Search results for " drive"

Cluster-Based RF Fingerprint Positioning Using LTE and WLAN Outdoor Signals

2015

In this paper we evaluate user-equipment (UE) positioning performance of three cluster-based RF fingerprinting methods using LTE and WLAN signals. Real-life LTE and WLAN data were collected for the evaluation purpose using consumer cellular-mobile handset utilizing ‘Nemo Handy’ drive test software tool. Test results of cluster-based methods were compared to the conventional grid-based RF fingerprinting. The cluster-based methods do not require grid-cell layout and training signature formation as compared to the gridbased method. They utilize LTE cell-ID searching technique to reduce the search space for clustering operation. Thus UE position estimation is done in short time with less comput…

An efficient cluster-based outdoor user positioning using LTE and WLAN signal strengths

2015

In this paper we propose a novel cluster-based RF fingerprinting method for outdoor user-equipment (UE) positioning using both LTE and WLAN signals. It uses a simple cost effective agglomerative hierarchical clustering with Davies-Bouldin criterion to select the optimal cluster number. The positioning method does not require training signature formation prior to UE position estimation phase. It is capable of reducing the search space for clustering operation by using LTE cell-ID searching criteria. This enables the method to estimate UE positioning in short time with less computational expense. To validate the cluster-based positioning real-time field measurements were collected using readi…

An Approach for Network Outage Detection from Drive-Testing Databases

2012

A data-mining framework for analyzing a cellular network drive testing database is described in this paper. The presented method is designed to detect sleeping base stations, network outage, and change of the dominance areas in a cognitive and self-organizing manner. The essence of the method is to find similarities between periodical network measurements and previously known outage data. For this purpose, diffusion maps dimensionality reduction and nearest neighbor data classification methods are utilized. The method is cognitive because it requires training data for the outage detection. In addition, the method is autonomous because it uses minimization of drive testing (MDT) functionalit…

Malliperustaista arkkitehtuuria tukevien CASE-välineiden arviointi- ja valintamenetelmä

2002

Predicting fruit and vegetable consumption in long-haul heavy goods vehicle drivers : application of a multi-theory, dual-phase model and the contrib…

2018

Fruit and vegetable intake is insufficient in industrialized nations and long-haul heavy goods vehicle (HGV) drivers are considered a particularly at-risk group. The aim of the current study was to test the effectiveness of a multi-theory, dual-phase model to predict fruit and vegetable consumption in Australian long-haul HGV drivers. A secondary aim was to examine the effect of past fruit and vegetable consumption on model paths. A prospective design with two waves of data collection spaced one week apart was adopted. Long-haul HGV drivers (N = 212) completed an initial survey containing theory-based measures of motivation (autonomous motivation, intention), social cognition (attitudes, su…

Piston driven yaw mechanism

2014

Masteroppgave i mekatronikk MAS 500 Universitetet i Agder 2014 The current thesis presents a piston driven yaw mechanism for wind turbines. Traditionally the yaw mechanismhas been one of the mayor contributors to down time and repair has been costly. The proposed designaims to improve the reliability of the yaw mechanism by reducing the point loads and by using hydrauliccylinders instead electrical motors to generate torque. In addition the design is modular allowing the mechanismto be disassembled and components to be replaced without the requirement of complicated or costlymachinery. The current thesis presents an analysis of the state of the art and discusses concepts which maysolve some…