wanyu/IteraTeR_v2 huggingface dataset:
Original:  Activities extracted from different data sources or the free-text nature within the same system may lead to inconsistent labels.
Revised:  Activities extracted from healthcare information systems with the free-text nature within the same system may lead to inconsistent labels.
Edit intent: clarity
Original:  Activities extracted from different data sources or the free-text nature within the same system may lead to inconsistent labels.
Revised:  Activities extracted from different data sources or the free-text nature may lead to inconsistent labels.
Edit intent: clarity
Original:  The identifications of these labels from data-driven process discovery are difficult and would rely heavily on human intervention.
Revised:  The identifications of these labels from data-driven process discovery are difficult and rely heavily on human intervention.
Edit intent: clarity
Original:  The results demonstrate that our approach can  detect redundant activity labels even with low occurrence frequencies .
Revised:  The results demonstrate that our approach can successfully detect redundant activity labels even with low occurrence frequencies .
Edit intent: clarity
Original:  The results demonstrate that our approach can  detect redundant activity labels even with low occurrence frequencies .
Revised:  The results demonstrate that our approach can detect redundant activity labels .
Edit intent: clarity
Original:  This approach can value-add to the preprocessing step to generate more representative event logs for process mining tasks  .
Revised:  This approach can add value to the preprocessing step to generate more representative event logs for process mining tasks .
Edit intent: fluency
Original:  Homomorphic encryption (HE) enables inference using encrypted data but it incurs 100x--10 ,000x memory and runtime overheads.
Revised:  Homomorphic encryption (HE) enables inference using encrypted data but it incurs 100x-10 ,000x memory and runtime overheads.
Edit intent: fluency
Original: In this paper we present a refined dual active-set solver for quadratic programming which has properties suitable for use in embedded model predictive control applications.
Revised: In this paper we present a dual active-set solver for quadratic programming which has properties suitable for use in embedded model predictive control applications.
Edit intent: clarity
Original:  Moreover, the solver is reliable since its exact worst-case computational complexity  can be determined offline and, by using outer proximal-point iterations, ill-conditioned problems can be handled in a robust manner.
Revised:  Moreover, the exact worst-case computational complexity can be determined offline and, by using outer proximal-point iterations, ill-conditioned problems can be handled in a robust manner.
Edit intent: coherence
Original:   To prevent spurious oscillations caused by irregular intersections of mesh cells, a penalization ensuring the stability of the approach and defining implicitly the extension to host domains is added.
Revised:  To prevent spurious oscillations caused by irregular intersections of mesh cells, a penalization , defining also implicitly the extension to host domains is added.
Edit intent: clarity
Original:   To prevent spurious oscillations caused by irregular intersections of mesh cells, a penalization ensuring the stability of the approach and defining implicitly the extension to host domains is added.
Revised:  To prevent spurious oscillations caused by irregular intersections of mesh cells, a penalization ensuring the stability of the approach and defining implicitly the extension to ghost domains, is added.
Edit intent: style
Original:  We propose two techniques to tackle this problem: multi-task modeling and dimensionality reduction through clustering .
Revised:  We propose two techniques to tackle this problem: multi-task modeling and dimensionality reduction through a manual grouping of parameters .
Edit intent: clarity
Original:  The calculation of the limit cycle is reformulated as the zero finding of a mixedmonotone operator , that is, of an operator that can be expressed as the difference of two maximally monotone operators .
Revised:  The calculation of the limit cycle is reformulated as the zero finding of a mixed-monotone relation , that is, of an operator that can be expressed as the difference of two maximally monotone operators .
Edit intent: clarity
Original:  The calculation of the limit cycle is reformulated as the zero finding of a mixedmonotone operator , that is, of an operator that can be expressed as the difference of two maximally monotone operators .
Revised:  The calculation of the limit cycle is reformulated as the zero finding of a mixedmonotone operator , that is, of the difference of two maximally monotone operators .
Edit intent: clarity
Original:  The calculation of the limit cycle is reformulated as the zero finding of a mixedmonotone operator , that is, of an operator that can be expressed as the difference of two maximally monotone operators .
