To better control the growing process of horticulture plants greenhouse growers need an automated way to efficiently and effectively find where diseases are spreading.The HiPerGreen project has done research in using an autonomous quadcopter for this scouting. In order for the quadcopter to be able to scout autonomously accurate location data is needed. Several different methods of obtaining location data have been investigated in prior research. In this research a relative sensor based on optical flow is looked into as a method of stabilizing an absolute measurement based on trilateration. For the optical flow sensor a novel block matching algorithm was developed. Simulated testing showed that Kalman Filter based sensor fusion of both measurements worked to reduce the standard deviation of the absolute measurement from 30 cm to less than 1 cm, while drift due to dead-reckoning was reduced to a maximum of 11 cm from over 36 cm.
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This paper extends the 'go-with-the-flow' method to explore enclosed environments, like oil reservoirs, pipe lines that transport liquids, and industrial tanks for processing chemicals, where sensing nodes cannot establish communication with the external world. Nonetheless, large quantities of highly miniaturized, thus power-constrained sensor nodes are injected into these environment and flow through them along with the medium, monitoring their environment but also reconstructing their time-varying position from mutual communication, but without any communication to external base stations or beacons. The relative trajectories of nodes yield essential insights of the fluid flow in the otherwise inaccessible environment. We present a functional implementation of a ranging protocol accommodating size and energy constraints. Our simulation chain models node movement from different types of flow dynamics. It comprehensively assesses not only the performance of the communication and ranging protocols, but also of the reconstruction algorithm. Our assessments cover a wide range of different environments and flow profiles, including highly dynamic ones.
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This paper presents the design of the offshore energy simulation CEL as a flow network, and its integration in the MSP Challenge 2050 simulation game platform. This platform is designed to aid learning about the key characteristics and complexity of marine or maritime spatial planning (MSP). The addition of CEL to this platform greatly AIDS MSP authorities in learning about and planning for offshore energy production, a highly topical and big development in human activities at sea. Rather than a standard flow network, CEL incorporates three additions to accommodate for the specificities of energy grids: an additional node for each team's expected energy, a split of each node representing an object into input and output parts to include the node's capacity, and bidirectional edges for all cables to enable more complex energy grid designs. Implemented with Dinic's algorithm it takes less than 30ms for the simulation to run for the average amount of grids included in an MSP Challenge 2050 game session. In this manner CEL enables MSP authorities and their energy stakeholders to use MSP Challenge 2050 for designing and testing more comprehensive offshore energy grids.
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AIM: To systematically review the available literature on the diagnostic accuracy of questionnaires and measurement instruments for headaches associated with musculoskeletal symptoms.DESIGN: Articles were eligible for inclusion when the diagnostic accuracy (sensitivity/specificity) was established for measurement instruments for headaches associated with musculoskeletal symptoms in an adult population. The databases searched were PubMed (1966-2018), Cochrane (1898-2018) and Cinahl (1988-2018). Methodological quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2) and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist for criterion validity. When possible, a meta-analysis was performed. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) recommendations were applied to establish the level of evidence per measurement instrument.RESULTS: From 3450 articles identified, 31 articles were included in this review. Eleven measurement instruments for migraine were identified, of which the ID-Migraine is recommended with a moderate level of evidence and a pooled sensitivity of 0.87 (95% CI: 0.85-0.89) and specificity of 0.75 (95% CI: 0.72-0.78). Six measurement instruments examined both migraine and tension-type headache and only the Headache Screening Questionnaire - Dutch version has a moderate level of evidence with a sensitivity of 0.69 (95% CI 0.55-0.80) and specificity of 0.90 (95% CI 0.77-0.96) for migraine, and a sensitivity of 0.36 (95% CI 0.21-0.54) and specificity of 0.86 (95% CI 0.74-0.92) for tension-type headache. For cervicogenic headache, only the cervical flexion rotation test was identified and had a very low level of evidence with a pooled sensitivity of 0.83 (95% CI 0.72-0.94) and specificity of 0.82 (95% CI 0.73-0.91).DISCUSSION: The current review is the first to establish an overview of the diagnostic accuracy of measurement instruments for headaches associated with musculoskeletal factors. However, as most measurement instruments were validated in one study, pooling was not always possible. Risk of bias was a serious problem for most studies, decreasing the level of evidence. More research is needed to enhance the level of evidence for existing measurement instruments for multiple headaches.
