Pub Date : 2022-06-24DOI: 10.1109/CONIT55038.2022.9848353
Karan Gala, Pravesh Ganwani, R. Kulkarni, R. Pawar
3D Reconstructions are being appreciated across various fields as a more informative means of visualisation that offers great insight about the qualitative characteristics of the objects or scene under consideration. Hence more research is being carried out in this area as 3D are proving to be of great help to fields such as medicine, for improving the diagnostic accuracy and surgical precision of the medical procedure. It has also found applications in fields such as intelligent robot navigation by reproduction of the depth map of a scene, object recognition and so on. We present a unique proposition to synthesize volumetric reconstructions from a singular or multiple positions of view, based on RGB images/videos. The project aims at rapidly generating all the different parts of the indoor environment, without having to actually observe them in reality.
{"title":"3DVAEReCNN: Region-based Convolutional Neural Network for Volumetric Rendering of Indoor Scenes","authors":"Karan Gala, Pravesh Ganwani, R. Kulkarni, R. Pawar","doi":"10.1109/CONIT55038.2022.9848353","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848353","url":null,"abstract":"3D Reconstructions are being appreciated across various fields as a more informative means of visualisation that offers great insight about the qualitative characteristics of the objects or scene under consideration. Hence more research is being carried out in this area as 3D are proving to be of great help to fields such as medicine, for improving the diagnostic accuracy and surgical precision of the medical procedure. It has also found applications in fields such as intelligent robot navigation by reproduction of the depth map of a scene, object recognition and so on. We present a unique proposition to synthesize volumetric reconstructions from a singular or multiple positions of view, based on RGB images/videos. The project aims at rapidly generating all the different parts of the indoor environment, without having to actually observe them in reality.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114201348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.1109/CONIT55038.2022.9847806
Mahfuzulhoq Chowdhury, Ajoy Deb Nath
The University library is one of the parts and parcels of the universities that can assist students and teachers teaching and learning work by providing necessary services related to in-formation sharing, book search, book borrow, research document access, and reading room facilities, among others. A vast amount of the literature works related to library facilities emphasize providing services via offline mode rather than online mode. Most of the existing works on online-based library services focus on a single or limited number of library facilities and resources. The existing research works on university library facilities do not consider multiple library resources, different types of users, and multiple features at the same time. Thus, the existing university library related works mainly suffer from the shortage of library resources along with higher time and cost wastage. To tackle with the existing challenges, this paper presents a mobile application featuring next-generation library facilities for university students in Bangladesh. Our proposed limitless mobile application provides several features for students like book or research document search, borrow, order and access, payment and checkout, course enrollment, reading room allocation, request or donate a book, history, notifications, track order, complaint, among others. By using our proposed application, one member of the university library can access the resources of other university libraries via the membership/join feature. Our review result indicates that the majority of the student users are satisfied with the usefulness and necessity of the proposed mobile application features.
{"title":"Limitless: A Mobile Application Featuring Next Generation Library Facilities For the Bangladeshi University Students","authors":"Mahfuzulhoq Chowdhury, Ajoy Deb Nath","doi":"10.1109/CONIT55038.2022.9847806","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847806","url":null,"abstract":"The University library is one of the parts and parcels of the universities that can assist students and teachers teaching and learning work by providing necessary services related to in-formation sharing, book search, book borrow, research document access, and reading room facilities, among others. A vast amount of the literature works related to library facilities emphasize providing services via offline mode rather than online mode. Most of the existing works on online-based library services focus on a single or limited number of library facilities and resources. The existing research works on university library facilities do not consider multiple library resources, different types of users, and multiple features at the same time. Thus, the existing university library related works mainly suffer from the shortage of library resources along with higher time and cost wastage. To tackle with the existing challenges, this paper presents a mobile application featuring next-generation library facilities for university students in Bangladesh. Our proposed limitless mobile application provides several features for students like book or research document search, borrow, order and access, payment and checkout, course enrollment, reading room allocation, request or donate a book, history, notifications, track order, complaint, among others. By using our proposed application, one member of the university library can access the resources of other university libraries via the membership/join feature. Our review result indicates that the majority of the student users are satisfied with the usefulness and necessity of the proposed mobile application features.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121701697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.1109/CONIT55038.2022.9847671
Bryan E. Escoto
The hard shading caused by dirt accumulation on the PV surface, shadows caused by near structures, trees, and even unwanted materials at the surface of the panels degrades the performance of the PV panels, significantly reducing the power output and its efficiency. However, the detection of shading of the solar panel is a complex and challenging process since the panel's power conversion varies and is affected by several factors such as solar irradiance, temperature, the position of the sun, location of shading, etc. This project created an Artificial Neural Network (ANN) model that detects the hard shading and its coverage to PV panels. The optimum ANN model developed in this study can detect solar panel hard shading coverage with 99.98 % accuracy. The best ANN network topology is 3-60-1 (input-hidden neurons-output) model which provides an excellent generalization ability. This model utilized the tan Sigmoid transfer function for both input-hidden and hidden-output layer, and for the optimization process, Levenberg Marquardt outperformed other algorithms. The optimum ANN model has the lowest MSE value of 0.000020333 and with highest R-values of 0.99992, 0.99989, 0.9999, and 0.99992 for training, validation, testing, and overall, respectively. Based on the sensitivity analysis result, the open-circuit voltage significantly contributes to the solar panel shading detection.
