wanyu/IteraTeR_v2 huggingface dataset:
Original:  Historically, researches on dynamic rating have been focused on real-time or near-future system operations.
Revised:  Historically, researches on dynamic rating have been focused on real-time / near-future system operations.
Edit intent: fluency
Original:  Currently, almost all utility companies still rely on static rating numbers when planning power transformers for the next few years.
Revised:  Currently, most utility companies still rely on static rating numbers when planning power transformers for the next few years.
Edit intent: clarity
Original:  In response, this paper proposes a novel and comprehensive method to analyze the past 5-year temperature, loading and transformer load composition data of existing power transformers for a planning region.
Revised:  In response, this paper proposes a novel and comprehensive method to analyze the past 5-year temperature, loading and load composition data of existing power transformers for a planning region.
Edit intent: clarity
Original:  In response, this paper proposes a novel and comprehensive method to analyze the past 5-year temperature, loading and transformer load composition data of existing power transformers for a planning region.
Revised:  In response, this paper proposes a novel and comprehensive method to analyze the past 5-year temperature, loading and transformer load composition data of existing power transformers in a planning region.
Edit intent: clarity
Original:  C57.91-2011, a power transformer thermal aging model can be established to incorporate future loading and temperature profiles under different scenarios .
Revised:  C57.91-2011, a power transformer thermal aging model can be established to incorporate future loading and temperature profiles .
Edit intent: clarity
Original:  As a result, an annual continuous dynamic rating profile can be determined.
Revised:  As a result, annual continuous dynamic rating profile can be determined.
Edit intent: fluency
Original:  As a result, an annual continuous dynamic rating profile can be determined.
Revised:  As a result, an annual continuous dynamic rating profiles under different temperature scenarios can be determined.
Edit intent: clarity
Original:  This profile can reflect the long-term thermal overloading risk in a much more realistic and granular way, which can significantly improve the cost-effectiveness of power transformer planning.
Revised:  The profiles can reflect the long-term thermal overloading risk in a much more realistic and granular way, which can significantly improve the cost-effectiveness of power transformer planning.
Edit intent: fluency
Original:  This profile can reflect the long-term thermal overloading risk in a much more realistic and granular way, which can significantly improve the cost-effectiveness of power transformer planning.
Revised:  This profile can reflect the long-term thermal overloading risk in a much more realistic and granular way, which can significantly improve the accuracy of power transformer planning.
Edit intent: clarity
Original:  A real utility application example in West Canada has been presented to demonstrate the practicality and usefulness of such method.
Revised:  A real utility application example in Canada has been presented to demonstrate the practicality and usefulness of such method.
Edit intent: clarity
Original:  A real utility application example in West Canada has been presented to demonstrate the practicality and usefulness of such method.
Revised:  A real utility application example in West Canada has been presented to demonstrate the practicality and usefulness of this method.
Edit intent: clarity
Original: Model View Definition (MVD) is the standard methodology to define the partial models and data exchange requirements for Building Information Model (BIM).
Revised: Model View Definition (MVD) is the standard methodology to define the exchange requirements and data constraints for Building Information Model (BIM).
Edit intent: clarity
Original:  Based on a simplified "rule chain" structure , a fast MVD validation algorithm which performs node set mapping calculations instead of traversing the subgraphs of each root entity is proposed.
Revised:  Based on a simplified "rule chain" structure , a fast MVD validation algorithm is proposed.
Edit intent: clarity
Original:   A case study is provided to show the workflow for developing an enterprise-level MVD based on MVDLite, and its applications in  validation and partial model extraction.
Revised:  A case study is provided to show the workflow for developing an enterprise-level MVD based on MVDLite, and its applications in MVD validation and partial model extraction.
Edit intent: clarity
Original:  The state-of-art involves 1) dividing portions of an image into overlapped tiles, where each tile can be processed by a single thread block and 2) fusing loops together to improve memory locality.
Revised:  The state-of-art involves 1) dividing the image into overlapped tiles, where each tile can be processed by a single thread block and 2) fusing loops together to improve memory locality.
