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PhD defense

Transcript: Relationship Between Laboratory and Field Tests in Service Life Assessment of Wood-based Materials Davor Kržišnik Introduction Introduction Laboratory vs. Field Tests Laboratory vs. Field Tests Service Life Assessment Service Life Assessment Functional Service Life Functional Service Life Exposure dose (DEd) ≤ Resistance dose (DRd) DRd = Dcrit × kwa × kinh Aesthetic Service Life Aesthetic Service Life The criterion of service life is subjective, depending on different criteria, such as colour stability of surfaces, cracks, dyeing due to the action of fungi and molds ... Wood-based Materials Wood-based materials Relationship Relationship Exposure position of wood and wood-based materials has a significant influence on moisture content. Hypothesis number 1 Publications Materials and Methods Materials and Methods Materials Methods Methods North North facing façade South South facing façade East East facing façade West West facing façade Decking Decking Stand Stand Results Conclusion Exposure position of wood and wood-based materials has a significant influence on moisture content. Improperly performed impregnation of wood with biocides does not significantly improve the service life of wood in contact and above ground exposure. Hypothesis number 2 Publications Materials and methods Materials and Methods Franja partisan hospital 2007 2012 Assessment of the decay Resistograph measurements and Retention of a wood preservative analysis Continuous monitoring of T and MC Results Results Assessment of the decay Monitoring Conclusion Improperly performed impregnation of wood with biocides does not significantly improve the service life of wood in contact and above ground exposure. Greying and blue staining of the wood surface is a continuous cyclical process. Hypothesis number 3 Publications Materials and methods Materials and methods Materials Laboratory test EN 152 test Artificial weathering In-service test Colour measurements Results Results Laboratory test In-service test In-service test Conclusion Greying and blue staining of the wood surface is a continuous cyclical process. Results obtained from field and laboratory tests are not easily comparable to one another. Hypothesis number 4 Publications Materials and methods Materials Methods Results 1st year 2nd year 3rd year 4th year 1st year 2nd year 3rd year 4th year 60 % RH prEN 16818 ±0.7000 - ±0.7999 ±0.8000 - ±0.8999 ±0.9000 - ±1.0000 ±0.7000 - ±0.7999 ±0.8000 - ±0.8999 ±0.9000 - ±1.0000 ±0.7000 - ±0.7999 ±0.8000 - ±0.8999 ±0.9000 - ±1.0000 Conclusion Results obtained from field and laboratory tests are not easily comparable to one another. Summary Summary H1: Exposure position of wood and wood-based materials has a significant influence on moisture content. H2: Improperly performed impregnation of wood with biocides does not significantly improve the service life of wood in contact and above ground exposure. H3: Greying and blue staining of the wood surface is a continuous cyclical process. H4: Results obtained from field and laboratory tests are not easily comparable to one another. Future work Future work Aesthetic Service Life * Colour modeling as a function of a climatic exposure Future work * Different laboratory tests * Different approach for correlation calculations Future work Functional Service Life

PhD Defense

Transcript: High-Dimensional Inference and Uncertainty Quantification for Object-oriented Variable Selection, Clustering and Object-oriented Analysis Approximate Bayesian Methods with Bayesian and Approximate Bayesian Methods Variable Selection Dynamic Feature Partitioning Big Variable Selection Regression Problems High-Dimensionality Big Data Streaming Data Fast Inference Quick Inferences as new data arrives Parallel computation DFP Motivation Motivation Previous Work Previous Work General Method DFP Dynamically Partition the parameters at every time point. Compute parameter estimators. Based on the partition and parameter estimators, build a pseudo-posterior distribution for posterior computation. Notation Notation From MCMC to DFP Evolution Simulations Simulations Bayesian Lasso Bayesian Lasso Partition Method Partition Results Results Spike & Lasso Spike & Lasso Partition Partition Results Bayesian Object Oriented Model BOOM High-Dimension. Multiple Objects. Objects with a structure. Joint Variable Selection. Motivation Motivation Regress scores of language dysfunction to multiple brain objects. Grey Matter map (GM). Brain connectivity network. Find Regions of Interest (ROIs). Previous Work Previous Work Model Model Simulations Simulation Settings Settings Simulation Results Results Bayesian Tensor Covariance Clustering BTC High-Dimensional, where the curse of dimensionality is instead a blessing. Clustering focus in difference in the covariance structure instead of the location. Small number of observations. Motivation Motivation Previous Work Previous Work Method Method A two step approach: First Step: Transform the observations. Second Step: Cluster the transformed objects. Picture Transformation Clustering Model Clustering Simulation Cases Cases Results 3 Competitors DEEM DTC Oracle EEG Data EEG Data

