Search results for "cluster analysis."
showing 10 items of 805 documents
Understanding the Study Experiences of Students in Low Agency Profile: Towards a Smart Education Approach
2020
In this paper, we use student agency analytics to examine how university students who assessed to have low agency resources describe their study experiences. Students ( n=292 ) completed the Agency of University Students (AUS) questionnaire. Furthermore, they reported what kinds of restrictions they experienced during the university course they attended. Four different agency profiles were identified using robust clustering. We then conducted a thematic analysis of the open-ended answers of students who assessed to have low agency resources. Issues relating to competence beliefs, self-efficacy, student-teacher relations, time as a resource, student well-being, and course contents seemed to …
Patient satisfaction : results of cluster analysis of finnish patients
2023
Background Healthcare providers must understand patients’ expectations and perceptions of the care they receive to provide high-quality care. The purpose of this study is to identify and analyse different clusters of patient satisfaction with the quality of care at Finnish acute care hospitals. Methods A cross-sectional design was applied. The data were collected in 2017 from three Finnish acute care hospitals with the Revised Humane Caring Scale (RHCS) as a paper questionnaire, including six background questions and six subscales. The k-means clustering method was used to define and analyse clusters in the data. The unit of analysis was a health system encompassing inpatients and outpatien…
A Statistical Approach for A-Posteriori Deployment of Microclimate Sensors in Museums: A Case Study
2022
[EN] The deployment of sensors is the first issue encountered when microclimate monitoring is planned in spaces devoted to the conservation of artworks. Sometimes, the first decision regarding the position of sensors may not be suitable for characterising the microclimate close to climate sensitive artworks or should be revised in light of new circumstances. This paper fits into this context by proposing a rational approach for a posteriori deployment of microclimate sensors in museums where long-term temperature and relative humidity observations were available (here, the Rosenborg Castle, Copenhagen, Denmark). Different statistical tools such as box-and-whisker plots, principal component …
Buone pratiche e strumenti di analisi per l’apprendimento, l’insegnamento e l’inclusione
2022
Il presente lavoro, nato in seno al progetto di ricerca “Best practices and tools of analysis in schools and community contexts: learning, teaching & inclusion”, avviato su fondi del Dipartimento SPPEFF dell’Università di Palermo, nel marzo 2019 e giunto alla sua seconda fase. La metodologia di ricerca utilizzata – perché ritenuta adeguata a perseguire le finalità fissate e a fornire una visione complessa ed articolata del fenomeno investigato – è stata quella del Mixed Method, con particolare riferimento all’Explanatory Design: Participant Selection Model di Creswell, Plano Clark, et al. (2003). L’«Explanatory Design is a two-phase mixed methods design. The overall purpose of this desi…
Agricultural feedstock for solid and liquid biofuel production in Ukraine: cluster analysis
2019
This study is focused on the cluster analysis of biofuel feedstock in Ukraine. In recent years, Ukraine has been facing energy issues. There was a drop in fossil fuel production. On other hand, there has been a rise in crop production. Therefore, one of Ukraine’s priorities is to develop energy application using agricultural feedstocks. The cluster analysis was used to distinguish regions by their feedstock potential. Feedstocks for solid biofuel, bioethanol, and biodiesel were investigated. Promising groups of regions for biofuel production were identified. The results can be used to create autonomous power supply systems based on agricultural by-products (straw and husk). The corn belt se…
Virtual Reality, Augmented Reality, and In Vivo Exposure Therapy: A Preliminary Comparison of Treatment Efficacy in Small Animal Phobia
2018
This study aggregated data from three randomized control trials to explore the differential efficacy of three forms of exposure therapy, namely, in vivo (iVET), virtual reality (VRET), and augmented reality (ARET), in the treatment of small animal phobia. Additionally, baseline patient characteristics were used to detect subgroups of patients who showed a differential response to certain treatment modalities. Primary measures were distance covered, anxiety during the behavioral avoidance test (BAT), and overall fear of small animals. A repeated-measures analysis of variance was used to explore the overall treatment effect across the exposure modalities. A cluster analysis and an analysis of…
Mental health profiles of Finnish adolescents before and after the peak of the COVID-19 pandemic
2023
Abstract Background The COVID-19 pandemic has had implications for adolescents’ interpersonal relationships, communication patterns, education, recreational activities and well-being. An understanding of the impact of the pandemic on their mental health is crucial in measures to promote the post-pandemic recovery. Using a person-centered approach, the current study aimed to identify mental health profiles in two cross-sectional samples of Finnish adolescents before and after the peak of the pandemic, and to examine how socio-demographic and psychosocial factors, academic expectations, health literacy, and self-rated health are associated with the emerging profiles. Methods and findings Surv…
SparseHC: A Memory-efficient Online Hierarchical Clustering Algorithm
2014
Computing a hierarchical clustering of objects from a pairwise distance matrix is an important algorithmic kernel in computational science. Since the storage of this matrix requires quadratic space with respect to the number of objects, the design of memory-efficient approaches is of high importance to this research area. In this paper, we address this problem by presenting a memory-efficient online hierarchical clustering algorithm called SparseHC. SparseHC scans a sorted and possibly sparse distance matrix chunk-by-chunk. Meanwhile, a dendrogram is built by merging cluster pairs as and when the distance between them is determined to be the smallest among all remaining cluster pairs. The k…
An Examination of Tourist Arrivals Dynamics Using Short-Term Time Series Data: A Space—Time Cluster Approach
2013
The purpose of this study is to examine the development of Italian tourist areas ( circoscrizioni turistiche) through a cluster analysis of short time series. The technique is an adaptation of the functional data analysis approach developed by Abraham et al (2003), which combines spline interpolation with k-means clustering. The findings indicate the presence of two patterns (increasing and stable) averagely characterizing groups of territories. Moreover, tests of spatial contiguity suggest the presence of ‘space–time clusters’; that is, areas in the same ‘time cluster’ are also spatially contiguous. These findings appear to be more robust in particular for those series characterized by an…
Measuring galaxy segregation with the mark connection function
2010
(abridged) The clustering properties of galaxies belonging to different luminosity ranges or having different morphological types are different. These characteristics or `marks' permit to understand the galaxy catalogs that carry all this information as realizations of marked point processes. Many attempts have been presented to quantify the dependence of the clustering of galaxies on their inner properties. The present paper summarizes methods on spatial marked statistics used in cosmology to disentangle luminosity, colour or morphological segregation and introduces a new one in this context, the mark connection function. The methods used here are the partial correlation functions, includi…