Pub Date : 2022-11-21DOI: 10.1109/CINTI-MACRo57952.2022.10029545
Andrea Pődör, Gergely Huszar
The study aims to support the idea that nonprofessional equipment can produce suitable images for detecting light pollution on a large scale. The authors in their study used a hobby UAV for producing the nighttime airborne image, and also measured brightness with SQM-L equipment in a pilot area in Budapest. In the study area, different lamp types were detected to produce light pollution to a different degree. Based on the field measurement we produced a graphical representation of the light pollution of the different lamp types. After processing the airborne images, we produced the brightness index map of the study area, which can be used to represent spatial variations in pollution. The results showed that when interpreting the results we should be careful, as certain phenomena are not related to light pollution.
{"title":"Detecting light pollution with UAV, a Hungarian case study","authors":"Andrea Pődör, Gergely Huszar","doi":"10.1109/CINTI-MACRo57952.2022.10029545","DOIUrl":"https://doi.org/10.1109/CINTI-MACRo57952.2022.10029545","url":null,"abstract":"The study aims to support the idea that nonprofessional equipment can produce suitable images for detecting light pollution on a large scale. The authors in their study used a hobby UAV for producing the nighttime airborne image, and also measured brightness with SQM-L equipment in a pilot area in Budapest. In the study area, different lamp types were detected to produce light pollution to a different degree. Based on the field measurement we produced a graphical representation of the light pollution of the different lamp types. After processing the airborne images, we produced the brightness index map of the study area, which can be used to represent spatial variations in pollution. The results showed that when interpreting the results we should be careful, as certain phenomena are not related to light pollution.","PeriodicalId":18535,"journal":{"name":"Micro","volume":"15 1","pages":"000197-000202"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88818682","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 : 2022-11-21DOI: 10.1109/CINTI-MACRo57952.2022.10029408
L. Horváth
This paper introduces concept and method of Integrated Autonomous Model System (IAMS) which is developed as organized content in dedicated collaborative virtual space (CVS).IAMS is a recent result and at the same time a possible answer to new requests by engineering related research. Development of IAMS in CVS uses capabilities offered by Modeling Sotware Platform (MSP). IAMS is devoted as model system which is capable of system, situation, behavior, and context representation. In its application proposed in this paper, IAMS is a purposeful experimental model serving research and represents results in applied informatics and applied mathematics in model environment suitable for development, validation, and experimental application of results. Research using IAMS is planned in the organization of a Virtual Research Laboratory (VRL). In this paper, first the relevant elements of recently modified concept of VRL are briefed to introduce contributions in this paper. Following this, IAMS is characterized as integrated media of research. Next, definition of global research organization in CVS using cloud organized services by research purpose configured MSP in the VRL is explained. Finally, PhD research program in functional organic shape modeling as means for the representation of living organizations in close connection with modeling of engineering shapes is introduced as example for key areas in future research at VRL.
{"title":"Integrated Autonomous Model System as Research Media","authors":"L. Horváth","doi":"10.1109/CINTI-MACRo57952.2022.10029408","DOIUrl":"https://doi.org/10.1109/CINTI-MACRo57952.2022.10029408","url":null,"abstract":"This paper introduces concept and method of Integrated Autonomous Model System (IAMS) which is developed as organized content in dedicated collaborative virtual space (CVS).IAMS is a recent result and at the same time a possible answer to new requests by engineering related research. Development of IAMS in CVS uses capabilities offered by Modeling Sotware Platform (MSP). IAMS is devoted as model system which is capable of system, situation, behavior, and context representation. In its application proposed in this paper, IAMS is a purposeful experimental model serving research and represents results in applied informatics and applied mathematics in model environment suitable for development, validation, and experimental application of results. Research using IAMS is planned in the organization of a Virtual Research Laboratory (VRL). In this paper, first the relevant elements of recently modified concept of VRL are briefed to introduce contributions in this paper. Following this, IAMS is characterized as integrated media of research. Next, definition of global research organization in CVS using cloud organized services by research purpose configured MSP in the VRL is explained. Finally, PhD research program in functional organic shape modeling as means for the representation of living organizations in close connection with modeling of engineering shapes is introduced as example for key areas in future research at VRL.","PeriodicalId":18535,"journal":{"name":"Micro","volume":"53 1","pages":"000125-000130"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90872134","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 : 2022-11-21DOI: 10.1109/CINTI-MACRo57952.2022.10029449
Miklós Vincze, M. Kucarov, Bence Biricz, Abdallah Benhamida, Melvin Ogbolu, M. Kozlovszky, V. Jonas, Róbert Paulik
Nowadays, the flow of information is paramount in order for everyone to have the knowledge they need to make decisions as soon as possible. It is no different in digital pathology either. There is still research and development today to make relevant medical information available to right holders as soon as possible. One possible direction of development is the use of real-time multi-user software. With these programs, users are able to collaborate in real time from around the world, set up a diagnosis together, and share it with others. By using this type of software, users can make decisions together by receiving the same data. These data can be, among other things, various measurement data, image data, morphological data. Implementing this software is difficult in several ways, such as processing huge amounts of data and ensuring smooth operation for multiple users. Some possible uses in the future include online medical training, preparation for and consultation on surgeries. In this paper, we present similar software solutions currently available on the market and under development, as well as our team’s solution to the problem described.
