Fault location based on synchronized measurements: a comprehensive survey.
Ontology highlight
ABSTRACT:
SUBMITTER: Al-Mohammed AH
PROVIDER: S-EPMC3948645 | biostudies-other | 2014
REPOSITORIES: biostudies-other
Similar Datasets
Project description:This repository offers smart-home wearable accelerometer and Radio Signal Strength Indicator (RSSI) data acquired : 1) with low-cost hardware; 2) with high-resolution location annotations; 3) from four UK homes. The data are intended to evaluate RSSI-based indoor localisation methods with activity measurements provided from a user-worn wearable device. A wrist worn accelerometer records activity signatures which are relayed to a number of receiving Access Points (AP) placed throughout the building. Upon reception of a packet, each AP measures the RSSI of the received radio signal and timestamps the accelerometer measurements. Location labels are recorded automatically using a small camera which registers fiducial floor tags as the participant carries out their normal routines in a natural way. Approximately 14?h of annotated wearable measurements are provided. A scripted fingerprint measurement is provided along with several unscripted natural living recordings, where the participant carried out a number of daily household activities which are annotated, where possible, throughout. Codes are provided to access the data and to replicate the ground-truthing procedure.
| S-EPMC6103259 | biostudies-literature
Project description:High-resolution animal location data are increasingly available, requiring analytical approaches and statistical tools that can accommodate the temporal structure and transient dynamics (non-stationarity) inherent in natural systems. Traditional analyses often assume uncorrelated or weakly correlated temporal structure in the velocity (net displacement) time series constructed using sequential location data. We propose that frequency and time-frequency domain methods, embodied by Fourier and wavelet transforms, can serve as useful probes in early investigations of animal movement data, stimulating new ecological insight and questions. We introduce a novel movement model with time-varying parameters to study these methods in an animal movement context. Simulation studies show that the spectral signature given by these methods provides a useful approach for statistically detecting and characterizing temporal dependency in animal movement data. In addition, our simulations provide a connection between the spectral signatures observed in empirical data with null hypotheses about expected animal activity. Our analyses also show that there is not a specific one-to-one relationship between the spectral signatures and behavior type and that departures from the anticipated signatures are also informative. Box plots of net displacement arranged by time of day and conditioned on common spectral properties can help interpret the spectral signatures of empirical data. The first case study is based on the movement trajectory of a lion (Panthera leo) that shows several characteristic daily activity sequences, including an active-rest cycle that is correlated with moonlight brightness. A second example based on six pairs of African buffalo (Syncerus caffer) illustrates the use of wavelet coherency to show that their movements synchronize when they are within approximately 1 km of each other, even when individual movement was best described as an uncorrelated random walk, providing an important spatial baseline of movement synchrony and suggesting that local behavioral cues play a strong role in driving movement patterns. We conclude with a discussion about the role these methods may have in guiding appropriately flexible probabilistic models connecting movement with biotic and abiotic covariates.
| S-EPMC3032889 | biostudies-literature
Project description:RNA samples from human tissues (brain and liver) and cell lines (K562 and HL60) were used to assess RNA fragmentation, RNA fractionation, cDNA synthesis, and single versus multiple tag counting. Technical replicates and different cDNA synthesis protocols were compared. Though protocols employing polyA RNA selection generate the highest number of non-ribosomal reads and the most precise measurements for coding transcripts, such protocols were found to detect only a fraction of the non-ribosomal RNA in human cells. PolyA RNA excludes thousands of annotated and even more unannotated transcripts, resulting in an incomplete view of the transcriptome. Ribosomal-depleted RNA provides a more cost-effective method for generating complete transcriptome coverage. Expression measurements using single tag counting provided advantages for assessing gene expression and for detecting short RNAs relative to multi-read protocols. Detection of short RNAs was also hampered by RNA fragmentation. 69 different sequencing channels from a HeliScope Genetic Analysis System and 2 channels from an Illumina machine are included. Some samples were sequenced on multiple channels and some samples include technical replicates.
