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Analyzing interactions between actors from a systems perspective yields valuable information about the overall system's form and function. When this is coupled with ecological modeling and analysis techniques, biological inspiration can also be applied to these systems. The diagnostic value of three metrics frequently used to study mutualistic biological ecosystems (nestedness, modularity, and connectance) is shown here using academic engineering makerspaces. Engineering students get hands‐on usage experience with tools for personal, class, and competition‐based projects in these spaces. COVID‐19 provides a unique study of university makerspaces, enabling the analysis of makerspace health through the known disturbance and resultant regulatory changes (implementation and return to normal operations). Nestedness, modularity, and connectance are shown to provide information on space functioning in a way that enables them to serve as heuristic diagnostics tools for system conditions. The makerspaces at two large R1 universities are analyzed across multiple semesters by modeling them as bipartite student‐tool interaction networks. The results visualize the predictive ability of these metrics, finding that the makerspaces tended to be structurally nested in any one semester, however when compared to a "normal" semester the restrictions are reflected via a higher modularity. The makerspace network case studies provide insight into the use and value of quantitative ecosystem structure and function indicators for monitoring similar human‐engineered interaction networks that are normally only tracked qualitatively. [ABSTRACT FROM AUTHOR]

Fire is a serious threat to people's lives and property. Be aimed at the low detection accuracy of the current fire detection system, a fire detection system based on one-chip computer is proposed in this work. To achieve fire detection and warning, the system collects these signals such as smoke and temperature from the surrounding environment, and processes them with a one-chip computer. The simulation experiments of the system are conducted with Proteus, and the experimental results indicate that the system can detect accurately. [ABSTRACT FROM AUTHOR]

X-ray imaging can be efficiently used for high-throughput in-line inspection of industrial products. However, designing a system that satisfies industrial requirements and achieves high accuracy is a challenging problem. The effect of many system settings is application-specific and difficult to predict in advance. Consequently, the system is often configured using empirical rules and visual observations. The performance of the resulting system is characterized by extensive experimental testing. We propose to use computational methods to substitute real measurements with generated images corresponding to the same experimental settings. With this approach, it is possible to observe the influence of experimental settings on a large amount of data and to make a prediction of the system performance faster than with conventional methods. We argue that a high accuracy of the image generator may be unnecessary for an accurate performance prediction. We propose a quantitative methodology to characterize the quality of the generation model using Probability of Detection curves. The proposed approach can be adapted to various applications and we demonstrate it on the poultry inspection problem. We show how a calibrated image generation model can be used to quantitatively evaluate the effect of the X-ray exposure time on the performance of the inspection system. [ABSTRACT FROM AUTHOR]

There is a growing demand for indoor positioning systems (IPSs) in a wide range of applications. However, traditional solutions such as GPS face many technical challenges. In recent years, a promising alternative has been emerging, the visible light communication (VLC)-based IPS, which offers a combination of high accuracy, low cost, and energy efficiency. This article presents a comprehensive review of VLC-based IPSs, providing a tutorial-like overview of the system. It begins by comparing various positioning systems and providing background information on their inherent limitations. Experimental results have demonstrated that VLC-based systems can achieve localization accuracy to within 10 cm in controlled environments. The mechanisms of VLC-based IPSs are then discussed, including a comprehensive examination of their performance metrics and underlying assumptions. The complexity, operating range, and efficiency of VLC-based IPSs are examined by analyzing factors such as channel modeling, signal processing, and localization algorithms. To optimize VLC-based IPSs, various strategies are explored, including the design of efficient modulation schemes, the development of advanced encoding and decoding algorithms, the implementation of adaptive power control, and the application of state-of-the-art localization algorithms. In addition, system parameters are carefully examined. These include LED placement, receiver sensitivity, and transmit power. Their impact on energy efficiency and localization accuracy is highlighted. Altogether, this paper serves as a comprehensive guide to VLC IPSs, providing in-depth insights into their vast potential and the challenges that they present. [ABSTRACT FROM AUTHOR]

