Smart FRP Composite Sandwich Bridge Decks in Cold Regions

INE/AUTC 12.0

Emotions Detection based on a Single-electrode EEG Device

The study of emotions using multiple channels of EEG represents a widespread practice in the field of research related to brain computer interfaces (Brain Computer Interfaces). To date, few studies have been reported in the literature with a reduced number of channels, which when used in the detection of emotions present results that are less accurate than the rest. To detect emotions using an EEG channel and the data obtained is useful for classifying emotions with an accuracy comparable to studies in which there is a high number of channels, is of particular interest in this research framework. This article uses the Neurosky Maindwave device; which has a single electrode to acquire the EEG signal, Matlab software and IBM SPSS Modeler; which process and classify the signals respectively. The accuracy obtained in the detection of emotions in relation to the economic resources of the hardware dedicated to the acquisition of EEG signal is remarkable

Decentralized and adaptive sensor data routing

Wireless sensor network (WSN) has been attracting research efforts due to the rapidly increasing applications in military and civilian fields. An important issue in wireless sensor network is how to send information in an efficient and adaptive way. Information can be directly sent back to the base station or through a sequence of intermediate nodes. In the later case, it becomes the problem of routing. Current routing protocols can be categorized into two groups, namely table-drive (proactive) routing protocols and source-initiated on-demand (reactive) routing. For ad hoc wireless sensor network, routing protocols must deal with some unique constraints such as energy conservation, low bandwidth, high error rate and unpredictable topology, of which wired network might not possess. Thus, a routing protocol, which is energy efficient, self-adaptive and error tolerant is highly demanded. A new peer to peer (P2P) routing notion based on the theory of cellular automata has been put forward to solve this problem. We proposed two different models, namely Spin Glass (Physics) inspired model and Multi-fractal (Chemistry) inspired model. Our new routing models are distributed in computation and self-adaptive to topological disturbance. All these merits can not only save significant amount of communication and computation cost but also well adapt to the highly volatile environment of ad hoc WSN. With the cellular automata Cantor modeling tool, we implemented two dynamic link libraries (DLL) in C++ and the corresponding graphic display procedures in Tcl/tk. Results of each model’s routing ability are discussed and hopefully it will lead to new peer to peer algorithms, which can combine the advantages of current models

Kablosuz sensör ağlarinda yönlü antenlerle enerji̇ veri̇mli̇ yönlendi̇rme

Without measurements, sustainable development effort can not progress in the right direction. Wireless sensor networks are vital for monitoring in real time and making accurate measurements for such an endeavor. However small energy storage in the sensors can become a bottleneck if the wireless sensor network is not optimized at the hardware and software level. Directional antennas are such optimization technologies at the hardware level. They have advantages over the omnidirectional antennas, such as high gain, less interference, longer transmission range, and less power consumption. In wireless sensor networks, most of the energy is consumed for communication. Considering the limited energy in small scale batteries of the sensors, energy efficient (aware) routing, is one of the most important software optimization techniques. The main goal of the technique is to improve the lifetime of the wireless sensor networks. In the light of these observations, it is desirable to do a coupled design of directional antennas with network software, for fully exploiting the advantages offered by directional antenna technology. In this thesis, the possibilities of doing such integrated design are surveyed and improvements are suggested. The design of the proposed microstrip patch antenna array is discussed and the performance characteristics are assessed through simulations. In the benchmarks, the proposed routing method showed improvements in energy usage compared to the existing approaches.Ölçümler olmadan sürdürülebilir kalkınma çabaları doğru yönde ilerleyemez. Bu tür çabalar için, kablosuz sensör ağları, gerçek zamanlı olarak izleme ve kesin ölçümler yapmak için vazgeçilemez unsurdur. Ancak, sensör ağı, donanım ve yazılım düzeylerinde optimize edilmemişse, sensörlerde enerji yetersizliği görülebilinir. Yönlü antenler, donanım düzeyinde uygulanan optimizasyon teknolojilerinden biri olmakla birlikte, çok yönlü antenlerden farklı olarak, yüksek kazanç, daha az parazit, daha uzun iletim mesafesi ve daha az güç tüketimi sağlarlar. Kablosuz sensör ağlarında enerjinin çoğu iletişim için tüketilir. Sensörlerdeki limitli enerjili küçük ölçekli piller göz önüne alındığında, yazılım düzeyindeki önemli metodlardan biri olan enerji verimli (duyarlı) yönlendirme protokolü, kablosuz sensör ağının genel enerji kullanımını optimize etmek ve ömrünü uzatmak için gereklidir. Bu gözlemlerin ışığında, yönlü anten teknolojisinin sunduğu potansiyel avantajlardan tam olarak yararlanmak için, yönlü antenlerin ağ yazılımıyla birlikte entegre tasarımını yapmak arzu edilir. Bu tezde, böyle bir entegre tasarımın yapılma olasılıkları araştırılmış ve iyileştirmeler önerilmiştir. Tezde, küçük şeritli yamalı anten dizisinin tasarımı tartışılmış ve performans karakteristikleri simulasyonlarla ölçülmüştür. Önerilen yönlendirme algoritması, diğer yönlendirme algoritmaları ile karşılaştırıldığında, enerji kullanımında iyileştirmeler göstermiştirM.S. - Master of Scienc

