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Relevant bibliographies by topics / Step duration detection

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Academic literature on the topic 'Step duration detection'

Author: Grafiati

Published: 2 June 2025

Last updated: 19 July 2025

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Journal articles on the topic "Step duration detection"

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Micó-Amigo, M. Encarna, Idsart Kingma, Erik Ainsworth, et al. "A novel accelerometry-based algorithm for the detection of step durations over short episodes of gait in healthy elderly." Journal of NeuroEngineering and Rehabilitation 13, no. 1 (2016): 38. https://doi.org/10.1186/s12984-016-0145-6.

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<strong>Background: </strong>The assessment of short episodes of gait is clinically relevant and easily implemented, especially given limited space and time requirements. BFS (body-fixed-sensors) are small, lightweight and easy to wear sensors, which allow the assessment of gait at relative low cost and with low interference. Thus, the assessment with BFS of short episodes of gait, extracted from dailylife physical activity or measured in a standardised and supervised setting, may add value in the study of gait quality of the elderly. The aim of this study was to evaluate the accuracy of a nov

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Cheng, T.-J., B. Yang, C. Holloway, and N. Tyler. "Effect of environmental factors on how older pedestrians detect an upcoming step." Lighting Research & Technology 50, no. 3 (2016): 405–15. http://dx.doi.org/10.1177/1477153516669968.

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The relationships between environmental features and older people's ability to safely move around a complex pedestrian environment are, as yet, poorly understood. Specifically, the impact of light levels on trip hazard detection during walking has received relatively little attention. This study investigates the effect of illuminance on people's ability to detect steps of different heights in a laboratory-based controlled environment. Sixteen young and 15 older participants walked along a 13.2 m walkway towards an either ascending or descending step at 200 lux or 4 lux light levels. Trial time

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Srihari, Vinod, Maria Ferrara, Emily Kline, et al. "O1.2. REDUCING THE DURATION OF UNTREATED PSYCHOSIS IN A U.S. CATCHMENT: THE MINDMAP CAMPAIGN." Schizophrenia Bulletin 46, Supplement_1 (2020): S1. http://dx.doi.org/10.1093/schbul/sbaa028.001.

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Abstract Background The Specialized Treatment Early in Psychosis (STEP) program has delivered a specialty-team based first-episode service (FES) since 2006 in New Haven. In 2015, STEP launched a 4-year early detection (ED) campaign (Mindmap), adapted from the Scandinavian TIPS approach, to shorten Duration of Untreated Psychosis (DUP) in a 10-town catchment (popn. 400,000). Methods Mindmap’s social-ecological model targeted demand (delays in identifying illness and help-seeking) and supply (delays in referring to and providing FES) side constituents of DUP. Mindmap used mass and social media m

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Ghafi, Hamid Kavousi, Roman Lesjak, Günther Obertaxer, Michael Schönhuber, Alexander Falk, and Holger Arthaber. "Characterization and Early Awareness of Interference in GNSS L1/E1 Band using an Outlier Detection Algorithm." TRANSACTIONS ON ELECTROMAGNETIC SPECTRUM 2, no. 1 (2023): 19–24. https://doi.org/10.5281/zenodo.7700070.

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One of the emerging challenges in the Global Navigation Satellite System (GNSS) is the vulnerability to radio frequency interference (RFI). The first step to deal with this problem is to identify and characterize the interference signals. In this work, we propose a combination of an outlier detection method and a time duration threshold checking to effectively detect and characterize RFIs in the GNSS L1/E1 band. The method is applied to the data recorded from a measurement campaign near the A9 highway in the southern part of Graz, Austria. During 6 hours of recording, three moving interference

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Wang, Xue-gui, Siu-ming Lo, and He-ping Zhang. "Influence of Feature Extraction Duration and Step Size on ANN based Multisensor Fire Detection Performance." Procedia Engineering 52 (2013): 413–21. http://dx.doi.org/10.1016/j.proeng.2013.02.162.

