Jason Thai, Carolina Díaz Piedra, Leandro Luigi Di Stasi, Sašo Tomažič, Kristina Stojmenova, Jaka Sodnik
In this paper we present a study aimed at distinguishing elderly (over 65 years) and young (under 25) participants in driving environment by observing solely their eye movements. Selected groups of elderly and young drivers were asked to drive 30 km on suburban, urban and regional roads in a high-fidelity motion-based driving simulator. During the drive their gaze behaviour and eye movements were recorded using the Tobii Pro Glasses 2 eye tracker, providing data on gaze position, blink rate and pupil size. The data was processed with the PyGaze library, which was adapted to be compatible with the Tobii Pro data output format. In the next step, a decision tree-based binary classification method was applied to distinguish between the two age groups based solely on their eye movements and pupillary responses. The machine learning approach showed an overall accuracy of 0.8 which means that eye tracking data can be a very good predictor of driver’s age in a driving environment.
在本文中，我们提出了一项研究，旨在通过观察老年人(65岁以上)和年轻人(25岁以下)在驾驶环境中的眼球运动来区分他们。经过挑选的老年人和年轻人驾驶组被要求在一个高保真的基于动作的驾驶模拟器中在郊区、城市和地区道路上行驶30公里。在驾驶过程中，研究人员使用Tobii Pro Glasses 2眼动仪记录了他们的凝视行为和眼球运动，提供了凝视位置、眨眼频率和瞳孔大小的数据。使用PyGaze库处理数据，该库经过调整以与Tobii Pro数据输出格式兼容。下一步，采用基于决策树的二值分类方法，仅根据他们的眼球运动和瞳孔反应来区分两个年龄组。机器学习方法的总体精度为0.8，这意味着眼动追踪数据可以很好地预测驾驶环境中驾驶员的年龄。
{"title":"Can We Distinguish Driver’s Age Based on Their Eye Movements?","authors":"Jason Thai, Carolina Díaz Piedra, Leandro Luigi Di Stasi, Sašo Tomažič, Kristina Stojmenova, Jaka Sodnik","doi":"10.54941/ahfe1004394","DOIUrl":"https://doi.org/10.54941/ahfe1004394","url":null,"abstract":"In this paper we present a study aimed at distinguishing elderly (over 65 years) and young (under 25) participants in driving environment by observing solely their eye movements. Selected groups of elderly and young drivers were asked to drive 30 km on suburban, urban and regional roads in a high-fidelity motion-based driving simulator. During the drive their gaze behaviour and eye movements were recorded using the Tobii Pro Glasses 2 eye tracker, providing data on gaze position, blink rate and pupil size. The data was processed with the PyGaze library, which was adapted to be compatible with the Tobii Pro data output format. In the next step, a decision tree-based binary classification method was applied to distinguish between the two age groups based solely on their eye movements and pupillary responses. The machine learning approach showed an overall accuracy of 0.8 which means that eye tracking data can be a very good predictor of driver’s age in a driving environment.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135262494","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}
Irina Kurnikova, Shirin Gulova, Natalia Danilina, Artyom Yurovsky, Vladimir Terekhov
According to the World Health Organization (WHO), over 1 billion people are overweight and 600 million are obese, with metabolic syndrome (MS) affecting 35% of adults in the US and 20-25% in Europe. MS patients require appropriate therapy with comorbidity in mind, which requires further study and optimization. As part of the study, we conducted Holter ECG monitoring (HM) of patients with MS. MS was diagnosed on the basis of the MTP 3rd revision criteria. Additional criteria were AH, elevated triglyceride levels, decreased HDL cholesterol levels, impaired glucose tolerance (IGT), impaired fasting glycemia (EGS), and combined EGS/IGT disorders. MS was diagnosed based on 3 criteria: 1 main and 2 additional ones.Design. A total of 154 patients were examined in in-patient setting. They were subdivided into 2 main groups: Group I - patients with MS receiving β-blockers (n-97) to treat AH; Group II - patients with MS not receiving β-blockers (n-57).Each main group was divided according to the degree of obesity according to the WHO classification. Each patient underwent HM with programmed computer analysis of the wave spectrum of the obtained data and allocation of frequencies - 0.004-0.08 Hz (very low frequency - VLF); 0.09-0.16 Hz (low frequency - LF); 0.17-0.5 Hz (high frequency - HF) more than 0.5 Hz (ultra-low frequency waves - ULF); two coefficients are calculated - LF/HF (vagosympathetic balance coefficient) - ratio of low frequency waves power (LF) to high frequency waves power (HF), and centralization index (CI) - ratio of central regulation circuit activity to autonomic one (LF+VLF/HF).Results. Analysis found changes in HF, LF, and ULF domains of HRV spectrum, indicating transition to a more energy-intensive level of control and depletion of regulatory mechanisms. ULF(%) values above 6.9 require correction with β-blockers. The study found ULF% and VLF% values to be higher in the non-β-blocker group and administration of β-blockers resulted in normalization of indexes