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Advancements in analytical tools have facilitated numerous studies on perceived street quality. However, most have focused on limited aspects of street quality, failing to capture a comprehensive perception. This study introduces a quantitative approach to holistically measure street quality by integrating three key dimensions: visual perception, network accessibility, and functional diversity. Using Beijing and Shanghai as case studies, we employed artificial neural networks to analyze street view images and quantify the visual characteristics of streets. Additionally, street network accessibility was assessed through spatial design network analysis, and functional diversity was evaluated using the entropy of points of interest (POIs) data. The evaluation results were combined using the analytic hierarchy process. The reliability and accuracy of this method were validated through further testing. Our approach offers a human-centered, large-scale measurement framework, providing valuable insights for urban street renewal and design. [ABSTRACT FROM AUTHOR]

Large language models (LLMs) and dialogue agents represent a significant shift in artificial intelligence (AI) research, particularly with the recent release of the GPT family of models. ChatGPT's generative capabilities and versatility across technical and creative domains led to its widespread adoption, marking a departure from more limited deployments of previous AI systems. While society grapples with the emerging cultural impacts of this new societal-scale technology, critiques of ChatGPT's impact within machine learning research communities have coalesced around its performance or other conventional safety evaluations relating to bias, toxicity, and "hallucination." We argue that these critiques draw heavily on a particular conceptualization of the "human-centered" framework, which tends to cast atomized individuals as the key recipients of technology's benefits and detriments. In this article, we direct attention to another dimension of LLMs and dialogue agents' impact: their effects on social groups, institutions, and accompanying norms and practices. By analyzing ChatGPT's social impact through a social-centered framework, we challenge individualistic approaches in AI development and contribute to ongoing debates around the ethical and responsible deployment of AI systems. We hope this effort will call attention to more comprehensive and longitudinal evaluation tools (e.g., including more ethnographic analyses and participatory approaches) and compel technologists to complement human-centered thinking with social-centered approaches. [ABSTRACT FROM AUTHOR]

Avoiding downtime is one of the major concerns of manufacturing industries. In the era of connected industry, acquiring data has become cheaper than ever; however, turning that data into actionable insights for operators is not always straightforward. In this work, we present a manufacturing scenario involving a circular blade rubber cutting machine, where the goal is to minimize downtime. Historical cutting data are available, and the aim is to provide the machine operators with an intuitive tool that helps them reduce this downtime. This work demonstrates how, in an Industry 4.0 environment, data can be leveraged to minimize downtime. To achieve this, different survival model approaches are compared, a Health Index (HI) is developed, and the model deployment is analysed, highlighting the importance of understanding the model as a dynamic system in which the operator plays a key role. [ABSTRACT FROM AUTHOR]

Introduction: In transitioning from Industry 4.0 to the forthcoming Industry 5.0, this research explores the fusion of the humanistic view and technological developments to redefine Continuing Engineering Education (CEE). Industry 5.0 introduces concepts like biomanufacturing and human-centricity, embodying the integration of sustainability and resiliency principles in CEE, thereby shaping the upskilling and reskilling initiatives for the future workforce. The interaction of sophisticated concepts such as Human-Machine Interface and Brain-Computer Interface (BCI) forms a conceptual bridge toward the approaching Fifth Industrial Revolution, allowing one to understand human beings and the impact of their biological development across diverse and changing workplace settings. Methods: Our research is based on recent studies into Knowledge, Skills, and Abilities taxonomies, linking these elements with dynamic labor market profiles. This work intends to integrate a biometric perspective to conceptualize and describe how cognitive abilities could be represented by linking a Neuropsychological test and a biometric assessment. We administered the brief Neuropsychological Battery in Spanish (Neuropsi Breve). At the same time, 15 engineering students used the Emotiv insight device that allowed the EEG recollection to measure performance metrics such as attention, stress, engagement, and excitement. Results: The findings of this research illustrate a methodology that allowed the first approach to the cognitive abilities of engineering students to be from neurobiological and behavioral perspectives. Additionally, two profiles were extracted from the results. The first illustrates the Neuropsi test areas, its most common mistakes, and its performance ratings regarding the students' sample. The second profile shows the interaction between the EEG and Neuropsi test, showing engineering students' cognitive and emotional states based on biometric levels. Discussions: The study demonstrates the potential of integrating neurobiological assessment into engineering education, highlighting a significant advancement in addressing the skills requirements of Industry 5.0. The results suggest that obtaining a comprehensive understanding of students' cognitive abilities is possible, and educational interventions can be adapted by combining neuropsychological approaches with EEG data collection. In the future, it is essential to refine these evaluation methods further and explore their applicability in different engineering disciplines. Additionally, it is necessary to investigate the long-termimpact of thesemethods on workforce preparation and performance. [ABSTRACT FROM AUTHOR]

With the advantages of new technologies and rising demand from customers, it is necessary to improve the manufacturing process. This necessity was recognized by the industry; therefore, the concept of Industry 4.0 has been implemented in various areas of manufacturing and services. The backbone and main aspect of Industry 4.0 is digitalization and the implementation of technologies into processes. While this concept helps manufacturers with the modernization and optimization of many attributes of the processes, Industry 5.0 takes a step further and brings importance to the human factor of industry practice, together with sustainability and resilience. The concept of Industry 5.0 contributes to the idea of creating a sustainable, prosperous, and human-friendly environment within companies. The main focus of the article is to analyze the existing literature regarding what is missing from the successful implementation of human centricity into industry practice, namely in small and medium-sized factories (SMEs). These findings are then presented in the form of requirements and barriers for the implementation of human centricity into SME factories, which can serve as guidelines for implementing human-centered manufacturing using axiomatic design theory in SMEs, which can serve as a roadmap for practitioners. [ABSTRACT FROM AUTHOR]

