nils-herrmann/clean_scirepeval huggingface dataset:
BPMN: An introduction to the standard

The Business Process Model and Notation (BPMN), formerly known as Business Process Modeling Notation, is the de-facto standard for representing in a very expressive graphical way the processes occurring in virtually every kind of organization one can think of, from cuisine recipes to the Nobel Prize assignment process, severe incident management, e-mail voting systems, travel booking procedures, to name few. In this work, we give an (rather condensed) overview of the BPMN standard, as devised by OMG and we present what are the links with other well-known machineries such as BPEL and XPDL. We also give an assessment of how the OMG's BPMN standard which is rather large and complex is perceived and used by practitioners in everyday business process modeling chores. URI: http://www.sciencedirect.com/science/article/pii/S0920548911000766  TROMBETTA Alberto Publication Year: 2011  Articles in Journals Publisher: ELSEVIER SCIENCE BV ISSN: 0920-5489 DOI: 10.1016/j.csi.2011.06.002   https://ec.europa.eu/jrc/en/publication/articles-journals/bpmn-introduction-standard Links  http://www.sciencedirect.com/science/article/pii/S0920548911000766  https://ec.europa.eu/jrc/en/person/michele-chinosi  http://dx.doi.org/10.1016/j.csi.2011.06.002
Flourishing Across Europe: Application of a New Conceptual Framework for Defining Well-Being

Governments around the world are recognising the importance of measuring subjective well-being as an indicator of progress. But how should well-being be measured? A conceptual framework is offered which equates high well-being with positive mental health. Well-being is seen as lying at the opposite end of a spectrum to the common mental disorders (depression, anxiety). By examining internationally agreed criteria for depression and anxiety (DSM and ICD classifications), and defining the opposite of each symptom, we identify ten features of positive well-being. These combine feeling and functioning, i.e. hedonic and eudaimonic aspects of well-being: competence, emotional stability, engagement, meaning, optimism, positive emotion, positive relationships, resilience, self esteem, and vitality. An operational definition of flourishing is developed, based on psychometric analysis of indicators of these ten features, using data from a representative sample of 43,000 Europeans. Application of this definition to respondents from the 23 countries which participated in the European Social Survey (Round 3) reveals a four-fold difference in flourishing rate, from 41% in Denmark to less than 10% in Slovakia, Russia and Portugal. There are also striking differences in country profiles across the 10 features. These profiles offer fresh insight into cultural differences in well-being, and indicate which features may provide the most promising targets for policies to improve well-being. Comparison with a life satisfaction measure shows that valuable information would be lost if well-being was measured by life satisfaction. Taken together, our findings reinforce the need to measure subjective well-being as a multi-dimensional construct in future surveys.
Resource management for isolation enhanced cloud services

The cloud infrastructure provider (CIP) in a cloud computing platform must provide security and isolation guarantees to a service provider (SP), who builds the service(s) for such a platform. We identify last level cache (LLC) sharing as one of the impediments to finer grain isolation required by a service, and advocate two resource management approaches to provide performance and security isolation in the shared cloud infrastructure - cache hierarchy aware core assignment and page coloring based cache partitioning. Experimental results demonstrate that these approaches are effective in isolating cache interference impacts a VM may have on another VM. We also incorporate these approaches in the resource management (RM) framework of our example cloud infrastructure, which enables the deployment of VMs with isolation enhanced SLAs.
An approach to detecting duplicate bug reports using natural language and execution information

An open source project typically maintains an open bug repository so that bug reports from all over the world can be gathered. When a new bug report is submitted to the repository, a person, called a triager, examines whether it is a duplicate of an existing bug report. If it is, the triager marks it as DUPLICATE and the bug report is removed from consideration for further work. In the literature, there are approaches exploiting only natural language information to detect duplicate bug reports. In this paper we present a new approach that further involves execution information. In our approach, when a new bug report arrives, its natural language information and execution information are compared with those of the existing bug reports. Then, a small number of existing bug reports are suggested to the triager as the most similar bug reports to the new bug report. Finally, the triager examines the suggested bug reports to determine whether the new bug report duplicates an existing bug report. We calibrated our approach on a subset of the Eclipse bug repository and evaluated our approach on a subset of the Firefox bug repository. The experimental results show that our approach can detect 67%-93% of duplicate bug reports in the Firefox bug repository, compared to 43%-72% using natural language information alone.
Opportunities for measuring wheelchair kinematics in match settings; reliability of a three inertial sensor configuration.

