Author Archives: Matthias Günter

Best Thesis 2018

The JAACS is the Alumni Association of the three Computer Science Institutes INF, IIUN and DIUF of the Universities of Bern, Neuchâtel, and Fribourg. More information about the association and how to register can be found at https://www.jointalumni.ch/admission.

The JAACS annually awards a prize for the best Bachelor, Master, and Doctoral thesis at the INF, IIUN and DIUF that was defended during the academic year. The winners are selected by the respective institutes and are presented the award at the institute’s end-of-year event.

PhD

Dr. Meiguang Jin

Motion Deblurring from a Single Image

INF, Bern

 

Abstract

Photos are the result of the accumulation of light from a scene during the exposure. Thus, photos of objects moving during the exposure show the confusing overlap of different images, an artifact called motion blur. Motion blur makes visual content less interpretable and is therefore often seen as a nuisance. Although motion blur can be reduced by setting a short exposure time, enough amount of light has to be compensated through increasing the sensor’s sensitivity, which will inevitably bring a large amount of sensor noise. This motivates the

necessity of removing motion blur computationally, a problem called motion deblurring. This problem is challenging because the solution is not unique. Mathematically, a blurry image caused by uniform motion is formed by the convolution operation between a blur kernel and a latent sharp image. Potentially there are infinite pairs blur kernel and latent sharp image that can result in the same blurry image. Hence, some prior knowledge or regularization is required to address this problem. Even if the blur kernel is known, restoring the latent sharp image is still difficult as the high frequency information has been removed. Although we can model the uniform motion deblurring problem mathematically, it can only address the cases where the camera translates on the x-y plane. In practice, however, motion is more complex and can be non-uniform. Non-uniform motion blur can come from many sources, camera out-of-plane rotation, scene depth change, object motion and so on. In this thesis, we present several methods for motion blur removal. We aim to address four challenging motion deblurring problems. We study from the noise blind image deblurring scenario where blur kernel is known but the noise level is unknown. We introduce an efficient and robust solution based on a Bayesian framework using a smooth generalization of the 0 − 1 loss to address this problem. Then we study the blind uniform motion deblurring scenario where both the blur kernel and the latent sharp image are unknown. We explore the relative scale ambiguity between the latent sharp image and blur kernel to address this issue. Moreover, we study the face deblurring problem and introduce a novel deep learning network architecture to solve it. We also address the general motion deblurring problem and particularly we aim at recovering a sequence of 7 frames each depicting some instantaneous motion of the objects in the scene.

 

Laudatio

Mr. Meiguang Jin has made significant contributions to the problem of removing blur in images due to moving objects. The solution to this problem is required to enable the understanding of an image. Mr. Jin’s methodology is solid and thorough: it begins with the mathematical description of blurred images, uses a probabilistic approach to formalize the estimation of the sharp image as an optimization problem, and creates efficient algorithms to solve the optimization problem. The experiments show state-of-the-art results, showing how a solid theory can lead to better performance. All of Mr. Jin’s work has been published at high-level international peer review conferences.

https://meiguangjin.github.io

 

PhD

Dr. Mirco Kocher

Text Clustering with Styles 

IIUN, Neuchâtel

 

Abstract

This thesis mainly describes the author clustering problem where, based on a set of n texts, the goal is to determine the number k of distinct authors and regroup the texts into k classes according to their author. We iteratively build a stable and simple model for text clustering with styles. We start by designing a measure reflecting the (un)certainty of the proposed decision such that every decision comes along with a confidence of correctness instead of only giving a single answer. Afterwards, we link those pairs of texts where we see an indication of a shared authorship and have enough evidence

that the same person has written them. Finally, after checking every text tuple, if we can link them together, we build the final clusters based on a strategy using a distance of probability distributions. Employing a dynamic threshold, we can choose the smallest relative distance values to detect a common origin of the texts. While in our study we mostly focus on the creation of simple methods, investigating more complex schemes leads to interesting findings. We evaluate distributed language representations and compare them to several state-­‐of-­‐the-­‐ art methods for authorship attribution. This comparison allows us to demonstrate that not every approach excels in every situation and that the deep learning methods might be sensitive to parameter settings. The most similar observations (or the category with the smallest distance) to the sample in question usually determines the proposed answers. We test multiple inter-­‐textual distance functions in theoretical and empirical tests and show that the Tanimoto and Matusita distances respect all theoretical properties. Both of them perform well in empirical tests, but the Canberra and Clark measures are even better suited even though they do not fulfill all the requirements. Overall, we can note that the popular Cosine function neither satisfies all the conditions nor works notably well. Furthermore, we see that reducing the text representation not only decreases the runtime but can also increase the performance by ignoring spurious features. Our model can choose the characteristics that are the most relevant to the text in question and can analyze the author adequately. We apply our systems in various natural languages belonging to a variety of language families and in multiple text genres. With the flexible feature selection, our systems achieve reliable results in any of the tested settings.