Revised:  The calculation of the limit cycle is reformulated as the zero finding of a mixedmonotone operator , that is, of an operator that can be expressed as the difference of two maximally monotone relations .
Edit intent: clarity
Original:  We show that the use of the " top-hat " formulation for steady speech flows can underestimate infection probabilities by a factor of 2-3.
Revised:  We show that the jets ejected from the mouth of each speaker produce a " top-hat " formulation for steady speech flows can underestimate infection probabilities by a factor of 2-3.
Edit intent: clarity
Original:  Moreover, simulations like these can provide useful inputs to the existing epidemiological models for improving their reliability and accuracy .
Revised:  Moreover, simulations like these can provide useful inputs to epidemiological models and to disease management .
Edit intent: clarity
Original: Reinforcement learning (RL ) has been successfully used to solve various robotic control tasks.
Revised: Reinforcement learning (RL ) has been successfully used to solve various robotic manipulation tasks.
Edit intent: clarity
Original:  What makes guaranteeing stability during RL difficult is threefold: non interpretable neural network policies , unknown system dynamics and random exploration.
Revised:  What makes traditional stability analysis difficult for DRL are the uninterpretable nature of the neural network policies , unknown system dynamics and random exploration.
Edit intent: clarity
Original:  What makes guaranteeing stability during RL difficult is threefold: non interpretable neural network policies , unknown system dynamics and random exploration.
Revised:  What makes guaranteeing stability during RL difficult is threefold: non interpretable neural network policies and unknown system dynamics and random exploration.
Edit intent: fluency
Original:  In this work, unconditional stability is obtained by deriving an interpretable deep policy structure based on the energy shaping control of Lagrangian systems.
Revised:  In this work, stability is obtained by deriving an interpretable deep policy structure based on the energy shaping control of Lagrangian systems.
Edit intent: clarity
Original:  Therefore, this paper aims to identify and analyze the published studies on process-aware recommender system techniques on business process management and process mining  .
Revised:  Therefore, this paper aims to identify and analyze the published studies on process-aware recommender system techniques in business process management and process mining .
Edit intent: fluency
Original:  A systematic review is run on 33 academic articles published between 2008 and 2020 according to several aspects.
Revised:  A systematic review was conducted on 33 academic articles published between 2008 and 2020 according to several aspects.
Edit intent: clarity
Original:  We present a summary of recent results developing such a theory and describe how the numerical experiments illustrate it.
Revised:  We present a summary of upcoming results developing such a theory and describe how the numerical experiments illustrate it.
Edit intent: clarity
Original: We propose a method for improving the quality of synthetic room impulse responses generated using acoustic simulators for far-field speech recognition tasks .
Revised: We present a method for improving the quality of synthetic room impulse responses generated using acoustic simulators for far-field speech recognition tasks .
Edit intent: clarity
Original: We propose a method for improving the quality of synthetic room impulse responses generated using acoustic simulators for far-field speech recognition tasks .
Revised: We propose a method for improving the quality of synthetic room impulse responses for far-field speech recognition tasks .
Edit intent: clarity
Original: We propose a method for improving the quality of synthetic room impulse responses generated using acoustic simulators for far-field speech recognition tasks .
Revised: We propose a method for improving the quality of synthetic room impulse responses generated using acoustic simulators for far-field speech recognition .
Edit intent: clarity
Original:  We pass a synthetic room impulse response in the form of raw-waveform audioto our one-dimensional CycleGAN and translate it into a real room impulse response .
Revised:  We pass a synthetic room impulse response in the form of raw audio, we use TS-RIRGAN to translate it into a real room impulse response .
Edit intent: clarity
Original:  We pass a synthetic room impulse response in the form of raw-waveform audioto our one-dimensional CycleGAN and translate it into a real room impulse response .
Revised:  We pass a synthetic room impulse response in the form of raw-waveform audioto our one-dimensional CycleGAN and translate it into a real RIR .
