pinecone/core-2020-05-10-deduplication huggingface dataset:
Collisions, Design & The Swerve

If only everything were formed of neat laminar flows, with easy to understand conditions, and determinable outcomes: there would be no risk to manage out, messy inconsistencies and uncertainties to disrupt well-laid out plans. Things are not so clear-cut however. Indeed, as scientists, poets and philosophers of science have pointed out it is under conditions of nondeterminism and complexity that everything comes into being. There is an issue, then, when creative disciplines in particular find such complexity problematic enough to design systems and models in which uncertainty, disruption and aleatory collisions are if not destroyed, then dampened. We wonder: what might become of a creative practice that championed its encounter with The Swerve, Lucretius's clinamen? This article examines the role, value and applicability of the concept of collision to design. It takes a philosophical approach to examining this concept and mapping the possibilities of its use in design. We will argue using concepts mainly from Lucretius and Serres – but also Deleuze and others – that collision is an important aspect of all creativity, and that there would be nothing were it not for collisions, disruptive deviation and swerves from equilibrium. The aim will be to articulate the conditions for the possibility of designing that is a 'fan of collisions'
Trajectories of Solidarities in France Across Fields of Vulnerability

This chapter approaches the study of solidarity in France by comparing three important vulnerable groups, namely, the disabled, the unemployed, and refugees. The way we approach solidarity hinges on an important distinction between two different meanings of solidarity: solidarity understood as an input and solidarity understood as an output. In particular, we distinguish between two main “trajectories of solidarity”, which helps us to understand the way certain individual variables (such as self-identification and proximity) combine with political variables (like voting, an interest in politics, or the reading of newspapers) in very different ways. Our main finding is the political trajectory of solidarity can have a remarkable potential even when it comes to helping vulnerable people outside the national boundaries of the political community in France
A continuum model of skeletal muscle tissue with loss of activation

We present a continuum model for the mechanical behavior of the skeletal
muscle tissue when its functionality is reduced due to aging. The loss of
ability of activating is typical of the geriatric syndrome called sarcopenia.
The material is described by a hyperelastic, polyconvex, transverse isotropic
strain energy function. The three material parameters appearing in the energy
are fitted by least square optimization on experimental data, while
incompressibility is assumed through a Lagrange multiplier representing the
hydrostatic pressure. The activation of the muscle fibers, which is related to
the contraction of the sarcomere, is modeled by the so called active strain
approach. The loss of performance of an elder muscle is then obtained by
lowering of some percentage the active part of the stress. The model is
implemented numerically and the obtained results are discussed and graphically
represented
Genetic Algorithm with Optimal Recombination for the Asymmetric
  Travelling Salesman Problem

We propose a new genetic algorithm with optimal recombination for the
asymmetric instances of travelling salesman problem. The algorithm incorporates
several new features that contribute to its effectiveness: (i) Optimal
recombination problem is solved within crossover operator. (ii) A new mutation
operator performs a random jump within 3-opt or 4-opt neighborhood. (iii)
Greedy constructive heuristic of W.Zhang and 3-opt local search heuristic are
used to generate the initial population. A computational experiment on TSPLIB
instances shows that the proposed algorithm yields competitive results to other
well-known memetic algorithms for asymmetric travelling salesman problem.Comment: Proc. of The 11th International Conference on Large-Scale Scientific
  Computations (LSSC-17), June 5 - 9, 2017, Sozopol, Bulgari
Parity games and automata for game logic

Parikh's game logic is a PDL-like fixpoint logic interpreted on monotone neighbourhood frames that represent the strategic power of players in determined two-player games. Game logic translates into a fragment of the monotone μ-calculus, which in turn is expressively equivalent to monotone modal automata. Parity games and automata are important tools for dealing with the combinatorial complexity of nested fixpoints in modal fixpoint logics, such as the modal μ-calculus. In this paper, we (1) discuss the semantics a of game logic over neighbourhood structures in terms of parity games, and (2) use these games to obtain an automata-theoretic characterisation of the fragment of the monotone μ-calculus that corresponds to game logic. Our proof makes extensive use of structures that we call syntax graphs that combine the ease-of-use of syntax trees of formulas with the flexibility and succinctness of automata. They are essentially a graph-based view of the alternating tree automata that were introduced by Wilke in the study of modal μ-calculus
Room Floor Plan Generation on a Project Tango Device

This article presents a method to ease the generation of room floor plans with a Project Tango device. Our method takes as input range images as well as camera poses. It is based on the extraction of vertical planar surfaces we label as wall or clutter. While the user is scanning the scene, we estimate the room layout from the labeled planar surfaces by solving a shortest path problem. The user can intervene in this process, and affect the estimated layout by changing the label of the extracted planar surfaces. We compare our approach with other mobile applications and demonstrate its validity
The Long Tail of Web Video