Laudatio by Prof. Jacques Savoy

During this research. M. Kocher and myself have published two papers in the journal Digital Scholarship in the Humanities, one in Information Processing & Management, and another one Journal of the American Society for Information Science and Technology. M. Kocher published one paper in the Joint Conference on Digital Libraries IEEE-ACM in 2017 (and two others in more minor conferences). Finally, Kocher and myself participate during three years to the CLEFPAN evaluation campaigns. Due to our good results, we ask three times M. Kocher to present his results during the CLEF conference.

Link: http://doc.rero.ch/record/306696

 

Master

Mario Kaufmann

Reproducible moldable interactions

INF, Bern

 

Abstract

Object inspectors are tools that allow developers to explore the state of run-time objects. This exploration creates many interaction events between the developer and the inspector. Recording, saving and using those interactions directly in an inspector opens opportunities to reduce the amount of repetitive actions developers need to do during development and debugging. To make this possible we propose an inspector model that records developer interactions as first-class entities and uses them to reduce repetition. This is enabled through a

model that uses a tree to keep track of an inspection session, and a recording infrastructure that allows each widget to decide how user interactions should be recorded. To validate this model, we identify several types of problems that can arise in object inspectors and show how they can be addressed if developer interactions are recorded by the inspector. For example, the new model allows developers to replay inspection sessions, restore partial navigation and generate code from an inspection session.

Laudatio

An “object inspector” is a tool commonly found in programming language debuggers, used to examine and explore the state of objects in a snapshot of the memory of a running program. The object inspector of the Pharo Smalltalk development environment is a state-of-the-art tool that supports sliding windows for navigation through object state, and “moldable” views of objects that are adapted to a given application domain, offering tailored visualizations and interactions.

Common shortcomings of objects inspectors are (i) the navigation path is lost when the focus moves to a new object, forcing the developer to manually replay the path, (ii) there is no possibility to record a navigation for later playback, and (iii) the code corresponding to a useful navigation must be manually reverse-engineered by the developer.

Mr. Kaufmann addresses these issues by extending the Pharo object inspector with “reproducible moldable interactions”. He has modified the underlying model of navigations to capture tree of interactions rather than simply a list. This makes it possible to reapply a sequence of interactions from one object to another one of the same type.

In his MSc thesis, Mr. Kaufmann has carefully surveyed and reported on the relevant related work, he has analyzed the shortcomings of existing object inspectors in detail, he describes the new tree-based model of interaction and presents the implementation details, and he convincingly conveys how the extension simplifies and enhances interaction with an object inspector.

 

Link: http://scg.unibe.ch/archive/masters/Kauf18a.pdf

 

Master

Ismaïl Senhaji

LSDSuite: Evaluation Framework for Large-Scale Distributed Systems

DIUF, Fribourg

 

Abstract

Testing large-scale distributed systems is a difficult task. Many testing frameworks attempt to alleviate these difficulties, but are often lacking in scalability, flexibility or ease-of-use. We present LSDSuite, an evaluation framework for largescale distributed systems. Based on Docker Swarm, and using containers as unit of execution, it aims at offering a simple and flexible way of designing experiments, and is capable of scaling

to thousands of concurrent tasks. An overview of its features is given, as well as a more in-depth look into the framework’s architecture. Finally, an example experiment is demonstrated, showcasing LSDSuite’s capabilities.

Laudatio

Testing large-scale distributed systems is a difficult task, and existing frameworks are often lacking in scalability, flexibility or ease-of-use. For his Master thesis, Ismaïl Senhaji has designed and developed LSDSuite, an evaluation framework for large-scale distributed systems that addresses some of the aforementioned shortcomings. Throughout his Master work, Ismaïl has proved his wide knowledge of distributed systems, his resourcefulness, and his capacity to solve complex problems. We congratulate him for this well-deserved award.