Objective: The objective of our research is to advance the understanding of behavioral responses to a system's error. By examining trust as a dynamic variable and drawing from attribution theory, we explain the underlying mechanism and suggest how terminology can be used to mitigate the so-called algorithm aversion. In this way, we show that the use of different terms may shape consumers' perceptions and provide guidance on how these differences can be mitigated. Background: Previous research has interchangeably used various terms to refer to a system and results regarding trust in systems have been ambiguous. Methods: Across three studies, we examine the effect of different system terminology on consumer behavior following a system failure. Results: Our results show that terminology crucially affects user behavior. Describing a system as "AI" (i.e., self-learning and perceived as more complex) instead of as "algorithmic" (i.e., a less complex rule-based system) leads to more favorable behavioral responses by users when a system error occurs. Conclusion: We suggest that in cases when a system's characteristics do not allow for it to be called "AI," users should be provided with an explanation of why the system's error occurred, and task complexity should be pointed out. We highlight the importance of terminology, as this can unintentionally impact the robustness and replicability of research findings. Application: This research offers insights for industries utilizing AI and algorithmic systems, highlighting how strategic terminology use can shape user trust and response to errors, thereby enhancing system acceptance. [ABSTRACT FROM AUTHOR]

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The nuclear energy sector can benefit from mobile robots for remote inspection and handling, reducing human exposure to radiation. Advances in cyber–physical systems have improved robotic platforms in this sector through digital twin (DT) technology. DTs enhance situational awareness for robot operators, crucial for safety in the nuclear energy sector, and their value is anticipated to increase with the growing complexity of cyber–physical systems. The primary motivation of this work is to rapidly develop and evaluate a robot fleet interface that accounts for these benefits in the context of nuclear environments. Here, we introduce a multimodal immersive DT platform for cyber–physical robot fleets based on the ROS‐Unity 3D framework. The system design enables fleet monitoring and management by integrating building information models, mission parameters, robot sensor data, and multimodal user interaction through traditional and virtual reality interfaces. A modified heuristic evaluation approach, which accounts for the positive and negative aspects of the interface, was introduced to accelerate the iterative design process of our DT platform. Robot operators from leading nuclear research institutions (Sellafield Ltd. and the Japan Atomic Energy Agency) performed a simulated robot inspection mission while providing valuable insights into the design elements of the cyber–physical system. The three usability themes that emerged and inspired our design recommendations for future developers include increasing the interface's flexibility, considering each robot's individuality, and adapting the platform to expand sensor visualization capabilities. [ABSTRACT FROM AUTHOR]

In my study, I spotlight the concept of digital humanism and briefly examine some aspects of the complex process that has become known in recent years as “digital transformation”. Throughout the paper, the underlying question persists: how does digitalization impact various human communities, and what (new) emphases emerge in the different formulations of responses to digitalization as a challenge? Given the monumental nature of the topic, with nearly every aspect being dynamic, malleable, and continuously evolving, I view this study as an outline and a thought-provoking piece, and I ask the reader to do the same. Although some global information and communication technology (ICT) guidelines and strategies appear to be already accepted, ICT itself, along with the human thinking that enables it, is perpetually dynamic. There is no “definitively” closed horizon as long as the observer of that horizon sees it as such. This is why it is important to realize that our actions, both within and outside the digital space, intentionally or unintentionally impact the process of digital transformation. In doing so, we influence its realization, thereby creating realities where humans control technology, not the other way around. [ABSTRACT FROM AUTHOR]

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cerebral palsy is a disorder of central motor and postural development, resulting in limited mobility. Cerebral palsy is often accompanied by cognitive impairment and abnormal behavior, significantly impacting individuals and society. Time, energy, and economic investment in the rehabilitation process is substantial, yet the rehabilitation outcomes often remain unsatisfactory. Additionally, some patients have limited sensory perception during rehabilitation training, making it challenging to effectively regulate exercise intensity. Traditional evaluation methods are mostly based on recovery performance, lack guidance at the neurophysiological level, and have an unequal distribution of medical rehabilitation resources, which pose great challenges to the rehabilitation of patients. Based on the issues mentioned above, this paper proposes a real-time cerebral signal monitoring system based on wearable devices. This system can monitor and store blood oxygen, heart rate, myoelectric, and EEG signals during cerebral palsy rehabilitation, and it can track and monitor signals during the rehabilitation treatment process. The system includes two parts: hardware design and software design. The hardware design includes a data signal acquisition module, a main control chip (ESP32), a muscle electrical sensor module, a brain electrical sensor module, a blood/heart rate acquisition module, etc. It is primarily for real-time signal data acquisition, processing, and uploading to the cloud server. The software design includes functions such as data receiving, data processing, data storage, network configuration, and remote communication and enables the visual monitoring of data signals. The system can achieve real-time monitoring of electromyography, electroencephalography, and blood oxygen levels, as well as the heart rate of patients with cerebral palsy, and adjust rehabilitation training in real-time during the rehabilitation process. At the same time, based on the real-time storage of the original electromyography and electroencephalography data, it can provide auxiliary guidance for later rehabilitation evaluation and effective data support for the entire rehabilitation treatment process. [ABSTRACT FROM AUTHOR]