[Purpose/Significance] Previous studies or reviews of digital twins have focused either on conceptual analysis and theoretical models, or on the current state of the art and implementation, with only a few studies analyzing human-digital twin interaction and collaboration. This paper explores the collaboration between human and digital twin systems, and offers recommendations on how digital twins can catalyze the progress of societal digitization. It envisions a future where the interaction and collaboration between humans and digital twins is not only deepened but also transcended, moving closer to the harmonious integration of man and machine. The proposed strategies aim to unlock the full potential of digital twins in promoting a more connected and intelligent world. [Method/Process] This paper is a systematic literature review focusing on the partnership between human and digital twin systems, emphasizing the role of artificial intelligence. We analyze the value positioning, key technologies and practical applications through 45 papers from home and abroad. Then, we explore the construction path of digital twin technologyenabled information resource management. [Results/Conclusions] The study shows that human and digital twin systems have different unique values in the whole ecology, the irreplaceable wisdom of the human brain is reflected in innovation and decision-making, and the core function of the digital twin system is to support and enhance the communication between man and machine. AI technology plays the role of the pedestal in the interaction. There are common enabling technologies for human intelligence collaboration in the digital twin ecosystem, and the types of key technologies supporting human intelligence collaboration in different twin modules are not identical but synergistic with each other. The supporting technologies in digital twin environment mainly involve data acquisition and data transmission, model twin mainly lies in data fusion and management, image recognition and processing, and process twin mainly involves human-computer interfaces, immersive perception and other key technologies. In terms of application areas, humanintelligent information system cooperation at home and abroad has rich applications in industry, healthcare, smart cities and public cultural services, especially in public cultural services, where cooperation has accelerated the intelligentization process of public cultural service institutions. Finally, the study categorizes the human-intelligent information system collaboration methods in the digital twin ecology into three types: pre-determined, collaborative, and autonomous, proposes a holistic framework for the twin cointelligence system of intelligent connections, and summarizes the current obstacles and development strategies from a realistic perspective. There are some limitations due to the limited samples, which can be increased in the future to deepen the mining and analysis to optimize the form of human-intelligent information system collaboration in the digital twin ecosystem. [ABSTRACT FROM AUTHOR]

Urban heat stress profoundly affects the health of residents. However, current research primarily focuses on quantifying the risk of urban heat based on LST, T a , etc., overlooking the crucial and intimate influence of continuous intense solar radiation on human thermal comfort and health. Simultaneously, there is a lack of smaller units to support more precise planning. This study utilized the radiant heat stress intensity (RHSI) metric concentrating on the intensity and duration of thermal radiation, to develop a thermal-radiation induced health risk (TIHR) assessment system. Leveraging technologies such as the SOLWEIG model, Python, BERT, and GIS enables precise calculations of 12 spatial indices, including RHSI and Weibo heat. This facilitates a more accurate assessment of health risks at the smallest urban units (blocks) and directly guides planning. The application of this workflow in the case of Suoyuwan, Dalian, China, confirms its value, as it can be used to determine which blocks should be prioritized for specific aspects of risk prevention and control. The results show that some blocks exhibited differences in TIHR even within close proximity, with disaster-causing factors varying according to locations. This study proposes a novel assessment framework based on the interactive perspective of thermal radiation-human-activity-space. [ABSTRACT FROM AUTHOR]

Gamification has become prevalent in educational settings, particularly in human-centered software engineering. Using gamified learning environments for comprehending software engineering concepts can significantly enhance students’ human factors, including motivation, engagement, and cognitive and critical thinking skills. Software requirements engineering constitutes one of the disciplines in the software development lifecycle. Based on the literature concerning agile-based software requirements engineering, coping with changing user requirements and constant alterations is often challenging. Consequently, both students and software developers must thoroughly grasp agile-based software requirements engineering. Over the last few years, educators and researchers have crafted gamified learning environments for agile-based software requirements engineering activities. Therefore, this paper aims to investigate the effectiveness of agile-based software requirements engineering activities through a gamified design approach. For this purpose, an application, ReGile, was developed and evaluated with 87 second and third-year software engineering students using the M-3 evaluation framework. Overall, the results were promising. Students expressed satisfaction with ReGile’s technological usability. They performed well (72.14%) in answering questions related to software requirements engineering and agile methodology concepts. Furthermore, gender-wise results indicated that male students outperformed female students when using ReGile.

IntroductionIn transitioning from Industry 4.0 to the forthcoming Industry 5.0, this research explores the fusion of the humanistic view and technological developments to redefine Continuing Engineering Education (CEE). Industry 5.0 introduces concepts like biomanufacturing and human-centricity, embodying the integration of sustainability and resiliency principles in CEE, thereby shaping the upskilling and reskilling initiatives for the future workforce. The interaction of sophisticated concepts such as Human-Machine Interface and Brain-Computer Interface (BCI) forms a conceptual bridge toward the approaching Fifth Industrial Revolution, allowing one to understand human beings and the impact of their biological development across diverse and changing workplace settings.MethodsOur research is based on recent studies into Knowledge, Skills, and Abilities taxonomies, linking these elements with dynamic labor market profiles. This work intends to integrate a biometric perspective to conceptualize and describe how cognitive abilities could be represented by linking a Neuropsychological test and a biometric assessment. We administered the brief Neuropsychological Battery in Spanish (Neuropsi Breve). At the same time, 15 engineering students used the Emotiv insight device that allowed the EEG recollection to measure performance metrics such as attention, stress, engagement, and excitement.ResultsThe findings of this research illustrate a methodology that allowed the first approach to the cognitive abilities of engineering students to be from neurobiological and behavioral perspectives. Additionally, two profiles were extracted from the results. The first illustrates the Neuropsi test areas, its most common mistakes, and its performance ratings regarding the students' sample. The second profile shows the interaction between the EEG and Neuropsi test, showing engineering students' cognitive and emotional states based on biometric levels.DiscussionsThe study demonstrates the potential of integrating neurobiological assessment into engineering education, highlighting a significant advancement in addressing the skills requirements of Industry 5.0. The results suggest that obtaining a comprehensive understanding of students' cognitive abilities is possible, and educational interventions can be adapted by combining neuropsychological approaches with EEG data collection. In the future, it is essential to refine these evaluation methods further and explore their applicability in different engineering disciplines. Additionally, it is necessary to investigate the long-term impact of these methods on workforce preparation and performance.

