nils-herrmann/clean_scirepeval huggingface dataset:
Mapping learning and game mechanics for serious games analysis

While there is a consensus on the instructional potential of Serious Games (SGs), there is still a lack of methodologies and tools not only for design but also to support analysis and assessment. Filling this gap is one of the main aims of the Games and Learning Alliance (GALA, www.galanoe.eu) European Network of Excellence on Serious Games (SGs), which has a focus upon pedagogy-driven SGs. This paper relies on the assumption that the fundamental aspect of SG design consists in the translation of learning goals/practices into mechanical element of game-play, serving to an instructional purpose beside that of play and fun. This paper proposes the Learning Mechanics-Game Mechanics (LM-GM) model, which supports SG analysis and design by allowing reflection on the various pedagogical and game elements in a SG. The LM-GM model includes a set of pre-defined game mechanics and pedagogical elements that we have abstracted from literature on game studies and learning theories. Designers and analysts can exploit these mechanics to draw the LM-GM map for a game, so as to identify and highlight its main pedagogical and entertainment features, and their interrelations. The tool may also be useful for teachers to evaluate the effectiveness of a given game and better understand how to implement it in educational settings. A case study is reported to illustrate the framework’s support in determining how game-play and pedagogy intertwine in a SG. Finally, the paper presents the results of two comparative user tests demonstrating the advantages of the proposed model with respect to a similar state-of-the-art framework.
A fractional order fuzzy PID controller for binary distillation column control

Expert and intelligent control schemes have recently emerged out as a promising solution with robustness which can efficiently deal with the nonlinearities, along with various types of modelling uncertainties, present in different real world systems e.g. binary distillation column. This paper is an attempt to propose an intelligent control system which takes the form of a Fractional Order Fuzzy Proportional – Integral – Derivative (FOFPID) controller which is investigated as a solution to deal with the complex dynamic nature of the distillation column. The FOFPID controller is an extension of an existing formula based self tuning fuzzy Proportional Integral controller structure, which varies its gains at run time in accordance with the instantaneous error and rate of change of error. The FOFPID controller is a Takagi-Sugeno (TS) model based fuzzy adaptive controller comprising of non-integer order of integration and differentiation operators used in the controller. It has been observed that inclusion of non-integer order of the integration and differentiation operators made the controller scheme more robust. For the performance evaluation of the proposed scheme, the performance of FOFPID controller is compared with that of its integer order counterpart, a Fuzzy Proportional – Integral – Derivative (FPID) controller. The parameters of both the controllers were optimized for minimum integral of absolute error (IAE) using a bio-inspired global optimization algorithm, Genetic Algorithm (GA). Intensive LabVIEW TM simulation studies were performed which included setpoint tracking with and without uncertainties, disturbance rejection, and noise suppression investigations. For testing the parameter uncertainty handling capability of the proposed controller, uncertain and time varying relative volatility and uncertain tray hydraulic constant were applied. Also, for the disturbance rejection studies, intensive simulations were conducted, which included two most common causes of disturbance i.e. variation in feed composition and variation in feed flow rate. All the simulation investigations clearly suggested that FOFPID controller provided superior performance over FPID controller for each case study i.e. setpoint tracking, disturbance rejection, noise suppression and parameter uncertainties.
FRIEND SUGGESTION SYSTEM FOR THE SOCIAL NETWORK BASED ON USER BEHAVIOR

Now-a-days online social networks such as Facebook, Twitter, Google+, LinkedIn, and others have become significantly popular all over the world and people are using it throughout their daily lives. The number of users in the social networks is increasing day by day. Besides traditional desktop PCs and laptops, new emerging mobile devices makes it easier to make social networking. In online social network user behavior means various social activities that users can do online, such as friendship creation, content publishing, profile browsing, messaging, and commenting, liking, sharing and so on. So we are proposing to suggest one person to another person as a friend based these behaviors.
Scalable and Secure Sharing of Personal Health Records in Cloud Computing Using Attribute-Based Encryption

