nils-herrmann/clean_scirepeval huggingface dataset:
Interprocedural Semantic Change-Impact Analysis using Equivalence Relations

Change-impact analysis (CIA) is the task of determining the set of program elements impacted by a program change. Precise CIA has great potential to avoid expensive t sting and code reviews for (parts of) changes that are refactoring s (semantics-preserving). Existing CIA is imprecise becaus e it is coarse-grained, deals with only few refactoring patterns,or is unaware of the change semantics. We formalize the notion of change impact in terms of the trace semantics of two program versions. We show how to leverage equivalence relations to make dataflow-based CIA aware of th e change semantics, thereby improving precision in the prese nce of semantics-preserving changes. We propose an anytime algorithm that allows applying costly equivalence relation inference incrementally to refine the set of impacted statements. We ha ve implemented a prototype in SYM DIFF , and evaluated it on 322 real-world changes from open-source projects and benchmar k programs used by prior research. The evaluation results sho w an average 35% improvement in the size of the set of impacted statements compared to standard dataflow-based techniques .
Error Mechanisms of the Oscillometric Fixed-Ratio Blood Pressure Measurement Method

The oscillometric fixed-ratio method is widely employed for non-invasive measurement of systolic and diastolic pressures (SP and DP) but is heuristic and prone to error. We investigated the accuracy of this method using an established mathematical model of oscillometry. First, to determine which factors materially affect the errors of the method, we applied a thorough parametric sensitivity analysis to the model. Then, to assess the impact of the significant parameters, we examined the errors over a physiologically relevant range of those parameters. The main findings of this model-based error analysis of the fixed-ratio method are that: (1) SP and DP errors drastically increase as the brachial artery stiffens over the zero trans-mural pressure regime; (2) SP and DP become overestimated and underestimated, respectively, as pulse pressure (PP) declines; (3) the impact of PP on SP and DP errors is more obvious as the brachial artery stiffens over the zero trans-mural pressure regime; and (4) SP and DP errors can be as large as 58 mmHg. Our final and main contribution is a comprehensive explanation of the mechanisms for these errors. This study may have important implications when using the fixed-ratio method, particularly in subjects with arterial disease.
The forest, the trees, and the chameleon: context dependence and mimicry.

Three studies examined the relation between context dependence in information processing and behavioral mimicry. In Experiment 1, a field-dependent cognitive style was related to a greater tendency to mimic a target's behavior. In Experiment 2 context dependence was experimentally manipulated, and results showed more mimicry in the session where a context-dependent processing style was induced compared with the session where a context-independent processing style was induced. Experiment 3 provided evidence for bidirectionality in the relation between context dependence and mimicry. Specifically, participants whose posture and behavior had been unobtrusively mimicked by an experimenter subsequently processed information in a more context-dependent manner than did nonmimicked participants. Taken together, these results illustrate the interplay between basic cognitive and behavioral processes.
Systematic literature studies: Database searches vs. backward snowballing

Systematic studies of the literature can be done in different ways. In particular, different guidelines propose different first steps in their recommendations, e.g. start with search strings in different databases or start with the reference lists of a starting set of papers.
 In software engineering, the main recommended first step is using search strings in a number of databases, while in information systems, snowballing has been recommended as the first step. This paper compares the two different search approaches for conducting literature review studies.
 The comparison is conducted by searching for articles addressing "Agile practices in global software engineering". The focus of the paper is on evaluating the two different search approaches.
 Despite the differences in the included papers, the conclusions and the patterns found in both studies are quite similar. The strengths and weaknesses of each first step are discussed separately and in comparison with each other.
 It is concluded that none of the first steps is outperforming the other, and the choice of guideline to follow, and hence the first step, may be context-specific, i.e. depending on the area of study.
The Stable Model Semantics for Logic Programming

This paper studies the stable model semantics of logic progr ams with (abstract) constraint atoms and their properties. We introduce a succinct abstract represe ntation of these constraint atoms in which a constraint atom is represented compactly. We show two appli cations. First, under this representation of constraint atoms, we generalize the Gelfond-Lifschitz t ransformation and apply it to define stable models (also called answer sets) for logic programs with arb itr y constraint atoms. The resulting semantics turns out to coincide with the one defined by Son et a l., which is based on a fixpoint approach. One advantage of our approach is that it can be appl ied, in a natural way, to define stable models for disjunctive logic programs with constraint atom s, which may appear in the disjunctive head as well as in the body of a rule. As a result, our approach t o the stable model semantics for logic programs with constraint atoms generalizes a number of prev ious approaches. Second, we show that our abstract representation of constraint atoms provides a me ns to characterize dependencies of atoms in a program with constraint atoms, so that some standa rd characterizations and properties relying on these dependencies in the past for logic programs with ordinary atoms can be extended to logic programs with constraint atoms.
Astrocytes from Familial and Sporadic ALS Patients are Toxic to Motor Neurons

Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease, with astrocytes implicated as contributing substantially to motor neuron death in familial (F)ALS. However, the proposed role of astrocytes in the pathology of ALS derives in part from rodent models of FALS based upon dominant mutations within the superoxide dismutase 1 (SOD1) gene, which account for <2% of all ALS cases. Their role in sporadic (S)ALS, which affects >90% of ALS patients, remains to be established. Using astrocytes generated from postmortem tissue from both FALS and SALS patients, we show that astrocytes derived from both patient groups are similarly toxic to motor neurons. We also demonstrate that SOD1 is a viable target for SALS, as its knockdown significantly attenuates astrocyte-mediated toxicity toward motor neurons. Our data highlight astrocytes as a non–cell autonomous component in SALS and provide an in vitro model system to investigate common disease mechanisms and evaluate potential therapies for SALS and FALS.
Identity-Based Cryptosystems and Signature Schemes

I n t h i s p a p e r w e i n t r o d u c e a novel t y p e of c r y p t o g r a p h i c scheme, which e n a b l e s any p a i r o f u s e r s t o communicate s e c u r e l y and t o v e r i f y each o t h e r ' s s i g n a t u r e s w i t h o u t exchanging p r i v a t e o r p u b l i c k e y s , w i t h-o u t keeping key d i r e c t o r i e s , and w i t h o u t using t h e s e r v i c e s of a t h i r d p a r t y. The scheme assumes t h e e x i s t e n c e of t r u s t e d key g e n e r a t i o n cent e r s , whose s o l e p u r p o s e i s t o g i v e each u s e r a p e r s o n a l i z e d s m a r t c a r d when he f i r s t j o i n s t h e network. The i n f o r m a t i o n embedded i n t h i s c a r d e n a b l e s t h e u s e r t o s i g n and e n c r y p t t h e messages he sends and t o d e c r y p t and v e r i f y t h e messages h e r e c e i v e s i n a t o t a l l y independent way, r e g a r d-less o f t h e i d e n t i …
A new design of XOR-XNOR gates for low power application

XOR and XNOR gate plays an important role in digital systems including arithmetic and encryption circuits. This paper proposes a combination of XOR-XNOR gate using 6-transistors for low power applications. Comparison between a best existing XOR-XNOR have been done by simulating the proposed and other design using 65nm CMOS technology in Cadence environment. The simulation results demonstrate the delay, power consumption and power-delay product (PDP) at different supply voltages ranging from 0.6V to 1.2V. The results show that the proposed design has lower power dissipation and has a full voltage swing.
Introducing Wikidata to the Linked Data Web

Wikidata is the central data management platform of Wikipedia. By the efforts of thousands of volunteers, the project has produced a large, open knowledge base with many interesting applications. The data is highly interlinked and connected to many other datasets, but it is also very rich, complex, and not available in RDF. To address this issue, we introduce new RDF exports that connect Wikidata to the Linked Data Web. We explain the data model of Wikidata and discuss its encoding in RDF. Moreover, we introduce several partial exports that provide more selective or simplified views on the data. This includes a class hierarchy and several other types of ontological axioms that we extract from the site. All datasets we discuss here are freely available online and updated regularly.
Beyond Autograding: Advances in Student Feedback Platforms

1.  Automatic grading of programming assignments has been a feature of computer science courses for almost as long as there have been computer science courses . However, contemporary autograding systems in computer science courses have extended their scope far beyond performing automated assessment to include gamification , test coverage analysis , managing human-authored feedback, contest adjudication [4], secure remote code execution [5], and more. Many of these individual features have been described and evaluated in the computer science education literature, but little attention has been given to the practical benefits and challenges of using the systems that implement these features in computer science courses.
Generative Adversarial Text to Image Synthesis

Automatic synthesis of realistic images from text would be interesting and useful, but current AI systems are still far from this goal. However, in recent years generic and powerful recurrent neural network architectures have been developed to learn discriminative text feature representations. Meanwhile, deep convolutional generative adversarial networks (GANs) have begun to generate highly compelling images of specific categories, such as faces, album covers, and room interiors. In this work, we develop a novel deep architecture and GAN formulation to effectively bridge these advances in text and image modeling, translating visual concepts from characters to pixels. We demonstrate the capability of our model to generate plausible images of birds and flowers from detailed text descriptions.
Ambient Intelligence in Assisted Living: Enable Elderly People to Handle Future Interfaces

