Human-system Interaction Research Articles

Design of Hotel Human Interaction System Based on Deep Learning

This paper designs a hotel human-computer interaction (HCI) system which is based on deep learning. The whole system mainly includes face detection, speech synthesis, and speech recognition. Real time face detection is realized by transplanting the Opencv library into the Android system and combining that with the AdaBoost algorithm. Furthermore, the local speech recognition is realized through the special chip for speech recognition hbr740, while the local speech synthesis is realized through the special chip for speech synthesis syn6288. Subsequently, the massive speech resources are obtained through the network connection into the iFLYTEK’s open platform, which can realize online speech recognition, semantic understanding, and speech synthesis. In the data flow phase, we transmit data to the lower computer through the serial port of tiny4412 in order to realize the motion control of the lower computer. This is achieved through the SQLite database for system voice interaction and motion control, which is built through the jar package of the Litepal and POI. Finally, a hybrid voice interaction system is designed combining the local voice interaction with the online voice interaction. Through numerical simulation, the suggested system is tested to verify the feasibility of the hybrid voice interaction scheme. We observed that when the network is in good condition, the speech recognition rate of the whole system reaches as high as 94.67%; while without the network, the speech recognition rate can still reaches up to 84.67%. The attained outcomes demonstrate the superiority of the suggested hybrid system.

Exo-Abs: A Wearable Robotic System Inspired by Human Abdominal Muscles for Noninvasive and Effort-Synchronized Respiratory Assistance

Existing technologies for patients with respiratory insufficiency have focused on providing reliable assistance in their breathing. However, the need for assistance in other everyday respiratory functions, such as coughing and speaking, has remained unmet in these patients. Here, we propose Exo-Abs, a wearable robotic system that can universally assist wide-ranging respiratory functions by applying compensatory force to a user's abdomen in synchronization with their air usage. Inspired by how human abdominal muscles transmit pressure to the lungs via abdominal cavity compression, a biomechanically interactive platform was developed to optimally utilize the abdominal compression while aligning the assistance with a user's spontaneous respiratory effort. In addition to the compact form factor, thorough analytic procedures are described as initial steps toward taking the human respiratory system into the scope of robotics technology. We demonstrate the validity of the overall human–system interaction with the assistance performance under three essential respiratory functions: breathing, coughing, and speaking. Our results show that the system can significantly improve the performance of all these functions by granting on-demand and self-reliant assistance to its users.

The hybrid method combined STPA and SLIM to assess the reliability of the human interaction system to the emergency shutdown system of LNG ship-to-ship bunkering

By introducing autonomous or software-controlled systems, human operators are increasingly required to perform cognitive-intensive tasks in addition to existing labour-intensive tasks. As a result, it will be more difficult to identify human roles in future complex systems with traditional approaches such as hierarchical task analysis used in the conventional HRA. This paper proposes a novel systematic approach for a human reliability assessment to better understand human activities in complex systems. The proposed framework is a hybrid method combining the System Theoretic Process Analysis (STPA) and the Success Likelihood Index Method (SLIM) to assess the system reliability. The STPA is adopted to analyse the interaction relationship between different system components. The primary purpose of STPA is to find and analyse human activities that affect the risk in human-machine interaction systems. Then the identified human activities are evaluated and quantified by the SLIM as a probability of human error. The system reliability block diagram represents the derived human error probabilities to assess the entire system for a probabilistic risk assessment. Furthermore, the study proposed system alternations by comparing three different system configurations. Results demonstrate the importance of human performance in a complex system where humans, machines, and software interact.

Human Rights Experimentalism in Action: The Potential of National Human Rights Institutions in Enhancing the Implementation and Monitoring of the Convention on the Rights of Persons with Disabilities

AbstractArticle 33(2) of the United Nations Convention on the Rights of Persons with Disabilities provides for the establishment and designation of independent monitoring mechanisms charged with the promotion, protection and monitoring of its implementation. In numerous States parties, National Human Rights Institutions have been designated as Article 33(2) institutions, either individually or in co-ordination with other bodies, and have consequently made effective contributions to the reporting and inquiry procedures of the Committee on the Rights of Persons with Disabilities. Drawing from experimentalist governance theory, this contribution interrogates whether, and to what extent, this dialogue between locally placed actors and institutions (such as National Human Rights Institutions) on the one hand, and internationally situated actors and institutions (such as the Committee) on the other, has the potential to bolster the implementation of the Convention on the Rights of Persons with Disabilities. At its core, experimentalism proffers a normatively attractive vision of how broadly agreed upon goals can be brought to life in a multi-level setting, such as the monitoring mechanism contemplated by the Convention on the Rights of Persons with Disabilities with its unique role and definition for both international and national actors. By analysing Article 33 through an experimentalist governance lens, the contribution thus hopes to highlight a routinely neglected or underestimated aspect of the human rights treaty system, that is, the iterative and dynamic interaction between locally situated actors and institutions and internationally situated actors and institutions, and bring to light what this portends for the Convention’s implementation in reality.

