nils-herrmann/clean_scirepeval huggingface dataset:
Live-action Virtual Reality Games

This paper proposes the concept of “liveaction virtual reality games” as a new genre of digital games based on an innovative combination of live-action, mixed-reality, context-awareness, and interaction paradigms that comprise tangible objects, context-aware input devices, and embedded/embodied interactions. Live-action virtual reality games are “live-action games” because a player physically acts out (using his/her real body and senses) his/her “avatar” (his/her virtual representation) in the game stage – the mixed-reality environment where the game happens. The game stage is a kind of “augmented virtuality” – a mixedreality where the virtual world is augmented with real-world information. In live-action virtual reality games, players wear HMD devices and see a virtual world that is constructed using the physical world architecture as the basic geometry and context information. Physical objects that reside in the physical world are also mapped to virtual elements. Liveaction virtual reality games keeps the virtual and real-worlds superimposed, requiring players to physically move in the environment and to use different interaction paradigms (such as tangible and embodied interaction) to complete game activities. This setup enables the players to touch physical architectural elements (such as walls) and other objects, “feeling” the game stage. Players have free movement and may interact with physical objects placed in the game stage, implicitly and explicitly. Live-action virtual reality games differ from similar game concepts because they sense and use contextual information to create unpredictable game experiences, giving rise to emergent gameplay.
THE EFFECT OF PERCEIVED BENEFITS , TRUST , QUALITY , BRAND AWARENESS / ASSOCIATIONS AND BRAND LOYALTY ON INTERNET BANKING BRAND EQUITY

This research examines the interrelationships of trust, brand awareness/associations, perceived quality and brand loyalty in building Internet banking brand equity. The model was based on data from customers using online banking (customers of an international bank) using the PLS technique. The results suggest that perceived quality and brand loyalty are more important to explain the Internet banking brand equity than brand awareness/associations and trust. Interestingly, trust contributes only indirectly, through perceived quality and brand awareness/association to Internet banking brand equity. Online perceived benefits impact positively on customers’ trust and online perceived risks tend to be lower when trust increases.
Edge Computing Resource Management and Pricing for Mobile Blockchain

The mining process in blockchain requires solving a proof-of-work puzzle, which is resource expensive to implement in mobile devices due to the high computing power and energy needed. In this paper, we, for the first time, consider edge computing as an enabler for mobile blockchain. In particular, we study edge computing resource management and pricing to support mobile blockchain applications in which the mining process of miners can be offloaded to an edge computing service provider. We formulate a two-stage Stackelberg game to jointly maximize the profit of the edge computing service provider and the individual utilities of the miners. In the first stage, the service provider sets the price of edge computing nodes. In the second stage, the miners decide on the service demand to purchase based on the observed prices. We apply the backward induction to analyze the sub-game perfect equilibrium in each stage for both uniform and discriminatory pricing schemes. For the uniform pricing where the same price is applied to all miners, the existence and uniqueness of Stackelberg equilibrium are validated by identifying the best response strategies of the miners. For the discriminatory pricing where the different prices are applied to different miners, the Stackelberg equilibrium is proved to exist and be unique by capitalizing on the Variational Inequality theory. Further, the real experimental results are employed to justify our proposed model.
Design of Cuk Converter Powered by PV Array

This study presents PV power based cuk converter for dc load application. The maximum power from the sun radiation is obtained by sun tracking and Maximum Power Point Tracking (MPPT). The sun tracking is implemented by the stepper motor control and MPPT is implemented by the Cuk converter and the load voltage is maintained constant irrespective of the variation in solar power. This technique improves the dynamic and steady state characteristics of the system. The simulation was done in MATLAB simulink and the experiments are carried out and the results are presented.
Error Correcting Graph Matching: On the Influence of the Underlying Cost Function

ÐThis paper investigates the influence of the cost function on the optimal match between two graphs. It is shown that, for a given cost function, there are an infinite number of other cost functions that lead, for any given pair of graphs, to the same optimal error correcting matching. Furthermore, it is shown that well-known concepts from graph theory, such as graph isomorphism, subgraph isomorphism, and maximum common subgraph, are special cases of optimal error correcting graph matching under particular cost functions. Index TermsÐGraph, subgraph, maximum common subgraph, graph isomorphism, subgraph isomorphism, graph matching, error correcting graph matching, cost function, edit operation, graph edit distance.
MICROCONTROLLER BASED CAPACITANCE METER

