Pub Date : 2020-06-01DOI: 10.1109/HORA49412.2020.9152837
M. Mikhov, M. Zhilevski
The main features of the tool magazine drive in a type of vertical machining centers with computer numerical control are analyzed. On this basis, an algorithm for optimal tool position searching has been presented. A control device using Verilog hardware description language has been developed. The approach offered achieves autonomous control of this drive and reduces the requirements to the respective CNC system. Experimental results of the synthesized control device and practical applications of the implemented tool magazine drive are presented and discussed. This research and the results obtained can be used in modernization of the considered machine tools.
{"title":"Control Device for Tool Magazine Drives of Vertical Machining Centers with CNC","authors":"M. Mikhov, M. Zhilevski","doi":"10.1109/HORA49412.2020.9152837","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152837","url":null,"abstract":"The main features of the tool magazine drive in a type of vertical machining centers with computer numerical control are analyzed. On this basis, an algorithm for optimal tool position searching has been presented. A control device using Verilog hardware description language has been developed. The approach offered achieves autonomous control of this drive and reduces the requirements to the respective CNC system. Experimental results of the synthesized control device and practical applications of the implemented tool magazine drive are presented and discussed. This research and the results obtained can be used in modernization of the considered machine tools.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","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":"128297793","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/HORA49412.2020.9152866
Mihriban Günay, Murat Köseoğlu, Özal Yıldırım
In this paper, the Convolutional Neural Network (CNN) architecture, which is one of the deep learning architectures, is used to classify the basic circuit components drawn by hand. During the training and testing stages of the model, a new dataset containing images of 863 circuit components manually drawn by different people is created. The data set contains images of four different classes of circuit components such as resistor, inductor, capacitor and voltage source. All images have been fixed to the same size and converted to grayscale to increase recognition performance and reduce process complexity. In the study, training for four classes is performed with CNN architecture. Based on the CNN architecture, four new CNN models are employed with different the number of layers. The training and validation results of these models are compared separately, the model with the highest training and validation performance is observed with four layer CNN model (CNN-4). This model obtained 84.41% accuracy rate at classification task.
{"title":"Classification of Hand-Drawn Basic Circuit Components Using Convolutional Neural Networks","authors":"Mihriban Günay, Murat Köseoğlu, Özal Yıldırım","doi":"10.1109/HORA49412.2020.9152866","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152866","url":null,"abstract":"In this paper, the Convolutional Neural Network (CNN) architecture, which is one of the deep learning architectures, is used to classify the basic circuit components drawn by hand. During the training and testing stages of the model, a new dataset containing images of 863 circuit components manually drawn by different people is created. The data set contains images of four different classes of circuit components such as resistor, inductor, capacitor and voltage source. All images have been fixed to the same size and converted to grayscale to increase recognition performance and reduce process complexity. In the study, training for four classes is performed with CNN architecture. Based on the CNN architecture, four new CNN models are employed with different the number of layers. The training and validation results of these models are compared separately, the model with the highest training and validation performance is observed with four layer CNN model (CNN-4). This model obtained 84.41% accuracy rate at classification task.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","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":"130589146","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/HORA49412.2020.9152861
Levent Türkler, L. Akkan, T. Akkan
In this study, Swarm robots, collective task behaviors, and communication models for motion integrity are examined. Collective Motion, which is one of the taxonomies of Swarm robots, has been defined to be suitable for Swarm robotics, one of the optimization methods based on genetic algorithm, to ensure its behavior. Among these optimization methods, Particle Swarm Optimization is discussed and the difficulties and problems arising from the equation and communication are discussed during the movements of the Swarm robots by moving from the basic equation. In addition, solutions of these problems were studied. And also, in the communication systems that will control the movements of the Swarm robots, a discussion has been made on the communication model that will contribute to the Swarm robotics in the literature. As a result of this study, in order to provide the collective movements of swarm robotics and to create more efficient communication, robots are divided into groups and the Swarm is modeled according to this modeling.
