Human-centered Approach Research Articles

Hourly values of an advanced human-biometeorological index for diverse populations from 1991 to 2020 in Greece

Existing assessments of the thermal-related impact of the environment on humans are often limited by the use of data that are not representative of the population exposure and/or not consider a human centred approach. Here, we combine high resolution regional retrospective analysis (reanalysis), population data and human energy balance modelling, in order to produce a human thermal bioclimate dataset capable of addressing the above limitations. The dataset consists of hourly, population-weighted values of an advanced human-biometeorological index, namely the modified physiologically equivalent temperature (mPET), at fine-scale administrative level and for 10 different population groups. It also includes the main environmental drivers of mPET at the same spatiotemporal resolution, covering the period from 1991 to 2020. The study area is Greece, but the provided code allows for the ease replication of the dataset in countries included in the domains of the climate reanalysis and population data, which focus over Europe. Thus, the presented data and code can be exploited for human-biometeorological and environmental epidemiological studies in the European continent.

Revisiting the role of HR in the age of AI: bringing humans and machines closer together in the workplace.

The functions of human resource management (HRM) have changed radically in the past 20 years due to market and technological forces, becoming more cross-functional and data-driven. In the age of AI, the role of HRM professionals in organizations continues to evolve. Artificial intelligence (AI) is transforming many HRM functions and practices throughout organizations creating system and process efficiencies, performing advanced data analysis, and contributing to the value creation process of the organization. A growing body of evidence highlights the benefits AI brings to the field of HRM. Despite the increased interest in AI-HRM scholarship, focus on human-AI interaction at work and AI-based technologies for HRM is limited and fragmented. Moreover, the lack of human considerations in HRM tech design and deployment can hamper AI digital transformation efforts. This paper provides a contemporary and forward-looking perspective to the strategic and human-centric role HRM plays within organizations as AI becomes more integrated in the workplace. Spanning three distinct phases of AI-HRM integration (technocratic, integrated, and fully-embedded), it examines the technical, human, and ethical challenges at each phase and provides suggestions on how to overcome them using a human-centric approach. Our paper highlights the importance of the evolving role of HRM in the AI-driven organization and provides a roadmap on how to bring humans and machines closer together in the workplace.

A Review of Immersive Technologies, Knowledge Representation, and AI for Human-Centered Digital Experiences

The evolution of digital technologies has resulted in the emergence of diverse interaction technologies. In this paper, we conducted a review of seven domains under a human-centric approach user interface design, human-centered web-based information systems, semantic knowledge representation, X-reality applications, human motion and 3D digitization, serious games, and AI. In this review, we studied these domains concerning their impact on the way we interact with digital interfaces, process information, and engage in immersive experiences. As such, we highlighted the shifts in design paradigms, user-centered principles, and the rise of web-based information systems. The results of such shifts are materialized in modern immersive technologies, semantic knowledge representation, serious games, and the facilitation of artificial intelligence for interactions. Through this exploration, we aimed to assist our understanding of the challenges that lie ahead. The seamless integration of technologies, ethical considerations, accessibility, education for technological literacy, interoperability, user trust, environmental sustainability, and regulatory frameworks are becoming significant. These challenges present opportunities for the future to enrich human experiences while addressing societal needs. This paper lays the groundwork for thoughtful and innovative approaches to the challenges that will define the future of human–computer interaction and information technologies.

Enhancing flexibility and safety: collaborative robotics for material handling in end-of-line industrial operations

The manufacturing landscape is rapidly evolving, being characterized by the emergence of Industry 5.0, leading to a growing recognition of the importance of a human-centered, sustainable and resilient approach. In response to these needs, collaborative robotics has emerged as a promising solution to enhance flexibility in industrial operations, while ensuring a higher level of safety. Cobots enable human-robot collaboration without the need for physical barriers, reduce the footprint of the robotic station, and foster a closer working relationship between humans and machines.This article focuses on an application of collaborative robotics in end-of-line industrial operations, specifically in the unloading of products from an automatic machine. By managing repetitive tasks, such as placing the trays near the end of the line of the automatic machine, waiting for them to be filled, and placing them on a trolley, which will then be moved by the human operator, the robot significantly improves efficiency. The proposed solution involves alternating the placement of trays in two rack trolleys, allowing the worker to replace the full trolleys with empty ones at his own timing. The paper examines the potential advantages of using a human-centric approach that emphasizes operator empowerment and human oversight: the collaborative robotic cell and the automation implemented free the workers from the low value-added operations and allow them to oversee and manage multiple machines simultaneously, thus enhancing productivity. The approach behind this proposal is to keep robotic tasks simple, easily reprogrammable and modular, while empowering the human operator to engage in supervision, decision-making, and problem-solving tasks. This collaboration allows the operator to assume a supervisory role, organizing production based on identified needs, and elevating their involvement to production line management tasks.