 

Bachelor

Florian Gerber

Capturing Complex Behavior of Mobile Users for Predicting Next Trajectories

INF, Bern

 

Abstract

The widespread adoption of cellular phones equipped with global positioning system (GPS) sensors makes the exploration of pedestrian mobility patterns possible. Discovering relevant places can be achieved through accumulating GPS coordinates. This thesis demonstrates a spatio-temporal analysis on collected geolocation points to discover Zones of Interest (ZOIs) of pedestrians to understand underlying movement patterns. This analysis involves the discovery of Points of Interest (POIs)

based on selected criteria and then an aggregation of these POIs to obtain the ZOIs. Furthermore, a new Markov based model to predict long distance trajectories of pedestrians is introduced. The model is capable of choosing between the first and second order Markov chain in order to accommodate to the different movement behaviours of individual pedestrians and the available trace data. To quantify the movement behaviour of users an existing Periodicity Detection algorithm is modified to achieve a better task-specific, computational performance. In addition, the adaptive Markov model is evaluated and compared to other current trajectory prediction methods using the real-life Mobile Data Challenge (MDC) dataset. The proposed model achieves a precision of up to 86% and a recall of up to 84% for predicting future trajectories of users in the MDC dataset. The thesis further presents a mechanism to predict the number of pedestrians in urban areas traveling on the same trajectory at a future point in time. This mechanism combines the adaptive Markov model with an existing next Place Prediction algorithm and a means of storing and aggregating predicted trajectories for multiple users.

Laudatio

The bachelor thesis of Florian Gerber focuses on the problem of human mobility understandings. He analysed the spatial and temporal parameters of pedestrians’ daily mobility to discover the movement patterns. He proposed advanced machine learning models to predict pedestrians’ future movement trajectories and locations. This work has a great potential in future smart transportation applications, such as route planning, mobile network performance optimisation, etc. His works have been successfully published in 4 scientific papers.

Link: http://rvs.unibe.ch/research/pub_files/BachelorThesisFlorianGerber.pdf

 

Bachelor

Martin Andreas Disch

DEFO DM2017: Developing a Deformation Monitoring System with the Microservices Pattern

DIUF, Fribourg

 

Abstract

In the construction business it is often necessary to keep an eye on structures or parts of the environment which may move inadvertently. This is done by continuously measuring the positions of several points in the area of interest. The author was given the opportunity to work at GEOINFO Vermessungen AG in Gossau, which provides this service to clients. The company used to collect this data, analyze it manually and upload it to a website where customers can look at it. The goal

of this thesis was to develop a web-based system that would analyze the measurements for critical deviations, alert staff if necessary, and automatically transfer it to the existing customer website. Besides automating this workflow, the system should also be easy to extend, reuse, and integrate into other applications. To accomplish this, the microservices architectural style was chosen for the implementation.

 

Laudatio

En juillet 2017, le candidat a eu l’opportunité de travailler pour la firme GEOINFO à Gossau, qui s’occupe de vérifier en continue que des mouvements de terrain même infimes ne se produisent pas dans le cadre d’infrastructures critiques comme par exemple des rails de chemin de fer.

Avant l’arrivée d’Andreas, la compagnie collectait l’ensemble des données; des ingénieurs procédaient à une analyse manuelle; et ensuite seulement les données étaient chargées sur un serveur web et les clients avertis en cas de problème.

En 9 semaines de travail et donc en respectant les délais, Andreas a été capable de comprendre le fonctionnement complexe de la collecte, de l’analyse et du transfert des données chez GEOINFO, d’apprendre un ensemble de technologies nouvelles pour lui (par exemple l’idée de web services REST) et de produire une solution informatique complète pour gérer les processus métiers formant le coeur du business de GEOINFO. De plus, la solution proposée se base sur des microservices réutilisables et sur un scheduler pour les composer. Une solution de grande qualité et qui semble donner totale satisfaction. Il est extrêmement rare qu’un étudiant parvienne à une solution aussi professionnelle et d’une telle qualité scientifique dans le cadre d’un travail de bachelor. Le rapport est lui aussi d’excellente facture.

Photo : IIUN, Mirco Kocher

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Best Maturarbeit 2017/2018

JAACS hat für 2018 nur eine Maturarbeit prämiert. Es ist dier Min-Max Algorithmus von Matthieu Protais

Das Institut für Informatik der Universität Bern, das Institut d’Informatique der Universität Neuenburg und das Department für Informatik der Universität Freiburg fördern zusammen mit der Joint Alumni Association in Computer Science (JAACS, www.jointalumni.ch) durch diese Auszeichnung das Engagement der Maturandinnen und Maturanden an Schweizer Gymnasien für diese wichtige Zukunftsbranche auf dem Platz Schweiz.