PhD Defense Presentation

Transcript: PhD Defense Presentation Advancements in Neuroscience Research Neurofeedback Applications Impactful Insights Utilizing real-time neuroimaging feedback for therapeutic interventions and cognitive enhancement. Highlighting the potential of neurofeedback in optimizing brain function and performance. Demonstrating the implications of the findings on advancing neuroscience theories and clinical applications. Open Floor for Questions Impact of Neurodegeneration Data Collection Techniques Q&A Session: Engaging Audience Groundbreaking Discoveries in Neuroscience fMRI: Functional Magnetic Resonance Imaging Advanced Signal Processing The research highlighted the grave consequences of neurodegeneration on cognitive functions and behavior, emphasizing the urgent need for novel treatment strategies and interventions. Audience participation is key for a dynamic discussion Key Discoveries Utilizing EEG and fMRI for Brain Imaging Mapping brain activity by detecting changes in blood flow. Offers detailed spatial information about brain regions involved in specific tasks. Applying sophisticated algorithms to enhance signal clarity and resolution in neuroimaging. Illustrating the role of signal processing in extracting valuable information from brain scans. Key Findings Recap Highlighting the significant findings in neural studies, shedding light on brain function and behavior correlations. Future Trends in Data Collection EEG: Electroencephalography Data Quality Assurance Neuroimaging Advancements Discussion and Debate Neural Plasticity Mechanisms Exploring innovations like wearable EEG devices and real-time fMRI for enhanced data collection. Discussing the potential of emerging technologies in advancing neuroimaging research. Implementing rigorous quality checks to maintain accuracy and reliability of neuroimaging data. Addressing common challenges and best practices in data validation. Measuring electrical activity in the brain through electrodes on the scalp. Provides insights into brain functions in real-time. Combining EEG and fMRI for comprehensive brain analysis. Enables a holistic understanding of brain function and connectivity. Interactive session where questions are welcomed Recent research revealed new insights into brain plasticity and neurodegenerative diseases. Case Studies in Neuroscience Ethics in Data Collection Neuroscience studies uncovered the intricate mechanisms behind neural plasticity, showcasing the brain's adaptive capabilities in response to stimuli and experiences. Engage in critical discourse to deepen understanding Real-world applications of EEG and fMRI in studying brain disorders. Showcases the impact of advanced imaging techniques in clinical settings. Ensuring participant confidentiality and informed consent in neuroimaging studies. Discussing ethical considerations and protocols in research practices. Summarizing the groundbreaking discoveries from the research journey in neuroscience. Big Data Analysis Processing and interpretation of large-scale neuroimaging data. Utilizing machine learning algorithms to extract meaningful insights from complex brain scans. Interpretation of Results Exploring the Background of Neuroscience Research Key Studies in Neuroscience Applying Research in Clinical Practice Impact on Patient Care Nobel Prize-Winning Discoveries Implementing findings from neuroscience research into clinical settings can revolutionize treatments and improve patient outcomes. Analyzing the implications of research findings to unravel the mysteries of the brain. Exploring groundbreaking studies that have shaped the field of neuroscience. Neuroscience research has a rich history and has significantly contributed to our understanding of the brain and behavior. Improving treatment efficacy and personalizing interventions based on neuroscientific insights to enhance patient care outcomes and quality of life. Highlighting Nobel laureates in neuroscience and their pioneering contributions to the field. Implementation Strategies Revealing Neural Pathways History of Neuroscience Studies Cognitive Function Insights Revolutionary Brain Mapping Techniques Significance of Current Neuroscientific Endeavors Developing structured protocols and guidelines for translating research discoveries into practical applications within healthcare institutions. Exploring how the research findings illuminate the intricate neural pathways in the brain. Neuroscience has evolved from classical theories to advanced technological approaches, shaping our comprehension of the intricate brain functions. Unpacking the correlation between research outcomes and cognitive functions for a deeper understanding. Exploring advanced brain mapping methods and their impact on understanding neural pathways. Modern neuroscience research aims to unravel complex brain mechanisms, offering insights into neurological disorders and cognitive processes.