Personal health record (PHR) is an emerging patient-centric model of health information exchange, which is often outsourced to be stored at a third party, such as cloud providers. However, there have been wide privacy concerns as personal health information could be exposed to those third party servers and to unauthorized parties. To assure the patients' control over access to their own PHRs, it is a promising method to encrypt the PHRs before outsourcing. Yet, issues such as risks of privacy exposure, scalability in key management, flexible access, and efficient user revocation, have remained the most important challenges toward achieving fine-grained, cryptographically enforced data access control. In this paper, we propose a novel patient-centric framework and a suite of mechanisms for data access control to PHRs stored in semitrusted servers. To achieve fine-grained and scalable data access control for PHRs, we leverage attribute-based encryption (ABE) techniques to encrypt each patient's PHR file. Different from previous works in secure data outsourcing, we focus on the multiple data owner scenario, and divide the users in the PHR system into multiple security domains that greatly reduces the key management complexity for owners and users. A high degree of patient privacy is guaranteed simultaneously by exploiting multiauthority ABE. Our scheme also enables dynamic modification of access policies or file attributes, supports efficient on-demand user/attribute revocation and break-glass access under emergency scenarios. Extensive analytical and experimental results are presented which show the security, scalability, and efficiency of our proposed scheme.
An innovative oscillometric blood pressure measurement: Getting rid of the traditional envelope

Oscillometric blood pressure devices are popular and are considered part of the family's medical chest at home. The popularity of these devices for private use is not shared by physicians mainly due to the fact that the blood pressures are computed instead of measured. The classical way to compute the systolic and diastolic blood pressure is based on the envelope of the oscillometric waveform. The algorithm to compute the blood pressures from the waveform is firm dependent, often patented and lacks scientific foundation. In this paper, we propose a totally new approach. Instead of the envelope of the oscillometric waveform, we use a statistical test to pin-point the time instances where the systolic and diastolic blood pressures are measured in the cuff. This technique has the advantage of being mathematically well-posed instead of the ill-posed problem of envelope fitting. Hence, in order to calibrate the oscillometric blood pressure monitor it is sufficient to make the statistical test unbiased.
Am I normal? A systematic review and construction of nomograms for flaccid and erect penis length and circumference in up to 15,521 men.

To systematically review and create nomograms of flaccid and erect penile size measurements.



 measurement of penis size by a health professional using a standard procedure; a minimum of 50 participants per sample.



samples with a congenital or acquired penile abnormality, previous surgery, complaint of small penis size or erectile dysfunction.  calculation of a weighted mean and pooled standard deviation (SD) and simulation of 20,000 observations from the normal distribution to generate nomograms of penis size.



Nomograms for flaccid pendulous [n = 10,704, mean (SD) 9.16 (1.57) cm] and stretched length [n = 14,160, mean (SD) 13.24 (1.89) cm], erect length [n = 692, mean (SD) 13.12 (1.66) cm], flaccid circumference [n = 9407, mean (SD) 9.31 (0.90) cm], and erect circumference [n = 381, mean (SD) 11.66 (1.10) cm] were constructed. Consistent and strongest significant correlation was between flaccid stretched or erect length and height, which ranged from r = 0.2 to 0.6.



relatively few erect measurements were conducted in a clinical setting and the greatest variability between studies was seen with flaccid stretched length.



Penis size nomograms may be useful in clinical and therapeutic settings to counsel men and for academic research.
FTP-SC: Fuzzy Topology Preserving Stroke Correspondence

Stroke correspondence construction is a precondition for vectorized 2D animation inbetweening and remains a challenging problem. This paper introduces the FTP-SC, a fuzzy topology preserving stroke correspondence technique, which is accurate and provides the user more effective control on the correspondence result than previous matching approaches. The method employs a two-stage scheme to progressively establish the stroke correspondence construction between the keyframes. In the first stage, the stroke correspondences with high confidence are constructed by enforcing the preservation of the so-called “fuzzy topology” which encodes intrinsic connectivity among the neighboring strokes. Starting with the high-confidence correspondences, the second stage performs a greedy matching algorithm to generate a full correspondence between the strokes. Experimental results show that the FTP-SC outperforms the existing approaches and can establish the stroke correspondence with a reasonable amount of user interaction even for keyframes with large geometric and spatial variations between strokes. CCS Concepts •Computing methodologies → Animation; Parametric curve and surface models;
Computer Vision Accelerators for Mobile Systems based on OpenCL GPGPU Co-Processing

In this paper, we present an OpenCL-based heterogeneous implementation of a computer vision algorithm – image inpainting-based object removal algorithm – on mobile devices. To take advantage of the computation power of the mobile processor, the algorithm workflow is partitioned between the CPU and the GPU based on the profiling results on mobile devices, so that the computationally-intensive kernels are accelerated by the mobile GPGPU (general-purpose computing using graphics processing units). By exploring the implementation trade-offs and utilizing the proposed optimization strategies at different levels including algorithm optimization, parallelism optimization, and memory access optimization, we significantly speed up the algorithm with the CPU-GPU heterogeneous implementation, while preserving the quality of the output images. Experimental results show that heterogeneous computing based on GPGPU co-processing can significantly speed up the computer vision algorithms and makes them practical on real-world mobile devices.
Multiobjective locomotion optimization of quadruped robot with different 2DOF configurations of actuated spine