This paper seeks to address ten questions that explore the burgeoning field of Human-Building Interaction (HBI), an interdisciplinary field that represents the next frontier in convergent research and innovation to enable the dynamic interplay of human and building interactional intelligence. The field of HBI builds on several existing efforts in historically separate research fields/communities and aims to understand how buildings affect human outcomes and experiences, as well as how humans interact with, adapt to, and affect the built environment and its systems, to support buildings that can learn, enable adaptation, and evolve at different scales to improve the quality-of-life of its users while optimizing resource usage and service availability. Questions were developed by a diverse group of researchers with backgrounds in design, engineering, computer science, social science, and health science. Answers to these questions draw conclusions from what has been achieved to date as reported in the available literature and establish a foundation for future HBI research. This paper aims to encourage interdisciplinary collaborations in HBI research to change the way people interact with and perceive technology within the context of buildings and inform the design, construction, and operation of next-generation, intelligent built environments. In doing so, HBI research can realize a myriad of benefits for human users, including improved productivity, health, cognition, convenience, and comfort, all of which are essential to societal well-being.

The importance of highly monitored and analyzed processes, linked by information systems such as knowledge graphs, is growing. In addition, the integration of operators has become urgent due to their high costs and from a social point of view. An appropriate framework for implementing the Industry 5.0 approach requires effective data exchange in a highly complex manufacturing network to utilize resources and information. Furthermore, the continuous development of collaboration between human and machine actors is fundamental for industrial cyber-physical systems, as the workforce is one of the most agile and flexible manufacturing resources. This paper introduces the human-centric knowledge graph framework by adapting ontologies and standards to model the operator-related factors such as monitoring movements, working conditions, or collaborating with robots. It also presents graph-based data querying, visualization, and analysis through an industrial case study. The main contribution of this work is a knowledge graph-based framework that focuses on the work performed by the operator, including the evaluation of movements, collaboration with machines, ergonomics, and other conditions. In addition, the use of the framework is demonstrated in a complex use case based on an assembly line, with examples of resource allocation and comprehensive support in terms of the collaboration aspect between shop-floor workers. [ABSTRACT FROM AUTHOR]

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IntroductioneHealth seems promising in addressing challenges in the provision of care for Huntington’s disease (HD) across Europe. By harnessing information and communication technologies, eHealth can partially relocate care from specialized centers to the patients’ home, thereby increasing the availability and accessibility of specialty care services beyond regional borders. Previous research on eHealth (development) in HD is however limited, especially when it comes to including eHealth services specifically designed together with HD gene expansion carriers (HDGECs) and their partners to fit their needs and expectations.MethodsThis article describes the qualitative human-centered design process and first evaluations of the Huntington Support App prototype: a web-app aimed to support the quality of life (QoL) of HDGECs and their partners in Europe. Prospective end-users, i.e., HDGECs, their partners, and healthcare providers (HCPs), from different countries were involved throughout the development process. Through interviews, we captured people’s experiences with the disease, quality of life (QoL), and eHealth. We translated their stories into design directions that were further co-designed and subsequently evaluated with the user groups.ResultsThe resulting prototype centralizes clear and reliable information on the disease, HD-related news and events, as well as direct contact possibilities with HCPs via an online walk-in hour or by scheduling an appointment. The app’s prototype was positively received and rated as (very) appealing, pleasant, easy to use and helpful by both HDGECs and partners.DiscussionBy involving end-users in every step, we developed a healthcare app that meets relevant needs of individuals affected by HD and therefore may lead to high adoption and retention rates. As a result, the app provides low-threshold access to reliable information and specialized care for HD in Europe. A description of the Huntington Support App as well as implications for further development of the app’s prototype are provided.

Advancements in analytical tools have facilitated numerous studies on perceived street quality. However, most have focused on limited aspects of street quality, failing to capture a comprehensive perception. This study introduces a quantitative approach to holistically measure street quality by integrating three key dimensions: visual perception, network accessibility, and functional diversity. Using Beijing and Shanghai as case studies, we employed artificial neural networks to analyze street view images and quantify the visual characteristics of streets. Additionally, street network accessibility was assessed through spatial design network analysis, and functional diversity was evaluated using the entropy of points of interest (POIs) data. The evaluation results were combined using the analytic hierarchy process. The reliability and accuracy of this method were validated through further testing. Our approach offers a human-centered, large-scale measurement framework, providing valuable insights for urban street renewal and design.

Avoiding downtime is one of the major concerns of manufacturing industries. In the era of connected industry, acquiring data has become cheaper than ever; however, turning that data into actionable insights for operators is not always straightforward. In this work, we present a manufacturing scenario involving a circular blade rubber cutting machine, where the goal is to minimize downtime. Historical cutting data are available, and the aim is to provide the machine operators with an intuitive tool that helps them reduce this downtime. This work demonstrates how, in an Industry 4.0 environment, data can be leveraged to minimize downtime. To achieve this, different survival model approaches are compared, a Health Index (HI) is developed, and the model deployment is analysed, highlighting the importance of understanding the model as a dynamic system in which the operator plays a key role.

In this article, we try to explain that although the Renaissance was a renaissance and a transformation that was not and is not desirable to the church, the preparations for this transformation have been gradually provided at least since the 13th century AD within the church itself. Certainties of the church itself, such as the belief in the Trinity, the infallibility of the Pope, the Aristotelian view of religion, various readings, at the top of all of them, the appearance of Martin Luther, which led to the establishment of the Protestant Church, translations from Islamic culture centered on Avicenna and Averroes was taught in Latin and was taught in the church itself. The consequences of these developments in the centuries leading to the Renaissance, such as anthropocentrism, the originality of reason, the controversy over the truth of the church and secularism, are exactly opposite to the medieval worldview. Medieval philosophers were planted and nurtured, and in the Renaissance, in various contexts that we have highlighted the philosophical dimension in this writing, it bore fruit. The establishment of naturalism in theology by the Catholic Church is only one example of these cases. Other cases we have tried to briefly explain in this article. In the end, the roots of some components of modernity should be sought in the same completely intertwined theological-philosophical complex in seminary tradition.

Abstract In recent years, artificial intelligence (AI) technology has been used in most if not all domains and has greatly benefited our lives. While AI can accurately extract critical features and valuable information from large amounts of data to help people complete tasks faster, there are growing concerns about the non-transparency of AI in the decision-making process. The emergence of explainable AI (XAI) has allowed humans to better understand and control AI systems, which is motivated to provide transparent explanations for the decisions made by AI. This article aims to present a comprehensive overview of recent research on XAI approaches from three well-defined taxonomies. We offer an in-depth analysis and summary of the status and prospects of XAI applications in several key areas where reliable explanations are urgently needed to avoid mistakes in decision-making. We conclude by discussing XAI’s limitations and future research directions.

