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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]

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.)

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]

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.)

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]

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]

In the Hualong-1 Unit (HPR1000), the hydrogen (H2) concentration should be reduced to 15 mL (STP)/kg 24 h before reactor shutdown when the reactor vessel is scheduled to be opened. The traditional degassing method, i.e., letting down the reactor coolant through a chemical and volume control system, will take longer, and its operation is more complicated. To shorten the degassing time and simplify the operation, this paper proposes a pressurizer degassing system design for HPR1000 by applying the pressurizer as thermal degassing equipment. Then, the degassing system optimization analysis is carried out under a full range of steady operating conditions during shutdown, and the optimal size of the flow-limiting orifice plate is obtained. Meanwhile, in order to verify the transient characteristic during the degassing process to ensure operating safety, a dedicated transient degassing program based on an improved non-equilibrium multi-region pressurizer model and a transient degassing model is used to carry out a transient simulation analysis of this process. The transient simulation results show that, under bounding conditions of hot-zero-power operation, during the degassing process, the pressure of the pressurizer decreases by a maximum of 0.038 MPa and the water level increases by 0.016 m above the normal level. As can be seen, both the pressure and water level are within the normal operation band and shall not initiate any safety signal. Meanwhile, the entire transient process lasts approximately 24 min and then enters a stable degassing period. It takes approximately 5.2 h to remove the gas dissolved in the reactor coolant from 35 mL (STP)/kg to 15 mL (STP)/kg. The analysis shows that the pressurizer degassing system designed for HPR1000 is safe, effective, and reliable. [ABSTRACT FROM AUTHOR]

Objective: Aiming at the shortcomings of artificial surgical path planning for the thermal ablation of liver tumors, such as the time-consuming and labor-consuming process, and relying heavily on doctors' puncture experience, an automatic path-planning system for thermal ablation of liver tumors based on CT images is designed and implemented. Methods: The system mainly includes three modules: image segmentation and three-dimensional reconstruction, automatic surgical path planning, and image information management. Through organ segmentation and three- dimensional reconstruction based on CT images, the personalized abdominal spatial anatomical structure of patients is obtained, which is convenient for surgical path planning. The weighted summation method based on clinical constraints and the concept of Pareto optimality are used to solve the multi-objective optimization problem, screen the optimal needle entry path, and realize the automatic planning of the thermal ablation path. The image information database was established to store the information related to the surgical path. Results: In the discussion with clinicians, more than 78% of the paths generated by the planning system were considered to be effective, and the efficiency of system path planning is higher than doctors' planning efficiency. Conclusion: After improvement, the system can be used for the planning of the thermal ablation path of a liver tumor and has certain clinical application value. [ABSTRACT FROM AUTHOR]

In recent years, there has been a rising interest in using gamification to promote local intangible cultural heritage. Gamification can make cultural heritage more accessible and relatable by transforming traditional practices into interactive digital experiences. Traditional hand-woven fabrics of tribal communities of Northeast India represent their cultural expression and identity. However, industrialization and globalization have negatively affected the inheritance of the traditional weaving practices. Their traditional fabrics also carry a rich legacy of oral narratives, which are underappreciated and at risk of being lost due to lack of adequate documentation. This paper attempts to investigate the relevance of using gamification for the dissemination of oral narratives embedded within the traditional fabrics of tribal communities of Northeast India. It further proposes a gamified system model to disseminate the oral cultural expressions associated with tribal fabrics and their textile heritage. It also integrates instructional design approach for creating a gamified learning environment for fostering cultural awareness and education among young generation of the tribal communities. This model may also offer a new approach for digitally archiving indigenous intangible cultural heritage. [ABSTRACT FROM AUTHOR]

Flexibility is a critical process competency for delivering mass customized services. Coproduction systems involve the customer as a productive resource alongside the firm's resources to co-create this customized service. This study analyses the performance and applicability of resource flexibility and service modularity for the design of such coproduction systems. Particularly, it examines the role of level of coproduction, positioning of the customer performed activities in the process flow, and the interplay of level of coproduction with other system parameters in selecting the design alternative. We employ a suite of simulation modelling tools towards this purpose. Contrary to popular belief, the results indicate that the dominance of the resource flexibility strategy is not absolute for coproductive systems, especially when costs are considered. Service modularity strategy is preferred for systems with higher levels of coproduction and when customer-performed tasks are positioned in the middle of the process flow. Our sensitivity analysis shows that not all service providers implementing a resource flexibility strategy can respond in the same way to changes in system conditions. When resource costs are considered, there exists a zone where the sensitivity demonstrates a perverse effect. Furthermore, our results show that pure strategies are superior to mixing components from the two alternatives and we characterize their preference in the form of a single threshold policy. The insights from this study will also be of interest to practitioners designing and managing coproductive systems. [ABSTRACT FROM AUTHOR]

