004 Datenverarbeitung; Informatik
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Image feature detection is a key task in computer vision. Scale Invariant Feature Transform (SIFT) is a prevalent and well known algorithm for robust feature detection. However, it is computationally demanding and software implementations are not applicable for real-time performance. In this paper, a versatile and pipelined hardware implementation is proposed, that is capable of computing keypoints and rotation invariant descriptors on-chip. All computations are performed in single precision floating-point format which makes it possible to implement the original algorithm with little alteration. Various rotation resolutions and filter kernel sizes are supported for images of any resolution up to ultra-high definition. For full high definition images, 84 fps can be processed. Ultra high definition images can be processed at 21 fps.
This paper describes the proof calculus LD for clausal propositional logic, which is a linearized form of the well-known DPLL calculus extended by clause learning. It is motivated by the demand to model how current SAT solvers built on clause learning are working, while abstracting from decision heuristics and implementation details. The calculus is proved sound and terminating. Further, it is shown that both the original DPLL calculus and the conflict-directed backtracking calculus with clause learning, as it is implemented in many current SAT solvers, are complete and proof-confluent instances of the LD calculus.
This paper describes the implementation of a workflow model for service-oriented computing of potential areas for wind turbines in jABC. By implementing a re-executable model the manual effort of a multi-criteria site analysis can be reduced. The aim is to determine the shift of typical geoprocessing tools of geographic information systems (GIS) from the desktop to the web. The analysis is based on a vector data set and mainly uses web services of the “Center for Spatial Information Science and Systems” (CSISS). This paper discusses effort, benefits and problems associated with the use of the web services.
Answer Set Programming faces an increasing popularity for problem solving in various domains. While its modeling language allows us to express many complex problems in an easy way, its solving technology enables their effective resolution. In what follows, we detail some of the key factors of its success. Answer Set Programming [ASP; Brewka et al. Commun ACM 54(12):92–103, (2011)] is seeing a rapid proliferation in academia and industry due to its easy and flexible way to model and solve knowledge-intense combinatorial (optimization) problems. To this end, ASP offers a high-level modeling language paired with high-performance solving technology. As a result, ASP systems provide out-off-the-box, general-purpose search engines that allow for enumerating (optimal) solutions. They are represented as answer sets, each being a set of atoms representing a solution. The declarative approach of ASP allows a user to concentrate on a problem’s specification rather than the computational means to solve it. This makes ASP a prime candidate for rapid prototyping and an attractive tool for teaching key AI techniques since complex problems can be expressed in a succinct and elaboration tolerant way. This is eased by the tuning of ASP’s modeling language to knowledge representation and reasoning (KRR). The resulting impact is nicely reflected by a growing range of successful applications of ASP [Erdem et al. AI Mag 37(3):53–68, 2016; Falkner et al. Industrial applications of answer set programming. K++nstliche Intelligenz (2018)]
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.
In this paper we describe the recent state of our research
project concerning computer science teachers’ knowledge on students’
cognition. We did a comprehensive analysis of textbooks, curricula
and other resources, which give teachers guidance to formulate assignments.
In comparison to other subjects there are only a few concepts
and strategies taught to prospective computer science teachers in university.
We summarize them and given an overview on our empirical
approach to measure this knowledge.
This document presents an axiom selection technique for classic first order theorem proving based on the relevance of axioms for the proof of a conjecture. It is based on unifiability of predicates and does not need statistical information like symbol frequency. The scope of the technique is the reduction of the set of axioms and the increase of the amount of provable conjectures in a given time. Since the technique generates a subset of the axiom set, it can be used as a preprocessor for automated theorem proving. This technical report describes the conception, implementation and evaluation of ARDE. The selection method, which is based on a breadth-first graph search by unifiability of predicates, is a weakened form of the connection calculus and uses specialised variants or unifiability to speed up the selection. The implementation of the concept is evaluated with comparison to the results of the world championship of theorem provers of the year 2012 (CASC J6). It is shown that both the theorem prover leanCoP which uses the connection calculus and E which uses equality reasoning, can benefit from the selection approach. Also, the evaluation shows that the concept is applyable for theorem proving problems with thousands of formulae and that the selection is independent from the calculus used by the theorem prover.
