Pub Date : 2020-06-01DOI: 10.1109/INCET49848.2020.9154057
Alok Sarkar, M. Maniruzzaman, Md. Shamim Ahsan, Mohiudding Ahmad, M. I. Kadir, S. M. Taohidul Islam
Magnetic resonance imaging is one of the best methods for detecting brain tumors. But the images captured by this method may contain different kinds of noises. So it is very essential to remove the noises for properly identifying the specific brain tumor. A filter is usually used to remove the noises. This paper illustrates different image filtering methods, such as low pass filter, high pass filter, and median filter, to improve the image quality by removing the noises from magnetic resonance images to identify the brain tumor. The MSE, RMSE, and the PSNR is used for understanding the quality of the filtered images. A graphical user interface is developed in MATLAB to implement all the filtering process and performance analysis for magnetic resonance images used to detect brain tumor.
{"title":"Filtering Magnetic Resonance Images to Detect Brain Tumor","authors":"Alok Sarkar, M. Maniruzzaman, Md. Shamim Ahsan, Mohiudding Ahmad, M. I. Kadir, S. M. Taohidul Islam","doi":"10.1109/INCET49848.2020.9154057","DOIUrl":"https://doi.org/10.1109/INCET49848.2020.9154057","url":null,"abstract":"Magnetic resonance imaging is one of the best methods for detecting brain tumors. But the images captured by this method may contain different kinds of noises. So it is very essential to remove the noises for properly identifying the specific brain tumor. A filter is usually used to remove the noises. This paper illustrates different image filtering methods, such as low pass filter, high pass filter, and median filter, to improve the image quality by removing the noises from magnetic resonance images to identify the brain tumor. The MSE, RMSE, and the PSNR is used for understanding the quality of the filtered images. A graphical user interface is developed in MATLAB to implement all the filtering process and performance analysis for magnetic resonance images used to detect brain tumor.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"1 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":"127411421","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/INCET49848.2020.9154001
Kaushika Pal, B. Patel
Text Classification of Indic language face fundamental challenges in terms of achieving good accuracy, as the languages are morphologically rich and too much information is fused in words. In this paper an actual experiment implemented is demonstrated for Classification of Hindi Poem documents to classify poems into 3 classes namely Shringar, Karuna and Veera. Poem content represents mood and have sentiments associated, the classification of emotions become more challenging when the language is morphologically rich. In current experiment 122 documents manually collected from web were processed and after preprocessing 122 documents were generated containing only meaningful data, than processed documents were used to extract features using Bag of Words Model and those features are converted into numeric representation for passing them into Training model. For classification 5 machine-learning classification algorithms namely Random Forest, Support Vector Machine, Decision Tree Algorithm, K nearest Neighbors and Naive Bayes each with it’s two versions are used. The model is tested with 20% of test data and the results are compared with stored label of this data to calculate accuracy. Experiments shows that Naïve Bayes with 64% accuracy and Random Forest with 56% are performing better as compared to other algorithms for Hindi Poem Classification.
{"title":"Automatic Multiclass Document Classification of Hindi Poems using Machine Learning Techniques","authors":"Kaushika Pal, B. Patel","doi":"10.1109/INCET49848.2020.9154001","DOIUrl":"https://doi.org/10.1109/INCET49848.2020.9154001","url":null,"abstract":"Text Classification of Indic language face fundamental challenges in terms of achieving good accuracy, as the languages are morphologically rich and too much information is fused in words. In this paper an actual experiment implemented is demonstrated for Classification of Hindi Poem documents to classify poems into 3 classes namely Shringar, Karuna and Veera. Poem content represents mood and have sentiments associated, the classification of emotions become more challenging when the language is morphologically rich. In current experiment 122 documents manually collected from web were processed and after preprocessing 122 documents were generated containing only meaningful data, than processed documents were used to extract features using Bag of Words Model and those features are converted into numeric representation for passing them into Training model. For classification 5 machine-learning classification algorithms namely Random Forest, Support Vector Machine, Decision Tree Algorithm, K nearest Neighbors and Naive Bayes each with it’s two versions are used. The model is tested with 20% of test data and the results are compared with stored label of this data to calculate accuracy. Experiments shows that Naïve Bayes with 64% accuracy and Random Forest with 56% are performing better as compared to other algorithms for Hindi Poem Classification.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"1 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":"129131562","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/incet49848.2020.9154127
D. K, K. N. Pillai
The Sophisticated wireless communications system requires larger bandwidth, huge gain and nominal size micro strip patch that is able to provide more desirable achievement done with board area of spectrum. Hence, This specification priority to the plan of Micro strip array antennas. In this method nominate the architecture of micro strip array antennas under the corporate feed techniques and series feed techniques for excitation and match the results with series feed and corporate feed technique. Dielectric constant for substrates should be low because of maximum radiation. This micro strip patch array antenna is designed initially by utilizing high frequency structure simulator(HFSS). Patch length and width are determined by utilizing relative permittivity of substrate is 2.2andsubstrate height (h=1.588mm) and centre frequency specification are impedance, returnloss and gain are calculated by using HFSS. The micro strip patch has been intended from 9 to11 GHz.
