Masaru Ito, Chiaki Raima, Seiji Saiki, Yoichiro Yamazaki, Y. Kurita
{"title":"A Study on Machine Instability Feedback During Digging Operation in Teleoperated Excavators","authors":"Masaru Ito, Chiaki Raima, Seiji Saiki, Yoichiro Yamazaki, Y. Kurita","doi":"10.1109/HSI49210.2020.9142685","DOIUrl":"https://doi.org/10.1109/HSI49210.2020.9142685","url":null,"abstract":"The construction industry in Japan has a shortage of workers and skilled operators because of the decrease in the working population due to the low birth rate and aging population. The number of operators of hydraulic excavators, which account for the largest proportion of construction machinery, is also decreasing and it has become difficult to employ operators with expert skills. Teleoperated hydraulic excavators can address this problem. It is difficult, however, to carry out safe and efficient construction work using a teleoperated excavator because of the lack of information available to the operator, such as the posture of the machinery and condition of the work object, in comparison with operating an actual excavator. Therefore, we propose a machine instability feedback system that calculates the attachment posture and digging reaction force and feeds the hydraulic excavator power margin directly back to the operator. This becomes an index of the margin until the excavator body, not the attachment, starts to move by the digging reaction force. We conducted a subject study using an excavator simulator to verify the effect of presenting the machine instability information to the operator. The results confirm that the operator could safely carry out digging work with acceptable work efficiency when machine instability information was provided.","PeriodicalId":371828,"journal":{"name":"2020 13th International Conference on Human System Interaction (HSI)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133220347","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}
{"title":"Decision making approaches optimizing the benefits of fully autonomous and connected collective cars","authors":"Jennie Lioris, N. Bhouri","doi":"10.1109/HSI49210.2020.9142643","DOIUrl":"https://doi.org/10.1109/HSI49210.2020.9142643","url":null,"abstract":"An Intelligent Transportation System (ITS) operating without prior reservations while offering high quality, door-to-door services at reduced fares is studied. The structure, comprised of fully autonomous cars, covers arbitrary urban areas and operates without prior reservations. Specifically developed control algorithms based on Optimization, Operations Research and Artificial Intelligence optimize the system management for any demand level and geometry. Due to V2V, V2I and V2C connectivity a fast and secure information update is achieved. Well-adapted itineraries considering customer preferences are dynamically defined. Idle vehicles are controlled and travel durations are reduced. Adequate use of the available vehicle capacity allows an important reduction of the costs for both cars and users. A comparative study with a self-service manually driven car scheme is also introduced. Qualitative and quantitative measurements appraise the system perfomance. The presented micro transit scheme in association with innovative technology (UV light sanitizing cars) could form a successful and affordable alternative for all involved entities commuters, traffic and environment under pandemic crisis where mass public transport operators increase traveller risks.","PeriodicalId":371828,"journal":{"name":"2020 13th International Conference on Human System Interaction (HSI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133812141","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}
{"title":"Dominate and Non-dominate Hand Prediction for Handheld Touchscreen Interaction","authors":"Li Liu, Shen Huang","doi":"10.1109/HSI49210.2020.9142634","DOIUrl":"https://doi.org/10.1109/HSI49210.2020.9142634","url":null,"abstract":"People have their individual preference of which hand they preferentially use to do certain things. It is not unusual to see them use mobile devices with a touchscreen one-handedly. Depending on where they are and what they do, people may use one hand over the other to hold and interact with mobile devices. Few studies have looked into the implication of using a preferred hand versus a non-preferred in touchscreen interaction on mobile devices. As the screen size increases, the difference between using a preferred hand and a non-preferred hand on the touchscreen becomes more significant. In this paper, we show how to extract features from 3 different interaction gestures on touchscreen, tap, swipe, and drag to learn if a user is using the dominant hand or the non-dominant hand. We compare the performance of using different sets of features in prediction by considering the constraints of handheld devices. A random forest-based prediction system is also created and enhanced to recognize if the user is using a preferred hand or a non-preferred hand. This technique enables the user interface of a touchscreen to adapt to which hand the user hold and interact with mobile devices.","PeriodicalId":371828,"journal":{"name":"2020 13th International Conference on Human System Interaction (HSI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133378587","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}