{"title":"Modeling and Detection of PV Panel Hard Shading Using Artificial Neural Network","authors":"Bryan E. Escoto","doi":"10.1109/CONIT55038.2022.9847671","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847671","url":null,"abstract":"The hard shading caused by dirt accumulation on the PV surface, shadows caused by near structures, trees, and even unwanted materials at the surface of the panels degrades the performance of the PV panels, significantly reducing the power output and its efficiency. However, the detection of shading of the solar panel is a complex and challenging process since the panel's power conversion varies and is affected by several factors such as solar irradiance, temperature, the position of the sun, location of shading, etc. This project created an Artificial Neural Network (ANN) model that detects the hard shading and its coverage to PV panels. The optimum ANN model developed in this study can detect solar panel hard shading coverage with 99.98 % accuracy. The best ANN network topology is 3-60-1 (input-hidden neurons-output) model which provides an excellent generalization ability. This model utilized the tan Sigmoid transfer function for both input-hidden and hidden-output layer, and for the optimization process, Levenberg Marquardt outperformed other algorithms. The optimum ANN model has the lowest MSE value of 0.000020333 and with highest R-values of 0.99992, 0.99989, 0.9999, and 0.99992 for training, validation, testing, and overall, respectively. Based on the sensitivity analysis result, the open-circuit voltage significantly contributes to the solar panel shading detection.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"520 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121977036","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}
Human health is severely endangered by the novel coronavirus (COVID-19). It is viewed as the worst global health threat humans have faced since the second world war and the WHO recognized it as a pandemic on March 11, 2020. This pandemic led several nations to adopt statewide lockdowns, while the industrial, construction, and transportation activities in several nations were disrupted, which lead to a significant shift in air pollutants. The lockdown, however, significantly impacted the environment and air quality in distinct cities. There are numerous ground stations deployed by pollution control organizations to monitor and collect the air pollutants data, but it is not feasible to set up a ground station in every city. In places where ground stations are not available for data collection, Google Earth Engine (GEE) satellite captured data can be used for data analysis. This study aimed to analyze the changes in air pollutants during the different lockdowns in India, such as nitrogen dioxide(NO2), sulfur dioxide(SO2), and carbon monoxide(CO) that contribute significantly to air pollution. In India, lockdowns were imposed during different periods of 2020, 2021, and 2022, according to COVID-19 waves. The air pollutants data during different waves have been analyzed and compared with the pre-COVID year (2019) data for the same duration. According to the study results, $N$ O2 and $S$ O2 were drastically reduced, but only a minor reduction in CO. Delhi, Jaipur, Ahmedabad, and Mumbai were among the major cities that saw the largest reduction, which was up to 60%.
