wanyu/IteraTeR_v2 huggingface dataset:
Original:  Mobile crowdsourcing requires an appropriate task assignment strategy, since different workers may have different performance in terms of acceptance rate and quality.
Revised:  MCS requires an appropriate task assignment strategy, since different workers may have different performance in terms of acceptance rate and quality.
Edit intent: clarity
Original:  Task assignment is challenging, since a worker's performance (i) may fluctuate, depending on both the worker's current  context and the task context, (ii) is not known a priori, but has to be learned over time.
Revised:  Task assignment is challenging, since a worker's performance (i) may fluctuate, depending on both the worker's current personal context and the task context, (ii) is not known a priori, but has to be learned over time.
Edit intent: clarity
Original:  However , learning context-specific worker performance requires access to context information, which workers may not grant to a central entity .
Revised:  Moreover , learning context-specific worker performance requires access to context information, which workers may not grant to a central entity .
Edit intent: coherence
Original:  However , learning context-specific worker performance requires access to context information, which workers may not grant to a central entity .
Revised:  However , learning context-specific worker performance requires access to context information, which may not be available at a central entity .
Edit intent: clarity
Original:  In this paper, we propose a context-aware hierarchical online learning algorithm addressing the problem of performance maximization in mobile crowdsourcing .
Revised:  In this paper, we propose a context-aware hierarchical online learning algorithm addressing the problem of performance maximization in MCS .
Edit intent: clarity
Original:  In our algorithm, a local controller (LC) in the mobile device of a worker regularly observes its worker's context,  his decisions to accept or decline tasks and the quality in completing tasks.
Revised:  In our algorithm, a local controller (LC) in the mobile device of a worker regularly observes the worker's context, his decisions to accept or decline tasks and the quality in completing tasks.
Edit intent: clarity
Original:  In our algorithm, a local controller (LC) in the mobile device of a worker regularly observes its worker's context,  his decisions to accept or decline tasks and the quality in completing tasks.
Revised:  In our algorithm, a local controller (LC) in the mobile device of a worker regularly observes its worker's context, her/ his decisions to accept or decline tasks and the quality in completing tasks.
Edit intent: clarity
Original:  Based on these observations, the LC regularly estimates its worker's context-specific performance.
Revised:  Based on these observations, the LC regularly estimates the worker's context-specific performance.
Edit intent: clarity
Original:  We present numerical evidences that an increase in the efficiency of navigation between the target areas, in dependence of the colony size, exists.
Revised:  We present numerical evidences that an increase in the efficiency of navigation in dependence of the colony size, exists.
Edit intent: clarity
Original:  Moreover, the shift, from the maladaptive to the adaptive behaviour, can be quantitative characterised, identifying and measuring a well defined crossover point.
Revised:  Moreover, the shift, from the diffusive to the directed motion can be quantitatively characterised, identifying and measuring a well defined crossover point.
Edit intent: clarity
Original:  Its scaling behaviour, as a function of the environment size , is clearly described .
Revised:  Its scaling behaviour, as a function of the environment size . This last result can be of particular interest for interpreting empirical observations or for the design of artificial swarms .
Edit intent: coherence
Original: We continue the study of k-monotone Boolean functions in the property testing model, initiated by Canonne et al. (ITCS 2017).
Edit intent: coherence
Original:  A function f : {0, 1} n -> {0, 1} is said to be k- monotone if it alternates between 0 and 1 at most k times on every ascending c-hain .
Revised:  A function f : {0, 1} n -> {0, 1} is said to be k-monotone if it flips between 0 and 1 at most k times on every ascending c-hain .
Edit intent: clarity
Original:  A function f : {0, 1} n -> {0, 1} is said to be k- monotone if it alternates between 0 and 1 at most k times on every ascending c-hain .
Revised:  A function f : {0, 1} n -> {0, 1} is said to be k- monotone if it alternates between 0 and 1 at most k times on every ascending chain .