with the index of centralization and vagosympathetic balance. In patients receiving β-blockers, the values of these parameters corresponded to those of patients with normal body weight. In MS patients not receiving β-blockers, ULF% was 50% higher and VLF was 18% higher than in the normal weight group. The centralization index was elevated to 3.5. Administration of drugs to 17 patients in group II resulted in normalization of the indexes and achievement of the same values as in group I patients. At the dynamic follow-up for 2 years, Group I patients had no cardiovascular events. The 40 patients who refused to change therapy had no change in HM values and 27% of these patients had acute cardiovascular events at 2 years.Conclusion:Daily ECG monitoring with assessment of ULF%, VLF% and IC indices is a more subtle method of investigation, which allows to detect latent disorders of regulatory mechanisms (with seeming clinical well-being) in patients with disorders of these indices the ri
{"title":"Computerized heart rate analysis in the selection of therapy for patients with arterial hypertension","authors":"Irina Kurnikova, Shirin Gulova, Natalia Danilina, Artyom Yurovsky, Vladimir Terekhov","doi":"10.54941/ahfe1004369","DOIUrl":"https://doi.org/10.54941/ahfe1004369","url":null,"abstract":"According to the World Health Organization (WHO), over 1 billion people are overweight and 600 million are obese, with metabolic syndrome (MS) affecting 35% of adults in the US and 20-25% in Europe. MS patients require appropriate therapy with comorbidity in mind, which requires further study and optimization. As part of the study, we conducted Holter ECG monitoring (HM) of patients with MS. MS was diagnosed on the basis of the MTP 3rd revision criteria. Additional criteria were AH, elevated triglyceride levels, decreased HDL cholesterol levels, impaired glucose tolerance (IGT), impaired fasting glycemia (EGS), and combined EGS/IGT disorders. MS was diagnosed based on 3 criteria: 1 main and 2 additional ones.Design. A total of 154 patients were examined in in-patient setting. They were subdivided into 2 main groups: Group I - patients with MS receiving β-blockers (n-97) to treat AH; Group II - patients with MS not receiving β-blockers (n-57).Each main group was divided according to the degree of obesity according to the WHO classification. Each patient underwent HM with programmed computer analysis of the wave spectrum of the obtained data and allocation of frequencies - 0.004-0.08 Hz (very low frequency - VLF); 0.09-0.16 Hz (low frequency - LF); 0.17-0.5 Hz (high frequency - HF) more than 0.5 Hz (ultra-low frequency waves - ULF); two coefficients are calculated - LF/HF (vagosympathetic balance coefficient) - ratio of low frequency waves power (LF) to high frequency waves power (HF), and centralization index (CI) - ratio of central regulation circuit activity to autonomic one (LF+VLF/HF).Results. Analysis found changes in HF, LF, and ULF domains of HRV spectrum, indicating transition to a more energy-intensive level of control and depletion of regulatory mechanisms. ULF(%) values above 6.9 require correction with β-blockers. The study found ULF% and VLF% values to be higher in the non-β-blocker group and administration of β-blockers resulted in normalization of indexes with the index of centralization and vagosympathetic balance. In patients receiving β-blockers, the values of these parameters corresponded to those of patients with normal body weight. In MS patients not receiving β-blockers, ULF% was 50% higher and VLF was 18% higher than in the normal weight group. The centralization index was elevated to 3.5. Administration of drugs to 17 patients in group II resulted in normalization of the indexes and achievement of the same values as in group I patients. At the dynamic follow-up for 2 years, Group I patients had no cardiovascular events. The 40 patients who refused to change therapy had no change in HM values and 27% of these patients had acute cardiovascular events at 2 years.Conclusion:Daily ECG monitoring with assessment of ULF%, VLF% and IC indices is a more subtle method of investigation, which allows to detect latent disorders of regulatory mechanisms (with seeming clinical well-being) in patients with disorders of these indices the ri","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135263414","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}
Sergey Drobinsky, Patrick Korte, Rastislav Pjontek, Armin Janß, Verena Nitsch, Klaus Radermacher