Edit intent: clarity
Original:  The state-of-art involves 1) dividing portions of an image into overlapped tiles, where each tile can be processed by a single thread block and 2) fusing loops together to improve memory locality.
Revised:  The state-of-art involves 1) dividing portions of an image into overlapped tiles, and 2) fusing loops together to improve memory locality.
Edit intent: coherence
Original:  The state-of-art involves 1) dividing portions of an image into overlapped tiles, where each tile can be processed by a single thread block and 2) fusing loops together to improve memory locality.
Revised:  The state-of-art involves 1) dividing portions of an image into overlapped tiles, where each tile can be processed by a single thread block and 2) fusing loops to improve memory locality.
Edit intent: clarity
Original:  However, the state-of-the-art has two limitations: 1) synchronization between all threads across thread blocks has a nontrivial costand 2)  autoscheduling algorithms use an overly simplified model of GPUs.
Revised:  However, current approaches have limitations: 1) synchronization between all threads across thread blocks has a nontrivial costand 2) autoscheduling algorithms use an overly simplified model of GPUs.
Edit intent: clarity
Original:  However, the state-of-the-art has two limitations: 1) synchronization between all threads across thread blocks has a nontrivial costand 2)  autoscheduling algorithms use an overly simplified model of GPUs.
Revised:  However, the state-of-the-art has two limitations: 1) they require intra thread block synchronization, which has a non-trivial cost, 2) autoscheduling algorithms use an overly simplified model of GPUs.
Edit intent: clarity
Original:  This paper presents a new approach for optimizing image processing programs on GPUs . First, we fuse loops to form overlapped tiles that can be processed by a single warp, which allows us to use lightweight warp synchronization.
Revised:  This paper presents a new approach for optimizing image processing programs on GPUs . First, we fuse loops to form overlapped tiles that fit in a single warp, which allows us to use lightweight warp synchronization.
Edit intent: clarity
Original:  Second, we introduce hybrid tiling, which is an approach that partially stores overlapped regions in  thread-local registers instead of shared memory, thus increasing occupancy and providing faster access to data.
Revised:  2) We introduce hybrid tiling, which is an approach that partially stores overlapped regions in thread-local registers instead of shared memory, thus increasing occupancy and providing faster access to data.
Edit intent: coherence
Original:  Second, we introduce hybrid tiling, which is an approach that partially stores overlapped regions in  thread-local registers instead of shared memory, thus increasing occupancy and providing faster access to data.
Revised:  Second, we introduce hybrid tiling, which stores overlapped regions in thread-local registers instead of shared memory, thus increasing occupancy and providing faster access to data.
Edit intent: clarity
Original:  Using a Tesla V100 GPU, our approach is 1.73x faster than manual schedules, 2.67x faster than the auto-scheduler, and 8x faster than autotuner .
Revised:  Using a Tesla V100 .
Edit intent: clarity
Original:  We also consider general stationary AR(p) processes , where we prove that the deconvolution C= A \ast B does not exist if the matrix B is diagonal and its size is larger than p.
Revised:  We also consider general autoregressive models of order p , where we prove that the deconvolution C= A \ast B does not exist if the matrix B is diagonal and its size is larger than p.
Edit intent: clarity
Original: It has been suggested that all resistive-switching memories are memristors.
Revised: It has been suggested that all resistive-switching memory cells are memristors.
Edit intent: clarity
Original:  Here, we experimentally apply such a test to Cu-SiO2-based electrochemical metallization memory cells, and show that electrochemical metallization memories are not memristors.
Revised:  Here, we experimentally apply such a test to Cu-SiO2-based electrochemical metallization memory cells, and show that electrochemical metallization memory cells are not memristors.
Edit intent: fluency
Original: Solving linear systems of equations is an essential component in science and technology, including in many machine learningalgorithms . Existing quantum algorithms have demonstrated large speedup in solving linear systems , but the required quantum resources are not  available on near-term quantum devices.
