nils-herrmann/clean_scirepeval huggingface dataset:
A reference architecture for educational data mining

In this paper we present a reference architecture for ETL stages of EDM and LA that works with different data formats and different extraction sites, ensuring privacy and making easier for new participants to enter into the process without demanding more computing power. Considering scenarios with a multitude of virtual environments hosting educational activities, accessible through a common infrastructure, we devised a reference model where data generated from interaction between users and among users and the environment itself, are selected, organized and stored in local “baskets”. Local baskets are then collected and grouped in a global basket. Organization resources like item modeling are used in both levels of basket construction. Using this reference upon a client-server architectural style, a reference architecture was developed and has been used to carry out a project for an official foundation linked to Brazilian Ministry of Education, involving educational data mining and sharing of 100+ higher education institutions and their respective virtual environments. In this architecture, a client-collector inside each virtual environment collects information from database and event logs. This information along with definitions obtained from item models are used to build local baskets. A synchronization protocol keeps all item models synced with client-collectors and server-collectors generating global baskets. This approach has shown improvements on ETL like: parallel processing of items, economy on storage space and bandwidth, privacy assurance, better tenacity, and good scalability.
Automatic car number plate recognition

A traffic surveillance system includes detection of vehicles which involves the detection and identification of license plate numbers. This paper proposes an intelligent approach of detecting vehicular number plates automatically using three efficient algorithms namely Ant colony optimization (ACO) used in plate localization for identifying the edges, a character segmentation and extraction algorithm and a hierarchical combined classification method based on inductive learning and SVM for individual character recognition. Initially the performance of the Ant Colony Optimization algorithm is compared with the existing algorithms for edge detection namely Canny, Prewitt, Roberts, Mexican Hat and Sobel operators. The Ant Colony Optimization used in communication systems has certain limitations when used in edge detection like random initial ant position in the image and the heuristic information being highly dictated by transition probabilities. In this paper, modifications like assigning a well-defined initial ant position and making use of weights to calculate heuristic value which will provide additional information about transition probabilities are used to overcome the limitations. Further a character extraction and segmentation algorithm which uses the concept of Kohonen neural network to identify the position and dimensions of characters is presented along with a comparison with the existing Histogram and Connected Pixels approach. Finally an inductive learning based classification method is compared with the Support Vector Machine based classification method and a combined classification method which uses both inductive learning and Support Vector Machine based approach for character recognition is proposed. The proposed character recognition algorithm may be more efficient than the other two.
Decoding algorithm for color QR code: A mobile scanner application

QR codes have revolutionized the industry because of its larger storage capacity and high damage resistance than the traditional barcodes. Color QR code is the future as it provides much higher encoding capacity that the typical B/W QR codes. We propose a color QR code decoding algorithm for mobile applications by considering the color profile of Red, Green and Blue channels respectively. We have developed a prototype by including various image processing techniques and the open source Zxing library. This paper presents an Android based color QR code decoder implementation and performance evaluation. Experimental results show the high success rate of the methodology implemented.
Evolutionary games on graphs

Game theory is one of the key paradigms behind many scientific disciplines from biology to behavioral sciences to economics. In its evolutionary form and especially when the interacting agents are linked in a specific social network the underlying solution concepts and methods are very similar to those applied in non-equilibrium statistical physics. This review gives a tutorial-type overview of the field for physicists. The first four sections introduce the necessary background in classical and evolutionary game theory from the basic definitions to the most important results. The fifth section surveys the topological complications implied by non-mean-field-type social network structures in general. The next three sections discuss in detail the dynamic behavior of three prominent classes of models: the Prisoner’s Dilemma, the Rock–Scissors–Paper game, and Competing Associations. The major theme of the review is in what sense and how the graph structure of interactions can modify and enrich the picture of long term behavioral patterns emerging in evolutionary games.
Energy Harvesting Wireless Communications: A Review of Recent Advances

This paper summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access, and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed, as well as models for energy consumption at the nodes.
Syntax Based Agent Simulation