Ambient Assisted Living is currently one of the important research and development areas, where accessibility, usability and learning plays a major role and where future interfaces are an important concern for applied engineering. The general goal of ambient assisted living solutions is to apply ambient intelligence technology to enable people with specific demands, e.g. handicapped or elderly, to live in their preferred environment longer. Due to the high potential of emergencies, a sound emergency assistance is required, for instance assisting elderly people with comprehensive ambient assisted living solutions sets high demands on the overall system quality and consequently on software and system engineering – user acceptance and support by various userinterfaces is an absolute necessity. In this article, we present an Assisted Living Laboratory that is used to train elderly people to handle modern interfaces for Assisted Living and evaluate the usability and suitability of these interfaces in specific situations, e.g., emergency cases.
The Evolution and Future of National Customer Satisfaction Index Models

A number of both national and international customer satisfaction barometers or indices have been introduced in the last decade. For the most part, these satisfaction indices are embedded within a system of cause and effect relationships or satisfaction model. Yet there has been little in the way of model development. Of critical importance to the validity and reliability of such indices is that the models and methods used to measure customer satisfaction and related constructs continue to learn, adapt, and improve over time. The primary goal of this research is to propose and test a number of modifications and improvements to the national index models. Using survey data from the Norwegian Customer Satisfaction Barometer (NCSB), we find general support for the proposed modifications.
No data left behind: real-time insights from a complex data ecosystem

The typical enterprise data architecture consists of several actively updated data sources (e.g., NoSQL systems, data warehouses), and a central data lake such as HDFS, in which all the data is periodically loaded through ETL processes. To simplify query processing, state-of-the-art data analysis approaches solely operate on top of the local, historical data in the data lake, and ignore the fresh tail end of data that resides in the original remote sources. However, as many business operations depend on real-time analytics, this approach is no longer viable. The alternative is hand-crafting the analysis task to explicitly consider the characteristics of the various data sources and identify optimization opportunities, rendering the overall analysis non-declarative and convoluted.
 Based on our experiences operating in data lake environments, we design System-PV, a real-time analytics system that masks the complexity of dealing with multiple data sources while offering minimal response times. System-PV extends Spark with a sophisticated data virtualization module that supports multiple applications - from SQL queries to machine learning. The module features a location-aware compiler that considers source complexity, and a two-phase optimizer that produces and refines the query plans, not only for SQL queries but for all other types of analysis as well. The experiments show that System-PV is often faster than Spark by more than an order of magnitude. In addition, the experiments show that the approach of accessing both the historical and the remote fresh data is viable, as it performs comparably to solely operating on top of the local, historical data.
Text and Object Detection on Billboards

To captivate people’s attention in a blink of an eye, a billboard as a commercial advertisement must be attractive and informative. When space means money like on the billboard, much important information must be dropped out. Unfortunately, insufficient details and the difficulty of accessing those details might easily kill the customer’s attention in a flash as well. In this work, we propose a system that automatically connects a billboard with the product website instantly. More specifically, given the billboard image as an input, the system will lead users immediately to the product website for more details, or contact information. The results demonstrate that our system is significantly outperform the Google image search baseline where the product website is always included in the top 10 websites. Finally, We posit that the system can save the customers’ time and complexity to access their product of interest, resulting the increasing of product sale.
MPTLsim: a cycle-accurate, full-system simulator for x86-64 multicore architectures with coherent caches

The introduction of multicore microprocessors in the recent years has made it imperative to use cycleaccurate and full-system simulators in the architecture research community. We introduce MPTLsim - a multicore simulator for the X86 ISA that meets this need. MPTLsim is a uop-accurate, cycle-accurate, full-system simulator for multicore designs based on the X86-64 ISA. MPTLsim extends PTLsim, a publicly available single core simulator, with a host of additional features to support hyperthreading within a core and multiple cores, with detailed models for caches, on-chip interconnections and the memory data flow. MPTLsim incorporates detailed simulation models for cache controllers, interconnections and has built-in implementations of a number of cache coherency protocols.
WebGLStudio: a pipeline for WebGL scene creation

We present WebGLStudio - a pipeline for the creation and editing of high-quality 3D scenes using WebGL. The pipeline features a 3D Scene-Graph rendering engine; an interactive scene editor allowing detailed setup and configuration of assets in real-time; a web-based asset manager; and a stand-alone rendering module ready to embedded in target applications. We further present a series of implementational details discovered to overcome limitations of the web browser context to enable realistic rendering and performance. The principal contribution of this work to the graphics community is the methodology used to take advantage of several unique aspects of Javascript when used as a 3D programming language; and the demonstration of possibilities involved in real-time editing of the parameters of materials, shaders and post-processing effects, in order for the user/artist to create a 3D scene as desired.
An investigation of factors associated with the health and well-being of HIV-infected or HIV-affected older people in rural South Africa

Despite the severe impact of HIV in sub-Saharan Africa, the health of older people aged 50+ is often overlooked owing to the dearth of data on the direct and indirect effects of HIV on older people's health status and well-being. The aim of this study was to examine correlates of health and well-being of HIV-infected older people relative to HIV-affected people in rural South Africa, defined as participants with an HIV-infected or death of an adult child due to HIV-related cause.