Revised: Solving linear systems of equations is essential for many problems in science and technology, including in many machine learningalgorithms . Existing quantum algorithms have demonstrated large speedup in solving linear systems , but the required quantum resources are not available on near-term quantum devices.
Edit intent: clarity
Original: Solving linear systems of equations is an essential component in science and technology, including in many machine learningalgorithms . Existing quantum algorithms have demonstrated large speedup in solving linear systems , but the required quantum resources are not  available on near-term quantum devices.
Revised: Solving linear systems of equations is an essential component in science and technology, including problems in machine learning . Existing quantum algorithms have demonstrated large speedup in solving linear systems , but the required quantum resources are not available on near-term quantum devices.
Edit intent: clarity
Original: Solving linear systems of equations is an essential component in science and technology, including in many machine learningalgorithms . Existing quantum algorithms have demonstrated large speedup in solving linear systems , but the required quantum resources are not  available on near-term quantum devices.
Revised: Solving linear systems of equations is an essential component in science and technology, including in many machine learningalgorithms . Existing quantum algorithms have demonstrated the potential for large speedups , but the required quantum resources are not available on near-term quantum devices.
Edit intent: clarity
Original: Solving linear systems of equations is an essential component in science and technology, including in many machine learningalgorithms . Existing quantum algorithms have demonstrated large speedup in solving linear systems , but the required quantum resources are not  available on near-term quantum devices.
Revised: Solving linear systems of equations is an essential component in science and technology, including in many machine learningalgorithms . Existing quantum algorithms have demonstrated large speedup in solving linear systems , but the required quantum resources are not immediately available on near-term quantum devices.
Edit intent: clarity
Original:  In this work, we study potential near-term quantum algorithms for linear systems of equations  .
Revised:  In this work, we study near-term quantum algorithms for linear systems of equations .
Edit intent: clarity
Original:  We found that a wide range of variational algorithms designed to avoid barren plateaus, such as properly-initialized imaginary time evolution and adiabatic-inspired optimization, still suffer from a fundamentally different plateau problem.
Revised:  We found that a wide range of variational algorithms designed to avoid barren plateaus, such as properly-initialized imaginary time evolution and adiabatic-inspired optimization, suffer from a fundamentally different plateau problem.
Edit intent: clarity
Original:  We found that a wide range of variational algorithms designed to avoid barren plateaus, such as properly-initialized imaginary time evolution and adiabatic-inspired optimization, still suffer from a fundamentally different plateau problem.
Revised:  We found that a wide range of variational algorithms designed to avoid barren plateaus, such as properly-initialized imaginary time evolution and adiabatic-inspired optimization, still suffer from a different plateau problem.
Edit intent: clarity
Original:  To circumvent this issue, we design a potentially near-term adaptive alternating algorithm based on a core idea: the classical combination of variational quantum states .
Revised:  To circumvent this issue, we design near-term adaptive alternating algorithm based on a core idea: the classical combination of variational quantum states .
Edit intent: clarity
Original:  To circumvent this issue, we design a potentially near-term adaptive alternating algorithm based on a core idea: the classical combination of variational quantum states .
Revised:  To circumvent this issue, we design a potentially near-term algorithms based on a core idea: the classical combination of variational quantum states .
Edit intent: clarity
Original:  These experiments demonstrate the algorithm' s ability to scale to system sizes within reach in near-term quantum devices of about 100-300 qubits.
Revised:  These experiments demonstrate the algorithms' ability to scale to system sizes within reach in near-term quantum devices of about 100-300 qubits.
Edit intent: fluency
Original: A simple drawing {\em  D(G) of a graph G = (V,E) is a drawing in which two edges have at most one point in common that is either an endpoint or a proper crossing.
Revised: A {\em D(G) of a graph G = (V,E) is a drawing in which two edges have at most one point in common that is either an endpoint or a proper crossing.
