Z. Kanetaki, C. Stergiou, G. Bekas, C. Troussas, C. Sgouropoulou
Faced with the disruption generated by the COVID-19 pandemic, the advent of enforced and exclusive online learning presented a challenging opportunity for researchers worldwide, to quickly adapt curricula to this new reality and gather electronic data by tracking students’ satisfaction after attending online modules. Many researchers have looked into the subject of student satisfaction to discover if there is a link between personal satisfaction and academic achievement. Using a set of data, filtered out of a statistical analysis applied on an online survey, with 129 variables, this study investigates students’ satisfaction prediction in a first-semester Mechanical Engineering CAD module combined with the evaluation and the effectiveness of specific curriculum reforms. A hybrid machine learning model that has been created, initially consists of a Generalized Linear Model (GLAR), based on critical variables that have been filtered out after a correlation analysis. Its fitting errors are utilized as an extra predictor, that is used as an input to an artificial neural network. The model has been trained using as a basis the 70% of the population (consisting of 165 observations) to predict the satisfaction of the remaining 30%. After several trials and gradual improvement, the metamodel’s architecture is produced. The trained hybrid model’s final form had a coefficient of determination equal to 1 (R = 1). This indicates that the data fitting method was successful in linking the independent variables with the dependent variable 100 percent of the time (satisfaction prediction).
{"title":"Creating a Metamodel for Predicting Learners' Satisfaction by Utilizing an Educational Information System During COVID-19 Pandemic","authors":"Z. Kanetaki, C. Stergiou, G. Bekas, C. Troussas, C. Sgouropoulou","doi":"10.3233/faia210085","DOIUrl":"https://doi.org/10.3233/faia210085","url":null,"abstract":"Faced with the disruption generated by the COVID-19 pandemic, the advent of enforced and exclusive online learning presented a challenging opportunity for researchers worldwide, to quickly adapt curricula to this new reality and gather electronic data by tracking students’ satisfaction after attending online modules. Many researchers have looked into the subject of student satisfaction to discover if there is a link between personal satisfaction and academic achievement. Using a set of data, filtered out of a statistical analysis applied on an online survey, with 129 variables, this study investigates students’ satisfaction prediction in a first-semester Mechanical Engineering CAD module combined with the evaluation and the effectiveness of specific curriculum reforms. A hybrid machine learning model that has been created, initially consists of a Generalized Linear Model (GLAR), based on critical variables that have been filtered out after a correlation analysis. Its fitting errors are utilized as an extra predictor, that is used as an input to an artificial neural network. The model has been trained using as a basis the 70% of the population (consisting of 165 observations) to predict the satisfaction of the remaining 30%. After several trials and gradual improvement, the metamodel’s architecture is produced. The trained hybrid model’s final form had a coefficient of determination equal to 1 (R = 1). This indicates that the data fitting method was successful in linking the independent variables with the dependent variable 100 percent of the time (satisfaction prediction).","PeriodicalId":234167,"journal":{"name":"International Conference on Novelties in Intelligent Digital Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123458348","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}
Z. Kanetaki, C. Stergiou, G. Bekas, C. Troussas, C. Sgouropoulou
Instructional materials, internet accessibility, student involvement and communication have always been integral characteristics of e-learning. During the transition from face-to-face to COVID-19 new online learning environments, the lectures and laboratories at universities have taken place either synchronously (using platforms, like MS Teams) or asynchronously (using platforms, like Moodle). In this study, a case study of a Greek university on the online assessment of learners is presented. As a testbed of this research, MS Teams was employed and tested as being a Learning Management System for evaluating a single platform use in order to avoid disruption of the educational procedure with concurrent LMS operations during the pandemic. A statistical analysis including a correlation analysis and a reliability analysis has been used to mine and filter data from online questionnaires. 37 variables were found to have a significant impact on the testing of tasks’ assignment into a single platform that was used at the same time for synchronous lectures. The calculation of Cronbach’s Alpha coefficient indicated that 89% of the survey questions have been found to be internally consistent and reliable variables and sampling adequacy measure (Bartlett’s test) was determined to be good at 0.816. Two clusters of students have been differentiated based on the parameters of their diligence, communication abilities and level of knowledge embedding. A hierarchical cluster analysis has been performed extracting a dendrogram indicating 2 large clusters in the upper branch, three clusters in the lower branch and an ensuing lower branch containing five clusters.