{"title":"Design Array Antenna Using Different Feeding Technique in HFSS","authors":"D. K, K. N. Pillai","doi":"10.1109/incet49848.2020.9154127","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154127","url":null,"abstract":"The Sophisticated wireless communications system requires larger bandwidth, huge gain and nominal size micro strip patch that is able to provide more desirable achievement done with board area of spectrum. Hence, This specification priority to the plan of Micro strip array antennas. In this method nominate the architecture of micro strip array antennas under the corporate feed techniques and series feed techniques for excitation and match the results with series feed and corporate feed technique. Dielectric constant for substrates should be low because of maximum radiation. This micro strip patch array antenna is designed initially by utilizing high frequency structure simulator(HFSS). Patch length and width are determined by utilizing relative permittivity of substrate is 2.2andsubstrate height (h=1.588mm) and centre frequency specification are impedance, returnloss and gain are calculated by using HFSS. The micro strip patch has been intended from 9 to11 GHz.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"38 3 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":"127986091","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/incet49848.2020.9154002
Yash Bhandare, Sumit Bharsawade, Dhurv Nayyar, Omkar Phadtare, Deipali. V. Gore
Currently there are a lot of analysts and experts who give out recommendations to laymen regarding the operations of the stock market and answering the when and where of investments in the stock market. The system developed aims to create an unbiased rating system that will analyze and quantify the performance of stock market analysts. Our system will keep these analysts’ reliability in check by analyzing their performance and providing a rating for each of these analysts on a 5 star rating system. The recommendations given by the analysts will be analyzed and factors relevant to the success/failure of the recommendation will be stored. The system will then use the Naive Bayes classifier to provide a rating on the factors thus extracted. The project will help curtail problems like incompetent analysts and simultaneously provide a system of reference to see how good an analyst is at his/her job.
{"title":"SMART : Stock Market Analyst Rating Technique Using Naive Bayes Classifier","authors":"Yash Bhandare, Sumit Bharsawade, Dhurv Nayyar, Omkar Phadtare, Deipali. V. Gore","doi":"10.1109/incet49848.2020.9154002","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154002","url":null,"abstract":"Currently there are a lot of analysts and experts who give out recommendations to laymen regarding the operations of the stock market and answering the when and where of investments in the stock market. The system developed aims to create an unbiased rating system that will analyze and quantify the performance of stock market analysts. Our system will keep these analysts’ reliability in check by analyzing their performance and providing a rating for each of these analysts on a 5 star rating system. The recommendations given by the analysts will be analyzed and factors relevant to the success/failure of the recommendation will be stored. The system will then use the Naive Bayes classifier to provide a rating on the factors thus extracted. The project will help curtail problems like incompetent analysts and simultaneously provide a system of reference to see how good an analyst is at his/her job.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"61 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":"130434386","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/incet49848.2020.9154158
Md Shamsul Haque Ansari, Monica Mehrotra
With the extensive use of different devices in smart cities the problems related to information security increases. Random nonce plays a vital role in communication security. A random nonce is used to generate the seeds randomly in various cryptographic applications to improve security measures. There are various alternative approaches for the generation of random nonce which are based on different cryptographic parameters. Researchers found that less power consumption implementation is preferable in a smart city environment. The devices under smart city environment have limited processing capability and storage capacity. To handle these challenges, many works are going on for reducing power consumption while generating random nonce for M2M communication. In this paper, authors are going to use the concept of light-weight cryptography to develop a new method for a random nonce generation. The focus of lightweight cryptography is to come up with such an algorithm that should be small enough to be suitable for constrained devices used in smart cities.