This paper addresses the problem of finding a set of optimal foot and spine trajectories for a biologically inspired quadruped robot in order to obtain energy optimal and fast locomotion in forward direction. Based on the previous work of finding optimal foot trajectories we now extend the scope of problem by investigating the effects of an added 2DOF actuated spine on the characteristics of robot locomotion in comparison with rigid spine. To tackle this problem a multiobjective genetic optimization algorithm was used. Purpose of the optimization procedure is to give a better insight in which of the two spine configurations is more beneficial to studied bound and trot gaits and how to design a control strategy that utilizes the spine in an effective way.
Optimal sizing method for stand-alone hybrid solar – wind system with LPSP technology by using genetic algorithm

System power reliability under varying weather conditions and the corresponding system cost are the two main concerns for designing hybrid solar–wind power generation systems. This paper recommends an optimal sizing method to optimize the configurations of a hybrid solar–wind system employing battery banks. Based on a genetic algorithm (GA), which has the ability to attain the global optimum with relative computational simplicity, one optimal sizing method was developed to calculate the optimum system configuration that can achieve the customers required loss of power supply probability (LPSP) with a minimum annualized cost of system (ACS). The decision variables included in the optimization process are the PV module number, wind turbine number, battery number, PV module slope angle and wind turbine installation height. The proposed method has been applied to the analysis of a hybrid system which supplies power for a telecommunication relay station, and good optimization performance has been found. Furthermore, the relationships between system power reliability and system configurations were also given.
A Relational Approach to Monitoring Complex Systems

Monitoring is an essential part of many program development tools, and plays a central role in debugging, optimization, status reporting, and reconfiguration. Traditional monitoring techniques are inadequate when monitoring complex systems such as multiprocessors or distributed systems. A new approach is described in which a historical database forms the conceptual basis for the information processed by the monitor. This approach permits advances in specifying the low-level data collection, specifying the analysis of the collected data, performing the analysis, and displaying the results. Two prototype implementations demonstrate the feasibility of the approach.
Analytics-driven data ingestion and derivation in the AWESOME polystore

Polystores, i.e., data management systems that use multiple stores for different data models, are gaining popularity. We are developing a polystore-based system called AWESOME to support social data analytics. The AWESOME polystore can support relational, semistructured, graph and text data and houses a Spark computation engine to produce derived data during ingestion. ADIL, the data ingestion language of AWESOME allows a user to flexibly specify the placement of original and derived data into and across component stores and the computation engine. The paper also outlines a number of optimization strategies for managing data placement in AWESOME.
Photographic tone reproduction for digital images

A classic photographic task is the mapping of the potentially high dynamic range of real world luminances to the low dynamic range of the photographic print. This tone reproduction problem is also faced by computer graphics practitioners who must map digital images to a low dynamic range print or screen. The work presented in this paper leverages the time-tested techniques of photographic practice to develop a new tone reproduction operator. In particular, we use and extend the techniques developed by Ansel Adams to deal with digital images. The resulting algorithm is simple and is shown to produce good results for the wide variety of images that we have tested. Photographic Tone Reproduction for Digital Images Erik Reinhard University of Utah Michael Stark University of Utah Peter Shirley University of Utah Jim Ferwerda Cornell University
Improved novel view synthesis from depth image with large baseline

In this paper, a new algorithm is developed for recovering the large disocclusion regions in depth image based rendering (DIBR) systems on 3DTV. For the DIBR systems, undesirable artifacts occur in the disocclusion regions by using the conventional view synthesis techniques especially with large baseline. Three techniques are proposed to improve the view synthesis results. The first is the preprocessing of the depth image by using the bilateral filter, which helps to sharpen the discontinuous depth changes as well as to smooth the neighboring depth of similar color, thus restraining noises from appearing on the warped images. Secondly, on the warped image of a new viewpoint, we fill the disocclusion regions on the depth image with the background depth levels to preserve the depth structure. For the color image, we propose the depth-guided exemplar-based image inpainting that combines the structural strengths of the color gradient to preserve the image structure in the restored regions. Finally, a trilateral filter, which simultaneous combines the spatial location, the color intensity, and the depth information to determine the weighting, is applied to enhance the image synthesis results. Experimental results are shown to demonstrate the superior performance of the proposed novel view synthesis algorithm compared to the traditional methods.
Autonomous Cross-Domain Knowledge Transfer in Lifelong Policy Gradient Reinforcement Learning

