In studies related to the behavior patterns that are generated from the interaction processes of a group of users with virtual products., It was detected that the activation of Focal Attention sub-system is a constant not only for persons with normal vision also for persons with vision weakness. However, there are behavioral differences depending on the user´s dominant sensory mechanism related with physio-anatomical and cognitive characteristics of the user. The effects are observed in the time of execution of the tasks, number of sensory mechanisms used during the process, stress responses generated by the fulfillment of objectives among others. The aim of these studies is to promote reflections on the attentional processes that are carried out from the interaction of a user with virtual products and their work systems. And explore how Focal Attention processes change with the personal characteristics of a person.
{"title":"The Activation of the Focal Attention Sub-System as a Product of a Hierarchical Process during the Interaction with Virtual Products","authors":"Lorena Olmos Pineda, Jorge Gil Tejeda","doi":"10.54941/ahfe1001146","DOIUrl":"https://doi.org/10.54941/ahfe1001146","url":null,"abstract":"In studies related to the behavior patterns that are generated from the interaction processes of a group of users with virtual products., It was detected that the activation of Focal Attention sub-system is a constant not only for persons with normal vision also for persons with vision weakness. However, there are behavioral differences depending on the user´s dominant sensory mechanism related with physio-anatomical and cognitive characteristics of the user. The effects are observed in the time of execution of the tasks, number of sensory mechanisms used during the process, stress responses generated by the fulfillment of objectives among others. The aim of these studies is to promote reflections on the attentional processes that are carried out from the interaction of a user with virtual products and their work systems. And explore how Focal Attention processes change with the personal characteristics of a person.","PeriodicalId":116806,"journal":{"name":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116765983","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}
Face tracking as innovative and unobtrusive sensor technology offers new possibilities for driver state monitoring regarding discomfort in automated driving. To explore the potential of automated facial expression analysis, video data of two driving simulator studies were analyzed using the Visage facial features and analysis software. A gender-balanced sample of 81 participants between 24 and 84 years took part in the studies. All participants were driven in highly automated mode on the same standardized track, consisting of three close approach situations to a truck driving ahead. By pressing the lever of a handset control, all participants could report perceived discomfort continuously. Tracking values for 23 facial action units were extracted from multiple video camera streams, z-transformed and averaged from 10 s before pressing the handset control until 10 s after to show changes over time. Results showed situation-related pressing and stretching of the lips, a pushback-movement of the head, raising of inner brows and upper lids as well as reduced eye closure. These patterns could be interpreted as visual attention, tension and surprise. Overall, there is potential of facial expression analysis for contributing information about users’ comfort with automated vehicle operations. However, effects became manifest on aggregated data level; obtaining stable and reliable results on individual level remains a challenging task.
{"title":"Multi-camera Face Tracking for Estimating User’s Discomfort with Automated Vehicle Operations","authors":"Matthias Beggiato, Nadine Rauh, J. Krems","doi":"10.54941/ahfe1001105","DOIUrl":"https://doi.org/10.54941/ahfe1001105","url":null,"abstract":"Face tracking as innovative and unobtrusive sensor technology offers new possibilities for driver state monitoring regarding discomfort in automated driving. To explore the potential of automated facial expression analysis, video data of two driving simulator studies were analyzed using the Visage facial features and analysis software. A gender-balanced sample of 81 participants between 24 and 84 years took part in the studies. All participants were driven in highly automated mode on the same standardized track, consisting of three close approach situations to a truck driving ahead. By pressing the lever of a handset control, all participants could report perceived discomfort continuously. Tracking values for 23 facial action units were extracted from multiple video camera streams, z-transformed and averaged from 10 s before pressing the handset control until 10 s after to show changes over time. Results showed situation-related pressing and stretching of the lips, a pushback-movement of the head, raising of inner brows and upper lids as well as reduced eye closure. These patterns could be interpreted as visual attention, tension and surprise. Overall, there is potential of facial expression analysis for contributing information about users’ comfort with automated vehicle operations. However, effects became manifest on aggregated data level; obtaining stable and reliable results on individual level remains a challenging task.","PeriodicalId":116806,"journal":{"name":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132139889","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}
Diego Vallejo-Huanga, Alisson Mendoza, Nicolás Carrasco
Ecuador was one of the first Latin American countries to have a proven case of the new coronavirus SARS-CoV-2. The social networks were the media most used by citizens to replicate news about the pandemic, and issue comments about the handling of the health crisis. This article aims to present a web tool for sentiment analysis on Twitter with three different ways to analyze the corpus and polarities: a word-dictionary-based model, a custom trained supervised machine learning model, and an open-source library to process textual data and allows obtaining a polarity metric from a tweet. Then, to define the final polarity of each tweet, an ensemble machine learning model is used for combining the predictions from the three techniques through a hard majority voting ensemble. The web system was developed with free software tools and is accompanied by visualizations and statistical graphics.
