Pub Date : 2019-09-01DOI: 10.1109/ICICT46931.2019.8977694
Khushi Maheshwari, Sampada Lamba
This paper explores patterns in Beijing’s Particulate Matter 2.5[7] concentration and forecasts future concentrations. Air quality has been an enormous health concern in recent decades as the place has become further industrialized and more and more of its citizens have begun driving automobiles. The occurenece of air pollution takes place in the following ways. 1. release and generation of pollutants from their source. 2. carry of pollutants in the atmosphere. 3. penetrating and negatively impacting human health and ecosystems. We tend to minimise the effects of these emissions as there is no practical, economical or technical method for zero emissions. PM 2.5 is especially dangerous because it can pass through the human body’s natural filters and enter the lungs. Health concerns related to PM 2.5 include heart and lung disease, asthma, bronchitis, and other respiratory problems. Machine learning, as one of the most accepted techniques, is capable to efficiently train a model using regression models to predict the hourly air pollution concentration [1]. Following six regressors chosen for this problem were Linear Regression, K-Nearnest Neighbor, Stochastic Gradient Descent, Decision Tree, Random Forest and Multi-layer Perceptron. Although performance of all models was comparable, Multi-layer Perceptron Algorithm model successfully bring about better accuracy and true positive rate with 95.4 accuracy.
{"title":"Air Quality Prediction using Supervised Regression Model","authors":"Khushi Maheshwari, Sampada Lamba","doi":"10.1109/ICICT46931.2019.8977694","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977694","url":null,"abstract":"This paper explores patterns in Beijing’s Particulate Matter 2.5[7] concentration and forecasts future concentrations. Air quality has been an enormous health concern in recent decades as the place has become further industrialized and more and more of its citizens have begun driving automobiles. The occurenece of air pollution takes place in the following ways. 1. release and generation of pollutants from their source. 2. carry of pollutants in the atmosphere. 3. penetrating and negatively impacting human health and ecosystems. We tend to minimise the effects of these emissions as there is no practical, economical or technical method for zero emissions. PM 2.5 is especially dangerous because it can pass through the human body’s natural filters and enter the lungs. Health concerns related to PM 2.5 include heart and lung disease, asthma, bronchitis, and other respiratory problems. Machine learning, as one of the most accepted techniques, is capable to efficiently train a model using regression models to predict the hourly air pollution concentration [1]. Following six regressors chosen for this problem were Linear Regression, K-Nearnest Neighbor, Stochastic Gradient Descent, Decision Tree, Random Forest and Multi-layer Perceptron. Although performance of all models was comparable, Multi-layer Perceptron Algorithm model successfully bring about better accuracy and true positive rate with 95.4 accuracy.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133908714","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 : 2019-09-01DOI: 10.1109/ICICT46931.2019.8977648
S. Arya, Rajeev Singh
Deep Learning (DL) is a fastest growing and a broader part of machine learning family. Deep learning uses Convolutional Neural Networks (CNN) for image classification as it gives the most accurate results in solving real- world problem. CNN has various pre-trained architecture like AlexNet, GoogleNet, DenseNet, SqueezeNet, ResNet, VGGNet etc. In this study, we have used CNN and AlexNet architecture for detecting the disease in Mango and Potato leaf and compare the accuracy and efficiency between these architectures. The dataset containing 4004 images were used for this work. The images for potato were taken from plantvillage website, while images for mango were collected from GBPUAT field location. The results show that accuracy achieved from AlexNet is higher than CNN architecture.