Endoscopic ultrasound (EUS) has emerged as a pivotal tool for the screening and diagnosis of submucosal tumors (SMTs). However, the inherently low-quality and highly variable image content presents substantial obstacles to the automation of SMT diagnosis. Deep learning, with its adaptive feature extraction capabilities, offers a potential solution, yet its implementation often requires a vast quantity of high-quality data - a challenging prerequisite in clinical settings. To address this conundrum, this paper proposes a novel data-efficient visual analytics method that integrates human feedback into the model lifecycle, thereby augmenting the practical utility of data. The methodology leverages a two-stage deep learning algorithm, which encompasses self-supervised pre-training and an attention-based network. Comprehensive experimental validation reveals that the proposed approach facilitates the model in deciphering the hierarchical structure information within high-noise EUS images. Moreover, when allied with human-machine interaction, it enhances data utilization, thereby elevating the accuracy and reliability of diagnostic outcomes. The code is available at https://github.com/Zehebi29/LA-RANet.git. [ABSTRACT FROM AUTHOR]

This paper delves into the concept of social metabolism as a foundation for the development of sociotechnical systems in Industry 5.0. The study conducts an analysis of the existing methods and approaches for designing sociotechnical systems, and reviews publications that utilize such systems to incorporate Industry 4.0 technologies into manufacturing processes. Additionally, it examines the three key factors of Industry 5.0 and the enabling framework of Industry 4.0 technologies. Based on these investigations, a theoretical model is proposed for manufacturing system design, employing sociotechnical systems to integrate Industry 4.0 enabling technologies, while considering the essential aspects of Industry 5.0. The model emphasizes the early consideration of sociotechnical systems to design manufacturing systems that prioritize human-centricity, sustainability, and resilience. By embracing this comprehensive approach, the proposed model contributes to the realization of a production environment aligned with societal needs, fostering a more conscious and adaptable industry. [ABSTRACT FROM AUTHOR]

With the advent of the so-called "philosophical revolution", it is clear that without the necessary procedures and issues of thought, any science is merely a continuation of the accepted world in its present state, denying its main role as a critical act versus a scientific act. Here we bring together the human (central) problem in modern philosophy and the philosophy of the city. Here we first examine the term in modern philosophy and then, to refine or reinterpret it in the philosophy of the city, we analyze main works to define the modern human-centered city. what is a human-centered city in modern philosophy? As Kant does the project of "humanizing science" by separating man from the immaterial realm of knowledge; Modern urban planners also carry out the plan of "humanizing the city" or the human-centered city by separating it from its original world. The transcendental plan of modernist urban planners, with a posteriori knowledge, receives what is appropriate for man in the city, and then applies it equally to the a priori in a general matter for all human beings and all cities. This is while understanding man in the same situation leads us to the point that there is no human being. Human personality traits, culture, and lived experience fall victim to abstract and general characteristics. This is the humanization of the modern city by removing human beings from the city.

In multimedia correspondence, steganography schemes are commonly applied. To reduce storage capacity, multimedia files, including images, are always compressed. Most steganographic video schemes are, therefore, not compression tolerant. In the frame sequences, the video includes extra hidden space. Artificial intelligence (AI) creates a digital world of real-time information for athletes, sponsors, and broadcasters. AI is reshaping business, and although it has already produced a significant impact on other sectors, the sports industry is the newest and most receptive one. Human-centered AI for web applications has substantially influenced audience participation, strategic plan execution, and other aspects of the sports industry that have traditionally relied heavily on statistics. Thus, this study presents the motion vector steganography of sports training video integrating with the artificial bee colony algorithm (MVS-ABC). The motion vector stenography detects the hidden information from the motion vectors in the sports training video bitstreams. Artificial bee colony (ABC) algorithm optimizes the block assignment to inject a hidden message into a host video, in which the block assignment is considered a combinatorial optimization problem. The experimental analysis evaluates the data embedding performance using steganographic technology compared with existing embedding technologies, using the ABC algorithm compared with other genetic algorithms. The findings show that the proposed model can give the highest performance in terms of embedding capacity and the least error rate of video steganography compared with the existing models.

PurposeThe discourse on the human-centricity of AI at work needs contextualization. The aim of this study is to distinguish prevalent criteria of human-centricity for AI applications in the scientific discourse and to relate them to the work contexts for which they are specifically intended. This leads to configurations of actor-structure engagements that foster human-centricity in the workplace.Theoretical foundationThe study applies configurational theory to sociotechnical systems’ analysis of work settings. The assumption is that different approaches to promote human-centricity coexist, depending on the stakeholders responsible for their application.MethodThe exploration of criteria indicating human-centricity and their synthesis into configurations is based on a cross-disciplinary literature review following a systematic search strategy and a deductive-inductive qualitative content analysis of 101 research articles.ResultsThe article outlines eight criteria of human-centricity, two of which face challenges of human-centered technology development (trustworthiness and explainability), three challenges of human-centered employee development (prevention of job loss, health, and human agency and augmentation), and three challenges of human-centered organizational development (compensation of systems’ weaknesses, integration of user-domain knowledge, accountability, and safety culture). The configurational theory allows contextualization of these criteria from a higher-order perspective and leads to seven configurations of actor-structure engagements in terms of engagement for (1) data and technostructure, (2) operational process optimization, (3) operators’ employment, (4) employees’ wellbeing, (5) proficiency, (6) accountability, and (7) interactive cross-domain design. Each has one criterion of human-centricity in the foreground. Trustworthiness does not build its own configuration but is proposed to be a necessary condition in all seven configurations.DiscussionThe article contextualizes the overall debate on human-centricity and allows us to specify stakeholder-related engagements and how these complement each other. This is of high value for practitioners bringing human-centricity to the workplace and allows them to compare which criteria are considered in transnational declarations, international norms and standards, or company guidelines.