{"title":"Sentiment Analysis in Contrast to Official Data During the COVID-19 Pandemic in Ecuador","authors":"Diego Vallejo-Huanga, Alisson Mendoza, Nicolás Carrasco","doi":"10.54941/ahfe1001169","DOIUrl":"https://doi.org/10.54941/ahfe1001169","url":null,"abstract":"Ecuador was one of the first Latin American countries to have a proven case of the new coronavirus SARS-CoV-2. The social networks were the media most used by citizens to replicate news about the pandemic, and issue comments about the handling of the health crisis. This article aims to present a web tool for sentiment analysis on Twitter with three different ways to analyze the corpus and polarities: a word-dictionary-based model, a custom trained supervised machine learning model, and an open-source library to process textual data and allows obtaining a polarity metric from a tweet. Then, to define the final polarity of each tweet, an ensemble machine learning model is used for combining the predictions from the three techniques through a hard majority voting ensemble. The web system was developed with free software tools and is accompanied by visualizations and statistical graphics.","PeriodicalId":116806,"journal":{"name":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","volume":"8 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134198894","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}
Evaluating the success of a risk assessment is demanding, and a clear description of a correctly performed risk assessment is lacking. To deepen understanding of this significant topic, ten occupational health and safety specialists and managers were interviewed, and a Delphi survey was completed by 13 respondents. The participants were from various industries, public authority, and consulting. The interviewees acknowledged the importance of evaluating risk assessment although they infrequently assessed the process or the results. Based on the Delphi survey, individual features affecting the risk assessment are, for example, understanding of the entity and communication and interaction skills. Organizational features influencing risk assessment include the organization’s commitment to safety and safety management, and risk assessment being a part of the safety management system. Future research topics include constructing a model for evaluating the quality and success of the risk assessment.
{"title":"Assessing the Success of Risk Assessment and Factors Affecting Its Success","authors":"M. Rantala, Maria Lindholm, Sari Tappura","doi":"10.54941/ahfe1001112","DOIUrl":"https://doi.org/10.54941/ahfe1001112","url":null,"abstract":"Evaluating the success of a risk assessment is demanding, and a clear description of a correctly performed risk assessment is lacking. To deepen understanding of this significant topic, ten occupational health and safety specialists and managers were interviewed, and a Delphi survey was completed by 13 respondents. The participants were from various industries, public authority, and consulting. The interviewees acknowledged the importance of evaluating risk assessment although they infrequently assessed the process or the results. Based on the Delphi survey, individual features affecting the risk assessment are, for example, understanding of the entity and communication and interaction skills. Organizational features influencing risk assessment include the organization’s commitment to safety and safety management, and risk assessment being a part of the safety management system. Future research topics include constructing a model for evaluating the quality and success of the risk assessment.","PeriodicalId":116806,"journal":{"name":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134352116","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}
Diego Palma, Christian M. Soto, Fernanda Rodríguez
In this paper, a discourse-based method that merges syntactic and semantic models for developing an automated system for reading comprehension assessment is proposed. For evaluating semantic content, we use the classical models from the literature: Vector Space Modelling and Latent Semantic Analysis. For evaluating the coherence of a text, we used an entity grid representation of the texts, which extracts syntactic patterns from the texts and relies on the assumption that coherent texts will have similar underlying syntactic patterns. The contribution of this work is twofold: firstly, we develop a new methodology for free-text responses in which we assess student‘s texts by semantic content and coherence. Secondly, we develop an automated system for assessing a student's reading comprehension for Spanish language using features that can be computed automatically. Experiments show that we can get accuracies of 90% when assessing text content, and of 55% - 60% when assessing text coherence.
