Sonderkolloquium (Mawi) von Jochen Schmitt, Analog Devices International

Kolloquium (Mawi) von Prof. Lutz Mädler, Universität Bremen

Kolloquium (INF) Prof. Dr. Petchporn Chawakitchareon, Environmental Engineering Department, Chulalongkorn University Bangkok

09.04.2019 von 17:00 bis 18:30

Water Quality Index Analysis and Prediction

Artificial neural network is a common method which has been used in many
data science projects. This talk presents a comparison of prediction
methods for water quality indexes using for classifying the water
quality in rivers or canals. We compare data analysis and data mining
results that can be obtained on the basis of full data records obtained
in Thailand for the decade 2007-2017. Special attention is directed
towards M5P, M5Rules and REPTree analysis algorithms compared to results
from multilayer perceptron - one type of artificial neural network. Our
experimental results show that the REPTree method yielded the highest
accuracy to predict Water quality indexes comparing to other methods.
For M5P and M5Rules, building models by using smoothing procedures and
unpruned techniques appears to give out the best model to predict with
the highest accuracy.

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Thermal stability and diffusion phenomena in metal/semiconductor superlattice thin films observed by aberrationcorredted TEM-methods at atomic resolution

Medical diagnosis aided by automatic classification: Non-blackbox approaches for clinical voice assessment

06.05.2019 von 16:00 bis 17:30

Voice disorders are socially relevant, because they may lead to significant follow-up costs for health insurances and the economic system, if no adequate treatment is administered timely. Voice quality characterization is pivotal to the clinical care of voice disorders, because it aids the indication, selection, evaluation, and optimization of clinical treatment techniques, including speech therapy by administered by logopedists / speech language pathologists, and phonosurgery, performed by medical doctors specialized on voice disorders.

Current approaches to artificial intelligence, including (Deep) Neural Networks, are not fully accepted by clinical experts, partly due to their black box nature. In particular, explanatory power of these approaches is low. In contrast, we propose to use hand-crafted model based features as input to low-dimensional classification automats. Our features are meant to represent closely the properties of the voice, which are described on the level of voice production, on the level of acoustics, and on the level of perception.

Diplophonia is a particular type of pathological voice qualities, in which two simultaneous pitches are reported by clinical experts to be audible simultaneously. Diplophonia may be a symptom of a vocal dysfunction that needs medical treatment. The inherently subjective definition located on the domain of auditory perception is complemented by our approaches to track two simultaneous fundamental frequencies from high-speed videos of the vocal folds, and from audio signals. Also, first steps with a physiologically grounded hearing model are presented. The hearing model is used to predict from decomposed audio signals of the voice the presence of two simultaneously perceivable pitches.

 

Short bio:

Philipp Aichinger is a Research Associate of the Medical University of Vienna (MUV). He is affiliated with the Department of Otorhinolaryngology, Division of Phoniatrics-Logopedics. He graduated interdisciplinary studies in Electrical Engineering/Sound Engineering at the Graz University of Technology (TUG) and the University of Music and Dramatic Arts in Graz (KUG), acquiring expertise both in engineering and in music/perception research. His PhD-thesis "Diplophonic Voice - Definitions, models, and detection" has been supervised by the TUG and the MUV. Philipp is Principal InvestigPhillip Aichingerator of a research project FWF KLI722-B30 funded within the Program Clinical Research of the Austrian Science Fund (FWF), entitled “Objective differentiation of dysphonic voice quality types”. He is an organizer of the 2019 Special Session at Interspeech, entitled “Voice quality characterization for clinical voice assessment: Voice production, acoustics, and auditory perception”. He is a member of the IEEE Signal Processing Society, the Audio Engineering Society, and the Acoustical Society of America. He is reviewer for the Journal of the Acoustical Society of America, for the IEEE Transactions on Audio, Speech and Language Processing, for the Journal of Medical and Biological Engineering, for the Journal Biomedical Signal Processing and Control, and for Acta Acustica united with Acustica.

 

 

 

 

 

 

 

 

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Organic and bio-organic electronic devices

03.05.2019 von 13:00 bis 14:30

Organic electronic devices are maturing from the academic research into the industrial development, entering the markets. In order to account for a sustainable future, the application of biodegradable and biocompatible systems for organic optoelectronics are needed. The use of cheap electronic devices in a large scale will introduce a “consumable electronics” into the market of “consumer electronics”. Therefore environmentally friendly materials are important to use. This is a next great challenge to material science in organic electronics. New developments of bio-inspired and/or bio-origin, bio-compatible materials are interesting. Such materials can also be used to interface the biological and biomedical research with the organic electronics field.