PhD defense

Transcript: Lateral Steel Confined Models FRP Confined Models Generalized Moment of Area Theorem Eccentricity Overview Eccentric Model Based on Mander Equations Eccentric Model Based on Lam and Teng Equations Finite Layer Approach FRP Wrapped Circular Columns Results Results Results Confined Analysis Muguruma et al (1980) Unconfined Analysis Park et al (1987) Samaan et al (1998) Results Questions? Conclusions Wang et al (1978) Mander et al (1988) Kent and Park (1971) Saatcioglu and Razvi (1992) Cheng et al (2002) Hayder Rasheed Asad Esmaeily Hani Melhem Sutton Stephens Brett DePaola Kdot - financial sponser Blume et al (1961) Cusson and Paultre (1995) Mills and Zimmerman (1970) BEHAVIOR OF CONCRETE COLUMNS UNDER VARIOUS CONFINEMENT EFFECTS Teng et al (2009) Recommendations Harajili (2006) Young et al (1987) Soliman and Yu (1967) Generalized Moment of Area Theorem Fujii et al (1988) Sheikh and Uzumeri et al (1982) Attard and Setunge (1996) Chan (1955) ` Harries and Kharrel (2002) Toutanji (1999) Lam and Teng Model Miyauchi et al (1997) Vallenas et al (1977) Acknowledgements Lam and Teng (2003) Ahmed Abd El Fattah Mander Model Campione and Miraglia (2003)

PhD Defense Presentation

Transcript: PhD Defense Presentation Defending Research Findings Title Title Discussion Methodology Analysis Subtitle Put something fun or important here Subtitle Data Collection Give a short description of this image. Write something high-impact about this photo Interpret and analyze the implications of the research outcomes. Describe the research methods and data sources used. Wrap up your presentation quickly: Summarize each point you made Give quick call-backs so your audience remembers Make it clear this is the end Results Conclusion Title Introduction Key Findings Subtitle Research Overview Final Remarks Follow up with another point Summarize the research findings and their significance in the field. Present the main results and discoveries from the research. Provide any important context here Conclude the presentation with key takeaways and future directions. Keep your words short and punchy so your audience stays focused. You can add imagery to keep their attention where you want it.

PhD Defense

Transcript: Hitziger et al. Electro-metabolic coupling investigated with jitter invariant dictionary learning, HBM 2014. Results SNR [dB] presented by Sebastian Hitziger Bruno Torrésani Alain Rakotomamonjy template vs. random Coefficient updates = sparse coding Matching pursuit (MP) Epoching (often manually): problematic if Response onsets are unknown Responses overlap Averaging: problematic if Response latencies vary Response shape changes alternate Hitziger et al. Jitter-adaptive dictionary learning - application to multi-trial neuroelectric signals, ICLR 2013. Collaborators Compared techniques Contiguous AWL from http://jonlieffmd.com Invited guest Main contributions Single long signal Multiple occurrences (overlaps) Variable latencies and durations Implementation: MP (detection) MC-Spike/AD-Spike Lasso problem maximal spiking potential Statistical independence of components Combine previous models Evaluation Stepwise activation using LARS Every step: ensure uniqueness (and non-negativity) AD-Spike/MC-Spike benefit from relearning bad template Difficult to know a priori Hierarchical approach Task-dependent stopping criterion Large noise levels (background activity) No ground truth -> Adequate modeling -> Statistical learning from data Epoching + averaging too simplistic Signal variability (amplitudes, latencies, wave shapes) Complex data (multi-channel, multi-trial, multi-modal) CBF activity around 1 Hz (respiration) Local spiking rates (LSR) match CBF activity Spikes synchronize, phase-locked to CBF rhythm Examiners Short epochs/trials Uniqueness constraint Jitter compensation Implementation: LARS General model Generic algorithm Coefficient updates High spiking activity = high CBF level MC-Spike Detection step Reviewers time to previous spike [s] Use matching pursuit Ensure minimal distance constraint Sandrine Saillet Alexandre Gramfort Christian G. Bénar Bruno Torrésani Tallon-Baudry and Bertrand (1999) Each method addresses only one type of variability Laure Blanc-Féraud Christian G. Bénar Coefficients provide clustering Spike-to-spike distances correlate with spike energies Number of waveforms No epoching Multiple responses Sparsity of components 6) Conclusion Processing full LFP recording Dynamic time warping Speech processing (Itakura, 1975; Sakoe and Chiba, 1971, 1978) Event-related potentials (Picton et al., 1988) Latency compensation Multi-component models Time-frequency representations frequency [Hz] Summation of electromagnetic fields Alternate minimization Woody (1967) Weighted average over isolated spikes Normalization + alignment of peaks Advisors No individual CBF response visible Non-linear summation of responses Overlapping effects: epoching problematic Multi-class spike learning (no dilations) Hierarchical structure, start with alternate Maximizes variance Orthogonality between components Shortcomings No explicit modeling of temporal variability Create dictionary Dictionary learning (DL): http://biomedicalengineering.yolasite.com/neurons.php Hitziger et al. Adaptive waveform learning - application to single- and multi-modal neurological data, in preparation. Adaptive waveform learning (AWL) The general model Jung et al. (2000) 3) Adaptive Waveform Learning (AWL) Using noisy spike template Rescaling of time axis Representations in Fourier or wavelet bases Meaningful representations: time-frequency Complex values: separate phase and amplitude Finite set : discretization of "variability space" Sum over p: multiple occurrences per waveform PhD Defense April 14, 2015 Fast Spiking Rates Coefficients Waveform updates 1) Neural Activity in the Brain 4) Epoched AWL Spikes well isolated Clear CBF response after each spike Modeling the Variability of Electrical Activity in the Brain LFP-CBF recording Within ANR project Multimodel Recording in 6 anesthetized rats with bicuculline injection (epilepsy model) Goal: develop/evaluate models explaining parameter couplings Realigned average for every waveform Normalization + centering Discussion E-AWL specialization Insightful representations Clear artifact separation Comparison to PCA, ICA, template matching Deformations of signal components Coefficient updates Convex problem Solve sequentially for each : generalized averaging Normalization + centering Essentially averaging Choice of right basis Multi-channel extension (preliminary results Papageorgakis, 2014) Different specializations/applications (MEG, detect sleep spindles, ...) More general deformations (e.g., dynamic time warping) Time frequency version Hemodynamic coupling more studies needed Interneuronal communication S. Hitziger, M. Clerc, S. Saillet, A. Gramfort, C. Bénar, T. Papadopoulo. Electro-metabolic coupling investigated with jitter invariant dictionary learning, International Human Brain Mapping Conference (HBM), 2014. S. Hitziger, M. Clerc, S. Saillet, A. Gramfort, C. Bénar, T. Papadopoulo. Jitter-adaptive dictionary learning - application to multi-trial neuroelectric signals, International