Radio frequency channel characterization for energy harvesting in factory environments

This thesis presents ambient energy data obtained from a measurement campaign carried out at an automobile plant. At the automobile plant, ambient light, ambient temperature and ambient radio frequency were measured during the day time over two days. The measurement results showed that ambient light generated the highest DC power. For plant and operation managers at the automobile plant, the measurement data can be used in system design considerations for future energy harvesting wireless sensor nodes at the plant. In addition, wideband measurements obtained from a machine workshop are presented in this thesis. The power delay profile of the wireless channel was obtained by using a frequency domain channel sounding technique. The measurements were compared with an equivalent ray tracing model in order to validate the suitability of the commercial propagation software used in this work. Furthermore, a novel technique for mathematically recreating the time dispersion created by factory inventory in a radio frequency channel is discussed. As a wireless receiver design parameter, delay spread characterizes the amplitude and phase response of the radio channel. In wireless sensor devices, this becomes paramount, as it determines the complexity of the receiver. In reality, it is sometimes difficult to obtain full detail floor plans of factories for deterministic modelling or carry out spot measurements during building construction. As a result, radio provision may be suboptimal. The method presented in this thesis is based on 3-D fractal geometry. By employing the fractal overlaying algorithm presented, metallic objects can be placed on a floor plan so as to obtain similar radio frequency channel effects. The environment created using the fractal approach was used to estimate the amount of energy a harvesting device can accumulate in a University machine workshop space

Quantitative Mapping of Soil Property Based on Laboratory and Airborne Hyperspectral Data Using Machine Learning