Edit intent: fluency
Original:  In property testing, the fact that 1-monotonicity can be locally tested with poly nqueries led to a previous conjecture that k-monotonicity can be tested with poly(n^k)queries ]  . In this work we disprove the conjecture, and show that even 2-monotonicity  requires an exponential in \sqrt n number of queries.
Revised:  In property testing, the fact that 1-monotonicity can be locally tested with poly nqueries led to a previous conjecture that k-monotonicity can be tested with poly(n^k)queries n] . In this work we disprove the conjecture, and show that even 2-monotonicity requires an exponential in \sqrt n number of queries.
Edit intent: clarity
Original:  In property testing, the fact that 1-monotonicity can be locally tested with poly nqueries led to a previous conjecture that k-monotonicity can be tested with poly(n^k)queries ]  . In this work we disprove the conjecture, and show that even 2-monotonicity  requires an exponential in \sqrt n number of queries.
Revised:  In property testing, the fact that 1-monotonicity can be locally tested with poly nqueries led to a previous conjecture that k-monotonicity can be tested with poly(n^k)queries ] . In this process we resolve a problem left open in previous work. Specifically, our results include the following. 1. Testing 2-monotonicity requires an exponential in \sqrt n number of queries.
Edit intent: clarity
Original:   Furthermore, even the apparently easier task of distinguishing 2-monotone functions from functions that are far from being n ^{.01 -monotone also requires an exponential number of queries.
Revised:  Furthermore, even the apparently easier task of distinguishing 2-monotone functions from functions that are far from being n ^.01 -monotone also requires an exponential number of queries.
Edit intent: fluency
Original:  We provide an overview of the OTDOA architecture and protocols, identify the design challenges of positioning support in LTE-M and NB-IoT, and summarize the designs of OTDOA positioning reference signals  .
Revised:  We provide an overview of the OTDOA architecture and protocols, summarize the designs of OTDOA positioning reference signals .
Edit intent: clarity
Original:  We then perform an extensive benchmark of BADS vs. many common and state-of-the-art nonconvex, derivative-free optimizers  on a set of model-fitting problems with real data and models from six studies in behavioral, cognitive, and computational neuroscience.
Revised:  We then perform an extensive benchmark of BADS vs. many common and state-of-the-art nonconvex, derivative-free optimizers , on a set of model-fitting problems with real data and models from six studies in behavioral, cognitive, and computational neuroscience.
Edit intent: fluency
Original: Developing an accurate and reliable injury prediction method is central to the biomechanics studies of traumatic brain injury.
Revised: Developing an accurate and reliable injury predictor is central to the biomechanics studies of traumatic brain injury.
Edit intent: clarity
Original: Developing an accurate and reliable injury prediction method is central to the biomechanics studies of traumatic brain injury.
Revised: Developing an accurate and reliable injury prediction method is central to the biomechanical studies of traumatic brain injury.
Edit intent: fluency
Original:  In this study, we developed a deep learning approach for concussion classification based on implicit features of the entire voxel-wise white matter fiber strains.
Revised:  In this study, we developed a deep learning approach for concussion classification using implicit features of the entire voxel-wise white matter fiber strains.
Edit intent: fluency
Original:  In this work, we address the computations that the Bayesian agent should undertake to realize the optimal actionsat every decision epoch .
Revised:  In this work, we address the computations that Bayesian agents undertake to realize the optimal actionsat every decision epoch .
Edit intent: clarity
Original:  We use the iterated eliminations of infeasible signals (IEIS) to model the thinking process as well as the calculations of a Bayesian agent in a group decision scenario.
Revised:  We use iterated eliminations of infeasible signals (IEIS) to model the thinking process as well as the calculations of a Bayesian agent in a group decision scenario.
Edit intent: fluency
Original:  We show that IEIS algorithm runs in exponential time;
Revised:  We show that IEIS runs in exponential time;
Edit intent: clarity
Original:  however, when the group structure is a partially ordered set  the Bayesian calculations simplify and polynomial-time computation of the Bayesian recommendations is possible.
