The whole planet today is having to fight COVID-19 with big obstacles. The COVID-19 influenced several countries around the world between December 2019 and the present day. Many organisations and scientists seek to find a vaccine and to minimize the spread of COVID-19. Artificial Intelligence is one technology that can successfully address this virus (AI). In the case of other pathogens, artificial intelligence performed very well and could help us cope with the virus COVID-19, too. It is the imagination and the information of the people who use it which will help to overcome this dilemma. In some previous instances AI played a major role in virus prevention and identification. We have an ability to detect certain aspects of the AI because of the COVID-19 crisis. Machine learning that an AI subclass is used to identify patterns and to plan valuable knowledge based on recorded data sets. At the point where used entirely, AI can exceed human efforts by speed and differentiate designs from knowledge previously ignored. However many correct and appropriate data are needed for effective implementation of AI systems. This paper discusses the AI's role in COVID-19 prevention and detection and examines numerous technological aspects of AI. This paper would also clarify where AI will contribute with likely solutions to stop the spread of COVID-19.
{"title":"The Avoidance And Detection Function Of Artificial Intelligence In Covid-19","authors":"Alaa Amjed Abdulateef, Alaa Hamid Mohammed, Ihsan Amjad Abdulateef","doi":"10.1109/HORA52670.2021.9461280","DOIUrl":"https://doi.org/10.1109/HORA52670.2021.9461280","url":null,"abstract":"The whole planet today is having to fight COVID-19 with big obstacles. The COVID-19 influenced several countries around the world between December 2019 and the present day. Many organisations and scientists seek to find a vaccine and to minimize the spread of COVID-19. Artificial Intelligence is one technology that can successfully address this virus (AI). In the case of other pathogens, artificial intelligence performed very well and could help us cope with the virus COVID-19, too. It is the imagination and the information of the people who use it which will help to overcome this dilemma. In some previous instances AI played a major role in virus prevention and identification. We have an ability to detect certain aspects of the AI because of the COVID-19 crisis. Machine learning that an AI subclass is used to identify patterns and to plan valuable knowledge based on recorded data sets. At the point where used entirely, AI can exceed human efforts by speed and differentiate designs from knowledge previously ignored. However many correct and appropriate data are needed for effective implementation of AI systems. This paper discusses the AI's role in COVID-19 prevention and detection and examines numerous technological aspects of AI. This paper would also clarify where AI will contribute with likely solutions to stop the spread of COVID-19.","PeriodicalId":270469,"journal":{"name":"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126801110","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 : 2021-06-11DOI: 10.1109/HORA52670.2021.9461315
M. Makhseed, F. Salam, S. El-Aswad, S. Esmaeili
Concentration of air pollutants exceeds levels associated with increased risk of health programs. In order to obtain a healthier quality of life with minimized health risks, a reduction of pollution is needed. A major factor of air pollution in urban cities is the burning of waste. Therefore, a reduction in pollution levels can be achieved by reducing waste. This paper discusses the design and implementation of a smart recycling bin (Enviro-Bin). The smart recycling bin filters the waste according to the following material types: metal, glass, and paper. Filtering waste according to material type will consequently lead to decreasing the amount of harmful gases produced from burning the waste and encourage recycling. The proposed prototype is an automated waste material filtering system that contains infrared sensors and two proximity sensors, an inductive sensor and a capacitive one, to determine the presence and type of material. Moreover, each compartment includes an IR sensor to detect the level of the waste in the container.
