Analysis of terrestrial laser scanning technology for structural

Monitoring displacements and deformations of anthropogenic spatial structures and objects represents\ud one of the most intricate areas in geodetic surveying. Besides the measurement technologies\ud that have been traditionally used for such tasks, terrestrial laser scanning represents another possibility\ud employing the surface-wise deformation inspection of the objects’ surfaces. The main aim of\ud the thesis is to try to provide answers whether terrestrial laser scanning can be used for monitoring\ud displacements and deformations in a long-term perspective and how this could be achieved for any\ud arbitrary surface. Furthermore, the hypothesis will be challenged with the statement that the deformation\ud inspection can be performed in the millimeter domain with this remote sensing measurement\ud technology. In order to solve the problem of a stable reference system and to assure the high quality\ud of possible position changes of point clouds, scanning is integrated with two complementary\ud surveying techniques, i.e., high quality static GNSS positioning and precise classical terrestrial surveying.\ud The methodology of such high precision monitoring approach is proposed in the thesis and\ud was tested in two case study outdoor experiments. Besides these two outdoor experiments, also indoor\ud tests were designed to evaluate the quality of the surveying equipment (laser scanning targets)\ud as well as the response of the scanner to the surface material

Analysis and Use of MapReduce for Recommender Systems

MapReduce je programski model, namenjen za razvoj skalabilnih paralelnih aplikacij za obdelavo velikih množic podatkov, izvajalno okolje, ki podpira programski model in koordinira izvajanje programov, in implementacija programskega modela in izvajalnega okolja. Cilj diplomskega dela je analizirati MapReduce in ga preizkusiti na dveh primerih priporočilnih sistemov. Cilj smo dosegli, saj smo uspeli realizirati izračun s pomočjo MapReduce na testnih primerih. Najprej smo analizirali programski model in izvajalno okolje ter primerjali tri implementacije MapReduce: Hadoop MapReduce, MongoDB in knjižnico MapReduce-MPI. Ugotovili smo, da je za realizacijo izbranih primerov priporočilnih sistemov najprimernejša implementacija Hadoop MapReduce, saj nudi toleranco za okvare in reproducira podatke, s čimer zagotavlja zanesljivost. Nato smo z uporabo navidezne naprave Cloudera QuickStart VM, ki je gruča Hadoop z enim vozliščem, realizirali izbrana primera priporočilnih sistemov.MapReduce is a programming model for developing scalable parallel applications for processing large data sets, an execution framework that supports the programming model and coordinates the execution of programs and an implementation of the programming model and the execution framework. The goal of the thesis is to analyse MapReduce and to use it on two examples of recommender systems. The goal is achieved by developing the computation with MapReduce successfully. At first the programming model and the execution framework are analysed and three implementations for MapReduce: Hadoop MapReduce, MongoDB and MapReduce-MPI Library are compared. It is discovered that Hadoop MapReduce is the most suitable implementation for developing the selected examples of recommender systems as it provides fault tolerance and data reproduction which ensure reliability. Then the selected examples of recommender systems are developed using Cloudera QuickStart VM which is a one node Hadoop cluster

Prediction of the peak shear strength of the rock joints with artificial neural networks

With the development of computer technology, artificial neural networks are becoming increasingly useful in the field of engineering geology and geotechnics. With artificial neural networks, the geomechanical properties of rocks or their behaviour could be predicted under different stress conditions. Slope failures or underground excavations in rocks mostly occurred through joints, which are essential for the stability of geotechnical structures. This is why the peak shear strength of a rock joint is the most important parameter for a rock mass stability. Testing of the shear characteristics of joints is often time consuming and suitable specimens for testing are difficult to obtain during the research phase. The roughness of the joint surface, tensile strength and vertical load have a great influence on the peak shear strength of the rock joint. In the presented paper, the surface roughness of joints was measured with a photogrammetric scanner, and the peak shear strength was determined by the Robertson direct shear test. Based on six input characteristics of the rock joints, the artificial neural network, using a backpropagation learning algorithm, successfully learned to predict the peak shear strength of the rock joint. The trained artificial neural network predicted the peak shear strength for similar lithological and geological conditions with average estimation error of 6 %. The results of the calculation with artificial neural networks were compared with the Grasselli experimental model, which showed a higher error in comparison with the artificial neural network model