Surgical adverse events can have serious consequences for patients ranging from temporary injuries to death. Thereby, up to 40% of surgical adverse events are preventable and over 60% of causal factors were found to be linked to human factors. To improve surgical performance and safety, computer-assisted surgical (CAS) systems can be used to reduce excessive workloads. This paper presents a method for prospective assessment of surgical task workloads. S-TAWL, developed with the support of a senior neurosurgeon and a usability engineer, consists of three parts: surgical task decomposition, workload rating scale application, and performance shaping factors characterization. For the proposed rating scales, composed of reference operators, relative workloads were determined by 11 neurosurgeons through pairwise comparison. Afterwards, one senior neurosurgeon, not involved in method development, analysed workloads of four common surgical tasks with the proposed method S-TAWL and a reference workload rating method Surg-TLX. Qualitatively, S-TAWL provides more detailed information about workloads with respect to human resources compared to the reference method. Quantitatively, however, the reliability of the results is still limited, as indicated by high standard deviations. Further research is needed to develop reliable and valid rating scales, compute compound workloads and identify overloads. Incorporating quantitative workload assessment in prospective human performance analysis will provide valuable information for targeted model-based design of assistance systems, supporting safe and successful surgery in the future.
{"title":"Development of a Prospective Method for Rating Surgical Task Workloads","authors":"Sergey Drobinsky, Patrick Korte, Rastislav Pjontek, Armin Janß, Verena Nitsch, Klaus Radermacher","doi":"10.54941/ahfe1004382","DOIUrl":"https://doi.org/10.54941/ahfe1004382","url":null,"abstract":"Surgical adverse events can have serious consequences for patients ranging from temporary injuries to death. Thereby, up to 40% of surgical adverse events are preventable and over 60% of causal factors were found to be linked to human factors. To improve surgical performance and safety, computer-assisted surgical (CAS) systems can be used to reduce excessive workloads. This paper presents a method for prospective assessment of surgical task workloads. S-TAWL, developed with the support of a senior neurosurgeon and a usability engineer, consists of three parts: surgical task decomposition, workload rating scale application, and performance shaping factors characterization. For the proposed rating scales, composed of reference operators, relative workloads were determined by 11 neurosurgeons through pairwise comparison. Afterwards, one senior neurosurgeon, not involved in method development, analysed workloads of four common surgical tasks with the proposed method S-TAWL and a reference workload rating method Surg-TLX. Qualitatively, S-TAWL provides more detailed information about workloads with respect to human resources compared to the reference method. Quantitatively, however, the reliability of the results is still limited, as indicated by high standard deviations. Further research is needed to develop reliable and valid rating scales, compute compound workloads and identify overloads. Incorporating quantitative workload assessment in prospective human performance analysis will provide valuable information for targeted model-based design of assistance systems, supporting safe and successful surgery in the future.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135312512","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 construction industry has been one of the most hazardous and waste-generating industries in the United States for decades, due to the unique nature of work and high degree of organizational complexity on jobsites. A number of citations against OSHA (Occupational Safety and Health Administration) 29 CFR (Code of Federal Regulations) 1926 Safety and Health Regulations for Construction, primarily in sections that address fall protection and safety training in construction, appear in OSHA’s annual top 10 list of most frequently cited violations consistently. Innovative, science-based, and technology-driven solutions become more and more utilized in the construction industry. Examples of these solutions include: situated learning approach to improve the effectiveness of training, wearable technology to enhance personal protection, remote-controlled drones to perform various functions specially to improve site security, prevention through design concept to minimize risks, total worker health initiative to advance worker well-being, etc. It is imperative that safety, health, and environmental professionals should attempt to clearly understand the impact of these emerging technologies on construction safety and health, and be able to apply scientific principles to anticipate, identify, analyze, and control workplace hazards within the construction industry. Specifically, the pros and cons of each solution need to be examined and compared in order to identify effective methods to promote sustainable workforce and improve safety and health in construction.