Over the past decade, existing online social networks have emerged as vital platforms for fostering and nurturing social relationships. However, their reliance on text and multimedia-based interactions has posed limitations, particularly in terms of accessibility and hands-free operation, and in turn, impeded the full potential of online social networking. Voice-based social networks (VBSNs) offer a way to address these constraints by enabling multitasking through real-time audio communication, catering to a broader spectrum of users. To ensure the widespread adoption and practical utility of VBSNs, it is imperative that voice-based social networks and their applications offer secure and privacy-preserving services. In this paper, we outline the urgent requirements for voice-based social networks and evaluate existing open-source online social networking software and platforms to find the most suitable one for developing a testbed for VBSNs. Employing the chosen platform, we propose a design for VBSN testbed that facilitates the development and evaluation of VBSN applications while ensuring robust security and privacy measures through a blockchain-based decentralized identity and reputation mechanism. This proposed testbed serves as a valuable resource for researchers and developers to explore and address security and privacy concerns within the realm of voice-based social networking, enhancing the quality and reliability of their innovations. [ABSTRACT FROM AUTHOR]

Traditional Chinese language teaching methods have always had problems, such as a lack of practical opportunities and interest and an inability to provide sufficient language environment and context. Virtual reality technology provides new possibilities to solve these problems. Through in-depth research and analysis, this article designs and develops a Chinese language teaching system based on virtual reality technology. This system utilizes virtual reality technology to create a simulated 3D Chinese language environment, enabling learners to experience interactive experiences firsthand. The system includes speech recognition, natural language processing, and artificial intelligence, enabling real-time language communication and student interaction. This system s design considers students learning needs and interests, allowing them to practice their Chinese application skills in realworld simulated environments. This system has broad prospects in Chinese language education and provides new research and innovation directions for educational institutions and developers. [ABSTRACT FROM AUTHOR]

Despite many benefits, the extensive deployment of Health Information Technology (HIT) systems by healthcare organizations has encountered many challenges, particularly in the field of telemetry concerning patient monitoring and its operational workflow. These challenges can add more layers of complexity when an unplanned software security patching is performed, affecting patient monitoring and causing disruption in daily clinical operations. This study is a reflection on what happened associated with software security patching and why it happened through the lens of an incident report to develop potential preventive and corrective strategies using qualitative analyses--inductive and deductive approaches. There is a need for such analyses to identify the underlying mechanism behind such issues since very limited research has been conducted on the study of software patching. The incident was classified as a "software functionality" issue, and the consequence was an "incident with a noticeable consequence but no patient harm", and the contributing factor was a software update, i.e., software security patching. This report describes how insufficient planning of software patching, lack of training for healthcare professionals, contingency planning on unplanned system disruption, and HIT system configuration can compromise healthcare quality and cause risks to patient safety. We propose 15 preventive and corrective strategies grouped under four key areas based on the system approach and socialtechnical aspects of the patching process. The key areas are (i) preparing, developing, and deploying patches; (ii) training the frontline operators; (iii) ensuring contingency planning; and (iv) establishing configuration and communication between systems. These strategies are expected to minimize the risk of HIT-related incidents, enhance software security patch management in healthcare organizations, and improve patient safety. However, further discussion should be continued about general HIT problems connected to software security patching. [ABSTRACT FROM AUTHOR]

Internet, also known as the Internet, refers to the huge Internet connected between the LAN and the LAN, which connects a huge Internet from a set of common protocols. Today, accurate real-time multimedia information publishing technology has been widely used in many fields. In order to achieve the purpose of information disclosure, the multimedia information disclosure system uses multimedia resources as an object, and the resources are displayed by the user's editing of the management party multimedia resource. With the increased workload of management and multimedia's maintenance information, the current multimedia information management and control software cannot meet the needs of the market. In order to ensure the real-time, accuracy of the multimedia information disclosure, it is necessary to check if the speech recognition technology can accurately collect voice information. Techniques are particularly important for speech recognition, so it is also called automatic voice recognition; its purpose is to convert the words content contained in human speech to computer recognition content. It is different from the speaker's identification, the speaker is different, the latter tries to identify or confirm that the person who makes a voice, rather than identifying or confirming the vocabulary included. However, voice recognition technology requires a very perfect system design, and the system design can use system science ideas and methods, according to systematic analysis results, it is also possible to design a new system. Therefore, this paper uses the voice system on the Internet to provide a solution to the inaccuracicity in speech recognition technology, and use speech recognition techniques to disclose multimedia information. [ABSTRACT FROM AUTHOR]

