nils-herrmann/clean_scirepeval huggingface dataset:
Rethinking Large-Scale Consensus

In this position paper, we initiate a systematic treatment of reaching consensus in a permissionless network. We prove several simple but hopefully insightful lower bounds that demonstrate exactly why reaching consensus in a permission-less setting is fundamentally more difficult than the classical, permissioned setting. We then present a simplified proof of Nakamoto's blockchain which we recommend for pedagogical purposes. Finally, we survey recent results including how to avoid well-known painpoints in permissionless consensus, and how to apply core ideas behind blockchains to solve consensus in the classical, permissioned setting and meanwhile achieve new properties that are not attained by classical approaches.
Underwater photogrammetry and XML based documentation system : the case of the ‘Grand Ribaud F' estruscan wreck

The interdisciplinary work presented here deals with the management of diverse types of information collected during an archaeological excavation, and organized as an XML based data management system. The approach is global, from the consultation of three-dimensional data to simple textual data, and to additional data captured by a digital photogrammetry system called ARPENTEUR, which is now fully integrated to the XML data management system. This work is available on the Internet: http://GrandRibaudF.gamsau.archi.fr A stratigraphic approach and a set of underwater photogrammetric survey was done after the excavation process. The photogrammetric orientation work was done in Photomodeler 4.0 (camera calibration and bundle adjustment). The final plotting of amphoras and other artefacts was done using the ARPENTEUR software after importation of all camera orientation data from Photomodeler. The Arpenteur plotting phase is driven by a theoretical model of the measured artefact. The resulting survey is described in a set of XML files containing all measured data (2D, 3D and computed amphoras or artefacts). At this point, a data management system (based on XML technology) is built in order to access to all the data from 2D or 3D representation of the site on the Internet. In the framework of multimedia data management system as photographs, indexation of metadata available as XML documents is particularly convenient. Thanks to this formalism we can represent in an homogeneous way a set of very different kind of data such as : − Structural description of the image content (given by an expert), − Physical data as color histogram, color zone, (with automatic extraction) − Photogrammetric data − Metadata as : intellectual properties, shooting date, policy of right, original support, etc ... This homogeneous representation management of the data coming from different sources is an opportunity to elaborate a request on the whole set of data. On the other hand the results data (also generated in XML) allows a simple and automatic publication of the result towards different media as HTML or PDF for example. The implementation of such a system has to be done in close collaboration with experts of the investigated domain (here underwater archaeology) in order to build a relevant data model and adapt the request algorithm to the specific problematic. The XML document structure allows different kind of data indexation : − Intuitive way, by interactive navigation, − Simple way as keyword research (for example as search engine, i.e. Google) − Accurate way by request formalisation as we can do in a traditional DBMS with SQL. After a brief introduction of the archaeological context, followed by the photogrammetric aspects of the plotting phase with ARPENTEUR, we will then present the existing system and explain the way to navigate into the heterogeneous data as 3D models, theoretical amphora models, oriented photographs and 2D measured points.
Using an information retrieval system to retrieve source code samples

Software developers often face steep learning curves in using a new framework, library, or new versions of frameworks for developing their piece of software. In large organizations, developers learn and explore use of frameworks, rarely realizing, several peers may have already explored the same. A tool that helps locate samples of code, demonstrating use of frameworks or libraries would provide benefits of reuse, improved code quality and faster development. This paper describes an approach for locating common samples of source code from a repository by providing extensions to an information retrieval system. The approach improves the existing approaches in two ways. First, it provides the scalability of an information retrieval system, supporting search over thousands of source code files of an organization. Second, it provides more specific search on source code by preprocessing source code files and understanding elements of the code as opposed to considering code as plain text.
The impact of tutorials on games of varying complexity

One of the key challenges of video game design is teaching new players how to play. Although game developers frequently use tutorials to teach game mechanics, little is known about how tutorials affect game learnability and player engagement. Seeking to estimate this value, we implemented eight tutorial designs in three video games of varying complexity and evaluated their effects on player engagement and retention. The results of our multivariate study of over 45,000 players show that the usefulness of tutorials depends greatly on game complexity. Although tutorials increased play time by as much as 29% in the most complex game, they did not significantly improve player engagement in the two simpler games. Our results suggest that investment in tutorials may not be justified for games with mechanics that can be discovered through experimentation.
Bayesian Optimization with Tree-structured Dependencies