{"title":"Application of Emerging Technologies to Promote Sustainable Workforce in Construction","authors":"Lu Yuan","doi":"10.54941/ahfe1004421","DOIUrl":"https://doi.org/10.54941/ahfe1004421","url":null,"abstract":"The construction industry has been one of the most hazardous and waste-generating industries in the United States for decades, due to the unique nature of work and high degree of organizational complexity on jobsites. A number of citations against OSHA (Occupational Safety and Health Administration) 29 CFR (Code of Federal Regulations) 1926 Safety and Health Regulations for Construction, primarily in sections that address fall protection and safety training in construction, appear in OSHA’s annual top 10 list of most frequently cited violations consistently. Innovative, science-based, and technology-driven solutions become more and more utilized in the construction industry. Examples of these solutions include: situated learning approach to improve the effectiveness of training, wearable technology to enhance personal protection, remote-controlled drones to perform various functions specially to improve site security, prevention through design concept to minimize risks, total worker health initiative to advance worker well-being, etc. It is imperative that safety, health, and environmental professionals should attempt to clearly understand the impact of these emerging technologies on construction safety and health, and be able to apply scientific principles to anticipate, identify, analyze, and control workplace hazards within the construction industry. Specifically, the pros and cons of each solution need to be examined and compared in order to identify effective methods to promote sustainable workforce and improve safety and health in construction.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135312915","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}
Raymond Freth Lagria, Lorelie Grepo, Joy Ann Malapit
This research paper explores the application of topic modelling algorithms to extract user requirements for a mental health-related mobile application. Specifically, the objective is to generate themes efficiently and effectively from Reddit posts related to mental health narratives, stories, calls for help, and knowledge sharing among others. Particularly, this research examines Latent Dirichlet Allocation algorithm to generate themes coming from the posts and validate using a thematic analysis process to check similarities in generated outputs. The output will be used to establish user requirements for a mental wellbeing app to be developed for the academic community. Hence, the significance of this research. The research findings demonstrate utilizing topic modelling has promising results and categorized thematic terms from the Reddit posts. By leveraging the extracted themes, the research team can gain valuable insights into the needs and preferences of their target audience. The results offer practical implications for the design and development of mobile apps that are guided by a user-centered design process that meets the needs and expectations of the target users. The qualitative analysis further validated the relevance of the generated themes.
{"title":"Generation of User Requirements for a Mental Health Mobile Application from an Online Public Forum A Topic Modelling Approach","authors":"Raymond Freth Lagria, Lorelie Grepo, Joy Ann Malapit","doi":"10.54941/ahfe1004380","DOIUrl":"https://doi.org/10.54941/ahfe1004380","url":null,"abstract":"This research paper explores the application of topic modelling algorithms to extract user requirements for a mental health-related mobile application. Specifically, the objective is to generate themes efficiently and effectively from Reddit posts related to mental health narratives, stories, calls for help, and knowledge sharing among others. Particularly, this research examines Latent Dirichlet Allocation algorithm to generate themes coming from the posts and validate using a thematic analysis process to check similarities in generated outputs. The output will be used to establish user requirements for a mental wellbeing app to be developed for the academic community. Hence, the significance of this research. The research findings demonstrate utilizing topic modelling has promising results and categorized thematic terms from the Reddit posts. By leveraging the extracted themes, the research team can gain valuable insights into the needs and preferences of their target audience. The results offer practical implications for the design and development of mobile apps that are guided by a user-centered design process that meets the needs and expectations of the target users. The qualitative analysis further validated the relevance of the generated themes.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135313226","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}
In this study, we aimed to clarify the characteristics of cerebral blood flow during the N-back task for males and for females in the follicular and luteal phases. Near infrared spectroscopy (NIRS) was used to measure Oxyhemoglobin (Oxy-Hb) in the prefrontal cortex during the N-back task. In the analysis, the prefrontal cortex was divided into right and left regions, and the integrated Oxy-Hb value, center of gravity value, and activation rate (initial activation) in the first 5 seconds of the task were calculated for each region. The percentage of correct responses to the N-back task was also calculated. Differences in each representative value among the three groups (follicular phase, luteal phase, and male) were examined. The task correct response rate was lowest in the luteal phase group for males and the luteal phase group (p<.05) and in the follicular phase group and the luteal phase group (p<.05). There were no significant differences between groups in integral and center-of-gravity values, and there were significant differences between groups in the initial activation of CH10-13 (left area) during the 2-back task (p<.05), with the lowest in the luteal phase group among males (p<.05), follicular phase group (p<.05) and luteal phase group (p<.05). A decrease in working memory is suggested in luteal phase women. This may be due to the presence of women with premenstrual syndrome symptoms or to sex hormone effects.
