Pub Date : 2023-05-23DOI: 10.1109/SACI58269.2023.10158648
K. Jäckel, Mónika Garai-Fodor
Our qualitative research was inspired by the 75-year long Harvard University Happiness Survey.In October-November 2022, 65 young marketing undergraduates from Generation Z were asked what value and happiness meant to them. Today’s 20-year-olds were forced to live one tenth of their lives, i.e., 2 years, locked in their homes, isolated from friends and university peers, during the COVID -19 pandemic. Hardly had they recovered from the threat of the pandemic, from their grief, when they were hit by another trauma, as were other members of society. War in neighbouring Ukraine, serious energy crisis, climate crisis, skyrocketing inflation, uncertain future…The focus of the research was therefore on the question of what kind of life they would be satisfied with, and what they would do to achieve the quality of life they want. What goals do they have, what do they want to achieve in their lives? Are human relationships important to them? As our interviewees were marketing students, we asked them if they were happy buying a product or using a service, how important is the experience of buying a product or service to them? How do they think about this topic, what strategy do they want to follow as marketing employees based on their life experiences? Their way of thinking is also decisive at a societal level.
{"title":"What Represents Value and Happiness for the Hungarian Generation Z in 2022-2023?","authors":"K. Jäckel, Mónika Garai-Fodor","doi":"10.1109/SACI58269.2023.10158648","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158648","url":null,"abstract":"Our qualitative research was inspired by the 75-year long Harvard University Happiness Survey.In October-November 2022, 65 young marketing undergraduates from Generation Z were asked what value and happiness meant to them. Today’s 20-year-olds were forced to live one tenth of their lives, i.e., 2 years, locked in their homes, isolated from friends and university peers, during the COVID -19 pandemic. Hardly had they recovered from the threat of the pandemic, from their grief, when they were hit by another trauma, as were other members of society. War in neighbouring Ukraine, serious energy crisis, climate crisis, skyrocketing inflation, uncertain future…The focus of the research was therefore on the question of what kind of life they would be satisfied with, and what they would do to achieve the quality of life they want. What goals do they have, what do they want to achieve in their lives? Are human relationships important to them? As our interviewees were marketing students, we asked them if they were happy buying a product or using a service, how important is the experience of buying a product or service to them? How do they think about this topic, what strategy do they want to follow as marketing employees based on their life experiences? Their way of thinking is also decisive at a societal level.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"48 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":"122368369","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/SACI58269.2023.10158549
Delia Moga, I. Filip
This paper presents a study on using innovative machine learning techniques that can be applied in automotive traffic scenarios to increase a vehicle’s level of autonomy. The overtaking traffic scenario is treated for predicting the vehicle trajectory when overtaking another vehicle and the data is obtained by image processing using a video camera. Two different methods are compared, first by using classic tracking methods and a Kalman filter (as an adaptive filter) and second by using a machine learning technique - Support Vector Machine. The present article uses as inputs the data received from the camera and focuses on tracking selected objects and estimating their position using mainly image processing in automotive scenarios. The main purpose of this work is to experiment and compare different tracking modes to determine those that have the best performances in terms of runtime, memory usage and prediction accuracy.
{"title":"Automotive Scenarios for Trajectory Tracking using Machine Learning Techniques and Image Processing","authors":"Delia Moga, I. Filip","doi":"10.1109/SACI58269.2023.10158549","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158549","url":null,"abstract":"This paper presents a study on using innovative machine learning techniques that can be applied in automotive traffic scenarios to increase a vehicle’s level of autonomy. The overtaking traffic scenario is treated for predicting the vehicle trajectory when overtaking another vehicle and the data is obtained by image processing using a video camera. Two different methods are compared, first by using classic tracking methods and a Kalman filter (as an adaptive filter) and second by using a machine learning technique - Support Vector Machine. The present article uses as inputs the data received from the camera and focuses on tracking selected objects and estimating their position using mainly image processing in automotive scenarios. The main purpose of this work is to experiment and compare different tracking modes to determine those that have the best performances in terms of runtime, memory usage and prediction accuracy.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"50 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":"125641867","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/SACI58269.2023.10158651
Lilla Kisbenedek, Melánia Puskás, L. Kovács, D. Drexler
Personalized therapy based on mathematical foundations is a promising method for treating various types of cancer. By identifying the parameters of mathematical equations, we could gain more information about the patients and the tumor. In previous works, a vast number of training data of virtual scenarios has been generated, then used to train a neural network to predict parameters. Besides the fact that in silico experiments have been used, and the actual parameters can differ from them, the algorithm still can be utilized for initial estimation. The main objective of this work is to find the parameters of living mice, by taking advantage of the learning capability of neural networks. As a result, the implementation encompasses two main stages. First, we created another supervised neural network, that is able to solve the applied differential equations faster with fewer algebraic steps, than the traditionally used ODE solvers. Then, we find a better-fitting parameter set for the real measurement, while we retrain the original network with these parameters and the associated error, without forgetting the already learned weights from in silico experiments. The results indicate that the implemented model can be used in further research as an unconstrained optimization technique for parameter fitting.