AI-Based Well-Integrity Monitoring Shows Promise

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 211093, “Development of an Artificial-Intelligence-Based Well-Integrity Monitoring Solution,” by Prihandono Aditama, SPE, Tina Koziol, and Meindert Dillen, Wintershall Dea. The paper has not been peer reviewed. _ This paper presents the proof of concept (PoC) of artificial intelligence (AI)-based well-integrity monitoring for gas-lift, natural-flow, and water-injector wells. AI-model prototypes were built to detect annulus leakage as incident-relevant anomalies from time-series sensor data. The AI models for gas-lift and natural-flow wells achieved a sufficient level of performance, with a minimum of 75% of historical events detected and less than one false positive per month per well. Problem Statement In the exploration and production industry, historical well-integrity events are rare because systems are designed as robustly as possible to prevent incidents. For the authors’ study, there were only 12 historical wellbore leakage incidents spanning 13 years of well operations in the assets considered. The events were treated separately for each well type. This challenge is normally known as anomaly detection and has been studied in various fields where time-series data are used. For a historical incident, two types of anomalies were identified: - Short-term incident relevant anomaly (SIRA), an anomaly occurring within 1 day - Long-term incident relevant anomaly (LIRA), an anomaly lasting for more than 1 day Objective and Success Criteria The primary objective of the PoC was to validate the hypothesis that incident-relevant anomalies from historical well-sensor data can be predicted and monitored by using adequate AI models. A generalized AI model was built so that it would detect a well-annulus leakage in future wells. Success criteria were defined by two approaches: a human-centric approach and a statistical approach. For the human-centric approach, the future users were interviewed to obtain insights about their requirements for tool performance. The feedback was mapped against a confusion matrix. Users preferred to optimize the number of correctly predicted historical incidents (true positives) while achieving an acceptable number of false positives. In general, wrong predictions were seen as acceptable (false positives) to a certain degree, depending on the number of wells under a user’s responsibility. Based on those insights, the AI model was optimized for recall instead of precision. Recall (sometimes known as sensitivity) is defined as the number of true positives divided by the total of true positives and false negatives and measures the miss rate. The tradeoff for choosing this approach means the AI model will report some false alarms.

DEVELOPMENT OF INCLUSIVE EDUCATION AS A COMPONENT OF THE PEDAGOGICAL MANAGEMENT SYSTEM OF A PRIVATE INNOVATIVE UNIVERSITY

The article is devoted the peculiarities of inclusive education development in the Republic of Tatarstan and the role of Kazan Innovation University (KIU) named after V.G. Timiryasov as a basic educational organization for the devel- opment of methodology and technologies for inclusive education. The results of a survey carried out by the Research Institute of Pedagogical Innovations and Inclusive Education of KIU together with the Ministry of Education and Science of the Republic of Tatarstan in the field of teachers’ readiness to implement inclusive approaches in educa- tion are presented. The author focuses on the need to transform the formalized management approach to managing a private innovative university into a human-centric approach, implying recognition of the uniqueness and value of all participants of educational process.

A Digital Twin for SMEs in the context of Industry 5.0

The deployment of Digital Twins in the age of Industry 5.0 is shifting towards a more flexible, efficient, sustainable and human-centric approach; providing ample opportunities for the manufacturing field. Having said that, Digital Twins may prove time-consuming, infrastructure-demanding, and potentially overwhelming for hefty data acquisition within simultaneous. This is particularly possible if the manufacturing company in context is a Small-Medium Enterprise (SME). SMEs contribute around 85% of new vacancies in the European Union; yet are still siloed from exploiting the full potential of Industry 4.0 technologies, due to financial hurdles and a potential absence of guidance or awareness. This research work therefore contributes an exemplary digital twin targeted towards the needs of manufacturing SMEs in the light of Industry 5.0, allowing for real-time data retrieval from a UR collaborative robot, a 3D printer and a corresponding MQTT broker. Real-time visualization of parameters such as temperatures, voltages, errors and progress will thus assist SMEs towards adopting an optimal sustainable approach. This paper will therefore outline the methodology behind the development of the digital twin, which can then be modified to incorporate human factors and a more human-centered viewpoint.