{"title":"Real-time multi-user 3D visualization software in medicine","authors":"Miklós Vincze, M. Kucarov, Bence Biricz, Abdallah Benhamida, Melvin Ogbolu, M. Kozlovszky, V. Jonas, Róbert Paulik","doi":"10.1109/CINTI-MACRo57952.2022.10029449","DOIUrl":"https://doi.org/10.1109/CINTI-MACRo57952.2022.10029449","url":null,"abstract":"Nowadays, the flow of information is paramount in order for everyone to have the knowledge they need to make decisions as soon as possible. It is no different in digital pathology either. There is still research and development today to make relevant medical information available to right holders as soon as possible. One possible direction of development is the use of real-time multi-user software. With these programs, users are able to collaborate in real time from around the world, set up a diagnosis together, and share it with others. By using this type of software, users can make decisions together by receiving the same data. These data can be, among other things, various measurement data, image data, morphological data. Implementing this software is difficult in several ways, such as processing huge amounts of data and ensuring smooth operation for multiple users. Some possible uses in the future include online medical training, preparation for and consultation on surgeries. In this paper, we present similar software solutions currently available on the market and under development, as well as our team’s solution to the problem described.","PeriodicalId":18535,"journal":{"name":"Micro","volume":"10 1","pages":"000045-000050"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77323640","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 : 2022-11-21DOI: 10.1109/CINTI-MACRo57952.2022.10029501
György Fekete, Habil. Andras Molnar
In this paper, we propose new patterns which combine attribute and time series data for classifications to soften or solve the overlapping classes problem. The solution was created for medical human gait analysis, where both types of input data are available.
{"title":"Scalar attributes and time series combining patterns for multivariate time series classification","authors":"György Fekete, Habil. Andras Molnar","doi":"10.1109/CINTI-MACRo57952.2022.10029501","DOIUrl":"https://doi.org/10.1109/CINTI-MACRo57952.2022.10029501","url":null,"abstract":"In this paper, we propose new patterns which combine attribute and time series data for classifications to soften or solve the overlapping classes problem. The solution was created for medical human gait analysis, where both types of input data are available.","PeriodicalId":18535,"journal":{"name":"Micro","volume":"55 1","pages":"000335-000340"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83839766","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 : 2022-11-21DOI: 10.1109/CINTI-MACRo57952.2022.10029557
A. Lantzky, D. Joo
In this study, the measurement accuracy of the Optitrack Mocap system biomechanical test models was tested. For testing, several marker arrays were used: These were the factory installed Baseline, Rizzoli and Helen Hayes. The results obtained were statistically compared. Our aim was to find similarities and differences between the different models.
{"title":"Bodymodel testing for biomechanical motion studies - Pilot Study","authors":"A. Lantzky, D. Joo","doi":"10.1109/CINTI-MACRo57952.2022.10029557","DOIUrl":"https://doi.org/10.1109/CINTI-MACRo57952.2022.10029557","url":null,"abstract":"In this study, the measurement accuracy of the Optitrack Mocap system biomechanical test models was tested. For testing, several marker arrays were used: These were the factory installed Baseline, Rizzoli and Helen Hayes. The results obtained were statistically compared. Our aim was to find similarities and differences between the different models.","PeriodicalId":18535,"journal":{"name":"Micro","volume":"40 1","pages":"000319-000324"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89116352","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 : 2022-11-21DOI: 10.1109/CINTI-MACRo57952.2022.10029560
A. Widner, Balázs Varga, Daniel Medgyesi, T. Tettamanti
Vehicle dynamics simulation is widely used in the automotive industry. The usability of each model depends on how well it can replicate the behaviour of the real vehicle. Each simulation model must go through a thorough investigation process- model validation- before use. Accordingly, the research introduces a comprehensive methodological framework for vehicle dynamics model validation using a sophisticated vehicle dynamics measurement system and a machine learning algorithm. The validation process of a two-wheel vehicle model (bicycle model) is presented where the authors’ previously proposed work is exploited as a base and further developed, i.e. by using a Genetic Algorithm (GA) the vehicle parameters (yaw inertia, axle cornering stiffness) are estimated in an automatized fashion.