{"title":"Indirect supervised fine-tuning of a tumor model parameter estimator neural network","authors":"Lilla Kisbenedek, Melánia Puskás, L. Kovács, D. Drexler","doi":"10.1109/SACI58269.2023.10158651","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158651","url":null,"abstract":"Personalized therapy based on mathematical foundations is a promising method for treating various types of cancer. By identifying the parameters of mathematical equations, we could gain more information about the patients and the tumor. In previous works, a vast number of training data of virtual scenarios has been generated, then used to train a neural network to predict parameters. Besides the fact that in silico experiments have been used, and the actual parameters can differ from them, the algorithm still can be utilized for initial estimation. The main objective of this work is to find the parameters of living mice, by taking advantage of the learning capability of neural networks. As a result, the implementation encompasses two main stages. First, we created another supervised neural network, that is able to solve the applied differential equations faster with fewer algebraic steps, than the traditionally used ODE solvers. Then, we find a better-fitting parameter set for the real measurement, while we retrain the original network with these parameters and the associated error, without forgetting the already learned weights from in silico experiments. The results indicate that the implemented model can be used in further research as an unconstrained optimization technique for parameter fitting.","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":"130003341","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/SACI58269.2023.10158605
Bence Richard Hach, Lucian Ionel Gaina, D. Stanescu, Bianca Gusita
In the National Basketball Association (NBA), understanding how age impacts player performance is crucial for team general managers and coaches, allowing them to construct the most competitive rosters. This research paper aims to investigate the relationship between the player’s performances and their age by clustering the players into six groups based on their ages and comparing their performance indicators. For each group, multiple widely known indicators as the Individual Player Efficiency (EFF) and Player Efficiency Rating (PER), were used. Experimental results show the age at which players commonly reach peak performance levels. Using these results, general managers have a cutting edge when searching for new players to enhance their team performance.
{"title":"The impact of age on NBA player’s performances: A Data Mining approach","authors":"Bence Richard Hach, Lucian Ionel Gaina, D. Stanescu, Bianca Gusita","doi":"10.1109/SACI58269.2023.10158605","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158605","url":null,"abstract":"In the National Basketball Association (NBA), understanding how age impacts player performance is crucial for team general managers and coaches, allowing them to construct the most competitive rosters. This research paper aims to investigate the relationship between the player’s performances and their age by clustering the players into six groups based on their ages and comparing their performance indicators. For each group, multiple widely known indicators as the Individual Player Efficiency (EFF) and Player Efficiency Rating (PER), were used. Experimental results show the age at which players commonly reach peak performance levels. Using these results, general managers have a cutting edge when searching for new players to enhance their team performance.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"31 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":"126385659","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/SACI58269.2023.10158633
Árpád Rigó, B. Tusor
The subject of this paper is an options modeling system, which aims to provide the most accurate profit forecast possible for options portfolios in a comprehensible form, as software on the market will misrepresent this in the absence of accurate implied volatility data, which can put trading success at risk. The software determines future implied volatility from 1-year historical options on VXX stock with 6 samples per trading day using statistics and a deep neural network (Long short-term memory LSTM). Using this statistical approach and the trained volatility model, the system calculates the profit/loss curve, thus providing a more accurate picture of the possible future outcomes of a given portfolio.
{"title":"Options Evaluator With an Artificial Intelligence-Based Volatility Model","authors":"Árpád Rigó, B. Tusor","doi":"10.1109/SACI58269.2023.10158633","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158633","url":null,"abstract":"The subject of this paper is an options modeling system, which aims to provide the most accurate profit forecast possible for options portfolios in a comprehensible form, as software on the market will misrepresent this in the absence of accurate implied volatility data, which can put trading success at risk. The software determines future implied volatility from 1-year historical options on VXX stock with 6 samples per trading day using statistics and a deep neural network (Long short-term memory LSTM). Using this statistical approach and the trained volatility model, the system calculates the profit/loss curve, thus providing a more accurate picture of the possible future outcomes of a given portfolio.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"69 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":"115968715","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/SACI58269.2023.10158536
Bence Hodák, Elemér Balázs
In this paper, a carpenter software is designed and implemented that supports the daily management processes (customers, orders, inventory) and generates a pattern from the product descriptions based on the parameters specified. During the pattern generation process, a two-dimensional optimization is performed to generate a pattern that includes horizontal or vertical cuts, depending on the target machine, on which the position of the required parts is placed, generates the smallest material loss and uses leftover materials from the past. From the application, the pattern can be viewed and extracted online or in PDF format. This all is implemented in a layered web application with a modern approach.