{"title":"Securing M2M communication in Smart Cities","authors":"Md Shamsul Haque Ansari, Monica Mehrotra","doi":"10.1109/incet49848.2020.9154158","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154158","url":null,"abstract":"With the extensive use of different devices in smart cities the problems related to information security increases. Random nonce plays a vital role in communication security. A random nonce is used to generate the seeds randomly in various cryptographic applications to improve security measures. There are various alternative approaches for the generation of random nonce which are based on different cryptographic parameters. Researchers found that less power consumption implementation is preferable in a smart city environment. The devices under smart city environment have limited processing capability and storage capacity. To handle these challenges, many works are going on for reducing power consumption while generating random nonce for M2M communication. In this paper, authors are going to use the concept of light-weight cryptography to develop a new method for a random nonce generation. The focus of lightweight cryptography is to come up with such an algorithm that should be small enough to be suitable for constrained devices used in smart cities.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"25 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":"124442374","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/incet49848.2020.9154117
Anant Rungta, Astha Rungta, Gaurav Sharma
This paper aims to prove the hypothesis set which is to humanize headless communication. The voice user interface is the application of headless communication which will be covered in this paper and the idea is to find a perfect symbiotic relationship between the voice user interface and the graphical user interface. There are many technologies which has emerged in the market to give a face to voice to make the solution more valuable and impactful for the customers, but each of these technologies have some pros and cons. This paper aims to discuss all those possible options to create a human centered intelligent user interface by weighing the plus and minus of all the technologies available in the market. The main purpose is to share the conceptual idea which has been designed by the team to create an affordable and effective solution for the customers. The team also went a step ahead to visualize and implement the conceptual idea and created a working prototype of the minimum viable product, which is further elaborated in the paper to showcase the demonstration.
{"title":"Humanizing Headless Communication : Marriage between Graphical and Voice Interface","authors":"Anant Rungta, Astha Rungta, Gaurav Sharma","doi":"10.1109/incet49848.2020.9154117","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154117","url":null,"abstract":"This paper aims to prove the hypothesis set which is to humanize headless communication. The voice user interface is the application of headless communication which will be covered in this paper and the idea is to find a perfect symbiotic relationship between the voice user interface and the graphical user interface. There are many technologies which has emerged in the market to give a face to voice to make the solution more valuable and impactful for the customers, but each of these technologies have some pros and cons. This paper aims to discuss all those possible options to create a human centered intelligent user interface by weighing the plus and minus of all the technologies available in the market. The main purpose is to share the conceptual idea which has been designed by the team to create an affordable and effective solution for the customers. The team also went a step ahead to visualize and implement the conceptual idea and created a working prototype of the minimum viable product, which is further elaborated in the paper to showcase the demonstration.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"1 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":"123292337","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/incet49848.2020.9154185
S. Meivel, S. Maheswari
Production in agriculture is not sufficient in today’s world. Therefore, we need to increase production to equalize the needs. However, due to the development in various fields, the human source for working and maintaining the cultivation land with proper consistency is insufficient. When it comes to Indian Agriculture System, the climatic environment is isotropic and there is a lack in the usage of agriculture assets. The irrigation system, which is controlled manually, is not an inefficient manner. There are several problems such as additional water consumption, bad quality of fertilizer preparation, Additional or insufficient fertilizer consumption. An automatic agricultural system with an automated irrigation system having a universal nozzle for spraying water, fertilizer, pesticides based on the need is implemented. The field is monitored by having a soil moisture sensor, humidity sensor, and temperature sensor. The sensing units are placed in various locations for observation. The growth of the plant is monitored using drone NDVI and NIR sensors. This module consists of a Programmable Logic Controller (DRONE) for its overall automation. NDVI Sensors are connected to the IoT controller and the output is given to the solenoid valve. A pumping motor is implemented for irrigation depending upon the requirement the values are opened by using an electrical valve named Solenoid valve (a logic function of ON and OFF as output). As soon as the required level of water is irrigated, the sensing element senses and stops the pump preventing excess irrigation. This DRONE automation is more efficient in automatic water drip Irrigation system, pesticide and fertilizer spraying with float level switch. IoT networking connected to the DRONE controller using the IoT multispectral camera of Drone Controller for damage plant detection, Sprayer controlling and saving the daily database.
