pinecone/core-2020-05-10-deduplication huggingface dataset:
Push-Pull Block Puzzles are Hard

This paper proves that push-pull block puzzles in 3D are PSPACE-complete to
solve, and push-pull block puzzles in 2D with thin walls are NP-hard to solve,
settling an open question by Zubaran and Ritt. Push-pull block puzzles are a
type of recreational motion planning problem, similar to Sokoban, that involve
moving a `robot' on a square grid with $1 \times 1$ obstacles. The obstacles
cannot be traversed by the robot, but some can be pushed and pulled by the
robot into adjacent squares. Thin walls prevent movement between two adjacent
squares. This work follows in a long line of algorithms and complexity work on
similar problems. The 2D push-pull block puzzle shows up in the video games
Pukoban as well as The Legend of Zelda: A Link to the Past, giving another
proof of hardness for the latter. This variant of block-pushing puzzles is of
particular interest because of its connections to reversibility, since any
action (e.g., push or pull) can be inverted by another valid action (e.g., pull
or push).Comment: Full version of CIAC 2017 paper. 17 page
Congestion Games with Complementarities

We study a model of selfish resource allocation that seeks to incorporate
dependencies among resources as they exist in modern networked environments.
Our model is inspired by utility functions with constant elasticity of
substitution (CES) which is a well-studied model in economics. We consider
congestion games with different aggregation functions. In particular, we study
$L_p$ norms and analyze the existence and complexity of (approximate) pure Nash
equilibria. Additionally, we give an almost tight characterization based on
monotonicity properties to describe the set of aggregation functions that
guarantee the existence of pure Nash equilibria.Comment: The final publication is available at Springer via
  http://dx.doi.org/10.1007/978-3-319-57586-5_1
On the complexity of finding a potential community

An independent 2-clique of a graph is a subset of vertices that is an independent set and such that any two vertices inside have a common neighbor outside. In this paper, we study the complexity of find-ing an independent 2-clique of maximum size in several graph classes and we compare its complexity with the complexity of maximum independent set. We prove that this problem is NP-hard on apex graphs, APX-hard on line graphs, not n1 /2−-approximable on bipartite graphs and not-approximable on split graphs, while it is polynomial-time solvable on graphs of bounded degree and their complements, graphs of bounded treewidth, planar graphs, (C3, C6)-free graphs, threshold graphs, interval graphs and cographs. © Springer International Publishing AG 2017
Inoculating an agile company with user-centred design: an empirical study

We present an empirical study on facilitating the adoption of user-centred design (UCD) in small Agile companies. To this end, we introduced a curated set of qualitative design practices in an Agile organisation, engaging developers in a lightweight series of workshops. Our results suggest that the approach followed enhanced internal communication and promoted a concrete shift towards a more user-centred perspective. However, the presence of a predominant non-Agile customer seems to have limited potential benefits. Â© The Author(s) 2017
Application of trajectory clustering for determining the source\ud
regions of secondary inorganic aerosols measured at K-puszta\ud
background monitoring station, Hungary

Understanding the formation process of atmospheric particles is vital be-cause of the significant impact of particulate matter on human health and climate change. Atmospheric particles can be formed by nucleation process via a number of different mechanisms, such as binary nucleation (involving H2SO4 and water va-pour), ternary nucleation (involving NH3, H2SO4 and water vapour) and ion-induced nucleation for charged particles, depending on the environmental conditions. Parti-cle formation increases the total number concentration of ambient submicron parti-cles and contributes thereby to climate forcing. The transformation processes of new particle formation (NPF) and secondary organic aerosol have been studied. It was found that gaseous sulphuric acid, ammonia, and organic compounds are important precursors to NPF events and H2SO4-NH3-H2O ternary nucleation is one of the im-portant mechanisms. Using cluster analysis on the backward trajectories makes it possible to identify the most relevant types of air mass transport routes, and the directions from where precursor gases are transported. The influence of synoptic-scale atmospheric transport patterns on observed levels of sulphate, nitrate and am-monium has been examined
A Core Model for Choreographic Programming

Choreographic Programming is a programming paradigm for building concurrent
programs that are deadlock-free by construction, as a result of programming
communications declaratively and then synthesising process implementations
automatically. Despite strong interest on choreographies, a foundational model
that explains which computations can be performed with the hallmark constructs
of choreographies is still missing.
  In this work, we introduce Core Choreographies (CC), a model that includes
only the core primitives of choreographic programming. Every computable
function can be implemented as a choreography in CC, from which we can
synthesise a process implementation where independent computations run in
parallel. We discuss the design of CC and argue that it constitutes a canonical
model for choreographic programming
Compositionality, Decompositionality and Refinement in Input/Output
  Conformance Testing - Technical Report