Activity recognition combined with artificial intelligence is a vital area of research, ranging across diverse domains, from sports and healthcare to smart homes. In the industrial domain, and the manual assembly lines, the emphasis shifts to human–machine interaction and thus to human activity recognition (HAR) within complex operational environments. Developing models and methods that can reliably and efficiently identify human activities, traditionally just categorized as either simple or complex activities, remains a key challenge in the field. Limitations of the existing methods and approaches include their inability to consider the contextual complexities associated with the performed activities. Our approach to address this challenge is to create different levels of activity abstractions, which allow for a more nuanced comprehension of activities and define their underlying patterns. Specifically, we propose a new hierarchical taxonomy for human activity abstraction levels based on the context of the performed activities that can be used in HAR. The proposed hierarchy consists of five levels, namely atomic, micro, meso, macro, and mega. We compare this taxonomy with other approaches that divide activities into simple and complex categories as well as other similar classification schemes and provide real-world examples in different applications to demonstrate its efficacy. Regarding advanced technologies like artificial intelligence, our study aims to guide and optimize industrial assembly procedures, particularly in uncontrolled non-laboratory environments, by shaping workflows to enable structured data analysis and highlighting correlations across various levels throughout the assembly progression. In addition, it establishes effective communication and shared understanding between researchers and industry professionals while also providing them with the essential resources to facilitate the development of systems, sensors, and algorithms for custom industrial use cases that adapt to the level of abstraction. [ABSTRACT FROM AUTHOR]

Structured meshes are becoming increasingly popular as a discretization technique in industries where solution accuracy is of paramount importance. However, generating structured meshes directly on the model surface presents a challenge. Consequently, many researchers are now exploring mapping methods for structured mesh generation. In this context, parameterization algorithms are vital as they map the model surface from 3D space to a 2D parametric domain. Existing parameterization algorithms, despite their advancements, still face limitations in preserving symmetry information from the input model. To address this issue, we propose a symmetry preserving parameterization algorithm based on geometric constraint. This algorithm utilizes plane reflection symmetry transformation to identify the main symmetry plane of the model and calculate the symmetry factor. Based on the fixed points and the symmetry factor, a conformal parametric symmetry plane is obtained. Furthermore, we develop a surface structured mesh generation system to provide engineers with a tool that can rapidly generate meshes. Experimental results demonstrate that our proposed algorithm achieves higher quality results compared to other parameterization algorithms. [ABSTRACT FROM AUTHOR]

Copyright of Grafica: Journal of Graphic Design / Documents de Disseny Gràfic is the property of Universitat Autonoma de Barcelona and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The complexity of engineered systems has grown leaps and bounds over the last forty years. One of the main challenges in modern engineering is managing this complexity, particularly as the pace of technological change continues to accelerate across industries. While most systems professionals agree, a viable early design concept is crucial to meeting stakeholders' needs and successfully scoping a development program, traditional early concept generation approaches focus on a design‐first approach, often glossing over an analysis of system intent and a synthesis of system goals and objectives. This tendency leads to an early focus on low‐level, highly‐granular design activities that focus on advanced technologies as design components instead of on the high‐level policy or desired emergence that the new system is being designed to achieve. To combat these shortcomings, this paper introduces a new framework for conceptualizing an early design for novel, complex systems in aerospace and defense that are employed as part of a portfolio‐of‐systems in an attempt to achieve a high‐level policy or portfolio‐level capability. It outlines an intent model for framing a new system's contribution to a portfolio‐level capability, and it posits a framework for delivering a new model for early design concepts while providing a foundation to extend system‐theoretic hazard and security analysis techniques to systematically analyze safety and security engineering challenges for the designs in the earliest possible phase of their lifecycle. [ABSTRACT FROM AUTHOR]

