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Integrated vehicle health management has been developed for several years in different industries, to be able to provide the required inputs to determine the optimal maintenance operations depending on the actual health status of the system. The purpose of this paper is to demonstrate the potential of a physics-based model (PbM) for prognostics with a real case study, based on the detection of incipient faults and estimate the remaining useful life of a planetary transmission of an aircraft system.

Most of the research in the area of health assessment algorithms has been focused on data-driven approaches that are not based on the knowledge of the physics of the system, while PbM approaches rely on the understanding of the system and the degradation mechanisms. A physics-based modelling approach to represent metal-metal contact and fatigue in the gears of the planetary transmission of an aircraft system is applied.

Both the failure mode caused by metal-metal contact as caused by fatigue in the gears is described. Furthermore, the real-time application that retrieves the results from the simulations to assess the health of the system is described. Finally the decision making that can be executed during flight in the aircraft is incorporated.

The paper proposes an innovative prognostics health management system that assesses two important failure modes of the planetary transmission that regulates the speed of the generators of an aircraft. The results from the models have been integrated in an application that emulates a real system in the aircraft and computes the remaining useful life in real time.

Previous IMP research has shown that innovation benefits tend to gravitate across organisational, company and legal borders. However, OECD and EU policy assume that innovation investments will create benefits in close spatial relation to where these were made. The overall purpose of this paper is to consider how opportunities and obstacles of innovation appear from the perspective of: a national policy actor, its regional mediators and a policy supported and research-based firm engaged in innovation. A specific interest is directed to what interactive aspects that are considered by these actors; in the using, producing and developing settings.

Influenced by the research question and theoretical point of departure the authors investigate what type of interfaces our focal actors recognise in the using, producing and developing settings. A total of 41 face-to-face and phone interviews focusing on each actor’s approach were conducted; 23 interviews in order to investigate the “policy side” of innovation attempts, while 18 interviews have been performed in order to understand a single business actor’s innovation approach.

The study shows that both the national policy agency and the regional policy mediators primarily operate within a developing setting, and furthermore, applies a rather peculiar interpretation of proximity. As long as the developing setting of the innovation journey is in focus, with the task to transfer academic knowledge advances to commercial actors, the proximity aspect is rather easy to fulfil. However, as soon as the producing and using settings of the innovation is taken into consideration, the innovation, if it survives, will gravitate to a producing setting where it can contribute to investments in place.

The study investigates the opportunities and obstacles of innovation; the spatial aspects included, and how these are considered by: a national policy agency, a regional mediator and a policy-supported innovating firm, in order to juxtapose the policy doctrine with the experience of the business actors such policy wishes to support.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

Monitoring of a process leading to the detection of faults and determination of the root causes are essential for the production of consistent good quality end products with improved yield. The history of process monitoring fault detection (PMFD) strategies can be traced back to 1930s. Thereafter various tools, techniques and approaches were developed along with their application in diversified fields. The purpose of this paper is to make a review to categorize, describe and compare the various PMFD strategies.

Taxonomy was developed to categorize PMFD strategies. The basis for the categorization was the type of techniques being employed for devising the PMFD strategies. Further, PMFD strategies were discussed in detail along with emphasis on the areas of applications. Comparative evaluations of the PMFD strategies based on some commonly identified issues were also carried out. A general framework common to all the PMFD has been presented. And lastly a discussion into future scope of research was carried out.

The techniques employed for PMFD are primarily of three types, namely data driven techniques such as statistical model based and artificial intelligent based techniques, priori knowledge based techniques, and hybrid models, with a huge dominance of the first type. The factors that should be considered in developing a PMFD strategy are ease in development, diagnostic ability, fault detection speed, robustness to noise, generalization capability, and handling of nonlinearity. The review reveals that there is no single strategy that can address all aspects related to process monitoring and fault detection efficiently and there is a need to mesh the different techniques from various PMFD strategies to devise a more efficient PMFD strategy.

The review documents the existing strategies for PMFD with an emphasis on finding out the nature of the strategies, data requirements, model building steps, applicability and scope for amalgamation. The review helps future researchers and practitioners to choose appropriate techniques for PMFD studies for a given situation. Further, future researchers will get a comprehensive but precise report on PMFD strategies available in the literature to date.

The review starts with identifying key indicators of PMFD for review and taxonomy was proposed. An analysis was conducted to identify the pattern of published articles on PMFD followed by evolution of PMFD strategies. Finally, a general framework is given for PMFD strategies for future researchers and practitioners.

Organizations involved in facility management (FM) can use building information modeling (BIM) as a knowledge repository to document evolving facility information and to support decisions made by the facility managers during the operational life of a facility. Despite ongoing advances in FM technologies, FM practices in most facilities are still labor intensive, time consuming and often rely on unreliable and outdated information. To address these shortcomings, the purpose of this study is to propose an automated approach that demonstrates the potential of using BIM to develop algorithms that automate decision-making for FM applications.

A BIM plug-in tool is developed that uses a fault detection and diagnostics (FDD) algorithm to automate the process of detecting malfunctioning heating, ventilation, and air conditioning (HVAC) equipment. The algorithm connects to a complaint ticket database and automates BIM to determine potentially damaged HVAC system components and develops a plan of action for the facility inspectors accordingly. The approach has been implemented as a case study in an operating facility to improve the process of HVAC system diagnosis and repair.

By implementing the proposed application in a case study, the authors found that automated BIM approaches such as the one developed in this study, can be highly beneficial in FM practices by increasing productivity and lowering costs associated with decision-making.

This study introduces an innovative approach that leverages BIM for automated fault detection in operational buildings. FM personnel in charge of HVAC inspection and repair can highly benefit from the proposed approach, as it eliminates the time required to locate HVAC equipment at fault manually.