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Wang, Xu, Linghua Zhang, Qin Cheng, and Feng Shu. "MoSeFi: Duration Estimation Robust Human Motion Sensing via Commodity WiFi Device." Wireless Communications and Mobile Computing 2022 (November 4, 2022): 1–19. http://dx.doi.org/10.1155/2022/1690602.

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Accurate motion interval segmentation is the basic and crucial step in the advanced human perception based on WiFi signals. However, previous works have rarely considered motion duration, which is one of the important parameters for complete description of human motion. On this basis, we deeply investigate the properties of the CSI ratio from the perspective of Mobius transformation and construct a novel motion indicator using its complementary real and imaginary parts. The new indicator can attenuate the impact of motion fragmentation under short-window conditions and significantly reduce the

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Dot, Tristan, Flavien Quijoux, Laurent Oudre, et al. "Non-Linear Template-Based Approach for the Study of Locomotion." Sensors 20, no. 7 (2020): 1939. http://dx.doi.org/10.3390/s20071939.

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The automatic detection of gait events (i.e., Initial Contact (IC) and Final Contact (FC)) is crucial for the characterisation of gait from Inertial Measurements Units. In this article, we present a method for detecting steps (i.e., IC and FC) from signals of gait sequences of individuals recorded with a gyrometer. The proposed approach combines the use of a dictionary of templates and a Dynamic Time Warping (DTW) measure of fit to retrieve these templates into input signals. Several strategies for choosing and learning the adequate templates from annotated data are also described. The method

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Urtecho, Louis, Siddharth Krishnamoorthy, Elizabeth Berg, et al. "Automated detection of dust-devil-induced pressure signatures." Journal of the Acoustical Society of America 152, no. 4 (2022): A164. http://dx.doi.org/10.1121/10.0015897.

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Dust devils are common on Mars and in Earth’s arid regions. On Mars, studying the dust devil population is important for understanding dust loading of the Martian climate and has important consequences for robotic and future human exploration. Studying dust devils on Mars is difficult due to insufficient spatio-temporal coverage. Our team is analyzing an infrasound dataset encompassing 7 years of data recorded at the Nevada Nuclear Security Site in the Mojave desert, to identify and characterize terrestrial dust devils as analogues for Martian dust devils. However, the size of this long-durati

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WANG, HONGYE, ZHAO CHEN, and XIUPING JIANG. "Improving the Enrichment and Plating Methods for Rapid Detection of Non-O157 Shiga Toxin–Producing Escherichia coli in Dairy Compost." Journal of Food Protection 79, no. 3 (2016): 413–20. http://dx.doi.org/10.4315/0362-028x.jfp-15-249.

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ABSTRACT A culture method to detect non-O157 Shiga toxin–producing Escherichia coli (STEC) was optimized in this study. The finished dairy compost with 30% moisture content was inoculated with a cocktail of six non-O157 STEC serovars at initial concentrations of 1 to 100 CFU/g. Afterward, non-O157 STEC cells in the inoculated dairy compost were enriched by four methods, followed by plating onto cefixime-tellurite sorbitol MacConkey agar supplemented with 5 mg/liter novobiocin (CTN-SMAC) and modified Rainbow agar containing 5 mg/liter novobiocin, 0.05 mg/liter cefixime trihydrate, and 0.15 mg/l

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Srajal, Kumar Shakya, and Soni Swati. "Plant Disease Detection using Machine Learning Algorithm." International Journal of Scientific Research and Engineering Development 8, no. 1 (2025): 311–16. https://doi.org/10.5281/zenodo.14729072.

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In various applications of the agricultural industry, computer methodologies have been used for automation. Timely farming decisions and disease management are taken using image analysis and machinery of learning techniques in planning and creating a method for the diagnosis of diseases. As human beings are still tracking crop disease, human visual vision is used for diagnosing plant disease. Machine learning and image processing methods are also ideally suited to this end. In this study, the processing of diseased pictures of plant leaf is taken into account. The work focuses on the identific

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Book chapters on the topic "Step duration detection"

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Vinkov, Michael, Igor Fominykh, and Nikolay Alekseev. "Detection of Anomalous Situations in an Unforeseen Increase in the Duration of Inference Step of the Agent in Hard Real Time." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50097-9_18.