Knowledge of wheelchair kinematics during a match is prerequisite for performance improvement in wheelchair basketball. Unfortunately, no measurement system providing key kinematic outcomes proved to be reliable in competition. In this study, the reliability of estimated wheelchair kinematics based on a three inertial measurement unit (IMU) configuration was assessed in wheelchair basketball match-like conditions. Twenty participants performed a series of tests reflecting different motion aspects of wheelchair basketball. During the tests wheelchair kinematics were simultaneously measured using IMUs on wheels and frame, and a 24-camera optical motion analysis system serving as gold standard. Results showed only small deviations of the IMU method compared to the gold standard, once a newly developed skid correction algorithm was applied. Calculated Root Mean Square Errors (RMSE) showed good estimates for frame displacement (RMSE≤0.05 m) and speed (RMSE≤0.1m/s), except for three truly vigorous tests. Estimates of frame rotation in the horizontal plane (RMSE<3°) and rotational speed (RMSE<7°/s) were very accurate. Differences in calculated Instantaneous Rotation Centres (IRC) were small, but somewhat larger in tests performed at high speed (RMSE up to 0.19 m). Average test outcomes for linear speed (ICCs>0.90), rotational speed (ICC>0.99) and IRC (ICC> 0.90) showed high correlations between IMU data and gold standard. IMU based estimation of wheelchair kinematics provided reliable results, except for brief moments of wheel skidding in truly vigorous tests. The IMU method is believed to enable prospective research in wheelchair basketball match conditions and contribute to individual support of athletes in everyday sports practice.
Derivation and comparison of SAR and frequency-wavenumber migration within a common inverse scalar wave problem formulation

Two common Fourier imaging algorithms used in ground penetrating radar (GPR), synthetic aperture radar (SAR), and frequency-wavenumber (F-K) migration, are reviewed and compared from a theoretical perspective. The two algorithms, while arising from seemingly different physical models: a point-scatterer model for SAR and the exploding source model for F-K migration, result in similar imaging equations. Both algorithms are derived from an integral equation formulation of the inverse scalar wave problem, which allows a clear understanding of the approximations being made in each algorithm and allows a direct comparison. This derivation brings out the similarities of the two techniques which are hidden by the traditional formulations based on physical scattering models. The comparison shows that the approximations required to derive each technique from the integral equation formulation of the inverse problem are nearly identical, and hence the two imaging algorithms and physical models are making similar assumptions about the solution to the inverse problem, thus clarifying why the imaging equations are so similar. Sample images of landmine-like targets buried in sand are obtained from experimental GPR data using both algorithms.
On How to Perform a Gold Standard Based Evaluation of Ontology Learning

In recent years several measures for the gold standard based evaluation of ontology learning were proposed. They can be distinguished by the layers of an ontology (e.g. lexical term layer and concept hierarchy) they evaluate. Judging those measures with a list of criteria we show that there exist some measures sufficient for evaluating the lexical term layer. However, existing measures for the evaluation of concept hierarchies fail to meet basic criteria. This paper presents a new taxonomic measure which overcomes the problems of current approaches.
Why people hate your app: making sense of user feedback in a mobile app store

User review is a crucial component of open mobile app markets such as the Google Play Store. How do we automatically summarize millions of user reviews and make sense out of them? Unfortunately, beyond simple summaries such as histograms of user ratings, there are few analytic tools that can provide insights into user reviews. In this paper, we propose Wiscom, a system that can analyze tens of millions user ratings and comments in mobile app markets at three different levels of detail. Our system is able to (a) discover inconsistencies in reviews; (b) identify reasons why users like or dislike a given app, and provide an interactive, zoomable view of how users' reviews evolve over time; and (c) provide valuable insights into the entire app market, identifying users' major concerns and preferences of different types of apps. Results using our techniques are reported on a 32GB dataset consisting of over 13 million user reviews of 171,493 Android apps in the Google Play Store. We discuss how the techniques presented herein can be deployed to help a mobile app market operator such as Google as well as individual app developers and end-users.
Instructional Design Consequences of an Analogy between Evolution by Natural Selection and Human Cognitive Architecture

Evolution by natural selection may be characterized as a system in which a large store of genetic information will persist indefinitely while it remains coordinated with its environment but will continuously produce small random variations that are tested for environmental effectiveness. In any environment, effective variations will persist while ineffective variations will disappear. Similarly, human cognitive architecture includes a large store of information held in long-term memory that coordinates our cognitive activities. A very limited working memory tests the effectiveness of small variations to long-term memory with effective variations altering long-term memory while ineffective variations are lost. Both an existing genetic code and information in long-term memory provide a central executive that guides behaviour. Such a central executive is unavailable when an environment alters or when working memory must be used to deal with novel information. A major function of instructional design is to provide the otherwise missing structure of a central executive when dealing with novel information and to reduce that structural support as knowledge accumulates in longterm memory. Cognitive load theory both provides instructional design principles that would be difficult to devise without its particular view of human cognitive architecture and throws further light on that architecture. Instructional design issues and human cognitive architecture are inseparably intertwined. Not only is no useable science of instruction feasible without knowledge of human cognitive structures, but instructional design issues can impact heavily on the development of our knowledge of cognitive structures. Knowing how students learn and solve problems informs us how we should organise their learning environment and without such knowledge, the effectiveness of instructional designs is likely to be random. Equally, discovering that some instructional designs are superior to others can provide insights into human cognitive architecture that may otherwise be difficult to achieve. Cognitive load theory, with its close links between human cognitive architecture and instructional design, provides an example of the advantages of linking the two areas. The theory has used our knowledge of human cognitive architecture to generate a large number of instructional designs, some of which are unlikely to have been mapped without our knowledge of cognitive structures. More recently, the theory has begun to provide insights
Improved adaptive sparse channel estimation based on the least mean square algorithm

