Pub Date : 2023-05-23DOI: 10.1109/SACI58269.2023.10158571
Csilla Mizser
Local regulations provide a number of opportunities for intervention to create an adaptable, resilient settlement. It is proposed to create a separate environmental (or more narrowly: climate protection) regulation, the elements of which could include a reduction in the business tax on companies that use renewable energy or build green roofs, while increasing the tax on companies that leave their car parks without trees planted and maintained in suitable conditions; the co-operation between the maintainer of green areas and the operators of public utilities should be extended and deepened, it should be regulated that not only the road operator but also the green area maintenance department should be notified in advance and at the same time when utilities perform maintenance or renovation on underground cables, or horticultural supervision in the event of such interventions. Green city regulation can be defining afforestation and greening requirements in traditionally built streets; setting strict replacement requirements for any felling and the procedure for financing actions formulated within the framework of other measures, the establishment of a climate protection fund. The present paper is an empirical study looking for the answer to how much the local population percieves the city as green and why.
{"title":"Green City as a Development Issue–Based on an Empirical Survey of Budaörs","authors":"Csilla Mizser","doi":"10.1109/SACI58269.2023.10158571","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158571","url":null,"abstract":"Local regulations provide a number of opportunities for intervention to create an adaptable, resilient settlement. It is proposed to create a separate environmental (or more narrowly: climate protection) regulation, the elements of which could include a reduction in the business tax on companies that use renewable energy or build green roofs, while increasing the tax on companies that leave their car parks without trees planted and maintained in suitable conditions; the co-operation between the maintainer of green areas and the operators of public utilities should be extended and deepened, it should be regulated that not only the road operator but also the green area maintenance department should be notified in advance and at the same time when utilities perform maintenance or renovation on underground cables, or horticultural supervision in the event of such interventions. Green city regulation can be defining afforestation and greening requirements in traditionally built streets; setting strict replacement requirements for any felling and the procedure for financing actions formulated within the framework of other measures, the establishment of a climate protection fund. The present paper is an empirical study looking for the answer to how much the local population percieves the city as green and why.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132453535","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158607
J. Tasic, M. Takács, L. Kovács
In this paper, we estimate hemoglobin A1c based on measured average glucose by applying a kinetic mathematical model. We use a training dataset of 226 patients with type 1 diabetes to analyze their daily continuous glucose monitoring profiles and hemoglobin A1c values measured every 13 weeks. We review the irreversible and reversible mathematical models that describe the kinetics of hemoglobin A1c formation. To estimate the mean age of red blood cells, we used a method based on the gamma distribution. Estimation of hemoglobin A1c was performed by using the proposed rate equations for the chemical reactions between glucose levels and changes in the concentration of hemoglobin A0, aldimine intermediate and glycosylated hemoglobin. We compare measured and estimated hemoglobin A1c values to cA1culate their standard deviation. The application of the kinetic mathematical model leads to a small standard deviation between the estimated and measured hemoglobin A1c values.
{"title":"A Kinetic Model-Based Approach for Estimating Hemoglobin A1c Based on Average Glucose","authors":"J. Tasic, M. Takács, L. Kovács","doi":"10.1109/SACI58269.2023.10158607","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158607","url":null,"abstract":"In this paper, we estimate hemoglobin A1c based on measured average glucose by applying a kinetic mathematical model. We use a training dataset of 226 patients with type 1 diabetes to analyze their daily continuous glucose monitoring profiles and hemoglobin A1c values measured every 13 weeks. We review the irreversible and reversible mathematical models that describe the kinetics of hemoglobin A1c formation. To estimate the mean age of red blood cells, we used a method based on the gamma distribution. Estimation of hemoglobin A1c was performed by using the proposed rate equations for the chemical reactions between glucose levels and changes in the concentration of hemoglobin A0, aldimine intermediate and glycosylated hemoglobin. We compare measured and estimated hemoglobin A1c values to cA1culate their standard deviation. The application of the kinetic mathematical model leads to a small standard deviation between the estimated and measured hemoglobin A1c values.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122202975","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158627
Ibrahim. A. M. Ahmed, L. Mihet-Popa
Balancing the power flow in a three-phase system is one of the challenges in distribution networks, which is even more exacerbated with the widespread adoption of renewable energy sources (RES) and the development of smart grids. The transformer is one of the fundamental devices in power distribution that provides a means to link high-voltage, medium-voltage, and low-voltage networks in addition to galvanic isolation. Classical transformers utilize magnetic coupling with a turn ratio between coils to achieve this basic functionality, but they are bulky, expensive, and do not provide additional smart features. The use of a power electronics transformer (PET), also called a solid-state transformer (SST), has been introduced in the literature using a three-phase to single-phase converter to solve this problem. However, the focus was mainly on the inverter and a basic diode rectifier was used without RES integration. This paper bridged this gap by replacing it with a bidirectional converter and investigating its performance using solar power connected to the DC-link of the three-phase to single-phase solid-state transformer. The bidirectional SST was verified using simulations and the results show that the SST is able to maintain the balance between the three-phase system and the integrated renewable sources while providing bidirectional power flow with high efficiency and low Total Harmonic Distortion.