Revised:  however, when the group structure is a partially ordered set , the Bayesian calculations simplify and polynomial-time computation of the Bayesian recommendations is possible.
Edit intent: fluency
Original: We address the computations that Bayesian agents in a networkundertake in an opinion exchange model, where they repeatedly act on private information, taking myopic actions maximizing expected utility according to a fully rational posterior  .
Revised: We study the computations that Bayesian agents in a networkundertake in an opinion exchange model, where they repeatedly act on private information, taking myopic actions maximizing expected utility according to a fully rational posterior .
Edit intent: clarity
Original: We address the computations that Bayesian agents in a networkundertake in an opinion exchange model, where they repeatedly act on private information, taking myopic actions maximizing expected utility according to a fully rational posterior  .
Revised: We address the computations that Bayesian agents undertake when exchanging opinions over a network. The agents act repeatedly on their private information and take myopic actions that maximize their expected utility according to a fully rational posterior .
Edit intent: clarity
Original: We address the computations that Bayesian agents in a networkundertake in an opinion exchange model, where they repeatedly act on private information, taking myopic actions maximizing expected utility according to a fully rational posterior  .
Revised: We address the computations that Bayesian agents in a networkundertake in an opinion exchange model, where they repeatedly act on private information, taking myopic actions maximizing expected utility according to a fully rational posterior belief .
Edit intent: clarity
Original:  Our results are robust in the sense that they show NP-hardness of distinguishing (and therefore also approximating) between posteriors that are concentrated on two distinct states of the world .
Revised:  Our results are robust in the sense that they show NP-hardness of distinguishing (and therefore also approximating) between posteriors that are concentrated on different states of the world .
Edit intent: clarity
Original:  We also describe a natural search algorithm that computes agents' actions, which we call iterated elimination of infeasible signals(IEIS) , and show that if the network is transitive, the algorithm can be modified to run in polynomial-time .
Revised:  We also describe a natural search algorithm to compute agents' actions, which we call iterated elimination of infeasible signals(IEIS) , and show that if the network is transitive, the algorithm can be modified to run in polynomial-time .
Edit intent: coherence
Original:  We also describe a natural search algorithm that computes agents' actions, which we call iterated elimination of infeasible signals(IEIS) , and show that if the network is transitive, the algorithm can be modified to run in polynomial-time .
Revised:  We also describe a natural search algorithm that computes agents' actions, which we call elimination of impossible signals , and show that if the network is transitive, the algorithm can be modified to run in polynomial-time .
Edit intent: clarity
Original:  We also describe a natural search algorithm that computes agents' actions, which we call iterated elimination of infeasible signals(IEIS) , and show that if the network is transitive, the algorithm can be modified to run in polynomial-time .
Revised:  We also describe a natural search algorithm that computes agents' actions, which we call iterated elimination of infeasible signals(IEIS) , and show that if the network is transitive, the algorithm can be modified to run in polynomial time .
Edit intent: fluency
Original:  Pavel \v{Z 's concepts of system theory which enable to devise a measurement in dynamic systems independently of the particular system behaviour.
Revised:  Pavel Zampa 's concepts of system theory which enable to devise a measurement in dynamic systems independently of the particular system behaviour.
Edit intent: clarity
Original:  From the point of view of \v{Z 's theory, terms like system time, system attributes, system link, system element, input, output, sub-systems , and state variables are defined.
Revised:  From the point of view of \v{Z 's theory, terms like system time, system attributes, system link, system element, input, output, subsystems , and state variables are defined.
Edit intent: fluency
Original: Modularity optimization is one of the state-of-the-art methods for community detection that has gained popularity in the last decade.
Revised: Modularity maximization is one of the state-of-the-art methods for community detection that has gained popularity in the last decade.
Edit intent: clarity
Original:  In many practical applications, however, modularity maximization algorithms suffer from the resolution limit problem because of their bias towards large communities over small ones.
Revised:  Yet it suffers from the resolution limit problem because of their bias towards large communities over small ones.