BugHunt
(2015)
Competencies related to operating systems and computer
security are usually taught systematically. In this paper we present
a different approach, in which students have to remove virus-like
behaviour on their respective computers, which has been induced by
software developed for this purpose. They have to develop appropriate
problem-solving strategies and thereby explore essential elements of
the operating system. The approach was implemented exemplarily in
two computer science courses at a regional general upper secondary
school and showed great motivation and interest in the participating
students.
Student teachers often struggle to keep track of everything that is happening in the classroom, and particularly to notice and respond when students cause disruptions. The complexity of the classroom environment is a potential contributing factor that has not been empirically tested. In this experimental study, we utilized a virtual reality (VR) classroom to examine whether classroom complexity affects the likelihood of student teachers noticing disruptions and how they react after noticing. Classroom complexity was operationalized as the number of disruptions and the existence of overlapping disruptions (multidimensionality) as well as the existence of parallel teaching tasks (simultaneity). Results showed that student teachers (n = 50) were less likely to notice the scripted disruptions, and also less likely to respond to the disruptions in a comprehensive and effortful manner when facing greater complexity. These results may have implications for both teacher training and the design of VR for training or research purpose. This study contributes to the field from two aspects: 1) it revealed how features of the classroom environment can affect student teachers' noticing of and reaction to disruptions; and 2) it extends the functionality of the VR environment-from a teacher training tool to a testbed of fundamental classroom processes that are difficult to manipulate in real-life.
Solving problems combining task and motion planning requires searching across a symbolic search space and a geometric search space. Because of the semantic gap between symbolic and geometric representations, symbolic sequences of actions are not guaranteed to be geometrically feasible. This compels us to search in the combined search space, in which frequent backtracks between symbolic and geometric levels make the search inefficient.We address this problem by guiding symbolic search with rich information extracted from the geometric level through culprit detection mechanisms.
The paper presents two approaches to the development of
a Computer Science Competence Model for the needs of curriculum
development and evaluation in Higher Education. A normativetheoretical
approach is based on the AKT and ACM/IEEE curriculum
and will be used within the recommendations of the German
Informatics Society (GI) for the design of CS curricula. An empirically
oriented approach refines the categories of the first one with regard to
specific subject areas by conducting content analysis on CS curricula of
important universities from several countries. The refined model will be
used for the needs of students’ e-assessment and subsequent affirmative
action of the CS departments.
Computational Thinking
(2015)
Digital technology has radically changed the way people
work in industry, finance, services, media and commerce. Informatics
has contributed to the scientific and technological development of our
society in general and to the digital revolution in particular. Computational
thinking is the term indicating the key ideas of this discipline that
might be included in the key competencies underlying the curriculum
of compulsory education. The educational potential of informatics has
a history dating back to the sixties. In this article, we briefly revisit this
history looking for lessons learned. In particular, we focus on experiences
of teaching and learning programming. However, computational
thinking is more than coding. It is a way of thinking and practicing interactive
dynamic modeling with computers. We advocate that learners
can practice computational thinking in playful contexts where they can
develop personal projects, for example building videogames and/or robots,
share and discuss their construction with others. In our view, this
approach allows an integration of computational thinking in the K-12
curriculum across disciplines.
This talk will describe My Digital Life (TU100), a distance learning module that introduces computer science through immediate engagement with ubiquitous computing (ubicomp). This talk will describe some of the principles and concepts we have adopted for this modern computing introduction: the idea of the ‘informed digital citizen’; engagement through narrative; playful pedagogy; making the power of ubicomp available to novices; setting technical skills in real contexts. It will also trace how the pedagogy is informed by experiences and research in Computer Science education.
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.
In this project I constructed a workflow that takes a DNA sequence as input and provides a phylogenetic tree, consisting of the input sequence and other sequences which were found during a database search. In this phylogenetic tree the sequences are arranged depending on similarities. In bioinformatics, constructing phylogenetic trees is often used to explore the evolutionary relationships of genes or organisms and to understand the mechanisms of evolution itself.