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Yuan, Xiang, Qipei Mei, and Xinming Li. "Integrating Real-Time Object Detection into an AR-Driven Task Assistance Prototype: An Approach Towards Reducing Specific Motions in Therbligs Theory." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/979-12-215-0289-3.12.

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Due to challenges in filling vacant positions and the heightened demands posed on existing staff, employers and project managers are progressively considering the recruitment of inexperienced individuals and seeking strategies to swiftly provide them with essential job-specific knowledge. The potential of industrial AR has been widely researched to support workers in overcoming skill-related knowledge and enhancing industrial processes. However, most studies focus on demonstrating technology usability across different processes and overcoming engineering hurdles on a case-by-case basis. There is no direct benefit analysis on how AR assists construction tasks at human motion level, and how to eliminate the ineffective motions and reduce the duration of effective motions. To fill this gap, this paper first establishes an AR-based near real-time object detection system of small tools and components involved in task processes for egocentric perception of workers in the construction industry. Later, the Standard Operating Procedure (SOP) for scaffolding assembly activities is deconstructed from a manual process into Therbligs-based elemental motions. Finally, this research conducted a comparative study of two prototypes across four dimensions of evaluation. As a step forward in this direction, this paper renews the connotations of Therbligs theory under industry 5.0 era, rethinks the AR-assisted construction task processes, and applies appropriate technologies enhancing the adaptability of AR technology for construction workers’ needs

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Yuan, Xiang, Qipei Mei, and Xinming Li. "Integrating Real-Time Object Detection into an AR-Driven Task Assistance Prototype: An Approach Towards Reducing Specific Motions in Therbligs Theory." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.12.

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Due to challenges in filling vacant positions and the heightened demands posed on existing staff, employers and project managers are progressively considering the recruitment of inexperienced individuals and seeking strategies to swiftly provide them with essential job-specific knowledge. The potential of industrial AR has been widely researched to support workers in overcoming skill-related knowledge and enhancing industrial processes. However, most studies focus on demonstrating technology usability across different processes and overcoming engineering hurdles on a case-by-case basis. There is no direct benefit analysis on how AR assists construction tasks at human motion level, and how to eliminate the ineffective motions and reduce the duration of effective motions. To fill this gap, this paper first establishes an AR-based near real-time object detection system of small tools and components involved in task processes for egocentric perception of workers in the construction industry. Later, the Standard Operating Procedure (SOP) for scaffolding assembly activities is deconstructed from a manual process into Therbligs-based elemental motions. Finally, this research conducted a comparative study of two prototypes across four dimensions of evaluation. As a step forward in this direction, this paper renews the connotations of Therbligs theory under industry 5.0 era, rethinks the AR-assisted construction task processes, and applies appropriate technologies enhancing the adaptability of AR technology for construction workers’ needs

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Saini Sheetal and Dua Sumeet. "Temporal Pattern Mining for Multivarite Clinical Decision Support." In Studies in Health Technology and Informatics. IOS Press, 2013. https://doi.org/10.3233/978-1-61499-289-9-1228.

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Multivariate temporal data are collections of contiguous data values that reflect complex temporal changes over a given duration. Technological advances have resulted in significant amounts of such data in high-throughput disciplines, including EEG and iEEG data for effective and efficient healthcare informatics, and decision support. Most data analytics and data-mining algorithms are effective in capturing global trends, but fail to capture localized behavioral changes in large temporal data sets. We present a two-step algorithmic methodology to uncover temporal patterns and exploiting them for an efficient and accurate decision support system. This methodology aids the discovery of previously unknown, nontrivial, and potentially useful temporal patterns for enhanced patient-specific clinical decision support with high degrees of sensitivity and specificity. Classification results on multivariate time series iEEG data for epileptic seizure detection also demonstrate the efficacy and accuracy of the technique to uncover interesting and effective domain class-specific temporal patterns.