Zum achten Mal in Folge zeichnen JAACS (www.jointalumni.ch) und die Informatik-Institute die besten Maturaarbeiten im Bereich der Informatik aus. Ausserdem bieten die drei Universitäten den gemeinsamen Studiengang Swiss Joint Master of Science in Computer Science an (http://mcs.unibnf.ch/). Das Einzugsgebiet des Preises umfasste in diesem Jahr die Kantone Bern, Neuenburg, Freiburg, Solothurn, Aargau, Luzern, Wallis und Jura.

Die prämierte Arbeit

Gymnasium Name Titel
Lycée Denis-de-Rougemont à Neuchâtel Matthieu Protais Algorithme Min-Max et élagage Alpha-Beta

Présentation TM Mathieu Protais

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GV JAACS 2018

Anwesend: 2 Personen

Jahresbericht

Erfolgte mündlich

Wahlen

Der Vorstand wurde wiedergewählt.

Rechnung 2017

Die Rechnung 2017 wurde genehmigt.

Budget 2018

Das Budget 2018 wurde mit einem Defizit von CHF 111 genehmigt.

Ausblick

Es wird dieses Jahr wieder ein Studenten-Alumni-Essen veranstaltet werden.

 

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Best Papers 2017

The JAACS annually awards a prize for the best Bachelor, Master, and Doctoral thesis at the INF, IIUN and DIUF that was defended during the academic year. The winners are selected by the respective institutes and are presented the award at the institute’s end-of-year event.

 

 

   PhD
Dr. Michel MartiContributions to Intuitionistic Epistemic Logic
INF, BernAbstractMarti analyzed the combination of intuitionistic and epistemic logic. He proved the soundness and completeness of of formal systems for intuitionistic common and distributed knowledge by means of so-called canonical model constructions and introduced new models of intuitionistic justification logics.

 Laudatio

Marti has worked in the general field of non-classical logics with a focus on intuitionistic epistemic logics. He has been able to solve some interesting problems in the context of intuitionistic common knowledge and intuitionistic distributed logic and to make some promising first steps into the new field of intuitionistic justification logics.

http://www.ltg.unibe.ch/staff/mmarti

  PhD
Dr. Andrei LapinApproaches for Cloudification of Complex High Performance Simulation Systems
IIUN, NeuchâtelAbstractScientific computing is often associated with ever-increasing need for computer resources to conduct experiments, simulations and gain outcomes in a reasonable time frame. With continuously increasing need for higher computing power, one of the solutions could be to offload certain resource-intensive applications to a cloud environment with resources available on-demand. We address efficient migration of MPI-based scientific applications to clouds

Laudatio

The thesis tackles the cloudification  of complex high performance simulation systems by addressing various aspects: (a) overview of high performance and cloud computing domains, (b) analysis of  existing simulation problem types, (c) describing and analysing an example Monte Carlo simulator stemming from the hydrogeology domain, (d) presenting two cloudification methodologies, (e) applying the methodologies to the example simulator, and (f) evaluating the potential application of methodologies in a real case study. The thesis concentrates on devising solutions that facilitate the adaptation of scientific applications to ever emerging new technologies and methodologies. It was thus in particular necessary to understand the high performance computing challenges as well as the mathematical grounds of the solutions and the application domain usage.

  PhD
Dr. Leonardo AngeliniA Framework for Abstracting, Designing and Building Tangible Gesture Interactive Systems
DIUF, FribourgAbstractThis thesis discusses tangible gesture interaction, a novel paradigm for interacting with computer that blends concepts from the more popular fields of tangible interaction and gesture interaction. The thesis presents a framework for designing interactions and building interfaces for everyday objects, leveraging our innate skills to manipulate physical objects and communicate through gestures.

Laudatio

Dr Leonardo Angelini has done his PhD in co-supervision between the University of Fribourg and the University of Applied Sciences in Fribourg. This PhD is the result of 10 years of collaboration between Prof. D. Lalanne and Prof. E. Mugelini.

Dr Leonardo Angelini is truly one of the best PhD students that we had between the two institutions. He succeeded to combine the best competencies of Human-IST and Human-Tech institutes. Not only he has developed, and evaluated with users, several systems combining gestural with tangible interaction, he has developed a conceptual framework to support their design, development and evaluation. During his PhD, Dr Angelini has published about 20 scientific articles and organized several international workshops which is remarkable at this stage of the career. We wish him a fruitful and long career in the academic field.

  Master
Simon JenniAn Approach to Unsupervised Visual Representation Learning
INF, BernAbstract

This work introduces a novel self-supervised learning model based on deep neural networks. This model can learn by itself what objects are through learning to distinguish real images from realistic images that it hallucinates from a cartoon input.
The proposed method can be applied to training models with very few examples of input-output mappings and dramatically boost their performance.