Space syntax derives from a set of analytic measures of configuration that have been shown to correlate well with how people move through and use buildings and urban environments. Space syntax represents the open space of an environment in terms of the intervisibility of points in space. The measures are thus purely configurational, and take no account of attractors, nor do they make any assumptions about origins and destinations or path planning. Space syntax has found that, despite many proposed higher-level cognitive models, there appears to be a fundamental process that informs human and social usage of an environment. In this paper we describe an exosomatic visual architecture, based on space syntax visibility graphs, giving many agents simultaneous access to the same pre-processed information about the configuration of a space layout. Results of experiments in a simulated retail environment show that a surprisingly simple ‘random next step’ based rule outperforms a more complex ‘destination based’ rule in reproducing observed human movement behaviour. We conclude that the effects of spatial configuration on movement patterns that space syntax studies have found are consistent with a model of individual decision behaviour based on the spatial affordances offered by the morphology of the local visual field.
Simulation of Impulse Voltage Generator and Impulse Testing of Insulator using MATLAB Simulink

The main objectives of this work are of two folds: the first is the design of impulse voltage generator and impulse testing of a standard disc type insulator experimentally. The second is the development of MATLAB Simulink model of the above mentioned experimental setup. Investigation shows that this software is very efficient in studying the effect of parameter changes in the design to obtain the desired impulse voltages and wave shapes from an impulse voltage generator for high voltage applications.
Visualizing the Execution of Java Programs

Jinsight is a tool for exploring a program’s run-time behavior visually. It is helpful for performance analysis, debugging, and any task in which you need to better understand what your Java program is really doing. Jinsight is designed specifically with object-oriented and multithreaded programs in mind. It exposes many facets of program behavior that elude conventional tools. It reveals object lifetimes and communication, and attendant performance bottlenecks. It shows thread interactions, deadlocks, and garbage collector activity. It can also help you find and fix memory leaks, which remain a hazard despite garbage collection. A user explores program execution through one or more views. Jinsight offers several types of views, each geared toward distinct aspects of object-oriented and multithreaded program behavior. The user has several different perspectives from which to discern performance problems, unexpected behavior, or bugs small and large. Moreover, the views are linked to each other in many ways, allowing navigation from one view to another. Navigation makes the collection of views far more powerful than the sum of their individual strengths.
Requirements Elicitation Techniques : Comparative Study

Over the years, software development failures is really a burning issue, might be ascribed to quite a number of attributes, of which, no-compliance of users requirements and using the non suitable technique to elicit user requirements are considered foremost. In order to address this issue and to facilitate system designers, this study had filtered and compared user requirements elicitation technique, based on principles of requirements engineering. This comparative study facilitates developers to build systems based on success stories, making use of a optimistic perspective for achieving a foreseeable future. This paper is aimed at enhancing processes of choosing a suitable technique to elicit user requirements; this is crucial to determine the requirements of the user, as it enables much better software development and does not waste resources unnecessarily. Basically, this study will complement the present approaches, by representing a optimistic and potential factor for every single method in requirements engineering, which results in much better user needs, and identifies novel and distinctive specifications.  Requirements Engineering, Requirements Elicitation Techniques, Conversational methods, Observational methods, Analytic methods, Synthetic methods.
The Sensorimotor System, Part II: The Role of Proprioception in Motor Control and Functional Joint Stability.

To discuss the role of proprioception in motor control and in activation of the dynamic restraints for functional joint stability.



Information was drawn from an extensive MEDLINE search of the scientific literature conducted in the areas of proprioception, motor control, neuromuscular control, and mechanisms of functional joint stability for the years 1970-1999.



Proprioception is conveyed to all levels of the central nervous system. It serves fundamental roles for optimal motor control and sensorimotor control over the dynamic restraints.



Although controversy remains over the precise contributions of specific mechanoreceptors, proprioception as a whole is an essential component to controlling activation of the dynamic restraints and motor control. Enhanced muscle stiffness, of which muscle spindles are a crucial element, is argued to be an important characteristic for dynamic joint stability. Articular mechanoreceptors are attributed instrumental influence over gamma motor neuron activation, and therefore, serve to indirectly influence muscle stiffness. In addition, articular mechanoreceptors appear to influence higher motor center control over the dynamic restraints. Further research conducted in these areas will continue to assist in providing a scientific basis to the selection and development of clinical procedures.
An Asian Origin of Virulent Aeromonas hydrophila Responsible for Disease Epidemics in United States-Farmed Catfish

