wanyu/IteraTeR_v2 huggingface dataset:
Original: Using elementary cellular automata as an example, a novel, information-based classification of complex systems is proposed that circumvents the problems associated with isolating the complexity generated as a product of an initial state from that which is intrinsic to a dynamical rule  .
Revised: Using elementary cellular automata as an example, a novel, information-based classification of complex systems is proposed that circumvents the problems associated with isolating whether complexity is in fact intrinsic to a dynamical rule .
Edit intent: clarity
Original:  Transfer entropy variations processed by the system for different initial states split the 256 elementary rules into three information classes  .
Revised:  Transfer entropy variations processed by the system split the 256 elementary rules into three information classes .
Edit intent: clarity
Original:  These classes form a hierarchy such that coarse-graining transitions permitted among automata rules predominately occur within each information-based class, or much more rarely  down the hierarchy.
Revised:  These classes form a hierarchy such that coarse-graining transitions permitted among automata rules predominately occur within each information- based class, or much more rarely down the hierarchy.
Edit intent: fluency
Original:  These classes form a hierarchy such that coarse-graining transitions permitted among automata rules predominately occur within each information-based class, or much more rarely  down the hierarchy.
Revised:  These classes form a hierarchy such that coarse-graining transitions permitted among automata rules predominately occur within each information-based class, or much more rarely , down the hierarchy.
Edit intent: fluency
Original: In dense small cell networks (SCNs), a large number of base stations (BSs)  can be put to idle modes without signal transmission, if there is no active user equipment (UE ) within their coverage areas.
Revised: In dense small cell networks (SCNs), a large number of base stations (BSs) can be put into idle modes without signal transmission, if there is no active user equipment (UE ) within their coverage areas.
Edit intent: fluency
Original: In dense small cell networks (SCNs), a large number of base stations (BSs)  can be put to idle modes without signal transmission, if there is no active user equipment (UE ) within their coverage areas.
Revised: In dense small cell networks (SCNs), a large number of base stations (BSs) can be put to idle modes without signal transmission, if there is no active UE within their coverage areas.
Edit intent: clarity
Original:  Setting those BSs to idle modes can mitigate unnecessary inter-cell interference and reduce energy consumption.
Revised:  Setting those BSs into idle modes mitigates unnecessary inter-cell interference and reduce energy consumption.
Edit intent: clarity
Original:  Setting those BSs to idle modes can mitigate unnecessary inter-cell interference and reduce energy consumption.
Revised:  Setting those BSs to idle modes can mitigate unnecessary inter-cell interference and reduces energy consumption.
Edit intent: fluency
Original:  Such idle mode feature at BSs is referred to as the idle mode capability (IMC) and it can largely improve the performance of the 5th-generation (5G) networks.
Edit intent: coherence
Original:  In this paper, we study the performance impact of the BS IMC on dense SCNs. Different from existing work, we consider a sophisticated and more realistic path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions.
Revised:  In this paper, we investigate the performance impact of the BS IMC on dense SCNs. Different from existing work, we consider a sophisticated and more realistic path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions.
Edit intent: clarity
Original:  In this paper, we study the performance impact of the BS IMC on dense SCNs. Different from existing work, we consider a sophisticated and more realistic path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions.
Revised:  In this paper, we study the performance impact of such BS idle mode capability (IMC) on dense SCNs. Different from existing work, we consider a sophisticated and more realistic path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions.
Edit intent: clarity
Original:  In this paper, we study the performance impact of the BS IMC on dense SCNs. Different from existing work, we consider a sophisticated and more realistic path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions.
Revised:  In this paper, we study the performance impact of the BS IMC on dense SCNs. Different from existing work, we consider a realistic path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions.
Edit intent: coherence
Original:  Analytical results are obtained for the coverage probability, the area spectral efficiency  and the energy efficiency  performance for SCNs with the BS IMC . An upper bound, a lower bound and an approximate expression of the density of the non-idle BSs are also derived.
Revised:  Moreover, we obtain analytical results for the coverage probability, the area spectral efficiency and the energy efficiency performance for SCNs with the BS IMC . An upper bound, a lower bound and an approximate expression of the density of the non-idle BSs are also derived.
Edit intent: coherence
Original:  The performance impact of the IMC on network densification is shown to be significant.
Revised:  The performance impact of the IMC on dense SCNs is significant.
Edit intent: clarity
Original:  This technical report is an extended version of a recently submitted conference paper.
Edit intent: coherence
Original:  We also obtain an algorithm with query complexity {O}(n^{5/6}(m\log n)^{1/6}+d_2n) where d_2 is the variance of the degree repartition .