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During crime scene investigations, numerous traces are secured and may be used as evidence for the evaluation of source and/or activity level propositions. The rapid chemical analysis of a biological trace enables the identification of body fluids and can provide significant donor profiling information, including age, sex, drug abuse, and lifestyle. Such information can be used to provide new leads, exclude from, or restrict the list of possible suspects during the investigative phase. This paper reviews the state-of-the-art labelling techniques to identify the most suitable visual enhancer to be implemented in a lateral flow immunoassay setup for the purpose of trace identification and/or donor profiling. Upon comparison, and with reference to the strengths and limitations of each label, the simplistic one-step analysis of noncompetitive lateral flow immunoassay (LFA) together with the implementation of carbon nanoparticles (CNPs) as visual enhancers is proposed for a sensitive, accurate, and reproducible in situ trace analysis. This approach is versatile and stable over different environmental conditions and external stimuli. The findings of the present comparative analysis may have important implications for future forensic practice. The selection of an appropriate enhancer is crucial for a well-designed LFA that can be implemented at the crime scene for a time- and cost-efficient investigation.
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Background: To experience external objects in such a way that they are perceived as an integral part of one's own body is called embodiment. Wearable technology is a category of objects, which, due to its intrinsic properties (eg, close to the body, inviting frequent interaction, and access to personal information), is likely to be embodied. This phenomenon, which is referred to in this paper as wearable technology embodiment, has led to extensive conceptual considerations in various research fields. These considerations and further possibilities with regard to quantifying wearable technology embodiment are of particular value to the mobile health (mHealth) field. For example, the ability to predict the effectiveness of mHealth interventions and knowing the extent to which people embody the technology might be crucial for improving mHealth adherence. To facilitate examining wearable technology embodiment, we developed a measurement scale for this construct. Objective: This study aimed to conceptualize wearable technology embodiment, create an instrument to measure it, and test the predictive validity of the scale using well-known constructs related to technology adoption. The introduced instrument has 3 dimensions and includes 9 measurement items. The items are distributed evenly between the 3 dimensions, which include body extension, cognitive extension, and self-extension.Methods: Data were collected through a vignette-based survey (n=182). Each respondent was given 3 different vignettes, describing a hypothetical situation using a different type of wearable technology (a smart phone, a smart wristband, or a smart watch) with the purpose of tracking daily activities. Scale dimensions and item reliability were tested for their validity and Goodness of Fit Index (GFI). Results: Convergent validity of the 3 dimensions and their reliability were established as confirmatory factor analysis factor loadings45 (>0.70), average variance extracted values40 (>0.50), and minimum item to total correlations50 (>0.40) exceeded established threshold values. The reliability of the dimensions was also confirmed as Cronbach alpha and composite reliability exceeded 0.70. GFI testing confirmed that the 3 dimensions function as intercorrelated first-order factors. Predictive validity testing showed that these dimensions significantly add to multiple constructs associated with predicting the adoption of new technologies (ie, trust, perceived usefulness, involvement, attitude, and continuous intention). Conclusions: The wearable technology embodiment measurement instrument has shown promise as a tool to measure the extension of an individual's body, cognition, and self, as well as predict certain aspects of technology adoption. This 3-dimensional instrument can be applied to mixed method research and used by wearable technology developers to improve future versions through such things as fit, improved accuracy of biofeedback data, and customizable features or fashion to connect to the users' personal identity. Further research is recommended to apply this measurement instrument to multiple scenarios and technologies, and more diverse user groups.