Since 2009, catfish farming in the southeastern United States has been severely impacted by a highly virulent and clonal population of Aeromonas hydrophila causing motile Aeromonas septicemia (MAS) in catfish. The possible origin of this newly emerged highly virulent A. hydrophila strain is unknown. In this study, we show using whole-genome sequencing and comparative genomics that A. hydrophila isolates from diseased grass carp in China and catfish in the United States have highly similar genomes. Our phylogenomic analyses suggest that U.S. catfish isolates emerged from A. hydrophila populations of Asian origin. Furthermore, we identified an A. hydrophila strain isolated in 2004 from a diseased catfish in Mississippi, prior to the onset of the major epidemic outbreaks in Alabama starting in 2009, with genomic characteristics that are intermediate between those of the Asian and Alabama fish isolates. Investigation of A. hydrophila strain virulence demonstrated that the isolate from the U.S. catfish epidemic is significantly more virulent to both channel catfish and grass carp than is the Chinese carp isolate. This study implicates the importation of fish or fishery products into the United States as the source of highly virulent A. hydrophila that has caused severe epidemic outbreaks in United States-farmed catfish and further demonstrates the potential for invasive animal species to disseminate bacterial pathogens worldwide.



Catfish aquaculture farming in the southeastern United States has been severely affected by the emergence of virulent Aeromonas hydrophila responsible for epidemic disease outbreaks, resulting in the death of over 10 million pounds of catfish. Because the origin of this newly emerged A. hydrophila strain is unknown, this study used a comparative genomics approach to conduct a phylogenomic analysis of A. hydrophila isolates obtained from the United States and Asia. Our results suggest that the virulent isolates from United States-farmed catfish have a recent common ancestor with A. hydrophila isolates from diseased Asian carp. We have also observed that an Asian carp isolate, like recent U.S. catfish isolates, is virulent in catfish. The results from this study suggest that the highly virulent U.S. epidemic isolates emerged from an Asian source and provide another example of the threat that invasive species pose in the dissemination of bacterial pathogens.
Multimodal Dialogue for Ambient Intelligence and Smart Environments

Ambient Intelligence (AmI) and Smart Environments (SmE) are based on three foundations: ubiquitous computing, ubiquitous communication and intelligent adaptive interfaces . This type of systems consists of a series of interconnected computing and sensing devices which surround the user pervasively in his environment and are invisible to him, providing a service that is dynamically adapted to the interaction context, so that users can naturally interact with the system and thus perceive it as intelligent. To ensure such a natural and intelligent interaction, it is necessary to provide an effective, easy, safe and transparent interaction between the user and the system. With this objective, as an attempt to enhance and ease human-to-computer interaction, in the last years there has been an increasing interest in simulating human-tohuman communication, employing the so-called multimodal dialogue systems [46]. These systems go beyond both the desktop metaphor and the traditional speech-only interfaces by incorporating several communication modalities, such as speech, gaze, gestures or facial expressions. Multimodal dialogue systems offer several advantages. Firstly, they can make use of automatic recognition techniques to sense the environment allowing the user to employ different input modalities, some of these technologies are automatic speech recognition [62], natural language processing , face location and tracking [77], gaze tracking [58], lipreading recognition [13], gesture recognition [39], and handwriting recognition [78].
Variational Learning for Recurrent Spiking Networks

We derive a plausible learning rule for feedforward, feedback and lateral connections in a recurrent network of spiking neurons. Operating in the context of a generative model for distributions of spike sequences, the learning mechanism is derived from variational inference principles. The synaptic plasticity rules found are interesting in that they are strongly reminiscent of experimental Spike Time Dependent Plasticity, and in that they differ for excitatory and inhibitory neurons. A simulation confirms the method’s applicability to learning both stationary and temporal spike patterns.
How Psychological Science Informs the Teaching of Reading.