{"title":"Design and Assembly of A Smart Recycling Bin","authors":"M. Makhseed, F. Salam, S. El-Aswad, S. Esmaeili","doi":"10.1109/HORA52670.2021.9461315","DOIUrl":"https://doi.org/10.1109/HORA52670.2021.9461315","url":null,"abstract":"Concentration of air pollutants exceeds levels associated with increased risk of health programs. In order to obtain a healthier quality of life with minimized health risks, a reduction of pollution is needed. A major factor of air pollution in urban cities is the burning of waste. Therefore, a reduction in pollution levels can be achieved by reducing waste. This paper discusses the design and implementation of a smart recycling bin (Enviro-Bin). The smart recycling bin filters the waste according to the following material types: metal, glass, and paper. Filtering waste according to material type will consequently lead to decreasing the amount of harmful gases produced from burning the waste and encourage recycling. The proposed prototype is an automated waste material filtering system that contains infrared sensors and two proximity sensors, an inductive sensor and a capacitive one, to determine the presence and type of material. Moreover, each compartment includes an IR sensor to detect the level of the waste in the container.","PeriodicalId":270469,"journal":{"name":"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122285886","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 : 2021-06-11DOI: 10.1109/HORA52670.2021.9461384
A. Duru, K. Ileri
RLC circuits are fundamental topics for engineering undergraduate students especially in electrical and electronics majors, and they have numerous applications to design electrical circuits. Medical devices, mobile phones, computers, FM radios, and TVs are just a few examples that use different forms of RLC circuits. Although the circuits are very useful for an intended application, step-by-step calculations must be done to analyze the behavior of each component in the circuitry. In this study, a mobile application was developed to catch the difference between two types of RLC circuits, series and parallel, and understand the effects of each components’ value change by checking simulation results.
{"title":"Implementation of a Mobile Application for Teaching and Analyzing RLC Circuits","authors":"A. Duru, K. Ileri","doi":"10.1109/HORA52670.2021.9461384","DOIUrl":"https://doi.org/10.1109/HORA52670.2021.9461384","url":null,"abstract":"RLC circuits are fundamental topics for engineering undergraduate students especially in electrical and electronics majors, and they have numerous applications to design electrical circuits. Medical devices, mobile phones, computers, FM radios, and TVs are just a few examples that use different forms of RLC circuits. Although the circuits are very useful for an intended application, step-by-step calculations must be done to analyze the behavior of each component in the circuitry. In this study, a mobile application was developed to catch the difference between two types of RLC circuits, series and parallel, and understand the effects of each components’ value change by checking simulation results.","PeriodicalId":270469,"journal":{"name":"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126551702","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 : 2021-06-11DOI: 10.1109/HORA52670.2021.9461273
H. Altunay, Zafer Albayrak, A. Özalp, Muhammet Çakmak
Supervisory control and data acquisition (SCADA) systems are used with monitoring and control purposes for the process not to fail in industrial control systems. Today, the increase in the use of standard protocols, hardware, and software in the SCADA systems that can connect to the internet and institutional networks causes these systems to become a target for more cyber-attacks. Intrusion detection systems are used to reduce or minimize cyber-attack threats. The use of deep learning-based intrusion detection systems also increases in parallel with the increase in the amount of data in the SCADA systems. The unsupervised feature learning present in the deep learning approaches enables the learning of important features within the large datasets. The features learned in an unsupervised way by using deep learning techniques are used in order to classify the data as normal or abnormal. Architectures such as convolutional neural network (CNN), Autoencoder (AE), deep belief network (DBN), and long short-term memory network (LSTM) are used to learn the features of SCADA data. These architectures use softmax function, extreme learning machine (ELM), deep belief networks, and multilayer perceptron (MLP) in the classification process. In this study, anomaly-based intrusion detection systems consisting of convolutional neural network, autoencoder, deep belief network, long short-term memory network, or various combinations of these methods on the SCADA networks in the literature were analyzed and the positive and negative aspects of these approaches were explained through their attack detection performances.