Edit intent: clarity
Original:  We show that far-field speech simulated with the improved room impulse response using our approach reduces the word error rate by up to 19.9\% compared to the unmodified room impulse response in Kaldi LibriSpeech far-field automatic speech recognition benchmark [2].
Revised:  We show that far-field speech simulated with the improved room impulse response using our approach reduces the word error rate by up to 19.9\% in Kaldi far-field automatic speech recognition benchmark [2].
Edit intent: clarity
Original:  Most quantization approaches use floating-point arithmetic during inference ;
Revised:  Most quantization approaches use floating-point arithmetic during inference 
Edit intent: fluency
Original:  and thus they cannot fully exploit  integer processing units , which use less power than their floating-point counterparts .
Revised:  and thus they cannot fully exploit integer processing units .
Edit intent: clarity
Original:  To address these limitations, we propose Q-ASR, an integer-only, zero-shot quantization scheme for ASR models.
Revised:  To address these limitations, we propose an integer-only, zero-shot quantization scheme for ASR models.
Edit intent: clarity
Original:  To address these limitations, we propose Q-ASR, an integer-only, zero-shot quantization scheme for ASR models.
Revised:  To address these limitations, we propose Q-ASR, an integer-only, zero shot quantization scheme for ASR models.
Edit intent: fluency
Original:  We then apply Q-ASR to quantize QuartzNet-15x5 and JasperDR-10x5 without any training data, and we show negligible WER change as compared to the full-precision baseline models .
Revised:  We apply our method to quantize QuartzNet, Jasper, and Conformer and show negligible WER change as compared to the full-precision baseline models .
Edit intent: clarity
Original:  In particular, the architecture, named super resolution CNN (SRCNN), is able to estimate the vibrational field with a higher spatial resolution compared to the input pressure.
Revised:  In particular, the architecture, named Super Resolution CNN (SRCNN), is able to estimate the vibrational field with a higher spatial resolution compared to the input pressure.
Edit intent: fluency
Original:  Code of MemVir will be publicly available.
Revised:  Code of MemVir is publicly available.
Edit intent: clarity
Original:  Surround view cameras typically comprise of four fisheye cameras with 190{\deg} field-of-view covering the entire 360{\deg} around the vehicle focused on near field sensing.
Revised:  Surround-view camera systems typically comprise of four fisheye cameras with 190{\deg} field-of-view covering the entire 360{\deg} around the vehicle focused on near field sensing.
Edit intent: clarity
Original:  Surround view cameras typically comprise of four fisheye cameras with 190{\deg} field-of-view covering the entire 360{\deg} around the vehicle focused on near field sensing.
Revised:  Surround view cameras typically comprise of four fisheye cameras with 190{\deg} field-of-view covering the entire 360{\deg} around the vehicle focused on near-field sensing.
Edit intent: fluency
Original:  They are the principal sensor for low-speed, high accuracy  and close-range sensing applications, such as automated parking, traffic jam assistance  and low-speed emergency braking.
Revised:  They are the principal sensors for low-speed, high accuracy and close-range sensing applications, such as automated parking, traffic jam assistance and low-speed emergency braking.
Edit intent: fluency
Original:  They are the principal sensor for low-speed, high accuracy  and close-range sensing applications, such as automated parking, traffic jam assistance  and low-speed emergency braking.
Revised:  They are the principal sensor for low-speed, high accuracy , and close-range sensing applications, such as automated parking, traffic jam assistance and low-speed emergency braking.
Edit intent: fluency
Original:  They are the principal sensor for low-speed, high accuracy  and close-range sensing applications, such as automated parking, traffic jam assistance  and low-speed emergency braking.
Revised:  They are the principal sensor for low-speed, high accuracy and close-range sensing applications, such as automated parking, traffic jam assistance , and low-speed emergency braking.
Edit intent: fluency
Original:  We have designed our system into four modular components namely Recognition, Reconstruction, Relocalization  and Reorganization.
Revised:  We have designed our system into four modular components namely Recognition, Reconstruction, Relocalization , and Reorganization.
Edit intent: fluency
Original:  For example, it can be used to constrain  vehicles running on road areas , which ensures driving safety.