Bayesian optimization has been successfully used to optimize complex black-box functions whose evaluations are expensive. In many applications, like in deep learning and predictive analytics, the optimization domain is itself complex and structured. In this work, we focus on use cases where this domain exhibits a known dependency structure. The benefit of leveraging this structure is twofold: we explore the search space more efficiently and posterior inference scales more favorably with the number of observations than Gaussian Process-based approaches published in the literature. We introduce a novel surrogate model for Bayesian optimization which combines independent Gaussian Processes with a linear model that encodes a tree-based dependency structure and can transfer information between overlapping decision sequences. We also design a specialized two-step acquisition function that explores the search space more effectively. Our experiments on synthetic tree-structured objectives and on the tuning of feedforward neural networks show that our method compares favorably with competing approaches.
Software Plagiarism Detection with Birthmarks Based on Dynamic Key Instruction Sequences

A software birthmark is a unique characteristic of a program. Thus, comparing the birthmarks between the plaintiff and defendant programs provides an effective approach for software plagiarism detection. However, software birthmark generation faces two main challenges: the absence of source code and various code obfuscation techniques that attempt to hide the characteristics of a program. In this paper, we propose a new type of software birthmark called DYnamic Key Instruction Sequence (DYKIS) that can be extracted from an executable without the need for source code. The plagiarism detection algorithm based on our new birthmarks is resilient to both weak obfuscation techniques such as compiler optimizations and strong obfuscation techniques implemented in tools such as SandMark, Allatori and Upx. We have developed a tool called DYKIS-PD (DYKIS Plagiarism Detection tool) and conducted extensive experiments on large number of binary programs. The tool, the benchmarks and the experimental results are all publicly available.
Bead: Explorations in Information Visualization

We describe work on the visualization of bibliographic data and, to aid in this task, the application of numerical techniques for multidimensional scaling.
Many areas of scientific research involve complex multivariate data. One example of this is Information Retrieval. Document comparisons may be done using a large number of variables. Such conditions do not favour the more well-known methods of visualization and graphical analysis, as it is rarely feasible to map each variable onto one aspect of even a three-dimensional, coloured and textured space.
Bead is a prototype system for the graphically-based exploration of information. In this system, articles in a bibliography are represented by particles in 3-space. By using physically-based modelling techniques to take advantage of fast methods for the approximation of potential fields, we represent the relationships between articles by their relative spatial positions. Inter-particle forces tend to make similar articles move closer to one another and dissimilar ones move apart. The result is a 3D scene which can be used to visualize patterns in the high-D information space.
A Clustering Approach to Unsupervised Attack Detection in Collaborative Recommender Systems

Securing collaborative filtering systems from malicious attack has become an important issue with increasing popularity of recommender Systems. Since recommender systems are entirely based on the input provided by the users or customers, they tend to become highly vulnerable to outside attacks. Prior research has shown that attacks can significantly affect the robustness of the systems. To prevent such attacks, researchers proposed several unsupervised detection mechanisms. While these approaches produce satisfactory results in detecting some well studied attacks, they are not suitable for all types of attacks studied recently. In this paper, we show that the unsupervised clustering can be used effectively for attack detection by computing detection attributes modeled on basic descriptive statistics. We performed extensive experiments and discussed different approaches regarding their performances. Our experimental results showed that attribute-based unsupervised clustering algorithm can detect spam users with a high degree of accuracy and fewer misclassified genuine users regardless of attack strategies.
Cardinality estimation and dynamic length adaptation for Bloom filters

Bloom filters are extensively used in distributed applications, especially in distributed databases and distributed information systems, to reduce network requirements and to increase performance. In this work, we propose two novel Bloom filter features that are important for distributed databases and information systems. First, we present a new approach to encode a Bloom filter such that its length can be adapted to the cardinality of the set it represents, with negligible overhead with respect to computation and false positive probability. The proposed encoding allows for significant network savings in distributed databases, as it enables the participating nodes to optimize the length of each Bloom filter before sending it over the network, for example, when executing Bloom joins. Second, we show how to estimate the number of distinct elements in a Bloom filter, for situations where the represented set is not materialized. These situations frequently arise in distributed databases, where estimating the cardinality of the represented sets is necessary for constructing an efficient query plan. The estimation is highly accurate and comes with tight probabilistic bounds. For both features we provide a thorough probabilistic analysis and extensive experimental evaluation which confirm the effectiveness of our approaches.
Juvéderm® Volbella™ in the perioral area: a 12-month prospective, multicenter, open-label study

Hyaluronic acid dermal fillers are frequently used for lip augmentation, and a new filler has been developed with characteristics especially suited for the lips.