Stress is a critical concern in manufacturing environments, as it impacts the well-being and performance of workers. Accurate measurement of stress is essential for effective intervention and mitigation strategies. This paper introduces a holistic and human-centered protocol to measure stress in manufacturing settings. The three-phased protocol integrates the analysis of physiological signals, performance indicators, and the human perception of stress. The protocol incorporates advanced techniques, such as electroencephalography (EEG), heart rate variability (HRV), galvanic skin response (GSR), and electromyography (EMG), to capture physiological responses associated with stress. Furthermore, the protocol considers performance indicators as an additional dimension of stress measurement. Indicators such as task execution time, errors, production rate, and other relevant performance metrics contribute to a comprehensive understanding of stress in manufacturing environments. The human perception of stress is also integrated into the protocol, recognizing the subjective experience of the individual. This component captures self-assessment and subjective reports, allowing for a more nuanced evaluation of stress levels. By adopting a holistic and human-centered approach, the proposed protocol aims to enhance our understanding of stress factors in manufacturing environments. The protocol was also applied in the automotive industry and plastic component manufacturing. The insights gained from this protocol can inform targeted interventions to improve worker well-being, productivity, and overall organizational performance. [ABSTRACT FROM AUTHOR]

In recent years, artificial intelligence (AI) technology has been used in most if not all domains and has greatly benefited our lives. While AI can accurately extract critical features and valuable information from large amounts of data to help people complete tasks faster, there are growing concerns about the non-transparency of AI in the decision-making process. The emergence of explainable AI (XAI) has allowed humans to better understand and control AI systems, which is motivated to provide transparent explanations for the decisions made by AI. This article aims to present a comprehensive overview of recent research on XAI approaches from three well-defined taxonomies. We offer an in-depth analysis and summary of the status and prospects of XAI applications in several key areas where reliable explanations are urgently needed to avoid mistakes in decision-making. We conclude by discussing XAI's limitations and future research directions. [ABSTRACT FROM AUTHOR]

Purpose—The sale of physical products has been manufacturing companies' main revenue source. A trend is known as servitization for earning revenue comes from services. With the convergence of servitization and digitization, many manufacturing organizations are undergoing digital servitization. In parallel, the digitization of industry is pushing new technological solutions to the top of the business agenda. Artificial intelligence can play a substantial role in this digital business transformation. This evolution is referred to in this paper as Servitization 5.0 and requires substantial changes. Aim—This paper explores the applications of artificial intelligence to Servitization 5.0 strategies and its role, particularly in changing organizations to EverythiA.I.ng as a Service. The paper underlines the contribution that A.I. can provide in moving to a human-centric, sustainable, and resilient servitization. Method used—The basis of the work is a literature review supported by information collected from business case studies by the authors. A follow-up study defined the models. The validity of the model was tested by collecting ten experts' opinions who currently work within servitization contracts sessions. Findings—For manufacturing companies, selling services requires completely different business models. In this situation, it is essential to consider advanced solutions to support these new business models. Artificial Intelligence can make it possible. On the inter-organizational side, empirical evidence also points to the support of A.I. in collaborating with ecosystems to support sustainability and resilience, as requested by Industry 5.0. Original value—Regarding theoretical implications, this paper contributes to interdisciplinary research in corporate marketing and operational servitization. It is part of the growing literature that deals with the applications of artificial intelligence-based solutions in different areas of organizational management. The approach is interesting because it highlights that digital solutions require an integrated business model approach. It is necessary to implement the technological platform with appropriate processes, people, and partners (the four Ps). The outcome of this study can be generalized for industries in high-value manufacturing. Implications—As implications for management, this paper defines how to organize the structure and support for Servitization 5.0 and how to work with the external business environment to support sustainability. [ABSTRACT FROM AUTHOR]

With the advent of the so-called "philosophical revolution", it is clear that without the necessary procedures and issues of thought, any science is merely a continuation of the accepted world in its present state, denying its main role as a critical act versus a scientific act. Here we bring together the human (central) problem in modern philosophy and the philosophy of the city. Here we first examine the term in modern philosophy and then, to refine or reinterpret it in the philosophy of the city, we analyze main works to define the modern human-centered city. what is a human-centered city in modern philosophy? As Kant does the project of "humanizing science" by separating man from the immaterial realm of knowledge; Modern urban planners also carry out the plan of "humanizing the city" or the humancentered city by separating it from its original world. The transcendental plan of modernist urban planners, with a posteriori knowledge, receives what is appropriate for man in the city, and then applies it equally to the a priori in a general matter for all human beings and all cities. This is while understanding man in the same situation leads us to the point that there is no human being. Human personality traits, culture, and lived experience fall victim to abstract and general characteristics. This is the humanization of the modern city by removing human beings from the city. [ABSTRACT FROM AUTHOR]

Faced with the generally poor experience in pediatric outpatient in China, under the guidance of design thinking, based on the analysis and research of the main elements affecting child outpatients' medical service experiences, this study proposes a set of strategic models that can improve child outpatients' medical service experiences. Specifically, this study takes Shanghai Xinhua Hospital as a research case, combined with SPSS data statistics software, and comprehensively uses preliminary field research methods, questionnaire descriptive analysis methods, questionnaire satisfaction analysis methods, and questionnaire principal component analysis (PCA) methods as well as the structured interview method; thus, the main elements affecting child outpatients' medical service experiences were obtained. Then, according to the main elements, a set of child outpatient medical service strategy models is proposed to improve child outpatients' medical service experiences. Finally, the effectiveness of the strategy model is tested through satisfaction analysis and simulation case verification. The model is a people-centered, sustainable strategic model. With the support of design thinking, the strategic model takes the experience of children as the core improvement point, which is able to fully protect the rights and demands of child patients. At the same time, this strategy model can also reduce the workload of doctors, improve the operational efficiency of hospitals, promote a more equal distribution of medical resources, and reduce medical service costs. More importantly, it also encourages patients and their families to communicate and express their opinions to medical professionals, which can greatly reduce the tension between doctors and patients and effectively avoid doctor–patient conflicts. This has important implications for the sustainability of healthcare. However, this strategy model is only a guiding strategy for improving outpatient care for children. It does not provide detailed solutions around certain specific issues and specific implementations. At the same time, it is not a complex engineering design system but only provides a reference for improving children's medical services in terms of strategic logic. [ABSTRACT FROM AUTHOR]