Mohsen Parisay, Charalambos (Charis) Poullis, Marta Kersten-Oertel
{"title":"FELiX: Fixation-based Eye Fatigue Load Index A Multi-factor Measure for Gaze-based Interactions","authors":"Mohsen Parisay, Charalambos (Charis) Poullis, Marta Kersten-Oertel","doi":"10.1109/HSI49210.2020.9142677","DOIUrl":"https://doi.org/10.1109/HSI49210.2020.9142677","url":null,"abstract":"Eye fatigue is a common challenge in eye tracking applications caused by physical and/or mental triggers. Its impact should be analyzed in eye tracking applications, especially for the dwell-time method. As emerging interaction techniques become more sophisticated, their impacts should be analyzed based on various aspects. We propose a novel compound measure for gaze-based interaction techniques that integrates subjective NASA TLX scores with objective measurements of eye movement fixation points. The measure includes two variations depending on the importance of (a) performance, and (b) accuracy, for measuring potential eye fatigue for eye tracking interactions. These variations enable researchers to compare eye tracking techniques on different criteria. We evaluated our measure in two user studies with 33 participants and report on the results of comparing dwell-time and gaze-based selection using voice recognition techniques.","PeriodicalId":371828,"journal":{"name":"2020 13th International Conference on Human System Interaction (HSI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133047579","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}
{"title":"Resolution Irrelevant Encoding and Difficulty Balanced Loss Based Network Independent Supervision for Multi-Person Pose Estimation","authors":"Haiyang Liu, Dingli Luo, Songlin Du, T. Ikenaga","doi":"10.1109/HSI49210.2020.9142625","DOIUrl":"https://doi.org/10.1109/HSI49210.2020.9142625","url":null,"abstract":"Sustainable efforts are made to improve the accuracy performance in multi-person pose estimation, but the current accuracy is still not enough for real-world applications. Besides, most improvement approaches are designed for special basement networks and ignore the speed performance, which results in limited applicability and low cost-performance. This paper proposes two network independent supervision: Resolution Irrelevant Encoding and Difficulty Balanced Loss. The proposed methods reorganize task representatives, the loss calculation method, and the loss punishment ratio in one-stage pose estimation frameworks to improve the joints' location accuracy with general applicability and high computational efficiency. Resolution Irrelevant Encoding fuses heatmaps and proposed inner block offsets to fix pixel-level joints positions without resolution limitations. To improve network training efficiency, Difficulty Balanced Loss adjusts loss weight in spatial and sequential aspects. On the MS COCO keypoints detection benchmark, the mAP of OpenPose trained with our proposals outperforms the OpenPose baseline over 4.9%.","PeriodicalId":371828,"journal":{"name":"2020 13th International Conference on Human System Interaction (HSI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125862184","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}
{"title":"Stickiness: Does It Apply To Gen X?","authors":"Jeffinsen Kurnia, Wella","doi":"10.1109/HSI49210.2020.9142667","DOIUrl":"https://doi.org/10.1109/HSI49210.2020.9142667","url":null,"abstract":"This study aims to find out what variables affect Facebook user stickiness towards generation X with ages around 39–51 years old. Stickiness is the ability to attract and retain users and extend the duration of each use. The model that will be used in this study involves nine factors that influence stickiness based on previous research, such as interaction quality, hedonic value, utilitarian value, sociability value, confirmation, perceived currency, perceived responsiveness, satisfaction, and usage intention. The data analysis method that will be used in this study is partial least square-structural equation modeling (PLS-SEM). The number of samples obtained in this study is 200 samples from generation X. The results of the research on the X generation sample show that the satisfaction variable mediates between the hedonic value variable and perceived currency against stickiness. Then, the stickiness variable mediates between satisfaction and the usage intention variable.","PeriodicalId":371828,"journal":{"name":"2020 13th International Conference on Human System Interaction (HSI)","volume":"207 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121544817","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}