{"title":"A Comparative Study of CNN and AlexNet for Detection of Disease in Potato and Mango leaf","authors":"S. Arya, Rajeev Singh","doi":"10.1109/ICICT46931.2019.8977648","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977648","url":null,"abstract":"Deep Learning (DL) is a fastest growing and a broader part of machine learning family. Deep learning uses Convolutional Neural Networks (CNN) for image classification as it gives the most accurate results in solving real- world problem. CNN has various pre-trained architecture like AlexNet, GoogleNet, DenseNet, SqueezeNet, ResNet, VGGNet etc. In this study, we have used CNN and AlexNet architecture for detecting the disease in Mango and Potato leaf and compare the accuracy and efficiency between these architectures. The dataset containing 4004 images were used for this work. The images for potato were taken from plantvillage website, while images for mango were collected from GBPUAT field location. The results show that accuracy achieved from AlexNet is higher than CNN architecture.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124809402","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 : 2019-09-01DOI: 10.1109/ICICT46931.2019.8977666
Dayanand, Mohini Chauhan
Microchips are the integrated embedded system of electronic components that are used to work in a designed fashion. These are attached to a surface which provide it a path to transfer the information and then in return provide power supply. In semiconductor base technology, these chips are used in many areas including robotics, electronics, smart cards etc. injectable chips are designs for making the tasks like payment, data travelling etc very easy through chips base design. IOT make this approach very simple and convenient. AI based industries are using such technologies to make applications more useful and hence very helpful. The technologies that are used nowadays are very much advance along with some vulnerabilities. The technologies that re using the bluetooth based mechanism and are very much secure as compare to the internet based. There are some weaknesses that are making this communication a little bit risky to use. In this paper I have solved this problem by making some advancements during the designing and releasing of the code. The overall coding makes the system more secure and reliable towards data transfer.
{"title":"Human Injectable Chip: Secure Transmission in Media","authors":"Dayanand, Mohini Chauhan","doi":"10.1109/ICICT46931.2019.8977666","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977666","url":null,"abstract":"Microchips are the integrated embedded system of electronic components that are used to work in a designed fashion. These are attached to a surface which provide it a path to transfer the information and then in return provide power supply. In semiconductor base technology, these chips are used in many areas including robotics, electronics, smart cards etc. injectable chips are designs for making the tasks like payment, data travelling etc very easy through chips base design. IOT make this approach very simple and convenient. AI based industries are using such technologies to make applications more useful and hence very helpful. The technologies that are used nowadays are very much advance along with some vulnerabilities. The technologies that re using the bluetooth based mechanism and are very much secure as compare to the internet based. There are some weaknesses that are making this communication a little bit risky to use. In this paper I have solved this problem by making some advancements during the designing and releasing of the code. The overall coding makes the system more secure and reliable towards data transfer.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125702986","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 : 2019-09-01DOI: 10.1109/ICICT46931.2019.8977718
Vineet Kumar, R. Naresh, Amita Singh
In day to day life, with an ever-growing demand in power sector, planning and operation plays a vital role in providing an economical, reliable and efficient electricity to the consumers. In this regard, unit commitment (UC) plays a significant part in daily planning and optimal scheduling of generating units so as to meet the hourly load demand in an efficient manner. This paper focusses on presenting a robust and effective methodology for solving the UC problem using GAMS simulation environment. In this work, to assess the effectiveness of GAMS over MATLAB environment, 3 and 4 thermal generating units with and without spinning reserves and ramp rate constraints have been considered over 24-hour time horizon.
