Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
621
datasets available to search
ShareScore release 0.9.0
Dataset results
621 results for “methodologies”
A Comparison of Survey Methodologies to Elicit Sensitive Information From Adolescents in Urban India
ClinicalTrials.gov study NCT00232986. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Testing Design Thinking Methodology to Engage Hispanic and Latino Families of Autistic Children in Research.
ClinicalTrials.gov study NCT06111092. IPD Sharing: YES. Countries: 0. Publications: 0.
Retroviral Insertion Site Methodology Study
ClinicalTrials.gov study NCT03311074. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Energy Expenditure Methodology Infant
ClinicalTrials.gov study NCT01905085. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Design and Evaluation of a Novel Methodology for SABR for Lung Cancer
ClinicalTrials.gov study NCT04928755. IPD Sharing: NO. Countries: 0. Publications: 0.
Study of Body Composition Methodology in Young Children (InfantPod)
ClinicalTrials.gov study NCT00730587. IPD Sharing: Not stated. Countries: 1. Publications: 0.
ISDH-seq: a robust methodology for profiling and characterization of open chromatin
GEO Series GSE235900. Oryza sativa. 11 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Other.
METHODOLOGY OF HISTORICAL AND ECONOMIC RESEARCH: A RETROSPECTIVE VIEW
Open the record for dataset details and reuse information.
Assessing the significance of chromosomal aberrations in cancer: Methodology and application to glioma
GEO Series GSE9635. Homo sapiens. 374 samples. Type: Genome variation profiling by SNP array; SNP genotyping by SNP array.
The ABRF Next-Generation Sequencing Study (ABRF-NGS): Multi-platform and cross-methodological reproducibility of transcriptome profiling by RNA-seq.
GEO Series GSE46876. synthetic construct; Homo sapiens. 105 samples. Type: Expression profiling by high throughput sequencing.
Prognostics Of Power Mosfets Under Thermal Stress Accelerated Aging Using Data-Driven And Model-Based Methodologies
An approach for predicting remaining useful life of power MOSFETs (metal oxide field effect transistor) devices has been developed. Power MOSFETs are semiconductor switching devices that are instrumental in electronics equipment such as those used in operation and control of modern aircraft and spacecraft. The MOSFETs examined here were aged under thermal overstress in a controlled experiment and continuous performance degradation data were collected from the accelerated aging experiment. Die-attach degradation was determined to be the primary failure mode. The collected run-to-failure data were analyzed and it was revealed that ON-state resistance increased as die-attach degraded under high thermal stresses. Results from finite element simulation analysis support the observations from the experimental data. Data-driven and model based prognostics algorithms were investigated where ON-state resistance was used as the primary precursor of failure feature. A Gaussian process regression algorithm was explored as an example for a data-driven technique and an extended Kalman filter and a particle filter were used as examples for model-based techniques. Both methods were able to provide valid results. Prognostic performance metrics were employed to evaluate and compare the algorithms.
A Model-Based Prognostics Methodology For Electrolytic Capacitors Based On Electrical Overstress Accelerated Aging
A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.
A Model-based Prognostics Methodology for Electrolytic Capacitors Based on Electrical Overstress Accelerated Aging
A remaining useful life prediction methodology for elec- trolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good can- didate for component level prognostics and health manage- ment. Prognostics provides a way to assess remaining use- ful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated ag- ing test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This prelim- inary remaining life prediction algorithm serves as a demon- stration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation pro- gression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognos- tics methods typically used for remaining useful life predic- tions in other applications.
A Testbed for Implementing Prognostic Methodologies on Cryogenic Propellant Loading Systems
Prognostics technologies determine the health state of a system and predict its remaining useful life. With this information, operators are able to make maintenance-related decisions, thus effectively streamlining operational and mission level activities. Experimentation on testbeds representative of critical systems is very useful for the maturation of prognostics technology; precise emulation of actual fault conditions on such a testbed further validates these technologies. In this paper we present the development of a pneumatic valve testbed, initial experimental results and progress towards the maturation and validation of component-level prognostic methods in the context of cryogenic refueling operations. The pneumatic valve testbed allows for the injection of time-varying leaks with specified damage progression profiles in order to emulate common valve faults. The pneumatic valve testbed also contains a battery used to power some pneumatic components, enabling the study of the effects of battery degradation on the operation of the valves.
Towards A Model-based Prognostics Methodology for Electrolytic Capacitors: A Case Study Based on Electrical Overstress Accelerated Aging
A remaining useful life prediction methodology for elec- trolytic capacitors is presented. This methodology adopts a Kalman filter approach in conjunction with an empirical state-based degradation model to predict the degradation of capacitor parameters through the life of the capacitor. Elec- trolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are good candi- dates for component level prognostics and health manage- ment. Prognostics provides a way to assess remaining use- ful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. This paper discusses the empirical degradation models and experi- mental results of an accelerated aging test performed on a set of identical capacitors subjected to electrical stress. The data form the basis for developing the Kalman-filter based remain- ing life prediction algorithm.