Edit intent: clarity
Original: A simple drawing {\em  D(G) of a graph G = (V,E) is a drawing in which two edges have at most one point in common that is either an endpoint or a proper crossing.
Revised: A simple drawing {\em D(G) of a graph G = (V,E) is a drawing in which two edges have at most one point : either a common endpoint or a proper crossing.
Edit intent: clarity
Original:  We show that it is NP-complete to decide whether a given edge can be inserted into a simple drawing , by this solving an open question by Arroyo, Derka, and Parada .
Revised:  We show that it is NP -complete to decide whether a given edge can be inserted into a simple drawing , by this solving an open question by Arroyo, Derka, and Parada .
Edit intent: fluency
Original:  We show that it is NP-complete to decide whether a given edge can be inserted into a simple drawing , by this solving an open question by Arroyo, Derka, and Parada .
Revised:  We show that it is NP-complete to decide whether one edge can be inserted into a simple drawing , by this solving an open question by Arroyo, Derka, and Parada .
Edit intent: clarity
Original:  In this paper, we formulate the problem of learning an Implicit Generative Model (IGM ) as minimizing the expected distance between characteristic functions.
Revised:  In this paper, we formulate the problem of learning an IGM as minimizing the expected distance between characteristic functions.
Edit intent: clarity
Original:  This distance measure , which we term as the characteristic function distance (CFD), can be (approximately) computed with linear time-complexity in the number of samples, compared to the quadratic-time Maximum Mean Discrepancy (MMD).
Revised:  This distance metric , which we term as the characteristic function distance (CFD), can be (approximately) computed with linear time-complexity in the number of samples, compared to the quadratic-time Maximum Mean Discrepancy (MMD).
Edit intent: clarity
Original:  This distance measure , which we term as the characteristic function distance (CFD), can be (approximately) computed with linear time-complexity in the number of samples, compared to the quadratic-time Maximum Mean Discrepancy (MMD).
Revised:  This distance measure , which we term as the characteristic function distance (CFD), can be (approximately) computed with linear time-complexity in the number of samples, in contrast with the quadratic-time Maximum Mean Discrepancy (MMD).
Edit intent: clarity
Original:  this obviates the need for manual tuning  and leads to an improvement in test power relative to CFD.
Revised:  this obviates the need for manual tuning , and leads to an improvement in test power relative to CFD.
Edit intent: fluency
Original:  Experiments show that our proposed method outperforms WGAN and MMD-GAN variants on a variety of unsupervised image generation benchmark datasets .
Revised:  We demonstrate experimentally that our proposed method outperforms WGAN and MMD-GAN variants on a variety of unsupervised image generation benchmark datasets .
Edit intent: clarity
Original:  Experiments show that our proposed method outperforms WGAN and MMD-GAN variants on a variety of unsupervised image generation benchmark datasets .
Revised:  Experiments show that our proposed method outperforms WGAN and MMD-GAN variants on a variety of unsupervised image generation benchmarks .
Edit intent: clarity
Original:  Based on a beautiful characterization that is proved in more than twenty pages, Chudnovsky and Seymour [ Com-binatorica 2010] gave the previously only known polynomial-time algorithm, running in O(mn^2) time, to solve the three-in-a-tree problem on an n-vertex m-edge graph.
Revised:  Based on a beautiful characterization that is proved in more than twenty pages, Chudnovsky and Seymour [ Combinatorica 2010] gave the previously only known polynomial-time algorithm, running in O(mn^2) time, to solve the three-in-a-tree problem on an n-vertex m-edge graph.
Edit intent: fluency
Original:  We prove this result for the linear advection equation but  carry out high-order experiments on the full Navier--Stokes equations.
Revised:  We prove this result for the linear advection equation but also carry out high-order experiments on the full Navier--Stokes equations.
Edit intent: clarity
Original:  In previous work, we studied how this issue can be tackled by interacting with the robots in two modalities --- environment-oriented and robot-oriented.
Revised:  In previous work, we studied how this issue can be tackled by interacting with the robots in two modalities -- environment-oriented and robot-oriented.