{"title":"Method to assess students summaries in an intelligent tutor system using coherence and content analysis in a reading comprehension task","authors":"Diego Palma, Christian M. Soto, Fernanda Rodríguez","doi":"10.54941/ahfe1001173","DOIUrl":"https://doi.org/10.54941/ahfe1001173","url":null,"abstract":"In this paper, a discourse-based method that merges syntactic and semantic models for developing an automated system for reading comprehension assessment is proposed. For evaluating semantic content, we use the classical models from the literature: Vector Space Modelling and Latent Semantic Analysis. For evaluating the coherence of a text, we used an entity grid representation of the texts, which extracts syntactic patterns from the texts and relies on the assumption that coherent texts will have similar underlying syntactic patterns. The contribution of this work is twofold: firstly, we develop a new methodology for free-text responses in which we assess student‘s texts by semantic content and coherence. Secondly, we develop an automated system for assessing a student's reading comprehension for Spanish language using features that can be computed automatically. Experiments show that we can get accuracies of 90% when assessing text content, and of 55% - 60% when assessing text coherence.","PeriodicalId":116806,"journal":{"name":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133651339","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}
The authors conducted experimental research using two examinee groups, one with peer pressure and one without, to compare the intensity of regret for an incorrect decision. The results show statistically significant differences be-tween the two groups, depending on whether they submitted to peer pressure. Those who changed their decision due to peer pressure showed significantly greater regret for their decision than those who did not change their answer, while there was no significant difference between those who changed and those who did not change where no peer pressure was involved. The authors also analyzed the results from the perspective of each examinee’s Big Five personality characteristics, and the results suggested a negative correlation between an extraverted personality and the intensity of regret among those who did not change their decision despite peer pressure to do so.
{"title":"How an Incorrect Decision Caused by Peer Pressure and Personality Affects Regret","authors":"A. Matsumae, Sei Hadano","doi":"10.54941/ahfe1001116","DOIUrl":"https://doi.org/10.54941/ahfe1001116","url":null,"abstract":"The authors conducted experimental research using two examinee groups, one with peer pressure and one without, to compare the intensity of regret for an incorrect decision. The results show statistically significant differences be-tween the two groups, depending on whether they submitted to peer pressure. Those who changed their decision due to peer pressure showed significantly greater regret for their decision than those who did not change their answer, while there was no significant difference between those who changed and those who did not change where no peer pressure was involved. The authors also analyzed the results from the perspective of each examinee’s Big Five personality characteristics, and the results suggested a negative correlation between an extraverted personality and the intensity of regret among those who did not change their decision despite peer pressure to do so.","PeriodicalId":116806,"journal":{"name":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116585346","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}
M. Jongprasithporn, N. Yodpijit, Thanaporn Nunthawarasilp
Blue light is the light that harmful to health in the long term. Understanding the dangers of blue light could prevent blue light hazards. This study aims to understand the basic knowledge and dangers of blue light. How it could harm people during using computers, tablets, and smartphones as well as to assess the level of knowledge about the usage and dangers of blue light. A questionnaire was used to study the behavior of electronic device users. 150 participants answered the questionnaire about personal information, the dangers of blue light, and the blue light prevention. The results showed that majority of participants have the basic understanding about blue light. People in age range 18-30 years old are most damaged by blue light more than people age 15-17 years old and 31-60 years old respectively. If the people do not protect their eyes, they might have blurred vision or in the worst case they might lose their vision.
{"title":"Understanding Harmful Blue Light in a group of Thai People","authors":"M. Jongprasithporn, N. Yodpijit, Thanaporn Nunthawarasilp","doi":"10.54941/ahfe1001206","DOIUrl":"https://doi.org/10.54941/ahfe1001206","url":null,"abstract":"Blue light is the light that harmful to health in the long term. Understanding the dangers of blue light could prevent blue light hazards. This study aims to understand the basic knowledge and dangers of blue light. How it could harm people during using computers, tablets, and smartphones as well as to assess the level of knowledge about the usage and dangers of blue light. A questionnaire was used to study the behavior of electronic device users. 150 participants answered the questionnaire about personal information, the dangers of blue light, and the blue light prevention. The results showed that majority of participants have the basic understanding about blue light. People in age range 18-30 years old are most damaged by blue light more than people age 15-17 years old and 31-60 years old respectively. If the people do not protect their eyes, they might have blurred vision or in the worst case they might lose their vision.","PeriodicalId":116806,"journal":{"name":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121735410","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}
Mónica-Daniela Gómez-Rios, Nestor-Raul Martillo-Martinez, Miguel A. Quiroz-Martínez, Maikel Leyva-Vázquez
In the medical field, it has been necessary to provide resources to detect early-stage diseases, including breast cancer. Deep learning is immersed in all aspects of medical image analysis, catapulting it as a possible dominant autonomous technology. In this systematic review, a total of 250 results were located, of which 40 were selected, for which a quantitative methodology with a descriptive basis was chosen. The objective of this bibliometric review is to analyze models in image processing for the early detection of breast cancer using deep learning. As result, digital mammography is the most effective method for detecting abnormalities in images. The research concludes that the application of CNN (Convolutional Neural Networks) is the most preferred choice of experts for medical image analysis due to its powerful pattern recognition and feature classifier.