{"title":"Optimization of Agricultural Smart System using Remote Sensible NDVI and NIR Thermal Image Analysis Techniques","authors":"S. Meivel, S. Maheswari","doi":"10.1109/incet49848.2020.9154185","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154185","url":null,"abstract":"Production in agriculture is not sufficient in today’s world. Therefore, we need to increase production to equalize the needs. However, due to the development in various fields, the human source for working and maintaining the cultivation land with proper consistency is insufficient. When it comes to Indian Agriculture System, the climatic environment is isotropic and there is a lack in the usage of agriculture assets. The irrigation system, which is controlled manually, is not an inefficient manner. There are several problems such as additional water consumption, bad quality of fertilizer preparation, Additional or insufficient fertilizer consumption. An automatic agricultural system with an automated irrigation system having a universal nozzle for spraying water, fertilizer, pesticides based on the need is implemented. The field is monitored by having a soil moisture sensor, humidity sensor, and temperature sensor. The sensing units are placed in various locations for observation. The growth of the plant is monitored using drone NDVI and NIR sensors. This module consists of a Programmable Logic Controller (DRONE) for its overall automation. NDVI Sensors are connected to the IoT controller and the output is given to the solenoid valve. A pumping motor is implemented for irrigation depending upon the requirement the values are opened by using an electrical valve named Solenoid valve (a logic function of ON and OFF as output). As soon as the required level of water is irrigated, the sensing element senses and stops the pump preventing excess irrigation. This DRONE automation is more efficient in automatic water drip Irrigation system, pesticide and fertilizer spraying with float level switch. IoT networking connected to the DRONE controller using the IoT multispectral camera of Drone Controller for damage plant detection, Sprayer controlling and saving the daily database.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"1 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":"123312232","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/incet49848.2020.9154076
Y. Mane, U. Khot
Initially, legitimate users were working under a normal web browser to do all activities over the internet [1]. To get more secure service and to get protection against Bot activity, the legitimate users switched their activity from Normal web browser to low latency anonymous communication such as Tor Browser. The Traffic monitoring in Tor Network is difficult as the packets are traveling from source to destination in an encrypted fashion and the Tor network hides its identity from destination. But lately, even the illegitimate users such as attackers/criminals started their activity on the Tor browser. The secured Tor network makes the detection of Botnet more difficult. The existing tools for botnet detection became inefficient against Tor-based bots because of the features of the Tor browser. As the Tor Browser is highly secure and because of the ethical issues, doing practical experiments on it is not advisable which could affect the performance and functionality of the Tor browser. It may also affect the endanger users in situations where the failure of Tor’s anonymity has severe consequences. So, in the proposed research work, Private Tor Networks (PTN) on physical or virtual machines with dedicated resources have been created along with Trusted Middle Node. The motivation behind the trusted middle node is to make the Private Tor network more efficient and to increase its performance.