Revised:  We also obtain an algorithm with query complexity {O}(n^{5/6}(m\log n)^{1/6}+d_2n) where d_2 is the variance of the degree distribution .
Edit intent: fluency
Original:  However, the self-healing ability emerges as a valuable opportunity where the overlaying cyber network can cure failures in the underlying physical network.
Revised:  However, the self-healing ability emerges as a valuable opportunity where the overlaying cyber network can cure failures in the underlying physical network.
Edit intent: fluency
Original:  A message-passing algorithm used in low-density parity-check codes is extended to this representation to study the dynamics of failure propagation and healing.
Revised:  A message-passing algorithm is proposed for this representation to study the dynamics of failure propagation and healing.
Edit intent: clarity
Original:  By applying a density evolution analysis to this algorithm, network reaction to initial disruptions is investigated.
Revised:  By conducting a density evolution analysis to this algorithm, network reaction to initial disruptions is investigated.
Edit intent: clarity
Original:  By applying a density evolution analysis to this algorithm, network reaction to initial disruptions is investigated.
Revised:  By applying a density evolution analysis for this algorithm, network reaction to initial disruptions is investigated.
Edit intent: clarity
Original:  We show empirically that multiplicative LSTM outperforms standard LSTM and  deep variants for a range of character level modelling tasks.
Revised:  We show empirically that multiplicative LSTM outperforms standard LSTM and its deep variants for a range of character level modelling tasks.
Edit intent: clarity
Original: This paper introduces multiplicative LSTM , a novel hybrid recurrent neural network architecture for sequence modelling that combines the long short-term memory (LSTM) and multiplicative recurrent neural network architectures.
Revised: We introduce multiplicative LSTM (mLSTM), a recurrent neural network architecture for sequence modelling that combines the long short-term memory (LSTM) and multiplicative recurrent neural network architectures.
Edit intent: clarity
Original:  Multiplicative LSTM is motivated by its flexibility to have very different recurrent transition functions for each possible input, which we argue helps make it more expressive in autoregressive density estimation.
Revised:  mLSTM is characterised by its ability to have different recurrent transition functions for each possible input, which we argue helps make it more expressive in autoregressive density estimation.
Edit intent: clarity
Original:  Multiplicative LSTM is motivated by its flexibility to have very different recurrent transition functions for each possible input, which we argue helps make it more expressive in autoregressive density estimation.
Revised:  Multiplicative LSTM is motivated by its flexibility to have very different recurrent transition functions for each possible input, which we argue makes it more expressive in autoregressive density estimation.
Edit intent: coherence
Original:  Multiplicative LSTM is motivated by its flexibility to have very different recurrent transition functions for each possible input, which we argue helps make it more expressive in autoregressive density estimation.
Revised:  Multiplicative LSTM is motivated by its flexibility to have very different recurrent transition functions for each possible input, which we argue helps make it more expressive for autoregressive density estimation.
Edit intent: fluency
Original:  We show empirically that multiplicative LSTM outperforms standard LSTM and its deep variants for a range of character level  modelling tasks.
Revised:  We demonstrate empirically that mLSTM outperforms standard LSTM and its deep variants for a range of character level modelling tasks.
Edit intent: clarity
Original:  But the very distinctiveness of spatial data that drives utility, comes at the cost of user privacy.
Revised:  But the very distinctiveness of spatial data that drives utility, can cost user privacy.
Edit intent: clarity
Original:  Such data represents the area of a user's most frequent visitation - such as "around home and nearby shops".
Revised:  Such data represents the area of a user's most frequent visitation---such as "around home and nearby shops".
Edit intent: fluency
Original:  Our novel constrained inference reduces noise and introduces covertness by (privately) imposing consistency.
Revised:  Our novel constrained inference reduces noise and promotes covertness by (privately) imposing consistency.
Edit intent: clarity
Original: The delivery and display of ultra high resolution 360-degree videos on Head-Mounted Displays (HMDs) presents a number of technical challenges.
Revised: The delivery and display of 360-degree videos on Head-Mounted Displays (HMDs) presents a number of technical challenges.
Edit intent: clarity
Original: The delivery and display of ultra high resolution 360-degree videos on Head-Mounted Displays (HMDs) presents a number of technical challenges.
Revised: The delivery and display of ultra high resolution 360-degree videos on Head-Mounted Displays (HMDs) presents many technical challenges.
Edit intent: clarity
Original:  360-degree videos are  high resolution spherical videos that contain an omnidirectional view of the scene , however only a portion of this scene is displayed at any time on the user's HMD. The delivery of such videos wastes network resources since most of the pixel data are never used.