{"title":"Model Predictive Control of a Packed-U-cells Inverter with PV, Boost and Bidirectional Rectifier for Solid-State Transformers","authors":"Ibrahim. A. M. Ahmed, L. Mihet-Popa","doi":"10.1109/SACI58269.2023.10158627","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158627","url":null,"abstract":"Balancing the power flow in a three-phase system is one of the challenges in distribution networks, which is even more exacerbated with the widespread adoption of renewable energy sources (RES) and the development of smart grids. The transformer is one of the fundamental devices in power distribution that provides a means to link high-voltage, medium-voltage, and low-voltage networks in addition to galvanic isolation. Classical transformers utilize magnetic coupling with a turn ratio between coils to achieve this basic functionality, but they are bulky, expensive, and do not provide additional smart features. The use of a power electronics transformer (PET), also called a solid-state transformer (SST), has been introduced in the literature using a three-phase to single-phase converter to solve this problem. However, the focus was mainly on the inverter and a basic diode rectifier was used without RES integration. This paper bridged this gap by replacing it with a bidirectional converter and investigating its performance using solar power connected to the DC-link of the three-phase to single-phase solid-state transformer. The bidirectional SST was verified using simulations and the results show that the SST is able to maintain the balance between the three-phase system and the integrated renewable sources while providing bidirectional power flow with high efficiency and low Total Harmonic Distortion.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"369 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115986770","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158585
Mehran Amini, Miklós F. Hatwágner, L. Kóczy
The infrequent emergence of traffic congestion on freeways can result in the decline of the transportation system over time. Without the implementation of appropriate countermeasures, congestion can escalate, leading to unfavorable impacts on other aspects of the traffic network. As a result, there is a greater need for reliable and optimal traffic control. The goal of this research is to manage the number of vehicles entering the main freeway from the ramp merging area, in order to balance the demand and capacity to satisfy the maximum utilization of the freeway capacity. Despite extensive research into different ramp metering techniques, this study aims to utilize the fuzzy cognitive map as a macroscopic traffic flow model in conjunction with the Q-learning algorithm. This combination prevents freeway congestion and maintains optimal performance by keeping freeway density below a key threshold. The inherent uncertainty of traffic conditions is addressed through the application of reinforcement learning, which is constructed on the principles of the Markov decision process. This approach represents an exploration-exploitation trade-off, as implemented through the Q-learning algorithm. The proposed technique was evaluated for its efficacy in the regulation of freeway ramp metering in both controlled and uncontrolled simulations. The findings demonstrate a significant improvement in the control of the mainstream traffic flow.