Data were collected within the Africa Centre surveillance area using instruments adapted from the World Health Organization (WHO) Study on global AGEing and adult health (SAGE). A stratified random sample of 422 people aged 50+ participated. We compared the health correlates of HIV-infected to HIV-affected participants using ordered logistic regressions. Health status was measured using three instruments: disability index, quality of life and composite health score.



Median age of the sample was 60 years (range 50-94). Women HIV-infected (aOR 0.15, 95% confidence interval (CI) 0.08-0.29) and HIV-affected (aOR 0.20, 95% CI 0.08-0.50), were significantly less likely than men to be in good functional ability. Women's adjusted odds of being in good overall health state were similarly lower than men's; while income and household wealth status were stronger correlates of quality of life. HIV-infected participants reported better functional ability, quality of life and overall health state than HIV-affected participants.



The enhanced healthcare received as part of anti-retroviral treatment as well as the considerable resources devoted to HIV care appear to benefit the overall well-being of HIV-infected older people; whereas similar resources have not been devoted to the general health needs of HIV uninfected older people. Given increasing numbers of older people, policy and programme interventions are urgently needed to holistically meet the health and well-being needs of older people beyond the HIV-related care system.
Using machine learning algorithms for housing price prediction: The case of Fairfax County, Virginia housing data

House sales are determined based on the Standard & Poor’s Case-Shiller home price indices and the housing price index of the Office of Federal Housing Enterprise Oversight (OFHEO). These reflect the trends of the US housing market. In addition to these housing price indices, the development of a housing price prediction model can greatly assist in the prediction of future housing prices and the establishment of real estate policies. This study uses machine learning algorithms as a research methodology to develop a housing price prediction model. To improve the accuracy of housing price prediction, this paper analyzes the housing data of 5359 townhouses in Fairfax County, Virginia, gathered by the Multiple Listing Service (MLS) of the Metropolitan Regional Information Systems (MRIS). We develop a housing price prediction model based on machine learning algorithms such as C4.5, RIPPER, Naïve Bayesian, and AdaBoost and compare their classification accuracy performance. We then propose an improved housing price prediction model to assist a house seller or a real estate agent make better informed decisions based on house price valuation. The experiments demonstrate that the RIPPER algorithm, based on accuracy, consistently outperforms the other models in the performance of housing price prediction.
Evaluation: From Precision, Recall and F-Factor to ROC, Informedness, Markedness & Correlation

Commonly used evaluation measures including Recall, Precision, F-Factor and Rand Accuracy are biased and should not be used without clear understanding of the biases, and corresponding identification of chance or bas e case levels of the statistic. Using these measures a sy tem that performs worse in the objective sense of Informedn ess, can appear to perform better under any of these commonly used measures. We discuss several concepts and measures that reflect the probability that prediction is infor med versus chance. Informedness and introduce Markedness as a dual measure for the probability that prediction is marked versus chance. Finally we demonstrate elegant connection s between the concepts of Informedness, Markedness, Correlation and Significance as well as their intuiti ve relationships with Recall and Precision, and outline th extension from the dichotomous case to the general multi-class case. .
SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity

Semantic Textual Similarity (STS) measures the degree of semantic equivalence between two texts. This paper presents the results of the STS pilot task in Semeval. The training data contained 2000 sentence pairs from previously existing paraphrase datasets and machine translation evaluation resources. The test data also comprised 2000 sentences pairs for those datasets, plus two surprise datasets with 400 pairs from a different machine translation evaluation corpus and 750 pairs from a lexical resource mapping exercise. The similarity of pairs of sentences was rated on a 0-5 scale (low to high similarity) by human judges using Amazon Mechanical Turk, with high Pearson correlation scores, around 90%. 35 teams participated in the task, submitting 88 runs. The best results scored a Pearson correlation>80%, well above a simple lexical baseline that only scored a 31% correlation. This pilot task opens an exciting way ahead, although there are still open issues, specially the evaluation metric.