Revised:  It can be used to constrain vehicles running on road areas , which ensures driving safety.
Edit intent: coherence
Original:  For example, it can be used to constrain  vehicles running on road areas , which ensures driving safety.
Revised:  For example, it can be used to constrain vehicles running on road areas to ensure driving safety.
Edit intent: coherence
Original:  Compared with on-line road-boundary detection using on-vehicle cameras/Lidars, off-line detection using aerial images could alleviate the severe occlusion issue.
Revised:  Compared with online road-boundary detection using on-vehicle cameras/Lidars, off-line detection using aerial images could alleviate the severe occlusion issue.
Edit intent: clarity
Original:  Compared with on-line road-boundary detection using on-vehicle cameras/Lidars, off-line detection using aerial images could alleviate the severe occlusion issue.
Revised:  Compared with on-line road-boundary detection using on-vehicle cameras/Lidars, offline detection using aerial images could alleviate the severe occlusion issue.
Edit intent: fluency
Original:  Moreover, the off-line detection results can be directly used to annotate high-definition (HD) maps.
Revised:  Moreover, the offline detection results can be directly used to annotate high-definition (HD) maps.
Edit intent: fluency
Original:  Moreover, the off-line detection results can be directly used to annotate high-definition (HD) maps.
Revised:  Moreover, the off-line detection results can be directly employed to annotate high-definition (HD) maps.
Edit intent: clarity
Original:  In recent years, deep-learning technologies have been used in off-line detection.
Revised:  In recent years, deep-learning technologies have been used in offline detection.
Edit intent: fluency
Original:  But there is still lacking a publicly available dataset for this task, which hinders the research progress in this area.
Revised:  But there still lacks a publicly available dataset for this task, which hinders the research progress in this area.
Edit intent: coherence
Original:  So in this paper, we propose a new benchmark dataset, named Topo-boundary, for off-line topological road-boundary detection.
Revised:  So in this paper, we propose a new benchmark dataset, named Topo-boundary, for offline topological road-boundary detection.
Edit intent: fluency
Original:  The dataset and our-implemented codes for the baselines are available at URL
Revised:  The dataset and our-implemented code for the baselines are available at URL
Edit intent: fluency
Original:  By going through the Discrete Fourier transform (DFT), matrix SVD and inverse DFT, a third order tensor is mapped to a f-diagonal third order tensor.
Revised:  By going through the Discrete Fourier Transform (DFT), matrix SVD and inverse DFT, a third order tensor is mapped to a f-diagonal third order tensor.
Edit intent: fluency
Original:  By going through the Discrete Fourier transform (DFT), matrix SVD and inverse DFT, a third order tensor is mapped to a f-diagonal third order tensor.
Revised:  By going through the Discrete Fourier transform (DFT), matrix SVD and inverse DFT, a third order tensor is mapped to an f-diagonal third order tensor.
Edit intent: fluency
Original:  Thus, the tensor tubal rank, T-rank, singular values and T-singular values of a third  tensor are invariant when it was taking T-product with some orthogonal tensors.
Revised:  Thus, tensor tubal rank, T-rank, singular values and T-singular values of a third tensor are invariant when it was taking T-product with some orthogonal tensors.
Edit intent: clarity
Original:  Thus, the tensor tubal rank, T-rank, singular values and T-singular values of a third  tensor are invariant when it was taking T-product with some orthogonal tensors.
Revised:  Thus, the tensor tubal rank, T-rank, singular values and T-singular values of a third order tensor are invariant when it was taking T-product with some orthogonal tensors.
Edit intent: clarity
Original:  Thus, the tensor tubal rank, T-rank, singular values and T-singular values of a third  tensor are invariant when it was taking T-product with some orthogonal tensors.
Revised:  Thus, the tensor tubal rank, T-rank, singular values and T-singular values of a third tensor are invariant when it is taking T-product with some orthogonal tensors.
Edit intent: fluency
Original:  The traditional approach abstracts the nonlinear terms as forcing that is unstructured, in the sense that  is not directly tied to the underlying nonlinearity in the dynamics.