{"title":"Particle Swarm Optimization in Swarm Robotics","authors":"Levent Türkler, L. Akkan, T. Akkan","doi":"10.1109/HORA49412.2020.9152861","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152861","url":null,"abstract":"In this study, Swarm robots, collective task behaviors, and communication models for motion integrity are examined. Collective Motion, which is one of the taxonomies of Swarm robots, has been defined to be suitable for Swarm robotics, one of the optimization methods based on genetic algorithm, to ensure its behavior. Among these optimization methods, Particle Swarm Optimization is discussed and the difficulties and problems arising from the equation and communication are discussed during the movements of the Swarm robots by moving from the basic equation. In addition, solutions of these problems were studied. And also, in the communication systems that will control the movements of the Swarm robots, a discussion has been made on the communication model that will contribute to the Swarm robotics in the literature. As a result of this study, in order to provide the collective movements of swarm robotics and to create more efficient communication, robots are divided into groups and the Swarm is modeled according to this modeling.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"5 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":"131208035","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/HORA49412.2020.9152870
Mohammed Jasim A. Alkhafaji, Abbas Fadhil Aljuboori, A. Ibrahim
The enormous data provided by the health care environment needs many important and powerful tools for analyzing and extracting data and accessing useful knowledge. Many researchers have been interested in applying many statistical tools as well as many different data mining tools in order to improve an analysis process and extract data from a different data set. The only thing that proves the success and robustness of data mining tool is accurate diagnosis of the disease. According to the (WHO), the biggest cause of death in the last ten years or so in this vast world is heart disease. The statistical exploration tools that researchers use are tools that help decision-makers in health care to predict and diagnose heart disease. The tools used in the diagnostic process for heart disease have been thoroughly tested in order to demonstrate sufficient and acceptable accuracy. A set of patient data divided into 665 records was used, of which 300 were for males, with 365 for females, with 10 different related characteristics. The decision-making department still suffers from a lack of performance and decision-making. Our paper aims to process data in different ways before the process of accessing knowledge to make the appropriate decision through expectations of classification analysis and then using techniques to extract data with acceptable accuracy. Our goal proposed in this paper is to purify the data before the disease prediction process to get the best possible prediction and compare the results with the results of a group of previous researchers to reach an accurate diagnosis and prediction. The second part of our goal is to compare between different technologies on different data sets such as decision tree technology and the second technique is Bayesian classification technology and the last technology is neural networks and the results were (98.85%, 98.16%, 91.31%), respectively. In the end, we hope to obtain acceptable results with high accuracy in the future, enhance clinical diagnosis, and promote appropriate decision-making for early treatment specialists.
{"title":"Clean medical data and predict heart disease","authors":"Mohammed Jasim A. Alkhafaji, Abbas Fadhil Aljuboori, A. Ibrahim","doi":"10.1109/HORA49412.2020.9152870","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152870","url":null,"abstract":"The enormous data provided by the health care environment needs many important and powerful tools for analyzing and extracting data and accessing useful knowledge. Many researchers have been interested in applying many statistical tools as well as many different data mining tools in order to improve an analysis process and extract data from a different data set. The only thing that proves the success and robustness of data mining tool is accurate diagnosis of the disease. According to the (WHO), the biggest cause of death in the last ten years or so in this vast world is heart disease. The statistical exploration tools that researchers use are tools that help decision-makers in health care to predict and diagnose heart disease. The tools used in the diagnostic process for heart disease have been thoroughly tested in order to demonstrate sufficient and acceptable accuracy. A set of patient data divided into 665 records was used, of which 300 were for males, with 365 for females, with 10 different related characteristics. The decision-making department still suffers from a lack of performance and decision-making. Our paper aims to process data in different ways before the process of accessing knowledge to make the appropriate decision through expectations of classification analysis and then using techniques to extract data with acceptable accuracy. Our goal proposed in this paper is to purify the data before the disease prediction process to get the best possible prediction and compare the results with the results of a group of previous researchers to reach an accurate diagnosis and prediction. The second part of our goal is to compare between different technologies on different data sets such as decision tree technology and the second technique is Bayesian classification technology and the last technology is neural networks and the results were (98.85%, 98.16%, 91.31%), respectively. In the end, we hope to obtain acceptable results with high accuracy in the future, enhance clinical diagnosis, and promote appropriate decision-making for early treatment specialists.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"93 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":"134270533","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/HORA49412.2020.9152871
Cynthia Brosque, Gunnar Skeie, Joakim Örn, J. Jacobson, T. Lau, M. Fischer
As robotic construction methods start being adopted on sites, construction managers should be able to answer how robots will impact safety, quality, schedule, and cost on a given project compared to traditional, manual methods. This study developed three comparative cases evaluating a drilling robot, a drywall robot, and a layout robot against traditional construction methods. We established an initial feasibility check that evaluates the lit between product, organization, and process variables, and then measures the robot’s impact on safety, quality, schedule, and cost. This study also outlines common implementation challenges to become aware of the effort faced to harness the robots’ benefits and provides strategies to mitigate these challenges. Finally, we recommend that a framework for analysis be formalized on the basis of the analysis method and the comparison variables presented in the paper.