{"title":"Characteristics of Cerebral Blood Flow during Working Memory Tasks - Comparison of the follicular and luteal phases in females and males","authors":"Makiko Aoki, Satoshi Suzuki","doi":"10.54941/ahfe1004391","DOIUrl":"https://doi.org/10.54941/ahfe1004391","url":null,"abstract":"In this study, we aimed to clarify the characteristics of cerebral blood flow during the N-back task for males and for females in the follicular and luteal phases. Near infrared spectroscopy (NIRS) was used to measure Oxyhemoglobin (Oxy-Hb) in the prefrontal cortex during the N-back task. In the analysis, the prefrontal cortex was divided into right and left regions, and the integrated Oxy-Hb value, center of gravity value, and activation rate (initial activation) in the first 5 seconds of the task were calculated for each region. The percentage of correct responses to the N-back task was also calculated. Differences in each representative value among the three groups (follicular phase, luteal phase, and male) were examined. The task correct response rate was lowest in the luteal phase group for males and the luteal phase group (p<.05) and in the follicular phase group and the luteal phase group (p<.05). There were no significant differences between groups in integral and center-of-gravity values, and there were significant differences between groups in the initial activation of CH10-13 (left area) during the 2-back task (p<.05), with the lowest in the luteal phase group among males (p<.05), follicular phase group (p<.05) and luteal phase group (p<.05). A decrease in working memory is suggested in luteal phase women. This may be due to the presence of women with premenstrual syndrome symptoms or to sex hormone effects.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135312942","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}
To improve sleep habits, we will create messages to raise awareness of sleep and examine the effects of messaging on sleep habits. Japanese people, especially children, and workers, sleep less than their counterparts, both men and women, in other countries. As a result, some people "sleep in on weekends," getting a lot of sleep on weekends to secure more sleep. Then, the rhythm becomes disturbed, and it becomes challenging to re-synchronize with the schedule. Therefore, it is necessary to improve sleeping habits to secure a certain amount of sleep. This study will utilize a messaging approach, gain/loss-framing messages. Then, we will investigate which message is more effective for sleep habits according to each participant's values about sleep. This experiment first administered a questionnaire to 130 college students and adults to assess their attitudes and values toward sleep. We conducted an exploratory factor analysis of 83 items of the questionnaire. As a result, factor scores were calculated for each respondent, and a total of six clusters were determined by cluster analysis. For the experiment, a total of 10 participants (college students in their 20s), five each with high factor scores, were selected from the "sleep-oriented" and "sleep-unoriented" types. The selected participants wore wristwatch-type terminals and went to bed after checking the messages sent to them. Participants received each of seven different kinds of gain/loss-framing messages per week. In questionnaires on 14 different messages, participants responded to the acceptability of the messages and changes in their attitudes toward sleep, such as going to bed early, getting up early, and reviewing their daily rhythms. A two-way ANOVA was conducted at the 5% significance level on the change in sleep awareness after confirmation of the sent message and on the evaluation of the acceptability of the sent message. We identified significant differences in sleep awareness in the main effects between clusters and in the interaction between clusters and message type. Sleep-oriented types tended to report more change in sleep awareness with loss-framing messages. In comparison, sleep-unoriented types tended to report more change in sleep awareness with gain-framing messages. Mean sleep time (minutes) during each period was calculated for each participant, and a two-way ANOVA was performed with message content and clusters as factors at a 5% significance level. We didn't find significant differences between clusters, message types, or interactions. However, sleep-oriented types tended to sleep longer than sleep-unoriented types. Furthermore, in both clusters, sleep duration tended to be longer in weeks when they received loss-framing messages than in weeks when they received gain-framing messages. The interventions in this study produced changes in sleep attitudes, but these changes differed across clusters. On the other hand, all clusters showed a trend toward longer sleep duration