Revised:  The traditional approach abstracts the nonlinear terms as forcing that is unstructured, in the sense that this forcing is not directly tied to the underlying nonlinearity in the dynamics.
Edit intent: clarity
Original:  Application of this method to transitional plane Couette and plane Poiseuille flows leads to identification of not only the  streamwise coherent structures predicted through traditional input-output approaches but also characterization of the oblique flow structures as those requiring the least energy to induce transition in agreement with DNS studies, and nonlinear optimal perturbation analysis.
Revised:  Application of this method to transitional plane Couette and plane Poiseuille flows leads to not only the streamwise coherent structures predicted through traditional input-output approaches but also characterization of the oblique flow structures as those requiring the least energy to induce transition in agreement with DNS studies, and nonlinear optimal perturbation analysis.
Edit intent: clarity
Original:  Application of this method to transitional plane Couette and plane Poiseuille flows leads to identification of not only the  streamwise coherent structures predicted through traditional input-output approaches but also characterization of the oblique flow structures as those requiring the least energy to induce transition in agreement with DNS studies, and nonlinear optimal perturbation analysis.
Revised:  Application of this method to transitional plane Couette and plane Poiseuille flows leads to identification of not only the identification of the streamwise coherent structures predicted through traditional input-output approaches but also characterization of the oblique flow structures as those requiring the least energy to induce transition in agreement with DNS studies, and nonlinear optimal perturbation analysis.
Edit intent: fluency
Original:  Application of this method to transitional plane Couette and plane Poiseuille flows leads to identification of not only the  streamwise coherent structures predicted through traditional input-output approaches but also characterization of the oblique flow structures as those requiring the least energy to induce transition in agreement with DNS studies, and nonlinear optimal perturbation analysis.
Revised:  Application of this method to transitional plane Couette and plane Poiseuille flows leads to identification of not only the streamwise coherent structures predicted through traditional input-output approaches , but also the characterization of the oblique flow structures as those requiring the least energy to induce transition in agreement with DNS studies, and nonlinear optimal perturbation analysis.
Edit intent: fluency
Original:  Capturing this key nonlinear mechanism enables the prediction of the wider range of known transitional flow structures within the analytical input--output modeling paradigm.
Revised:  Capturing this key nonlinear effect enables the prediction of the wider range of known transitional flow structures within the analytical input--output modeling paradigm.
Edit intent: clarity
Original:  Capturing this key nonlinear mechanism enables the prediction of the wider range of known transitional flow structures within the analytical input--output modeling paradigm.
Revised:  Capturing this key nonlinear mechanism enables the prediction of the wider range of known transitional flow structures within the analytical input-output modeling paradigm.
Edit intent: fluency
Original:  In specific , we present a formulation of MPC designed for 10 degree-of-freedom (DoF) bipedal robots using a simplified rigid body dynamics with input forces and moments.
Revised:  Specifically , we present a formulation of MPC designed for 10 degree-of-freedom (DoF) bipedal robots using a simplified rigid body dynamics with input forces and moments.
Edit intent: fluency
Original:  In specific , we present a formulation of MPC designed for 10 degree-of-freedom (DoF) bipedal robots using a simplified rigid body dynamics with input forces and moments.
Revised:  In specific , we present a formulation of MPC designed for 10 degree-of-freedom (DoF) bipedal robots using simplified rigid body dynamics with input forces and moments.
Edit intent: fluency
Original:  THU-splines are piecewise polynomials that form a partition of unity.
Edit intent: coherence
Original:  Population-level ideas have so far had their greatest impact in motor neurophysiology , but they hold incredible promise for resolving open questions in cognition  .
Revised:  Population-level ideas have so far had their greatest impact in motor neuroscience , but they hold incredible promise for resolving open questions in cognition .
Edit intent: clarity
Original:  Population-level ideas have so far had their greatest impact in motor neurophysiology , but they hold incredible promise for resolving open questions in cognition  .
Revised:  Population-level ideas have so far had their greatest impact in motor neurophysiology , but they hold great promise for resolving open questions in cognition .
Edit intent: clarity