Copyright in AI Training Data: A Human-Centered Approach

Copyright in AI Training Data: A Human-Centered Approach

Feasibility and Usability of EnergyPoints: A Mobile Health App to Guide Acupressure Use for Cancer Symptom Management.

To examine the feasibility and usability of EnergyPoints™, an innovative mobile health app that teaches and guides people with cancer to implement daily acupressure to self-manage their fatigue and sleep disturbances. The study used an integrated agile, human-centered approach. Adults (age 18 years and over) with cancer experiencing at least moderate fatigue, and living in the Greater New York City community, were recruited from social media, patient advocacy groups, and referrals. Twenty participants (in 3 sprints of 3, 5, and 12) were video-recorded thinking aloud while using the app for the first time. They then used the app at home to self-administer acupressure (twice daily for 1 week) while continuously wearing a fitness tracker. Each participant completed an exit interview and modified Computer System Usability Questionnaire post-participation. Participants were ages 40 to 76 years and 65% female; 65% were non-Hispanic white. Mean pass rates per ritual exceeded 80%. Users completed (totally or partially) greater than 90% of stimulating acupressure and 70% of relaxing acupressure rituals. Sprint 3 SPs totally completed at least 1 ritual 87% of the time. The majority agreed or strongly agreed the app was easy to use (90%), easy to learn (85%), easy to understand (75%), and effective in helping perform self-acupressure (85%). In an analysis of ease of completing 5 key tasks, all successfully completed the tasks; 3 users required some assistance. Of 654 usability statements, those coded as personal experience/context (197), content related to acupressure learning (105), and content related to the onboarding/profile (71) were most frequent. The design team integrated recommendations into the app before the next sprint. Findings supported feasibility and usability, as well as acceptability, and led to significant alterations and improvements. EnergyPoints™ offers an opportunity to mainstream acupressure and help cancer survivors self-manage their symptoms.

ФАКТОРИ МОБІЛЬНОСТІ ПРАЦІВНИКА У СУЧАСНИХ УМОВАХ

The article examines the peculiarities of employee mobility under martial law, which consist in a fundamental change in the labor market environment due to increased imbalances in the labor market in terms of labor supply and demand, mass migration movements to the western regions of the state and abroad, and the impact of global changes in human resource management on the course of employee mobility. The article examines the trends in the development of global trends in human resources management and their impact on employee mobility, identifies peculiarities in the processes of employee mobility under the influence of destructive factors caused by the consequences of active hostilities, analyzes the impact of global trends in human resources management on employee mobility, and identifies problematic aspects in the existing processes of employee mobility. The reasons for internal employee mobility are analyzed, taking into account the impact of the COVID-19 pandemic and military escalation, namely, the increase in gender imbalances in the labor market, the reorientation of its qualification and professional component, and the introduction of the latest technologies in human resource management processes, in particular, models of generative artificial intelligence. The role of social dialogue, a human-centered approach, and macroeconomic stability in enhancing employee mobility is highlighted. The influence of corporate culture, relevant skills, and social status, in particular as a result of the mass migration of Ukrainians to save their lives, an increase in the share of women in the labor market due to the mobilization of men, new concepts of employment, and alternative ways of acquiring qualifications, is determined. The author identifies and summarizes the negative and positive factors of labor mobility that affect labor productivity and human capital development. The importance of the latest technologies and digital access for employee mobility is considered, namely the introduction of environmental, social, and governance standards, in particular the reorientation of business processes in accordance with the principles of the green economy, and the importance of proper corporate insurance and social protection is emphasized since, as never before, safety is now a key aspect of an effective working environment.

Prístup zameraný na človeka v kontexte vedenia ľudí v školstve

The above article pays attention to the personality of Carl R. Rogers and his human-centered approach. It is an approach that can be used in any relationship to help an effective communication or conflict resolution. We will present basic characteristics of the approach and in the conclusion of the article, we will describe possible application of a person-centered approach in leadership in schools, specifically, by the school Principal.