{"title":"Air Quality Analysis During COVID-19 Utilizing Satellite Data","authors":"Tinku Singh, Nikhil Sharma, Vinarm Rajput, Suryanshi Mishra, Satakshi, Manish Kumar","doi":"10.1109/CONIT55038.2022.9848299","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848299","url":null,"abstract":"Human health is severely endangered by the novel coronavirus (COVID-19). It is viewed as the worst global health threat humans have faced since the second world war and the WHO recognized it as a pandemic on March 11, 2020. This pandemic led several nations to adopt statewide lockdowns, while the industrial, construction, and transportation activities in several nations were disrupted, which lead to a significant shift in air pollutants. The lockdown, however, significantly impacted the environment and air quality in distinct cities. There are numerous ground stations deployed by pollution control organizations to monitor and collect the air pollutants data, but it is not feasible to set up a ground station in every city. In places where ground stations are not available for data collection, Google Earth Engine (GEE) satellite captured data can be used for data analysis. This study aimed to analyze the changes in air pollutants during the different lockdowns in India, such as nitrogen dioxide(NO2), sulfur dioxide(SO2), and carbon monoxide(CO) that contribute significantly to air pollution. In India, lockdowns were imposed during different periods of 2020, 2021, and 2022, according to COVID-19 waves. The air pollutants data during different waves have been analyzed and compared with the pre-COVID year (2019) data for the same duration. According to the study results, $N$ O2 and $S$ O2 were drastically reduced, but only a minor reduction in CO. Delhi, Jaipur, Ahmedabad, and Mumbai were among the major cities that saw the largest reduction, which was up to 60%.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115781556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.1109/CONIT55038.2022.9847910
Kiran Ingale, Neel Madane, Pradyna Patil
The advent of Machine Learning and development in statistics has made it possible to gain crucial insights from immense data obtained from surveys. It has made it easy to interpret huge numbers and made it possible to make predictions with extreme accuracy in a myriad of fields. Healthcare is one such field in which this technology can be extensively applied to make early and precise predictions of diseases based on the medical information of the patient. Arteriosclerosis of the human heart is a major concern worldwide as it is responsible for the majority of deaths. Early signs of arteriosclerosis of human heart prediction based on the health and lifestyle parameters of a patient can prove lifesaving. This research aims to create and train a machine learning model which can predict whether an individual faces a risk of arteriosclerosis. The highest prediction accuracy obtained was 86.8293% by logistic regression.
{"title":"An Evaluation of Prediction Accuracy of Machine Learning Algorithms for Arteriosclerosis of the Human Heart","authors":"Kiran Ingale, Neel Madane, Pradyna Patil","doi":"10.1109/CONIT55038.2022.9847910","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847910","url":null,"abstract":"The advent of Machine Learning and development in statistics has made it possible to gain crucial insights from immense data obtained from surveys. It has made it easy to interpret huge numbers and made it possible to make predictions with extreme accuracy in a myriad of fields. Healthcare is one such field in which this technology can be extensively applied to make early and precise predictions of diseases based on the medical information of the patient. Arteriosclerosis of the human heart is a major concern worldwide as it is responsible for the majority of deaths. Early signs of arteriosclerosis of human heart prediction based on the health and lifestyle parameters of a patient can prove lifesaving. This research aims to create and train a machine learning model which can predict whether an individual faces a risk of arteriosclerosis. The highest prediction accuracy obtained was 86.8293% by logistic regression.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115974467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.1109/CONIT55038.2022.9847854
S. Sushanth Kumar, I. Ali, A. Siddiqui
This paper proposes Maximum Power Point Tracking (MPPT) for a fixed speed wind energy system based on single phase grid-connected three-phase Permanent Magnet Synchronous Generator (PMSG) for residential applications. The proposed method of MPPT based converter topology with AC-DC converter and DC-DC boost converter allied with single phase grid-connected wind energy system to obtain maximum power. Synchronization of grid along with wind energy, the switching approaches of projected inverter is used with a combination of square wave (SW) and sinusoidal pulse width modulation (SPWM) signals. The performance of projected inverter power circuit under the single-phase grid-connected wind energy developed via MATLAB. Furthermore, maintain power balance and increase the efficiency of the system, the PMSG module is developed in MATLAB with a simple MPPT based converter topology.
{"title":"Control of Wind Energy Connected Single Phase Grid with MPPT for Domestic Purposes","authors":"S. Sushanth Kumar, I. Ali, A. Siddiqui","doi":"10.1109/CONIT55038.2022.9847854","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847854","url":null,"abstract":"This paper proposes Maximum Power Point Tracking (MPPT) for a fixed speed wind energy system based on single phase grid-connected three-phase Permanent Magnet Synchronous Generator (PMSG) for residential applications. The proposed method of MPPT based converter topology with AC-DC converter and DC-DC boost converter allied with single phase grid-connected wind energy system to obtain maximum power. Synchronization of grid along with wind energy, the switching approaches of projected inverter is used with a combination of square wave (SW) and sinusoidal pulse width modulation (SPWM) signals. The performance of projected inverter power circuit under the single-phase grid-connected wind energy developed via MATLAB. Furthermore, maintain power balance and increase the efficiency of the system, the PMSG module is developed in MATLAB with a simple MPPT based converter topology.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132016328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.1109/CONIT55038.2022.9847836
V. Bhende, A. Sinha, A. Junnarkar
Because of the nature and characteristics of conveying significant level road security and enhanced traffic the executives, vehicular networks are turning into a key report subject under the intelligent transportation system (ITS). Weighty correspondence gear is introduced under vehicles, which requires a powerful stock, an on-board handling system, and information stockpiling gadgets. To keep up with and further develop the traffic signal system, an assortment of remote correspondence advances is utilized. The ITS can offer types of assistance to traffic specialists as well as security precautionary measures for drivers and travelers. Multiple ways for discussing security and protection issues for vehicle ad hoc networks (VANETs). In this paper, novel routing protocol called Secure VANET communications using Hybrid Trust (SVC-HT) is proposed to protect the communications from the malicious vehicles in the network. We integrated the hybrid trust approach with the clustering mechanism to improve the VANET performances. The proposed SVC-HT consists of two phases such as attacker detection with Cluster Head (CH) selection and reliable route formation for secure data transmission. The experimental outcomes of SVC-HT protocol are compared with three recent VANET protocols in terms of average throughput, Packet Delivery Ratio (PDR), delay, and overhead. The results of SVC-HT outperformed the existing protocols.