A method for constructing a feedback that ensures the attraction of trajectories of an affine system to an equilibrium state and to a given manifold is proposed. The feedback is found in an analytical form as a solution to an auxiliary optimal control problem. Sufficient conditions for the existence of the optimal control are given. Application of the proposed method to some classes of linear and nonlinear systems is discussed. [ABSTRACT FROM AUTHOR]

To address the issues of excessive heat loss from the roofs of multi-span greenhouses and high energy consumption for heating during winter production, we propose an approach for the external insulation of the roof of multi-span glass greenhouses and have developed an external insulation system (EIS) to practice this approach. The system achieved full coverage of the greenhouse roof through mechanized unfurling and furling of external thermal blankets, thereby achieving energy-saving insulation. This paper describes the overall design and working method of the EIS, providing detailed design and structural parameters for critical components such as the traction rope transmission mechanism and the rail-type sealing structure. Through a system verification experiment, the specifications of the traction rope were determined and the rationality of the EIS's thermal blanket unfurling and furling time was confirmed. An insulation performance experiment indicated that the average heat flux of the greenhouse roof covered with the external thermal blanket over 14 continuous nights was 54.2 W/m2, compared with 198.6 W/m2 for a single-layer glass roof. Covering the roof with the external thermal blanket reduced heat loss from the glass roof by 72.7%. The average heat flux of the roof of the Venlo-type multi-span greenhouse with double-layer internal insulation was 99.9 W/m2 during the same period, indicating that the heat loss from the roof using external insulation was only 50.3%. This study provides a novel thermal insulation approach and an energy-saving system for multi-span greenhouses. [ABSTRACT FROM AUTHOR]

Objective: Assess operator performance in a simulation of US Coast Guard small boat recovery to a larger vessel on a large scale, six degree-of-freedom, full motion simulator. Background: Studies of human performance in small boat recovery task have never been conducted on a high amplitude, low frequency simulator. Empirical evidence of small boat recovery task performance in challenging motion conditions is needed to inform future maritime systems designs. Method: Experienced active-duty boat crewmembers (N = 13) conducted a small boat recovery task in three sea states on the Vertical Motion Simulator (VMS) at the NASA Ames Research Center. Task performance was assessed using a task equivalent for time to complete the task. Participant behaviors associated with increasing motion severity were observed. Results: Task performance declined as motion conditions became more severe. Participants were more likely to use at least one hand to maintain balance during motion conditions, becoming more frequent with increasing motion severity. Many participants used one hand to complete the task despite contrary instructions and previous experience. Conclusion: Two design recommendations were proposed to counter declining task performance in increasingly severe motion conditions. Handholds available to participants during the task, and task design supporting single handed completion were recommended for small boat recovery systems. Application: This research is directly applicable to gross motor tasks requiring simultaneous maintenance of balance in a maritime environment, and may be extended to other environments where humans experience complex motions while completing tasks. [ABSTRACT FROM AUTHOR]

Problem-based learning has been one of the major pedagogies that support various learning styles, utilizing problems as a key element in studies. While there are many ways to solve a problem, Computational Thinking can be one of them. Typically, we formulate learning outcomes and design assessments to attain these goals. However, there are cases where a single outcome may not suffice, especially with multi-layered problems. In such scenarios, we propose using Dublin Descriptors and evaluate the study using system design problems. Two case studies were designed, requiring students to reflect on the components of computational thinking. Reflections in the second case study were designed according to the written Dublin Descriptors. We conducted qualitative and quantitative analyses on data from 37 students in two case studies to identify themes related to Bloom's and Dublin Descriptors, using In Vivo, Descriptive, and Focus coding in two rounds of analysis. Statistical inferences suggest that the method holds promise for cases requiring advancement beyond Level 4. Dublin Descriptors show promise in cases where information needs to be communicated from ideas to inferences. [ABSTRACT FROM AUTHOR]

