scholarly journals Integrated modulo scheduling and cluster assignment for TI TMS320C64x+ architecture

Author(s):  
Nikolai Kim ◽  
Andreas Krall
2017 ◽  
Vol 225 (3) ◽  
pp. 268-284 ◽  
Author(s):  
Andrew J. White ◽  
Dieter Kleinböhl ◽  
Thomas Lang ◽  
Alfons O. Hamm ◽  
Alexander L. Gerlach ◽  
...  

Abstract. Ambulatory assessment methods are well suited to examine how patients with panic disorder and agoraphobia (PD/A) undertake situational exposure. But under complex field conditions of a complex treatment protocol, the variability of data can be so high that conventional analytic approaches based on group averages inadequately describe individual variability. To understand how fear responses change throughout exposure, we aimed to demonstrate the incremental value of sorting HR responses (an index of fear) prior to applying averaging procedures. As part of their panic treatment, 85 patients with PD/A completed a total of 233 bus exposure exercises. Heart rate (HR), global positioning system (GPS) location, and self-report data were collected. Patients were randomized to one of two active treatment conditions (standard exposure or fear-augmented exposure) and completed multiple exposures in four consecutive exposure sessions. We used latent class cluster analysis (CA) to cluster heart rate (HR) responses collected at the start of bus exposure exercises (5 min long, centered on bus boarding). Intra-individual patterns of assignment across exposure repetitions were examined to explore the relative influence of individual and situational factors on HR responses. The association between response types and panic disorder symptoms was determined by examining how clusters were related to self-reported anxiety, concordance between HR and self-report measures, and bodily symptom tolerance. These analyses were contrasted with a conventional analysis based on averages across experimental conditions. HR responses were sorted according to form and level criteria and yielded nine clusters, seven of which were interpretable. Cluster assignment was not stable across sessions or treatment condition. Clusters characterized by a low absolute HR level that slowly decayed corresponded with low self-reported anxiety and greater self-rated tolerance of bodily symptoms. Inconsistent individual factors influenced HR responses less than situational factors. Applying clustering can help to extend the conventional analysis of highly variable data collected in the field. We discuss the merits of this approach and reasons for the non-stereotypical pattern of cluster assignment across exposures.


2019 ◽  
Vol 12 (2) ◽  
pp. 1-26 ◽  
Author(s):  
Julian Oppermann ◽  
Melanie Reuter-Oppermann ◽  
Lukas Sommer ◽  
Andreas Koch ◽  
Oliver Sinnen

2020 ◽  
pp. 152483992097298
Author(s):  
Alexis K. Grant

Local health departments (LHDs) are positioned to act as the community health strategist for their catchment area, which requires cross-sector collaboration. However, little research exists to understand how much and what types of cross-sector collaboration occur and its impact on LHD practice. Data from 490 LHDs who participated in the 2016 National Profile of Local Health Departments survey were analyzed to identify patterns of cross-sector collaboration among LHDs. In the survey, LHDs reported the presence of collaborative activities for each of 22 categories of organizations. Factor analysis was used to identify patterns in the types of organizations with which LHDs collaborate. Then, cluster analysis was conducted to identify patterns in the types of cross-sector collaboration, and cross-sectional analyses examined which LHD characteristics were associated with cluster assignment. LHDs collaborated most with traditional health care–oriented organizations, but less often with organizations focused on upstream determinants of health such as housing. Three distinct clusters represented collaboration patterns in LHDs: coordinators, networkers, and low-collaborators. LHDs who were low-collaborators were more likely to serve smaller populations, be unaccredited, have a smaller workforce, have a White top executive, and have a top executive without a graduate degree. These findings imply that public health practitioners should prioritize building bridges to a variety of organizations and engage in collaboration beyond information sharing. Furthermore, LHDs should prioritize accreditation and workforce development activities for supporting cross-sector collaboration. With these investments, the public health system can better address the social and structural determinants of health and promote health equity.


Data in Brief ◽  
2021 ◽  
pp. 106967
Author(s):  
Pascale Mistral ◽  
Flavie Vanlerberghe-Masutti ◽  
Sonia Elbelt ◽  
Nathalie Boissot

1999 ◽  
Vol 34 (7) ◽  
pp. 28-34 ◽  
Author(s):  
Eric Stotzer ◽  
Ernst Leiss

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Weston J. Jackson ◽  
Ipsita Agarwal ◽  
Itsik Pe’er

Motivation. Microbiome sequencing allows defining clusters of samples with shared composition. However, this paradigm poorly accounts for samples whose composition is a mixture of cluster-characterizing ones and which therefore lie in between them in the cluster space. This paper addresses unsupervised learning of 2-way clusters. It defines a mixture model that allows 2-way cluster assignment and describes a variant of generalized k-means for learning such a model. We demonstrate applicability to microbial 16S rDNA sequencing data from the Human Vaginal Microbiome Project.


Author(s):  
Julian Oppermann ◽  
Patrick Sittel ◽  
Martin Kumm ◽  
Melanie Reuter-Oppermann ◽  
Andreas Koch ◽  
...  

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