{"title":"Solution Approach to Unit Commitment Problem Using GAMS Environment","authors":"Vineet Kumar, R. Naresh, Amita Singh","doi":"10.1109/ICICT46931.2019.8977718","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977718","url":null,"abstract":"In day to day life, with an ever-growing demand in power sector, planning and operation plays a vital role in providing an economical, reliable and efficient electricity to the consumers. In this regard, unit commitment (UC) plays a significant part in daily planning and optimal scheduling of generating units so as to meet the hourly load demand in an efficient manner. This paper focusses on presenting a robust and effective methodology for solving the UC problem using GAMS simulation environment. In this work, to assess the effectiveness of GAMS over MATLAB environment, 3 and 4 thermal generating units with and without spinning reserves and ramp rate constraints have been considered over 24-hour time horizon.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125894355","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 : 2019-09-01DOI: 10.1109/ICICT46931.2019.8977677
Sakshi Goel, M. Kumar, Yogesh
Images are the best tool for the information to be visualize and analyze it further. Thus, for this purpose and to extract information and features, image segmentation has been used. The popularity of image segmentation has achieved a remark in the few years. Its application has been increasing day by day. It is a great field of interest for the researchers. It is used in medical, agricultural, engineering, security, industrial and many more fields. Even for the layman it is a boon. Image segmentation refers to the procedure of dividing an image into segments which further process for finding the desired results. Based on the characteristic and properties of an image, an outline is formed for segmentation. In this paper the focus is on finding the defects of apple such as fungal growth, bruising, scab and disease which is harmful for the humans. Different methods have been used for finding the defects by image segmentation such as Gabor Method, Clustering, Edge Detection, Otsu Method and Watershed Method. We have compared different methods and find the best result.
{"title":"An Improved Segmentation Algorithm for Detecting Defects on Fruit Surface","authors":"Sakshi Goel, M. Kumar, Yogesh","doi":"10.1109/ICICT46931.2019.8977677","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977677","url":null,"abstract":"Images are the best tool for the information to be visualize and analyze it further. Thus, for this purpose and to extract information and features, image segmentation has been used. The popularity of image segmentation has achieved a remark in the few years. Its application has been increasing day by day. It is a great field of interest for the researchers. It is used in medical, agricultural, engineering, security, industrial and many more fields. Even for the layman it is a boon. Image segmentation refers to the procedure of dividing an image into segments which further process for finding the desired results. Based on the characteristic and properties of an image, an outline is formed for segmentation. In this paper the focus is on finding the defects of apple such as fungal growth, bruising, scab and disease which is harmful for the humans. Different methods have been used for finding the defects by image segmentation such as Gabor Method, Clustering, Edge Detection, Otsu Method and Watershed Method. We have compared different methods and find the best result.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130064764","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 : 2019-09-01DOI: 10.1109/ICICT46931.2019.8977640
Pooja Gupta, Vineet Sharma
Clustering is a popular data mining technique which can be applied to a given data set to identify the data objects that belong to a single class, such that data objects in different clusters are distinct while similarity exists for data objects belonging to the same cluster. Usually, clustering techniques are based on optimizing single objective function criteria, which may not be capable of performing well in many real time scenarios. Motivated by this many multi-objective based optimization techniques are discussed in this paper. Multi-objective based optimization techniques are capable of optimizing several conflicting objective functions simultaneously. Under this context, evolutionary based approach and simulated annealing based techniques are adopted in various MOO techniques and proven well in case of noise, non-spherical and high dimensional feature space. The paper further discusses various validity measures to evaluate the goodness of clustering techniques.
{"title":"A Survey on Multi-objective based clustering techniques for solving real life problems","authors":"Pooja Gupta, Vineet Sharma","doi":"10.1109/ICICT46931.2019.8977640","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977640","url":null,"abstract":"Clustering is a popular data mining technique which can be applied to a given data set to identify the data objects that belong to a single class, such that data objects in different clusters are distinct while similarity exists for data objects belonging to the same cluster. Usually, clustering techniques are based on optimizing single objective function criteria, which may not be capable of performing well in many real time scenarios. Motivated by this many multi-objective based optimization techniques are discussed in this paper. Multi-objective based optimization techniques are capable of optimizing several conflicting objective functions simultaneously. Under this context, evolutionary based approach and simulated annealing based techniques are adopted in various MOO techniques and proven well in case of noise, non-spherical and high dimensional feature space. The paper further discusses various validity measures to evaluate the goodness of clustering techniques.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130076302","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 : 2019-09-01DOI: 10.1109/ICICT46931.2019.8977689
Shubham Shukla, Nk Shukla, V. Sachan
Through Particle Swarm Optimization (PSO) path planning in an intricate environment turns out to be a novel approach for robot’s multi path planning. Automation and detection capabilities of robots are the major challenges, to overcome these problems optimized path needs to be established. Robot path planning is one of the main problem that deals with the computation of collision free path for the given robot (agent) with the map, which helps it to operate. When the environment is known and the target location is estimated then only the path establishment is possible. The work we have presented on our paper totally focusses on the path planning problem. We have taken only one case into consideration, according to it the robot (agent) tracks the coordinated targets and reach towards the unknown environment through obstacle avoidance technique when the location of the target is unknown. Important parameters that we have taken to asses these algorithms are: (a) Number of visited node we consider as (Move). (b) Area explored considered as (Coverage). (c) Distance travelled considered as (Energy) and time elapsed as (Time).