Edit intent: clarity
Original:  In many practical applications, however, modularity maximization algorithms suffer from the resolution limit problem because of their bias towards large communities over small ones.
Revised:  In many practical applications, however, modularity maximization algorithms suffer from the resolution limit problem by preferring under certain conditions large communities over small ones.
Edit intent: clarity
Original:  Given a large unweighted network, we construct artificial graphs based on the parameters sampled from the network and train the regression model with the ground truth communities of these artificial graphs in a supervised fashion.
Revised:  We construct artificial graphs based on the parameters sampled from the network and train the regression model with the ground truth communities of these artificial graphs in a supervised fashion.
Edit intent: clarity
Original:  Given a large unweighted network, we construct artificial graphs based on the parameters sampled from the network and train the regression model with the ground truth communities of these artificial graphs in a supervised fashion.
Revised:  Given a large unweighted network, we construct artificial graphs based on the parameters sampled from a given unweighted network and train the regression model with the ground truth communities of these artificial graphs in a supervised fashion.
Edit intent: clarity
Original:  Given a large unweighted network, we construct artificial graphs based on the parameters sampled from the network and train the regression model with the ground truth communities of these artificial graphs in a supervised fashion.
Revised:  Given a large unweighted network, we construct artificial graphs based on the parameters sampled from the network and train the regression model on ground truth communities of these artificial graphs in a supervised fashion.
Edit intent: clarity
Original:  Since the local topological features of an edge can be extracted efficiently, this approach assigns weight to edges in a linear time . Experimental results on real and synthetic networks show that the state-of-the-art community detection algorithms improve their performance significantly when applied to weighted graphs produced by our model.
Revised:  The extraction of local topological edge features can be done in linear time, making this process efficient . Experimental results on real and synthetic networks show that the state-of-the-art community detection algorithms improve their performance significantly when applied to weighted graphs produced by our model.
Edit intent: clarity
Original:  Since the local topological features of an edge can be extracted efficiently, this approach assigns weight to edges in a linear time . Experimental results on real and synthetic networks show that the state-of-the-art community detection algorithms improve their performance significantly when applied to weighted graphs produced by our model.
Revised:  Since the local topological features of an edge can be extracted efficiently, this approach assigns weight to edges in a linear time . Experimental results on real and synthetic networks show that the state-of-the-art community detection algorithms improve their performance significantly by finding communities in the weighted graphs produced by our model.
Edit intent: clarity
Original:  Here, we explore the efficiency of  SIMEX-RK methods in overcoming parabolic stiffness . Examples of applications to linear and nonlinear reaction-advection-diffusion equations are shown .
Revised:  Here, we explore the efficiency of a SIMEX-RK methods in overcoming parabolic stiffness . Examples of applications to linear and nonlinear reaction-advection-diffusion equations are shown .
Edit intent: fluency
Original:  Here, we explore the efficiency of  SIMEX-RK methods in overcoming parabolic stiffness . Examples of applications to linear and nonlinear reaction-advection-diffusion equations are shown .
Revised:  Here, we explore the efficiency of SIMEX-RK method in overcoming parabolic stiffness . Examples of applications to linear and nonlinear reaction-advection-diffusion equations are shown .
Edit intent: fluency
Original:  Here, we explore the efficiency of  SIMEX-RK methods in overcoming parabolic stiffness . Examples of applications to linear and nonlinear reaction-advection-diffusion equations are shown .
Revised:  Here, we explore the efficiency of SIMEX-RK methods in overcoming parabolic stiffness by applying it to a nonlinear reaction-advection-diffusion equations are shown .
Edit intent: clarity
Original:  Here, we explore the efficiency of  SIMEX-RK methods in overcoming parabolic stiffness . Examples of applications to linear and nonlinear reaction-advection-diffusion equations are shown .
Revised:  Here, we explore the efficiency of SIMEX-RK methods in overcoming parabolic stiffness . Examples of applications to linear and nonlinear reaction-advection-diffusion equation .
