localize these three important regions of retina that is the Outer Boundary of Retina, the Optic Disk, and the Macula.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126426856","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154023
G. Sebastian, D. N. Kyatanavar
Model preparation of evaporation process and optimizing the same have been a challenging task for researchers. Evaporation process in sugar industries is characterized by its highly non-linear nature and conventional control strategies do not yield good results for the control of the same. With the evaporator being the most energy consuming unit in sugar manufacturing process, it has direct impact on sugar quality as well as steam economy. In this paper, a simulation model of an evaporator having four effects has been developed in Simulink. For optimizing this model, Taguchi technique combined with Grey relational analysis has been employed. The level of influence of variables like Temperature of the feed, Rate of flow of the feed and Rate of steam flow, on the steam economy and sugarcane juice concentration has been determined using ANOVA (Analysis of Variance). Minitab 17 software has been used for this. Finally, the relative contribution of each process parameter on the performance characteristics of the evaporator has also been determined.
{"title":"Modeling and Optimization of Evaporation Process in Sugar Industries","authors":"G. Sebastian, D. N. Kyatanavar","doi":"10.1109/incet49848.2020.9154023","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154023","url":null,"abstract":"Model preparation of evaporation process and optimizing the same have been a challenging task for researchers. Evaporation process in sugar industries is characterized by its highly non-linear nature and conventional control strategies do not yield good results for the control of the same. With the evaporator being the most energy consuming unit in sugar manufacturing process, it has direct impact on sugar quality as well as steam economy. In this paper, a simulation model of an evaporator having four effects has been developed in Simulink. For optimizing this model, Taguchi technique combined with Grey relational analysis has been employed. The level of influence of variables like Temperature of the feed, Rate of flow of the feed and Rate of steam flow, on the steam economy and sugarcane juice concentration has been determined using ANOVA (Analysis of Variance). Minitab 17 software has been used for this. Finally, the relative contribution of each process parameter on the performance characteristics of the evaporator has also been determined.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127613156","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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