In the geoinformatics field, remote sensing data is often used for analyzing the characteristics of the current investigation area. This includes DEMs, which are simple raster grids containing grey scales representing the respective elevation values. The project CREADED that is presented in this paper aims at making these monochrome raster images more significant and more intuitively interpretable. For this purpose, an executable interactive model for creating a colored and relief-shaded Digital Elevation Model (DEM) has been designed using the jABC framework. The process is based on standard jABC-SIBs and SIBs that provide specific GIS functions, which are available as Web services, command line tools and scripts.
Through the use of next generation sequencing (NGS) technology, a lot of newly sequenced organisms are now available. Annotating those genes is one of the most challenging tasks in sequence biology. Here, we present an automated workflow to find homologue proteins, annotate sequences according to function and create a three-dimensional model.
The aim of our project design space exploration with answer set programming is to develop a general framework based on Answer Set Programming (ASP) that finds valid solutions to the system design problem and simultaneously performs Design Space Exploration (DSE) to find the most favorable alternatives. We leverage recent developments in ASP solving that allow for tight integration of background theories to create a holistic framework for effective DSE.
M-rate 0L systems are interactionless Lindenmayer systems together with a function assigning to every string a set of multisets of productions that may be applied simultaneously to the string. Some questions that have been left open in the forerunner papers are examined, and the computational power of deterministic M-rate 0L systems is investigated, where also tabled and extended variants are taken into consideration.
Participants of this workshop will be confronted exemplarily
with a considerable inconsistency of global Informatics education at
lower secondary level. More importantly, they are invited to contribute
actively on this issue in form of short case studies of their countries.
Until now, very few countries have been successful in implementing
Informatics or Computing at primary and lower secondary level. The
spectrum from digital literacy to informatics, particularly as a discipline
in its own right, has not really achieved a breakthrough and seems to
be underrepresented for these age groups. The goal of this workshop
is not only to discuss the anamnesis and diagnosis of this fragmented
field, but also to discuss and suggest viable forms of therapy in form of
setting educational standards. Making visible good practices in some
countries and comparing successful approaches are rewarding tasks for
this workshop.
Discussing and defining common educational standards on a transcontinental
level for the age group of 14 to 15 years old students in a readable,
assessable and acceptable form should keep the participants of this
workshop active beyond the limited time at the workshop.
In the project MoKoM, which is funded by the German
Research Foundation (DFG) from 2008 to 2012, a test instrument
measuring students’ competences in computer science was developed.
This paper presents the results of an expert rating of the levels of
students’ competences done for the items of the instrument.
At first we will describe the difficulty-relevant features that were
used for the evaluation. These were deduced from computer science,
psychological and didactical findings and resources. Potentials and
desiderata of this research method are discussed further on. Finally
we will present our conclusions on the results and give an outlook on
further steps.
Exploratory Data Analysis
(2014)
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.
Geocoder accuracy ranking
(2014)
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.
GraffDok is an application helping to maintain an overview over sprayed images somewhere in a city. At the time of writing it aims at vandalism rather than at beautiful photographic graffiti in an underpass. Looking at hundreds of tags and scribbles on monuments, house walls, etc. it would be interesting to not only record them in writing but even make them accessible electronically, including images.
GraffDok’s workflow is simple and only requires an EXIF-GPS-tagged photograph of a graffito. It automatically determines its location by using reverse geocoding with the given GPS-coordinates and the Gisgraphy WebService. While asking the user for some more meta data, GraffDok analyses the image in parallel with this and tries to detect fore- and background – before extracting the drawing lines and make them stand alone. The command line based tool ImageMagick is used here as well as for accessing EXIF data.
Any meta data is written to csv-files, which will stay easily accessible and can be integrated in TeX-files as well. The latter ones are converted to PDF at the end of the workflow, containing a table about all graffiti and a summary for each – including the generated characteristic graffiti pattern image.
How does the Implementation of a Literacy Learning Tool Kit influence Literacy Skill Acquisition?