Revised:  360-degree videos are ultra high resolution spherical videos that contain an omnidirectional view of the scene , however only a portion of this scene is displayed at any time on the user's HMD. The delivery of such videos wastes network resources since most of the pixel data are never used.
Edit intent: clarity
Original:  360-degree videos are  high resolution spherical videos that contain an omnidirectional view of the scene , however only a portion of this scene is displayed at any time on the user's HMD. The delivery of such videos wastes network resources since most of the pixel data are never used.
Revised:  360-degree videos are high resolution spherical videos , which contain an omnidirectional view of the scene , however only a portion of this scene is displayed at any time on the user's HMD. The delivery of such videos wastes network resources since most of the pixel data are never used.
Edit intent: fluency
Original:  360-degree videos are  high resolution spherical videos that contain an omnidirectional view of the scene , however only a portion of this scene is displayed at any time on the user's HMD. The delivery of such videos wastes network resources since most of the pixel data are never used.
Revised:  360-degree videos are high resolution spherical videos that contain an omnidirectional view of the scene . However only a portion of this scene is displayed at any time on the user's HMD. The delivery of such videos wastes network resources since most of the pixel data are never used.
Edit intent: fluency
Original:  With high refresh rates, HMDs need to respond in less than 10 ms to head movements .
Revised:  With high refresh rates, HMDs need to respond in 10 ms to head movements .
Edit intent: clarity
Original:  Instead, an entire 360-degree video scene needs to be delivered to the client to extract the appropriate fraction of this scene on the client's end.
Edit intent: coherence
Original:  To reduce the required immense video bit-rate , while still providing an immersive experience to the user, a viewpoint-adaptive 360-degree video streaming system is proposed.
Revised:  To reduce the bandwidth waste , while still providing an immersive experience to the user, a viewpoint-adaptive 360-degree video streaming system is proposed.
Edit intent: clarity
Original:  To reduce the required immense video bit-rate , while still providing an immersive experience to the user, a viewpoint-adaptive 360-degree video streaming system is proposed.
Revised:  To reduce the required immense video bit-rate , while still providing an immersive experience , a viewport-adaptive 360-degree video streaming system is proposed.
Edit intent: clarity
Original:  In this system, the server prepares multiple video representations that differ not only by their bit-rate, but also by the qualities of different scene regions they support .
Revised:  The server prepares multiple video representations that differ not only by their bit-rate, but also by the qualities of different scene regions they support .
Edit intent: clarity
Original:  In this system, the server prepares multiple video representations that differ not only by their bit-rate, but also by the qualities of different scene regions they support .
Revised:  In this system, the server prepares multiple video representations , which differ not only by their bit-rate, but also by the qualities of different scene regions they support .
Edit intent: fluency
Original:  In this system, the server prepares multiple video representations that differ not only by their bit-rate, but also by the qualities of different scene regions they support .
Revised:  In this system, the server prepares multiple video representations that differ not only by their bit-rate, but also by the qualities of different scene regions .
Edit intent: clarity
Original:  The client chooses a representation for the next segment such that its bit-rate fits the available throughput and a full quality region matches its viewing direction .
Revised:  The client chooses a representation for the next segment such that its bit-rate fits the available throughput and a full quality region matches its viewing .
Edit intent: clarity
Original: User preference integration is of great importance in multiobjective optimization, in particular in many objective optimization.
Revised: User preference integration is of great importance in multi-objective optimization, in particular in many objective optimization.
Edit intent: fluency
Original:  Preferences have long been considered in traditional multicriteria decision making (MCDM) which is based on mathematical programming and recently it is integrated in evolutionary multiobjective optimization (EMO ), resulting in focus on preferred parts of the Pareto front instead of the whole Pareto front.
Revised:  Preferences have long been considered in traditional multicriteria decision making (MCDM) which is based on mathematical programming . Recently, it is integrated in evolutionary multiobjective optimization (EMO ), resulting in focus on preferred parts of the Pareto front instead of the whole Pareto front.
Edit intent: coherence
Original:  The number of publications and results on preference-based multiobjective evolutionary algorithms (PMOEAs) has increased rapidly over the past decade .
Revised:  The number of publications on preference-based multiobjective evolutionary algorithms (PMOEAs) has increased rapidly over the past decade .
Edit intent: clarity
Original:  The number of publications and results on preference-based multiobjective evolutionary algorithms (PMOEAs) has increased rapidly over the past decade .
Revised:  The number of publications and results on preference-based multi-objective metaheuristics has increased rapidly over the past decade .
Edit intent: clarity
Original:  The number of publications and results on preference-based multiobjective evolutionary algorithms (PMOEAs) has increased rapidly over the past decade .