{"title":"Carpentry software designing and development with pane cutting optimization functionality","authors":"Bence Hodák, Elemér Balázs","doi":"10.1109/SACI58269.2023.10158536","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158536","url":null,"abstract":"In this paper, a carpenter software is designed and implemented that supports the daily management processes (customers, orders, inventory) and generates a pattern from the product descriptions based on the parameters specified. During the pattern generation process, a two-dimensional optimization is performed to generate a pattern that includes horizontal or vertical cuts, depending on the target machine, on which the position of the required parts is placed, generates the smallest material loss and uses leftover materials from the past. From the application, the pattern can be viewed and extracted online or in PDF format. This all is implemented in a layered web application with a modern approach.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"42 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":"130828007","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/SACI58269.2023.10158623
Borbála Gergics, F. Vajda, Alexander Ládi, András Füredi, D. Drexler
Optimized therapies for the individual patient provide a more cost-effective, more secure method of chemotherapy. Therapy optimization demands a reliable mathematical model of tumor growth, pharmacodynamics, and the effect of the chemotherapeutic agent used during the therapy. Examining these effects and processes in vitro cell culture experiments maintain a cheaper and more ethical method to create tumor growth and pharmacodynamics models and estimate their parameters. In this work, parameter identification was carried out by using cytotoxicity measurements of two- and three-dimensional (spheroid) tumor cell cultures. In vitro experiments were accomplished on mice breast cancer cell line. Four experiments were done: two experiments on two-dimensional cell cultures, with the initial number of 5000 and 10000 cells, and two experiments on three-dimensional spheroid cell cultures, with the initial number of 5000 and 10000 cells. The drug used was Doxorubicin at the same serial dilution in all cases. Parameter identification was performed by fitting to fluorescent intensity confluence data measured by an automatic time-lapse microscope for five days. We compared the results of two- and three-dimensional cell cultures and identified the model parameters in all four cases. The value of the sum square error showed that the fitting and identification performed better in the case of tumor spheroid cultures.
{"title":"Pharmacodynamics modeling based on in vitro 3D cell culture experiments","authors":"Borbála Gergics, F. Vajda, Alexander Ládi, András Füredi, D. Drexler","doi":"10.1109/SACI58269.2023.10158623","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158623","url":null,"abstract":"Optimized therapies for the individual patient provide a more cost-effective, more secure method of chemotherapy. Therapy optimization demands a reliable mathematical model of tumor growth, pharmacodynamics, and the effect of the chemotherapeutic agent used during the therapy. Examining these effects and processes in vitro cell culture experiments maintain a cheaper and more ethical method to create tumor growth and pharmacodynamics models and estimate their parameters. In this work, parameter identification was carried out by using cytotoxicity measurements of two- and three-dimensional (spheroid) tumor cell cultures. In vitro experiments were accomplished on mice breast cancer cell line. Four experiments were done: two experiments on two-dimensional cell cultures, with the initial number of 5000 and 10000 cells, and two experiments on three-dimensional spheroid cell cultures, with the initial number of 5000 and 10000 cells. The drug used was Doxorubicin at the same serial dilution in all cases. Parameter identification was performed by fitting to fluorescent intensity confluence data measured by an automatic time-lapse microscope for five days. We compared the results of two- and three-dimensional cell cultures and identified the model parameters in all four cases. The value of the sum square error showed that the fitting and identification performed better in the case of tumor spheroid cultures.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"120 6 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":"128488900","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/SACI58269.2023.10158584
Jean Rosemond Dora, L. Hluchý
Over decades, the software-defined network commonly named SDN has been prioritized by many industries and academia over traditional networks. The SDN properties offer better security of the managed network and offer better network monitoring. However, its popularity has been drawn drastically to attackers’ attention. In this paper, we evaluate the security posture of the SDN networks and prove that they are subject to several vulnerabilities by simulating attacks against devices in the network. Abusing those weaknesses can jeopardize the company’s reputation as well as its financial situation. Therefore, to achieve the exploitation, we simulate the attacks using Mininet and RYU controller tools. Additionally, we briefly talk about the mitigation techniques as we will deal with them in our future work.