(2015)
This study aimed at following how teachers transfer skills
into results while using ABRA literacy software. This was done in
the second part of the pilot study whose aim was to provide equity to
control group teachers and students by exposing them to the ABRACADABRA
treatment after the end of phase 1. This opportunity was
used to follow the phase 1 teachers to see how the skills learned were
being transformed into results. A standard three-day initial training and
planning session on how to use ABRA to teach literacy was held at the
beginning of each phase for ABRA teachers (phase 1 experimental and
phase 2 delayed ABRA). Teachers were provided with teaching materials
including a tentative ABRA curriculum developed to align with the
Kenyan English Language requirements for year 1 and 3 students. Results
showed that although there was no significant difference between
the groups in vocabulary-related subscales which include word reading
and meaning as well as sentence comprehension, students in ABRACADABRA
classes improved their scores at a significantly higher rate
than students in control classes in comprehension related scores. An
average student in the ABRACADABRA group improved by 12 and
16 percentile points respectively compared to their counterparts in the
control group.
How Things Work
(2015)
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.
This paper discusses results from a small-scale research
study, together with some recently published research into student
perceptions of ICT for learning in schools, to consider relevant skills
that do not appear to currently being taught. The paper concludes by
raising three issues relating to learning with and through ICT that need
to be addressed in school curricula and classroom teaching.
With the jABC it is possible to realize workflows for numerous questions in different fields. The goal of this project was to create a workflow for the identification of differentially expressed genes. This is of special interest in biology, for it gives the opportunity to get a better insight in cellular changes due to exogenous stress, diseases and so on. With the knowledge that can be derived from the differentially expressed genes in diseased tissues, it becomes possible to find new targets for treatment.
The objectives of this study were to examine (a) the effect
of dynamic assessment (DA) in a 3D Immersive Virtual Reality
(IVR) environment as compared with computerized 2D and noncomputerized
(NC) situations on cognitive modifiability, and (b) the
transfer effects of these conditions on more difficult problem solving
administered two weeks later in a non-computerized environment. A
sample of 117 children aged 6:6-9:0 years were randomly assigned
into three experimental groups of DA conditions: 3D, 2D, and NC, and
one control group (C). All groups received the pre- and post-teaching
Analogies subtest of the Cognitive Modifiability Battery (CMB-AN).
The experimental groups received a teaching phase in conditions similar
to the pre-and post-teaching phases. The findings showed that cognitive
modifiability, in a 3D IVR, was distinctively higher than in the two
other experimental groups (2D computer group and NC group). It was
also found that the 3D group showed significantly higher performance
in transfer problems than the 2D and NC groups.
The paper discusses the issue of supporting informatics
(computer science) education through competitions for lower and
upper secondary school students (8–19 years old). Competitions play
an important role for learners as a source of inspiration, innovation,
and attraction. Running contests in informatics for school students
for many years, we have noticed that the students consider the contest
experience very engaging and exciting as well as a learning experience.
A contest is an excellent instrument to involve students in problem
solving activities. An overview of infrastructure and development
of an informatics contest from international level to the national one
(the Bebras contest on informatics and computer fluency, originated
in Lithuania) is presented. The performance of Bebras contests in 23
countries during the last 10 years showed an unexpected and unusually
high acceptance by school students and teachers. Many thousands of
students participated and got a valuable input in addition to their regular
informatics lectures at school. In the paper, the main attention is paid
to the developed tasks and analysis of students’ task solving results in
Lithuania.
Physical computing covers the design and realization of interactive
objects and installations and allows students to develop concrete,
tangible products of the real world that arise from the learners’
imagination. This way, constructionist learning is raised to a level that
enables students to gain haptic experience and thereby concretizes the
virtual. In this paper the defining characteristics of physical computing
are described. Key competences to be gained with physical computing
will be identified.
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.
Lessons Learned
(2014)
This chapter summarizes the experience and the lessons we learned concerning the application of the jABC as a framework for design and execution of scientific workflows. It reports experiences from the domain modeling (especially service integration) and workflow design phases and evaluates the resulting models statistically with respect to the SIB library and hierarchy levels.
Let’s talk about CS!