Intercultural competence has been found to be increasingly important. The purpose of this paper is to understand how intercultural competence impacts service providers’ ability to recognition faces of both black and white consumers.

Two experiments were administered to understand how intercultural competence impacts recognition of black and white consumer faces.

The authors find that the more intercultural competence that respondents report with blacks, the better they are at distinguishing between black regular customers and black new shoppers in an experiment. The authors find no impact of intercultural competence on the ability of respondents to differentiate between white consumers. These findings hold for respondents in the USA and South Africa.

One limitation of this research is that the studies were conducted in a controlled lab setting. Thus, one could imagine additional noise from a true consumer setting might increase the effects of these results. Another limitation is the focus on only black and white consumer faces. In this paper, the authors focused on these two races, specifically to keep the factorial design as simplified as possible.

The implications of this research are important given that the ability of employees’ recognizing customer faces can affect customers’ day-to-day interactions in the marketplace.

The purpose of this paper is to present the topic of control computers diagnostics. They are part of an unmanned aerial vehicle (UAV) control system implemented in a modified version of MP-2 Czajka aircraft.

The algorithms were designed as a basic version of the diagnostic system. The system is open and will be developed.

First results show that the diagnostic system works properly. The system is easy for implementation and burdens the control computers only insignificantly.

The system presented can detect only computers out of work. In its present version, it cannot detect such errors as improper calculations of control signals. After first in-flight testing, the system will be further developed.

The diagnostic system is implemented in an UAV technology demonstrator.

The designed system is the part of an UAV control system, designed for ground observation. Such technology demonstrator and flying laboratory enable different type of research in the area of aviation.

Molecularly imprinted polymers (MIPs) have aroused focus in medicinal chemistry in recent decades, especially for biomedical applications. Considering the exceptional abilities to immobilize any guest of medical interest (antibodies, enzymes, etc.), MIPs is attractive to substantial research efforts in complementing the quest of biomimetic recognition systems. This study aims to review the key-concepts of molecular imprinting, particularly emphasizes on the conformational adaptability of MIPs beyond the usual description of molecular recognition. The optimal morphological integrity was also outlined in this review to acknowledge the successful sensing activities by MIPs.

This review highlighted the fundamental mechanisms and underlying challenges of MIPs from the preparation stage to sensor applications. The progress of electrochemical and optical sensing using molecularly imprinted assays has also been furnished, with the evolvement of molecular imprinting as a research hotspot.

The lack of standard synthesis protocol has brought about an intriguing open question in the selection of building blocks that are biocompatible to the imprint species of medical interest. Thus, in this paper, the shortcomings associated with the applications of MIPs in electrochemical and optical sensing were addressed using the existing literature besides pointing out possible solutions. Future perspectives in the vast development of MIPs also been postulated in this paper.

The present review intends to furnish the underlying mechanisms of MIPs in biomedical diagnostics, with the aim in electrochemical and optical sensing while hypothesizing on future possibilities.

The purpose of this study was to design a paper strip-based non-invasive urine analysis system for the qualitative detection of biomarker aquaporin-1 (AQP1) in renal cancer (RC). RC accounts for 3% of all cancers and 85% of all kidney tumors and mainly originates from the kidney cortex. In recent times, higher urine concentration of AQP1 in patients with RC was confirmed as a specific biomarker of the disease. Hence, the noninvasive, user-friendly and self-diagnostic method is required for the detection of aquaporin biomarkers in RC.

The present research work was focused on the development and characterization of a dye conjugated cyclodextrin-based miniaturized system for impregnation on Whatman filter paper to identify RC using AQP1 biomarker present in urine samples.

It was observed that the test strip dipped into the urine sample, and the yellow color intensity increased with a decrease in AQP1 concentration due to the transformation of the dye system of free basic form into bound acidic form. The Hue-Saturation-Value profiling was used to observe the effect of color change using a smartphone application. The paper strip-based urine analysis system is highly sensitive for the detection of AQP1 in the range of 10 to 1,000 ng.

The successful validation indicated that this biosensor is likely to contribute to the development of point-of-care, novel, personalized diagnostics and ensure prolonged survival of RC patients in the near future.

The purpose of this paper is analysis of the sensorless control system of induction machine with broken rotor for diagnostic purposes. Increasing popularity of sensorless controlled variable speed drives requires research in area of reliability, range of stable operation, fault symptoms and application of diagnosis methods.

T transformation used for conversion of instantaneous rotor currents electrical circuit representation to space vector components is investigated to apply with closed‐loop modeling algorithm. Evaluation of the algorithm is based on analysis of asymmetry influence to the orthogonal and zero components of space vector representation. Multiscalar model of the machine and selected structures of state observers are used for sensorless control system synthesis. Proposed method of frequency characteristics calculation is used for state observers analysis in open‐loop operation.

New algorithm of applying the T transformation allows for closed‐loop and sensorless control system simulation with asymmetric machine due to broken rotor. Compensating effect of the closed‐loop control system with speed measurements and diagnosis information in control system variables are identified. Proposed frequency analysis of state observers is presented and applied. Variables with amplified characteristic frequency components related to rotor asymmetry are compared for selected structures of state observers and with closed‐loop and open‐loop operation. Method of improving the sensorless system stability is proposed.

In closed‐loop and sensorless control system rotor fault can be diagnosed by using PI output controllers variables. Compensating effect of mechanical variables sets limitation to specified diagnosis methods. Rotor asymmetry affects sensorless control system stability depending on estimator structure.

This paper concentrates upon sensorless control system operation with machine asymmetry and indicates rotor fault symptoms.