The importance of highly monitored and analyzed processes, linked by information systems such as knowledge graphs, is growing. In addition, the integration of operators has become urgent due to their high costs and from a social point of view. An appropriate framework for implementing the Industry 5.0 approach requires effective data exchange in a highly complex manufacturing network to utilize resources and information. Furthermore, the continuous development of collaboration between human and machine actors is fundamental for industrial cyber-physical systems, as the workforce is one of the most agile and flexible manufacturing resources. This paper introduces the human-centric knowledge graph framework by adapting ontologies and standards to model the operator-related factors such as monitoring movements, working conditions, or collaborating with robots. It also presents graph-based data querying, visualization, and analysis through an industrial case study. The main contribution of this work is a knowledge graph-based framework that focuses on the work performed by the operator, including the evaluation of movements, collaboration with machines, ergonomics, and other conditions. In addition, the use of the framework is demonstrated in a complex use case based on an assembly line, with examples of resource allocation and comprehensive support in terms of the collaboration aspect between shop-floor workers.

This paper delves into the concept of social metabolism as a foundation for the development of sociotechnical systems in Industry 5.0. The study conducts an analysis of the existing methods and approaches for designing sociotechnical systems, and reviews publications that utilize such systems to incorporate Industry 4.0 technologies into manufacturing processes. Additionally, it examines the three key factors of Industry 5.0 and the enabling framework of Industry 4.0 technologies. Based on these investigations, a theoretical model is proposed for manufacturing system design, employing sociotechnical systems to integrate Industry 4.0 enabling technologies, while considering the essential aspects of Industry 5.0. The model emphasizes the early consideration of sociotechnical systems to design manufacturing systems that prioritize human-centricity, sustainability, and resilience. By embracing this comprehensive approach, the proposed model contributes to the realization of a production environment aligned with societal needs, fostering a more conscious and adaptable industry.

Abstract Background Existing assistive technologies attempt to mimic biological functions through advanced mechatronic designs. In some occasions, the information processing demands for such systems require substantial information bandwidth and convoluted control strategies, which make it difficult for the end-user to operate. Instead, a practical and intuitive semi-automated system focused on accomplishing daily tasks may be more suitable for end-user adoption. Methods We developed an intelligent prosthesis for the Cybathlon Global Edition 2020. The device was designed in collaboration with the prosthesis user (pilot), addressing her needs for the competition and aiming for functionality. Our design consists of a soft robotic-based two finger gripper controlled by a force-sensing resistor (FSR) headband interface, automatic arm angle dependent wrist flexion and extension, and manual forearm supination and pronation for a shared control system. The gripper is incorporated with FSR sensors to relay haptic information to the pilot based on the output of a neural network model that estimates geometries and objects material. Results As a student team of the Munich Institute of Robotics and Machine Intelligence, we achieved 12th place overall in the Cybathlon competition in which we competed against state-of-the-art prosthetic devices. Our pilot successfully accomplished two challenging tasks in the competition. During training sessions, the pilot was able to accomplish the remaining competition tasks except for one. Based on observation and feedback from training sessions, we adapted our developments to fit the user’s preferences. Usability ratings indicated that the pilot perceived the prosthesis to not be fully ergonomic due to the size and weight of the system, but argued that the prosthesis was intuitive to control to perform the tasks from the Cybathlon competition. Conclusions The system provides an intuitive interface to conduct common daily tasks from the arm discipline of the Cybathlon competition. Based on the feedback from our pilot, future improvements include the prosthesis’ reduction in size and weight in order to enhance its mobility. Close collaboration with our pilot has allowed us to continue with the prosthesis development. Ultimately, we developed a simple-to-use solution, exemplifying a new paradigm for prosthesis design, to help assist arm amputees with daily activities.

In Society 5.0, the central concept is Human-Centered and supported by super-smart technology that frees humans from burdened workloads and allows humans to innovate new values ??without limits. All of this results in prosperity for everyone and that is the achievement of the global Sustainable Development Goals (SDGs). The application of this concept must be realized by all stakeholders of the nation, including universities that are responsible for the education of the younger generation. However, the implementation of sustainability university has been very numerous, varied, and there is no clear definition in the literature or practice. This study aims to develop a Human-Centered sustainable model that can be used as a reference in implementation. The research method used is qualitative by conducting library research, interviews and observations. Respondents and objects of interviews and observations are Telkom University’s sustainability teams and programs/ projects. The result of this study is a Human-Centered sustainable university model that is recommended as an implementation reference, not only for Telkom University but also for other universities with similar characteristics.

Human beings today, due to the growth of industry and technology, have departed from ethical standards and values, so they need to do everything in their power to promote this vitality. Erich Fromm does not consider psychology to be separate from ethics, so he views human nature and personality in life as a combination of non-fertile orientations, including recipient, exploitative, market-oriented, and fertile and spontaneous. He extensively values human dignity because he believes in the principle of humanity in the life of humanism. Man has a high place in Behbahani's poetry because he believes in the existence of the Necessary Being and believes in it as a source of power beyond man. The purpose of this essay is to analyze the orientations of personality (fertile and non-fertile) in the psycho-sociological approach of Erich Fromm in Simin Behbahani's poems in order to understand his personality and thoughts more and more. The research method in this study is analytical-descriptive. Behbahani and Fromm consider man's place in existence, his evolution, prosperity, and achievement of goodness and transcendence, but the obvious difference between them is the man-centered forum and religion-centered behavior.

Human-centricity is considered a central aspect in the development and governance of artificial intelligence (AI). Various strategies and guidelines highlight the concept as a key goal. However, we argue that current uses of Human-Centered AI (HCAI) in policy documents and AI strategies risk downplaying promises of creating desirable, emancipatory technology that promotes human wellbeing and the common good. Firstly, HCAI, as it appears in policy discourses, is the result of aiming to adapt the concept of human-centered design (HCD) to the public governance context of AI but without proper reflection on how it should be reformed to suit the new task environment. Second, the concept is mainly used in reference to realizing human and fundamental rights, which are necessary, but not sufficient for technological emancipation. Third, the concept is used ambiguously in policy and strategy discourses, making it unclear how it should be operationalized in governance practices. This article explores means and approaches for using the HCAI approach for technological emancipation in the context of public AI governance. We propose that the potential for emancipatory technology development rests on expanding the traditional user-centered view of technology design to involve community- and society-centered perspectives in public governance. Developing public AI governance in this way relies on enabling inclusive governance modalities that enhance the social sustainability of AI deployment. We discuss mutual trust, transparency, communication, and civic tech as key prerequisites for socially sustainable and human-centered public AI governance. Finally, the article introduces a systemic approach to ethically and socially sustainable, human-centered AI development and deployment.