(2015)
To communicate about a science is the most important key
competence in education for any science. Without communication we
cannot teach, so teachers should reflect about the language they use in
class properly. But the language students and teachers use to communicate
about their CS courses is very heterogeneous, inconsistent and
deeply influenced by tool names. There is a big lack of research and
discussion in CS education regarding the terminology and the role of
concepts and tools in our science. We don’t have a consistent set of
terminology that we agree on to be helpful for learning our science.
This makes it nearly impossible to do research on CS competencies as
long as we have not agreed on the names we use to describe these. This
workshop intends to provide room to fill with discussion and first ideas
for future research in this field.
Location analyses are among the most common tasks while working with spatial data and geographic information systems. Automating the most frequently used procedures is therefore an important aspect of improving their usability. In this context, this project aims to design and implement a workflow, providing some basic tools for a location analysis. For the implementation with jABC, the workflow was applied to the problem of finding a suitable location for placing an artificial reef. For this analysis three parameters (bathymetry, slope and grain size of the ground material) were taken into account, processed, and visualized with the The Generic Mapping Tools (GMT), which were integrated into the workflow as jETI-SIBs. The implemented workflow thereby showed that the approach to combine jABC with GMT resulted in an user-centric yet user-friendly tool with high-quality cartographic outputs.
Machine learning for improvement of thermal conditions inside a hybrid ventilated animal building
(2021)
In buildings with hybrid ventilation, natural ventilation opening positions (windows), mechanical ventilation rates, heating, and cooling are manipulated to maintain desired thermal conditions. The indoor temperature is regulated solely by ventilation (natural and mechanical) when the external conditions are favorable to save external heating and cooling energy. The ventilation parameters are determined by a rule-based control scheme, which is not optimal. This study proposes a methodology to enable real-time optimum control of ventilation parameters. We developed offline prediction models to estimate future thermal conditions from the data collected from building in operation. The developed offline model is then used to find the optimal controllable ventilation parameters in real-time to minimize the setpoint deviation in the building. With the proposed methodology, the experimental building's setpoint deviation improved for 87% of time, on average, by 0.53 degrees C compared to the current deviations.
Mentoring in a Digital World
(2015)
This paper focuses on the results of the evaluation of the first
pilot of an e-mentoring unit designed by the Hands-On ICT consortium,
funded by the EU LLL programme. The overall aim of this two-year
activity is to investigate the value for professional learning of Massive
Online Open Courses (MOOCs) and Community Online Open Courses
(COOCs) in the context of a ‘community of practice’. Three units in the
first pilot covered aspects of using digital technologies to develop creative
thinking skills. The findings in this paper relate to the fourth unit
about e-mentoring, a skill that was important to delivering the course
content in the other three units. Findings about the e-mentoring unit
included: the students’ request for detailed profiles so that participants
can get to know each other; and, the need to reconcile the different
interpretations of e-mentoring held by the participants when the course
begins. The evaluators concluded that the major issues were that: not all
professional learners would self-organise and network; and few would
wish to mentor their colleagues voluntarily. Therefore, the e-mentoring
issues will need careful consideration in pilots two and three to identify
how e-mentoring will be organised.
We summarize here the main characteristics and features of the jABC framework, used in the case studies as a graphical tool for modeling scientific processes and workflows. As a comprehensive environment for service-oriented modeling and design according to the XMDD (eXtreme Model-Driven Design) paradigm, the jABC offers much more than the pure modeling capability. Associated technologies and plugins provide in fact means for a rich variety of supporting functionality, such as remote service integration, taxonomical service classification, model execution, model verification, model synthesis, and model compilation. We describe here in short both the essential jABC features and the service integration philosophy followed in the environment. In our work over the last years we have seen that this kind of service definition and provisioning platform has the potential to become a core technology in interdisciplinary service orchestration and technology transfer: Domain experts, like scientists not specially trained in computer science, directly define complex service orchestrations as process models and use efficient and complex domain-specific tools in a simple and intuitive way.
As a result of the Bologna reform of educational systems in
Europe the outcome orientation of learning processes, competence-oriented
descriptions of the curricula and competence-oriented assessment
procedures became standard also in Computer Science Education
(CSE). The following keynote addresses important issues of shaping
a CSE competence model especially in the area of informatics system
comprehension and object-oriented modelling. Objectives and research
methodology of the project MoKoM (Modelling and Measurement
of Competences in CSE) are explained. Firstly, the CSE competence
model was derived based on theoretical concepts and then secondly the
model was empirically examined and refined using expert interviews.