The fast progress of artificial intelligence (AI) technology has significantly impacted the field of interpretation. Nonetheless, interpretation education at many Chinese schools and universities is poor quality. It strongly emphasizes theory while providing basic content, resulting in minimal pupil growth. Furthermore, existing interpretation assessment procedures must be revaluated to improve comprehensive instructional growth. Aiming at this problem, this paper systematically constructs the Automatic Interpretation Assessment System by integrating key components. Firstly, this paper explains the significance of interpretation as a cognitive bridge between AI and human cognition by emphasizing the critical relevance of interpretability in AI systems. Second, the research explores the intricacies of the internal workings of backpropagation (BP) neural networks. It explains their structural composition, signal propagation processes, and weight adjustment procedures, all of which are strategically employed to enable optimal learning within the context of the model. Third, it integrates genetic algorithms (GA) with BP neural networks in a unique way, combining the optimization capabilities of GA. This collaborative strategy employs selection, crossover, and mutation strategies to improve system performance and create a strong issue-detection feedback mechanism. Finally, utilizing interpretable AI theory, the study methodically creates the Automatic Interpretation Assessment System. This approach has a three-tier paradigm, with careful evaluation criteria including interpreter ability and skill. The requirements include bilingual competence, extra-lingual knowledge, interpreting abilities, professional excellence, and psychological quality. We comprehensively evaluated using essential parameters such as accuracy, precision, recall, F1 score, and execution time. These results demonstrate that our proposed system excels with an accuracy of 95%, a precision of 94%, a recall of 96%, and an F1-score of 0.95, showcasing its superiority over the other systems. These findings highlight our proposed system effectiveness in reliably assessing interpretation quality and efficient processing capabilities. [ABSTRACT FROM AUTHOR]

This paper describes a practical methodology for benchmarking the Intelligent Traffic Management System (ITMS) of Smart City Application. It explains the complete development of the application from defining requirements to verifying the software. The system design is demonstrated using MATLAB System Composer. To achieve the intelligent traffic system, we used the You Only Look Once (YOLO) v5 algorithm for vehicle detection. The other deep learning prediction logics are shown to realize the various features such as the optimal route detection, hi‐traffic detection of ITMS. Followed by the verification and structural coverage of Intelligent Traffic Management System is demonstrated with example. [ABSTRACT FROM AUTHOR]

With the rapid development of science and technology, intelligent logistics plays an increasingly important role in various fields. This study focuses on the design, application and optimization of intelligent logistics system. Through empirical analysis and model construction, the design and division of system architecture are deeply discussed, and the efficient operation of the system is realized with the support of cloud computing platform. By collecting and preprocessing a large amount of actual data, a complete system modeling scheme is constructed in this study. Then, relying on user feedback, the system is deeply evaluated and continuously optimized to achieve a more userfriendly intelligent logistics service. The research results show that through scientific system design and model construction, combined with advanced cloud computing technology and user experience evaluation, the performance and application value of intelligent logistics system can be significantly improved. [ABSTRACT FROM AUTHOR]

With the growth of the Internet, network security issues have become increasingly complex, and the importance of node interaction security is also gradually becoming prominent. At present, research on network security protection mainly starts from the overall perspective, and some studies also start from the interaction between nodes. However, the trust management mechanisms in these studies do not have a predictive function. Therefore, to predict trust levels and protect network security, this paper innovatively proposes a trust management system for network security protection based on the improved hidden Markov model. The research divides the trust level of inter-node interactions by calculating the threat level of inter-node interactions and predicts the trust level of inter-node interactions through an optimized hidden Markov model. In addition, the study designs an estimation of the types of interactive threats between nodes based on alarm data. The research results show that when inactive interaction tuples are not excluded, the average prediction accuracy of the combined model is 95.5%. In response time, the maximum values of the active and passive cluster management pages are 38 ms and 33 ms, respectively, while the minimum values are 16 ms and 14 ms, with an average of 26.2 ms and 24 ms, respectively. The trust management system designed by the research institute has good performance and can provide systematic support for network security protection, which has good practical significance. [ABSTRACT FROM AUTHOR]

Traditional planar double-enveloping hourglass worm pairs have the characteristics such as the strong bearing capacity, high transmission efficiency and long life-span. However, the high relative sliding velocity and the serious agglutination or abrasion may also occur at the contact point on tooth surfaces. In this paper, a novel type of double-roller hourglass worm pair is proposed and analyzed, wherein, the worm part adopts from the planar double-enveloping worm pair, the corresponding meshing tooth surface of worm gear is replaced by two rows of cylinder rollers for reducing friction and enhancing meshing efficiency. That is, the original meshing tooth surfaces in worm gear are replaced by the common tangent plane of rollers to form a special type of meshing drive, the original line-contact form between tooth surfaces was changed to point-contact so that the sliding friction was transformed into rolling friction, and the meshing efficiency can be greatly improved. The theoretical model of double-roller hourglass worm pair was established based on spatial enveloping principle, the meshing equation and tooth surface equations were derived. The solid models of worm and gear were established and assembled. The parameters of enveloping surface angle, roller radius and friction coefficient, which affecting relative motion velocity at meshing contact point and efficiency during the whole transmission process was analyzed and discussed systematically. The results showed that comparing to the traditional worm pair, the roller's rotation greatly reduced the relative sliding velocity and improved meshing efficiency at the contact point in this double-roller hourglass worm pair. [ABSTRACT FROM AUTHOR]