Laudatio

This thesis presents very original work which produced a performance comparable and also superior to current state of the art methods by the leading groups at the international level. More precisely, this competes with the best results from Google Deep Mind, from the FAIR group at Facebook, and from the research groups of the University of Berkeley and Carnegie Mellon University. An evolution of this work has been submitted to one of the 3 top tier conferences in computer vision and machine learning.

  Master
Michele Alberti
Using Linear Discriminant Analysis for Deep Neural Network Initialization
DIUF, FribourgAbstract

This work tackles the long training time of Neural Networks with smart weights initialization conveyed through Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) algorithms. We show that these two algorithms can be used to achieve faster and better performances compared to State of Art initialization methods.

Laudatio

The Master thesis of Michele Alberti is an outstanding contribution to deep neural networks for image analysis. Michele has extended a given framework with novel initialization algorithms and has made extensive experiments. He has obtained interesting results allowing him to question approaches usually used by deep learning practitioners. Finally, he came up with novel ideas, enabling new learning strategies with less data, while simultaneously providing higher recognition accuracy. The work has given raise to several publications.

  Bachelor
Joel NiklausMachine Learning for Indoor Positioning
INF, BernAbstractThis bachelor thesis explores the potentials of using advanced machine learning algorithms to perform indoor positioning tasks on smartphones using Wi-Fi received signal strength and on-board inertial sensors measurements. Intensive experiment results show that the system achieves highly accurate room-level positioning, which can be further used to enhance the indoor tracking.

 

Laudatio

Recently, machine learning has been popular in computer vision studies. This works applies advanced machine learning techniques in wireless networks and illustrates how it can be used to enhance the performance of indoor positioning.

  Bachelor
Simon StuderSimple Protocol for Encrypted Messaging (SPEM)
DIUF, FribourgAbstractSPEM (Simple Protocol for Encrypted Messaging) is a protocol for end-to-end encrypted instant messaging. It is designed to protect the privacy of its users without compromising usability. SPEM relies on decentralized servers for message delivery, allowing anyone to manage their own messaging servers.

 

Laudatio

In his BSc-thesis, Simon Studer developed a lean messaging protocol with end-to-end encryption, aiming at being an improvement over, for instance, WhatsApp that at the start of the thesis did not use end-to-end encryption. The protocol that Simon designed is very clever and takes security as well as efficiency aspects into account. Simon worked extremely independently, reducing the supervision effort to regular meetings with interesting discussions on new ideas Simon had. Technically as well as presentation-wise, “Simple Protocol for Encrypted Messaging (SPEM)” by Simon Studer is an absolutely excellent and prize-worthy BSc-thesis.

 

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Beste Maturarbeiten Informatik 2016/2017

 Die besten Maturarbeiten im Bereich Informatik für das Schuljahr 2016/2017 umfassen vielfältige Themen. .

Timothée Hirt hat einen Roboter für das Mühlespiel konstruiert.

Loic Wermeille hat mit seinem Projekt Cubix einen Roboter gebaut, der einen Rubric’s Cube löst.

Paul Coral hat eine Agenda für Schulen entwickelt.

David Scherrer hat sich in seiner Arbeit mit der Geolokalisation im Innern von Gebäuden beschäftigt

Oliver D’Ancona hat mit seiner Arbeit “Barycentre géographique” untersucht, wie in Geodaten Schwerpunkte bestimmt werden können.

Alle Gewinner haben sich intensiv mit ihrem Gebiet beschäftigt und zeigen, was mit persönlichem Engagement alles möglich ist.

Das Institut für Informatik der Universität Bern, das Institut d’Informatique der Universität Neuenburg und das Department für Informatik der Universität Freiburg fördern zusammen mit der Joint Alumni Association in Computer Science (JAACS, www.jointalumni.ch) durch diese Auszeichnung das Engagement der Maturandinnen und Maturanden an Schweizer Gymnasien für diese wichtige Zukunftsbranche auf dem Platz Schweiz.

Zum siebten Mal in Folge zeichnen JAACS (www.jointalumni.ch) und die Informatik-Institute die besten Maturaarbeiten im Bereich der Informatik aus. Ausserdem bieten die drei Universitäten den gemeinsamen Studiengang Swiss Joint Master of Science in Computer Science an (http://mcs.unibnf.ch/). Das Einzugsgebiet des Preises umfasste in diesem Jahr die Kantone Bern, Neuenburg, Freiburg, Solothurn, Aargau, Luzern, Wallis und Jura.