{"title":"SVC-HT: Secure Vehicular Ad hoc Communications using Hybrid Trust","authors":"V. Bhende, A. Sinha, A. Junnarkar","doi":"10.1109/CONIT55038.2022.9847836","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847836","url":null,"abstract":"Because of the nature and characteristics of conveying significant level road security and enhanced traffic the executives, vehicular networks are turning into a key report subject under the intelligent transportation system (ITS). Weighty correspondence gear is introduced under vehicles, which requires a powerful stock, an on-board handling system, and information stockpiling gadgets. To keep up with and further develop the traffic signal system, an assortment of remote correspondence advances is utilized. The ITS can offer types of assistance to traffic specialists as well as security precautionary measures for drivers and travelers. Multiple ways for discussing security and protection issues for vehicle ad hoc networks (VANETs). In this paper, novel routing protocol called Secure VANET communications using Hybrid Trust (SVC-HT) is proposed to protect the communications from the malicious vehicles in the network. We integrated the hybrid trust approach with the clustering mechanism to improve the VANET performances. The proposed SVC-HT consists of two phases such as attacker detection with Cluster Head (CH) selection and reliable route formation for secure data transmission. The experimental outcomes of SVC-HT protocol are compared with three recent VANET protocols in terms of average throughput, Packet Delivery Ratio (PDR), delay, and overhead. The results of SVC-HT outperformed the existing protocols.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"29 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132372365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.1109/CONIT55038.2022.9848290
V. V., P. Samuel
A software Requirements Specification (SRS) document is an NL (Natural Language) written textual specification that documents the functional and non-functional requirements of the system and various expectations of clients in a software development project. To understand the different requirements of the system, developers make use of this SRS document. In this paper, we apply Naive Bayes classifiers - Multinomial and Gaussian over different SRS documents and classify the software requirement entities (Actors and Use Cases) using Machine Learning based methods. SRS documents of 28 different systems are considered for our purpose and we define labels for the entities Actor and Use Case. Multinomial Naive Bayes is a popular classifier because of its computational efficiency and relatively good predictive performance. Out of the classifiers tried out, the Multinomial Naive Bayes recognizes Actors and Use Cases with an accuracy of 91%. Actors and Use Cases can be extracted with high accuracy from the SRS documents using Multinomial Naive Bayes, which then can be used for plotting the Use Case diagram of the system. Automated UML (Unified Modeling Language) model generation approaches have a very prominent role in an agile development environment where requirements change frequently. In this work, we attempt to automate the Requirement Engineering (RE) phase that can improve and accelerate the entire Software Development Life Cycle (SDLC).