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Gamal Masoud, Nagham, Nagwa Mostafa El-Sayed, and Manar Ezzelarab Ramadan. "Role of Nanomedicine in Ocular Parasitic Infections." In Applications of Nanomaterials in Medical Procedures and Treatments. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815136951123040006.

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Ocular parasites cause serious vision-threatening diseases. An early diagnosis and effective treatment are crucial to avoid side effects, such as blindness or eye removal. The first important step in diagnosing ocular parasite infections is to suspect them. Diagnosis is aided by ophthalmic examination, direct parasite identification in clinical samples and/or pathological lesions, immunoassays, and molecular methods. Despite this, ocular parasite infection diagnosis is fraught with difficulties in terms of sensitivity, specificity, and accuracy. The usage of nanoparticles may improve diagnosis by providing precise procedures for parasitic DNA, antigens, and antibodies detection in a variety of body specimens with fast, sensitive, and specific results. Low tolerability, long therapeutic duration, multiple adverse effects, and the emergence of medication resistance are all problems with existing anti-parasitic medications. Nanoparticles represent a promising way for the successful treatment of parasitic diseases by developing innovative drug carriers to target medications to infected sites while limiting high doses and adverse effects. They can also overcome the limitations of antiparasitic medications' low bioavailability, poor cellular permeability, non-specific distribution, and fast elimination from the body. The aim of the present chapter is to throw light on possible nanotechnology applications in ocular parasitic diseases caused by Toxoplasma gondii, Acanthamoeba spp. and Toxocara spp. with a focus on diagnosis, treatment, and vaccination.

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Micalizio Roberto and Torta Gianluca. "Diagnosing Delays in Multi-Agent Plans Execution." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2012. https://doi.org/10.3233/978-1-61499-098-7-594.

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The paper introduces the notion of Temporal Multi-Agent Plan (TMAP) and proposes a methodology, based on Simple Temporal Problems (STP), for detecting and diagnosing action execution delays. Actions are characterized by a finite set of behavioral modes, and each behavioral mode is a continuous interval of possible durations of the action. Nominal modes represent the expected durations, whereas faulty modes represent delays. Solving such diagnostic problems requires to find an assignment of modes to the actions that is consistent with the received observations and maximizes the likelihood of the delayed durations. An implementation of the approach and some preliminary experimental results are also discussed.

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Sakhare, Dhanashree, H. Sharath Chandra, and M. H. Raghunath Reddy. "Oral Habits and its Prevention in Children." In Illustrated Pediatric Dentistry - Part 2. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815080773123010013.

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A habit is a repetitive action that is being done automatically and is resistant to change. In the infantile period, certain repetitive behaviours are common, the majority of them begin and stop spontaneously. If oral habits persist beyond a particular developmental age, it results in unfavourable outcomes for the developing teeth, occlusion and surrounding orofacial tissues. Oral habits are considered one of the main causes of malocclusion, leading to unfavourable growth and development of dentoalveolar, which starts in the early childhood and mixed dentition stage. The severity of malocclusion depends on the frequency, duration, and intensity of the habit. Early detection and interception of the habit should be done by parent/child habit awareness and counselling, elimination, etiology, behaviour modifications and correction of malocclusion.

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Nou-Plana, Ignasi, Marc Freixes, Jesús Vaquerizo-Serrano, et al. "The DeuteroNoise Dataset: An Initial Exploration of an Underwater Vessel Sound Dataset Within the Framework of a JPI-Oceans Project." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2024. http://dx.doi.org/10.3233/faia240446.