{"title":"Comparison of Construction Robots and Traditional Methods for Drilling, Drywall, and Layout Tasks","authors":"Cynthia Brosque, Gunnar Skeie, Joakim Örn, J. Jacobson, T. Lau, M. Fischer","doi":"10.1109/HORA49412.2020.9152871","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152871","url":null,"abstract":"As robotic construction methods start being adopted on sites, construction managers should be able to answer how robots will impact safety, quality, schedule, and cost on a given project compared to traditional, manual methods. This study developed three comparative cases evaluating a drilling robot, a drywall robot, and a layout robot against traditional construction methods. We established an initial feasibility check that evaluates the lit between product, organization, and process variables, and then measures the robot’s impact on safety, quality, schedule, and cost. This study also outlines common implementation challenges to become aware of the effort faced to harness the robots’ benefits and provides strategies to mitigate these challenges. Finally, we recommend that a framework for analysis be formalized on the basis of the analysis method and the comparison variables presented in the paper.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"344 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":"132715147","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/HORA49412.2020.9152901
S. Mousavi, fatemeh moradianpour, Fatemeh Heidari, S. Yasoubi, Seyed Ehsan Tahami, Mahdi Azarnoush
With the industrialization of societies, the number of disabilities is increasing, and one of these disabilities can occur and severely affect the lives of individuals and society. There are several ways to control an artificial prosthesis, one of which is to use an electromyography signal. For this purpose, we use the dataset set available at the UCI database, which has 6 different hand movements in the form of free access. In this study, each signal is first decomposed into intrinsic mode, and each signal is converted to 8 IMF, and then, using high-order spectrum to show the changes. The results show that from the third IMF onwards, HOS patterns are repeated. The first and second IMFs are used as an input signal to artificial prosthesis and the feature of kurtosis, skewness and variance are extracted. The results have shown the accuracy of classification with the first IMF and SVM classifier is 98.26%.
{"title":"Hand Movement detection Using Empirical Mode Decomposition And Higher Order Spectra","authors":"S. Mousavi, fatemeh moradianpour, Fatemeh Heidari, S. Yasoubi, Seyed Ehsan Tahami, Mahdi Azarnoush","doi":"10.1109/HORA49412.2020.9152901","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152901","url":null,"abstract":"With the industrialization of societies, the number of disabilities is increasing, and one of these disabilities can occur and severely affect the lives of individuals and society. There are several ways to control an artificial prosthesis, one of which is to use an electromyography signal. For this purpose, we use the dataset set available at the UCI database, which has 6 different hand movements in the form of free access. In this study, each signal is first decomposed into intrinsic mode, and each signal is converted to 8 IMF, and then, using high-order spectrum to show the changes. The results show that from the third IMF onwards, HOS patterns are repeated. The first and second IMFs are used as an input signal to artificial prosthesis and the feature of kurtosis, skewness and variance are extracted. The results have shown the accuracy of classification with the first IMF and SVM classifier is 98.26%.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"329 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113998472","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/hora49412.2020.9152935
{"title":"HORA 2020 Author Index","authors":"","doi":"10.1109/hora49412.2020.9152935","DOIUrl":"https://doi.org/10.1109/hora49412.2020.9152935","url":null,"abstract":"","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"27 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":"131930179","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/hora49412.2020.9152895
{"title":"HORA 2020 Cover Page","authors":"","doi":"10.1109/hora49412.2020.9152895","DOIUrl":"https://doi.org/10.1109/hora49412.2020.9152895","url":null,"abstract":"","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"59 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":"133380549","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/HORA49412.2020.9152932
Farzana Anowar, Mohsena Ashraf, Ashraful Islam, Eshtiak Ahmed, A. I. Chowdhury
Proper and sufficient health-care services have always been of great importance to the society and its’ people. There are some common health issues that are frequently faced by people which can be taken care of by introducing innovative healthcare and monitoring systems. Diabetes is one of these issues as recent studies state that a total number of 387 million people all over the world are suffering from it. This number is even more alarming in the developing countries as there are approximately 7 million people suffering from diabetes on an average in each developing country. In this prospect, Information and Communication Technology (ICT) can provide a monitoring system with the help of interactive smart applications such as smart phone applications (apps) which provides the users with real time monitoring, suggestions and also, provides statistical report to indicate progress of healthcare. There are a significant number of smartphone applications in various operating systems (OSs) such as Android, iOS, Blackberry, Windows etc. that provide previously stated features. However, due to the widespread use in the developing countries and abundance of free applications of Android OS, this study only reviews Android based apps. By analyzing the features and usefulness of these apps, 54 apps have been identified with satisfactory level of functionality. In our study, we compare these apps to analyze the provided features and the feasibility of these apps for becoming a robust interactive system for continuous monitoring and support for people with diabetes. This study could lead to the development of a complete monitoring system and would take the health-care system to a whole new level for the developing countries.