We propose an input/output conformance testing theory utilizing Modal
Interface Automata with Input Refusals (IR-MIA) as novel behavioral formalism
for both the specification and the implementation under test. A modal
refinement relation on IR-MIA allows distinguishing between obligatory and
allowed output behaviors, as well as between implicitly underspecified and
explicitly forbidden input behaviors. The theory therefore supports positive
and negative conformance testing with optimistic and pessimistic environmental
assumptions. We further show that the resulting conformance relation on IR-MIA,
called modal-irioco, enjoys many desirable properties concerning
component-based behaviors. First, modal-irioco is preserved under modal
refinement and constitutes a preorder under certain restrictions which can be
ensured by a canonical input completion for IR-MIA. Second, under the same
restrictions, modal-irioco is compositional with respect to parallel
composition of IR-MIA with multi-cast and hiding. Finally, the quotient
operator on IR-MIA, as the inverse to parallel composition, facilitates
decompositionality in conformance testing to solve the unknown-component
problem.Comment: 36 pages, 14 figure
Progression and Forecast of a Curated Web-of-Trust: A Study on the Debian Project's Cryptographic Keyring

The Debian project is one of the largest free software undertakings worldwide. It is geographically distributed, and participation in the project is done on a voluntary basis, without a single formal employee or directly funded person. As we will explain, due to the nature of the project, its authentication needs are very strict — User/password schemes are way surpassed, and centralized trust management schemes such as PKI are not compatible with its distributed and flat organization; fully decentralized schemes such as the PGP Web of Trust are insuficient by themselves. The Debian project has solved this need by using what we termed a ``curated Web of Trust''.\ud
\ud
We will explain some lessons learned from a massive key migration process that was triggered in 2014. We will present the social insight we have found from examining the relationships expressed as signatures in this curated Web of Trust, some recommendations on personal key-signing policies, and a statistical study and forecast on aging, refreshment and survival of project participants stemming from an analysis on their key-handling
Assessing Code Authorship: The Case of the Linux Kernel

Code authorship is a key information in large-scale open source systems.
Among others, it allows maintainers to assess division of work and identify key
collaborators. Interestingly, open-source communities lack guidelines on how to
manage authorship. This could be mitigated by setting to build an empirical
body of knowledge on how authorship-related measures evolve in successful
open-source communities. Towards that direction, we perform a case study on the
Linux kernel. Our results show that: (a) only a small portion of developers (26
%) makes significant contributions to the code base; (b) the distribution of
the number of files per author is highly skewed --- a small group of top
authors (3 %) is responsible for hundreds of files, while most authors (75 %)
are responsible for at most 11 files; (c) most authors (62 %) have a specialist
profile; (d) authors with a high number of co-authorship connections tend to
collaborate with others with less connections.Comment: Accepted at 13th International Conference on Open Source Systems
  (OSS). 12 page
A First Step Towards Synthesising Rubrics and Video for the Formative Assessment of Complex Skills

Abstract. The performance objectives used for the formative assessment of com- plex skills are generally set through text-based analytic rubrics[1]. Moreover, video modeling examples are a widely applied method of observational learning, providing students with context-rich modeling examples of complex skills that act as an analogy for problem solving [1]. The purpose of this theoretical paper is to synthesize the components of video modeling and rubrics to support the formative assessment of complex skills. Based on theory, we argue that application of the developed Video Enhanced Rubrics (VER) fosters learners’ development of mental models, quality of provided feedback by various actors and finally, the learners mastery of complex skills.We would like to gratefully acknowledge the contribution of the Viewbrics project, that is funded by the practice-oriented research pro- gramme of the Netherlands Initiative for Education Research (NRO), part of The Netherlands Organisation for Scientific Research (NWO)
Prediction of difficulty levels in video games from ongoing EEG

Real-time assessment of mental workload from EEG plays an important role in enhancing symbiotic interaction of human operators in immersive environments. In this study we thus aimed at predicting the difficulty level of a video game a person is playing at a particular moment from the ongoing EEG activity. Therefore, we made use of power modulations in the theta (4–7 Hz) and alpha (8–13 Hz) frequency bands of the EEG which are known to reflect cognitive workload. Since the goal was to predict from multiple difficulty levels, established binary classification approaches are futile. Here, we employ a novel spatial filtering method (SPoC) that finds spatial filters such that their corresponding bandpower dynamics maximally covary with a given target variable, in this case the difficulty level. EEG was recorded from 6 participants playing a modified Tetris game at 10 different difficulty levels. We found that our approach predicted the levels with high accuracy, yielding a mean prediction error of less than one level.EC/FP7/611570/EU/Symbiotic Mind Computer Interaction for Information Seeking/MindSeeBMBF, 01GQ0850, Verbundprojekt: Bernstein Fokus Neurotechnologie - Nichtinvasive Neurotechnologie für Mensch-Maschine Interaktio
Total Immersion: Designing for Affective Symbiosis in a Virtual Reality Game with Haptics, Biosensors, and Emotive Agents