{"title":"Analysis of Anomaly Detection Approaches Performed Through Deep Learning Methods in SCADA Systems","authors":"H. Altunay, Zafer Albayrak, A. Özalp, Muhammet Çakmak","doi":"10.1109/HORA52670.2021.9461273","DOIUrl":"https://doi.org/10.1109/HORA52670.2021.9461273","url":null,"abstract":"Supervisory control and data acquisition (SCADA) systems are used with monitoring and control purposes for the process not to fail in industrial control systems. Today, the increase in the use of standard protocols, hardware, and software in the SCADA systems that can connect to the internet and institutional networks causes these systems to become a target for more cyber-attacks. Intrusion detection systems are used to reduce or minimize cyber-attack threats. The use of deep learning-based intrusion detection systems also increases in parallel with the increase in the amount of data in the SCADA systems. The unsupervised feature learning present in the deep learning approaches enables the learning of important features within the large datasets. The features learned in an unsupervised way by using deep learning techniques are used in order to classify the data as normal or abnormal. Architectures such as convolutional neural network (CNN), Autoencoder (AE), deep belief network (DBN), and long short-term memory network (LSTM) are used to learn the features of SCADA data. These architectures use softmax function, extreme learning machine (ELM), deep belief networks, and multilayer perceptron (MLP) in the classification process. In this study, anomaly-based intrusion detection systems consisting of convolutional neural network, autoencoder, deep belief network, long short-term memory network, or various combinations of these methods on the SCADA networks in the literature were analyzed and the positive and negative aspects of these approaches were explained through their attack detection performances.","PeriodicalId":270469,"journal":{"name":"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126579167","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 : 2021-06-11DOI: 10.1109/HORA52670.2021.9461305
Jan-Philipp Kress, A. Morgado-Estevez, F. Perez-Peña, K. Schmidt, Hektor Hebert
The precise measurement and processing of dynamic vehicle data lays the foundation for modern active safety systems and driver assistance systems for automobiles and two-wheelers. For the determination of the longitudinal vehicle dynamics, sensing the wheel speed is one elementary measured quantity. This paper proposes a Hardware in the Loop (HiL) test bench that is used for the development and evaluation of a velocity measurement, consisting of two redundant magneto-resistive sensor elements and an encoder disk. This is intended to precisely determine the vehicle velocity on the rear axle (single axis) of scooters with an engine displacement of 50 cubic centimeters. Therefore, a stepper motor powers the encoder disk on which two sensors are placed. An Electronic Control Unit (ECU) manages the measurement, the motor control, the Human Machine Interface (HMI) and the real-time communication through a serial interface to the computer, running the simulation. To represent the virtual test vehicle, the mathematical model is integrated into Matlab Simulink. The test bench was developed under the criteria of low cost, small size and different operating modes.
{"title":"Development of single-Axis Wheel Speed Sensor HiL Test Bench for Vehicle Velocity Control","authors":"Jan-Philipp Kress, A. Morgado-Estevez, F. Perez-Peña, K. Schmidt, Hektor Hebert","doi":"10.1109/HORA52670.2021.9461305","DOIUrl":"https://doi.org/10.1109/HORA52670.2021.9461305","url":null,"abstract":"The precise measurement and processing of dynamic vehicle data lays the foundation for modern active safety systems and driver assistance systems for automobiles and two-wheelers. For the determination of the longitudinal vehicle dynamics, sensing the wheel speed is one elementary measured quantity. This paper proposes a Hardware in the Loop (HiL) test bench that is used for the development and evaluation of a velocity measurement, consisting of two redundant magneto-resistive sensor elements and an encoder disk. This is intended to precisely determine the vehicle velocity on the rear axle (single axis) of scooters with an engine displacement of 50 cubic centimeters. Therefore, a stepper motor powers the encoder disk on which two sensors are placed. An Electronic Control Unit (ECU) manages the measurement, the motor control, the Human Machine Interface (HMI) and the real-time communication through a serial interface to the computer, running the simulation. To represent the virtual test vehicle, the mathematical model is integrated into Matlab Simulink. The test bench was developed under the criteria of low cost, small size and different operating modes.","PeriodicalId":270469,"journal":{"name":"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131642752","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 : 2021-06-11DOI: 10.1109/HORA52670.2021.9461348
V. Gasimov, Adil Nastakalov
The article is devoted to the problem of quantitative assessment of the sustainability of communication channels or, more precisely, the sustainability of communication between two neighboring network nodes built on the basis of computer technology. Here, in order to achieve more accurate results, the process of assessing the quality of communication is carried out by determining the probability of its break within one segment. To carry out the calculations, network segments that are popular in practice are considered, where a different number of devices and communication lines are used. For this purpose, the article analyzes various models of network segments and examines the assessment of their stability. In particular, the “ 1x1” model is considered, built on one network device on each side and a plurality of communication lines between them; a “lx2” model built using one network device on one side and two network devices on the other side with two communication lines; and a 2x2” model built using two network devices on each side and four communication lines. It also compares the ring topology of the network- the”lxlxl” network model consisting of three elements, with these segment models. Finally, the optimal structure of complex networks located over a large geographical area is proposed in terms of sustainability and efficiency.