{"title":"Effects of Gain/Loss Messages on Reinforcing Motivation to Sleep","authors":"Shugo Ono, Aoi Nambu, Kouki Kamada, Toru Nakata, Takashi Sakamoto, Toshikazu Kato","doi":"10.54941/ahfe1004206","DOIUrl":"https://doi.org/10.54941/ahfe1004206","url":null,"abstract":"To improve sleep habits, we will create messages to raise awareness of sleep and examine the effects of messaging on sleep habits. Japanese people, especially children, and workers, sleep less than their counterparts, both men and women, in other countries. As a result, some people \"sleep in on weekends,\" getting a lot of sleep on weekends to secure more sleep. Then, the rhythm becomes disturbed, and it becomes challenging to re-synchronize with the schedule. Therefore, it is necessary to improve sleeping habits to secure a certain amount of sleep. This study will utilize a messaging approach, gain/loss-framing messages. Then, we will investigate which message is more effective for sleep habits according to each participant's values about sleep. This experiment first administered a questionnaire to 130 college students and adults to assess their attitudes and values toward sleep. We conducted an exploratory factor analysis of 83 items of the questionnaire. As a result, factor scores were calculated for each respondent, and a total of six clusters were determined by cluster analysis. For the experiment, a total of 10 participants (college students in their 20s), five each with high factor scores, were selected from the \"sleep-oriented\" and \"sleep-unoriented\" types. The selected participants wore wristwatch-type terminals and went to bed after checking the messages sent to them. Participants received each of seven different kinds of gain/loss-framing messages per week. In questionnaires on 14 different messages, participants responded to the acceptability of the messages and changes in their attitudes toward sleep, such as going to bed early, getting up early, and reviewing their daily rhythms. A two-way ANOVA was conducted at the 5% significance level on the change in sleep awareness after confirmation of the sent message and on the evaluation of the acceptability of the sent message. We identified significant differences in sleep awareness in the main effects between clusters and in the interaction between clusters and message type. Sleep-oriented types tended to report more change in sleep awareness with loss-framing messages. In comparison, sleep-unoriented types tended to report more change in sleep awareness with gain-framing messages. Mean sleep time (minutes) during each period was calculated for each participant, and a two-way ANOVA was performed with message content and clusters as factors at a 5% significance level. We didn't find significant differences between clusters, message types, or interactions. However, sleep-oriented types tended to sleep longer than sleep-unoriented types. Furthermore, in both clusters, sleep duration tended to be longer in weeks when they received loss-framing messages than in weeks when they received gain-framing messages. The interventions in this study produced changes in sleep attitudes, but these changes differed across clusters. On the other hand, all clusters showed a trend toward longer sleep duration","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135313222","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}
"Industry 4.0," initially a German initiative focused on technological advancements within the industrial sector, has garnered global recognition. Other nations have also initiated similar strategic endeavours, leading to extensive research dedicated to the development and implementation of Industry 4.0 technologies. More recently, the European Commission introduced "Industry 5.0," a decade following the inception of Industry 4.0. While Industry 4.0 is commonly perceived as technology-driven, Industry 5.0 is heralded as value-driven. The coexistence of these two industrial revolutions has spurred significant debates and necessitates thorough explanations. The business sector plays a pivotal role in fostering economic growth. However, the integration of new technology and the growing complexity of products and production processes have direct repercussions on industrial companies and their workforce. Critics of the Industry 4.0 paradigm underscore its technocratic focus on digitalization and novel technologies. Consequently, when Industry 5.0 emerged, discussions regarding its function and rationale gained rapid prominence. Industry 5.0 complements Industry 4.0, emphasizing the pivotal role of workers in the industrial process. Industry 4.0 has facilitated remarkable technological advancements, including additive manufacturing, artificial intelligence, augmented reality, cyber-physical systems, blockchain, and cybersecurity. These technologies address issues like demand fluctuations and market instability by minimizing human involvement in decision-making through the integration of computers, materials, and AI. Nonetheless, Industry 4.0 must surmount challenges in data security, supply chain management, human resource administration, and technological integration. In contrast, Industry 5.0 tackles these challenges with innovations such as predictive maintenance, hyper-customization, cyber-physical cognitive systems, and collaborative robots, placing a strong emphasis on human-centricity. The introduction