{"title":"A Multinomial Naïve Bayes Classifier for identifying Actors and Use Cases from Software Requirement Specification documents","authors":"V. V., P. Samuel","doi":"10.1109/CONIT55038.2022.9848290","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848290","url":null,"abstract":"A software Requirements Specification (SRS) document is an NL (Natural Language) written textual specification that documents the functional and non-functional requirements of the system and various expectations of clients in a software development project. To understand the different requirements of the system, developers make use of this SRS document. In this paper, we apply Naive Bayes classifiers - Multinomial and Gaussian over different SRS documents and classify the software requirement entities (Actors and Use Cases) using Machine Learning based methods. SRS documents of 28 different systems are considered for our purpose and we define labels for the entities Actor and Use Case. Multinomial Naive Bayes is a popular classifier because of its computational efficiency and relatively good predictive performance. Out of the classifiers tried out, the Multinomial Naive Bayes recognizes Actors and Use Cases with an accuracy of 91%. Actors and Use Cases can be extracted with high accuracy from the SRS documents using Multinomial Naive Bayes, which then can be used for plotting the Use Case diagram of the system. Automated UML (Unified Modeling Language) model generation approaches have a very prominent role in an agile development environment where requirements change frequently. In this work, we attempt to automate the Requirement Engineering (RE) phase that can improve and accelerate the entire Software Development Life Cycle (SDLC).","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130199771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.1109/CONIT55038.2022.9847809
M. Alam, Maruf Haider Chowdhury, M. Islam, Afroza Akter, Affaf Hasan, Mahfuz Ullah
Vehicle ad-hoc network is an intelligent transport system. We investigate trifles of the ad-hoc networking system and discovered there are a number of inconclusive issues that could lead to the network collapse. In this paper we tried to ameliorate the road management system and solve the traffic jam issue in real time. VANET applications enable vehicles to connect to the internet to obtain real time news, traffic and weather reports. In real-time VANET is a scheme system, where assorted volatile vehicles and connecting devices come in concretion with a wireless medium. Vehicle to vehicle (V2V) communication is a wireless network, which exchange information about the speed and location of contiguous vehicles, shows great assurance to help fudge accidents, diminish traffic congestion and flourish the ambience. Recent studies have showed that routing protocols may redact on vehicle networks developed using dynamic road traffic information for select the most suitable forwarding path or node.
{"title":"Improving Routing System in Vehicular Ad Hoc Network using Real Time Vehicular Traffic Information on City Roads","authors":"M. Alam, Maruf Haider Chowdhury, M. Islam, Afroza Akter, Affaf Hasan, Mahfuz Ullah","doi":"10.1109/CONIT55038.2022.9847809","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847809","url":null,"abstract":"Vehicle ad-hoc network is an intelligent transport system. We investigate trifles of the ad-hoc networking system and discovered there are a number of inconclusive issues that could lead to the network collapse. In this paper we tried to ameliorate the road management system and solve the traffic jam issue in real time. VANET applications enable vehicles to connect to the internet to obtain real time news, traffic and weather reports. In real-time VANET is a scheme system, where assorted volatile vehicles and connecting devices come in concretion with a wireless medium. Vehicle to vehicle (V2V) communication is a wireless network, which exchange information about the speed and location of contiguous vehicles, shows great assurance to help fudge accidents, diminish traffic congestion and flourish the ambience. Recent studies have showed that routing protocols may redact on vehicle networks developed using dynamic road traffic information for select the most suitable forwarding path or node.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133876322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-24DOI: 10.1109/CONIT55038.2022.9848228
Eakanath Raparla, Veeresh Raavipaati, Shiva Nikhil G, Sameer S T Md, K. S
The task of Text-to-Face synthesis is quite intricate and there hasn't been much research done on it, until recently. This is mainly due to the complex nature of human face and it's features, which vary widely over different situations. That being said, the field of Text-to-Image synthesis has gathered considerable interest quite late. In earlier research, generation is mainly done using reconstruction of visuals which correlate to the given words. Due to the rise of generative models in the field of deep learning, there has been a departure from these traditional computer vision based retrieval methods. One of the most significant factors for this change is the introduction of GANs. The idea of learning and reproducing the image as a whole, helped in producing better images. The introduction of attention based mechanisms, helped in synthesizing more detailed images which manages to show several facial features like eye brows, hair color, nose shape etc. In this survey, we discuss and summarize some of the methods used for the purpose of image & face generation and their development over the years.
{"title":"Different Techniques of Facial Image Generation from Textual Input : A Survey","authors":"Eakanath Raparla, Veeresh Raavipaati, Shiva Nikhil G, Sameer S T Md, K. S","doi":"10.1109/CONIT55038.2022.9848228","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848228","url":null,"abstract":"The task of Text-to-Face synthesis is quite intricate and there hasn't been much research done on it, until recently. This is mainly due to the complex nature of human face and it's features, which vary widely over different situations. That being said, the field of Text-to-Image synthesis has gathered considerable interest quite late. In earlier research, generation is mainly done using reconstruction of visuals which correlate to the given words. Due to the rise of generative models in the field of deep learning, there has been a departure from these traditional computer vision based retrieval methods. One of the most significant factors for this change is the introduction of GANs. The idea of learning and reproducing the image as a whole, helped in producing better images. The introduction of attention based mechanisms, helped in synthesizing more detailed images which manages to show several facial features like eye brows, hair color, nose shape etc. In this survey, we discuss and summarize some of the methods used for the purpose of image & face generation and their development over the years.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132625286","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：