{"title":"Data Mining for Improving Online Higher Education Amidst COVID-19 Pandemic: A Case Study in the Assessment of Engineering Students","authors":"Z. Kanetaki, C. Stergiou, G. Bekas, C. Troussas, C. Sgouropoulou","doi":"10.3233/faia210088","DOIUrl":"https://doi.org/10.3233/faia210088","url":null,"abstract":"Instructional materials, internet accessibility, student involvement and communication have always been integral characteristics of e-learning. During the transition from face-to-face to COVID-19 new online learning environments, the lectures and laboratories at universities have taken place either synchronously (using platforms, like MS Teams) or asynchronously (using platforms, like Moodle). In this study, a case study of a Greek university on the online assessment of learners is presented. As a testbed of this research, MS Teams was employed and tested as being a Learning Management System for evaluating a single platform use in order to avoid disruption of the educational procedure with concurrent LMS operations during the pandemic. A statistical analysis including a correlation analysis and a reliability analysis has been used to mine and filter data from online questionnaires. 37 variables were found to have a significant impact on the testing of tasks’ assignment into a single platform that was used at the same time for synchronous lectures. The calculation of Cronbach’s Alpha coefficient indicated that 89% of the survey questions have been found to be internally consistent and reliable variables and sampling adequacy measure (Bartlett’s test) was determined to be good at 0.816. Two clusters of students have been differentiated based on the parameters of their diligence, communication abilities and level of knowledge embedding. A hierarchical cluster analysis has been performed extracting a dendrogram indicating 2 large clusters in the upper branch, three clusters in the lower branch and an ensuing lower branch containing five clusters.","PeriodicalId":234167,"journal":{"name":"International Conference on Novelties in Intelligent Digital Systems","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126318038","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}
Recently, smart technologies as well as the digitization has entered dynamically into our lives. Cities become mega-cities because of the over population, human health conditions are gradually degraded. The existence of disabled people and the lack of their socialization the diversity of stakeholders as human beings and the difficulty of integrating them into society are few of some problems that Smart City and Smart Technology come to give manageable solutions. Solutions that could find into suggesting researches and intelligence analytics. It is important to refer to this relationship of intelligent capabilities and human resources. This study presents an overview of digital technology especially for people with disabilities. It highlights the contribution of technology to simple everyday habits of disabled and the ability to access the immediate environment. In conclusion, this article is based on the individual requirements, human rights, and preferences of people with disabilities and gives an intriguing perspective to a subject that will be in the limelight and provide effective solutions in the next years driven by technological developments.
{"title":"Smart Technologies and the Case of People with Disabilities: A Preliminary Overview","authors":"Maria Poli","doi":"10.3233/faia210096","DOIUrl":"https://doi.org/10.3233/faia210096","url":null,"abstract":"Recently, smart technologies as well as the digitization has entered dynamically into our lives. Cities become mega-cities because of the over population, human health conditions are gradually degraded. The existence of disabled people and the lack of their socialization the diversity of stakeholders as human beings and the difficulty of integrating them into society are few of some problems that Smart City and Smart Technology come to give manageable solutions. Solutions that could find into suggesting researches and intelligence analytics. It is important to refer to this relationship of intelligent capabilities and human resources. This study presents an overview of digital technology especially for people with disabilities. It highlights the contribution of technology to simple everyday habits of disabled and the ability to access the immediate environment. In conclusion, this article is based on the individual requirements, human rights, and preferences of people with disabilities and gives an intriguing perspective to a subject that will be in the limelight and provide effective solutions in the next years driven by technological developments.","PeriodicalId":234167,"journal":{"name":"International Conference on Novelties in Intelligent Digital Systems","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130288304","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}
Jozelle C. Addawe, Jaime D. L. Caro, R. A. Juayong
The analysis of disease occurrence over the smallest unit of a region is critical in designing data-driven and targeted intervention plans to reduce health impacts in the population and prevent spread of disease. This study aims to characterize groups of local communities that exhibit the same temporal patterns in dengue occurrence using the Fuzzy C-means (FCM) algorithm for clustering spatiotemporal data and investigate its performance in clustering data on dengue cases aggregated yearly, monthly and weekly. In particular, this study investigates similar patterns of Dengue cases in 129 barangays of Baguio City, Philippines recorded over a period of 9 years. Results have shown that the FCM has promising results in grouping together time series data of barangays when using data that is aggregated weekly.