of Industry 5.0 heralds an anticipated paradigm shift, prioritizing holistic, sustainable, and human-centered value generation. However, the escalating complexity of digitalization poses considerable difficulties, particularly for small and medium-sized businesses (SMEs) with limited resources for effective digitalization initiatives. This study delves into the literature surrounding improvements for both Industry 4.0 and Industry 5.0, addressing issues such as data privacy and technical integration problems. In Industry 5.0, resilience emerges as a crucial factor in enabling hyper-individualization and customized product offerings. Additionally, this study provides a concise exploration of the primary drivers and facilitators of the adoption of these new paradigms. It subsequently conducts a literature-based analysis, examining how these two paradigms differ from three essential perspectives: people, technology, and organizations. Moreover, it of
{"title":"The Paradigm Shift from Industry 4.0 Implementation to Industry 5.0 Readiness","authors":"Arvin Shadravan, Hamid Parsaei","doi":"10.54941/ahfe1004296","DOIUrl":"https://doi.org/10.54941/ahfe1004296","url":null,"abstract":"\"Industry 4.0,\" initially a German initiative focused on technological advancements within the industrial sector, has garnered global recognition. Other nations have also initiated similar strategic endeavours, leading to extensive research dedicated to the development and implementation of Industry 4.0 technologies. More recently, the European Commission introduced \"Industry 5.0,\" a decade following the inception of Industry 4.0. While Industry 4.0 is commonly perceived as technology-driven, Industry 5.0 is heralded as value-driven. The coexistence of these two industrial revolutions has spurred significant debates and necessitates thorough explanations. The business sector plays a pivotal role in fostering economic growth. However, the integration of new technology and the growing complexity of products and production processes have direct repercussions on industrial companies and their workforce. Critics of the Industry 4.0 paradigm underscore its technocratic focus on digitalization and novel technologies. Consequently, when Industry 5.0 emerged, discussions regarding its function and rationale gained rapid prominence. Industry 5.0 complements Industry 4.0, emphasizing the pivotal role of workers in the industrial process. Industry 4.0 has facilitated remarkable technological advancements, including additive manufacturing, artificial intelligence, augmented reality, cyber-physical systems, blockchain, and cybersecurity. These technologies address issues like demand fluctuations and market instability by minimizing human involvement in decision-making through the integration of computers, materials, and AI. Nonetheless, Industry 4.0 must surmount challenges in data security, supply chain management, human resource administration, and technological integration. In contrast, Industry 5.0 tackles these challenges with innovations such as predictive maintenance, hyper-customization, cyber-physical cognitive systems, and collaborative robots, placing a strong emphasis on human-centricity. The introduction of Industry 5.0 heralds an anticipated paradigm shift, prioritizing holistic, sustainable, and human-centered value generation. However, the escalating complexity of digitalization poses considerable difficulties, particularly for small and medium-sized businesses (SMEs) with limited resources for effective digitalization initiatives. This study delves into the literature surrounding improvements for both Industry 4.0 and Industry 5.0, addressing issues such as data privacy and technical integration problems. In Industry 5.0, resilience emerges as a crucial factor in enabling hyper-individualization and customized product offerings. Additionally, this study provides a concise exploration of the primary drivers and facilitators of the adoption of these new paradigms. It subsequently conducts a literature-based analysis, examining how these two paradigms differ from three essential perspectives: people, technology, and organizations. Moreover, it of","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135316648","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}
Michelle Stewart, Andrea Tineo, Benjamin Woodrow, Michael Wasik, Selina Chan
Exposure to extreme heat during physical exertion may impair cognitive and physical abilities commonly known as heat stress. Industrial workers are vulnerable to the effects of extreme heat due to increasing ambient temperatures, tasks with radiant heat exposures, work intensity, and added personal protective equipment (PPE) burden. New wearable sweat sensors may help mitigate heat stress by monitoring physiological signs of dehydration and provide real-time hydration recommendations. As wearable sensors are introduced into the workplace, this study aims to understand whether continuous personal, physiological monitoring is a better indicator of heat stress risk than current, traditional industrial hygiene, environmental monitoring.