The potential of artificial intelligence (AI) to reduce health care disparities and inequities is recognized, but it can also exacerbate these issues if not implemented in an equitable manner. This perspective identifies potential biases in each stage of the AI life cycle, including data collection, annotation, machine learning model development, evaluation, deployment, operationalization, monitoring, and feedback integration. To mitigate these biases, we suggest involving a diverse group of stakeholders, using human-centered AI principles. Human-centered AI can help ensure that AI systems are designed and used in a way that benefits patients and society, which can reduce health disparities and inequities. By recognizing and addressing biases at each stage of the AI life cycle, AI can achieve its potential in health care. [ABSTRACT FROM AUTHOR]

Abstract Robotics has a special place in AI as robots are connected to the real world and robots increasingly appear in humans everyday environment, from home to industry. Apart from cases were robots are expected to completely replace them, humans will largely benefit from real interactions with such robots. This is not only true for complex interaction scenarios like robots serving as guides, companions or members in a team, but also for more predefined functions like autonomous transport of people or goods. More and more, robots need suitable interfaces to interact with humans in a way that humans feel comfortable and that takes into account the need for a certain transparency about actions taken. The paper describes the requirements and state-of-the-art for a human-centered robotics research and development, including verbal and non-verbal interaction, understanding and learning from each other, as well as ethical questions that have to be dealt with if robots will be included in our everyday environment, influencing human life and societies.

The smart revolution has penetrated in a wide range of applications. Smart campus, as the high-end form of education systems, deploys cutting-edge information and communication technologies to enhance the effectiveness and efficiency of campus services. Under the pandemic of COVID-19, smart campus has shown unprecedented importance owing to its remote, personalized, and ubiquitous features. All these factors have made smart campus an ongoing intense research topic in recent years, whereas existing reviews on smart campus were conducted in earlier years and thus an update is imperatively needed to investigate and summarize the emerging knowledge, technologies, and applications in this context. This paper conducts a systematic review on smart campus technologies and applications, and then strategically classifying them into different domains to investigate the current research pattern. Moreover, adhering to the human-centered principle of smart campus development, a human-centered case study has been carried out and presented in this paper to evaluate the consistency and adherence of current research trend to the stakeholders needs and interests.

Phishing attacks are still seen as a significant threat to cyber security, and large parts of the industry rely on anti-phishing simulations to minimize the risk imposed by such attacks. This study conducted a large-scale anti-phishing training with more than 31000 participants and 144 different simulated phishing attacks to develop a data-driven model to classify how users would perceive a phishing simulation. Furthermore, we analyze the results of our large-scale anti-phishing training and give novel insights into users’ click behavior. Analyzing our anti-phishing training data, we find out that 66% of users do not fall victim to credential-based phishing attacks even after being exposed to twelve weeks of phishing simulations. To further enhance the phishing awareness-training effectiveness, we developed a novel manifold learning-powered machine learning model that can predict how many people would fall for a phishing simulation using the several structural and state-of-the-art NLP features extracted from the emails. In this way, we present a systematic approach for the training implementers to estimate the average “convincing power” of the emails prior to rolling out. Moreover, we revealed the top-most vital factors in the classification. In addition, our model presents significant benefits over traditional rule-based approaches in classifying the difficulty of phishing simulations. Our results clearly show that anti-phishing training should focus on the training of individual users rather than on large user groups. Additionally, we present a promising generic machine learning model for predicting phishing susceptibility.

Stress is a critical concern in manufacturing environments, as it impacts the well-being and performance of workers. Accurate measurement of stress is essential for effective intervention and mitigation strategies. This paper introduces a holistic and human-centered protocol to measure stress in manufacturing settings. The three-phased protocol integrates the analysis of physiological signals, performance indicators, and the human perception of stress. The protocol incorporates advanced techniques, such as electroencephalography (EEG), heart rate variability (HRV), galvanic skin response (GSR), and electromyography (EMG), to capture physiological responses associated with stress. Furthermore, the protocol considers performance indicators as an additional dimension of stress measurement. Indicators such as task execution time, errors, production rate, and other relevant performance metrics contribute to a comprehensive understanding of stress in manufacturing environments. The human perception of stress is also integrated into the protocol, recognizing the subjective experience of the individual. This component captures self-assessment and subjective reports, allowing for a more nuanced evaluation of stress levels. By adopting a holistic and human-centered approach, the proposed protocol aims to enhance our understanding of stress factors in manufacturing environments. The protocol was also applied in the automotive industry and plastic component manufacturing. The insights gained from this protocol can inform targeted interventions to improve worker well-being, productivity, and overall organizational performance.

Many industries have successfully implemented the define-measure-analyze-improve-control (DMAIC) method of Lean Six Sigma to improve their production activities. Value stream mapping (VSM) for Industry 4.0 allows us to understand the current state of operations in order to plan future improvements. In this study, we propose an improvement model based on DMAIC with VSM 4.0 for a truck cooler manufacturer to improve the picking workstation design with a human-centered approach. We use the DMAIC method to analyze the project step by step. After identifying the root cause, we identified countermeasures to improve the productivity. To reduce human error, the project team adopted a human-centered approach and applied lean tools, such as visual management, error prevention, and waste analysis. As a result of this case study, the yield rate was improved from 98% to 100%, and the direct savings of the project amounted to EUR 3180, mainly due to the freeing up of space. A human-centered LSS framework is also presented as a novel contribution of this study. [ABSTRACT FROM AUTHOR]

Although comparative psychologists have made considerable strides in the past several decades, expanding the breadth of species and questions examined, the field still suffers from an overemphasis on top-down approaches that begin and end with a focus on humans. This top-down perspective leads to biases and oversights that hamper the further development of the field. A bottom-up approach that considers species-specific abilities and behaviors in the context of theoretically relevant comparisons will be most useful in advancing knowledge of species-specific and shared abilities. This will allow a better determination of the extent to which continuities and discontinuities exist as a function of different ecological forces. In addition, a bottom-up approach will facilitate a shift in focus from using animals to better understand humans, to understanding animals themselves. This new approach will allow for an appreciation of how humans can benefit other species.