{"title":"Assessment of the sustainability of communication networks built on the basis of computer networks","authors":"V. Gasimov, Adil Nastakalov","doi":"10.1109/HORA52670.2021.9461348","DOIUrl":"https://doi.org/10.1109/HORA52670.2021.9461348","url":null,"abstract":"The article is devoted to the problem of quantitative assessment of the sustainability of communication channels or, more precisely, the sustainability of communication between two neighboring network nodes built on the basis of computer technology. Here, in order to achieve more accurate results, the process of assessing the quality of communication is carried out by determining the probability of its break within one segment. To carry out the calculations, network segments that are popular in practice are considered, where a different number of devices and communication lines are used. For this purpose, the article analyzes various models of network segments and examines the assessment of their stability. In particular, the “ 1x1” model is considered, built on one network device on each side and a plurality of communication lines between them; a “lx2” model built using one network device on one side and two network devices on the other side with two communication lines; and a 2x2” model built using two network devices on each side and four communication lines. It also compares the ring topology of the network- the”lxlxl” network model consisting of three elements, with these segment models. Finally, the optimal structure of complex networks located over a large geographical area is proposed in terms of sustainability and efficiency.","PeriodicalId":270469,"journal":{"name":"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132951757","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 : 2021-06-11DOI: 10.1109/HORA52670.2021.9461367
F. O. Babalola, Önsen Toygar, Y. Bi̇ti̇ri̇m
A wrist vein recognition system is proposed in this paper. The system combines three texture-based feature descriptors, namely, multiple filters of Binarized Statistical Image Features (M-BSIF), 2D Gabor filter, and Histogram of Gradient orientation by Decision-Level Fusion. The method was tested on two publicly available datasets obtained from FYO and PUT databases. The proposed method outperforms the individual descriptors and achieves 95.63% and 93.92% accuracies on FYO and PUT databases, respectively.
{"title":"Wrist Vein Recognition by Fusion of Multiple Handcrafted Methods","authors":"F. O. Babalola, Önsen Toygar, Y. Bi̇ti̇ri̇m","doi":"10.1109/HORA52670.2021.9461367","DOIUrl":"https://doi.org/10.1109/HORA52670.2021.9461367","url":null,"abstract":"A wrist vein recognition system is proposed in this paper. The system combines three texture-based feature descriptors, namely, multiple filters of Binarized Statistical Image Features (M-BSIF), 2D Gabor filter, and Histogram of Gradient orientation by Decision-Level Fusion. The method was tested on two publicly available datasets obtained from FYO and PUT databases. The proposed method outperforms the individual descriptors and achieves 95.63% and 93.92% accuracies on FYO and PUT databases, respectively.","PeriodicalId":270469,"journal":{"name":"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124835207","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 : 2021-06-11DOI: 10.1109/hora52670.2021.9461375
{"title":"[HORA 2021 Copyright notice]","authors":"","doi":"10.1109/hora52670.2021.9461375","DOIUrl":"https://doi.org/10.1109/hora52670.2021.9461375","url":null,"abstract":"","PeriodicalId":270469,"journal":{"name":"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128020809","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 : 2021-06-11DOI: 10.1109/HORA52670.2021.9461378
Mehmet Korkmaz, Emre Kocyigit, O. K. Sahingoz, B. Diri
Recently, cyber-attacks have increased worldwide, especially during the pandemic period. The number of connected devices in the world and the anonymous structure of the internet enable this security deficit for not only computer networks but also single computing devices. With the connected use of computing device in anytime and anywhere conditions, lots of real-world activities are transferred to the digital world by adapting them to new lifestyles. Thus, the concept of cybersecurity has become more focused not only for security admins but also for academicians/researchers. Phishing attacks, which hackers mostly prefer to use in the last decade, have become even more harmful because its focuses on the weakest part of the security chain: computer user. Therefore, it is extremely important to prevent these cyber-attacks before they reach users. Based on this idea, we aimed to implement a phishing detection system by using a Convolutional Neural Network with n-gram features that are extracted from URLs. There are different n-gram feature extraction techniques, and in this work, it is aimed to determine which of them is more effective for our proposals. As a second goal, it is aimed to discover what parameters of the n-gram work best. In experiments, it is discovered that unigram has the highest accuracy rate. It was observed that, instead of all the characters that are obtained in unigram, the specified 70 characters (regardless of case sensitivity) give the highest accuracy rate of 88.90% with a High-Risk URL dataset. Experimental results also showed that a URL can be classified (either as legitimate or phishing) in about 0.008 seconds. These metrics can be accepted at a very good rate both in accuracy and run-time efficiency.