Soil visible and near-infrared spectroscopy provides a non-destructive, rapid and low-cost approach to quantify various soil physical and chemical properties based on their reflectance in the spectral range of 400–2500 nm. With an increasing number of large-scale soil spectral libraries established across the world and new space-borne hyperspectral sensors, there is a need to explore methods to extract informative features from reflectance spectra and produce accurate soil spectroscopic models using machine learning. Features generated from regional or large-scale soil spectral data play a key role in the quantitative spectroscopic model for soil properties. The Land Use/Land Cover Area Frame Survey (LUCAS) soil library was used to explore PLS-derived components and fractal features generated from soil spectra in this study. The gradient-boosting method performed well when coupled with extracted features on the estimation of several soil properties. Transfer learning based on convolutional neural networks (CNNs) was proposed to make the model developed from laboratory data transferable for airborne hyperspectral data. The soil clay map was successfully derived using HyMap imagery and the fine-tuned CNN model developed from LUCAS mineral soils, as deep learning has the potential to learn transferable features that generalise from the source domain to target domain. The external environmental factors like the presence of vegetation restrain the application of imaging spectroscopy. The reflectance data can be transformed into a vegetation suppressed domain with a force invariance approach, the performance of which was evaluated in an agricultural area using CASI airborne hyperspectral data. However, the relationship between vegetation and acquired spectra is complicated, and more efforts should put on removing the effects of external factors to make the model transferable from one sensor to another.:Abstract I Kurzfassung III Table of Contents V List of Figures IX List of Tables XIII List of Abbreviations XV 1 Introduction 1 1.1 Motivation 1 1.2 Soil spectra from different platforms 2 1.3 Soil property quantification using spectral data 4 1.4 Feature representation of soil spectra 5 1.5 Objectives 6 1.6 Thesis structure 7 2 Combining Partial Least Squares and the Gradient-Boosting Method for Soil Property Retrieval Using Visible Near-Infrared Shortwave Infrared Spectra 9 2.1 Abstract 10 2.2 Introduction 10 2.3 Materials and methods 13 2.3.1 The LUCAS soil spectral library 13 2.3.2 Partial least squares algorithm 15 2.3.3 Gradient-Boosted Decision Trees 15 2.3.4 Calculation of relative variable importance 16 2.3.5 Assessment 17 2.4 Results 17 2.4.1 Overview of the spectral measurement 17 2.4.2 Results of PLS regression for the estimation of soil properties 19 2.4.3 Results of PLS-GBDT for the estimation of soil properties 21 2.4.4 Relative important variables derived from PLS regression and the gradient-boosting method 24 2.5 Discussion 28 2.5.1 Dimension reduction for high-dimensional soil spectra 28 2.5.2 GBDT for quantitative soil spectroscopic modelling 29 2.6 Conclusions 30 3 Quantitative Retrieval of Organic Soil Properties from Visible Near-Infrared Shortwave Infrared Spectroscopy Using Fractal-Based Feature Extraction 31 3.1 Abstract 32 3.2 Introduction 32 3.3 Materials and Methods 35 3.3.1 The LUCAS topsoil dataset 35 3.3.2 Fractal feature extraction method 37 3.3.3 Gradient-boosting regression model 37 3.3.4 Evaluation 41 3.4 Results 42 3.4.1 Fractal features for soil spectroscopy 42 3.4.2 Effects of different step and window size on extracted fractal features 45 3.4.3 Modelling soil properties with fractal features 47 3.4.3 Comparison with PLS regression 49 3.5 Discussion 51 3.5.1 The importance of fractal dimension for soil spectra 51 3.5.2 Modelling soil properties with fractal features 52 3.6 Conclusions 53 4 Transfer Learning for Soil Spectroscopy Based on Convolutional Neural Networks and Its Application in Soil Clay Content Mapping Using Hyperspectral Imagery 55 4.1 Abstract 55 4.2 Introduction 56 4.3 Materials and Methods 59 4.3.1 Datasets 59 4.3.2 Methods 62 4.3.3 Assessment 67 4.4 Results and Discussion 67 4.4.1 Interpretation of mineral and organic soils from LUCAS dataset 67 4.4.2 1D-CNN and spectral index for LUCAS soil clay content estimation 69 4.4.3 Application of transfer learning for soil clay content mapping using the pre-trained 1D-CNN model 72 4.4.4 Comparison between spectral index and transfer learning 74 4.4.5 Large-scale soil spectral library for digital soil mapping at the local scale using hyperspectral imagery 75 4.5 Conclusions 75 5 A Case Study of Forced Invariance Approach for Soil Salinity Estimation in Vegetation-Covered Terrain Using Airborne Hyperspectral Imagery 77 5.1 Abstract 78 5.2 Introduction 78 5.3 Materials and Methods 81 5.3.1 Study area of Zhangye Oasis 81 5.3.2 Data description 82 5.3.3 Methods 83 5.3.3 Model performance assessment 85 5.4 Results and Discussion 86 5.4.1 The correlation between NDVI and soil salinity 86 5.4.2 Vegetation suppression performance using the Forced Invariance Approach 86 5.4.3 Estimation of soil properties using airborne hyperspectral data 88 5.5 Conclusions 90 6 Conclusions and Outlook 93 Bibliography 97 Acknowledgements 11

QoE Driven Multimedia Service Schemes in Wireless Networks Resource Allocation: Evolution from Optimization, Game Theory, to Economics

In order to deal with the Quality of Experience (QoE) improvement issue in the wireless networks services. In this dissertation we first investigated the Device to Device (D2D) relaying approach in the conventional Base Station (BS) to User Equipment (UE) two entities multimedia service system. In this part, the Multiple Input Multiple Output (MIMO) technology will be implemented in the D2D communication. Furthermore, factors such as the multimedia content distribution (i.e., Quad-tree fractal image compression method), the power allocation strategy, and modulation size are jointly considered to improve the QoE performance and energy efficiency. In addition, the emerging Non-Orthogonal Multiple Access (NOMA) transmission method is becoming very popular and being considered as one of the most potential technologies for the next generation of wireless networks. For the purpose of improving the QoE of UE in the wireless multimedia service, the power allocation method and the corresponding limitations are studied in detail in the wireless system where the traditional Orthogonal Multiple Access (OMA) technology and the promising NOMA technology are compared. At last, facing the real business model in the wireless network services, where the Content Provider (CP), Wireless Carrier (WC), and UE are included, we extend on work from the conventional BS-UE two entities research model to the CP-WC-UE three entities model. More specifically, a generalized best response Smart Media Pricing (SMP) method is studied in this dissertation. In our work, the CP and WC are treated as the service provider alliance. The SMP approach and the game theory are utilized to determine the data length of UE and the data price rate determined by the CP-WC union. It is worth pointing out that the concavity of utility function is no longer necessary for seeking the game equilibrium under the proposed best response game solution. Numerical simulation results also validate the system performance improvement of our proposed transmission schemes