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The solar photovoltaic system is one of the technologies which is used to pump water in rural, isolated and desert areas where electric connection to the main grid is a problem. The study area is selected because of its higher natural resources of solar radiation over the year. Thus, that encourages us to adopt this study in order to understand the effects of various operating parameters on performance behaviour, which leads to enhancing the system design. This paper aims to assess the solar water pump system's design and estimated performance in real environmental conditions. The PVsyst has been used to design and simulate a system which allows us to analyse the operating behaviour of a photovoltaic solar water pumping system. The solar PV pumping system design is considered; the photovoltaic module has characteristics and the pumping system characteristics. The photovoltaic array losses due to temperature were estimated about −14.3% and the soiling losses represented approximately −5%. The results showed that performance losses were significant variance in the months of the summer season from May to July. Therefore, their implication on the water flow rates significantly decreases throughout the months of the summer season from May to July, respectively. [ABSTRACT FROM AUTHOR]

The aerospace industry is one of the leading figures in the development and improvement of techniques for the design of new products. One of the most promising developments of the last decades is the exploitation of digital models that make it possible to evaluate design solutions and simulate the behavior of the individual systems and their interactions. The goal is to be able to predict and analyze all aspects an aircraft much in advance of its industrialization in order to heavily reduce the time and costs of product development and to guarantee flexibility to test a multitude of solutions. The main issue in this context is the complexity of creating models that are capable of accurately sizing and simulating multiple interacting systems, thus considering the constraints imposed by the need for their mutual compatibility. The present contribution introduces two interconnected models regarding an aircraft system, in particular, the landing gear, that make it possible to size its main components and subsystems and to use the found parameters to populate a dynamic model that simulates the behavior of the aircraft during landing. These models provide a preliminary digitalization of the system itself and of the design process as well, thereby making it possible to define a potential configuration and to test it in a dynamic virtual environment, thus taking into account the interaction between the individual subsystems. The model was tested through three use cases, differentiated by class and scope, which made it possible to compare and validate the obtained results with actual values. [ABSTRACT FROM AUTHOR]

This is an opinion paper of an examination of effects-based ideas. It examines the idea from its fundamental concept. This is developed to examine its broader application to more than air force operations to almost any project concerning military, social, political, and business. In fact, this approach can be used wherever effects of project development have external implications outside systems boundaries and where unforeseen internal implications can affect society. [ABSTRACT FROM AUTHOR]

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Despite substantial gains facilitated by Artificial Intelligence (AI) in recent years, it has to be applied very cautiously in sensitive domains like medicine due to the lack of explainability of many methods in this field. We aim to provide a system to overcome these issues of medical AI applications by means of our concept of medical operational AI detailed in this paper. We make use of various methods of AI and utilize knowledge graphs in particular. The latter is continuously updated by medical experts based on medical literature such as peer-reviewed papers and standard online sources such as UpToDate. We thoroughly derive a multi-level system tackling the corresponding challenges. In particular, its design encompasses (i) holistic diagnostic assistance on a macro level, (ii) predicitions and detailed suggestions for specific medical domains on a micro level, as well as (iii) AI-based optimizations of the overall system on a meta level. We detail practical merits of medical operational AI and discuss the state of the art beyond our solution. [ABSTRACT FROM AUTHOR]

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The integration and remoteness of mobile terminals, as well as local area network-based office issues, have basically been solved, that is, a solution established on the basis of a cloud service collaborative platform, which can be implemented between various service systems. Each place enters the office system at all times to process related business, which improves the overall efficiency of our company's collaboration, and each information management system is no longer an information island. Technically, this article provides the possibility for the implementation of the system, and analyzes in detail the business requirements, performance requirements and functional modules of the system. In addition, it briefly introduces the requirements for the key technical means used. The system designed in this paper can effectively process a large amount of data and improve the operation efficiency of the system by separating the front-end management and back-end management. More importantly, the collaborative office platform designed by this system increases the sharing degree of information to the maximum, which can effectively reduce useless work, maximize work efficiency, and stimulate the enthusiasm of workers. At the same time, the operating costs of the system are reduced. It realizes the integration of information processing of data and efficient management of data. [ABSTRACT FROM AUTHOR]