{"title":"A Systematic Way to Implement Private Tor Network with Trusted Middle Node","authors":"Y. Mane, U. Khot","doi":"10.1109/incet49848.2020.9154076","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154076","url":null,"abstract":"Initially, legitimate users were working under a normal web browser to do all activities over the internet [1]. To get more secure service and to get protection against Bot activity, the legitimate users switched their activity from Normal web browser to low latency anonymous communication such as Tor Browser. The Traffic monitoring in Tor Network is difficult as the packets are traveling from source to destination in an encrypted fashion and the Tor network hides its identity from destination. But lately, even the illegitimate users such as attackers/criminals started their activity on the Tor browser. The secured Tor network makes the detection of Botnet more difficult. The existing tools for botnet detection became inefficient against Tor-based bots because of the features of the Tor browser. As the Tor Browser is highly secure and because of the ethical issues, doing practical experiments on it is not advisable which could affect the performance and functionality of the Tor browser. It may also affect the endanger users in situations where the failure of Tor’s anonymity has severe consequences. So, in the proposed research work, Private Tor Networks (PTN) on physical or virtual machines with dedicated resources have been created along with Trusted Middle Node. The motivation behind the trusted middle node is to make the Private Tor network more efficient and to increase its performance.","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":"115908703","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/INCET49848.2020.9154009
Deena Nath Gupta, R. Kumar
The researchers found random numbers beneficial to implement a secure IoT environment. To secure the communications between constrained devices, researchers can use either true random number generators (TRNGs) or pseudorandom number generators (PRNGs) to generate the secure key. Encryption or decryption of the plain text and the mutual authentication between devices uses these keys. PRNGs are highly dependable on TRNGs for the perfect randomness because the randomness of the natural sources or TRNGs is not traceable. Although TRNGs are much safe to generate random numbers, programmers write codes for pseudorandom number generation, commonly known as PRNGs. These PRNGs should use less complicated methods for use in the IoT environment. Authors are writing the programs to generate random numbers independently, without any hardware interruption. In this paper, authors are going to use these concepts to form a new lightweight mechanism for the generation of cryptographically secure random binary bit sequences. Here authors are trying to incorporate the goodness of every flavor at one platform.
{"title":"Generating Random Binary Bit Sequences for Secure Communications between Constraint Devices under the IOT Environment","authors":"Deena Nath Gupta, R. Kumar","doi":"10.1109/INCET49848.2020.9154009","DOIUrl":"https://doi.org/10.1109/INCET49848.2020.9154009","url":null,"abstract":"The researchers found random numbers beneficial to implement a secure IoT environment. To secure the communications between constrained devices, researchers can use either true random number generators (TRNGs) or pseudorandom number generators (PRNGs) to generate the secure key. Encryption or decryption of the plain text and the mutual authentication between devices uses these keys. PRNGs are highly dependable on TRNGs for the perfect randomness because the randomness of the natural sources or TRNGs is not traceable. Although TRNGs are much safe to generate random numbers, programmers write codes for pseudorandom number generation, commonly known as PRNGs. These PRNGs should use less complicated methods for use in the IoT environment. Authors are writing the programs to generate random numbers independently, without any hardware interruption. In this paper, authors are going to use these concepts to form a new lightweight mechanism for the generation of cryptographically secure random binary bit sequences. Here authors are trying to incorporate the goodness of every flavor at one platform.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"25 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":"132054479","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/incet49848.2020.9154069
Atharva Barve, Vishwa Mohan Singh, Shivam Shrirao, M. Bedekar
Air pollution is a growing threat towards society and various measures are being taken recently to control it. The problem of concern which remains is the efficient prediction of air pollution to work in the right direction for reducing the same. Since the AQI follows a periodic pattern, deep learning models can be used to effectively predict the future AQI values. LSTM being a prominent time series forecasting model can be integrated with a separate DNN model to effectively add the impact of weather, temperature and other factors that can affect the future AQI values. The paper also explores the impact of having a parallel DNN to the LSTM cell instead of using the cell alone.
{"title":"Air Quality Index forecasting using parallel Dense Neural Network and LSTM cell","authors":"Atharva Barve, Vishwa Mohan Singh, Shivam Shrirao, M. Bedekar","doi":"10.1109/incet49848.2020.9154069","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154069","url":null,"abstract":"Air pollution is a growing threat towards society and various measures are being taken recently to control it. The problem of concern which remains is the efficient prediction of air pollution to work in the right direction for reducing the same. Since the AQI follows a periodic pattern, deep learning models can be used to effectively predict the future AQI values. LSTM being a prominent time series forecasting model can be integrated with a separate DNN model to effectively add the impact of weather, temperature and other factors that can affect the future AQI values. The paper also explores the impact of having a parallel DNN to the LSTM cell instead of using the cell alone.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"1 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":"130894827","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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