 

Last but not least the conversion of CO2 to methane (or other synthetic fuels) using solar energy is an important step to make an efficient, large scale energy storage.  At the same time this will make a cyclic and sustainable CO2 economy. We report organic as well as bio-organic catalysts which can be used in photo-electro-catalytic conversion devices. Such bio-catalysts can be enzymes as well as living bacteria immobilized on electrodes. Selectivity of such bio-catalysts is very high and combined with the room temperature operation of such bio-electro-catalytic systems makes them industrially highly attractive.

 

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Activity Sensing and Localization in Indoor Enviroments

24.05.2019 von 14:00 bis 14:45

Sensing people and mobile objects in indoor environments are key
building blocks of many smart building applications. In this talk, I
will share some recent results from my research in indoor localization
and people sensing in buildings. We have developed new ways to use
ultra sonic sensing to count and track people in buildings while
ensuring privacy. We have made ultra-wide band radio based indoor
localization more accurate, efficient, and scalable. I will also
describe what we learned from evaluating these approaches on long and
short-term deployments in buildings and on testbeds.

Speaker Bio

Omprakash Gnawali is an Associate Professor at the Computer Science
Department of the University of Houston. He does research on IoT, with
a focus on wireless and sensing technologies. Other areas of interest
include cybersecurity, data analytics, mobile systems, and technology
for the emerging markets. He received his SB and MEng from MIT, PhD
from USC, and was a postdoc at Stanford.

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All-optical magnetization switching in spin-valve structures mediated by spin-polarized hot electron transport

Broadband Ferromagnetic Resonance Spectroscopy: The “Swiss Army Knife” for Understanding Spin-Orbit Phenomena

Neuromorphic control

27.05.2019 von 14:15 bis 15:00

Neurophysiological circuits exhibit control properties unparalleled in man-made control systems. They combine sensitivity to the tiny and robustness to the large in an astonishing way, seemingly  paradoxical. They form control systems across scales, allowing sensing and actuation from the molecular scale up to the whole body scale. This talk will explore some of the basic feedback principles that allow for such properties. In particular, I will emphasize the key role of mixed feedback, which involves a  combination of positive and negative feedback, or excitation and inhibition, at every scale. I will then discuss the possibility of implementing such properties in neuromorphic circuits and discuss the potential of neuromorphic control in engineering.
 

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Near infrared fluorescent materials and sensors for biomedical applications

03.06.2019 um 16:00 bis 03.07.2019 um 17:00

In our research we investigate and create functional (nano)materials for biomedical applications. We are especially interested in 1D and 2D materials that provide novel photophysical properties such as near Infrared (nIR) fluorescence. The nIR range (800-1700 nm) of the spectrum is beneficial for optical applications because it falls into the tissue transparency window. One example of such a material are semiconducting single-walled carbon nanotubes (SWCNTs). SWCNTs fluoresce in the nIR and their optoelectronic properties are very sensitive to changes in the chemical environment and they are therefore versatile building blocks for biosensors. In my talk I will cover the following current research topics of my group:

1)    I will show fundamental insights into SWCNT photophysics and how capabilities of SWCNT-based fluorescent sensors can be enhanced. SWCNTs were for example conjugated to nanobodies that can be targeted in vivo to any Green Fluorescent Protein (GFP) moiety. These SWCNTs were used for single-particle tracking and microrheology measurements in living drosophila embryos.

2)    The corona phase around SWCNTs was tailored to enhance selectivity and photophysics of SWCNT-based sensors for the important neurotransmitters dopamine and serotonine. These sensors can be used to image neurotransmitter efflux from neuronal cells and blood cells.

3)    We introduce a novel class of 2D nIR fluorescent silicate nanosheets, characterize their photophysical properties as a function of their dimensionality and use them for in vivo particle tracking as well as standoff detection in living plants.

4)    Immune cells were used for programmed transport and release of nanoscale cargo. The cells take up SWCNT-based sensors, transport them and release them again.

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Revealing novel power laws and quantization in electrospinning considering jet splitting – towards predicting fiber diameter and its distribution

Evolutionary Computing for Problems with Dynamically Changing Constraints

08.07.2019 von 11:00 bis 12:00

Dynamic problems appear frequently in real-world applications such as
logistics for mining and are usually subject to a large set of
constraints. These constraints change over time due to changes in
resources and having algorithms that can deal with such dynamic changes
delivers direct benefit to decision makers. Evolutionary algorithms are
well suited for such dynamic problems as they can easily adapt to
changing environments. In this talk, I will report on some theoretical
and experimental investigations that we have carried out in the area of
evolutionary algorithms for problems with dynamic constraints. The focus
will be the classical knapsack problem and constrained submodular
functions where the given constraint bound changes over time.