Four European sites treated 60 subjects with Juvéderm(®) Volbella™ injectable gel in the perioral area, and subjects returned to the clinic at 1, 3, 6, 9, and 12 months for follow-up. The primary effectiveness endpoint established a priori was a Month 3 responder rate on the 4-point Lip Fullness Scale (LFS) of ≥40% and statistically > 0%, where responders improved ≥ 1 point from baseline on the investigator's assessment of LFS. At follow-up, subjects assessed lip fullness goal achievement, the look and feel of their lips, and their satisfaction with the effects of treatment.



The Month 3 LFS responder rate was 93.2% (P < 0.0001), so the primary endpoint was met, and clinical effectiveness was demonstrated. The responder rate over time showed that 78.0% of subjects still had improved lip fullness at Month 9 and 48.3% at Month 12. After treatment 98.3% of subjects reported that their lip fullness goal had been achieved, and this was maintained at 86.4% at Month 9 and 56.9% at Month 12. At Month 1, 81.0% of subjects reported that their lips felt smooth, and 91.4% reported that their lips looked natural (scores of 7-10 on an 11-point scale, where 0 was an unfavorable outcome and 10 was a favorable outcome). Similarly, 96.6% of subjects reported being satisfied (scores between 7 and 10 on an 11-point scale where 0 = very dissatisfied, 10 = very satisfied) at Month 1, and by Month 12 more than 80% of subjects were still satisfied. There were no severe adverse events related to treatment.



Juvéderm(®) Volbella™ injectable gel is well tolerated and has been demonstrated to provide a smooth and natural improvement in lip fullness that lasts for up to 1 year.
Job stressors, personality and burnout in primary school teachers.

Teaching is considered a highly stressful occupation. Burnout is a negative affective response occurring as a result of chronic work stress. While the early theories of burnout focused exclusively on work-related stressors, recent research adopts a more integrative approach where both environmental and individual factors are studied. Nevertheless, such studies are scarce with teacher samples.



The present cross-sectional study sought to investigate the association between burnout, personality characteristics and job stressors in primary school teachers from Cyprus. The study also investigates the relative contribution of these variables on the three facets of burnout - emotional exhaustion, depersonalization and reduced personal accomplishment.


SAMPLE
A representative sample of 447 primary school teachers participated in the study.



Teachers completed measures of burnout, personality and job stressors along with demographic and professional data. Surveys were delivered by courier to schools, and were distributed at faculty meetings.



Results showed that both personality and work-related stressors were associated with burnout dimensions. Neuroticism was a common predictor of all dimensions of burnout although in personal accomplishment had a different direction. Managing student misbehaviour and time constraints were found to systematically predict dimensions of burnout.



Teachers' individual characteristics as well as job related stressors should be taken into consideration when studying the burnout phenomenon. The fact that each dimension of the syndrome is predicted by different variables should not remain unnoticed especially when designing and implementing intervention programmes to reduce burnout in teachers.
Continuous mobile authentication using touchscreen gestures

Securing the sensitive data stored and accessed from mobile devices makes user authentication a problem of paramount importance. The tension between security and usability renders however the task of user authentication on mobile devices a challenging task. This paper introduces FAST (Fingergestures Authentication System using Touchscreen), a novel touchscreen based authentication approach on mobile devices. Besides extracting touch data from touchscreen equipped smartphones, FAST complements and validates this data using a digital sensor glove that we have built using off-the-shelf components. FAST leverages state-of-the-art classification algorithms to provide transparent and continuous mobile system protection. A notable feature is FAST 's continuous, user transparent post-login authentication. We use touch data collected from 40 users to show that FAST achieves a False Accept Rate (FAR) of 4.66% and False Reject Rate of 0.13% for the continuous post-login user authentication. The low FAR and FRR values indicate that FAST provides excellent post-login access security, without disturbing the honest mobile users.
A comprehensive review on automation of Indian sign language

Hearing impaired people uses signs to communicate with others. Just like verbally spoken languages, there is no universal language as every country has its own spoken language so every country has their own dialect of sign language and in India they uses Indian Sign Language (ISL). In the last few years, researchers take interest in the automation of ISL. Some attempts have been made in India and other countries. In this study we try to explore and analyze the work have been made with automation of sign language and gesture recognition. We tried to explore the challenges comes in the real time sign recognition system. This review also includes the progress of standard corpus creation of the ISL.
A ranking approach to keyphrase extraction