A microcontroller based capacitance meter using 89C52 microcontroller for the measurement of capacitance has been design and developed. It is based on the principle of charging and discharging of the capacitor. Atmel’s AT89C52 microcontroller is used in the present study. Further, an LCD module is interfaced with the microcontroller in 4-bit mode, which reduces the hardware complexity. Software is developed in C using Kiel’s C-cross compiler. The instrument system covers a range 1pF to 1000μF. The paper deals with the hardware and software details. This instrument has auto range selection and auto calibration facility i.e., auto reset facility. This instrument is provided with 400-value storage capacity. The system is quite successful in the measurement of capacitance with an accuracy of ±1 % and capacitance of whole construction is around 10 pF. The power consumption is less than 1W.
Autonomous vehicles control in the VisLab Intercontinental Autonomous Challenge

1367-5788/$ see front matter Crown Copyright 2 http://dx.doi.org/10.1016/j.arcontrol.2012.03.012 q An earlier version of this paper appeared in Broggi control system for the VisLab Intercontinental Auton Transportation Systems (ITSC), Madeira, Portugal, Oct ⇑ Corresponding author. E-mail addresses: broggi@ce.unipr.it (A. Broggi), m zani@ce.unipr.it (P. Zani), coati@ce.unipr.it (A. Coati), pa 1 This test, carried out by VisLab in summer 2010 vehicles drive themselves from Parma, Italy, to Shang route, mostly across regions for which digital map information were not available.
TEEI - A Mobile Security Infrastructure for TEE Integration

Mobile security becomes a hot topic recently, especially in mobile payment and privacy data fields. Traditional solution can't keep a good balance between convenience and security. Against this background, a dual OS security solution named Trusted Execution Environment (TEE) is proposed and implemented by many institutions and companies. However, it raised TEE fragmentation and control problem. Addressing this issue, a mobile security infrastructure named Trusted Execution Environment Integration (TEEI) is presented to integrate multiple different TEEs. By using Trusted Virtual Machine (TVM) tech-nology, TEEI allows multiple TEEs running on one secure world on one mobile device at the same time and isolates them safely. Furthermore, a Virtual Network protocol is proposed to enable communication and cooperation among TEEs which includes TEE on TVM and TEE on SE. At last, a SOA-like Internal Trusted Service (ITS) framework is given to facilitate the development and maintenance of TEEs.
MegDet: A Large Mini-Batch Object Detector

The development of object detection in the era of deep learning, from R-CNN [11], Fast/Faster R-CNN [10, 31] to recent Mask R-CNN [14] and RetinaNet [24], mainly come from novel network, new framework, or loss design. However, mini-batch size, a key factor for the training of deep neural networks, has not been well studied for object detection. In this paper, we propose a Large Mini-Batch Object Detector (MegDet) to enable the training with a large minibatch size up to 256, so that we can effectively utilize at most 128 GPUs to significantly shorten the training time. Technically, we suggest a warmup learning rate policy and Cross-GPU Batch Normalization, which together allow us to successfully train a large mini-batch detector in much less time (e.g., from 33 hours to 4 hours), and achieve even better accuracy. The MegDet is the backbone of our submission (mmAP 52.5%) to COCO 2017 Challenge, where we won the 1st place of Detection task.
A Collection of Definitions of Intelligence

Despite a long history of research and debate, there is still no standard definition of intelligence. This has lead some to believe that intelligence may be approximately described, but cannot be fully defined. We believe that this degree of pessimism is too strong. Although there is no single standard definition, if one surveys the many definitions that have been proposed, strong similarities between many of the definitions quickly become obvious. In many cases different definitions, suitably interpreted, actually say the same thing but in different words. This observation lead us to believe that a single general and encompassing definition for arbitrary systems was possible. Indeed we have constructed a formal definition of intelligence, called universal intelligence [21], which has strong connections to the theory of optimal learning agents [19]. Rather than exploring very general formal definitions of intelligence, here we will instead take the opportunity to present the many informal definitions that we have collected over the years. Naturally, compiling a complete list would be impossible as many definitions of intelligence are buried deep inside articles and books. Nevertheless, the 70 odd definitions presented below are, to the best of our knowledge, the largest and most well referenced collection there is. We continue to add to this collect as we discover further definitions, and keep the most up to date version of the collection available online [22]. If you know of additional definitions that we could add, please send us an email.
Activity theory for designing mobile learning

Mobile computing offers potential opportunities for students’ learning. It is important to have an operational understanding of the context in developing a user interface that is both useful and flexible. The author believes that the complexity of the relationships involved can be analysed using activity theory. Activity theory, as a social and cultural psychological theory, can be used to design a mobile learning environment. This paper presents the use of activity theory as a framework for describing the components of an activity system for the design of a context-aware mobile learning application.
Advances in Automated Knowledge Base Construction

