As of July 1, 2018, SCS has launched a new Department for Blockchain and Internet-Of-Things. Alain Brenzikofer heads the newly formed group as the new Department Head. We congratulate Alain Brenzikofer on the new role and wish him every success.

Distributed Ledger Technologies, Blockchain, Cryptocurrencies, IoT: The terms are ubiquitous and will disrupt various industries. Alain Brenzikofer has been observing these technologies for years and is a profound expert on the scene. Interesting applications arise today in the energy sector, but also in the commodity trade, with guarantees of origin. Some of these are already under development at SCS: As Partner in the “Quartierstrom” project in Walenstadt, where a blockchain-based peer-to-peer energy market is being created.

Last Friday, we celebrated our 25th anniversary with customers, our staff, friends and colleagues at the Aura event hall in Zurich.
The “Lauf der Dinge” has started over 25 years ago and continuous ever since following interesting cause-and-effect chains.
We gladly thank all participants and especially the artists for their joining us in our experiment.

We are extremely proud to announce that the world-renowned design prize iF DESIGN AWARD has been awarded to the rc_visard of our customer Roboception!

From the very beginning, it has been one of Roboception’s goals to not only optimize our sensors in terms of functionality, but to make them visually attractive as well. In the end, they are typically mounted to their customer’s robots in very prominent positions.

And obviously, the rc_visard’s combination of functionality and design convinced the iF DESIGN AWARD’s 63-member jury, made up of independent experts from all over the world.

Further Infos at Roboception Website.

Also in ML projects the usability of the user interface is key to success.

On the IBM Watson Platform, PDF documents can be used for the training of Machine learning (ML) algorithms. For this purpose, a large number of documents need to be annotated manually.

The annotation is an time-consuming work. Making a suitable tool available for this process step is key to success for IBM Watson.



CCS Page Annotator
The page annotator allows the user to mark the various kinds of texts graphically. Thereby, a document model can be established.

On behalf of IBM research, SCS has created a web based tool for this task.

The SCS usability engineer has designed the user interface according to the requirements of IBM. During this process, a special focus was placed on self-explanatory and efficient procedures. Studies at IBM have shown that thanks to this user interface, the time spent on annotation work could be cut by a factor of 10 and more.



CCS Table Annotator
For tables, a dedicated table annotation pagehas been set up.

We congratulate IBM Watson Group, represented by Peter Staar and his team for the presentation of the poster at the SysML conference in Standford, CA.

Peter W J Staar, Michele Dolfi, Christoph Auer, Costas Bekas. Corpus Conversion Service: A machine learning platform to ingest documents at scale. SysML 2018.

Topics: User Centered Design, HTML5, Sass/CSS, TypeScript, Angular, D3



At the third TechEvent this year Dr. med. Thomas Baumann and Dr. med. et phil. Stefan Essig have shown us how telemedicine can support pediatricians when diagnosing hip dysplasia.


SVUPP is the Swiss association for pediatric ultra sound applications. Thanks to the new SVUPP Exchange Portal, the vision for telemedicine, designed for practicing pediatricians in Switzerland in the area of ultrasound, has become a reality. The digitalization of the imagery exchange leads to a fast and high-quality ultrasound examination of newborns.





The original idea for the SVUPP Exchange Portal stems from an assistance project in Mongolia, which has been supported by Switzerland and runs an evidence-based prevention program for hip dysplasia, a common development disorder in newborns.




Applied Technologies: Angular, TypeScript, Microsoft .NET Core, Event Store, MongoDB, OAuth 2

SVUPP – Schweizerische Vereinigung für Ultraschall in der Pädiatrie
SMPOPP – SwissMongolian Pediatric Project

SCS - Studienarbeiten

OverviewTechnical maintenance on ticket vending machines requires a high level of expertise. Technicians usually need many weeks to get a good understanding of the vending machines, under the tight supervision of their mentor. The goal of the present study is to design and implement an AR (Augmented Reality) system that will facilitate the work of the technicians and reduce their apprenticeship time. In fact, this AR solution will provide in real-time the necessary information with the corresponding documentation of the component that needs maintenance. For instance, a technician will be able to immediately scan the different components in the TVM and determine which are the cables that must be connected between them. Continue reading “Facilitated Maintenance with Augmented Reality”

SCS - Studienarbeiten

A large part of the medical imaging data available today is available in 3D. This is true for example for magnetic resonance imaging data, computed tomography scan data and many other techniques. This is advantageous as it allows drawing conclusions based not only on single images but taking into account more information. Many medical images have to be further processed by segmenting different objects in the images such as bones or tissue layers. In the past years, the analysis of 2D medical images with Deep Learning methods has become a standard in research. With more and more computing power available, the focus is moving towards 3D analysis to profit from more spatial context.

Continue reading “Extend Machine- and Deep Learning into 3D – Enabling volumetric Analysis of Medical Image Data”

SCS - Studienarbeiten

Die wachsende Transparenz im Niederspannungsnetz ermöglicht es unter anderem transiente Vorgänge hochauflösend aufzuzeichnen. Somit wird es denkbar, mit geeigneten Algorithmen die Fehlerstelle im Störungsfall zu lokalisieren, wie es heute nur auf höheren Spannungsebenen gemacht wird. Die Kosten für die Suche nach der Fehlerstelle und die Interventionszeiten der Netzbetreiber könnten somit gesenkt werden und damit wird ein Mehrwert geschaffen.Im ersten Schritt soll der Student im Rahmen seiner Arbeit die bestehenden Fehlerortungsalgorithmen auf deren Anwendbarkeit im Niederspannungsnetz untersuchen und eine Evaluation vornehmen. Im zweiten Schritt soll ein geeigneter Algorithmus implementiert und mittels simulierter Daten getestet werden. Zudem sollen Versuche im ewz Labor durchgeführt werden, um echte Messdaten zu gewinnen.

Continue reading “Fehlerlokalisierung im Niederspannungsnetz”

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Today’s Machine Learning algorithms rely on large data sets of ground truth. Especially for medical use cases the lack of appropriate data for training can be a limiting factor for successful Deep Learning. For some imaging problems, the creation of synthetic ground truth can effectively overcome the lack of original ground truth and enable successful learning.In this work we aim to explore the potential of synthetic ground truth for tumor segmentation in medical imagery of eyes. The student will work with 3D stacks of optical coherence tomography (OCT) images. The currently implemented Convolutional Neural Networks (CNNs, e.g. U-net) shall be extended to segment tumors using both synthetic ground truth data and state-of-art CNNs.

Continue reading “Generation of synthetic ground truth for Machine Learning”

SCS - Studienarbeiten

Pediatricians and general practitioners use ultrasound for diagnostic purposes in their office. Ultrasound is fast, reliable, safe, and is seen as the visual stethoscope of the 21st century. Standardized, high-quality examinations depend on the exact position of the transducer for transmitting and receiving the ultrasound beam. However, the correct plane defining the image cross section obtained from the patient is often difficult to achieve.Advanced technology might support physicians with feedback based on automated analyses of examinations by ultrasound. We will use the example of ultrasound-based diagnosis of developmental dysplasia of the hip (DDH) in newborns to suggest such an approach using Neural Networks.

Continue reading “Learning Angles from Ultrasonography Imagery with Machine Learning and Deep Learning”