2011-03-24 | E-GEOD-28123 | biostudies-arrayexpress
Project description:RNA samples from human tissues (brain and liver) and cell lines (K562 and HL60) were used to assess RNA fragmentation, RNA fractionation, cDNA synthesis, and single versus multiple tag counting. Technical replicates and different cDNA synthesis protocols were compared. Though protocols employing polyA RNA selection generate the highest number of non-ribosomal reads and the most precise measurements for coding transcripts, such protocols were found to detect only a fraction of the non-ribosomal RNA in human cells. PolyA RNA excludes thousands of annotated and even more unannotated transcripts, resulting in an incomplete view of the transcriptome. Ribosomal-depleted RNA provides a more cost-effective method for generating complete transcriptome coverage. Expression measurements using single tag counting provided advantages for assessing gene expression and for detecting short RNAs relative to multi-read protocols. Detection of short RNAs was also hampered by RNA fragmentation.
2011-03-24 | GSE28123 | GEO
Project description:Artificial neural networks (ANNs) are powerful computational tools that are designed to replicate the human brain and adopted to solve a variety of problems in many different fields. Fault tolerance (FT), an important property of ANNs, ensures their reliability when significant portions of a network are lost. In this paper, a fault/noise injection-based (FIB) genetic algorithm (GA) is proposed to construct fault-tolerant ANNs. The FT performance of an FIB-GA was compared with that of a common genetic algorithm, the back-propagation algorithm, and the modification of weights algorithm. The FIB-GA showed a slower fitting speed when solving the exclusive OR (XOR) problem and the overlapping classification problem, but it significantly reduced the errors in cases of single or multiple faults in ANN weights or nodes. Further analysis revealed that the fit weights showed no correlation with the fitting errors in the ANNs constructed with the FIB-GA, suggesting a relatively even distribution of the various fitting parameters. In contrast, the output weights in the training of ANNs implemented with the use the other three algorithms demonstrated a positive correlation with the errors. Our findings therefore indicate that a combination of the fault/noise injection-based method and a GA is capable of introducing FT to ANNs and imply that the distributed ANNs demonstrate superior FT performance.
| S-EPMC5055486 | biostudies-literature
Project description:ObjectiveMonitoring inequality in healthcare utilisation is essential to reduce persistent inequalities in health in lower-middle income countries. This study aimed to assess socioeconomic inequalities in the utilisation of primary care, secondary care and preventive care in Indonesia.MethodsA cross-sectional study was conducted using data from the 2014 Indonesia Family Life Survey with a total of 42?083 adult participants. Socioeconomic status (SES) was measured by educational level and income. Healthcare utilisation was measured in: (1) primary care, (2) outpatient in secondary care, (3) inpatient care and (4) cardiovascular-related preventive care. The magnitude of inequalities was measured using the relative index of inequality (RII).ResultsSmall educational inequalities were found for primary care utilisation (RII 1.13, 95%?CI 1.01 to 1.26). Larger educational inequalities were found for outpatient secondary care (RII 10.35, 95%?CI 8.11 to 13.22) and inpatient care (RII 2.78, 95%?CI 2.32 to 3.32). The largest educational inequalities were found for preventive care, particularly regarding blood glucose tests (RII 30.31, 95%?CI 26.13 to 35.15) and electrocardiography tests (RII 30.90, 95%?CI 24.97 to 38.23). Compared with educational inequalities, income inequalities were larger for primary care (RII 1.68, 95%?CI 1.52 to 1.85) and inpatient care (RII 3.11, 95%?CI 2.63 to 3.66), but not for outpatient secondary care and preventive care.ConclusionsSocioeconomic inequalities in healthcare utilisation in Indonesia are particularly large in secondary and preventive care. Therefore, it is recommended to prioritise policies focused on improving timely, geographical and financial access to secondary and preventive care for lower SES groups.