Designer-centric and function-oriented development framework for complex industrial products

Derived from the RFLP method (requirements, functions, logic, product) of model-based systems engineering, a function-oriented development approach can enable a universal, data and model-driven knowledge management system for complex product development, facilitate cross-disciplinary development, and support innovation. While function-orientation has been investigated from a technological standpoint, the successful implementation of such a concept is also dependent on human factors, which have not yet been sufficiently explored. This study aims to understand the needs of the designers for the implementation of the function-oriented development framework. Using a human-centred design approach, a study was conducted where the current version of the function-oriented framework was tested with potential users from the automotive industry. The basics of the framework were implemented in a prototype to immerse the subjects in the workflow. The subjects developed a fictitious product subsystem on the prototype using the framework. The results of the study illustrate the potential benefits, challenges, and implementation ideas for the framework from the designer perspective. The valuable insights from this industrial study can be used to develop a designer-centric function-oriented development framework and derive introduction and implementation strategies for large organizations.

Proof of concept: a practical approach to machine learning in video consultations’ acceptance in higher education institutions

Video consultations and telemedicine play a key role in healthcare. It is crucial to assist institutions in identifying which patients are more likely to use them, increasing the adoption rate. Even though Artificial Intelligence models are important, certain cases require a human centric approach to inform patients and doctors, ensuring trust in the tools provided. This can be achieved through interpretable Machine Learning models and Statistical Analysis. In this paper we show that even though the accuracy of the Machine Learning models used (Decision Trees, Logistic Regression, and Random Forest) was between 84%-89% on the training set and 69%-76% on the test set the models lacked good ability to identify the users. Afterwards, additional statistical analysis evidenced that the main driver to use video consultations in a sample of participations with a higher-than-average education is the presence of one or more chronic diseases.

Why "ML in Health Science"

This is the first editorial of the journal, discussing the balance between humans and AI in healthcare and emphasizing the need for a human-centric approach in AI and ML applications.

Advancing Smart Cyber Physical System with Self-Adaptive Software

The proposed integration of DevOps and Digital Twins presents a ground-breaking approach to enhancing the resilience and adaptability of Cyber-Physical Systems in the context of Industry 4.0 and the forthcoming Industry 5.0 era. This research explores the synergistic potential of DevOps principles in fostering collaborative and efficient development and maintenance processes for embedded systems and distributed control systems within CPS. Concurrently, the utilization of Digital Twins offers real-time monitoring and simulation capabilities, heralding a shift towards a human-centric approach to CPS operation. The emphasis on self-adaptive systems within CPS anticipates the ability to address dynamic conditions and unforeseen challenges, paving the way for the evolution of resilient and responsive industrial systems. This research explores the integration of DevOps and Digital Twins in the context of Industry 4.0 and anticipates the requirements of Industry 5.0, emphasizing the need for resilient and human-centric Cyber-Physical Systems. This study investigates the integration of DevOps and Digital Twins to enhance the resilience and adaptability of Cyber-Physical Systems in the context of Industry 4.0 and Industry 5.

Capturing the system requirements for adopting Industry 5.0 in quality inspection: an evidence-based approach

Manufacturers face the challenge of adopting digital solutions to maintain competitiveness in the era of flexible manufacturing. The human remains a crucial asset in ensuring this flexibility. Industry 5.0 strongly emphasizes human-centric approaches to achieve sustainability and resilience in the industry. Notably, in-line quality inspection stands out among the assembly operations to minimize waste and ensure quality. With the increasing trend toward high-mix low-volume manufacturing, the reliance on operators’ traditional tools and cognitive skills for quality inspections is no longer sufficient. Complexity escalates when manual assemblies involve components of varying sizes. Technologies such as augmented reality and computer vision can potentially support quality inspection in manual assembly. However, successful implementation depends on comprehending the specific requirements of the end users. We propose a qualitative approach to refining the requirements in applied research projects that aim to implement human-centered technologies. The approach was applied in a research project for in-line quality inspection with 18 professionals from two manufacturing companies. We instantiated the method using qualitative methods including questionnaires and focus groups with diverse stakeholders with demonstrations. We further investigated the verification and implementation of our method.