{"title":"Validation of a two-wheel vehicle model using Genetic Algorithm","authors":"A. Widner, Balázs Varga, Daniel Medgyesi, T. Tettamanti","doi":"10.1109/CINTI-MACRo57952.2022.10029560","DOIUrl":"https://doi.org/10.1109/CINTI-MACRo57952.2022.10029560","url":null,"abstract":"Vehicle dynamics simulation is widely used in the automotive industry. The usability of each model depends on how well it can replicate the behaviour of the real vehicle. Each simulation model must go through a thorough investigation process- model validation- before use. Accordingly, the research introduces a comprehensive methodological framework for vehicle dynamics model validation using a sophisticated vehicle dynamics measurement system and a machine learning algorithm. The validation process of a two-wheel vehicle model (bicycle model) is presented where the authors’ previously proposed work is exploited as a base and further developed, i.e. by using a Genetic Algorithm (GA) the vehicle parameters (yaw inertia, axle cornering stiffness) are estimated in an automatized fashion.","PeriodicalId":18535,"journal":{"name":"Micro","volume":"10 1","pages":"000405-000410"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81272731","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 : 2022-11-21DOI: 10.1109/cinti-macro57952.2022.10029607
A. DeGaetano
Mathematical models of the cardiovascular system and of cerebral autoregulation (CAR) have been employed for several years in order to describe the time course of pressures and flows changes subsequent to postural changes. The assessment of the degree of efficiency of cerebral auto regulation has indeed importance in the prognosis of such conditions as cerebro-vascular accidents or Alzheimer. In the quest for a simple but realistic mathematical description of cardiovascular control, which may be fitted onto non-invasive experimental observations after postural changes, the present work proposes a first version of an empirical Stochastic Delay Differential Equations (SDDEs) model. The model consists of a total of four SDDEs and two ancillary algebraic equations, incorporates four distinct delayed controls from the brain onto different components of the circulation, and is able to accurately capture the time course of mean arterial pressure and cerebral blood flow velocity signals, reproducing observed auto-correlated error around the expected drift.
{"title":"Modeling Cerebro-Vascular Autoregulation after Postural Change Perturbations : Plenary Talk","authors":"A. DeGaetano","doi":"10.1109/cinti-macro57952.2022.10029607","DOIUrl":"https://doi.org/10.1109/cinti-macro57952.2022.10029607","url":null,"abstract":"Mathematical models of the cardiovascular system and of cerebral autoregulation (CAR) have been employed for several years in order to describe the time course of pressures and flows changes subsequent to postural changes. The assessment of the degree of efficiency of cerebral auto regulation has indeed importance in the prognosis of such conditions as cerebro-vascular accidents or Alzheimer. In the quest for a simple but realistic mathematical description of cardiovascular control, which may be fitted onto non-invasive experimental observations after postural changes, the present work proposes a first version of an empirical Stochastic Delay Differential Equations (SDDEs) model. The model consists of a total of four SDDEs and two ancillary algebraic equations, incorporates four distinct delayed controls from the brain onto different components of the circulation, and is able to accurately capture the time course of mean arterial pressure and cerebral blood flow velocity signals, reproducing observed auto-correlated error around the expected drift.","PeriodicalId":18535,"journal":{"name":"Micro","volume":"22 1","pages":"000177-000178"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90679730","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 : 2022-11-21DOI: 10.1109/CINTI-MACRo57952.2022.10029506
Anastasia Yashchenko, Ilya Makarov
In this paper, we focus on the problem of automatic analysis of literature via its characters’ interaction networks. We demonstrate the ability of the well-known knowledge retrieval algorithms on the text series of books by John Ronald Reuel Tolkien about Middle-earth. We study the identified relationships of characters, visualizing the results using the network science approaches via introducing the general pipeline for named entities recognition, relation retrieval, and analysis of their clustering via racial division by using the Adjusted Rand Index.