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The vast and largely unexplored underwater environment is a rich source of diverse sound events. These sounds, which range from the calls of marine life to the noise generated by human activities, create a complex acoustic environment. Research has been conducted on gathering and categorizing this type of data. However, only a few databases have been recently openly published focusing on anthropogenic sounds. This paper outlines the preliminary steps towards the creation of a comprehensive dataset for the detection of underwater sound events, with an initial emphasis on the sounds of vessels and boats. Within the framework of the JPI Oceans project, DeuteroNoise, a wide spectrum of vessel sounds under varying conditions has been captured and annotated with the necessary metadata for sound event detection tasks. Moreover, the proposed dataset will facilitate the development of more accurate and adaptable vessel sound event detection models and encourage further research in this area. The dataset contains raw audio files and the respective initial analysis based on labeled events, duration of the events, signal-to-noise ratio (SNR) and impact measurements. The retrieved data can be grouped into noisy and non-noisy spots. The noisy locations include the Port of Barcelona (Spain), the Port of Constant,a (Romania), and the Lagoon of Venice (Italy). In contrast, non-noisy data was collected during two measurement campaigns at Pont del Petroli in Badalona (Spain). In addition to the dataset, to illustrate its potential application, a classifier for vessel/boat sound events is proposed. The classifier uses mel spectrograms as input data and is built on a pre-trained model that leverages a residual neural network. This system is capable of classifying vessel/boat related events from background sound environment.

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Kozerke, Sebastian, Redha Boubertakh, and Marc Miquel. "Motion compensation." In The EACVI Textbook of Cardiovascular Magnetic Resonance, edited by Massimo Lombardi, Sven Plein, Steffen Petersen, et al. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198779735.003.0006.

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This chapter introduces the different methods used to synchronize pulse sequences with both cardiac and respiratory motions, to suppress motion-related blurring and image artefacts. A single frame or a series of images (cine imaging) can be acquired at different time points (cardiac phases) throughout the cardiac cycle by detecting the patient’s heart rate, usually by using an electrocardiogram (ECG) or, in case of poor ECG signals, a pulse oximeter signal. Fast single-shot and segmented k-space acquisition techniques are introduced, and for segmented cine imaging, both prospective and retrospective gating techniques are described. To suppress breathing motion artefacts, acquisitions use respiratory motion techniques. For short acquisition durations, breath-holding is the easiest method to stop the patient’s breathing during data collection. However, for long scans, respiratory gating or respiratory navigated techniques can be used. The principles of these techniques and their applications are presented.

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Tiber, Simon. "Upper and Lower Respiratory Tract Infections." In Tutorial Topics in Infection for the Combined Infection Training Programme. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198801740.003.0040.

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Pharyngitis is common with incidence peaking from autumn to spring. Respiratory viruses are most commonly implicated, and are generally self-limiting conditions not requiring diagnostic workup or treatment. Bacterial pharyngitis is less common, is spread by droplets or direct transmission, and Streptococcus pyogenes (Group A strep, or GAS) is the most frequent cause. Haemophilus influenzae, Mycoplasma pneumoniae, and Neisseria gonorrhoeae are less frequent causes. Rapid antigen detection tests make the point-of-care assessment of GAS pharyngitis possible, although a negative test does not exclude infection. No method can distinguish oropharyngeal colonization from actual infection, but culture can obtain antibiotic susceptibility testing. Suspicion of infection with Neisseria gonorrhoeae, Bordetella pertussis, Haemophilus influenzae, Mycoplasma pneumoniae, Chlamydophila pneumoniae, or Corynebacterium diptheriae should be communicated to the laboratory so that the appropriate culture media is utilized. The Centor criteria provide a clinical predictive score that can give the likelihood a sore throat is due to a bacterial infection with the following: the presence of tonsillar exudate, tender anterior cervical adenopathy, fever over 38°C, and absence of cough. If three or four of these criteria are met, the positive predictive value is 40% to 60%. The absence of three or four of the Centor criteria has a relatively high negative predictive value of 80%, and may be use to evaluate whether antibiotics can be withheld or deferred. Oral penicillin or macrolide are used to treat streptococcal pharyngitis. Treatment may reduce severity, duration, transmission, and risk of post-infectious sequelae like rheumatic heart disease and post-streptococcal glomerulonephritis. Other complications include scarlet fever, streptococcal toxic shock syndrome, and quinsy. Otitis media, is frequent in the young children, possibly due to a short and horizontal Eustachian tube. Purulent material buils up leading to a bulging, red tympanic membrane which may rupture and discharge. Intense local pain and fevers may occur. Streptococcus pneumoniae, Moraxella catarrhalis, and Haemophilus influenzae are frequently implicated. Frequently there are no sequelae, although complications include hearing impairment, and less common are mastoiditis, bacteraemia, and meningitis. Diagnosis is clinical based on presentation and otoscopic examination. Microbiological diagnosis is possible through culture of exuate on swab or following tympanocentesis.