PhD defense

Transcript: The problem to be addressed is to perform 3D data registration of an object within a scene using a network of cameras and inertial sensors. Top view Motivations 'Height' indicates the error in the height measuring process (input), shown in cm X, Y and Z are the elements of t vector (output), shown in cm Performing 3D data registration and scene reconstruction using a set of planar images is still one of the key challenges of computer vision. Average processing times in ms for different size of inertial planes. Infinite homography is used to construct image plane of virtual camera. Homography is used to project virtual images onto Euclidean planes in the scene. A person within the scene is being observed by three cameras Extrinsic Parameters Among Cameras A network of cameras, whose usage and ubiquitousness have been increasing in the last decade, can provide such planar images from different views of the scene. x and y indicate the errors in image correspondences (input), shown in pixel X, Y and Z are the elements of t vector (output), shown in cm 3D reconstruction is obtained by stacking several inertial planes Architecture Modelization of Uncertainties Recently, IS has been becoming much cheaper and more available so that nowadays most smart-phones are equipped in both IS and camera sensors. 3D earth cardinal orientation (North-East-Down) is one of the outputs of an IS. Keeping the intersection of shadows The yellow parts are implemented on GPU How can we benefit from having a network of IS and camera couples, for the purpose of 3D data registration? Extension to a network IS' noise is assumed by what is provided by the manufacturer X, Y and Z are the elements of t vector, shown in cm Data of 3rd camera-IS couple 2D images Each point on a virtual image plane conveys an uncertainty due to IS noise Each projected point onto an inertial plane in the scene conveys some uncertainties due to IS noise plus translation vector's noise Having a model of such uncertainties is of importance in fusion stage of the points projected from different cameras and moreover for a further application which will use the final registered points We used statistical geometry to modelized Problem Statement Considering each camera as a light projector, there will appear three shadows on inertial plane 3D orientations 3D reconstruction of the person A set of camera-IS couples can be used to cover the scene from different views PDF (Probability Distribution Function) of results (estimated t) Translation recovery Volumetric reconstruction of a scene normally is a heavy process and time consuming We developed a real-time algorithm using CUDA enabled GP-GPU. Data of 1st camera-IS couple Data of 2nd camera-IS couple It provides the cross-section of the inertial plane with the object. Two arbitrary points in the scene are selected. Their height w.r.p. one camera is measured. The translation t is estimated. Among the extrinsic parameters among two cameras, namely rotation R and translation t, the R is already relaxed once we used the concept of virtual cameras. What remains is t, for which an effective method is introduced to recover. t = f(the height of two arbitrary points w.r.t. one camera, image correspondences) Target applications: Surveillance, human behaviour modelling, virtual-reality, smart-room, health-care, games, teleconferencing, human-robot interaction, medical industries, and scene and object understanding. Average processing times in ms for different number of inertial planes. Illustrative example Real-time implementation using GP-GPU Overall view The certainty of the proposed method has been empirically in three different impacts: Noise of IS 3D observation Heights measurement errors Extraction of image correspondences Geometry behind 3D orientation of IS is fused with 2D image to provide an earth-aligned virtual camera. The orientation is used to virtually generate a set of Euclidean planes in the scene. The 3D data registration is obtained by projection of virtual images onto the Euclidean planes.