Navigating the crossroads of aging, caregiving and technology: Insights from a southern Spain about video-based technology in the care context.

As the world faces an aging population, the complexities of care management become increasingly pronounced. While technological solutions hold promise in addressing the dynamic demands of care, many nuances are to be considered in the design and implementation of active and assisted living technologies (AAL) for older adult care. This qualitative study, set in southern Spain, is positioned at the crossroads of healthcare challenges, as seen by the different actors involved in the care process and the technological solutions developed in response to these challenges. By investigating the complex landscape of caregiving and by examining the experiences and challenges faced by caregivers, healthcare professionals, and older adults, we aim to guide the development of vision-based AAL technologies that are responsive to the genuine needs of older adults and those requiring care. A qualitative research methodology was used in the study. In total15 in-depth interviews and five focus groups were conducted with a diverse group of stakeholders involved in the process of care provision and reception. While the results demonstrate that there is a readiness for technological solutions, concerns over privacy and trust highlight the need for a carefully integrated, human-centric approach to technology in caregiving. This research serves as a compass, guiding future discussions on the intersection of aging, technology, and care, with the ultimate goal of transforming caregiving into a collaborative and enriching journey for all stakeholders involved.

Task Allocation in Human-Robot Collaboration: A Simulation-based approach to optimize Operator's Productivity and Ergonomics

This paper delves into the transformative realm of Industry 4.0, emphasizing the pivotal role of Human-Robot Collaboration (HRC) in redefining manufacturing landscapes. Central to this revolution is the integration of cyber-physical systems, automation, and the Internet of Things (IoT), culminating in the advent of smart manufacturing. We explore how HRC fosters a synergistic work environment, blurring the traditional boundaries between human workers and robotic counterparts. This research emphasizes the importance of intelligent task allocation in optimizing operational efficiency while safeguarding the ergonomic well-being of human operators. A simulation-based approach is presented, focusing on task allocation within HRC contexts to enhance both human operators' productivity and fatigue levels. The study provides an analysis of fatigue dynamics and its repercussions on industrial settings. The paper outlines various collaborative scenarios, including sole human operation, robot support, a Flexible Workstation (F-WS) support, and combined robot-FWS support, evaluated through a case study of an assembly station. The results underscore the tangible benefits of integrating robotic and F-WS support, demonstrating a balanced improvement in processing speed, operator efficiency, and a significant reduction in fatigue accumulation. In conclusion, this paper advocates for a balanced, human-centric approach to Industry 4.0, where the integration of HRC and ergonomic considerations pave the way for a sustainable, efficient, and health-preserving industrial future.

Automated HMI design as a custom feature in industrial SCADA systems

The adoption of emerging technologies under the Industry 4.0 paradigm has resulted in an increased quantity of data projected on the human-machine interface (HMI). This complexity is imposed in combination with users’ limited cognitive capabilities to interpret such data quantity. We foresee this limitation fails to address the human-centric approach of the Industry 5.0 paradigm. To overcome this challenge, an automated approach is proposed to enable user-guided ad hoc visualization forms, which ultimately increases users’ situational awareness of supervised industrial processes. In this paper, we present a framework for introducing automated HMI design as a custom feature of standard SCADA-based HMI functionality and showcase an example of how open technology may be used for such purposes, thus opening new avenues for rapid innovation on SCADA HMI. The framework enables integration of the user-initiated additions for loosely coupled visualization components configurable and integrated into the standard HMI runtime layer to meet changing user needs.

Improved interaction with collaborative robots - evaluation of event-specific haptic feedback in virtual reality

Industry 5.0 adopts a human-centric approach that views humans as a natural part of introducing new technology, such as collaborative robots. However, one of the main challenges in implementing collaborative robots is safety, including the sense of safety. Trust is also a primary challenge when establishing functional collaboration. Influencing factors includes experience and expertise, and research shows that Virtual Reality has the potential to perform such training. This research aims to investigate whether using virtual reality with appropriate feedback can be an effective platform for familiarization and training. In our experiment, we utilized haptic feedback from commercial Virtual Reality controllers to simulate physical interactions with collaborative robots. The experiment involved the participation of fifteen individuals. The results showed that participants regarded haptic feedback while moving as the most appropriate representation. This research aims to identify whether Virtual Reality with suitable feedback can serve as a familiarization and training platform.