Furthermore, the paper depicts the development and examination of
a competence measurement instrument, which was derived from the
competence model. Therefore, the instrument was applied to a large
sample of students at the gymnasium’s upper class level. Subsequently,
efforts to develop a competence level model, based on the retrieved empirical
results and on expert ratings are presented. Finally, further demands
on research on competence modelling in CSE will be outlined.
A project involving the composition of a number of pieces
of music by public participants revealed levels of engagement with and
mastery of complex music technologies by a number of secondary student
volunteers. This paper reports briefly on some initial findings of
that project and seeks to illuminate an understanding of computational
thinking across the curriculum.
In control theory, to solve a finite-horizon sequential decision problem (SDP) commonly means to find a list of decision rules that result in an optimal expected total reward (or cost) when taking a given number of decision steps. SDPs are routinely solved using Bellman's backward induction. Textbook authors (e.g. Bertsekas or Puterman) typically give more or less formal proofs to show that the backward induction algorithm is correct as solution method for deterministic and stochastic SDPs. Botta, Jansson and Ionescu propose a generic framework for finite horizon, monadic SDPs together with a monadic version of backward induction for solving such SDPs. In monadic SDPs, the monad captures a generic notion of uncertainty, while a generic measure function aggregates rewards. In the present paper, we define a notion of correctness for monadic SDPs and identify three conditions that allow us to prove a correctness result for monadic backward induction that is comparable to textbook correctness proofs for ordinary backward induction. The conditions that we impose are fairly general and can be cast in category-theoretical terms using the notion of Eilenberg-Moore algebra. They hold in familiar settings like those of deterministic or stochastic SDPs, but we also give examples in which they fail. Our results show that backward induction can safely be employed for a broader class of SDPs than usually treated in textbooks. However, they also rule out certain instances that were considered admissible in the context of Botta et al. 's generic framework. Our development is formalised in Idris as an extension of the Botta et al. framework and the sources are available as supplementary material.
We introduce a new measure of descriptional complexity on finite automata, called the number of active states. Roughly speaking, the number of active states of an automaton A on input w counts the number of different states visited during the most economic computation of the automaton A for the word w. This concept generalizes to finite automata and regular languages in a straightforward way. We show that the number of active states of both finite automata and regular languages is computable, even with respect to nondeterministic finite automata. We further compare the number of active states to related measures for regular languages. In particular, we show incomparability to the radius of regular languages and that the difference between the number of active states and the total number of states needed in finite automata for a regular language can be of exponential order.
plasp 3
(2019)
We describe the new version of the Planning Domain Definition Language (PDDL)-to-Answer Set Programming (ASP) translator plasp. First, it widens the range of accepted PDDL features. Second, it contains novel planning encodings, some inspired by Satisfiability Testing (SAT) planning and others exploiting ASP features such as well-foundedness. All of them are designed for handling multivalued fluents in order to capture both PDDL as well as SAS planning formats. Third, enabled by multishot ASP solving, it offers advanced planning algorithms also borrowed from SAT planning. As a result, plasp provides us with an ASP-based framework for studying a variety of planning techniques in a uniform setting. Finally, we demonstrate in an empirical analysis that these techniques have a significant impact on the performance of ASP planning.
The study reported in this paper involved the employment
of specific in-class exercises using a Personal Response System (PRS).
These exercises were designed with two goals: to enhance students’
capabilities of tracing a given code and of explaining a given code in
natural language with some abstraction. The paper presents evidence
from the actual use of the PRS along with students’ subjective impressions
regarding both the use of the PRS and the special exercises. The
conclusions from the findings are followed with a short discussion on
benefits of PRS-based mental processing exercises for learning programming
and beyond.
The protein classification workflow described in this report enables users to get information about a novel protein sequence automatically. The information is derived by different bioinformatic analysis tools which calculate or predict features of a protein sequence. Also, databases are used to compare the novel sequence with known proteins.
ProtoSense
(2015)