{"title":"Multi Robot Path Planning Parameter Analysis Based on Particle Swarm Optimization (PSO) in an Intricate Unknown Environments","authors":"Shubham Shukla, Nk Shukla, V. Sachan","doi":"10.1109/ICICT46931.2019.8977689","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977689","url":null,"abstract":"Through Particle Swarm Optimization (PSO) path planning in an intricate environment turns out to be a novel approach for robot’s multi path planning. Automation and detection capabilities of robots are the major challenges, to overcome these problems optimized path needs to be established. Robot path planning is one of the main problem that deals with the computation of collision free path for the given robot (agent) with the map, which helps it to operate. When the environment is known and the target location is estimated then only the path establishment is possible. The work we have presented on our paper totally focusses on the path planning problem. We have taken only one case into consideration, according to it the robot (agent) tracks the coordinated targets and reach towards the unknown environment through obstacle avoidance technique when the location of the target is unknown. Important parameters that we have taken to asses these algorithms are: (a) Number of visited node we consider as (Move). (b) Area explored considered as (Coverage). (c) Distance travelled considered as (Energy) and time elapsed as (Time).","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127394753","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 : 2019-09-01DOI: 10.1109/ICICT46931.2019.8977704
N. Khera, Akash Kumar, Fajr Fajr, T. Khajwal
In this paper, the important parameters of milk like pH value, Correct Lactometer Reading (CLR), Fat percentage and Solid but Not Fat (SNF) are monitored. The pH sensor interfaced with the low cost microcontroller board (Arduino Uno) is used to measure the pH value and CLR of the milk is obtained from Lactometer. Butyrometer is used to measure the Fat percentage. From the calculated Fat percentage and CLR values, the SNF value has been obtained from their mathematical relationship which is implemented in real-time by programming microcontroller board. Finally, the obtained pH and SNF values on the serial monitor of Arduino software are stored as MS Excel database file using the CoolTerm software for further quality analysis of milk. The developed system is an efficient tool for detecting the adulteration of the milk based on the variation in the obtained data values of pH and SNF content of milk from their standard values.
{"title":"Microcontroller Based Parametric Data Monitoring and Quality Analysis of Milk","authors":"N. Khera, Akash Kumar, Fajr Fajr, T. Khajwal","doi":"10.1109/ICICT46931.2019.8977704","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977704","url":null,"abstract":"In this paper, the important parameters of milk like pH value, Correct Lactometer Reading (CLR), Fat percentage and Solid but Not Fat (SNF) are monitored. The pH sensor interfaced with the low cost microcontroller board (Arduino Uno) is used to measure the pH value and CLR of the milk is obtained from Lactometer. Butyrometer is used to measure the Fat percentage. From the calculated Fat percentage and CLR values, the SNF value has been obtained from their mathematical relationship which is implemented in real-time by programming microcontroller board. Finally, the obtained pH and SNF values on the serial monitor of Arduino software are stored as MS Excel database file using the CoolTerm software for further quality analysis of milk. The developed system is an efficient tool for detecting the adulteration of the milk based on the variation in the obtained data values of pH and SNF content of milk from their standard values.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"67 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128026246","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 : 2019-09-01DOI: 10.1109/ICICT46931.2019.8977671
Pranav Gangwar, Satvik Maurya, N. Pandey
This paper deals with realization of search algorithms used in the game solvers on the FPGA. Three algorithms namely Minimax, Alpha-Beta Pruning, and NegaScout are realized and compared amongst each other, and also with their software realization for the sake of completion. Results show that the FPGA based implementations are exceptionally faster than their software counterparts, with the NegaScout algorithm outperforming the conventionally used Alpha-Beta Pruning, and the Minimax algorithm, both in software and hardware. The NegaScout algorithm is 1.3 times faster than the Alpha-Beta Pruning algorithm and 2.6 times faster than the Minimax algorithm on hardware, while incurring a nominal cost in terms of FPGA resource utilization.