This paper addresses the issue of automatically extracting keyphrases from a document. Previously, this problem was formalized as classification and learning methods for classification were utilized. This paper points out that it is more essential to cast the problem as ranking and employ a learning to rank method to perform the task. Specifically, it employs Ranking SVM, a state-of-art method of learning to rank, in keyphrase extraction. Experimental results on three datasets show that Ranking SVM significantly outperforms the baseline methods of SVM and Naive Bayes, indicating that it is better to exploit learning to rank techniques in keyphrase extraction.
Ocimum sanctum Linn. A reservoir plant for therapeutic applications: An overview

The medicinal plants are widely used by the traditional medicinal practitioners for curing various diseases in their day to day practice. In traditional system of medicine, different parts (leaves, stem, flower, root, seeds and even whole plant) of Ocimum sanctum Linn. have been recommended for the treatment of bronchitis, malaria, diarrhea, dysentery, skin disease, arthritis, eye diseases, insect bites and so on. The O. sanctum L. has also been suggested to possess anti-fertility, anticancer, antidiabetic, antifungal, antimicrobial, cardioprotective, analgesic, antispasmodic and adaptogenic actions. Eugenol (1-hydroxy-2-methoxy-4-allylbenzene), the active constituents present in O. sanctum L. have been found to be largely responsible for the therapeutic potentials. The pharmacological studies reported in the present review confirm the therapeutic value of O. sanctum L. The results of the above studies support the use of this plant for human and animal disease therapy and reinforce the importance of the ethno-botanical approach as a potential source of bioactive substances.
Design and Construction of a Rogowski Coil for Measuring Wide Pulsed Current

In this paper, the design, installation, and performance of a Rogowski coil are presented. Based on the lumped-element model of Rogowski coil, the low-frequency distortion of wide pulsed current measurement is studied. The optimal damping resistance of the external-integrating Rogowski coil is obtained under the sinusoidal steady-state excitation. The amplitude-frequency characteristics of measuring systems (MSs) based on Rogowski coils with an RC integrator and an active integrator, respectively, are compared, and the actual bandwidths of the two MSs are also determined by the measurement accuracy. As a result of using an active integrator, the measuring bandwidth is broadened and the transient performance of the MS is improved compared with that of the MS with an RC integrator. Some measures of resisting electromagnetic interference caused by the Marx generator and spark gap switch are described. In the end, the experimental results of the MS based on the Rogowski coil in SG-III are presented.
A frequency-domain analysis of head-motion prediction

The use of prediction to eliminate or reduce the effects of system delays in Head-Mounted Display systems has been the subject of several recent papers. A variety of methods have been proposed but almost all the analysis has been empirical, making comparisons of results difficult and providing little direction to the designer of new systems. In this paper, we characterize the performance of two classes of head-motion predictors by analyzing them in the frequency domain. The first predictor is a polynomial extrapolation and the other is based on the Kalman filter. Our analysis shows that even with perfect, noise-free inputs, the error in predicted position grows rapidly with increasing prediction intervals and input signal frequencies. Given the spectra of the original head motion, this analysis estimates the spectra of the predicted motion, quantifying a predictor's performance on different systems and applications. Acceleration sensors are shown to be more useful to a predictor than velocity sensors. The methods described will enable designers to determine maximum acceptable system delay based on maximum tolerable error and the characteristics of user motions in the application.
Curiosity and exploration: facilitating positive subjective experiences and personal growth opportunities.

In an effort to expand research on curiosity, we elaborate on a theoretical model that informs research on the design of a new measure and the nomological network of curiosity. Curiosity was conceptualized as a positive emotional-motivational system associated with the recognition, pursuit, and self-regulation of novelty and challenge. Using 5 independent samples, we developed the Curiosity and Exploration Inventory (CEI) comprising 2 dimensions: exploration (appetitive strivings for novelty and challenge) and absorption (full engagement in specific activities). The CEI has good psychometric properties, is relatively unaffected by socially desirable responding, is relatively independent from positive affect, and has a nomological network consistent with our theoretical framework. Predicated on our personal growth facilitation model, we discuss the potential role of curiosity in advancing understanding of various psychological phenomena.