{"title":"A Fuzzy C-Means-Based Algorithm for the Surveillance of Dengue Cases Distribution in Local Communities","authors":"Jozelle C. Addawe, Jaime D. L. Caro, R. A. Juayong","doi":"10.3233/faia210091","DOIUrl":"https://doi.org/10.3233/faia210091","url":null,"abstract":"The analysis of disease occurrence over the smallest unit of a region is critical in designing data-driven and targeted intervention plans to reduce health impacts in the population and prevent spread of disease. This study aims to characterize groups of local communities that exhibit the same temporal patterns in dengue occurrence using the Fuzzy C-means (FCM) algorithm for clustering spatiotemporal data and investigate its performance in clustering data on dengue cases aggregated yearly, monthly and weekly. In particular, this study investigates similar patterns of Dengue cases in 129 barangays of Baguio City, Philippines recorded over a period of 9 years. Results have shown that the FCM has promising results in grouping together time series data of barangays when using data that is aggregated weekly.","PeriodicalId":234167,"journal":{"name":"International Conference on Novelties in Intelligent Digital Systems","volume":" 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132095576","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}
J. C. Boque, J. Caro, Richelle Anne Juayong, R. Jamora
Parkinson’s Disease is a progressive, irreversible disease that is only slowed down with the use of medications and therapy. These are the only way to slow down the progression of the disease to more severe situation. Currently, virtual reality is being use on games and entertainment. Some doctors prefer the use of virtual reality like Wii to help supplement the therapy done on rehabilitation. However, devices to cater virtual reality for mid-class to lower-class patients cannot afford such devices. An alternative device, usually accessible to everyone is proposed to cater these virtual reality applications that can help in therapy of Parkinson’s patients. With that, the capabilities of VR can be accessible to more patients who cannot avail expense medication and devices for virtual reality.
{"title":"Virtual Reality Tool for Rehabilitation of Patients with Parkinson's Disease: A Conceptual Design Review","authors":"J. C. Boque, J. Caro, Richelle Anne Juayong, R. Jamora","doi":"10.3233/faia210076","DOIUrl":"https://doi.org/10.3233/faia210076","url":null,"abstract":"Parkinson’s Disease is a progressive, irreversible disease that is only slowed down with the use of medications and therapy. These are the only way to slow down the progression of the disease to more severe situation. Currently, virtual reality is being use on games and entertainment. Some doctors prefer the use of virtual reality like Wii to help supplement the therapy done on rehabilitation. However, devices to cater virtual reality for mid-class to lower-class patients cannot afford such devices. An alternative device, usually accessible to everyone is proposed to cater these virtual reality applications that can help in therapy of Parkinson’s patients. With that, the capabilities of VR can be accessible to more patients who cannot avail expense medication and devices for virtual reality.","PeriodicalId":234167,"journal":{"name":"International Conference on Novelties in Intelligent Digital Systems","volume":"243 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124682819","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}
Different methods have been proposed for designing the personalization process in a recommendation system. In the past, multi-criteria decision making theories have been proposed for the design of stereotypes in a recommendation system for environmental awareness. The main objective of this paper is on presenting the main differences when applying the fuzzy AHP and AHP for designing the weights of criteria in a recommendation system that its personalization process is based on multi-criteria decision making theories.
{"title":"Designing Personalisation in a Environmental Recommendation System: Differences of AHP and Fuzzy AHP","authors":"K. Kabassi","doi":"10.3233/faia210097","DOIUrl":"https://doi.org/10.3233/faia210097","url":null,"abstract":"Different methods have been proposed for designing the personalization process in a recommendation system. In the past, multi-criteria decision making theories have been proposed for the design of stereotypes in a recommendation system for environmental awareness. The main objective of this paper is on presenting the main differences when applying the fuzzy AHP and AHP for designing the weights of criteria in a recommendation system that its personalization process is based on multi-criteria decision making theories.","PeriodicalId":234167,"journal":{"name":"International Conference on Novelties in Intelligent Digital Systems","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134429707","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}
There is an increasing number of people with Alzheimer’s disease. Negative emotions are not only one of the symptoms of AD, but also the accelerator of the disease. Animal therapy can have a positive impact on the negative emotions of patients, but it has strict requirements for both environments and animals. In this study, we aim to explore the effectiveness of using virtual animals and their impact on the reduction of patients’ negative emotions to improve the user’s cognitive functions. This approach has been implemented in the Zoo Therapy project, which presents an immersive 3D virtual reality animal environment, where the impact on the patient’s emotion is measured in real-time by using electroencephalography (EEG). In addition to creating highly realistic virtual animals, the innovation of Zoo Therapy is also in its communication mechanism as it implements bidirectional human-computer interaction supported by 3 interaction methods: 3D buttons, speech instruction, and Neurofeedback. Patients can actively interact with virtual animals through 3D buttons or speech instructions. The Neurofeedback system will guide the animal to actively interact with the patients according to their real-time emotional changes to reduce their negative emotions. Experiments and preliminary results show that it is possible to interact with virtual animals in Zoo Therapy, and the Neurofeedback system can intervene in Zoo VR environment when the emotional value goes down and might reduce patients’ negative emotions.