A Design Contribution to Ergonomic PC Mice Development.

Developing new manual computer pointing devices abiding to the requirements set out in ergonomic product design literature necessitates joining contributions from several areas, including the ergonomic guidelines applicable to hand tool design, human–system interaction, and certain user characteristics such as anthropometric data. Computer mice are hand tools enabling the interaction with the computer, for use by people from both sexes and practically all ages. Moreover, the PC mouse’s intensive usage is able to cause musculoskeletal disorders. This paper reports on a study aimed at developing new computer mouse shapes, reducing forearm pronation, and providing hand–palm holding, supported by a literature review and an adequate design methodology, starting from known shapes of commercial products, the traditional (horizontal) computer mouse, and the vertical computer mouse. In this regard, potential concepts were generated as solutions to the previously specified problem through a set of creative tasks based on the specifications. Four new shapes were proposed to be evaluated through an assessment matrix; as a result, two new PC mice geometries were designed and fully prototyped. This study also reports on selected results of usability and an electromyographic evaluation of the prototypes against three commercial PC mice (horizontal, slanted, and vertical) by a sample of 20 participants, supporting validation of the development process and the newly developed geometries, with emphasis on the slanted conical innovative shape.

Voice Assistant ZIA using HDG algorithm

Abstract: In this computerized world, machine human interaction system was more common. For that kind of interaction, we achieve this voice assistant using machine learning and artificial intelligence. Using this we deploy executable code which works according to the user’s voice command. Voice assistants are the kind of software that use voice recognition technology, natural language processing and AI to response humans. using this technology, the device synthesizes the user’s message, breaks it down, evaluates it, and offers a meaningful response in return. So far google assistance, apple’s siri, amazon’s alexa, microsoft’s cortana were being well known assistance but they were all developed for specific platforms. We developed a software that can be bridge with all the platforms, as we did for the windows machine because we mainly concentrated to achieve some more features to give better experience. The purpose of this paper is to build the voice assistant with the speech recognition algorithm, interactional graphical interface and has a voice cloning technology to perform a task. Keywords: Artificial intelligence, Machine learning, Natural language processing, Speech Recognition, Graphical user interface, Voice cloning

Human–System Interaction Based on Eye Tracking for a Virtual Workshop

With the constant exploration and development of intelligent manufacturing, the concept of digital twins has been proposed and applied. In view of the complexity and intellectualization of virtual workshop systems, real workshops can link with virtual workshosp based on AR under the structure of digital twins, which allows users to interact with virtual information and perceive the virtual information superimposed on the real world with great immersion. However, the three-dimensionality of virtual workshops and interaction with complex workshop information can be challenging for users. Due to a shortage of input bandwidth and the nontraditional mode of interaction, a more natural interaction technique for virtual workshops is required. To solve such problems, this paper presents a technical framework for 3D eye movement interaction applied to a virtual workshop. An eye movement interaction technique, oriented to implicit interaction and explicit interaction, is developed by establishing behavior recognition and interaction intention understanding. An eye-movement experiment verifies the former’s accuracy is above 90% and had better recognition performance. A better feature vector group of the latter is selected to establish a model and verify its feasibility and effectiveness. Finally, the feasibility of the framework is verified through the development of an application example.

Extracting Behavior Identification Features for Monitoring and Managing Speech-Dependent Smart Mental Illness Healthcare Systems.