Edit intent: fluency
Original:  In particular, one challenge arises --- the out-of-the-loop performance problem caused by a lack of engagement in the task, awareness of its state, and trust in the system and in the other operators.
Revised:  In particular, one challenge arises -- the out-of-the-loop performance problem caused by a lack of engagement in the task, awareness of its state, and trust in the system and in the other operators.
Edit intent: fluency
Original:  To the best of our knowledge, these are the first constant pass, logspace streaming PTASs for constrained versions of the k-means problem. - Faster PTAS under stability: Our generalisation is also useful in k-means clustering scenarios where finding good centers becomes easy once good centers for a few "bad" clusters have been chosen.
Revised:  - Faster PTAS under stability: Our generalisation is also useful in k-means clustering scenarios where finding good centers becomes easy once good centers for a few "bad" clusters have been chosen.
Edit intent: clarity
Original: We conduct to our knowledge a first measurement study of commercial mmWave 5G performance on smartphones by closely examining 5G networks in two U.S. cities.
Revised: We conduct to our knowledge a first measurement study of commercial 5G performance on smartphones by closely examining 5G networks in two U.S. cities.
Edit intent: clarity
Original:  We conduct extensive field tests on 5G performance under diverse conditions including different obstruction levels, phone-tower distances, and device orientations .
Revised:  We conduct extensive field tests on 5G performance in diverse urban environments .
Edit intent: clarity
Original:  These experiments provide a baseline for studying how 5G performance evolves, and identify key research directions on improving 5G users' experience in a cross-layer manner. 
Revised:  These experiments provide a baseline for studying how 5G performance evolves, and identifies key research directions on improving 5G users' experience in a cross-layer manner. 
Edit intent: fluency
Original:  While EFX is our primary focus, we also exhibit how to fine-tune our algorithm and improve the guarantees for GMMS or PMMS. Finally, we show that GMMS -and thus PMMS and EFX- allocations always exist when the number of goods does not exceed the number of agents by more than two.
Revised:  While EFX is our primary focus, we also exhibit how to fine-tune our algorithm and improve the guarantees for GMMS or PMMS. Finally, we show that GMMS -- and thus PMMS and EFX- allocations always exist when the number of goods does not exceed the number of agents by more than two.
Edit intent: fluency
Original:  While EFX is our primary focus, we also exhibit how to fine-tune our algorithm and improve the guarantees for GMMS or PMMS. Finally, we show that GMMS -and thus PMMS and EFX- allocations always exist when the number of goods does not exceed the number of agents by more than two.
Revised:  While EFX is our primary focus, we also exhibit how to fine-tune our algorithm and improve the guarantees for GMMS or PMMS. Finally, we show that GMMS -and thus PMMS and EFX -- allocations always exist when the number of goods does not exceed the number of agents by more than two.
Edit intent: fluency
Original:  To do so, we start from Bou et al.'s minimal modal logic over a finite and linearly ordered residuated lattice and define appropriate extensions on a multi-modal language with graded modalities, both for weak and strict preferences .
Revised:  To do so, we start from Bou et al.'s minimal modal logic over a finite and linearly ordered residuated lattice . We then define appropriate extensions on a multi-modal language with graded modalities, both for weak and strict preferences .
Edit intent: coherence
Original: We propose K-TanH, a novel, highly accurate, hardware efficient approximation of popular activation function Tanh for Deep Learning.
Revised: We propose K-TanH, a novel, highly accurate, hardware efficient approximation of popular activation function TanH for Deep Learning.
Edit intent: fluency
Original:  K-TanH consists of a sequence of parameterized bit/ integer operations, such as, masking, shift and add/subtract (no floating point operation needed) where parameters are stored in a very small look-up table (bit-masking step can be eliminated).
Revised:  K-TanH consists of parameterized low-precision integer operations, such as, masking, shift and add/subtract (no floating point operation needed) where parameters are stored in a very small look-up table (bit-masking step can be eliminated).
Edit intent: clarity