This monograph discusses research, theory, and practice relevant to how children learn to read English. After an initial overview of writing systems, the discussion summarizes research from developmental psychology on children's language competency when they enter school and on the nature of early reading development. Subsequent sections review theories of learning to read, the characteristics of children who do not learn to read (i.e., who have developmental dyslexia), research from cognitive psychology and cognitive neuroscience on skilled reading, and connectionist models of learning to read. The implications of the research findings for learning to read and teaching reading are discussed. Next, the primary methods used to teach reading (phonics and whole language) are summarized. The final section reviews laboratory and classroom studies on teaching reading. From these different sources of evidence, two inescapable conclusions emerge: (a) Mastering the alphabetic principle (that written symbols are associated with phonemes) is essential to becoming proficient in the skill of reading, and (b) methods that teach this principle directly are more effective than those that do not (especially for children who are at risk in some way for having difficulty learning to read). Using whole-language activities to supplement phonics instruction does help make reading fun and meaningful for children, but ultimately, phonics instruction is critically important because it helps beginning readers understand the alphabetic principle and learn new words. Thus, elementary-school teachers who make the alphabetic principle explicit are most effective in helping their students become skilled, independent readers.
The similarity metric

A new class of metrics appropriate for measuring effective similarity relations between sequences, say one type of similarity per metric, is studied. We propose a new "normalized information distance", based on the noncomputable notion of Kolmogorov complexity, and show that it minorizes every metric in the class (that is, it is universal in that it discovers all effective similarities). We demonstrate that it too is a metric and takes values in [0, 1]; hence it may be called the similarity metric. This is a theory foundation for a new general practical tool. We give two distinctive applications in widely divergent areas (the experiments by necessity use just computable approximations to the target notions). First, we computationally compare whole mitochondrial genomes and infer their evolutionary history. This results in a first completely automatic computed whole mitochondrial phylogeny tree. Secondly, we give fully automatically computed language tree of 52 different language based on translated versions of the "Universal Declaration of Human Rights".
Evolved Policy Gradients

We propose a metalearning approach for learning gradient-based reinforcement learning (RL) algorithms. The idea is to evolve a differentiable loss function, such that an agent, which optimizes its policy to minimize this loss, will achieve high rewards. The loss is parametrized via temporal convolutions over the agent’s experience. Because this loss is highly flexible in its ability to take into account the agent’s history, it enables fast task learning. Empirical results show that our evolved policy gradient algorithm (EPG) achieves faster learning on several randomized environments compared to an off-the-shelf policy gradient method. We also demonstrate that EPG’s learned loss can generalize to out-of-distribution test time tasks, and exhibits qualitatively different behavior from other popular metalearning algorithms.
Can LSTM Learn to Capture Agreement? The Case of Basque

Sequential neural networks models are powerful tools in a variety of Natural Language Processing (NLP) tasks. The sequential nature of these models raises the questions: to what extent can these models implicitly learn hierarchical structures typical to human language, and what kind of grammatical phenomena can they acquire? We focus on the task of agreement prediction in Basque, as a case study for a task that requires implicit understanding of sentence structure and the acquisition of a complex but consistent morphological system. Analyzing experimental results from two syntactic prediction tasks – verb number prediction and suffix recovery – we find that sequential models perform worse on agreement prediction in Basque than one might expect on the basis of a previous agreement prediction work in English. Tentative findings based on diagnostic classifiers suggest the network makes use of local heuristics as a proxy for the hierarchical structure of the sentence. We propose the Basque agreement prediction task as challenging benchmark for models that attempt to learn regularities in human language.
Rasch model analysis of the Depression, Anxiety and Stress Scales (DASS)

There is a growing awareness of the need for easily administered, psychometrically sound screening tools to identify individuals with elevated levels of psychological distress. Although support has been found for the psychometric properties of the Depression, Anxiety and Stress Scales (DASS) using classical test theory approaches it has not been subjected to Rasch analysis. The aim of this study was to use Rasch analysis to assess the psychometric properties of the DASS-21 scales, using two different administration modes.



The DASS-21 was administered to 420 participants with half the sample responding to a web-based version and the other half completing a traditional pencil-and-paper version. Conformity of DASS-21 scales to a Rasch partial credit model was assessed using the RUMM2020 software.



To achieve adequate model fit it was necessary to remove one item from each of the DASS-21 subscales. The reduced scales showed adequate internal consistency reliability, unidimensionality and freedom from differential item functioning for sex, age and mode of administration. Analysis of all DASS-21 items combined did not support its use as a measure of general psychological distress. A scale combining the anxiety and stress items showed satisfactory fit to the Rasch model after removal of three items.



The results provide support for the measurement properties, internal consistency reliability, and unidimensionality of three slightly modified DASS-21 scales, across two different administration methods. The further use of Rasch analysis on the DASS-21 in larger and broader samples is recommended to confirm the findings of the current study.