Towards A Model-Based Prognostics Methodology For Electrolytic Capacitors: A Case Study Based On Electrical Overstress Accelerated Aging
This paper presents a model-driven methodology for predict- ing the remaining useful life of electrolytic capacitors. This methodology adopts a Kalman filter approach in conjunction with an empirical state-based degradation model to predict the degradation of capacitor parameters through the life of the capacitor. Electrolytic capacitors are important components of systems that range from power supplies on critical avion- ics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their critical role in the system, they are good candidates for component level prognostics and health management. Prognostics provides a way to assess remain- ing useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. This paper proposes and empirical degradation model and discusses experimental results for an accelerated aging test performed on a set of identical capacitors subjected to electrical stress. The data forms the basis for developing the Kalman-filter based remaining life prediction algorithm.
Implementation of Prognostic Methodologies to Cryogenic Propellant Loading Test-bed
Prognostics methodologies determine the health state of a system and predict the end of life and remaining useful life. This information enables operators to take maintenance related decisions, thus effectively streamlining operational and mission-level activities. Prognostics testbeds help in the prototyping, development, and maturation of prognostic technologies. In this work, we present a prognostics testbed for pneumatic valves. Pneumatic valves are critical components in many industrial processes, and the testbed will be used to showcase how remaining life prediction works in the context of cryogenic refueling operations. The testbed allows for the injection of time-varying leaks with specified damage progression profiles in order to emulate common valve faults. In addition, the testbed contains a battery used to power some components, allowing the study of the effects of battery degradation on the operation of the valves. Prognostic algorithms will utilize sensor data collected from the different transducers in order to estimate component health and make life predictions, based on mathematical models describing the underlying physics of component degradation and employing a Bayesian filtering algorithm for state-parameter estimation from which life predictions are made.
Aging Methodologies and Prognostic Health Management for Electrolytic Capacitors
Understanding the ageing mechanisms of electronic components critical avionics systems such as the GPS and INAV are of critical importance. Electrolytic capacitors and MOSFET’s have higher failure rates among the components of DC-DC power converter systems. Our current work focuses on analyzing and modeling electrolytic capacitor degradation and its effects on the output of DC-DC converter systems. The output degrada- tion is typically measured by an increase in ESR (Equivalent Series Resistance) and decrease in the capacitance value over long periods of use even under nominal operating conditions. Typically the primary effect of degradation is increased ripple current and this has adverse effects on downstream components. For example, in avionics systems where the power supply drives a GPS unit, ripple currents can cause glitches in the GPS position and velocity output, and this may cause errors in the Inertial Navigation (INAV) system, causing the aircraft to fly off course. In this paper, we present the details of our ageing methodology along with details of experiments and analysis of the results.
Prognostics of Power MOSFETs under Thermal Stress Accelerated Aging using Data-Driven and Model-Based Methodologies
An approach for predicting remaining useful life of power MOSFETs (metal oxide field effect transistor) devices has been developed. Power MOSFETs are semiconductor switching devices that are instrumental in electronics equipment such as those used in operation and control of modern aircraft and spacecraft. The MOSFETs examined here were aged under thermal overstress in a controlled experiment and continuous performance degradation data were collected from the accelerated aging experiment. Die- attach degradation was determined to be the primary failure mode. The collected run-to-failure data were analyzed and it was revealed that ON-state resistance increased as die-attach degraded under high thermal stresses. Results from finite element simulation analysis support the observations from the experimental data. Data-driven and model based prognostics algorithms were investigated where ON-state resistance was used as the primary precursor of failure feature. A Gaussian process regression algorithm was explored as an example for a data-driven technique and an extended Kalman filter and a particle filter were used as examples for model-based techniques. Both methods were able to provide valid results. Prognostic performance metrics were employed to evaluate and compare the algorithms.
Towards Accelerated Aging Methodologies and Health Management of Power MOSFETs
Understanding aging mechanisms of electronic components is of extreme importance in the aerospace domain where they are part of numerous critical subsystems including avionics. In particular, power MOSFETs are of special interest as they are involved in high voltage switching circuits such as drivers for electrical motors. With increased use of electronics in aircraft control, it becomes more important to understand the degradation of these components in aircraft specific environments. In this paper, we present an accelerated aging methodology for power MOSFETs that subject the devices to indirect thermal overstress during high voltage switching. During this accelerated aging process, two major modes of failure were observed – latch-up and die attach degradation. In this paper we present the details of our aging methodology along with details of experiments and analysis of the results.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.