Recent years have seen significant advances on the creation of large-scale knowledge bases (KBs). Extracting knowledge from Web pages, and integrating it into a coherent KB is a task that spans the areas of natural language processing, information extraction, information integration, databases, search and machine learning. Some of the latest developments in the field were presented at the AKBC-WEKEX workshop on knowledge extraction at the NAACL-HLC 2012 conference. This workshop included 23 accepted papers, and 11 keynotes by senior researchers. The workshop had speakers from all major search engine providers, government institutions, and the leading universities in the field. In this survey, we summarize the papers, the keynotes, and the discussions at this workshop.
Multiple Spatio-temporal Feature Learning for Video-based Emotion Recognition in the Wild

The difficulty of emotion recognition in the wild (EmotiW) is how to train a robust model to deal with diverse scenarios and anomalies. The Audio-video Sub-challenge in EmotiW contains audio-video short clips with several emotional labels and the task is to distinguish which label the video belongs to. For the better emotion recognition in videos, we propose a multiple spatio-temporal feature fusion (MSFF) framework, which can more accurately depict emotional information in spatial and temporal dimensions by two mutually complementary sources, including the facial image and audio. The framework is consisted of two parts: the facial image model and the audio model. With respect to the facial image model, three different architectures of spatial-temporal neural networks are employed to extract discriminative features about different emotions in facial expression images. Firstly, the high-level spatial features are obtained by the pre-trained convolutional neural networks (CNN), including VGG-Face and ResNet-50 which are all fed with the images generated by each video. Then, the features of all frames are sequentially input to the Bi-directional Long Short-Term Memory (BLSTM) so as to capture dynamic variations of facial appearance textures in a video. In addition to the structure of CNN-RNN, another spatio-temporal network, namely deep 3-Dimensional Convolutional Neural Networks (3D CNN) by extending the 2D convolution kernel to 3D, is also applied to attain evolving emotional information encoded in multiple adjacent frames. For the audio model, the spectrogram images of speech generated by preprocessing audio, are also modeled in a VGG-BLSTM framework to characterize the affective fluctuation more efficiently. Finally, a fusion strategy with the score matrices of different spatio-temporal networks gained from the above framework is proposed to boost the performance of emotion recognition complementally. Extensive experiments show that the overall accuracy of our proposed MSFF is 60.64%, which achieves a large improvement compared with the baseline and outperform the result of champion team in 2017.
The 12 th man ? : refereeing bias in English and German soccer

The paper investigates potential bias in awards of player disciplinary sanctions, in the form of cautions (yellow cards) and dismissals (red cards) by referees in the English Premier League and the German Bundesliga. Previous studies of behaviour of soccer referees have not adequately incorporated within-game information.Descriptive statistics from our samples clearly show that home teams receive fewer yellow and red cards than away teams. These differences may be wrongly interpreted as evidence of bias where the modeller has failed to include withingame events such as goals scored and recent cards issued.What appears as referee favouritism may actually be excessive and illegal aggressive behaviour by players in teams that are behind in score. We deal with these issues by using a minute-by-minute bivariate probit analysis of yellow and red cards issued in games over six seasons in the two leagues. The significance of a variable to denote the difference in score at the time of sanction suggests that foul play that is induced by a losing position is an important influence on the award of yellow and red cards. Controlling for various pre-game and within-game variables, we find evidence that is indicative of home team favouritism induced by crowd pressure: in Germany home teams with running tracks in their stadia attract more yellow and red cards than teams playing in stadia with less distance between the crowd and the pitch. Separating the competing teams in matches by favourite and underdog status, as perceived by the betting market, yields further evidence, this time for both leagues, that the source of home teams receiving fewer cards is not just that they are disproportionately often the favoured team and disproportionately ahead in score.Thus there is evidence that is consistent with pure referee bias in relative treatments of home and away teams.
Lifelong Learning for Sentiment Classification

This paper proposes a novel lifelong learning (LL) approach to sentiment classification. LL mimics the human continuous learning process, i.e., retaining the knowledge learned from past tasks and use it to help future learning. In this paper, we first discuss LL in general and then LL for sentiment classification in particular. The proposed LL approach adopts a Bayesian optimization framework based on stochastic gradient descent. Our experimental results show that the proposed method outperforms baseline methods significantly, which demonstrates that lifelong learning is a promising research direction.
Secondary trauma symptoms in clinicians: a critical review of the construct, specificity, and implications for trauma-focused treatment.

