TY  - JOUR
A1  - Zieris, Holger
A1  - Gerstberger, Herbert
A1  - Müller, Wolfgang
T1  - Using Arduino-Based Experiments to Integrate Computer Science Education and Natural Science
JF  - KEYCIT 2014 - Key Competencies in Informatics and ICT
N2  - Current curricular trends require teachers in Baden-
Wuerttemberg (Germany) to integrate Computer Science (CS) into
traditional subjects, such as Physical Science. However, concrete guidelines
are missing. To fill this gap, we outline an approach where a
microcontroller is used to perform and evaluate measurements in the
Physical Science classroom.
Using the open-source Arduino platform, we expect students to acquire
and develop both CS and Physical Science competencies by using a
self-programmed microcontroller. In addition to this combined development
of competencies in Physical Science and CS, the subject matter
will be embedded in suitable contexts and learning environments,
such as weather and climate.
KW  - Computer Science Education
KW  - Natural Science Education
KW  - Inquiry-based Learning
KW  - Physical Science
KW  - Measurement
KW  - Arduino
KW  - Sensors
Y1  - 2015
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-82938
SN  - 1868-0844
SN  - 2191-1940
IS  - 7
SP  - 381
EP  - 389
PB  - Universitätsverlag Potsdam
CY  - Potsdam
ER  - 
TY  - JOUR
A1  - Weigend, Michael
T1  - How Things Work
BT  - Recognizing and Describing Functionality
JF  - KEYCIT 2014 - Key Competencies in Informatics and ICT
N2  - Recognizing and defining functionality is a key competence
adopted in all kinds of programming projects. This study investigates
how far students without specific informatics training are able to identify
and verbalize functions and parameters. It presents observations
from classroom activities on functional modeling in high school chemistry
lessons with altogether 154 students. Finally it discusses the potential
of functional modelling to improve the comprehension of scientific
content.
KW  - Function
KW  - programming
KW  - parameter
KW  - competence
KW  - abstraction
Y1  - 2015
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-82814
SN  - 1868-0844
SN  - 2191-1940
IS  - 7
SP  - 285
EP  - 298
PB  - Universitätsverlag Potsdam
CY  - Potsdam
ER  - 
TY  - JOUR
A1  - Wegner, Christian
A1  - Zender, Raphael
A1  - Lucke, Ulrike
T1  - ProtoSense
BT  - Interactive Paper Prototyping with Multi-Touch Tables
JF  - KEYCIT 2014 - Key Competencies in Informatics and ICT
KW  - Interface design
KW  - paper prototyping
KW  - NUI
Y1  - 2015
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-82970
SN  - 1868-0844
SN  - 2191-1940
IS  - 7
SP  - 405
EP  - 407
PB  - Universitätsverlag Potsdam
CY  - Potsdam
ER  - 
TY  - JOUR
A1  - Webb, Mary
T1  - Considerations for the Design of Computing Curricula
JF  - KEYCIT 2014 - Key Competencies in Informatics and ICT
N2  - This paper originated from discussions about the need for
important changes in the curriculum for Computing including two focus
group meetings at IFIP conferences over the last two years. The
paper examines how recent developments in curriculum, together with
insights from curriculum thinking in other subject areas, especially mathematics
and science, can inform curriculum design for Computing.
The analysis presented in the paper provides insights into the complexity
of curriculum design as well as identifying important constraints and
considerations for the ongoing development of a vision and framework
for a Computing curriculum.
KW  - Curriculum
KW  - Computer Science
KW  - Informatics
KW  - curriculum theory
Y1  - 2015
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-82723
SN  - 1868-0844
SN  - 2191-1940
IS  - 7
SP  - 267
EP  - 283
PB  - Universitätsverlag Potsdam
CY  - Potsdam
ER  - 
TY  - JOUR
A1  - Vierheller, Janine
ED  - Lambrecht, Anna-Lena
ED  - Margaria, Tiziana
T1  - Exploratory Data Analysis
JF  - Process Design for Natural Scientists: an agile model-driven approach
N2  - In bioinformatics the term exploratory data analysis refers to different methods to get an overview of large biological data sets. Hence, it helps to create a framework for further analysis and hypothesis testing. The workflow facilitates this first important step of the data analysis created by high-throughput technologies. The results are different plots showing the structure of the measurements. The goal of the workflow is the automatization of the exploratory data analysis, but also the flexibility should be guaranteed. The basic tool is the free software R.
Y1  - 2014
SN  - 978-3-662-45005-5
SN  - 1865-0929
IS  - 500
SP  - 110
EP  - 126
PB  - Axel Springer Verlag
CY  - Berlin
ER  - 
TY  - JOUR
A1  - Teske, Daniel
T1  - Geocoder accuracy ranking
JF  - Process design for natural scientists: an agile model-driven approach
N2  - Finding an address on a map is sometimes tricky: the chosen map application may be unfamiliar with the enclosed region. There are several geocoders on the market, they have different databases and algorithms to compute the query. Consequently, the geocoding results differ in their quality. Fortunately the geocoders provide a rich set of metadata. The workflow described in this paper compares this metadata with the aim to find out which geocoder is offering the best-fitting coordinate for a given address.