Web Video continues to gain importance not only in many areas of computer science but in society in general. With the growth in numbers, both of videos, viewers, and views, there arise several technical challenges. In order to address them effectively, the properties of Web Video in general need to be known. There is however comparatively little analysis of these properties. In this paper, we present insights gained from the analysis of a data set containing the meta data of over 100 million videos from YouTube. We were able to confirm common wisdom about the relationship between video duration and user engagement and show the extreme long tail of the distribution of video views overall. Such data can be beneficial in making informed decisions regarding strategies for large scale video storage, delivery, processing and retrieval
Approaches for event segmentation of visual lifelog data

A personal visual lifelog can be considered to be a human memory augmentation tool and in recent years we have noticed an increased interest in the topic of lifelogging both in academic research and from industry practitioners. In this preliminary work, we explore the concept of event segmentation of visual lifelog data. Lifelog data, by its nature is continual and streams of multimodal data can easy run into thousands of wearable camera images per day, along with a significant number of other sensor sources. In this paper, we present two new approaches to event segmentation and compare them against pre-existing approaches in a user experiment with ten users. We show that our approaches based on visual concepts occurrence and image categorization perform better than the pre-existing approaches. We finalize the paper with a suggestion for next steps for the research community
Empowering a Cyber-Physical System for a Modular Conveyor System with Self-organization

The Industry 4.0 advent, advocating the digitalization and transformation of current production systems towards the factories of future, is introducing significant social and technological challenges. Cyber-physical systems (CPS) can be used to realize these Industry 4.0 compliant systems, integrating several emergent technologies, such as Internet of Things, big data, cloud computing and multi-agent systems. The paper analyses the advantages of using biological inspiration to empower CPS, and particularly those developed using distributed and intelligent paradigms such as multi-agent systems technology. For this purpose, the self-organization capability, as one of the main drivers in this industrial revolution is analysed, and the way to translate it to solve complex industrial engineering problems is discussed. Its applicability is illustrated by building a self-organized cyber-physical conveyor system composed by different individual modular and intelligent transfer modules.info:eu-repo/semantics/publishedVersio
Multi-agent System Architecture for Zero Defect Multi-stage Manufacturing

Multi-stage manufacturing, typical in important industrial sectors, is inherently a complex process. The application of the zero defect manufacturing (ZDM) philosophy, together with recent technological advances in cyber-physical systems (CPS), presents significant challenges and opportunities for the implementation of new methodologies towards the continuous system improvement. This paper introduces the main principles of a multi-agent CPS aiming the application of ZDM in multi-stage production systems, which is being developed under the EU H2020 GO0D MAN project. In particular, this paper describes the MAS architecture that allows the distributed data collection and the balancing of the data analysis for monitoring and adaptation among cloud and edge layers, to enable the earlier detection of process and product variability, and the generation of new optimized knowledge by correlating the aggregated data.This work his part of the GO0D MAN project that has received funding from
the European Union’s Horizon 2020 research and innovation programme
under grant agreement No 723764.info:eu-repo/semantics/publishedVersio
Ageism and sexuality

Sexuality remains important throughout a person’s life, but sexual behavior does not receive the same levels of acceptance at all ages. Older people are challenged by ageist attitudes and perceptions that hinder their sexual expression. They are stereotyped as non-sexual beings who should not, cannot, and do not want to have sexual relationships. Expressing sexuality or engaging in sexual activity in later life is considered by many in society as immoral or perverted. False expectations for older people also stem from ideals of beauty, centralization of the biomedical perspective on sexuality of older adults, and the association of sex with reproduction. Unfortunately, older people internalize many ageist attitudes towards sexuality in later life and become less interested in sex and less sexually active. The following chapter explores attitudes towards sexuality in later life among the media, young people, older people themselves, and care providers. In order to enable older people to express their sexuality and sexual identity freely and fully, awareness of ageist perceptions must be raised and defeated
Data-Driven Decisions and Actions in Today’s Software Development

Today’s software development is all about data: data about the software product itself, about the process and its different stages, about the customers and markets, about the development, the testing, the integration, the deployment, or the runtime aspects in the cloud. We use static and dynamic data of various kinds and quantities to analyze market feedback, feature impact, code quality, architectural design alternatives, or effects of performance optimizations. Development environments are no longer limited to IDEs in a desktop application or the like but span the Internet using live programming environments such as Cloud9 or large-volume repositories such as BitBucket, GitHub, GitLab, or StackOverflow. Software development has become “live” in the cloud, be it the coding, the testing, or the experimentation with different product options on the Internet. The inherent complexity puts a further burden on developers, since they need to stay alert when constantly switching between tasks in different phases. Research has been analyzing the development process, its data and stakeholders, for decades and is working on various tools that can help developers in their daily tasks to improve the quality of their work and their productivity. In this chapter, we critically reflect on the challenges faced by developers in a typical release cycle, identify inherent problems of the individual phases, and present the current state of the research that can help overcome these issues
Many touchings force many crossings