Advocates of the concept of secondary traumatization propose that clinicians who provide trauma-focused treatment may be particularly at risk for experiencing secondary trauma symptoms. This specific symptom presentation purportedly develops following exposure to the traumatic experiences described by their clients. Consequently, these professionals have advocated for increases in resources devoted to the prevention and treatment of secondary trauma symptoms (e.g., enhanced clinician training, increase in availability of treatment options for affected trauma workers, etc.). A review of empirical literature examining prevalence and specificity of secondary trauma symptoms in trauma clinicians is provided. Findings are mixed and often indicate that trauma clinicians are not frequently experiencing "clinically significant" levels of symptoms and that these symptoms may not be uniquely associated with trauma-focused treatment. Finally, it is argued that additional clarification and research on the criterion, course, and associated impairment are needed. Recommendations for future research are provided.
A Systematic Review of the Use of Blockchain in Healthcare

Blockchain technology enables a decentralized and distributed environment with no need for a central authority. Transactions are simultaneously secure and trustworthy due to the use of cryptographic principles. In recent years, blockchain technology has become very trendy and penetrated different domains, mostly due to the popularity of cryptocurrencies. One field where blockchain technology has tremendous potential is healthcare, due to the need for a more patient-centric approach to healthcare systems and to connect disparate systems and increase the accuracy of electronic healthcare records (EHRs). In this systematic review, an analysis of state-of-the-art blockchain research in the field of healthcare is conducted. The aim is to reveal the potential applications of the technology and to highlight the challenges and possible directions of blockchain research in healthcare. First, background information is discussed, followed by a description of the exact methodology used in this paper. Next, an analysis of the results is given, which includes a bibliometric overview, an analysis of gathered data and its properties, and the results of a literature quality assessment. Lastly, there is a discussion of the results from the analysis. The findings indicate that blockchain technology research in healthcare is increasing and it is mostly used for data sharing, managing health records and access control. Other scenarios are very rare. Most research is aimed at presenting novel structural designs in the form of frameworks, architectures or models. Findings also show that technical details about the used blockchain elements are not given in most of the analyzed publications and that most research does not present any prototype implementation or implementation details. Often even with a prototype implementation, no details about blockchain elements are given.
Fifty Years of Research in ARDS. Is Extracorporeal Circulation the Future of Acute Respiratory Distress Syndrome Management?

Mechanical ventilation (MV) remains the cornerstone of acute respiratory distress syndrome (ARDS) management. It guarantees sufficient alveolar ventilation, high FiO2 concentration, and high positive end-expiratory pressure levels. However, experimental and clinical studies have accumulated, demonstrating that MV also contributes to the high mortality observed in patients with ARDS by creating ventilator-induced lung injury. Under these circumstances, extracorporeal lung support (ECLS) may be beneficial in two distinct clinical settings: to rescue patients from the high risk for death associated with severe hypoxemia, hypercapnia, or both not responding to maximized conventional MV, and to replace MV and minimize/abolish the harmful effects of ventilator-induced lung injury. High extracorporeal blood flow venovenous extracorporeal membrane oxygenation (ECMO) may therefore rescue the sickest patients with ARDS from the high risk for death associated with severe hypoxemia, hypercapnia, or both not responding to maximized conventional MV. Successful venovenous ECMO treatment in patients with extremely severe H1N1-associated ARDS and positive results of the CESAR trial have led to an exponential use of the technology in recent years. Alternatively, lower-flow extracorporeal CO2 removal devices may be used to reduce the intensity of MV (by reducing Vt from 6 to 3-4 ml/kg) and to minimize or even abolish the harmful effects of ventilator-induced lung injury if used as an alternative to conventional MV in nonintubated, nonsedated, and spontaneously breathing patients. Although conceptually very attractive, the use of ECLS in patients with ARDS remains controversial, and high-quality research is needed to further advance our knowledge in the field.
Corporate social responsibility and economic performance in the top British companies : are they linked ?

This paper investigates the relationship between corporate social responsibility (CSR) and the economic performance of corporations. It first examines the theories that suggest a relationship between the two. To test these theories, measures of CSR performance and disclosure developed by the New Consumer Group were analysed against the (past, concurrent and subsequent to CSR performance period) economic performance of 56 large UK companies. Economic performance included: financial (return on capital employed, return on equity and gross profit to sales ratios); and capital market performance (systematic risk and excess market valuation). The results supported the conclusion that (past, concurrent and subsequent) economic performance is related to both CSR performance and disclosure. However, the relationships were weak and lacked an overall consistency. For example, past economic performance was found to partly explain variations in firms’ involvement in philanthropic activities. CSR disclosure was affected (positively) by both a firm’s CSR performance and its concurrent financial performance. Involvement in environmental protection activities was found to be negatively correlated with subsequent financial performance. Whereas, a firm’s policies regarding women’s positions seem to be more rewarding in terms of positive capital market responses (performance) in the subsequent period. Donations to the Conservative Party were found not to be related to companies’ (past, concurrent or subsequent) financial and/or capital performance. operation must fall within the guidelines set by society; and • businesses act as moral agents within