Y1  - 2014
SN  - 978-3-662-45005-5
SN  - 1865-0929
IS  - 500
SP  - 161
EP  - 174
PB  - Springer
CY  - Berlin
ER  - 
TY  - JOUR
A1  - Tavakoli, Hamad
A1  - Alirezazadeh, Pendar
A1  - Hedayatipour, Ava
A1  - Nasib, A. H. Banijamali
A1  - Landwehr, Niels
T1  - Leaf image-based classification of some common bean cultivars using discriminative convolutional neural networks
JF  - Computers and electronics in agriculture : COMPAG online ; an international journal
N2  - In recent years, many efforts have been made to apply image processing techniques for plant leaf identification. However, categorizing leaf images at the cultivar/variety level, because of the very low inter-class variability, is still a challenging task. In this research, we propose an automatic discriminative method based on convolutional neural networks (CNNs) for classifying 12 different cultivars of common beans that belong to three various species. We show that employing advanced loss functions, such as Additive Angular Margin Loss and Large Margin Cosine Loss, instead of the standard softmax loss function for the classification can yield better discrimination between classes and thereby mitigate the problem of low inter-class variability. The method was evaluated by classifying species (level I), cultivars from the same species (level II), and cultivars from different species (level III), based on images from the leaf foreside and backside. The results indicate that the performance of the classification algorithm on the leaf backside image dataset is superior. The maximum mean classification accuracies of 95.86, 91.37 and 86.87% were obtained at the levels I, II and III, respectively. The proposed method outperforms the previous relevant works and provides a reliable approach for plant cultivars identification.
KW  - Bean
KW  - Plant identification
KW  - Digital image analysis
KW  - VGG16
KW  - Loss
KW  - functions
Y1  - 2021
U6  - https://doi.org/10.1016/j.compag.2020.105935
SN  - 0168-1699
SN  - 1872-7107
VL  - 181
PB  - Elsevier
CY  - Amsterdam [u.a.]
ER  - 
TY  - JOUR
A1  - Sysło, Maciej M.
A1  - Kwiatkowska, Anna Beata
T1  - Think logarithmically!
JF  - KEYCIT 2014 - Key Competencies in Informatics and ICT
N2  - We discuss here a number of algorithmic topics which we
use in our teaching and in learning of mathematics and informatics to
illustrate and document the power of logarithm in designing very efficient
algorithms and computations – logarithmic thinking is one of the
most important key competencies for solving real world practical problems.
We demonstrate also how to introduce logarithm independently
of mathematical formalism using a conceptual model for reducing a
problem size by at least half. It is quite surprising that the idea, which
leads to logarithm, is present in Euclid’s algorithm described almost
2000 years before John Napier invented logarithm.
KW  - Logarithm
KW  - binary search
KW  - binary representation
KW  - exponentiation
KW  - Euclid’s algorithm
KW  - Fibonacci numbers
KW  - divide and conquer
KW  - complexity
Y1  - 2015
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-82923
SN  - 1868-0844
SN  - 2191-1940
IS  - 7
SP  - 371
EP  - 380
PB  - Universitätsverlag Potsdam
CY  - Potsdam
ER  - 
TY  - JOUR
A1  - Steinert, Fritjof
A1  - Stabernack, Benno
T1  - Architecture of a low latency H.264/AVC video codec for robust ML based image classification how region of interests can minimize the impact of coding artifacts
JF  - Journal of Signal Processing Systems for Signal, Image, and Video Technology
N2  - The use of neural networks is considered as the state of the art in the field of image classification. A large number of different networks are available for this purpose, which, appropriately trained, permit a high level of classification accuracy. Typically, these networks are applied to uncompressed image data, since a corresponding training was also carried out using image data of similar high quality. However, if image data contains image errors, the classification accuracy deteriorates drastically. This applies in particular to coding artifacts which occur due to image and video compression. Typical application scenarios for video compression are narrowband transmission channels for which video coding is required but a subsequent classification is to be carried out on the receiver side. In this paper we present a special H.264/Advanced Video Codec (AVC) based video codec that allows certain regions of a picture to be coded with near constant picture quality in order to allow a reliable classification using neural networks, whereas the remaining image will be coded using constant bit rate. We have combined this feature with the ability to run with lowest latency properties, which is usually also required in remote control applications scenarios. The codec has been implemented as a fully hardwired High Definition video capable hardware architecture which is suitable for Field Programmable Gate Arrays.
KW  - H.264
KW  - Advanced Video Codec (AVC)
KW  - Low Latency
KW  - Region of Interest
KW  - Machine Learning
KW  - Inference
KW  - FPGA
KW  - Hardware accelerator
Y1  - 2022
U6  - https://doi.org/10.1007/s11265-021-01727-2
SN  - 1939-8018
SN  - 1939-8115
VL  - 94
IS  - 7
SP  - 693
EP  - 708
PB  - Springer
CY  - New York
ER  - 
TY  - JOUR
A1  - Sens, Henriette
T1  - Web-Based map generalization tools put to the test: a jABC workflow
JF  - Process Design for Natural Scientists: an agile model-driven approach
N2  - Geometric generalization is a fundamental concept in the digital mapping process. An increasing amount of spatial data is provided on the web as well as a range of tools to process it. This jABC workflow is used for the automatic testing of web-based generalization services like mapshaper.org by executing its functionality, overlaying both datasets before and after the transformation and displaying them visually in a .tif file. Mostly Web Services and command line tools are used to build an environment where ESRI shapefiles can be uploaded, processed through a chosen generalization service and finally visualized in Irfanview.
Y1  - 2014
SN  - 978-3-662-45005-5
SN  - 1865-0929
IS  - 500
SP  - 175
EP  - 185
PB  - Springer
CY  - Berlin
ER  -