High-technology businesses face severe competition in their respective industries, necessitating constant innovation of their systems through the infusion of new technologies. To this end, these companies incorporate multiple technologies into new successful systems to improve key requirements that can ultimately affect the overall revenue and profitability of their systems. In many cases, comprehensive effects of infused technologies including improvements to the overall system performance, the extent of engineering design change, total investment cost, and profitability, are assessed a posteriori. In this study, a structured assessment framework was introduced for the infusion of multiple technologies into a parent system. The framework was conceived to address the requirements of companies for technology-based system development that need to assess the impact of infusing multiple technologies into their system. The proposed technology infusion framework is demonstrated through a printing system case study. [ABSTRACT FROM AUTHOR]

Objective: Low-cost low-field point-of-care MRI systems are used in many different applications. System design has correspondingly different requirements in terms of imaging field-of-view, spatial resolution and magnetic field strength. In this work an iterative framework has been created to design a cylindrical Halbach-based magnet along with integrated gradient and RF coils that most efficiently fulfil a set of user-specified imaging requirements. Methods: For efficient integration, target field methods are used for each of the main hardware components. These have not been used previously in magnet design, and a new mathematical model was derived accordingly. These methods result in a framework which can design an entire low-field MRI system within minutes using standard computing hardware. Results: Two distinct point-of-care systems are designed using the described framework, one for neuroimaging and the other for extremity imaging. Input parameters are taken from literature and the resulting systems are discussed in detail. Discussion: The framework allows the designer to optimize the different hardware components with respect to the desired imaging parameters taking into account the interdependencies between these components and thus give insight into the influence of the design choices. [ABSTRACT FROM AUTHOR]

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To improve the convertibility of reconfigurable manufacturing system (RMS), the concept of delayed reconfigurable manufacturing system (D-RMS) was proposed. RMS and D-RMS are both constructed around part family. However, D-RMS may suffer from ultra-long system problem with unacceptable idle machines using generic RMS part families. Besides, considering the complex basic system structure of D-RMS, machine selection of D-RMS should be addressed, including dedicated machine, flexible machine, and reconfigurable machine. Therefore, a system design method for D-RMS based on part family grouping and machine selection is proposed. Firstly, a part family grouping method is proposed for D-RMS that groups the parts with more former common operations into the same part family. The concept of longest relative position common operation subsequence (LPCS) is proposed. The similarity coefficient among the parts is calculated based on LPCS. The reciprocal value of the operation position of LPCS is adopted as the characteristic value. The average linkage clustering (ALC) algorithm is used to cluster the parts. Secondly, a machine selection method is proposed to complete the system design of D-RMS, including machine selection rules and the dividing point decision model. Finally, a case study is given to implement and verify the proposed system design method for D-RMS. The results show that the proposed system design method is effective, which can group parts with more former common operations into the same part family and select appropriate machine types. [ABSTRACT FROM AUTHOR]

With the continuous progress of Internet technology, so there is a higher demand for English translation. In this context, this paper realizes the design and improvement of the online English translation system by combining the image segmentation algorithm. After the experimental test of the algorithm of this system, if there is a lot of salt-and-pepper noise in the target image in the actual system application process, the method designed in this paper can reflect a better processing effect. Based on the analysis of performance parameters, this method can effectively process Gaussian noise images with high precision. After the completion of the system design, this paper tests the system. From the test and operation results, the software has reached the design objectives and completed the work tasks. The English translation online teaching system can form a safe, stable and high-bandwidth English translation teaching network and can realize the connection of the whole network. Users can share various software and hardware resources, completed the design of a translation platform that can realize rapid English communication, share experience and discuss, to effectively improve the learner's initiative. In this paper, an effective online teaching system is designed by introducing image segmentation algorithm into the field of English translation. [ABSTRACT FROM AUTHOR]