Speech is one of the major communication tools to share information among people. This exchange method has a complicated construction consisting of not the best imparting of voice but additionally consisting of the transmission of many-speaker unique information. The most important aim of this research is to extract individual features through the speech-dependent health monitoring and management system; through this system, the speech data can be collected from a remote location and can be accessed. The experimental analysis shows that the proposed model has a good efficiency. Consequently, in the last 5 years, many researchers from this domain come in front to explore various aspects of speech which includes speech analysis using mechanical signs, human system interaction, speaker, and speech identification. Speech is a biometric that combines physiological and behavioural characteristics. Especially beneficial for remote attack transactions over telecommunication networks, the medical information of each person is quite a challenge, e.g., like COVID-19 where the medical team has to identify each person in a particular region that how many people got affected by some disease and took a quick measure to get protected from such diseases and what are the safety measure required. Presently, this task is the most challenging one for researchers. Therefore, speech-based mechanisms might be useful for tracking his/her voice quality or throat getting affected. By collecting the database of people matched and comparing with his/her original database, it can be identified in such scenarios. This provides the better management system without touching and maintains a safe distance data that can be gathered and processed for further medical treatment. Many research studies have been done but speech-dependent approach is quite less and it requires more work to provide such a smart system in society, and it may be possible to reduce the chances to come into contact with viral effected people in the future and protect society for the same.

Chatbots as Cognitive, Educational, Advisory & Coaching Systems

Chatbots are software applications assimilating human communication with the aim to raise adherence and engagement between human-systems interaction. Text messaging-based conversational agents (CAs) make an interesting use of natural language processing and improve by learning, allowing coherent two-way communication with humans, either oral or written as well as real-time decision-making. Chatbots serve as means of learning and teaching, as virtual assistants and social companions. Machine learning algorithms embedded into Chatbots simulate human cognition, including cognitive learning, decision making and adaptation to the environment. Thus, the future of artificial intelligence in Chatbots lies in the development of a global, reliable and sustainable ecosystem of knowledge, skills and values by bringing together all interested stakeholders, such as scientists, consumers, businesses and the state. Such effective customized/personalized learning frameworks depend on sophisticated conversational flows based on user models, which cluster user preferences and attributes in combination with learning analytics to induce end users’ personal skills, knowledge mastery, learning ability as well as professional development.

Threats Detection during Human-Computer Interaction in Driver Monitoring Systems.

This paper presents an approach and a case study for threat detection during human–computer interaction, using the example of driver–vehicle interaction. We analyzed a driver monitoring system and identified two types of users: the driver and the operator. The proposed approach detects possible threats for the driver. We present a method for threat detection during human–system interactions that generalizes potential threats, as well as approaches for their detection. The originality of the method is that we frame the problem of threat detection in a holistic way: we build on the driver–ITS system analysis and generalize existing methods for driver state analysis into a threat detection method covering the identified threats. The developed reference model of the operator–computer interaction interface shows how the driver monitoring process is organized, and what information can be processed automatically, and what information related to the driver behavior has to be processed manually. In addition, the interface reference model includes mechanisms for operator behavior monitoring. We present experiments that included 14 drivers, as a case study. The experiments illustrated how the operator monitors and processes the information from the driver monitoring system. Based on the case study, we clarified that when the driver monitoring system detected the threats in the cabin and notified drivers about them, the number of threats was significantly decreased.

Interactive Learning System for Learning Calculus

Background: IT tools assist in creating a more participative and independent learning environment. They have brought a new perspective to collaborative learning where students do not just sit in a chair and swallow lecture content but instead participate in creating and sharing knowledge. However, interactivity promoted through the implementation of technology is limited in many cases. Purpose: This research develops an interactive application for learning calculus that promotes human-system interaction via augmented reality (AR) and human-human interaction through chat functions. The study examines the effect of both interactivities on learning experience and how that learning experience affects the performance of learning. Methods: The research adopted a quasi-experimental study design and pre-post test data analysis to evaluate the effect of interactivities on learning experience and consequently the effect of learning experience on learning performance. The subjects were exposed to the developed application for learning the calculus chapter ‘Revolution of Solids” in a controlled environment. The study validated its research framework through partial least squares path modelling and tested three hypotheses via pre-and post-test evaluation. Conclusions: The results found that both interactivities affect learning experience positively; human-human interactivity has a higher impact than human-system interactivity. It was also found that learning performance as part of the learning experience increased from pre-test to post-test.