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Conference papers on the topic "Step duration detection"

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Sun, Zhen, Elsa Caetano, Omar Saadi, and Catarina Miranda Oliveira. "Detection of trainloads of suspension bridges with bridge responses: a comparative study using displacement and stress." In IABSE Symposium, Istanbul 2023: Long Span Bridges. International Association for Bridge and Structural Engineering (IABSE), 2023. http://dx.doi.org/10.2749/istanbul.2023.0175.

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<p>Trainloads play an essential role in the fatigue life of railway bridges as they cause important repetitive stress cycles at critical locations. Therefore, estimating such loads is relevant for preventive maintenance plans. This paper investigates an approach to detect trainloads using responses of the bridge, such as displacement and stress. Firstly, the temperature-response correlation is investigated to assess the influence of possible effects on the detection. Secondly, two response characteristics are proposed to detect trainloads: amplitude and duration. Statistical analysis of

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Cipollone, R. "Low-thrust maneuver anomaly detection of a cooperative asset using publicly available orbital data." In Aeronautics and Astronautics. Materials Research Forum LLC, 2023. http://dx.doi.org/10.21741/9781644902813-136.

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Abstract. This work presents a novel method to estimate perturbations with respect to nominal maneuver planning by exploiting Two-Line-Element (TLE) data as initial step, then moving on to Global Positioning System (GPS) processed data. The case study is a low-thrust engine validation mission in Low Earth Orbit. The first algorithm exploits a couple of TLEs as boundary conditions to set up a least-squares problem and find the tangential thrust magnitude and firing duration to best fit the bounding orbital states, making use of Taylor differential algebra and Picard iterations. The second one m

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Ambrus, A., J. Mugisha, A. Shchipanov, U. J. F. Aarsnes, and A. M. Øverland. "Automated Rate Control to Prevent Induced Fracturing and Fracture Opening Monitored with Step Rate Tests." In SPE Europe Energy Conference and Exhibition. SPE, 2024. http://dx.doi.org/10.2118/220016-ms.

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Abstract Designed and occasionally induced fracturing occur during injection and production operations in petroleum, geothermal energy, and geological CO2 storage. Although the goals and perspectives vary across industries, fracture monitoring and control remains crucial. Induced fracturing enhances petroleum and geothermal energy production, whereas its prevention is a key challenge in CO2 storage. Therefore, incorporating fracture management into automated injection control would be beneficial as enabled by the recent wide deployment of permanent well surveillance technologies. This paper pr

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Galindo, Raul Lema, Elise Weimholt, and James P. Schmiedeler. "Actuated Dual-Slip Model of Planar Slope Walking." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97601.

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Abstract The planar dual spring-loaded inverted pendulum (dual-SLIP) model is a well-established passive template of human walking on flat ground. This paper applies an actuated extension of the model to walking on inclines and declines to evaluate how well it captures the behavior observed in human slope walking. The motivation is to apply the template to improve control of humanoid robot walking and/or intent detection in exoskeleton-assisted walking. Gaits of the actuated planar dual-SLIP model are found via the solution of a constrained nonlinear optimization problem in ten parameters. The

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William, Darren Eduardo, Mitra Andini Sigilipoe, and Widya Christine Manus. "Comparison of Mini-Mental State Examination and Clock Drawing Test with Orientation-Memory-Concentration Test in the Elderly with Cognitive Function Impairment in Jetis Sub-District, Yogyakarta." In The 7th International Conference on Public Health 2020. Masters Program in Public Health, Universitas Sebelas Maret, 2020. http://dx.doi.org/10.26911/the7thicph.05.17.