Use of Terrestrial Laser Scanning Technology for Long Term High Precision Deformation Monitoring

The paper presents a new methodology for high precision monitoring of deformations with a long term perspective using terrestrial laser scanning technology. In order to solve the problem of a stable reference system and to assure the high quality of possible position changes of point clouds, scanning is integrated with two complementary surveying techniques, i.e., high quality static GNSS positioning and precise tacheometry. The case study object where the proposed methodology was tested is a high pressure underground pipeline situated in an area which is geologically unstable

Ultrasensitive Label-Free Detection of Protein-Membrane Interaction Exemplified by Toxin-Liposome Insertion.

Measuring the high-affinity binding of proteins to liposome membranes remains a challenge. Here, we show an ultrasensitive and direct detection of protein binding to liposome membranes using high throughput second harmonic scattering (SHS). Perfringolysin O (PFO), a pore-forming toxin, with a highly membrane selective insertion into cholesterol-rich membranes is used. PFO inserts only into liposomes with a cholesterol concentration >30%. Twenty mole-percent cholesterol results in neither SHS-signal deviation nor pore formation as seen by cryo-electron microscopy of PFO and liposomes. PFO inserts into cholesterol-rich membranes of large unilamellar vesicles in an aqueous solution with Kd = (1.5 ± 0.2) × 10-12 M. Our results demonstrate a promising approach to probe protein-membrane interactions below sub-picomolar concentrations in a label-free and noninvasive manner on 3D systems. More importantly, the volume of protein sample is ultrasmall (<10 μL). These findings enable the detection of low-abundance proteins and their interaction with membranes

Evaluation of High-Precision Sensors in Structural Monitoring

One of the most intricate branches of metrology involves the monitoring of displacements and deformations of natural and anthropogenic structures under environmental forces, such as tidal or tectonic phenomena, or ground water level changes. Technological progress has changed the measurement process, and steadily increasing accuracy requirements have led to the continued development of new measuring instruments. The adoption of an appropriate measurement strategy, with proper instruments suited for the characteristics of the observed structure and its environmental conditions, is of high priority in the planning of deformation monitoring processes. This paper describes the use of precise digital inclination sensors in continuous monitoring of structural deformations. The topic is treated from two viewpoints: (i) evaluation of the performance of inclination sensors by comparing them to static and continuous GPS observations in deformation monitoring and (ii) providing a strategy for analyzing the structural deformations. The movements of two case study objects, a tall building and a geodetic monument in Istanbul, were separately monitored using dual-axes micro-radian precision inclination sensors (inclinometers) and GPS. The time series of continuous deformation observations were analyzed using the Least Squares Spectral Analysis Technique (LSSA). Overall, the inclinometers showed good performance for continuous monitoring of structural displacements, even at the sub-millimeter level. Static GPS observations remained insufficient for resolving the deformations to the sub-centimeter level due to the errors that affect GPS signals. With the accuracy advantage of inclination sensors, their use with GPS provides more detailed investigation of deformation phenomena. Using inclinometers and GPS is helpful to be able to identify the components of structural responses to the natural forces as static, quasi-static, or resonant

Analysis of terrestrial laser scanning technology for structural deformation monitoring