{"title":"Phishing Web Page Detection Using N-gram Features Extracted From URLs","authors":"Mehmet Korkmaz, Emre Kocyigit, O. K. Sahingoz, B. Diri","doi":"10.1109/HORA52670.2021.9461378","DOIUrl":"https://doi.org/10.1109/HORA52670.2021.9461378","url":null,"abstract":"Recently, cyber-attacks have increased worldwide, especially during the pandemic period. The number of connected devices in the world and the anonymous structure of the internet enable this security deficit for not only computer networks but also single computing devices. With the connected use of computing device in anytime and anywhere conditions, lots of real-world activities are transferred to the digital world by adapting them to new lifestyles. Thus, the concept of cybersecurity has become more focused not only for security admins but also for academicians/researchers. Phishing attacks, which hackers mostly prefer to use in the last decade, have become even more harmful because its focuses on the weakest part of the security chain: computer user. Therefore, it is extremely important to prevent these cyber-attacks before they reach users. Based on this idea, we aimed to implement a phishing detection system by using a Convolutional Neural Network with n-gram features that are extracted from URLs. There are different n-gram feature extraction techniques, and in this work, it is aimed to determine which of them is more effective for our proposals. As a second goal, it is aimed to discover what parameters of the n-gram work best. In experiments, it is discovered that unigram has the highest accuracy rate. It was observed that, instead of all the characters that are obtained in unigram, the specified 70 characters (regardless of case sensitivity) give the highest accuracy rate of 88.90% with a High-Risk URL dataset. Experimental results also showed that a URL can be classified (either as legitimate or phishing) in about 0.008 seconds. These metrics can be accepted at a very good rate both in accuracy and run-time efficiency.","PeriodicalId":270469,"journal":{"name":"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115426864","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 : 2021-06-11DOI: 10.1109/HORA52670.2021.9461393
Sezgin Yolcu, M. Akdağ
Fixed-wing vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV)s are designed to combine the advantages of multi-rotor UAVs and fixed-wing UAVs in different flight phases in a single UAV. Fixed-wing VTOL UAVs can achieve the mobility of multi-rotor UAVs in hovering, vertical take-off and landing flight phases. Since fixed-wing UAVs are known for their efficiency in power consumption, fixed-wing VTOL UAVs were created to efficiently perform the cruise phase of the flight for a similar reason. In this paper, we made the conceptual design of a fixed-wing VTOL UAV which is called “DOGA”. The mission of DOGA is to carry 0.5 kg. payload. Firstly, maximum take-off weight was calculated, and then the airfoil profile, wings geometry, and the propulsion systems were determined. Also, design and performance parameters of DOGA were calculated. As a result, conceptual design of DOGA was completed and all the needed parameters for the detail design of the fixed-wing VTOL UAV were derived.
{"title":"Conceptual Design of a Cargo UAV That Can Take-off and Land Vertically","authors":"Sezgin Yolcu, M. Akdağ","doi":"10.1109/HORA52670.2021.9461393","DOIUrl":"https://doi.org/10.1109/HORA52670.2021.9461393","url":null,"abstract":"Fixed-wing vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV)s are designed to combine the advantages of multi-rotor UAVs and fixed-wing UAVs in different flight phases in a single UAV. Fixed-wing VTOL UAVs can achieve the mobility of multi-rotor UAVs in hovering, vertical take-off and landing flight phases. Since fixed-wing UAVs are known for their efficiency in power consumption, fixed-wing VTOL UAVs were created to efficiently perform the cruise phase of the flight for a similar reason. In this paper, we made the conceptual design of a fixed-wing VTOL UAV which is called “DOGA”. The mission of DOGA is to carry 0.5 kg. payload. Firstly, maximum take-off weight was calculated, and then the airfoil profile, wings geometry, and the propulsion systems were determined. Also, design and performance parameters of DOGA were calculated. As a result, conceptual design of DOGA was completed and all the needed parameters for the detail design of the fixed-wing VTOL UAV were derived.","PeriodicalId":270469,"journal":{"name":"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115188570","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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