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Objective: To systematically review and critically appraise the literature on measurement properties of cardiopulmonary exercise test protocols for measuring aerobic capacity, VO2max, in persons after stroke. Data sources: PubMed, Embase and Cinahl were searched from inception up to 15 June 2016. A total of 9 studies were identified reporting on 9 different cardiopulmonary exercise test protocols. Study selection: VO2max measured with cardiopulmonary exercise test and open spirometry was the construct of interest. The target population was adult persons after stroke. We included all studies that evaluated reliability, measurement error, criterion validity, content validity, hypothesis testing and/ or responsiveness of cardiopulmonary exercise test protocols. Data extraction: Two researchers independently screened the literature, assessed methodological quality using the COnsensus-based Standards for the selection of health Measurement INstruments checklist and extracted data on measurement properties of cardiopulmonary exercise test protocols. Data synthesis: Most studies reported on only one measurement property. Best-evidence synthesis was derived taking into account the methodological quality of the studies, the results and the consistency of the results. Conclusion: No judgement could be made on which protocol is “best” for measuring VO2max in persons after stroke due to lack of high-quality studies on the measurement properties of the cardiopulmonary exercise test.
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Background The Six-Minute Walk Test (6MWT) is increasingly being used as a functional outcome measure for chronic pediatric conditions. Knowledge about its measurement properties is needed to determine whether it is an appropriate test to use. Purpose The purpose of this study was to systematically review all published clinimetric studies on the 6MWT in chronic pediatric conditions. Data Sources The databases MEDLINE, EMBASE, CINAHL, PEDro, and SPORTDiscus were searched up to February 2012. Study Selection Studies designed to evaluate measurement properties of the 6MWT in a chronic pediatric condition were included in the systematic review. Data Extraction The methodological quality of the included studies and the measurement properties of the 6MWT were examined. Data Synthesis A best evidence synthesis was performed on 15 studies, including 9 different chronic pediatric conditions. Limited evidence to strong evidence was found for reliability in various chronic conditions. Strong evidence was found for positive criterion validity of the 6MWT with peak oxygen uptake in some populations, but negative criterion validity was found in other populations. Construct validity remained unclear in most patient groups because of methodological flaws. Little evidence was available for responsiveness and measurement error. Studies showed large variability in test procedures despite existing guidelines for the performance of the 6MWT. Limitations Unavailability of a specific checklist to evaluate the methodological quality of clinimetric studies on performance measures was a limitation of the study. Conclusions Evidence for measurement properties of the 6MWT varies largely among chronic pediatric conditions. Further research is needed in all patient groups to explore the ability of the 6MWT to measure significant and clinically important changes. Until then, changes measured with the 6MWT should be interpreted with caution. Future studies or consensus regarding modified test procedures in the pediatric population is recommended.
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This study presents an automated method for detecting and measuring the apex head thickness of tomato plants, a critical phenotypic trait associated with plant health, fruit development, and yield forecasting. Due to the apex's sensitivity to physical contact, non-invasive monitoring is essential. This paper addresses the demand for automated, contactless systems among Dutch growers. Our approach integrates deep learning models (YOLO and Faster RCNN) with RGB-D camera imaging to enable accurate, scalable, and non-invasive measurement in greenhouse environments. A dataset of 600 RGB-D images captured in a controlled greenhouse, was fully preprocessed, annotated, and augmented for optimal training. Experimental results show that YOLOv8n achieved superior performance with a precision of 91.2 %, recall of 86.7 %, and an Intersection over Union (IoU) score of 89.4 %. Other models, such as YOLOv9t, YOLOv10n, YOLOv11n, and Faster RCNN, demonstrated lower precision scores of 83.6 %, 74.6 %, 75.4 %, and 78 %, respectively. Their IoU scores were also lower, indicating less reliable detection. This research establishes a robust, real-time method for precision agriculture through automated apex head thickness measurement.
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Particle image velocimetry has been widely used in various sectors from the automotive to aviation, research, and development, energy, medical, turbines, reactors, electronics, education, refrigeration for flow characterization and investigation. In this study, articles examined in open literature containing the particle image velocimetry techniques are reviewed in terms of components, lasers, cameras, lenses, tracers, computers, synchronizers, and seeders. The results of the evaluation are categorized and explained within the tables and figures. It is anticipated that this paper will be a starting point for researchers willing to study in this area and industrial companies willing to include PIV experimenting in their portfolios. In addition, the study shows in detail the advantages and disadvantages of past and current technologies, which technologies in existing PIV laboratories can be renewed, and which components are used in the PIV laboratories to be installed.
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