With the continuous improvement and promotion of new technologies in the information age, virtual reality technology has been widely used. Virtual interaction technology has also begun to penetrate into the application market. At present, virtual reality technology has been widely recognized in the field of interior design, which can be used for target display based on virtual exhibition halls, so it is sought after by many users. This form is different from the previous rigid scene reproduction methods such as images and videos. Customers do not have to be in the actual scene, as long as they can run and watch through the network, and get a sense of reality. This paper develops a kind of virtual interior design system based on VR technology and divides it into two categories: One is virtual reality based on software technology and the other is virtual reality based on virtual hardware technology. The technical principle is based on the following four steps: preprocessing, model transformation, image fusion, and registration, which are tested by simulation experiments. The algorithm proposed in this paper can determine whether the Cu is continuously divided in advance, so as to improve coding efficiency, accelerate the effect display of interior design, and improve customer experience. The intended task of the system design is to bring immersive experience to the target users, so that they can get the most real perception at anytime and anywhere. This paper introduces the virtual reality technology into the interior design to carry out the system application analysis and effect display. [ABSTRACT FROM AUTHOR]

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Current Internet of Things (IoT) systems comprise multiple software systems that are deployed to provide users with the required functionalities. System architects create system blueprints and draw specifications for the software artefacts that are needed; subsequently, either custom-made software is developed according to these specifications and/or ready-made COTS/open source software may be identified and customized to realize the overall system goals. All deployed software however may entail vulnerabilities, either due to insecure coding practices or owing to misconfigurations and unexpected interactions. Moreover, software artefacts may implement a much broader set of functionalities than may be strictly necessary for the system at hand, in order to serve a wider range of needs, and failure to appropriately configure the deployed software to include only the required modules results in the further increase of the system attack surface and the associated risk. In this paper, we present a software vulnerability management framework which facilitates (a) the configuration of software to include only the necessary features, (b) the execution of security-related tests and the compilation of platform-wide software vulnerability lists, and (c) the prioritization of vulnerability addressing, considering the impact of each vulnerability, the associated technical debt for its remediation, and the available security budget. The proposed framework can be used as an aid in IoT platform implementation by software architects, developers, and security experts. [ABSTRACT FROM AUTHOR]

In March 2018, the State Council issued a reform plan for institutions. Through the establishment of the Ministry of natural resources, the planning of the national space system was carried out, and the historical division phenomenon within the administrative institutions was solved by using the transformation of fragmentation. Subsequently, relevant functional departments began to design the land spatial planning system and coordinate the mechanism. From the policy guidance, it can be seen that land use spatial planning has risen to the central position in the national management system. From the current situation of planning control, planning control becomes more and more important in the management process. At the same time, the construction of ecological civilization requires us to examine the regulatory mechanism from a new perspective. Therefore, based on machine vision technology, this paper develops a land use spatial planning method system. The sub-pixel edge detection algorithm used in the system design can obtain the point coordinates on the edge of the gauge block with high accuracy. After testing, we can see that in terms of storage space, the octree map used in this paper can save more space than the point cloud map under the same resolution. The data results obtained from the test are also better than the existing system, indicating that the machine vision spatial planning system studied in this paper can better serve the field of land and resources planning. [ABSTRACT FROM AUTHOR]

In order to test the accuracy of the weapon hitting the target, it is very important to locate and measure the spatial coordinates of the falling point target. Aiming at the needs of space coordinate positioning and measurement of targets falling into the sea/ground plane, this paper studies a positioning method of UAV camera combined with target, and uses the principle of homography transformation to calculate the space coordinates of targets. The influence of pixel error on the positioning method is simulated by Monte Carlo method, and the shooting attitude range meeting the measurement requirements is determined by simulation. The results show that the positioning method of UAV camera combined with target has high accuracy, which can meet the needs of landing target positioning and measurement. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to support total productive maintenance implementers by providing a roadmap for autonomous maintenance (AM) preparation phase. Design/methodology/approach: The authors use the axiomatic design (AD) methodology with lean philosophy as a paradigm. Findings: This is an exploratory research to find the most important factors in AM preparation phase. A decoupled AD design ensures an effective usage of training within industry (TWI) and the introduction of standardized work (SW). TWI provides value in importance it assigns to leaders, with its "train the trainers" approach and in preparing a training program. Besides being an effective training method, TWI job instruction (TWI JI) provides needed information infrastructure to front load operators SW and equipment trainings. Research limitations/implications: Although AD, TWI and lean artifacts are generally field proven, the research is limited due to the lack of an industrial application. Practical implications: In many real-life projects, companies do not know where to start and how to proceed, which leads to costly iterations. The proposed roadmap minimizes iterations and increases the chance of project success. Originality/value: The authors apply AD for the first time to AM preparation phase despite it is used in the analysis of lean manufacturing. AD permits to structure holistically the most relevant lean manufacturing solutions to obtain a risk free roadmap. TWI has emerged as a training infrastructure; TWI JI-based operator SW training and the adaptation of JI structure to equipment training are original additions. [ABSTRACT FROM AUTHOR]