Affective symbiosis for human–computer interaction refers to the dynamic relationship between the user and affective virtual agents. In order to facilitate a true, immersive experience, we believe that it is necessary to adapt the presentation of an affective agent to the user’s affective state. Investigating the experience, behavior, and physiological correlates of affective events, such as winning and losing during a competitive game, therefore might be used to adapt the agent’s emotional states and system events. An experimental virtual reality game environment was designed as a stepping stone toward a system to demonstrate affective symbiosis. Users were invited to play a game of air hockey with affective agents in virtual reality. We collected the electrocardiography, electrodermal activity, and postural data, as well as self-reports, to investigate how emotional events affected physiology, behavior, and experience. The users were found to be engaged in the competition strongly while only paying limited attention to their adversaries’ emotional expressions. We discuss how game events are much stronger causes for affective responses, with the physiological effects of winning and losing becoming more enhanced as the game progresses. We discuss how an affective, symbiotic system could implement both game events and dynamic, affective agents to create a system for total immersion
Maritime cognitive workload assessment

The human factor plays the key role for safety in many industrial and civil every-day operations in our technologized world. Human failure is more likely to cause accidents than technical failure, e.g. in the challenging job of tugboat captains. Here, cognitive workload is crucial, as its excess is a main cause of dangerous situations and accidents while being highly participant and situation dependent. However, knowing the captain’s level of workload can help to improve man-machine interaction. The main contributions of this paper is a successful workload indication and a transfer of cognitive workload knowledge from laboratory to realistic settings
Landsat surface temperature data analysis for urban heat resilience: case study of Adelaide

Meeting: CUPUM 2017: 15th International Conference on Computers in Urban Planning and Urban Management (11-14 July 2017 Adelaide, Australia )Smarter urban futures require resilient built environment in the context of climate change. This chapter demonstrates the application of satellite-based surface cover and temperature data to support planning for urban heat resilience. Landsat 7 ETM+ and Landsat 8 data is used to analyse the correlation of urban surface covers to the urban heat island effect in Adelaide. Methods for data source selection, surface cover classification, surface temperature calculation and analysis are detailed in this chapter. Results indicate that tree canopy and surface water covers had the least surface temperature variations in mesoscale. The average minimum surface temperature of tree canopy cover was 2.79 °C lower than asphalt and 4.74 °C lower than paved areas. Freely available satellite urban surface temperature data can assist urban planning authorities in planning heat resilient urban spaces for smarter urban futures in the context of climate change.Ehsan Sharifi, Alpana Sivam, Sadasivam Karuppannan and John W Bolan
Smart is a matter of context

Smart cities involve, in a large scale, a wide array of interconnected components and agents, giving birth to large and heterogeneous data flows. They are inherently cross-disciplinary, provide interesting challenges, and constitute a very promising field for future urban developments, such as smart grids, eco-feedback, intelligent traffic control, and so on. We advocate that the key to these challenges is the proper modelling and exploitation of context. However, said context is highly dynamic and mainly unpredictable. Improved AI and machine learning techniques are required. Starting from some of the main smart cities features, this paper highlights the key challenges, explains why handling context is crucial to them, and gives some insights to address them, notably with multi-agent systems
Towards Contextualizing Community Detection in Dynamic Social Networks

With the growing number of users and the huge amount of information in dynamic social networks, contextualizing community detection has been a challenging task. Thus, modeling these social networks is a key issue for the process of contextualized community detection. In this work, we propose a temporal multiplex information graph-based model to represent dynamic social networks: we consider simultaneously the social network dynamicity, its structure (different social connections) and various members’ profiles so as to calculate similarities between “nodes” in each specific context. Finally a comparative study on a real social network shows the efficiency of our approach and illustrates practical uses
Unified Modeling of Quality of Context and Quality of Situation for Context-Aware Applications in the Internet of Things

This paper discusses the requirements of situation identification in the Internet of Things and the necessity to consider the quality of the input context data during the inference process for deriving a situation and evaluating its resulting quality. We propose to extend previous works by integrating the QoCIM meta-model within the muSIC framework dedicated to situation identification. Situation identification is derived using an ontological approach and Quality criteria are aggregated using the fuzzy Choquet operator for computing the quality of a situation. This paper shows that QoCIM allows to model quality of context (QoC) as well as quality of situation in a unified approach
Elaborating the Context Calculator: A Design Experiment in Geothermy