{"title":"Continuous personal monitoring and personalized hydration recommendations with wearable sweat sensors to prevent occupational heat stress","authors":"Michelle Stewart, Andrea Tineo, Benjamin Woodrow, Michael Wasik, Selina Chan","doi":"10.54941/ahfe1004205","DOIUrl":"https://doi.org/10.54941/ahfe1004205","url":null,"abstract":"Exposure to extreme heat during physical exertion may impair cognitive and physical abilities commonly known as heat stress. Industrial workers are vulnerable to the effects of extreme heat due to increasing ambient temperatures, tasks with radiant heat exposures, work intensity, and added personal protective equipment (PPE) burden. New wearable sweat sensors may help mitigate heat stress by monitoring physiological signs of dehydration and provide real-time hydration recommendations. As wearable sensors are introduced into the workplace, this study aims to understand whether continuous personal, physiological monitoring is a better indicator of heat stress risk than current, traditional industrial hygiene, environmental monitoring.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135316839","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}
Nowadays the rapid advancements in artificial intelligence (AI) have significantly transformed various industries, including the business ecosystem (Agrawal, A., Gans, J., & Goldfarb, A., 2022). This study aims to examine the multifaceted impact of AI on business ecosystem development, considering both the positive and negative aspects mostly focused on developed countries.The positive effects of AI implementation on the business ecosystem are manifold. AI-powered technologies enhance productivity and efficiency, automate repetitive tasks, and optimize resource allocation(Floridi, L., 2019). Furthermore, AI algorithms enable businesses to gain valuable insights from large volumes of data, leading to improved decision-making processes and the identification of new market trends (Martin, R., & McCrae, D., 2020). However, along with the promising prospects, there are notable concerns surrounding the implementation of AI in the business ecosystem. Ethical issues, such as privacy infringement and data security, arise due to the vast amounts of sensitive information processed by AI systems. (Davenport, T. H., & Ronanki, R. (2018). Furthermore, the concentration of power in AI technologies within a few dominant players can lead to challenges related to market competition and access to AI-driven solutions.This study combines a comprehensive review of existing literature with case studies and expert interviews to provide a balanced assessment of the impact of AI on business ecosystem development. By analyzing real-world examples and industry cases, this research aims to shed light on the practical implications of AI implementation and identify strategies to mitigate potential risks and challenges.The findings of this study will contribute to the ongoing discussions surrounding the integration of AI technologies in the business ecosystem. The results will be of interest to policymakers, business leaders, and researchers, providing valuable insights into harnessing the potential benefits of AI while addressing the associated concerns.
{"title":"The impact of AI on business ecosystem development: pro and contra","authors":"Olga Shvetsova","doi":"10.54941/ahfe1004425","DOIUrl":"https://doi.org/10.54941/ahfe1004425","url":null,"abstract":"Nowadays the rapid advancements in artificial intelligence (AI) have significantly transformed various industries, including the business ecosystem (Agrawal, A., Gans, J., & Goldfarb, A., 2022). This study aims to examine the multifaceted impact of AI on business ecosystem development, considering both the positive and negative aspects mostly focused on developed countries.The positive effects of AI implementation on the business ecosystem are manifold. AI-powered technologies enhance productivity and efficiency, automate repetitive tasks, and optimize resource allocation(Floridi, L., 2019). Furthermore, AI algorithms enable businesses to gain valuable insights from large volumes of data, leading to improved decision-making processes and the identification of new market trends (Martin, R., & McCrae, D., 2020). However, along with the promising prospects, there are notable concerns surrounding the implementation of AI in the business ecosystem. Ethical issues, such as privacy infringement and data security, arise due to the vast amounts of sensitive information processed by AI systems. (Davenport, T. H., & Ronanki, R. (2018). Furthermore, the concentration of power in AI technologies within a few dominant players can lead to challenges related to market competition and access to AI-driven solutions.This study combines a comprehensive review of existing literature with case studies and expert interviews to provide a balanced assessment of the impact of AI on business ecosystem development. By analyzing real-world examples and industry cases, this research aims to shed light on the practical implications of AI implementation and identify strategies to mitigate potential risks and challenges.The findings of this study will contribute to the ongoing discussions surrounding the integration of AI technologies in the business ecosystem. The results will be of interest to policymakers, business leaders, and researchers, providing valuable insights into harnessing the potential benefits of AI while addressing the associated concerns.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135317060","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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