{"title":"Machine learning and fuzzy cognitive maps in a hybrid approach toward freeway on-ramp traffic control","authors":"Mehran Amini, Miklós F. Hatwágner, L. Kóczy","doi":"10.1109/SACI58269.2023.10158585","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158585","url":null,"abstract":"The infrequent emergence of traffic congestion on freeways can result in the decline of the transportation system over time. Without the implementation of appropriate countermeasures, congestion can escalate, leading to unfavorable impacts on other aspects of the traffic network. As a result, there is a greater need for reliable and optimal traffic control. The goal of this research is to manage the number of vehicles entering the main freeway from the ramp merging area, in order to balance the demand and capacity to satisfy the maximum utilization of the freeway capacity. Despite extensive research into different ramp metering techniques, this study aims to utilize the fuzzy cognitive map as a macroscopic traffic flow model in conjunction with the Q-learning algorithm. This combination prevents freeway congestion and maintains optimal performance by keeping freeway density below a key threshold. The inherent uncertainty of traffic conditions is addressed through the application of reinforcement learning, which is constructed on the principles of the Markov decision process. This approach represents an exploration-exploitation trade-off, as implemented through the Q-learning algorithm. The proposed technique was evaluated for its efficacy in the regulation of freeway ramp metering in both controlled and uncontrolled simulations. The findings demonstrate a significant improvement in the control of the mainstream traffic flow.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116168301","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158569
Tamás Dániel Szücs, Melánia Puskás, D. Drexler, L. Kovács
Nowadays clinical therapies in chemotherapy sessions are generalized for patients, therefore we are working to provide a personalized drug plan to help reduce the drug dosage, causing the reduction of side effects and costs. Also, one benefit of this method is to prevent drug resistance. In order to improve the efficiency of the in vivo experiments, mathematical optimization is needed. We implemented a chemotherapeutical drug dosing algorithm based on a fuzzy logic search that is providing an initial value for a model predictive control system that calculates the minimum dose using a linear quadratic fitness function. This results in a suboptimal drug dose therapy plan. These results seem satisfactory in order to replace the traditional chemotherapy plans in the nearby future.
{"title":"Model predictive fuzzy control in chemotherapy optimization","authors":"Tamás Dániel Szücs, Melánia Puskás, D. Drexler, L. Kovács","doi":"10.1109/SACI58269.2023.10158569","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158569","url":null,"abstract":"Nowadays clinical therapies in chemotherapy sessions are generalized for patients, therefore we are working to provide a personalized drug plan to help reduce the drug dosage, causing the reduction of side effects and costs. Also, one benefit of this method is to prevent drug resistance. In order to improve the efficiency of the in vivo experiments, mathematical optimization is needed. We implemented a chemotherapeutical drug dosing algorithm based on a fuzzy logic search that is providing an initial value for a model predictive control system that calculates the minimum dose using a linear quadratic fitness function. This results in a suboptimal drug dose therapy plan. These results seem satisfactory in order to replace the traditional chemotherapy plans in the nearby future.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122703745","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158602
Gréta Gonda, Gábor Kertész
The goal of this paper is to describe a predictive model that is able to estimate the expected time of the child’s birth using contraction data collected since the beginning of labor. During research both classical and neural network time series forecasting models were investigated. Among the classic time series forecasting methods, the Integrated Autoregressive Moving Average Model, i.e., ARIMA, and Holt’s exponential smoothing were examined. And among the time series forecasting methods based on neural networks, the LSTM i.e., Long short-term memory and the one-dimensional convolutional neural network were implemented. The evaluation results show that the neural networks outperformed the classical methods. The best result was achieved using the one-dimensional convolutional neural network.
{"title":"Birth time prediction based on uterus-activity using machine learning","authors":"Gréta Gonda, Gábor Kertész","doi":"10.1109/SACI58269.2023.10158602","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158602","url":null,"abstract":"The goal of this paper is to describe a predictive model that is able to estimate the expected time of the child’s birth using contraction data collected since the beginning of labor. During research both classical and neural network time series forecasting models were investigated. Among the classic time series forecasting methods, the Integrated Autoregressive Moving Average Model, i.e., ARIMA, and Holt’s exponential smoothing were examined. And among the time series forecasting methods based on neural networks, the LSTM i.e., Long short-term memory and the one-dimensional convolutional neural network were implemented. The evaluation results show that the neural networks outperformed the classical methods. The best result was achieved using the one-dimensional convolutional neural network.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"336 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115669322","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158563
Modafar Al-Shouha, G. Szücs
The rapid advancement in Deep Learning (DL) proposes viable solutions to various real-world problems. However, deploying DL-based models in some applications is hindered by their black-box nature and the inability to explain them. This has pushed Explainable Artificial Intelligence (XAI) research toward DL-based models, aiming to increase the trust by reducing their opacity. Although many XAI algorithms were proposed earlier, they lack the ability to explain certain tasks, i.e. image captioning (IC). This is caused by the IC task nature, e.g. the presence of multiple objects from the same category in the captioned image. In this paper we propose and investigate an XAI approach for this particular task. Additionally, we provide a method to evaluate XAI algorithms performance in the domain1.1Our code is available at https://github.com/modafarshouha/PIC-XAI.
