Search results for "K-Means"

Joint interpretation of seismic refraction tomography and electrical resistivity tomography by cluster analysis to detect buried cavities

2020

Abstract In the last few years, the geophysical methods of seismic refraction tomography (SRT) and electrical resistivity tomography (ERT) are among the most used geophysical techniques for the reconstruction of subsoil geometries, for the investigation of underground cavities and also for the archaeological prospecting. However, the main disadvantage of each geophysical method is the difficulty of final interpretation of the data. In order to eliminate artifacts and generally improve the reliability and accuracy of geophysical interpretation, it is useful to perform a joint approach of different geophysical methods, also introducing the a priori information. In this work, it is shown the i…

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…

Balance Perturbations as a Measurement Tool for Trunk Impairment in Cross-Country Sit Skiing

2018

In cross-country sit-skiing, the trunk plays a crucial role in propulsion generation and balance maintenance. Trunk stability is evaluated by automatic responses to unpredictable perturbations; however, electromyography is challenging. The aim of this study was to identify a measure to group sit-skiers according to their ability to control the trunk. Seated in their competitive sit-ski, 10 male and 5 female Paralympic sit-skiers received 6 forward and 6 backward unpredictable perturbations in random order. k-means clustered trunk position at rest, delay to invert the trunk motion, and trunk range of motion significantly into 2 groups. In conclusion, unpredictable perturbations might quantif…

A Clustering approach for profiling LoRaWAN IoT devices

2019

Internet of Things (IoT) devices are starting to play a predominant role in our everyday life. Application systems like Amazon Echo and Google Home allow IoT devices to answer human requests, or trigger some alarms and perform suitable actions. In this scenario, any data information, related device and human interaction are stored in databases and can be used for future analysis and improve the system functionality. Also, IoT information related to the network level (wireless or wired) may be stored in databases and can be processed to improve the technology operation and to detect network anomalies. Acquired data can be also used for profiling operation, in order to group devices according…

K-means Clustering to Study How Student Reasoning Lines Can Be Modified by a Learning Activity Based on Feynman’s Unifying Approach

2017

Background:Research in Science Education has shown that often students need to learn how to identify differences and similarities between descriptive and explicative models. The development and use of explicative skills in the field of thermal science has always been a difficult objective to reach. A way to develop analogical reasoning is to use in Science Education unifying conceptual frameworks.Material and methods:A questionnaire containing six open-ended questions on thermally activated phenomena was administered to the students before instruction. A second one, similar but focused on different physical content was administered after instruction. Responses were analysed using k-means Cl…

Improving clustering of Web bot and human sessions by applying Principal Component Analysis

2019

View references (18) The paper addresses the problem of modeling Web sessions of bots and legitimate users (humans) as feature vectors for their use at the input of classification models. So far many different features to discriminate bots’ and humans’ navigational patterns have been considered in session models but very few studies were devoted to feature selection and dimensionality reduction in the context of bot detection. We propose applying Principal Component Analysis (PCA) to develop improved session models based on predictor variables being efficient discriminants of Web bots. The proposed models are used in session clustering, whose performance is evaluated in terms of the purity …

Complex Networked Systems: Convergence Analysis, Dynamic Behaviour, and Security.

Complex networked systems are a modern reference framework through which very dierent systems from far disciplines, such as biology, computer science, physics, social science, and engineering, can be described. They arise in the great majority of modern technological applications. Examples of real complex networked systems include embedded systems, biological networks, large-scale systems such as power generation grids, transportation networks, water distribution systems, and social network. In the recent years, scientists and engineers have developed a variety of techniques, approaches, and models to better understand and predict the behaviour of these systems, even though several research…

Cluster-based RF fingerprint positioning using LTE and WLAN signal strengths

2017

Wireless Local Area Network (WLAN) positioning has become a popular localization system due to its low-cost installation and widespread availability of WLAN access points. Traditional grid-based radio frequency (RF) fingerprinting (GRFF) suffers from two drawbacks. First it requires costly and non-efficient data collection and updating procedure; secondly the method goes through time-consuming data pre-processing before it outputs user position. This paper proposes Cluster-based RF Fingerprinting (CRFF) to overcome these limitations by using modified Minimization of Drive Tests data which can be autonomously collected by cellular operators from their subscribers. The effect of environmental…

Classification of cat ganglion retinal cells and implications for shape-function relationship

2002

This article presents a quantitative approach to ganglion cell classification by considering combinations of several geometrical features including fractal dimension, symmetry, diameter, eccentricity and convex hull. Special attention is given to moment and symmetry-based features. Several combinations of such features are fed to two clustering methods (Ward's hierarchical scheme and K-Means) and the respectively obtained classifications are compared. The results indicate the superiority of some features, also suggesting possible biological implications.

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…