{"title":"Tracking Knowledge Evolution, Hotspots and future directions of Breast Cancer Detection using Deep Learning: A bibliometrics Review","authors":"Mónica-Daniela Gómez-Rios, Nestor-Raul Martillo-Martinez, Miguel A. Quiroz-Martínez, Maikel Leyva-Vázquez","doi":"10.54941/ahfe1001164","DOIUrl":"https://doi.org/10.54941/ahfe1001164","url":null,"abstract":"In the medical field, it has been necessary to provide resources to detect early-stage diseases, including breast cancer. Deep learning is immersed in all aspects of medical image analysis, catapulting it as a possible dominant autonomous technology. In this systematic review, a total of 250 results were located, of which 40 were selected, for which a quantitative methodology with a descriptive basis was chosen. The objective of this bibliometric review is to analyze models in image processing for the early detection of breast cancer using deep learning. As result, digital mammography is the most effective method for detecting abnormalities in images. The research concludes that the application of CNN (Convolutional Neural Networks) is the most preferred choice of experts for medical image analysis due to its powerful pattern recognition and feature classifier.","PeriodicalId":116806,"journal":{"name":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122235039","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}
María Judith López, Jaime Moscoso-Salazar, V. Ramos, C. Ramos-Galarza
Addictions are part of psychopathological disorders. They encompass an obsessive behavior towards the consumption of psychotropic substances, activities, or relations. In the psychological treatment of these issues, procedures based on behavioral and cognitive behavioral techniques are applied through the traditional approach during sessions. The development of mobile apps for smartphones has resulted in a relevant contribution to the treatment of addictions and therefore a series of technological innovations are currently available to aid the clinical work within this context. This article reviews the main apps developed for this purpose.
{"title":"Technological Innovations for the Treatment of Addictions","authors":"María Judith López, Jaime Moscoso-Salazar, V. Ramos, C. Ramos-Galarza","doi":"10.54941/ahfe1001100","DOIUrl":"https://doi.org/10.54941/ahfe1001100","url":null,"abstract":"Addictions are part of psychopathological disorders. They encompass an obsessive behavior towards the consumption of psychotropic substances, activities, or relations. In the psychological treatment of these issues, procedures based on behavioral and cognitive behavioral techniques are applied through the traditional approach during sessions. The development of mobile apps for smartphones has resulted in a relevant contribution to the treatment of addictions and therefore a series of technological innovations are currently available to aid the clinical work within this context. This article reviews the main apps developed for this purpose.","PeriodicalId":116806,"journal":{"name":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129481010","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}
Henry Javier, William Cochachi, G. Quispe, Heyul Chavez, Luis Rivera, Francisco Dominguez
The research designs and developed a biofertilizer from Mycorrhiza and Rhizobium evaluating its antagonistic capacity and biotization in the cultivation of vegeta-bles with a DCA, the sample considers potatoes, peas and barley in the District of Huasahuasi, with 9 treatments in three formulas, considering a control group without inoculation and two repetitions. As a result, the optimal formula is ob-tained with 300g of mycorrhiza and Rhizobium strains + 500g of black soil + 200g of potato peel bran, which has an effective antagonistic capacity of 100% in pea crops, 90% in the barley and 85% in the potato, besides that it achieves a bio-tization in the pea crop of 95%, in the barley 100% and in the potato 90%.
{"title":"Biomaterials and Technologies for Sustainability","authors":"Henry Javier, William Cochachi, G. Quispe, Heyul Chavez, Luis Rivera, Francisco Dominguez","doi":"10.54941/ahfe1001193","DOIUrl":"https://doi.org/10.54941/ahfe1001193","url":null,"abstract":"The research designs and developed a biofertilizer from Mycorrhiza and Rhizobium evaluating its antagonistic capacity and biotization in the cultivation of vegeta-bles with a DCA, the sample considers potatoes, peas and barley in the District of Huasahuasi, with 9 treatments in three formulas, considering a control group without inoculation and two repetitions. As a result, the optimal formula is ob-tained with 300g of mycorrhiza and Rhizobium strains + 500g of black soil + 200g of potato peel bran, which has an effective antagonistic capacity of 100% in pea crops, 90% in the barley and 85% in the potato, besides that it achieves a bio-tization in the pea crop of 95%, in the barley 100% and in the potato 90%.","PeriodicalId":116806,"journal":{"name":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117034830","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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