{"title":"PIC-XAI: Post-hoc Image Captioning Explanation using Segmentation","authors":"Modafar Al-Shouha, G. Szücs","doi":"10.1109/SACI58269.2023.10158563","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158563","url":null,"abstract":"The rapid advancement in Deep Learning (DL) proposes viable solutions to various real-world problems. However, deploying DL-based models in some applications is hindered by their black-box nature and the inability to explain them. This has pushed Explainable Artificial Intelligence (XAI) research toward DL-based models, aiming to increase the trust by reducing their opacity. Although many XAI algorithms were proposed earlier, they lack the ability to explain certain tasks, i.e. image captioning (IC). This is caused by the IC task nature, e.g. the presence of multiple objects from the same category in the captioned image. In this paper we propose and investigate an XAI approach for this particular task. Additionally, we provide a method to evaluate XAI algorithms performance in the domain1.1Our code is available at https://github.com/modafarshouha/PIC-XAI.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117220624","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158587
Marcell Csaba Sárkány, András Kovács
This paper presents the design and development of a web-based system that allows Hungarian university students to create personalized and optimized timetables during the subject-taking period. The system is based on a backtracking algorithm that considers the user’s preferences and constraints. The requirements specification, use cases, data structures, and architecture of the system are detailed, as well as the selection of the ASP.NET Core and Angular frameworks. The system was tested with real data and results showed that the stricter the user’s preferences, the faster the results were generated. The paper concludes with a summary of the system’s development and testing documentation.
{"title":"Timetable generator and optimizer for Hungarian university students","authors":"Marcell Csaba Sárkány, András Kovács","doi":"10.1109/SACI58269.2023.10158587","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158587","url":null,"abstract":"This paper presents the design and development of a web-based system that allows Hungarian university students to create personalized and optimized timetables during the subject-taking period. The system is based on a backtracking algorithm that considers the user’s preferences and constraints. The requirements specification, use cases, data structures, and architecture of the system are detailed, as well as the selection of the ASP.NET Core and Angular frameworks. The system was tested with real data and results showed that the stricter the user’s preferences, the faster the results were generated. The paper concludes with a summary of the system’s development and testing documentation.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123098493","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 : 2023-05-23DOI: 10.1109/SACI58269.2023.10158617
J. Varga, Ágnes Csiszárik-Kocsir, B. Bíró, Kinga Katalin Székely, Boróka-Júlia Bíró, Mónika Garai-Fodor
The pandemic has had an impact in many areas, leading to significant changes in preferences, work organisation and quality of life in both consumer and B2B markets. The focus of the study is on small and medium sized enterprises (SMEs), which play a dominant role in the domestic B2B market, and in particular the mechanisms and processes of change management and its effectiveness. The primary data presented in the study are the results of quantitative research in the Hungarian and Romanian markets. In this context, the change management processes and practices of Hungarian and Romanian SMEs are compared to identify similarities and differences. The data collection took the form of a pre-tested, standardised online questionnaire with an arbitrary sampling. The results of the study shed light on the role of change management in the lives of SMEs, which techniques are considered effective in the two markets studied, and which tools and solutions can be adapted to other enterprises operating in different sociocultural contexts.
{"title":"Change Management Practices and the Impact of the Pandemic on Hungarian and Romanian SMEs1","authors":"J. Varga, Ágnes Csiszárik-Kocsir, B. Bíró, Kinga Katalin Székely, Boróka-Júlia Bíró, Mónika Garai-Fodor","doi":"10.1109/SACI58269.2023.10158617","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158617","url":null,"abstract":"The pandemic has had an impact in many areas, leading to significant changes in preferences, work organisation and quality of life in both consumer and B2B markets. The focus of the study is on small and medium sized enterprises (SMEs), which play a dominant role in the domestic B2B market, and in particular the mechanisms and processes of change management and its effectiveness. The primary data presented in the study are the results of quantitative research in the Hungarian and Romanian markets. In this context, the change management processes and practices of Hungarian and Romanian SMEs are compared to identify similarities and differences. The data collection took the form of a pre-tested, standardised online questionnaire with an arbitrary sampling. The results of the study shed light on the role of change management in the lives of SMEs, which techniques are considered effective in the two markets studied, and which tools and solutions can be adapted to other enterprises operating in different sociocultural contexts.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123147534","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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