Search results for "K-means"
showing 10 items of 43 documents
Exploratory approach for network behavior clustering in LoRaWAN
2021
AbstractThe interest in the Internet of Things (IoT) is increasing both as for research and market perspectives. Worldwide, we are witnessing the deployment of several IoT networks for different applications, spanning from home automation to smart cities. The majority of these IoT deployments were quickly set up with the aim of providing connectivity without deeply engineering the infrastructure to optimize the network efficiency and scalability. The interest is now moving towards the analysis of the behavior of such systems in order to characterize and improve their functionality. In these IoT systems, many data related to device and human interactions are stored in databases, as well as I…
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…
Cluster-Based Relocation of Stations for Efficient Forest Fire Management in the Province of Valencia (Spain)
2021
Forest fires are undesirable situations with tremendous impacts on wildlife and people&rsquo
Privacy preserving data collection for smart grid using self-organizing map
2017
Homomorphic encryption is widely researched in the smart grid area to publish and transfer electricity consumption data between electricity companies. This method makes it feasible to calculate total electricity consumption of neighborhoods without sharing any raw electricity consumption data. In the area of demand response(DR), calculating the total consumption of electricity is important in order to create DR reports which are published by third party to reduce the peak period of electricity usage such as 7 am or 6pm. Nevertheless, the possibility of data exposing or data decryption may lead to individual households private information revealing, for example, the timing of leaving home, t…
H&E Multi-Laboratory Staining Variance Exploration with Machine Learning
2022
In diagnostic histopathology, hematoxylin and eosin (H&E) staining is a critical process that highlights salient histological features. Staining results vary between laboratories regardless of the histopathological task, although the method does not change. This variance can impair the accuracy of algorithms and histopathologists’ time-to-insight. Investigating this variance can help calibrate stain normalization tasks to reverse this negative potential. With machine learning, this study evaluated the staining variance between different laboratories on three tissue types. We received H&E-stained slides from 66 different laboratories. Each slide contained kidney, skin, and colon tissue sampl…
Syntaxonomy and biogeography of the Irano‐Turanian mires and springs
2021
Aims: To develop the first comprehensive syntaxonomic classification for patchy montane mire and spring vegetation across the Irano-Turanian phytogeographical region in Iran, Tajikistan and Kyrgyzstan and to explore the effects of the main environmental and geographic gradients on their distribution. Location: Alborz Mountain range (Iran), Pamir-Alai Mountains (Tajikistan) and Tian Shan Mountains (Kyrgyzstan); total area of about 3,000,000 km2. Methods: A database of 1,015 vegetation relevés including a total of 675 vascular and bryophyte taxa was established, covering the large mountains ranges of the Irano-Turanian regions in Iran, Tajikistan and Kyrgyzstan, at altitude ranging from 1,300…
Fast PET Scan Tumor Segmentation Using Superpixels, Principal Component Analysis and K-Means Clustering
2018
Positron Emission Tomography scan images are extensively used in radiotherapy planning, clinical diagnosis, assessment of growth and treatment of a tumor. These all rely on fidelity and speed of detection and delineation algorithm. Despite intensive research, segmentation remained a challenging problem due to the diverse image content, resolution, shape, and noise. This paper presents a fast positron emission tomography tumor segmentation method in which superpixels are extracted first from the input image. Principal component analysis is then applied on the superpixels and also on their average. Distance vector of each superpixel from the average is computed in principal components coordin…
Automatic detection of cervical cells in Pap-smear images using polar transform and k-means segmentation
2016
We introduce a novel method of cell detection and segmentation based on a polar transformation. The method assumes that the seed point of each candidate is placed inside the nucleus. The polar representation, built around the seed, is segmented using k-means clustering into one candidate-nucleus cluster, one candidate-cytoplasm cluster and up to three miscellaneous clusters, representing background or surrounding objects that are not part of the candidate cell. For assessing the natural number of clusters, the silhouette method is used. In the segmented polar representation, a number of parameters can be conveniently observed and evaluated as fuzzy memberships to the non-cell class, out of …
Hierarchical and non-hierarchical clustering methods to study students algebraic thinking in solving an open-ended questionnaire
2017
The problem of taking a data set and separating it into subgroups, where the members of each subgroup are more similar to each other than they are to members outside the subgroup, has been extensively studied in science and mathematics education research. Student responses to written questions and multiple-choice tests have been characterised and studied using several qualitative and/or quantitative analysis methods. However, there are inherent difficulties in the categorisation of student responses in the case of open-ended questionnaires. Very often, researcher bias means that the categories picked out tend to find the groups of students that the researcher is seeking out. In our contribu…
Unsupervised change detection with kernels
2012
In this paper an unsupervised approach to change detection relying on kernels is introduced. Kernel based clustering is used to partition a selected subset of pixels representing both changed and unchanged areas. Once the optimal clustering is obtained the estimated representatives (centroids) of each group are used to assign the class membership to all others pixels composing the multitemporal scenes. Different approaches of considering the multitemporal information are considered with accent on the computation of the difference image directly in the feature spaces. For this purpose a difference kernel approach is successfully adopted. Finally an effective way to cope with the estimation o…