Online multi-task learning is an important capability for lifelong learning agents, enabling them to acquire models for diverse tasks over time and rapidly learn new tasks by building upon prior experience. However, recent progress toward lifelong reinforcement learning (RL) has been limited to learning from within a single task domain. For truly versatile lifelong learning, the agent must be able to autonomously transfer knowledge between different task domains. A few methods for cross-domain transfer have been developed, but these methods are computationally inefficient for scenarios where the agent must learn tasks consecutively. In this paper, we develop the first cross-domain lifelong RL framework. Our approach efficiently optimizes a shared repository of transferable knowledge and learns projection matrices that specialize that knowledge to different task domains. We provide rigorous theoretical guarantees on the stability of this approach, and empirically evaluate its performance on diverse dynamical systems. Our results show that the proposed method can learn effectively from interleaved task domains and rapidly acquire high performance in new domains.
The relative impact of cognitive anxiety and self-confidence upon sport performance: a meta-analysis.

This meta-analysis (k = 48) investigated two relationships in competitive sport: (1) state cognitive anxiety with performance and (2) state self-confidence with performance. The cognitive anxiety mean effect size was r = -0.10 (P < 0.05). The self-confidence mean effect size was r = 0.24 (P < 0.001). A paired-samples t-test revealed that the magnitude of the self-confidence mean effect size was significantly greater than that of the cognitive anxiety mean effect size. The moderator variables for the cognitive anxiety-performance relationship were sex and standard of competition. The mean effect size for men (r = -0.22) was significantly greater than the mean effect size for women (r = -0.03). The mean effect size for high-standard competition (r = -0.27) was significantly greater than that for comparatively low-standard competition (r = -0.06). The significant moderator variables for the self-confidence-performance relationship were sex, standard of competition and measurement. The mean effect size for men (r = 0.29) was significantly greater than that for women (r = 0.04) and the mean effect size for high-standard competition (r = 0.33) was significantly greater than that for low-standard competition (r = 0.16). The mean effect size derived from studies employing the Competitive State Anxiety Inventory-2 (r = 0.19) was significantly smaller than the mean effect size derived from studies using other measures of self-confidence (r = 0.38). Measurement issues are discussed and future research directions are offered in light of the results.
Free-form shape design using triangulated surfaces

We present an approach to modeling with truly mutable yet completely controllable free-form surfaces of arbitrary topology. Surfaces may be pinned down at points and along curves, cut up and smoothly welded back together, and faired and reshaped in the large. This style of control is formulated as a constrained shape optimization, with minimization of squared principal curvatures yielding graceful shapes that are free of the parameterization worries accompanying many patch-based approaches. Triangulated point sets are used to approximate these smooth variational surfaces, bridging the gap between patch-based and particle-based representations. Automatic refinement, mesh smoothing, and re-triangulation maintain a good computational mesh as the surface shape evolves, and give sample points and surface features much of the freedom to slide around in the surface that oriented particles enjoy. The resulting surface triangulations are constructed and maintained in real time.
Artificial Intelligence techniques: An introduction to their use for modelling environmental systems

Knowledge-based or Artificial Intelligence techniques are used increasingly as alternatives to more classical techniques to model environmental systems. We review some of them and their environmental applicability, with examples and a reference list. The techniques covered are case-based reasoning, rule-based systems, artificial neural networks, fuzzy models, genetic algorithms, cellular automata, multi-agent systems, swarm intelligence, reinforcement learning and hybrid systems.
Analyzing Enterprise Architecture in National Governments: The Cases of Denmark and the Netherlands

National enterprise architectures (NEA) promise to fill the gap between policy and implementation. NEAs are embedded within an institutional environment consisting of active players capable of responding strategically and innovatively to architectural initiatives, which might complicate NEA adoption. In this paper we analyze the efforts of two European national governments in developing enterprise architecture. Grounded in institutional theory and practice we develop an analytical framework and use this framework to analyze the efforts of two countries, Denmark and the Netherlands. Our framework and analysis draws the attention to the need to take a broader perspective on enterprise architecture, especially governance aspects determine the adoption and diffusion of NEA
Treatment of Lower lip Mucocele with Diode Laser - A Novel Approach

Mucoceles are benign, mucus containing cystic lesions of the minor salivary glands. Most dental literature reports a higher incidence of mucocele in young patients, with trauma being a leading cause. The purpose of this report was to describe a clinical case of a 22 year old female with a 6 mm mucocele on the lower lip treated by a high-intensity diode laser. Diode laser surgery provided satisfactory results, which was rapid, bloodless, and well accepted by patients. Postoperative problems, discomfort, and scarring were minimal. The histopathological report confirmed the presurgical diagnosis. No relapse was observed upto one year after surgery.  (2013) 2 Suppl 1, 102-108