Based on:

-V. Roostapour, A. Neumann, F. Neumann (2018): On the performance of
baseline evolutionary algorithms on the dynamic knapsack problem.
In: Parallel Problem Solving from Nature XV, PPSN 2018.

-V. Roostapour, A. Neumann, F. Neumann, T. Friedrich (2019): Pareto
optimization for subset selection with dynamic cost constraints.
In: Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019.

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Direct water splitting by surface-conditioned n-GaP (100) photoanodes

12.06.2019 von 13:00 bis 14:00

Abstract

III-V semiconductors are candidates for photoelectrochemical (PEC) water splitting but they are prone to corrosion and suffer from corrosion-related decrease of efficiency. Gallium phosphide (GaP) has an indirect band gap of 2.26 eV which covers both the hydrogen evolution potential (HEP) and the oxygen evolution potential (OEP). Thus, in principle, GaP can be used as photocathode and photoanode. We have studied the structural and chemical surface modifications of n-GaP(100) photoanodes before and after extended PEC treatment by scanning electron microscopy (SEM), atomic force microscopy (AFM), Auger electron spectroscopy (AES) and X-ray photoelectron spectroscopy (XPS). A 2±0.5 nm thin stable oxide film is produced at the surface of n-GaP(100) photoanode via oxidizing the surface at 0.8 V vs RHE (reversible hydrogen electrode) and subsequent hydrogenation to passivate the electrically active defects in the oxide film. After appropriate surface-conditioning, direct water splitting is demonstrated without any applied potential.

Indirect charge transfer from photoanode to electrolyte via interface states in oxide.

Direct water splitting by surface-conditioned n-GaP (100) photoanodes

During direct water splitting, charge transfer across n-GaP(100) photoanode-electrolyte interface is analyzed with electrochemical impedance spectroscopy (EIS). The Nyquist plots, measured with EIS, are reproduced with simulation of an equivalent electrical circuit. It is determined that during water splitting, the charge transfer from V.B of the photoanode to the electrolyte via interface states in the oxide. It is also determined that the direct water splitting is a 6-step charge transfer process, including 4-step water oxidation reaction.

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Energy-Aware Real-Time Task Scheduling on Local/Shared Memory Systems

17.06.2019

The rapid development of the Real-Time and Embedded System
(RTES) has increased the requirement on the processing capabilities of
sensors, mobile phones and smart devices, etc. Meanwhile, energy
efficiency techniques are in desperate need as most devices in RTES are
battery powered. Following the above two trends, this work explores the
memory system energy efficiency for a general multi-core architecture.
This architecture integrates a local memory in each processing core,
with a large off-chip memory shared among multiple cores. Decisions need
to be made on whether tasks will be executed with the shared memory or
the local memory to minimize the total energy consumption within
real-time constraints. This paper proposes optimal schemes as well as a
polynomial-time approximation algorithm with constant ratio.

Bio: Minming Li is currently an associate professor in the Department of
Computer Science, City University of Hong Kong. He received his Ph. D.
and B.E. degree in the Department of Computer Science and Technology at
Tsinghua University in 2006 and 2002 respectively. His research
interests include algorithmic game theory, combinatorial optimization
and algorithm design and analysis for scheduling problems.

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New Avenues for Exploration and Applications of Gallium Nitride and related materials

25.06.2019 von 15:00 bis 16:00

New Avenues for Exploration and Applications of Gallium Nitride and related materials

Ion Tiginyanu

Academy of Sciences and Technical University of Moldova, Chisinau, Republic of Moldova

Gallium nitride, a wide-bandgap semiconductor compound, has in the last two decades registered a fascinating increase in the crystalline quality of epitaxial layers determining its leading role in the development of the modern solid-state lighting industry. The demonstration and successful commercialization of GaN-based blue light emitting diodes resulted in the physics Nobel prize to I. Akasaki, H. Amano and S. Nakamura in 2014. Exhibiting an impressive number of unique properties, over the last decade GaN has been remarkably successful in the area of high-power/high-frequency electronic applications and is now considered the second most important semiconductor material after Silicon. In this paper, we report on new fields of research and applications of gallium nitride and related materials such as nano-biomedicine, nano-microfluidics, nano-microrobotics and memristor networks. The feasibility of high-performance light-driven nano/microengines based on GaN nano/microtubular structures will be demonstrated.