{"title":"Realization of Game Tree Search Algorithms on FPGA: A Comparative Study","authors":"Pranav Gangwar, Satvik Maurya, N. Pandey","doi":"10.1109/ICICT46931.2019.8977671","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977671","url":null,"abstract":"This paper deals with realization of search algorithms used in the game solvers on the FPGA. Three algorithms namely Minimax, Alpha-Beta Pruning, and NegaScout are realized and compared amongst each other, and also with their software realization for the sake of completion. Results show that the FPGA based implementations are exceptionally faster than their software counterparts, with the NegaScout algorithm outperforming the conventionally used Alpha-Beta Pruning, and the Minimax algorithm, both in software and hardware. The NegaScout algorithm is 1.3 times faster than the Alpha-Beta Pruning algorithm and 2.6 times faster than the Minimax algorithm on hardware, while incurring a nominal cost in terms of FPGA resource utilization.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117145358","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 : 2019-09-01DOI: 10.1109/ICICT46931.2019.8977631
Tejinderpal Singh, Simranjit Singh, M. Singh, Rajbir Kaur
This paper presents a Planar Antenna which is used to recognize the cancerous Tumor into human brain. The Antenna is designed that its dimensions are small enough for practical purpose. Antenna is designed using Rogers RT6002 substrate of thickness 1.6 mm and permittivity 2.94. Real size of this antenna is (45.5 × 54 × 1.6) mm. It resonates at 2.39 GHz (2.35 GHz – 2.43 GHz). A human brain phantom model is designed for the simulation purpose. For the patient’s protection, antenna is placed above the human head phantom which consists of four homogeneous layersbrain, fat, bone and skin with different electrical properties. Above mentioned model is designed in CST microwave studio 2016. Designed antenna observes return loss, electric field, SAR (Specific Absorption Ratio) and current density. In the end, note the dissimilarity with cancerous tumor head phantom that includes a small tumor within it. It clearly visualizing that functioning of antenna covers the ISM band under IEEE standard regulation.
{"title":"Design of Patch Antenna to Detect Brain Tumor","authors":"Tejinderpal Singh, Simranjit Singh, M. Singh, Rajbir Kaur","doi":"10.1109/ICICT46931.2019.8977631","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977631","url":null,"abstract":"This paper presents a Planar Antenna which is used to recognize the cancerous Tumor into human brain. The Antenna is designed that its dimensions are small enough for practical purpose. Antenna is designed using Rogers RT6002 substrate of thickness 1.6 mm and permittivity 2.94. Real size of this antenna is (45.5 × 54 × 1.6) mm. It resonates at 2.39 GHz (2.35 GHz – 2.43 GHz). A human brain phantom model is designed for the simulation purpose. For the patient’s protection, antenna is placed above the human head phantom which consists of four homogeneous layersbrain, fat, bone and skin with different electrical properties. Above mentioned model is designed in CST microwave studio 2016. Designed antenna observes return loss, electric field, SAR (Specific Absorption Ratio) and current density. In the end, note the dissimilarity with cancerous tumor head phantom that includes a small tumor within it. It clearly visualizing that functioning of antenna covers the ISM band under IEEE standard regulation.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121147948","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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