Copyright of Signos is the property of Universidad Santo Tomas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

INTRODUCTION: This paper describes the method for assigning medical diagnostic and treatment capabilities and resources to the database which assists with an updated probabilistic risk analysis (PRA) tool for exploration class medical system planning. The National Aeronautics and Space Administration has used PRA since 2011 to inform mission medical system design, but existing tools are designed only for low Earth orbit. An updated PRA tool was needed to assist with exploration class missions. METHODS: A team of medical experts with a wide range of expertise and experience, including Space Medicine, was assembled to build capability and resource tables for the new PRA tool. This team met over 8 mo and used practice guidelines, literature, and experience to build capability and resource tables (CRTs) for each condition in the new PRA tool database. RESULTS: This process led to CRTs for each condition and a total of 617 distinct capabilities and 839 discrete resources. CONCLUSION: The CRT method is an effective way to translate medical practice guidelines into capabilities and resources usable by PRA tools for exploration class medical system planning. This same method may be used in commercial space ventures and in other applications in which medical predictive analytics are informative. [ABSTRACT FROM AUTHOR]

Introduction: Telehealth systems, including patient telemonitoring systems, have consistently faced challenges in user adoption since their introduction. The diversity and conflicts in users' views, needs, and concerns about changes in health service delivery create a complex situation, which can be defined as a "soft problem." Designing these systems requires an approach to understand the issues and complexities and achieve feasible solutions considering the social and cultural conditions of the implementation environment. This research aims to use the modified soft systems methodology framework as a structured method to tackle these soft problems in the design and implementation of patient telemonitoring systems from the perspective of human factors. Methods: This research employs a hybrid approach, incorporating soft systems methodology to identify problems, define requirements, and determine actions, alongside the NASSS framework as a theoretical lens to guide participants' views. This approach was used to develop the patient telemonitoring system with a focus on system adoption. The study involved conducting interviews, drawing rich pictures, analyzing users' views, identifying problems during the finding phase, and performing root definition, CATWOE analysis, and presenting conceptual models in the modeling phase. During the discussion and definition phases, based on conceptual models from physicians' and patients' perspectives, desirable and feasible actions were defined. Results and discussion: Semi-structured interviews were conducted with 15 physicians and 13 patients, individually and in groups of two and three, as end-users of the patient telemonitoring system. The interview results were analyzed, and participants' views were categorized into four issues: telemonitoring process requirements, trust in the system, cost-effectiveness, and the implementation of the telemonitoring system within the current hospital structure and procedures. In the modeling phase, root definitions were created using the PQR formula and enriched with CATWOE analysis. Conceptual models of the problems were then presented based on patients' and physicians' perspectives. Finally, after the discussion and definition phases, desirable and feasible actions for developing the patient telemonitoring system were defined in four dimensions: expected system features, executive processes, required rules and instructions, and necessary policies. Conclusions: The results show that soft systems methodology, by understanding human factors' perspectives and identifying and conceptualizing the problems and complexities of various aspects of the patient telemonitoring system, can significantly aid system developers, implementers, and health system policymakers. It helps them understand the requirements and agreed processes of potential users before design and implementation, reducing resistance and increasing user adherence. [ABSTRACT FROM AUTHOR]

Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In response to mcomplexity inefficiency caused by the use of VGG16/VGG19 or traditional texture imitation in existing style transfer tystems, the aim of this paper is to create a user-friendly, high-performance and highly interactive deep learning-based transfer prototype system. The system was designed to its use among the general public and stimulate creative production in the professional art fieLi. Taking the impressionistic style as an female using CycleGAN, SSIM index and user subjective evaluation for effect measurement, all of them have different magnitudes of improvement compared within the traditional VGG19, with the lowest improvement of 29. 33% and the highest improvement of 153. 52% in the test group. In addition, for the user side, a style migration prototype system was developed, which allows users to realize the impressionistic style migration of hand-works and uploaded images through an easy-to-use interface. The system display and user experience were optimized and received positive feedback from users. These results show its great potential in the field of enhancing users' aesthetic awareness and computer-aided design, and provide new ideas for future esthetic education and artistic creation. [ABSTRACT FROM AUTHOR]