Die prämierten Arbeiten

Gymnasium Name Titel
Lycee Cantonal de Porrentruy Timothée Hirt Le Jeu Du Moulin

2017_Poster JAACS – Timothée Hirt

Lycee Cantonal de Porrentruy Loic Wermeille Cubix

2017_CUBIX_poster

Collège Sainte Croix, Fribourg Paul Coral Agenda scolaire
connecté2017_Poster_Coral_Paul
Lycée Denis-de-Rougemont, Neuchâtel David Scherrer SYSTÈME DE GÉOLOCALISATION À
L’INTÉRIEUR D’UN BÂTIMENT2017_Poster_David_Scherrer_
Gymnase Intercantonal de la Broye, Payerne Olivier D’Ancona Barycentre géographique

2017_Poster_D_Anconca_Olivier

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Beste Maturarbeiten 2015/2016 ausgezeichnet

 Die besten Maturarbeiten im Bereich Informatik für das Schuljahr 2015/2016 umfassen vielfältige. Gemäss Dr. Matthias Günter, Präsident der JAACS, ist es wichtig, dass in dieser Zukunftsbranche genügen lokale Talente gefördert werden. Die eingereichten Arbeiten zeigten eine sehr hohe Qualität.

Nourredine Gueddach (Collège St. Michel, Fribourg) entwickelte das Videospiel „Nightmare Gravity“. Die Dynamik und „Spielfluss“ sind zentral. Diese müssen bei der Entwicklung berücksichtigt werden.

Massimo Jörin (Kantonsschule Zofingen) entwickelte ein Programm, das die Geschichte der Verschlüsselung nachvollzieht und historische kryptographische Funktionen nachvollzieht. Dazu wurde auch eine verbesserte Enigma von ihm entwickelt.

Roman Riesen (Gymnasium Lerbermatt) entwickelte ein Add-on für die sehr bekannte 3D-Software Blender, welches Landschaften mit Erosion, Wald- und Wasserverteilung kreiert.

Alle Gewinner haben sich intensiv mit ihrem Gebiet beschäftigt und zeigen, was mit persönlichem Engagement alles möglich ist.

Das Institut für Informatik der Universität Bern, das Institut d’Informatique der Universität Neuenburg und das Department für Informatik der Universität Freiburg fördern zusammen mit der Joint Alumni Association in Computer Science (JAACS, www.jointalumni.ch) durch diese Auszeichnung das Engagement der Maturandinnen und Maturanden an Schweizer Gymnasien für diese wichtige Zukunftsbranche auf dem Platz Schweiz.

Zum sechsten Mal in Folge zeichnen JAACS (www.jointalumni.ch) und die Informatik-Institute die besten Maturaarbeiten im Bereich der Informatik aus. Ausserdem bieten die drei Universitäten den gemeinsamen Studiengang Swiss Joint Master of Science in Computer Science an (http://mcs.unibnf.ch/). Das Einzugsgebiet des Preises umfasste in diesem Jahr die Kantone Bern, Neuenburg, Freiburg, Solothurn, Aargau, Luzern, Wallis und Jura.

 

Die prämierten Arbeiten

Gymnasium Name Titel
Collège St.-Michel, Fribourg Noureddine Gueddach Nightmare Gravity
Création d’un jeu vidéo d’arcade
Kantonsschule Zofingen Massimo Jörin ℂryptura –Entwicklung eines Programmes zum
Verschlüsseln und Verstecken von Nachrichten
Gymnasium Lerbermatt, Bern Roman Riesen Landschaften aus dem Computer

 

 

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Best Papers 2016

In 2016 the following best paper awards were granted:

2016 PhD DIUF for “Entity-Centric Knowledge Discovery for Idiosyncratic Domains“, by Roman Prokofyev
2016 PhD INF for “Uncertain Reasoning in Justification Logic”, by Ioannis Kokkinis
2016 Master DIUF for “Dynamic Tailored Intervention System”, by Fabio Sodani
2016 Master INF for “Improving live debugging of concurrent threads”, by Max Leske
2016 BachelorDIUF for “Interactive dance visualisation – a collaboration between art and technology”, by Valentine Bernasconi
2016 Bachler INF for “Universal Large Scale Sensor Network”, by Jakob Schaerer and Severin Zumbrunn

 

More information:

  • In her Bachelor thesis, Valentine Bernasconi has elaborated an interactive dance visualization that is projected on a transparent mesh fabric between dancers and spectators, thus creating an augmented reality environment. Her innovative work was part of an interdisciplinary collaboration with dancers from the HKB Biel and engineers from the HEIA-FR. Valentine Bernasconi has investigated the rise of digital media in performing arts from an art history point of view and contributed with her visualization, both, technically and artistically, to the resulting dance performance “Nautilus”. She also co-authored a scientific publication for an international conference, where she demonstrated the interactive environment.
  • Fabio Sodani: Le projet européen Pegaso est vaste (17 partenaires) et a pour but d’aider les adolescents à vivre plus sainement à l’aide d’applications mobiles. Le candidat s’est concentré sur des algorithmes pour proposer des messages aux ados basés sur leur contexte de vie. Pour ce faire le candidat a travaillé avec l’Espagne pour la partie raisonnement, avec l’Italie pour le design et avec la HEIA-FR pour le développement. Il s’agit d’un effort très conséquent et qui aura un impact sur la suite du projet dans son ensemble.
  • Roman Prokofyev: Despite the increasing popularity of Big Data tools to efficiently manage structured data, textual content is still the most dominant form used to represent scientific knowledge. Dr. Prokofyev worked on groundbreaking, scalable methods for extracting, structuring and organizing knowledge from text. Specifically, he made important contributions in entity recognition, disambiguation, linking, and co-reference resolution in idiosyncratic domains with an emphasis on scientific literature.
  • Die beiden Bachelor-Studenten Jakob Schaerer und Severin Zumbrunn haben eine Hardware für einen Sensorknoten entwickelt, welche erlaubt über grössere Distanzen (mehrere 100 m, ggf. über 1 km) zwischen Sensorknoten zu kommunizieren. Im Rahmen Ihrer gemeinsam erstellten Bachelor-Arbeit haben Sie einen Protokollstack zur energieeffizienten Kommunikation entworfen und in Software implementiert. Jakob Schaerer hat dabei ein MAC-Protokoll entwickelt, welches auf dem Prinzip von Low Power Listening beruht. Severin Zumbrunn implementierte einen Routing-Mechanismus, welcher auf den beiden Internet-RFCs (RFC: Request for Comments) RPL (Routing Protocol for Low-Power and Lossy Networks) und Trickle beruht. Die beiden Teile wurden integriert und auf der – ausserhalb der Bachelorarbeit entwickelten – Sensor-Hardware implementiert sowie getestet. Die Arbeit resultierte in einem Artikel, welcher bei einer internationalen Konferenz eingereicht wurde.
  • In his Masters thesis, entitled “Improving live debugging of concurrent threads”, Max Leske develops a novel approach to link a thread of an interrupted software program to the “parent” thread that created it. Although the basic idea, which is to connect the stack of the child thread to that of its parent, is deceptively simple, there are a host of difficult technical issues to make this work well in practice. Max has developed an advanced prototype in Smalltalk, explored in detail performance issues, and presented his work at an International Workshop on Smalltalk Technology. A journal paper is in preparation.
  • Ioannis Kokkinis gelang es in seiner Doktorarbeit zwei klassische Theorien, Wahrscheinlichkeitslogik und Justification Logik, miteinander zu verknüpfen. Damit hat er den Grundstein gelegt um unsicheres Schliessen mit Rechtfertigungen präzise zu modellieren. Dies ermöglicht eine Vielzahl neuer Anwendungen in verschiedensten Gebieten wie z.B. Informatik (künstliche Intelligenz), Ökonomie oder Philosophie.
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Best Papers 2015

In 2015 the following best works were given an award by JAACS:

  • PhD INF for “On Modeling and Simulating Reptile Skin Coloration”, by Daljit Singh
  • PhD DIUF for “A Model-Driven, Component Generation Approach for the Web of Things”, by Andreas Ruppen
  • Master INF for “Agent-Based Data Retrieval for Opportunistic Content-Centric Networks”, by Tobias Schmid
  • Master DIUF for “Data Skepticism in Practice – Online Anomaly Detection over Big Data Streams”, by Laura Rettig
  • Bachelor INF for “proof of the arithmetical equivalence of EC with full induction and ACA”, by Paul Frischknecht
  • Bachelor DIUF for “Boids Simulator: Un framework pour concevoir des simulations dynamiques et interactives de groupes d’individus”, by Jocelyn Thode
Posted in Allgemein.

Beste Maturaarbeiten 2014/2015 Informatik ausgezeichnet.