{"title":"Zoo Therapy for Alzheimer's Disease with Real-Time Speech Instruction and Neurofeedback System","authors":"Y. Ai, H. Abdessalem, C. Frasson","doi":"10.3233/faia210079","DOIUrl":"https://doi.org/10.3233/faia210079","url":null,"abstract":"There is an increasing number of people with Alzheimer’s disease. Negative emotions are not only one of the symptoms of AD, but also the accelerator of the disease. Animal therapy can have a positive impact on the negative emotions of patients, but it has strict requirements for both environments and animals. In this study, we aim to explore the effectiveness of using virtual animals and their impact on the reduction of patients’ negative emotions to improve the user’s cognitive functions. This approach has been implemented in the Zoo Therapy project, which presents an immersive 3D virtual reality animal environment, where the impact on the patient’s emotion is measured in real-time by using electroencephalography (EEG). In addition to creating highly realistic virtual animals, the innovation of Zoo Therapy is also in its communication mechanism as it implements bidirectional human-computer interaction supported by 3 interaction methods: 3D buttons, speech instruction, and Neurofeedback. Patients can actively interact with virtual animals through 3D buttons or speech instructions. The Neurofeedback system will guide the animal to actively interact with the patients according to their real-time emotional changes to reduce their negative emotions. Experiments and preliminary results show that it is possible to interact with virtual animals in Zoo Therapy, and the Neurofeedback system can intervene in Zoo VR environment when the emotional value goes down and might reduce patients’ negative emotions.","PeriodicalId":234167,"journal":{"name":"International Conference on Novelties in Intelligent Digital Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129526350","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}
Gabrielle Toupin, Mohamed S. Benlamine, C. Frasson
Amusement can help modulate psychological disorders and cognitive functions. Unfortunately, algorithms classifying emotions still combine multiple positive emotions into a unique emotion, namely joy, making it hard to use amusement in a real-life setting. Here we train a Long-Short-Term-Memory (LSTM) on electroencephalography (EEG) to predict amusement on a categorical scale. Participants (n=10) watched and rated 120 videos with various funniness levels while their brain activity was recorded with an Emotiv Headset. Participant’s ratings were divided into four bins of amusement (low, medium, high & very high) based on the participant’s ranking’s percentile. Nested cross-validation was used to validate the models. We first left out one video from each participant for the final model’s validation and a leave-one-group-out technique was used to test the model on an unseen participant during the training phase. The nested cross-validation was tested on sixteen different videos. We created an LSTM model with five hidden layers, vatch size of 256 and an input layer of 14 x 128 (number of electrodes x 1 sec of recording) and four nodes representing the different levels of amusement. The best model obtained during the training phase was tested on the unseen video. While the level of accuracy between the validation videos varies slightly (mean=57.3%, std=13.7%), our best model obtained an accuracy of 82,4%. This high accuracy supports the use of brain activity to predict amusement. Moreover, the validation process we design conveys that models using this technique are transferable across participants and videos.
娱乐可以帮助调节心理障碍和认知功能。不幸的是，情绪分类算法仍然将多种积极情绪合并为一种独特的情绪，即快乐，这使得在现实生活中很难使用娱乐。在此，我们在脑电图(EEG)上训练一个长短期记忆(LSTM)来预测分类尺度上的娱乐。参与者(n=10)观看了120个不同搞笑程度的视频，并对其进行了评分，同时用Emotiv耳机记录了他们的大脑活动。根据参与者排名的百分位数，参与者的评分被分为四个类别(低、中、高和非常高)。采用嵌套交叉验证对模型进行验证。我们首先从每个参与者那里留下一个视频用于最终模型的验证，并在训练阶段使用留一组技术在未见过的参与者身上测试模型。在16个不同的视频上测试了嵌套交叉验证。我们创建了一个LSTM模型，它有5个隐藏层，手表大小为256，输入层为14 x 128(电极数量x 1秒记录)，四个节点代表不同的娱乐水平。在训练阶段得到的最佳模型在未看过的视频上进行了测试。虽然验证视频之间的准确度水平略有不同(平均值=57.3%，标准差=13.7%)，但我们的最佳模型获得了82,4%的准确度。这种高准确性支持使用大脑活动来预测娱乐。此外，我们设计的验证过程表明，使用该技术的模型可在参与者和视频之间转移。
{"title":"Prediction of Amusement Intensity Based on Brain Activity","authors":"Gabrielle Toupin, Mohamed S. Benlamine, C. Frasson","doi":"10.3233/faia210099","DOIUrl":"https://doi.org/10.3233/faia210099","url":null,"abstract":"Amusement can help modulate psychological disorders and cognitive functions. Unfortunately, algorithms classifying emotions still combine multiple positive emotions into a unique emotion, namely joy, making it hard to use amusement in a real-life setting. Here we train a Long-Short-Term-Memory (LSTM) on electroencephalography (EEG) to predict amusement on a categorical scale. Participants (n=10) watched and rated 120 videos with various funniness levels while their brain activity was recorded with an Emotiv Headset. Participant’s ratings were divided into four bins of amusement (low, medium, high & very