Search results for "clusterin"

Non‐uniform displacement within ruptured Achilles tendon during isometric contraction

2021

The purpose of this study was investigate tendon displacement patterns in non‐surgically treated patients 14 months after acute Achilles tendon rupture (ATR) and to classify patients into groups based on their Achilles tendon (AT) displacement patterns. Twenty patients were tested. Sagittal images of AT were acquired using B‐mode ultrasonography during ramp contractions at a torque level corresponding to 30% of the maximal isometric plantarflexion torque of the uninjured limb. A speckle tracking algorithm was used to track proximal‐distal movement of the tendon tissue at 6 antero‐posterior locations. Two‐way repeated measures ANOVA for peak tendon displacement was performed. K‐means cluster…

A bibliometric approach to finding fields that co-evolved with information technology

2020

Among the declining industries, for example music industry, some have been revived by information technology (IT). At the same time, in academic fields, some have expected co-evolutions between IT and other fields to cause the resurgence of either field. In this research, the clustering of citation networks with 14,438 academic papers resulted in the identification of 28 academic fields in the areas “Computer Science” or “Information Science and Library Science.” Co-evolutions between these 28 fields and citing fields to the 28 fields were evaluated by an investigation of contents; a methodology to search co-evolutions was also proposed. This paper proposes that pairs of academic fields (wi…

Ensemble deep clustering analysis for time window determination of event-related potentials

2023

Objective Cluster analysis of spatio-temporal event-related potential (ERP) data is a promising tool for exploring the measurement time window of ERPs. However, even after preprocessing, the remaining noise can result in uncertain cluster maps followed by unreliable time windows while clustering via conventional clustering methods. Methods We designed an ensemble deep clustering pipeline to determine a reliable time window for the ERP of interest from temporal concatenated grand average ERP data. The proposed pipeline includes semi-supervised deep clustering methods initialized by consensus clustering and unsupervised deep clustering methods with end-to-end architectures. Ensemble clusterin…

ProcMiner: Advancing Process Analysis and Management

2007

This paper contributes both to research and practice on process mining. Previous research on process mining has focused on mining patterns from event log files to generate process models. The process mining approach adopted in this paper is focused on producing patterns about process models, not the models themselves. The approach is demonstrated by ProcMiner -an explorative research prototype for management, consolidating, publishing, retrieving, and analyzing process models. Content-based document clustering is applied to process models represented as XML database in order to find topical groups from models. In practice, organizations face numerous challenges in managing their process mod…

Unstable feature relevance in classification tasks

2011

Knowledge discovery using diffusion maps

2013

Radio frequency fingerprinting for outdoor user equipment localization

2017

The recent advancements in cellular mobile technology and smart phone usage have opened opportunities for researchers and commercial companies to develop ubiquitous low cost localization systems. Radio frequency (RF) fingerprinting is a popular positioning technique which uses radio signal strength (RSS) values from already existing infrastructures to provide satisfactory user positioning accuracy in indoor and densely built outdoor urban areas where Global Navigation Satellite System (GNSS) signal is poor and hard to reach. However a major requirement for the RF fingerprinting to maintain good localization accuracy is the collection and updating of large training database. The Minimization…

CLUSTERING INCOMPLETE SPECTRAL DATA WITH ROBUST METHODS

2018

Abstract. Missing value imputation is a common approach for preprocessing incomplete data sets. In case of data clustering, imputation methods may cause unexpected bias because they may change the underlying structure of the data. In order to avoid prior imputation of missing values the computational operations must be projected on the available data values. In this paper, we apply a robust nan-K-spatmed algorithm to the clustering problem on hyperspectral image data. Robust statistics, such as multivariate medians, are more insensitive to outliers than classical statistics relying on the Gaussian assumptions. They are, however, computationally more intractable due to the lack of closed-for…

Assessment of nonnegative matrix factorization algorithms for electroencephalography spectral analysis.

2020

AbstractBackgroundNonnegative matrix factorization (NMF) has been successfully used for electroencephalography (EEG) spectral analysis. Since NMF was proposed in the 1990s, many adaptive algorithms have been developed. However, the performance of their use in EEG data analysis has not been fully compared. Here, we provide a comparison of four NMF algorithms in terms of accuracy of estimation, stability (repeatability of the results) and time complexity of algorithms with simulated data. In the practical application of NMF algorithms, stability plays an important role, which was an emphasis in the comparison. A Hierarchical clustering algorithm was implemented to evaluate the stability of NM…

Toolbox for Distance Estimation and Cluster Validation on Data With Missing Values

2022

Missing data are unavoidable in the real-world application of unsupervised machine learning, and their nonoptimal processing may decrease the quality of data-driven models. Imputation is a common remedy for missing values, but directly estimating expected distances have also emerged. Because treatment of missing values is rarely considered in clustering related tasks and distance metrics have a central role both in clustering and cluster validation, we developed a new toolbox that provides a wide range of algorithms for data preprocessing, distance estimation, clustering, and cluster validation in the presence of missing values. All these are core elements in any comprehensive cluster analy…