Spremljanje premikov in deformacij antropogenih prostorskih struktur in objektov predstavlja eno izmed najbolj zahtevnih področij v geodeziji. Poleg merskih tehnologij, ki se tradicionalno uporabljajo za izvedbo takšnih nalog, predstavlja terestrično lasersko skeniranje dodatno možnost ploskovnega načina analiziranja objektnih površin. Glavni cilj doktorske naloge je v zagotovitvi odgovorov o možnostih uporabe terestričnega laserskega skeniranja za dolgoročno spremljanje premikov in deformacij ter o načinu izvedbe takšne oblike spremljave na poljubnih objektih. Poleg tega bo v okviru naloge ovrednotena hipoteza, da lahko s pomočjo te tehnologije daljinskega zaznavanja k analizi deformacij pristopimo v območju milimetrov. Za rešitev problema stabilnega referenčnega sistema, ki pogojuje visoko kakovostno analiziranje morebitnih sprememb položajev oblakov točk, je skeniranje treba povezati z ostalimi geodetskimi tehnikami, tj. zelo natančno statično izmero GNSS in precizno klasično terestrično izmero. Naloga predlaga metodologijo takšnega zelo natančnega načina spremljanja, ki je bila preizkušena v okviru dveh testov v naravi. Poleg teh dveh testov so bili za potrebe naloge zasnovani tudi testi za preverjanje kakovosti uporabljene merske opreme (tarč laserskega skeniranja) in odzivnosti skenerja na lastnosti površinskega materiala..Monitoring displacements and deformations of anthropogenic spatial structures and objects represents one of the most intricate areas in geodetic surveying. Besides the measurement technologies that have been traditionally used for such tasks, terrestrial laser scanning represents another possibility employing the surface-wise deformation inspection of the objects’ surfaces. The main aim of the thesis is to try to provide answers whether terrestrial laser scanning can be used for monitoring displacements and deformations in a long-term perspective and how this could be achieved for any arbitrary surface. Furthermore, the hypothesis will be challenged with the statement that the deformation inspection can be performed in the millimeter domain with this remote sensing measurement technology. In order to solve the problem of a stable reference system and to assure the high quality of possible position changes of point clouds, scanning is integrated with two complementary surveying techniques, i.e., high quality static GNSS positioning and precise classical terrestrial surveying. The methodology of such high precision monitoring approach is proposed in the thesis and was tested in two case study outdoor experiments. Besides these two outdoor experiments, also indoor tests were designed to evaluate the quality of the surveying equipment (laser scanning targets) as well as the response of the scanner to the surface material