Least mean square (LMS) based adaptive algorithms have been attracted much attention since their low computational complexity and robust recovery capability. To exploit the channel sparsity, LMS-based adaptive sparse channel estimation methods, e.g., zero-attracting LMS (ZA-LMS), reweighted zero-attracting LMS (RZA-LMS) and Lp - norm sparse LMS (LP-LMS), have also been proposed. To take full advantage of channel sparsity, in this paper, we propose several improved adaptive sparse channel estimation methods using Lp -norm normalized LMS (LP-NLMS) and L0 -norm normalized LMS (L0-NLMS). Comparing with previous methods, effectiveness of the proposed methods is confirmed by computer simulations.
Two-Stage Monte Carlo Tree Search for Connect6

Recently, Monte Carlo tree search (MCTS) has become a well-known game search method, and has been successfully applied to many games. This method performs well in solving search trees with numerous branches, such as Go, Havannah, etc. Connect6 is a game involving a search tree with numerous branches, and it is also one of the sudden-death games. This paper thus proposes a new MCTS variant related to Connect6, called two-stage MCTS. The first stage focuses on threat space search (TSS), which is designed to solve the sudden-death problem. For the double-threat TSS in Connect6, this study proposes an algorithm called iterative threat space search (ITSS) which combines normal TSS with conservative threat space search (CTSS). The second stage uses MCTS to estimate the game-theoretic value of the initial position. This stage aims at finding the most promising move. The experimental result shows that two-stage MCTS is considerably more efficient than traditional MCTS on those positions with TSS solution in Connect6. Furthermore, according to Connect6 heuristic knowledge, this paper uses relevance-zone search to accelerate identifying winning and losing moves.
Examining playfulness in adults : Testing its correlates with personality , positive psychological functioning , goal aspirations , and multi-methodically assessed ingenuity

The prime aim of this set of studies was to test the disposition to play (playfulness) in adults in its relation with various measures of personality but also ability (self-estimated but also psychometrically measured ingenuity). Study 1 (n = 180) shows that adults playfulness relates primarily to extraversion, lower conscientiousness, and higher endorsements of culture; joy of being laughed at (gelotophilia) and agreeableness were also predictive in a regression analysis; Study 2 (n = 264) shows that playfulness relates primarily to a high expectation of intrinsic and a low expectation of extrinsic goals as well as greater intrinsic and lower extrinsic importance of goals (for expressive and fun-variants of playfulness); Study 3 (n = 212) shows that playfulness relates to greater selfperception of one’s degree of ingenuity and psychometric ingenuity correlated primarily with greater spontaneous and creative variants of playfulness (in about the same range for origence and fluidity of the productions). Overall, the findings were in line with the expectations and could stimulate further studies of playfulness in adults. Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-63532 Published Version Originally published at: Proyer, Rene T (2012). Examining playfulness in adults: Testing its correlates with personality, positive psychological functioning, goal aspirations, and multi-methodically assessed ingenuity.  Test and Assessment Modeling, 54(2):103-127.  Test and Assessment Modeling, Volume 54, 2012 (2), 103-127 Examining playfulness in adults: Testing its correlates with personality, positive psychological functioning, goal aspirations, and multi-methodically assessed ingenuity
RDF Graph Embeddings for Content-based Recommender Systems

Linked Open Data has been recognized as a useful source of background knowledge for building content-based recommender systems. Vast amount of RDF data, covering multiple domains, has been published in freely accessible datasets. In this paper, we present an approach that uses language modeling approaches for unsupervised feature extraction from sequences of words, and adapts them to RDF graphs used for building content-based recommender system. We generate sequences by leveraging local information from graph sub-structures and learn latent numerical representations of entities in RDF graphs. Our evaluation on two datasets in the domain of movies and books shows that feature vector representations of general knowledge graphs such as DBpedia and Wikidata can be effectively used in content-based recommender systems.
Maximum a posteriori Based Decoding for CTC Acoustic Models