{"title":"Detection of Attacks in Software-Defined Networks (SDN)* : *How to conduct attacks in SDN environments","authors":"Jean Rosemond Dora, L. Hluchý","doi":"10.1109/SACI58269.2023.10158584","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158584","url":null,"abstract":"Over decades, the software-defined network commonly named SDN has been prioritized by many industries and academia over traditional networks. The SDN properties offer better security of the managed network and offer better network monitoring. However, its popularity has been drawn drastically to attackers’ attention. In this paper, we evaluate the security posture of the SDN networks and prove that they are subject to several vulnerabilities by simulating attacks against devices in the network. Abusing those weaknesses can jeopardize the company’s reputation as well as its financial situation. Therefore, to achieve the exploitation, we simulate the attacks using Mininet and RYU controller tools. Additionally, we briefly talk about the mitigation techniques as we will deal with them in our future work.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"3 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":"130644979","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/SACI58269.2023.10158591
Dénes Tompos, B. Németh
This paper proposes a design method for achieving safe trajectory of indoor drones. The trajectory design with a reinforcement-learning-based (RL) agent is facilitated, which can result in efficient and collision-free motion. The method is developed for motion in indoor area with moving mobile robots, and thus, the collision with these obstacles must be avoided. Through RL-based design the fast motion of the drones can be achieved, which must perform a mission between workstations in a manufacturing system. The effectiveness of the design process through a simulation example on a real laboratory environment is illustrated.
{"title":"Safe trajectory design for indoor drones using reinforcement-learning-based methods","authors":"Dénes Tompos, B. Németh","doi":"10.1109/SACI58269.2023.10158591","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158591","url":null,"abstract":"This paper proposes a design method for achieving safe trajectory of indoor drones. The trajectory design with a reinforcement-learning-based (RL) agent is facilitated, which can result in efficient and collision-free motion. The method is developed for motion in indoor area with moving mobile robots, and thus, the collision with these obstacles must be avoided. Through RL-based design the fast motion of the drones can be achieved, which must perform a mission between workstations in a manufacturing system. The effectiveness of the design process through a simulation example on a real laboratory environment is illustrated.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"216 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":"114816441","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/SACI58269.2023.10158545
K. Jäckel, Mónika Garai-Fodor, Zoltán Gábor Lukács
The objective of our research was to examine the jaycustomers in healthcare. Thematic qualitative interviews were conducted with frontline healthcare staff (doctors, healthcare workers - nurses, caretakers and pharmacists). The respondents were asked to recall extraordinary situations and events. Based on the events, we asked them to describe the unpleasantness of the situation and then classify the healthcare jaycustomers. Our goal with this research is to explore the most common conflict situations in healthcare, the causes, the characteristics of destructive/deviant users, in order to formulate recommendations to service providers on how to deal with these jaycustomer types. The practical applicability of the research therefore lies in its potential to help develop proactive service provider behaviour. The identification of conflict situations allows quality improvement procedures to regulate where defects arise. 46 physicians, pharmacists/pharmacy staff, nurses, nurse practitioners, medical assistants and ambulance nurses were interviewed in September-November 2022.
{"title":"Jaycustomers in the Hungarian healthcare system","authors":"K. Jäckel, Mónika Garai-Fodor, Zoltán Gábor Lukács","doi":"10.1109/SACI58269.2023.10158545","DOIUrl":"https://doi.org/10.1109/SACI58269.2023.10158545","url":null,"abstract":"The objective of our research was to examine the jaycustomers in healthcare. Thematic qualitative interviews were conducted with frontline healthcare staff (doctors, healthcare workers - nurses, caretakers and pharmacists). The respondents were asked to recall extraordinary situations and events. Based on the events, we asked them to describe the unpleasantness of the situation and then classify the healthcare jaycustomers. Our goal with this research is to explore the most common conflict situations in healthcare, the causes, the characteristics of destructive/deviant users, in order to formulate recommendations to service providers on how to deal with these jaycustomer types. The practical applicability of the research therefore lies in its potential to help develop proactive service provider behaviour. The identification of conflict situations allows quality improvement procedures to regulate where defects arise. 46 physicians, pharmacists/pharmacy staff, nurses, nurse practitioners, medical assistants and ambulance nurses were interviewed in September-November 2022.","PeriodicalId":339156,"journal":{"name":"2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"15 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":"115268249","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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