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ABSTRACT Background: Dementia is a collective term for several diseases that affect memory, other cognitive abilities, and behavior. These diseases can seriously interfere with people’s ability of daily living. This is not a normal phenomenon of aging. With the increasing prevalence of dementia in the elderly, the importance of dementia as a comorbidity of hypertension is increasing. However, several questions regarding the link between hypertension and dementia remain unresolved. This study aimed to determine Orientation-Memory-Concentration-Test (OMCT) can be used to assess cognitive functio

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Raduenz, Henrique, Fábio José Souza, Pedro P. C. Bastos, Desyel Ferronatto, Victor J. De Negri, and João Marcos Castro Soares. "Evaluation of an On-Line Fault Detection Method for Proportional Hydraulic Valves." In 9th FPNI Ph.D. Symposium on Fluid Power. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/fpni2016-1569.

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This paper presents the analysis of an on-line fault detection method for proportional directional hydraulic valves applied on speed governors of hydroelectric power plants. This application area is very sensitive for unexpected maintenance or long duration stops since most of power plants are interconnected on an electrical power grid. A plant stop must be programmed previously and approved by a regulatory agency. Consequently, the implementation of a fault detection and monitoring system can reduce maintenance and operational costs as well as safety risks of equipment and operators. The deve

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Daneshy, Ali. "Use of FDI Data for Comprehensive Evaluation of Horizontal Well Frac Treatments." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/206140-ms.

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Abstract Effective fracturing of horizontal wells is the key to successfully producing unconventional reservoirs. Correct evaluation of existing created fractures is essential for identification of key treatment variables in the target reservoir and continuous process improvement of the total process. Measurement and analysis of Frac-driven Interactions (FDI) has become a popular technique for rapid and cost-effective evaluation of existing and new fractures created in horizontal wells for production of unconventional reservoirs. Specific parameters used for their evaluation include detection

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Alharbi, Sadeen. "Ambiguity Detection in Requirements Classification Task using Fine-Tuned Transformation Technique." In 3rd International Conference on Machine Learning Techniques and Data Science (MLDS 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.122105.

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The software requirement specification (SRS) document is essential in software development. This document influences all subsequent steps in software development. Nevertheless, requirements problems, such as insufficient or ambiguous specifications, can cause misunderstandings during the requirement analysis stage. This influences testing activities and increases the project’s duration and cost overrun risk. This paper represents an intuitive approach to detecting ambiguity in software requirements. The classifiershould learn ambiguous features and characteristics extracted from the text on a

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Waszkowski, Robert, Tadeusz Nowicki, and Agata Chodowska Wasilewska. "Low-code development platform for modeling and implementation of business processes to support outbreak investigations." In AHFE 2023 Hawaii Edition. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004326.

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This article describes the functional scope of a low-code development platform for modeling and implementation of business processes to support outbreak investigations.LCDP (Low-Code Development Platforms) are development tools that allow you to create applications using a minimum amount of traditional programming code. They help speed up the software development process by reducing the need to write manual code and enabling the development of applications using visual interfaces, ready-made components, and configuration rules. They can also support business process management through various

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Pszeida, Martin, Lucas Paletta, Silvia Russegger, et al. "Mild Dementia Decision Support from AI-based Digital Biomarkers using Mobile Playful Exercises with High Adherence." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003970.

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Early detection of cognitive decline and monitoring of cognitive functioning in mild dementia are fundamental for timely adaptation of lifestyle and intervention strategies. The development of digital dementia biomarkers through playful exercises with high adherence rate was a key objective of the national project multimodAAL (no. FFG 875345). The results of a study on computer-based cognitive and physical training (CCPT) in persons diagnosed with mild Alzheimer’s disease (PwAD) are presented.Method: Tablet-PC-based intervention was applied within 6 months in Austria, engaging PwADs living at

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