Model za oceno dolžine koraka z inercijskimi senzorji

Pedestrian dead reckoning (PDR) using inertial sensors has paved the way for developing several approaches to step length estimation. In particular, emerging step length estimation models are readily available to be utilized on smartphones, yet they are seldom formulated considering the kinematics of the human body during walking in combination with measured step lengths. Besides, there is an absence of performance evaluation protocols when dealing with the analysis and comparison of the models. The main scientific contributions of this doctoral dissertation encompass a new approach to performance evaluation of the models and two improved inertial-sensor-based step length estimation models that estimated step length more accurately than related models selected for comparison. Both models were designed considering measured stride lengths and kinematics of the human body during walking. We present two step length estimation models herein. The first model utilizes acceleration magnitude as the predominant input, whereas the second model also includes step frequency. To the best of our knowledge, we were the first to employ principal component analysis and canonical correlation analysis to characterize the acquired experimental data that included spatial positions of anatomical landmarks on the human body during walking, tracked by an optical measurement system. We evaluated the performance of the proposed models for four common smartphone positions and walking on a treadmill and a rectangular-shaped test polygon. Both models yielded promising results, i.e., overall mean absolute stride length estimation errors of 6.44 cm and 5.64 cm, respectively. On average, the first model achieved a mean absolute error (MAE) of stride length estimation approximately 27% less than the average MAEs produced by the related models included in the comparison. Whereas the second model achieved an MAE of stride length estimation approximately 26% less than the MAEs of the related models included in the comparison on average. Both models are unaffected by smartphone orientation, having the advantage that no special care regarding orientation being needed when attaching the smartphone to a particular body segment. Due to promising results and favorable characteristics, both models could present an appealing alternative for step length estimation in PDR-based approaches. During this research, we also started setting the basis for standardizing the performance evaluation procedure by dealing with an in-depth analysis and comparison of step length estimation models, proposing the following categories of models: step-frequency-based, acceleration-based, angle-based, and multiparameter. Furthermore, we investigated the evaluation approaches of step length estimation models and extracted the evaluation guidelines considering several criteria. In the scope of this work, we also established an open benchmark repository including over 70 km of gait measurements obtained from a group of healthy adults. This repository fosters the comparability of the evaluation results and simplifies the benchmarking of new models. To the best of our knowledge, we were the first to introduce this way of comparison of the models, which has the potential to become a generalized and accepted way of evaluating and comparing performances of step length estimation models.Računska navigacija z inercijskimi senzorji uporablja številne pristope za oceno dolžine koraka, zlasti modele, ki so namenjeni oceni dolžine koraka na pametnih telefonih. Vendar pa avtorji modelov pri njihovi zasnovi redko uporabijo izmerjene dolžine korakov in kinematiko človeškega telesa med hojo. Prav tako ni uveljavljenega protokola za ovrednotenje modelov, kar še posebej pride do izraza pri njihovi analizi in primerjavi. Glavni znanstveno raziskovalni doprinosi te doktorske disertacije zajemajo nov pristop za ovrednotenje modelov ter dva nova izboljšana modela za oceno dolžine koraka z inercijskimi senzorji, ki dosegata boljše rezultate od primerljivih modelov ter sta zasnovana upoštevajoč izmerjene dolžine ciklov korakov in kinematiko gibanja človeškega telesa med hojo. Prvi predlagani model temelji na magnitudi pospeška, drugi pa na magnitudi pospeška in frekvenci korakov. Za karakterizacijo zbranih eksperimentalnih podatkov pri izpeljavi modelov smo kot prvi uporabili analizo glavnih komponent in kanonično korelacijsko analizo, pri čemer smo se osredotočili na prostorske položaje referenčnih točk na človeškem telesu med hojo, ki jih je spremljal optični merilni sistem. Predlagana modela smo ovrednotili za štiri tipične položaje pametnega telefona ter hojo po tekalni stezi in pravokotnem testnem poligonu. Oba modela sta dosegla obetavne rezultate. Skupna povprečna absolutna napaka ocene dolžine ciklov korakov je znašala 6.44 cm za prvi model oziroma 5.64 cm za drugi model. Prvi model je na enaki množici podatkov v povprečju dosegel približno 27% manjšo skupno povprečno absolutno napako ocene dolžine ciklov korakov kot modeli, ki smo jih vključili v njegovo primerjalno analizo. Drugi model pa je v povprečju dosegel približno 26% manjšo skupno povprečno absolutno napako ocene dolžine ciklov korakov kot modeli, ki smo jih vključili v njegovo primerjalno analizo. Posledično predlagana modela predstavljata atraktivno alternativo za oceno dolžine koraka pri računski navigaciji, saj orientacija pametnega telefona na njiju ne vpliva in zato ni potrebno posebne pozornosti nameniti usmerjenosti pametnega telefona pri namestitvi na določen del telesa, kar predstavlja pomembno prednost v primerjavi s številnimi drugimi modeli. Med to raziskavo smo začeli postavljati tudi osnove za standardizacijo ovrednotenja modelov za oceno dolžine koraka. Na podlagi poglobljene analize in primerjave smo predlagali nove kategorije modelov: modeli, zasnovani na frekvenci koraka, modeli, zasnovani na pospešku, modeli, zasnovani na kotu, in multiparametrični modeli. Poleg tega smo raziskali obstoječe pristope ovrednotenja modelov za oceno dolžine koraka in izluščili smernice za ovrednotenje ob upoštevanju več kriterijev. V okviru tega dela smo za primerjavo vzpostavili javno dostopen referenčni repozitorij z več kot 70 km meritev hoje zdravih odraslih oseb. Ta repozitorij spodbuja primerljivost rezultatov ovrednotenja in poenostavlja primerjalno analizo novih modelov. Kot prvi smo začeli z aktivnostmi za vzpostavitev takega načina primerjave, ki ima potencial, da postane splošno sprejet način za ovrednotenje in primerjavo performans modelov za oceno dolžine koraka