{"title":"A Review on Diabetes Self-management Applications for Android Smartphones: Perspective of Developing Countries","authors":"Farzana Anowar, Mohsena Ashraf, Ashraful Islam, Eshtiak Ahmed, A. I. Chowdhury","doi":"10.1109/HORA49412.2020.9152932","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152932","url":null,"abstract":"Proper and sufficient health-care services have always been of great importance to the society and its’ people. There are some common health issues that are frequently faced by people which can be taken care of by introducing innovative healthcare and monitoring systems. Diabetes is one of these issues as recent studies state that a total number of 387 million people all over the world are suffering from it. This number is even more alarming in the developing countries as there are approximately 7 million people suffering from diabetes on an average in each developing country. In this prospect, Information and Communication Technology (ICT) can provide a monitoring system with the help of interactive smart applications such as smart phone applications (apps) which provides the users with real time monitoring, suggestions and also, provides statistical report to indicate progress of healthcare. There are a significant number of smartphone applications in various operating systems (OSs) such as Android, iOS, Blackberry, Windows etc. that provide previously stated features. However, due to the widespread use in the developing countries and abundance of free applications of Android OS, this study only reviews Android based apps. By analyzing the features and usefulness of these apps, 54 apps have been identified with satisfactory level of functionality. In our study, we compare these apps to analyze the provided features and the feasibility of these apps for becoming a robust interactive system for continuous monitoring and support for people with diabetes. This study could lead to the development of a complete monitoring system and would take the health-care system to a whole new level for the developing countries.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","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":"129355649","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/HORA49412.2020.9152842
M.R Naqvi, M. Arfan Jaffar, Muhammad Aslam, S. Shahzad, Muhammad Waseem Iqbal, A. Farooq
The rapidly increasing adaptation of Big data technologies in biomedicine, has introduced a revolution in and medical research practice. Trending high-throughput data analysis techniques, have converted the appearance of the biological system to acquire idolization methods for complicated diseases. Majority of the acquired Big-data models govern the materialization of illustrating medicine. This transformation aims at quantification of the period of P4 medicine that will then progressively be more predictive, personalized, pre-emptive, and participatory. It layouts a track to modernize antiseptic methods for the patient’s concern center. P4 medicine besides being a scientific face of systems medicine has two highlighted purposes first of which is to evaluate wellness, while the other is, to identify and expose disease. Patients are major operators in the cognizance of P4 medicine as they directly get engaged with a medically familiar network that helps them boost their health. This article will discuss the maturity in big data planning and correlated challenges in biomedicine.
{"title":"Importance of Big Data in Precision and Personalized Medicine","authors":"M.R Naqvi, M. Arfan Jaffar, Muhammad Aslam, S. Shahzad, Muhammad Waseem Iqbal, A. Farooq","doi":"10.1109/HORA49412.2020.9152842","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152842","url":null,"abstract":"The rapidly increasing adaptation of Big data technologies in biomedicine, has introduced a revolution in and medical research practice. Trending high-throughput data analysis techniques, have converted the appearance of the biological system to acquire idolization methods for complicated diseases. Majority of the acquired Big-data models govern the materialization of illustrating medicine. This transformation aims at quantification of the period of P4 medicine that will then progressively be more predictive, personalized, pre-emptive, and participatory. It layouts a track to modernize antiseptic methods for the patient’s concern center. P4 medicine besides being a scientific face of systems medicine has two highlighted purposes first of which is to evaluate wellness, while the other is, to identify and expose disease. Patients are major operators in the cognizance of P4 medicine as they directly get engaged with a medically familiar network that helps them boost their health. This article will discuss the maturity in big data planning and correlated challenges in biomedicine.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123566948","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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