Abstract. This paper presents a research project in science education that is positioned at the intersection of computer science and context in learning. The main objective is to improve learning process by creating a software tool that participates, from the inception to the achievement, in the design of leaning scenarios, based on context effects, and, to show that context effects’ learning is an efficient method in the development of student’s knowledge regarding a concept. The software will\ud
compute differences between two – or more – external contexts based on specific parameters, related to the phenomenon or object that students are expected to study. The elaboration of the calculator (“the MazCalc”) is conducted using the design based research theory, meaning that several iterations of learning field experiments are conducted in order to collect relevant data which are used for the tool creation. In this paper, the design of the scenario involves students from North America and from the French West Indies and the concept studied is about geothermal energy. The instantiation of the context calculator is made with the geothermal object of study, and the differences are computed in the calculator between the two contexts mentioned. This example makes possible to validate the link between context effects predicted and observed, and also to study the impact of external context on the learning process. This study has been conducted thanks to the GEOTREF project support. Keywords : Modelling, Context, Science Education, Learning, Context Effects,\ud
Geotherm
The DBR Methodology for the Study of Context in Learning

In the Design-Based Research (DBR) methodology, the process is as im-portant as the product, and each iteration is considered a sub-result leading to the next one. This methodology is being used in the TEE project, to both study and elaborate solutions for Learning in Context. This paper describes the origins of the project, as well as the steps taken to conduct it, with a perspective for future work. The DBR methodology is presented as applied in the TEEC project (TEEC= Tech-nologies Educatives et Enseignement en Contexte).\ud
Keywords: Design-Based Research, DBR, Methodology, Modelling, Context, Learning, Intelligent Tutoring System
Getting the Priorities Right: Saturation for Prioritised Petri Nets

Prioritised Petri net is a powerful modelling language that often \ud
constitutes the core of even more expressive modelling languages such as \ud
GSPNs (Generalized Stochastic Petri nets). The saturation state space \ud
traversal algorithm has proved to be efficient for non-prioritised \ud
concurrent models. Previous works showed that priorities may be encoded into \ud
the transition relation, but doing so defeats the main idea of saturation by \ud
spoiling the locality of transitions. This paper presents an extension of \ud
saturation to natively handle priorities by considering the priority-related \ud
enabledness of transitions separately, adopting the idea of constrained \ud
saturation. To encode the highest priority of enabled transitions in every \ud
state we introduce edge-valued interval decision diagrams. We show that in \ud
case of Petri nets, this data structure can be constructed offline. \ud
According to preliminary measurements, the proposed solution scales better \ud
than previously known matrix decision diagram-based approaches, paving the \ud
way towards efficient stochastic analysis of GSPNs and the model checking of \ud
prioritised models
Accelerating Hash-Based Query Processing Operations on FPGAs by a Hash Table Caching Technique

Extracting valuable information from the rapidly growing field of Big Data faces serious performance constraints, especially in the software-based database management systems (DBMS). In a query processing system, hash-based computational primitives such as the hash join and the group-by are the most time-consuming operations, as they frequently need to access the hash table on the high-latency off-chip memories and also to traverse whole the table. Subsequently, the hash collision is an inherent issue related to the hash tables, which can adversely degrade the overall performance.\ud
In order to alleviate this problem, in this paper, we present a novel pure hardware-based hash engine, implemented on the FPGA. In order to mitigate the high memory access latencies and also to faster resolve the hash collisions, we follow a novel design point. It is based on caching the hash table entries in the fast on-chip Block-RAMs of FPGA. Faster accesses to the correspondent hash table entries from the cache can lead to an improved overall performance.\ud
We evaluate the proposed approach by running hash-based table join and group-by operations of 5 TPC-H benchmark queries. The results show 2.9×–4.4× speedups over the cache-less FPGA-based baseline.The research leading to these results has received funding from the European Union’s Seventh Framework Program (FP7/2007-2013), for Advanced\ud
Analytics for Extremely Large European Databases (AXLE) project under grant\ud
agreement number 318633, and from the Ministry of Economy and Competitiveness\ud
of Spain under contract number TIN2015-65316-p.Peer ReviewedPostprint (author's final draft
Enhancing Energy Production with Exascale HPC Methods

High Performance Computing (HPC) resources have become the key actor for achieving more ambitious challenges in many disciplines. In this step beyond, an explosion on the available parallelism and the use of special purpose\ud
processors are crucial. With such a goal, the HPC4E project applies new exascale HPC techniques to energy industry simulations, customizing them if necessary, and going beyond the state-of-the-art in the required HPC exascale\ud
simulations for different energy sources. In this paper, a general overview of these methods is presented as well as some specific preliminary results.The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) under the HPC4E Project (www.hpc4e.eu), grant agreement n° 689772, the Spanish Ministry of\ud
Economy and Competitiveness under the CODEC2 project (TIN2015-63562-R), and\ud
from the Brazilian Ministry of Science, Technology and Innovation through Rede\ud
Nacional de Pesquisa (RNP). Computer time on Endeavour cluster is provided by the\ud
Intel Corporation, which enabled us to obtain the presented experimental results in\ud
uncertainty quantification in seismic imagingPostprint (author's final draft