high) based on the participant’s ranking’s percentile. Nested cross-validation was used to validate the models. We first left out one video from each participant for the final model’s validation and a leave-one-group-out technique was used to test the model on an unseen participant during the training phase. The nested cross-validation was tested on sixteen different videos. We created an LSTM model with five hidden layers, vatch size of 256 and an input layer of 14 x 128 (number of electrodes x 1 sec of recording) and four nodes representing the different levels of amusement. The best model obtained during the training phase was tested on the unseen video. While the level of accuracy between the validation videos varies slightly (mean=57.3%, std=13.7%), our best model obtained an accuracy of 82,4%. This high accuracy supports the use of brain activity to predict amusement. Moreover, the validation process we design conveys that models using this technique are transferable across participants and videos.","PeriodicalId":234167,"journal":{"name":"International Conference on Novelties in Intelligent Digital Systems","volume":"345 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120892229","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}
Aira Jazel Y. Ang, Roberto D. Principio, R. A. Juayong, J. D. L. Caro
The study aims to explore VR Serious Games as a form of therapy for people with dementia. It seeks to establish the utility of VR-based interventions with the application of Montessori Method. This study also serves as a basis for researchers, healthcare professionals, and developers who plan to incorporate VR therapy with other therapeutic approaches and to create a system that may be replicated for other illnesses via telemedicine to address the most vulnerable sectors. The main beneficiaries of this study are people with dementia and those who directly interact with them such as their doctors, caregivers, and family members of the patient.
{"title":"GunitaHu: A VR Serious Game with Montessori Approach for Dementia Patients During COVID-19","authors":"Aira Jazel Y. Ang, Roberto D. Principio, R. A. Juayong, J. D. L. Caro","doi":"10.3233/faia210082","DOIUrl":"https://doi.org/10.3233/faia210082","url":null,"abstract":"The study aims to explore VR Serious Games as a form of therapy for people with dementia. It seeks to establish the utility of VR-based interventions with the application of Montessori Method. This study also serves as a basis for researchers, healthcare professionals, and developers who plan to incorporate VR therapy with other therapeutic approaches and to create a system that may be replicated for other illnesses via telemedicine to address the most vulnerable sectors. The main beneficiaries of this study are people with dementia and those who directly interact with them such as their doctors, caregivers, and family members of the patient.","PeriodicalId":234167,"journal":{"name":"International Conference on Novelties in Intelligent Digital Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124746751","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}
G. Kopsiaftis, Ioannis Georgoulas, I. Rallis, Ioannis Markoulidakis, Kostis Tzanettis, Michael Sfakianos, N. Doulamis
This paper analyzes the architecture of an application programming interface (API) developed for a novel customer experience tool. The CX tool aims to monitor the customer satisfaction, based on several experience attributes and metrics, such as the Net Promoter Score. The API aims to create an efficient and user-friendly environment, which allow users to utilize all the available features of the customer experience system, including the exploitation of state-of-the-art machine learning algorithms, the analysis of the data and the graphical representation of the results.
{"title":"Application Programming Interface for a Customer Experience Analysis Tool","authors":"G. Kopsiaftis, Ioannis Georgoulas, I. Rallis, Ioannis Markoulidakis, Kostis Tzanettis, Michael Sfakianos, N. Doulamis","doi":"10.3233/faia210092","DOIUrl":"https://doi.org/10.3233/faia210092","url":null,"abstract":"This paper analyzes the architecture of an application programming interface (API) developed for a novel customer experience tool. The CX tool aims to monitor the customer satisfaction, based on several experience attributes and metrics, such as the Net Promoter Score. The API aims to create an efficient and user-friendly environment, which allow users to utilize all the available features of the customer experience system, including the exploitation of state-of-the-art machine learning algorithms, the analysis of the data and the graphical representation of the results.","PeriodicalId":234167,"journal":{"name":"International Conference on Novelties in Intelligent Digital Systems","volume":"736 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131621376","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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