PhD defense

Transcript: THEORETICAL INQUIRY OF A 3D ANALYTICAL FRAMEWORK FOR THE ASSESSMENT AND EXPLORATION OF THE EUROPEAN MIGRATION SYSTEM Živka Deleva, PhD candidate Research goal: The goal of this thesis is to propose an analytical framework for exploring and assessing the European migration system. Chapter 2: What are the criteria that would allow for better exploration and assessment of an international migration system? Chapter 3: What are the criteria that would allow for better exploration and assessment of an international migration system? Chapter 4: -How can we characterize the European migration system? -What justifies the multidimensional division of the European migration system? -How the criteria are set and what are their implications in hypothesised systems? Main hypothesis: The European migration system can be assessed and explored taking different criteria as variables, thus allowing for the development of a multidimensional analytical framework i.e. the results achieved could only contribute to a thorough understanding of the EMS if the set of model-indicators is consistent and could be tested in each of the developed dimensions. Goal and unit of analysis: The existing EU policy on migration, local policies, the theoretical background on international migration and migration experiences in Europe Analytical framework: Deconstruct the theoretical approaches to achieve levels on which migration occurs Identification of actors to be involved: The EU, Schengen area, nation-states, capital cities, migration networks, the TCN, International organizations, Multinational companies Describe the main dimensions of the evaluation (subject of modification) - Transnational Union - Capital cities networks - International organizations and multinational companies Indicators for each of the dimensions 1. Identify the reason for migrating: a) economic b) study c) family reunification d) refugee/asylum e) other 2. Classify the regulations that determine status 3. Determine the roots of the immigrant 4. Identify if migration networks play important role in the dimension 5. Identify the extent to which the immigrant engages in transnational behaviour/movement and the role of the Diaspora in the home country 6. Determine the possibility for citizenship acquisition and the importance of holding the host citizenship alongside the national 7. Identify whether relations (emotional, legal, etc.) are established with the nation-state or on more local leve 8. Difference between the status of ethnic minorities and immigrants, appearance of racism against the immigrants vs. the recognized ethnic minorities 1. As long as the nation-states do not impose a strict policy on holding accounts for the size and measure of third country nationals present in the territory, the Transnational Union will not manifest plausible migration policy development. 2. If policy makers oversee the transnational behaviour of the third country nationals danger exists that the policy created would be marked by its support of exclusion and will drive towards the creation of ethnic minorities. 3. Without the unification of the regulation on citizenship acquisition a policy developed for the purposes of the whole territory will amount in the inability to regulate the flow of new immigrants and distinct them from the ones that have settled already. 4. As long as the nation-states and national politics rule out the possibility of adjusting and admitting that immigration is necessary in the solution of the rise of the population, further on, that immigration will contribute in diminishing the lack of work power and also stabilize the economy, and as long as they do not accept that in order to achieve this, diligent steps need to be developed over time, the policy developed in the Transnational Union will not suffice in its executive powers and will not achieve any particular results. 1. Achieving convergence among local, national and supranational policies should start with broadening the competences of the local government in regulating immigration. 2. Will immigrants feel and identify themselves as the citizens of the nation or of their immediate environment? 1. The international organizations and multinational companies having the competences and power to influence the world executing their policies and action plans for development would represent a settlement for the immigrant which would circle around all national, regional and local policies. 2. Citizenship acquisition in this dimension will not influence the integration process in the position of interest for the third country national, as well as for the one pertaining to keep him/her there. 3. TCNs identified in this position have individually decided to migrate and have been granted the working permit settled from the human resources at the company or organization that hired them. They are the one that will fully develop their transnational identities while maintaining working status in the EU and the Schengen

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