Given n continuous open curves in the plane, we say that a pair is touching if they have only one interior point in common and at this point the first curve does not get from one side of the second curve to its other side. Otherwise, if the two curves intersect, they are said to form a crossing pair. Let t and c denote the number of touching pairs and crossing pairs, respectively. We prove that c ≥ 1/105 t2/n2, provided that t ≥ 10n Apart from the values of the constants, this result is best possible. © Springer International Publishing AG 2018
Thrackles: An improved upper bound

A thrackle is a graph drawn in the plane so that every pair of its edges meet exactly once: either at a common end vertex or in a proper crossing. We prove that any thrackle of n vertices has at most 1.3984n edges. Quasi-thrackles are defined similarly, except that every pair of edges that do not share a vertex are allowed to cross an odd number of times. It is also shown that the maximum number of edges of a quasi-thrackle on n vertices is 3/2(n-1), and that this bound is best possible for infinitely many values of n. © Springer International Publishing AG 2018
Structural Feature Selection for Event Logs

We consider the problem of classifying business process instances based on
structural features derived from event logs. The main motivation is to provide
machine learning based techniques with quick response times for interactive
computer assisted root cause analysis. In particular, we create structural
features from process mining such as activity and transition occurrence counts,
and ordering of activities to be evaluated as potential features for
classification. We show that adding such structural features increases the
amount of information thus potentially increasing classification accuracy.
However, there is an inherent trade-off as using too many features leads to too
long run-times for machine learning classification models. One way to improve
the machine learning algorithms' run-time is to only select a small number of
features by a feature selection algorithm. However, the run-time required by
the feature selection algorithm must also be taken into account. Also, the
classification accuracy should not suffer too much from the feature selection.
The main contributions of this paper are as follows: First, we propose and
compare six different feature selection algorithms by means of an experimental
setup comparing their classification accuracy and achievable response times.
Second, we discuss the potential use of feature selection results for computer
assisted root cause analysis as well as the properties of different types of
structural features in the context of feature selection.Comment: Extended version of a paper published in the proceedings of the BPM
  2017 workshop
A systematic literature review of the use of social media for business process management

In today’s expansion of new technologies, innovation is found necessary for organizations to be up to date with the latest management trends. Although organizations are increasingly using new technologies, opportunities still exist to achieve the nowadays essential omnichannel management strategy. More precisely, social media are opening a path for benefiting more from an organization’s process orientation. However, social media strategies are still an under-investigated field, especially when it comes to the research of social media use for the management and improvement of business processes or the internal way of working in organizations. By classifying a variety of articles, this study explores the evolution of social media implementation within the BPM discipline. We also provide avenues for future research and strategic implications for practitioners to use social media more comprehensively
Sustainability performance measurement : a preliminary classification framework of models and indicators

In this position paper we focus on the diversity of sustainability measurements. Based on existing research on performance measurement, we propose a preliminary classification framework summarizing sustainability models and indicators. By describing illustrative examples, we claim that several models and indicators can be distinguished with their own peculiarities. Having such a framework is interesting for both academia and business to structure the range of models and indicators and to ultimately select the appropriate sustainability measurement approach. The proposed framework should be validated by further research
On the Tractability of (k, i)-Coloring

In an undirected graph, a proper (\ud
k, i\ud
)-coloring is an assign-\ud
ment of a set of\ud
k\ud
colors to each vertex such that any two adjacent\ud
vertices have at most\ud
i\ud
common colors. The (\ud
k, i\ud
)-coloring problem is\ud
to compute the minimum number of colors required for a proper\ud
(\ud
k, i\ud
)-\ud
coloring. This is a generalization of the classic graph colo\ud
ring problem.\ud
Majumdar et. al. [CALDAM 2017] studied this problem and show\ud
ed\ud
that the decision version of the (\ud
k, i\ud
)-coloring problem is fixed parameter\ud
tractable (FPT) with tree-width as the parameter. They aske\ud
d if there\ud
exists an FPT algorithm with the size of the feedback vertex s\ud
et (FVS)\ud
as the parameter without using tree-width machinery. We ans\ud
wer this in\ud
positive by giving a parameterized algorithm with the size o\ud
f the FVS\ud
as the parameter. We also give a faster and simpler exact algo\ud
rithm for\ud
(\ud
k, k\ud
−\ud
1)-coloring, and make progress on the NP-completeness of sp\ud
ecific\ud
cases of (\ud
k, i\ud
)-colorin
An Approach for Isolated Testing of Self-Organization Algorithms