Virtual reality is immersive, personalized, and highly interactive. The data is rich and diverse, and privacy involves a wide range. It is crucial to study the privacy protection of virtual reality. This paper introduces the development process of virtual reality privacy protection in detail. From the form of data generation, the virtual reality privacy protection system is proposed, divided into perception, transmission, application, and interaction. According to the shortcomings of current research, the pending problems and possible solutions faced in virtual reality privacy protection are summarized. [ABSTRACT FROM AUTHOR]

During the real-time tracking of marine organisms, due to the huge amount of data, the problem of not being able to upload data in time will occur. Therefore, the application of massive data in the real-time tracking system of marine organisms is studied. According to the overall design requirements of the system, the overall framework of the system is established. Based on the system construction, the hardware part of the design system is composed of multiple serial port MCU, sim808 module and camera module. The host of the marine biological positioning and tracking system is designed using the STC15W4K32S4 multi-serial single-chip microcomputer. The real-time positioning data is uploaded to the network through the host control program design, and the whole system is designed based on GPS module and GPRS module. The experimental results show that: The similarity between the proposed method and the actual trajectory is very high with and without interference. And the data transmission time of the method in this paper is up to 6 min, which shows that the method in this paper can upload data in time, with small error and good performance. [ABSTRACT FROM AUTHOR]

In the current auction-based electricity market, the design of utility-scale renewable energy systems has traditionally been driven by the levelised cost of energy (LCoE). However, the market is gradually moving towards a subsidy-free era, which will expose the power plant owners to the fluctuating prices of electricity. This paper presents a computational approach to account for the influence of time-varying electricity prices on the design of airborne wind energy (AWE) systems. The framework combines an analytical performance model, providing the power curve of the system, with a wind resource characterisation based on ERA5 reanalysis data. The resulting annual energy production (AEP) model is coupled with a parametric cost model based on reference prototype data from Ampyx Power B.V. extended by scaling laws. Ultimately, an energy price model using real-life data from the ENTSO-E platform maintained by the association of EU transmission system operators was used to estimate the revenue profile. This framework was then used to compare the performance of systems based on multiple economic metrics within a chosen design space. The simulation results confirmed the expected behaviour that the electricity produced at lower wind speeds has a higher value than that produced at higher wind speeds. To account for this electricity price dependency on wind speeds in the design process, we propose an economic metric defined as the levelised profit of energy (LPoE). This approach determines the trade-offs between designing a system that minimises cost and designing a system that maximises value. [ABSTRACT FROM AUTHOR]

This article studies a model for risk aversion when designing a flexible capacity expansion plan for a multi-facility system. In this setting, the decision maker can dynamically expand the capacity of each facility given observations of uncertain demand. We model this situation as a multi-stage stochastic programming problem, and we express risk aversion through the Conditional Value-at-Risk (CVaR) and a mean-CVaR objective. We optimize the multi-stage problem over a tractable family of if–then decision rules using a decomposition algorithm. This algorithm decomposes the stochastic program over scenarios and updates the solutions via the subgradients of the function of cumulative future costs. To illustrate the practical effectiveness of this method, we present a numerical study of a decentralized waste-to-energy system in Singapore. The simulation results show that the risk-averse model can improve the tail risk of investment losses by adjusting the weight factors of the mean-CVaR objective. The simulations also demonstrate that the proposed algorithm can converge to high-performance policies within a reasonable time, and that it is also more scalable than existing flexible design approaches. [ABSTRACT FROM AUTHOR]

Digital twin technology is a key technology to realize cyber-physical system. Owing to the problems of low visual monitoring of the blade-rotor test rig and poor equipment monitoring capabilities, this paper proposes a framework based on the digital twin technology. The digital-twin based architecture and major function implementation have been carried out form five dimensions, i.e. Physical layer, Virtual layer, Data layer, Application layer and User layer. Three key technologies utilized to create the system including underlying equipment real-time communication, virtual space building and virtual reality interaction have been demonstrated in this paper. Based on RS-485 and other communication protocols, the data acquisition of the underlying devices have been successfully implemented, and then the real-time data reading has been achieved. Finally, the rationality of the system has been validated by taking the blade-rotor test rig as the application object, which provides a reference for the monitoring and evaluation of equipment involved in manufacturing and experiment. [ABSTRACT FROM AUTHOR]