Edit intent: coherence
Original:  A myriad of stability regions can be reached by changing the RK tableau and the number of solveriterations .
Revised:  A myriad of stability regions can be reached by changing the RK tableau and the solver .
Edit intent: clarity
Original:  This decompositionallows any residual occurring in the implicit equation of the implicit-step to be moved into the explicit part of the decomposition.
Revised:  This decompositionallows any residual occurring in the implicit equation of the implicit-step into the explicit part of the decomposition.
Edit intent: clarity
Original:  Here, we explore the efficiency of a SIMEX-RK method in overcoming parabolic stiffness by applying it to a nonlinear reaction-advection-diffusion equation.
Revised:  Here, we show the efficiency of a SIMEX-RK method in overcoming parabolic stiffness by applying it to a nonlinear reaction-advection-diffusion equation.
Edit intent: clarity
Original: Scalar features in  fluid flow are traditionally visualized with glyphs or using direct 3D representation, and their topology changes over time are often conveyed with abstract graphs.
Revised: Scalar features in fluid flow are traditionally visualized using 3D representation, and their topology changes over time are often conveyed with abstract graphs.
Edit intent: clarity
Original:  Using these techniques, however, the spatio-temporal evolution of features undergoing topological changes is difficult to analyze.
Revised:  Using such techniques, however, the spatio-temporal evolution of features undergoing topological changes is difficult to analyze.
Edit intent: fluency
Original:  Using these techniques, however, the spatio-temporal evolution of features undergoing topological changes is difficult to analyze.
Revised:  Using these techniques, however, the spatio-temporal evolution of features undergoing topological changes are difficult to analyze.
Edit intent: fluency
Original:  In this paper, we propose a novel approach for the visualization of the dynamics of feature topology that represents the separation of a feature spatiotemporally with respect to its volumetric contributions .
Revised:  In this paper, we propose a novel approach for the spatio-temporal visualization of feature separation that segments feature volumes into regions with respect to its volumetric contributions .
Edit intent: clarity
Original:  The utility of our technique is demonstrated by application to scalar physical quantities of single-phase flows, and two-phase  flows where the scalar field represents the fraction of the liquid phase .
Revised:  The utility of our technique is demonstrated by application to two-phase flows where the scalar field represents the fraction of the liquid phase .
Edit intent: clarity
Original:  The utility of our technique is demonstrated by application to scalar physical quantities of single-phase flows, and two-phase  flows where the scalar field represents the fraction of the liquid phase .
Revised:  The utility of our technique is demonstrated by application to scalar physical quantities of single-phase flows, and two-phase flows where the scalar field represents the fraction of one of the phases .
Edit intent: clarity
Original:  We plan to announce the public availability of a first version of PrivacyScore at the Annual Privacy Forum in June 2017.
Revised:  The public availability of a first version of PrivacyScore at the Annual Privacy Forum in June 2017.
Edit intent: clarity
Original:  First, using variable importance measure (VIM), we used RF to evaluate which individual characteristics had the highest influence on gait LDS. Second, we used MARS to detect potential interactions among individual characteristics that may influence LDS.
Revised:  First, through variable importance measure (VIM), we used RF to evaluate which individual characteristics had the highest influence on gait LDS. Second, we used MARS to detect potential interactions among individual characteristics that may influence LDS.
Edit intent: fluency
Original:  The VIM and MARS results evidenced that PWS and age correlated with LDS, whereas no associations were found for sex, body height, and body mass.
Revised:  The VIM and MARS results indicated that PWS and age correlated with LDS, whereas no associations were found for sex, body height, and body mass.
Edit intent: clarity
Original:  Further, the MARS model detected an age x PWS interaction: on one hand, at high PWS, gait stability is constant across age while, on the other hand, at low PWS, gait instability increases substantially with age.
Revised:  Further, the MARS model detected an age by PWS interaction: on one hand, at high PWS, gait stability is constant across age while, on the other hand, at low PWS, gait instability increases substantially with age.
Edit intent: clarity