{"title":"Knowledge Retrieval and Relation Mining from Tolkien’s History of Middle Earth","authors":"Anastasia Yashchenko, Ilya Makarov","doi":"10.1109/CINTI-MACRo57952.2022.10029506","DOIUrl":"https://doi.org/10.1109/CINTI-MACRo57952.2022.10029506","url":null,"abstract":"In this paper, we focus on the problem of automatic analysis of literature via its characters’ interaction networks. We demonstrate the ability of the well-known knowledge retrieval algorithms on the text series of books by John Ronald Reuel Tolkien about Middle-earth. We study the identified relationships of characters, visualizing the results using the network science approaches via introducing the general pipeline for named entities recognition, relation retrieval, and analysis of their clustering via racial division by using the Adjusted Rand Index.","PeriodicalId":18535,"journal":{"name":"Micro","volume":"48 1","pages":"000257-000264"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88353760","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 : 2022-11-21DOI: 10.1109/CINTI-MACRo57952.2022.10029511
A. Gergely, R. Farmos, J. Kántor, Andrea Eva Kantor, Norbert Hodagyi
This work aims to investigate the air filtration performance of nanofiber mats generated from recycled PET water bottle by the electrospinning fiber production method. The trifluoroacetic acid amount was minimized to prepare the PET solution that can be used in a stable electrospinning process. The electrospinning parameters were optimized and bead free PET fiber mat was produced with an average fiber diameter of 593 ± 182 nm and average thickness of 208 ± 41 $mu$m. A pneumatic test circuit was developed to test the filtration performance. The recycled PET fiber mats were able to effectively filter out the visible particles from cigarette smoke, however, was unable to filter out the molecules responsible for the smell.
{"title":"Recycled PET nanofiber membranes for air filtration","authors":"A. Gergely, R. Farmos, J. Kántor, Andrea Eva Kantor, Norbert Hodagyi","doi":"10.1109/CINTI-MACRo57952.2022.10029511","DOIUrl":"https://doi.org/10.1109/CINTI-MACRo57952.2022.10029511","url":null,"abstract":"This work aims to investigate the air filtration performance of nanofiber mats generated from recycled PET water bottle by the electrospinning fiber production method. The trifluoroacetic acid amount was minimized to prepare the PET solution that can be used in a stable electrospinning process. The electrospinning parameters were optimized and bead free PET fiber mat was produced with an average fiber diameter of 593 ± 182 nm and average thickness of 208 ± 41 $mu$m. A pneumatic test circuit was developed to test the filtration performance. The recycled PET fiber mats were able to effectively filter out the visible particles from cigarette smoke, however, was unable to filter out the molecules responsible for the smell.","PeriodicalId":18535,"journal":{"name":"Micro","volume":"15 1","pages":"000057-000062"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78463796","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 : 2022-11-21DOI: 10.1109/CINTI-MACRo57952.2022.10029519
Peter Sarcevic, J. Sárosi, Dominik Csík, Á. Odry
In this paper, a novel feature aggregation method is proposed for dimension reduction in inertial sensor-based pattern recognition applications. The method is utilized in a movement classification algorithm, which applies measurements of wearable sensor units attached to the wrists of the subjects. The feature aggregation is realized separately for each feature type by using a linear combination of the feature values extracted for each sensor axis. The weights are computed using genetic algorithm-based optimization, which uses the classification efficiency provided by the k-nearest neighbor (kNN) method to compute the fitness value. After the weights are determined for all feature types and the aggregated inputs are computed for both the training and validation data, a multi-layer perceptron (MLP) classifier is trained, which can be used during real-time classification. The algorithm was tested with multiple datasets based on features extracted using different processing window sizes and used sensor combinations. The achieved results show that the proposed weighted aggregation provides significantly, mostly 5-6%, higher recognition rates on validation data than when equal coefficients are utilized during aggregation. The method in the case of some datasets with the same configuration gives even higher classification efficiencies than when using the features extracted for the sensor axes separately.
{"title":"Inertial sensor-based movement classification with dimension reduction based on feature aggregation","authors":"Peter Sarcevic, J. Sárosi, Dominik Csík, Á. Odry","doi":"10.1109/CINTI-MACRo57952.2022.10029519","DOIUrl":"https://doi.org/10.1109/CINTI-MACRo57952.2022.10029519","url":null,"abstract":"In this paper, a novel feature aggregation method is proposed for dimension reduction in inertial sensor-based pattern recognition applications. The method is utilized in a movement classification algorithm, which applies measurements of wearable sensor units attached to the wrists of the subjects. The feature aggregation is realized separately for each feature type by using a linear combination of the feature values extracted for each sensor axis. The weights are computed using genetic algorithm-based optimization, which uses the classification efficiency provided by the k-nearest neighbor (kNN) method to compute the fitness value. After the weights are determined for all feature types and the aggregated inputs are computed for both the training and validation data, a multi-layer perceptron (MLP) classifier is trained, which can be used during real-time classification. The algorithm was tested with multiple datasets based on features extracted using different processing window sizes and used sensor combinations. The achieved results show that the proposed weighted aggregation provides significantly, mostly 5-6%, higher recognition rates on validation data than when equal coefficients are utilized during aggregation. The method in the case of some datasets with the same configuration gives even higher classification efficiencies than when using the features extracted for the sensor axes separately.","PeriodicalId":18535,"journal":{"name":"Micro","volume":"333 1","pages":"000113-000118"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82941098","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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