Predictors of customers’ continuance intention of mobile banking from the perspective of the interactivity theory

In order to test the key factors affecting users' continuance intention of mobile banking Apps, this study combined the Technology acceptance model (TAM) with the perceptual sinteraction model, and further added human-system interaction and perceived privacy security that was not explored in these models before. Data were collected from 349 users who had experience with mobile banking to test the model and were analyzed with a structural equation model. The present study showed that various interactive characteristics of mobile banking (human-human interaction, human-information interaction, human-system interaction) had significant positive impacts on users' perceptions of using mobile banking (perceived usefulness, perceived ease of use, perceived privacy security). Users' perceptions of using mobile banking had significantly positive impacts on users' satisfaction with mobile banking, and user satisfaction had a significant impact on users' continuance intention. Users’ income level had a significantly negative impact on their continuance intention. In order to further enhance users’ continuance intention for mobile banking, designers and managers of mobile banking are suggested to pay special attention to the interactive characteristics of mobile banking and the impact on users' perceptions of mobile banking, so as to improve customer satisfaction and continuous intention.

A response surface methodology to determine the optimal objective function weightings within a multi-objective optimization digital human model used to predict postures

Multi-objective optimization digital human models permit users to predict postures that follow performance criteria, such as minimizing torques. Currently, it is unknown how to weight different objective functions to best predict postures. Objective one was to describe a response surface method to determine optimal objective function weightings to predict lift postures. Objective two was to evaluate the sensitivity of different error calculation methods. Our response surface approach has utility for determining optimal objective function weightings when using a digital human model to evaluate human-system interactions in early design stages. The approach was not dependent on variations in error calculation methods.

How Does Socio-Technical Lock-In Cause Unsustainable Consumption in Cities? A Framework and Case Study on Mobility in Bangkok

Consumption of raw materials, energy, manufactured goods, and services is increasingly concentrated in cities, as urbanization accelerates globally. Such consumption is influenced by complex interactions arising between the various socio-technical and natural systems that make up cities. To improve understanding of the interlinked factors that can perpetuate—or “lock-in”—unsustainable consumption, we build an explanatory framework that conceptually joins the literature on socio-technical systems and on urban consumption. Two questions guide our study: (1) What are the principal socio-technical systems in cities that influence consumption behavior? (2) How do these systems interact to lock urban dwellers into unsustainable consumption behavior? The resulting framework incorporates theories of socio-technical lock-in with factors relating to both “structure” and “agency” in consumption literature. Specifically, it describes the influence and interactions of physical, non-physical, and human systems on two interlinked scales: macro-scale (structure and collectively shared conditions) and micro-scale (agency and individually shaped conditions). To demonstrate the practical value of this framework, we apply it to a case study on mobility in Bangkok, Thailand. This allows us to systematically identify the interlinked mechanisms contributing to the growing dependence on and lock-in to individually owned passenger vehicles. Our study thus provides a comprehensive understanding of the multiplex drivers of consumption behavior, taking into account both structure and agency. The framework also provides a tool for other scholars to empirically identify lock-in mechanisms that hamper the adoption of more sustainable consumption behavior in other sectors and geographies.

Intra-Company Crowdsensing: Datafication with Human-in-the-Loop.

Every day employees learn about things happening in their company. This includes plain facts witnessed while on the job, related or not to one’s job responsibilities. Many of these facts, which we call “occurrence data”, are known by employees but remain unknown to the company. We suppose that some of them are valuable and may improve the company’s situational awareness. In the spirit of mobile crowdsensing, we propose intra-company crowdsensing (ICC), a method of “extracting” occurrence data from employees. In ICC, an employee occasionally responds to sensing requests, each about one plain fact. We elaborate the concept of ICC, proposing a model of human-system interaction, a system architecture, and an organizational process. We position ICC with respect to related concepts from information technology, and we look at it from selected organizational and managerial viewpoints. Finally, we conducted a survey, in which we presented the concept of ICC to employees of different companies and asked for their evaluation. Respondents positive about ICC outnumbered skeptics by a wide margin. The survey also revealed some concerns, mostly related to ICC being perceived as another employee surveillance tool. However, useful and acceptable sensing requests are likely to be found in every organization.