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Experimental Pitfalls

17.07.2019 von 14:00 bis 15:00

We all run experiments to prove the value of what we do and to try to persuade others that our visualisations are not just pretty but have a useful function outside the research team. But designing and conducting experiments is full of pitfalls: equipment failure, limited participant pool, confounding factors, incomplete data etc. And results are often uncertain and always limited. In my 20+ years of running experiments, I have made numerous mistakes - I estimate that I have thrown away about as much data as I have published. In this talk, I discuss some of my failures, highlighting the things that went wrong.  As part of this, I discuss the value of conducting follow-on experiments, and the danger of relying on p-values.

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Things that communicate and decide autonomously

12.07.2019 von 14:00 bis 15:00

Access to the Internet and communication is a key driving force in our modern society. Today, connectivity and computing come to physical objects and places: Even traditionally simple objects such as step counters, thermostats, and light bulbs begin to enjoy wireless connectivity. Similarly, cars, production lines and medical equipment will become networked. Predictions indicate that smart, connected objects soon will outnumber today's traditional connected devices such as smartphones or PCs. By 2025 we expect to reach 50 billion connected devices. This is called the Internet of Things (IoT) and it aims to make our daily lives easier, safer, and more sustainable. The Internet of Things monitory and interacts with the physical world and allows for new applications such as smart power grids, intelligent transportation, or advanced automation in factories and homes. Many of these applications are mission and safety-critical: For example, when two autonomous vehicles approach an intersection, they have to coordinate within a split second on which car shall cross first. Similarly, a wireless glucose sensor must quickly and reliably exchange information with, for example, an insulin pump to ensure a patient’s well-being. As a result, applications require fast, distributed networking and data analysis to ensure reliable coordination and decision making. In my talk, I will give an introduction to the field, give an overview of the work of my group in the area, outline open research challenges and future directions.

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Understanding Mg corrosion and biocorrosion

08.07.2019 von 16:00 bis 17:00

Andrej Atrens1, Sean Johnston2, Zhiming Shi1 , Matthew S. Dargusch2

1The University of Queensland, Materials Engineering Division, School of Mechanical & Mining Engineering, Brisbane, Qld 4072, Australia; 2The University of Queensland, Centre for Advanced Materials Processing and Manufacturing (AMPAM), Brisbane, Qld 4072, Australia

Abstract:

The first part of this talk reviews the main factors that control Mg corrosion immersed in aqueous solutions: (i) crystallographic orientation, (ii) impurity concentration (particularly Fe), and the influence of heat treatment, (iii) second phases, (iv) corrosion product films on the alpha-phase. Measurement effects are also mentioned.

The second part deals with Mg alloys for biodegradable medical implants. Over the last decade, Mg alloys have progressed from a laboratory concept to significant clinical successes. For this application, corrosion which is normally an unwanted feature of Mg alloys, becomes critical for success. It is vital to understand and control the corrosion rate. In vitro research has identified the following factors as the most important: (a) the inorganic ions like calcium, chlorides, bicarbonates, phosphates; and (b) the organic compounds including proteins, amino acids and vitamins. The best estimates for Mg corrosion rates (based on in vitro measurements) are larger than the corrosion rates measured in vivo. This suggests that the Mg corrosion mechanism in vivo is not adequately characterized, or the in vivo environment is not equivalent to immersion in a solution as used in the in vitro experiments. In fact, recent examination of specimens  implanted subcutaneously into Sprague-Dawley rats indicated that the in vivo environment was not at all equivalent to immersion in a solution, but rather the environment could be better described as damp.

Prepared as an invited presentation to Symposium F: Biomaterials

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Towards Data Science: From Data to Patterns to Knowledge

12.07.2019 von 14:00 bis 14:00

Recent advances of sensor technologies and the new user mentality of generating and voluntarily sharing information produce a tremendous source of rich data. This data contains information which is very useful for an incredible number of applications enhancing studies for diverse fields of science, supporting the productivity in industry, and enabling advanced services for our society. A necessary building block for taking advantage from this vast amount of information is the development of efficient and effective searching and mining algorithms which is very challenging because of the

specific characteristic of the data that is often unstructured or complex structured, heterogeneous, dynamic, uncertain or incomplete.

Furthermore, entities in our real world need to be considered as a set of interacting or interrelated, multi-typed components. To make such data useful for diverse applications, advanced methods for managing and retrieving information, pattern mining, machine learning and knowledge discovery that can cope with the afore mentioned characteristic of data are necessary. In my talk, I will address some of these issues in the context of scientific applications. In addition, I will introduce current research activities on heterogeneous information networks for cross-domain data fusion and analysis with an outlook to future research opportunities.

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