Die fünf besten Maturarbeiten im Bereich Informatik für das Schuljahr 2014/2015 umfassen vielfältige Lösungen zu Spiele, Plattform- und Android-Anwendungen sowie komplexe Hardware- und Software-Systeme. Vermehrt werden Projekte mit mobilen Technologien eingereicht. Gemäss Matthias Günter, Präsident der JAACS, ist es wichtig, dass Talente in der Informatik bereits auf Stufe Gymnasium gefördert werden, da die IT eine für die Schweiz zentrale Wachstumsbranche ist.

 Der Maturand Vladimir Bourquin beschäftigte sich mit der Herstellung eines Plotters, um nebst der informatik-technischen Programmierung auch robotische und elektronische Konzepte gleichzeitig integrieren zu können. Timothée Duran und Jérémy Colombo haben zusammen eine Plattform errichtet, mit der Freizeit- und touristische Aktivitäten in der jeweiligen Region auf den persönlichen Geschmack des Benutzers abgestimmt werden können. Diese Plattform kann wiederum vom Handy oder Tablet aus benutzt werden. Pablo Mercado hat es sich zum Ziel gesetzt, aufgrund einer Spielerfahrung aus der Kindheit ein zweidimensionales Spiel mithilfe von JavaScript und HTML zu codieren und daraus ein Videospiel zu generieren. Aurélie Piazza produzierte und programmierte einen LEGO-Roboter, der Teile eines LEGO-Autos zusammenbauen konnte. Ein anderer Gymnasiast Maël Wildi setzte sich mit der Open Source Software Android auseinander. Er verwende dieses täglich und wolle darum verstehen, wie es funktioniert. Dabei wollte er auch die Sicht des Programmiers einnehmen, weshalb er ein Memory basierend auf Farben kreiert hat.

Das Institut für Informatik der Universität Bern, das Institut d’Informatique der Universität Neuenburg und das Department für Informatik der Universität Freiburg fördern zusammen mit der Joint Alumni Association in Computer Science (JAACS) durch diese Auszeichnung das Engagement der Maturandinnen und Maturanden an Schweizer Gymnasien für diese wichtige Zukunftsbranche auf dem Platz Schweiz.

Zum fünften Mal in Folge zeichnen JAACS (www.jointalumni.ch) und die Informatik-Institute die fünf besten Maturaarbeiten im Bereich der Informatik aus. Ausserdem bieten die drei Universitäten den gemeinsamen Studiengang Swiss Joint Master of Science in Computer Science an (http://mcs.unibnf.ch/). Das Einzugsgebiet des Preises umfasste in diesem Jahr die Kantone Bern, Neuenburg, Freiburg, Solothurn, Aargau, Luzern, Wallis und Jura.

Die prämierten Arbeiten (mit Poster)

Gymnasium Name Titel
Lycée cantonal de Porrentruy Vladimir Bourquin Fabrication et programmation d’un plotter
Lycée Blaise-Cendrars de la Chaux-de-Fonds Jérémy Colombo Pindex, un site unique de recherche personalisée d’activités
Lycée Blaise-Cendrars de la Chaux-de-Fonds Timothée Duran Pindex, un site unique de recherche personalisée d’activités
Lycée Denis-de-Rougemont de Neuchâtel Pablo Mercado Création d’un jeu vidéoludique reprenant des concepts de jeux préexistants
Gymnase intercantonal de la Broye de Payerne Aurélie Piazza My Car Factory
Lycée Blaise-Cendrars de la Chaux-de-Fonds Maël Wildi Développement d’une application Android «Finalco »

Auskunft: Dr. Matthias Günter, Präsident JAACS (www.jointalumni.ch) , 079 457 13 22, matthias.guenter@mentor.ch

Posted in Allgemein.

Begegnungsmittagessen Studierende Alumni 28. 10. 2014

Am 28. Oktober 2014 wird die zehnte Ausgabe des Studierenden-Alumni Begegnungsmittagessen stattfinden.

Der diesjährige Anlass wird an der Fachhochschule in Bern durchgeführt. Andreas Spichiger wird uns unter anderen die Rolle der Fachhochschule als möglichen Arbeitgeber vorstellen.

Agenda

  • Ab 12:00 Eintreffen Alumnis, Austausch & Networking unter Alumnis
  • 12:30h Treffen im Raum H251
  • 13:00 gemeinsames Mittagessen in der (kleinen) Kantine

Ort

Event in der Xing Alumni Gruppe

https://www.xing.com/events/studierende-alumni-essen-1453862

Damit die Kantine der FH planen kann, bitte ich euch bis zum 23. Oktober 2014 via Xing oder E-Mail anzumelden (frank.buchli@zuehlke.com)

Beste Grüsse

Frank Buchli

 

 

Posted in Allgemein.