Limitations of the new ISO standard for health and wellness apps

Limitations of the new ISO standard for health and wellness apps

A voice-driven IMU-enabled BIM-based multi-user system for indoor navigation in fire emergencies

Real-time location information between participants is critical but scarcely available during fire emergencies, making response operations solitary and inefficient. To address the issue, this study proposes a system that provides dynamic pathfinding, position tracking, and location sharing to on-site emergency participants via instinctive human-system interactions. The system consists of four modules, namely building information modeling-based indoor route planning, voice-based command processing, inertial sensor-based continuous positioning, and a multi-user sharing environment. The feasibility of the system is assessed by an exploratory user test with a real-world case study. The results show that the system enables participants to track and share locations with others timely and plan a route dynamically for response operations. The results further suggest that the system can potentially provide fundamental techniques to establish new mechanisms for supporting decision-making and enable comparative evaluations on adopted technologies to develop human-centered emergency response systems.

Associations between Wildfire Risk and Socio-Economic-Demographic Characteristics Using GIS Technology

Wildfire is a natural hazard caused mostly by the interaction of human systems and natural phenomena. This research aims to investigate how extreme wildfire events and disasters that occurred in California in the recent three decades are related to socio-economic-demographic characteristics at the levels of census tracts and counties. In addition, this research will use the data of historic wildfires to show counties and census tracts vulnerable to the natural hazard as well as the cyclical changes such as seasonal and annual fluctuations in the wildfire occurrences in the state. To decide how those variables correlate, this research used a Geographic Information System (GIS) designed to collect, analyze, query, and display geographical information. Two types of secondary data were used to conduct the research. One is the geospatial data showing each location of wildfires. The other is the data about such sociodemographic characteristics as race, ethnicity, level of education, and income, which can be collected through the Bureau of Census. In particular, the research employing GIS-based spatial analysis created maps that represent information on the geographic locations of the wildfires at the different geographic levels as well as demographic and socioeconomic factors influenced by the potential risk of wildfires. There are several researching findings. First, this research showed the wildfire-prone communities have comparatively higher level of representation for the populations such as the White and Native Americans. Second, it reveals that Asian people would prefer to reside in communities with a lower level of wildfire risk. In contrast with previous research reporting the Black, Hispanic or Native American people are more vulnerable to wildfire, this research showed only the census tracts with the higher number of the Native Americans are more exposed to the wildfire risk, compared with other census tracts. Third, it revealed that people with a higher level of educational attainment would prefer to reside in communities with a lower level of chemical risk. Forth and lastly, this research indicates that the census tracts that have a higher median household income and median housing price have a negative relationship with the wildfire risk, meaning that people with a higher level of the income or a relatively higher-priced home prefer residing in communities less subject to the natural hazard. Therefore, it can be concluded that associations exist between wildfire risk and certain socio-economic and demographic characteristics.

Modelling of Indian vendors posture using rapid upper limb assessment (RULA)

Ergonomics is an interdisciplinary subject that deals with human interaction with computers, malfunctions, machines, products, and services. For the past two decades it has played a major role in human interaction systems, redesigning many workstations to improve human health and their livelihoods in the context of currency analysis. As per the (MHUPI) ministry of housing and urban poverty alleviation, Govt. of India, there are 10 lakh street merchants operating across the country, of which about 20% are street food vendors. Most of the street vendors are working 8–10 h a day to tell the currency with strange posture. Repetitive work and awkward posture cause many people to experience the ill effects of outer muscle issues (MSD) and business-related constant wounds. This research has been carried out posture risk assessment Indian food street vendors. The risk assessment of MSD was performed on RULA, which based on the questionnaire survey, anthropometry data and posture of vendors. 32 responses were collected and applied on RULA assessment @ CATIA-V5 Software. This study shows the requirement of cart or workstation redesign which are highly expected for un-organized sectors to up-liftment of vendor’s life.

The impact of business simulation games on Vietnamese students’ entrepreneurial intention

In Vietnam, business simulation games have been affirmed as a very effective business learning tool for entrepreneurship education. However, few educators have properly applied them to arouse students' desire to study entrepreneurship. This paper aims to explore the role of human-system interaction and subjective norms (extrinsic) with self-efficacy (intrinsic) in building students’ entrepreneurial intention using the theories of Self-Determination (SDT), and Stimulus-Organism-Response (SOR). The PLS-SEM was employed to analyze the data collected from 195 undergraduates from Vietnam’s southern business universities. The results showed that self-efficacy plays a full mediator between human-system interaction and entrepreneurial intention. Additionally, subjective norms strengthens the effect of human-systems interaction on self-efficacy, implying that subjective norms plays a moderating role in this connection. It is anticipated that the study's findings will provide practical applications for universities' boards of management, game designers, and future researchers to focus on developing entrepreneurship that accommodates students’ values.