{"title":"Explicitly Defined Sampling Categories for ESA on a Bipartite Graph","authors":"Mateusz Ozga, J. Szymański","doi":"10.1109/HSI49210.2020.9142653","DOIUrl":"https://doi.org/10.1109/HSI49210.2020.9142653","url":null,"abstract":"This paper presents a study of extensions of the Explicit Semantic Analysis (ESA) used for text representation. The standard ESA algorithm leads to allocation of blocks of words in $(mathcal{O} vert V_2vert times n)$ time on average, where n is the size of the words in text corpora being the subject of analysis and $vert V_2vert$ stands for the size of the vocabulary. Proposed extensions have been based on the selection of training data for ESA and employs for that purpose the category structure of Wikipedia called CESA. The paper proposes the metrics for evaluation of the quality and test the performance of the methods in the function of the training data size. We also study the influence of these methods on the quality of the representation. We established that the total number of queries in case of training is $(mathcal{O} vert D subseteq V_2vert times n)$. Furthermore, the CESA method leads to allocation of blocks of words in $mathcal{O} (vert V_{1} times V_{2} vert times n)$ time on average, and $mathcal{O} (vert V_{1} times V_{2} vert times n)$ time on worse case.","PeriodicalId":371828,"journal":{"name":"2020 13th International Conference on Human System Interaction (HSI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128354835","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}
{"title":"A systemic approach for a well-documented situation awareness in human-centered automation systems","authors":"Hind Bouami, P. Millot","doi":"10.1109/HSI49210.2020.9142651","DOIUrl":"https://doi.org/10.1109/HSI49210.2020.9142651","url":null,"abstract":"Automation has led to cost savings, increased safety, and efficiency, in high risk and complex systems such as the Nuclear Power Plant (NPP) Industry and medication dispensing process in hospitals. However, automation can also lead to critical risks and malfunctions due to a misunderstanding of the system and its automation, a mistrust of automation, or a lack of appropriate automation [2]. Knowledge about systems and automation will help human agents to document their situation awareness so they can understand system's complexity fully, and make decisions to ensure an appropriate systems' automation. This paper describes a diagnosis study based on our systemic approach to document medical operators' situation awareness about medication dispensing process functions, tasks, and risks, within both therapy management (care units) and logistic medication dispensing (pharmacy) circuits of drug dispensing process. Our methodology helps medical agents to document their situation awareness about major types of medication errors in unit care and pharmacy, and the allocation of automated and nonautomated solutions to control medication errors and malfunctions of drug dispensing process. It appears that automation can control 36% of identified medication errors in care units and 27% of identified medication errors in pharmacy. As automation is a non-self-sustaining leverage, they also have to secure their system with complementary human-based solutions. Automation systems have to be secured and reinforced by a relevant redeployment of freed medical agents in care units, to ensure full control of medication dispensing risks.","PeriodicalId":371828,"journal":{"name":"2020 13th International Conference on Human System Interaction (HSI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128984321","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}
{"title":"Human System Interaction for Elderly and Disabled","authors":"","doi":"10.1109/hsi49210.2020.9142682","DOIUrl":"https://doi.org/10.1109/hsi49210.2020.9142682","url":null,"abstract":"Human System Interaction for Elderly and Disabled","PeriodicalId":371828,"journal":{"name":"2020 13th International Conference on Human System Interaction (HSI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125722362","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}
{"title":"A Cost-Effective Automatic Dial Meter Reader Using a Lightweight Convolutional Neural Network","authors":"Cheng-Hung Lin, Kuan-Yi Kuo","doi":"10.1109/HSI49210.2020.9142669","DOIUrl":"https://doi.org/10.1109/HSI49210.2020.9142669","url":null,"abstract":"With the vigorous development of the Internet of Things technology, the government has gradually phased out the traditional meter and began the era of smart meters. However, the replacement of smart meters is expensive and the yield is too low, which has led to the slow deployment of smart meters. Our idea is to develop a low-cost alternative solution that uses an edge device with a camera to automatically identify traditional electric dial meters, and then uploads the identified value to cloud servers. In the past, there have been studies to automatically read dial meters through traditional image segmentation methods. However, because traditional electric meters are mostly set in an environment with high concealment, dim light, and dirt, it is difficult for traditional methods to obtain good identification results for unclear meter images. In this paper, we propose a cost-effective automatic dial meter reader with a lightweight convolutional neural network on edge devices. In order to easily deploy and improve the accuracy of dial meter recognition, the proposed meter reader has the ability to automatically adjust tilt meter images. Experimental results show that the proposed lightweight convolutional neural network achieves significant improvements in segmentation errors, false positives, and elapsed time compared with the relative approaches.","PeriodicalId":371828,"journal":{"name":"2020 13th International Conference on Human System Interaction (HSI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130379779","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}