Background: HIV mobile health (mHealth) interventions often incorporate interactive peer-to-peer features. The user-generated content (UGC) created by these features can offer valuable design insights by revealing what topics and life events are most salient for participants, which can serve as targets for subsequent interventions. However, unstructured, textual UGC can be difficult to analyze. Interpretive thematic analyses can preserve rich narratives and latent themes but are labor-intensive and therefore scale poorly. Natural language processing (NLP) methods scale more readily but often produce only coarse descriptive results. Recent calls to advance the field have emphasized the untapped potential of combined NLP and qualitative analyses toward advancing user attunement in next-generation mHealth. Objective: In this proof-of-concept analysis, we gain human-centered design insights by applying hybrid consecutive NLP-qualitative methods to UGC from an HIV mHealth forum. Methods: UGC was extracted from Thrive With Me, a web app intervention for men living with HIV that includes an unstructured peer-to-peer support forum. In Python, topics were modeled by latent Dirichlet allocation. Rule-based sentiment analysis scored interactions by emotional valence. Using a novel ranking standard, the experientially richest and most emotionally polarized segments of UGC were condensed and then analyzed thematically in Dedoose. Design insights were then distilled from these themes. Results: The refined topic model detected K=3 topics: A: disease coping; B: social adversities; C: salutations and check-ins. Strong intratopic themes included HIV medication adherence, survivorship, and relationship challenges. Negative UGC often involved strong negative reactions to external media events. Positive UGC often focused on gratitude for survival, well-being, and fellow users’support. Conclusions: With routinization, hybrid NLP-qualitative methods may be viable to rapidly characterize UGC in mHealth environments. Design principles point toward opportunities to align mHealth intervention features with the organically occurring uses captured in these analyses, for example, by foregrounding inspiring personal narratives and expressions of gratitude, or de-emphasizing anger-inducing media. [ABSTRACT FROM AUTHOR]

The functionality of existing cyber-physical production systems generally focuses on mapping technologic specifications derived from production requirements. Consequently, such systems base their conception on a structurally mechanistic paradigm. Insofar as these approaches have considered humans, their conception likewise is based on the structurally identical paradigm. Due to the fundamental reorientation towards explicitly human-centered approaches, the fact that essential aspects of the dimension "human" remain unconsidered by the previous paradigm becomes more and more apparent. To overcome such limitations, mapping the "social" dimension requires a structurally different approach. In this paper, an anthropocentric approach is developed based on possible conceptions of the human being, enabling a structural integration of the human being in an extended dimension. Through the model, extending concepts for better integration of the human being in the sense of human-centered approaches, as envisioned in the Industrie 5.0 conception, is possible. [ABSTRACT FROM AUTHOR]

Background: Existing assistive technologies attempt to mimic biological functions through advanced mechatronic designs. In some occasions, the information processing demands for such systems require substantial information bandwidth and convoluted control strategies, which make it difficult for the end-user to operate. Instead, a practical and intuitive semi-automated system focused on accomplishing daily tasks may be more suitable for end-user adoption.Methods: We developed an intelligent prosthesis for the Cybathlon Global Edition 2020. The device was designed in collaboration with the prosthesis user (pilot), addressing her needs for the competition and aiming for functionality. Our design consists of a soft robotic-based two finger gripper controlled by a force-sensing resistor (FSR) headband interface, automatic arm angle dependent wrist flexion and extension, and manual forearm supination and pronation for a shared control system. The gripper is incorporated with FSR sensors to relay haptic information to the pilot based on the output of a neural network model that estimates geometries and objects material.Results: As a student team of the Munich Institute of Robotics and Machine Intelligence, we achieved 12th place overall in the Cybathlon competition in which we competed against state-of-the-art prosthetic devices. Our pilot successfully accomplished two challenging tasks in the competition. During training sessions, the pilot was able to accomplish the remaining competition tasks except for one. Based on observation and feedback from training sessions, we adapted our developments to fit the user's preferences. Usability ratings indicated that the pilot perceived the prosthesis to not be fully ergonomic due to the size and weight of the system, but argued that the prosthesis was intuitive to control to perform the tasks from the Cybathlon competition.Conclusions: The system provides an intuitive interface to conduct common daily tasks from the arm discipline of the Cybathlon competition. Based on the feedback from our pilot, future improvements include the prosthesis' reduction in size and weight in order to enhance its mobility. Close collaboration with our pilot has allowed us to continue with the prosthesis development. Ultimately, we developed a simple-to-use solution, exemplifying a new paradigm for prosthesis design, to help assist arm amputees with daily activities. [ABSTRACT FROM AUTHOR]

As Dr. Martin Luther King, Jr., observed, Injustice anywhere is a threat to justice everywhere. We are caught in an inescapable network of mutuality, tied in a single garment of destiny. Whatever affects one directly, affects all indirectly. [1, para. 4] [ABSTRACT FROM AUTHOR]

In this paper, we address the challenge of believability in multiplayer video games. Our contribution is a system for assessing the believability of computer players. The state of the art examines existing methods and identifies seven distinguishing features that differ considerably from one assessment to the next. Our investigation reveals that assessment procedures typically alter gameplay, posing a considerable danger of bias. This is a major flaw since computer players are evaluated in a specific context rather than in the context of the game as it should be played, potentially skewing the findings of the evaluation. As a result, we begin on a trial-and-error process, with each new proposal building on the achievements of the previous one while removing the flaws. New proposals are tested with new assessments, a total of three experiments are then presented. We created a computer program that partially automates the execution of the assessment procedure, making these trials easier to implement. At the end, thanks to our proposal, gamers can assess the believability of computer players indirectly by employing reporting forms that alert users to the presence of bots. We assume that the more a bot is reported, the less credible it becomes. We ran a final experiment to test our proposal, which yielded extremely encouraging results.