| S-EPMC6661624 | biostudies-literature
Project description:Location-based sampling is a method to obtain samples of people within ecological contexts relevant to specific public health outcomes. Random selection increases generalizability; however, in some circumstances (such as surveying bar patrons), recruitment conditions increase risks of sample bias. We attempted to recruit representative samples of bars and patrons in six California cities, but low response rates precluded meaningful analysis. A systematic review of 24 similar studies revealed that none addressed the key shortcomings of our study. We recommend steps to improve studies that use location-based sampling: (i) purposively sample places of interest, (ii) use recruitment strategies appropriate to the environment, and (iii) provide full information on response rates at all levels of sampling.
| S-EPMC5062950 | biostudies-literature
Project description:Control systems need to be able to operate under uncertainty and especially under attacks. To address such challenges, this paper formulates the solution of robust control for uncertain systems under time-varying and unknown time-delay attacks in cyber-physical systems (CPSs). A novel control method able to deal with thwart time-delay attacks on closed-loop control systems is proposed. Using a descriptor model and an appropriate Lyapunov functional, sufficient conditions for closed-loop stability are derived based on linear matrix inequalities (LMIs). A design procedure is proposed to obtain an optimal state feedback control gain such that the uncertain system can be resistant under an injection time-delay attack with variable delay. Furthermore, various fault detection frameworks are proposed by following the dynamics of the measured data at the system's input and output using statistical analysis such as correlation analysis and K-L (Kullback-Leibler) divergence criteria to detect attack's existence and to prevent possible instability. Finally, an example is provided to evaluate the proposed design method's effectiveness.
| S-EPMC8220189 | biostudies-literature
Project description:Non-invasive MEG/EEG source imaging provides valuable information about the epileptogenic brain areas which can be used to aid presurgical planning in focal epilepsy patients suffering from drug-resistant seizures. However, the source extent estimation for electrophysiological source imaging remains to be a challenge and is usually largely dependent on subjective choice. Our recently developed algorithm, fast spatiotemporal iteratively reweighted edge sparsity minimization (FAST-IRES) strategy, has been shown to objectively estimate extended sources from EEG recording, while it has not been applied to MEG recordings. In this work, through extensive numerical experiments and real data analysis in a group of focal drug-resistant epilepsy patients' interictal spikes, we demonstrated the ability of FAST-IRES algorithm to image the location and extent of underlying epilepsy sources from MEG measurements. Our results indicate the merits of FAST-IRES in imaging the location and extent of epilepsy sources for pre-surgical evaluation from MEG measurements.
| S-EPMC8648830 | biostudies-literature
Project description:We have screened the nearly complete DNA sequence of the human Y chromosome for microsatellites (short tandem repeats) that meet the criteria of having a repeat-unit size of > or = 3 and a repeat count of > or = 8 and thus are likely to be easy to genotype accurately and to be polymorphic. Candidate loci were tested in silico for novelty and for probable Y specificity, and then they were tested experimentally to identify Y-specific loci and to assess their polymorphism. This yielded 166 useful new Y-chromosomal microsatellites, 139 of which were polymorphic, in a sample of eight diverse Y chromosomes representing eight Y-SNP haplogroups. This large sample of microsatellites, together with 28 previously known markers analyzed here--all sharing a common evolutionary history--allowed us to investigate the factors influencing their variation. For simple microsatellites, the average repeat count accounted for the highest proportion of repeat variance (approximately 34%). For complex microsatellites, the largest proportion of the variance (again, approximately 34%) was explained by the average repeat count of the longest homogeneous array, which normally is variable. In these complex microsatellites, the additional repeats outside the longest homogeneous array significantly increased the variance, but this was lower than the variance of a simple microsatellite with the same total repeat count. As a result of this work, a large number of new, highly polymorphic Y-chromosomal microsatellites are now available for population-genetic, evolutionary, genealogical, and forensic investigations.
| S-EPMC1182082 | biostudies-other