We provide a systematic approach for testing self-organization (SO)
algorithms. The main challenges for such a testing domain are the strongly
ramified state space, the possible error masking, the interleaving of
mechanisms, and the oracle problem resulting from the main characteristics of
SO algorithms: their inherent non-deterministic behavior on the one hand, and
their dynamic environment on the other. A key to success for our SO algorithm
testing framework is automation, since it is rarely possible to cope with the
ramified state space manually. The test automation is based on a model-based
testing approach where probabilistic environment profiles are used to derive
test cases that are performed and evaluated on isolated SO algorithms. Besides
isolation, we are able to achieve representative test results with respect to a
specific application. For illustration purposes, we apply the concepts of our
framework to partitioning-based SO algorithms and provide an evaluation in the
context of an existing smart-grid application.Comment: Preprint of Eberhardinger, B., Anders, G., Seebach, H., Siefert, F.,
  Knapp, A., Reif, W.: An approach for isolated testing of self-organization
  algorithms. In: de Lemos, R., et al. (eds.) Software Engineering for
  Self-Adaptive Systems III, LNCS, vol. 9640. Springer (2016
Seeking serendipity: The art of finding the unsought in professional music

Serendipity is a valuable constituent of professional work. In order to ‘control’ the phenomenon it is important to gain insight in its processes and influencing factors. This study examined two cases of serendipitous information behavior in professional improvised music, a domain often associated with unpredictability. The aim of the study was to validate McCay-Peet and Toms’ latest model on work-related serendipitous experiences. The study followed a semi-structured interview procedure that consisted of three one-hour interview sessions to select cases and collect data. Results show that our data fit the model. Process elements like ‘trigger’, ‘connection’, ‘valuable outcome’, ‘unexpected thread’, and ‘perception of serendipity’ were identified, as well as factors such as ‘trigger-rich’, ‘openness’, and ‘prepared mind’. We also identified other factors (i.e., ‘curiosity’, ‘interest’, and ‘initiative’) that might influence serendipitous discovery. Additional (multi) case studies are necessary to generalize findings
Detecting Community Structure in Dynamic Social Networks Using the
  Concept of Leadership

Detecting community structure in social networks is a fundamental problem
empowering us to identify groups of actors with similar interests. There have
been extensive works focusing on finding communities in static networks,
however, in reality, due to dynamic nature of social networks, they are
evolving continuously. Ignoring the dynamic aspect of social networks, neither
allows us to capture evolutionary behavior of the network nor to predict the
future status of individuals. Aside from being dynamic, another significant
characteristic of real-world social networks is the presence of leaders, i.e.
nodes with high degree centrality having a high attraction to absorb other
members and hence to form a local community. In this paper, we devised an
efficient method to incrementally detect communities in highly dynamic social
networks using the intuitive idea of importance and persistence of community
leaders over time. Our proposed method is able to find new communities based on
the previous structure of the network without recomputing them from scratch.
This unique feature, enables us to efficiently detect and track communities
over time rapidly. Experimental results on the synthetic and real-world social
networks demonstrate that our method is both effective and efficient in
discovering communities in dynamic social networks
Exploring Food Detection using CNNs

One of the most common critical factors directly related to the cause of a
chronic disease is unhealthy diet consumption. In this sense, building an
automatic system for food analysis could allow a better understanding of the
nutritional information with respect to the food eaten and thus it could help
in taking corrective actions in order to consume a better diet. The Computer
Vision community has focused its efforts on several areas involved in the
visual food analysis such as: food detection, food recognition, food
localization, portion estimation, among others. For food detection, the best
results evidenced in the state of the art were obtained using Convolutional
Neural Network. However, the results of all these different approaches were
gotten on different datasets and therefore are not directly comparable. This
article proposes an overview of the last advances on food detection and an
optimal model based on GoogLeNet Convolutional Neural Network method, principal
component analysis, and a support vector machine that outperforms the state of
the art on two public food/non-food datasets
Alpha Decay and Beta-Delayed Fission: Tools for Nuclear Physics Studies

α decay and β-delayed fission are two important decay modes of heavy exotic nuclei. Experimental α decay and β-delayed fission studies deliver significant nuclear-structure information in regions of the nuclear chart with limited accessibility. This information is important to improve the predictability of contemporary nuclear models used for e.g. nuclear astrophysics calculations. The basic principles and the current understanding of α and β-delayed fission decay are introduced. Examples of recent experiments and their impact on the understanding of heavy nuclei are presented