This paper presents a novel decoding framework for connectionist temporal classification (CTC)-based acoustic models (AM). Although CTC-based AM inherently has the property of a language model (LM) in itself, an external LM trained with a large text corpus is still essential to obtain the best results. In the previous literatures, a naive interpolation of the CTCbased AM score and the external LM score was used, although there is no theoretical justification for it. In this paper, we propose a theoretically more sound decoding framework derived from a maximization of the posterior probability of a word sequence given an observation. In our decoding framework, a subword LM (SLM) is newly introduced to coordinate the CTCbased AM score and the word-level LM score. In experiments with the Wall Street Journal (WSJ) corpus and Corpus of Spontaneous Japanese (CSJ), our proposed framework consistently achieved improvements of 7.4 – 15.3 % over the conventional interpolation-based framework. In the CSJ experiment, given 586 hours of training data, the CTC-based AM finally achieved a 6.7 % better word error rate than the baseline method with deep neural networks and hidden Markov models.
Bimanual marking menu for near surface interactions

We describe a mouseless, near-surface version of the Bimanual Marking Menu system. To activate the menu system, users create a pinch gesture with either their index or middle finger to initiate a left click or right click. Then they mark in the 3D space near the interactive area. We demonstrate how the system can be implemented using a commodity range camera such as the Microsoft Kinect, and report on several designs of the 3D marking system.
 Like the multi-touch marking menu, our system offers a large number of accessible commands. Since it does not rely on contact points to operate, our system leaves the non-dominant hand available for other multi-touch interactions.
Shape-based automatic detection of a large number of 3D facial landmarks

We present an algorithm for automatic detection of a large number of anthropometric landmarks on 3D faces. Our approach does not use texture and is completely shape based in order to detect landmarks that are morphologically significant. The proposed algorithm evolves level set curves with adaptive geometric speed functions to automatically extract effective seed points for dense correspondence. Correspondences are established by minimizing the bending energy between patches around seed points of given faces to those of a reference face. Given its hierarchical structure, our algorithm is capable of establishing thousands of correspondences between a large number of faces. Finally, a morphable model based on the dense corresponding points is fitted to an unseen query face for transfer of correspondences and hence automatic detection of landmarks. The proposed algorithm can detect any number of pre-defined landmarks including subtle landmarks that are even difficult to detect manually. Extensive experimental comparison on two benchmark databases containing 6, 507 scans shows that our algorithm outperforms six state of the art algorithms.
How many people would benefit from a smart wheelchair?

Independent mobility is important, but some wheelchair users find operating existing manual or powered wheelchairs difficult or impossible. Challenges to safe, independent wheelchair use can result from various overlapping physical, perceptual, or cognitive symptoms of diagnoses such as spinal cord injury, cerebrovascular accident, multiple sclerosis, amyotrophic lateral sclerosis, and cerebral palsy. Persons with different symptom combinations can benefit from different types of assistance from a smart wheelchair and different wheelchair form factors. The sizes of these user populations have been estimated based on published estimates of the number of individuals with each of several diseases who (1) also need a wheeled mobility device and (2) have specific symptoms that could interfere with mobility device use.
Technique for automatic emotion recognition by body gesture analysis

This paper illustrates our recent work on the analysis of expressive gesture related to the motion of the upper body (the head and the hands) in the context of emotional portrayals performed by professional actors. An experiment is presented which is the result of a multidisciplinary joint work. The experiment aims at (i) developing models and algorithms for analysis of such expressive content (ii) individuating which motion cues are involved in conveying the actorpsilas expressive intentions to portray four emotions (anger, joy, relief, sadness) via a scenario approach. The paper discusses the experiment in detail with reference to related conceptual issues, developed techniques, and the obtained results.
Markov random walk under constraint for discovering overlapping communities in complex networks

Detection of overlapping communities in complex networks has motivated recent research in the relevant fields. Aiming this problem, we propose a Markov dynamics based algorithm, called UEOC, which means, “unfold and extract overlapping communities”. In UEOC, when identifying each natural community that overlaps, a Markov random walk method combined with a constraint strategy, which is based on the corresponding annealed network (degree conserving random network), is performed to unfold the community. Then, a cutoff criterion with the aid of a local community function, called conductance, which can be thought of as the ratio between the number of edges inside the community and those leaving it, is presented to extract this emerged community from the entire network. The UEOC algorithm depends on only one parameter whose value can be easily set, and it requires no prior knowledge on the hidden community structures. The proposed UEOC has been evaluated both on synthetic benchmarks and on some real-world networks, and was compared with a set of competing algorithms. Experimental result has shown that UEOC is highly effective and efficient for discovering overlapping communities.