Revised:  The number of publications and results on preference-based multiobjective evolutionary algorithms (PMOEAs) has increased rapidly over the past decades .
Edit intent: clarity
Original:  There already exists a large variety of preference handling methods and EMO methods, which have been combined in various ways.
Revised:  There already exist various preference handling methods and EMO methods, which have been combined in various ways.
Edit intent: clarity
Original:  There already exists a large variety of preference handling methods and EMO methods, which have been combined in various ways.
Revised:  There already exists a large variety of preference handling methods and EMO methods, which have been combined in diverse ways.
Edit intent: fluency
Original:  An extensive review of the existing work is provided, based on which an ontology is built and instantiated with state of the art results.
Revised:  A review of the existing work is provided, based on which an ontology is built and instantiated with state of the art results.
Edit intent: clarity
Original:  An extensive review of the existing work is provided, based on which an ontology is built and instantiated with state of the art results.
Revised:  An extensive review of the existing work is provided, based on which an ontology is built and instantiated with state-of-the-art results.
Edit intent: fluency
Original:  Moreover, the usage of the ontology is exemplified for different use-cases, including training new researchers into this knowledge domain, querying for methods that match an application problem in engineering optimization, checking existence of combinations of preference models and EMO techniques, and discovering opportunities for new research and open research questions.
Revised:  Moreover, the usage of the ontology is exemplified for different use-cases, including querying for methods that match an application problem in engineering optimization, checking existence of combinations of preference models and EMO techniques, and discovering opportunities for new research and open research questions.
Edit intent: clarity
Original: Autonomous Mobility On Demand (MOD) systems can utilize fleet management strategies to properly position vehicles and allocate customers in order to maintain a high customer quality of service (QoS).
Revised: Autonomous Mobility On Demand (MOD) systems can utilize fleet management strategies in order to maintain a high customer quality of service (QoS).
Edit intent: clarity
Original: Autonomous Mobility On Demand (MOD) systems can utilize fleet management strategies to properly position vehicles and allocate customers in order to maintain a high customer quality of service (QoS).
Revised: Autonomous Mobility On Demand (MOD) systems can utilize fleet management strategies to properly position vehicles and allocate customers in order to provide a high customer quality of service (QoS).
Edit intent: clarity
Original:  A predictive positioning method is presented for improving customer QoS in small-fleet MOD systems by identifying key locations which minimize expected customer wait time.
Revised:  A predictive positioning method is presented for improving customer QoS by identifying key locations which minimize expected customer wait time.
Edit intent: clarity
Original:  A predictive positioning method is presented for improving customer QoS in small-fleet MOD systems by identifying key locations which minimize expected customer wait time.
Revised:  A predictive positioning method is presented for improving customer QoS in small-fleet MOD systems by identifying key locations to position the fleet in order to minimize expected customer wait time.
Edit intent: clarity
Original: A combined predictive positioning and ridesharing approach is shown to reduce customer service times by up to 29\% . and the customer ratings model is shown to provide the best overall MOD fleet management performance over a range of customer preferences.
Revised: A combined predictive positioning and ridesharing approach is shown to reduce customer service times by up to 29\% and the customer ratings model is shown to provide the best overall MOD fleet management performance over a range of customer preferences.
Edit intent: fluency
Original:  Finally, we experimentally demonstrate that the performance of our algorithm tracks recent information theoretic bounds for exact recovery in the stochastic block model  .
Revised:  We also experimentally demonstrate that the performance of our algorithm tracks recent information theoretic bounds for exact recovery in the stochastic block model .
Edit intent: coherence
Original:  The gain in speed is about two orders of magnitude.
Revised:  The gain in speed is between one and two orders of magnitude.
Edit intent: clarity
Original: We consider a cyclically competing species model on a ring with global mixing at finite rate, which corresponds to the well-known Lotka-Volterra equation in the  infinite mixing rate.
Revised: We consider a cyclically competing species model on a ring with global mixing at finite rate, which corresponds to the well-known Lotka-Volterra equation in the limit of infinite mixing rate.
Edit intent: clarity
Original:  Within a perturbation analysis of the model from the infinite mixing rate, we provide analytical evidence that extinction occurs deterministically at sufficiently large but finite values of the mixing rate for any odd species numbers\ge3 . Further,  we discuss numerical results concerning the trajectories toward such deterministic extinction, including bifurcations, in more general cases .
Revised:  Within a perturbation analysis of the model from the infinite mixing rate, we provide analytical evidence that extinction occurs deterministically at sufficiently large but finite values of the mixing rate for any species number N\ge3 . Further, we discuss numerical results concerning the trajectories toward such deterministic extinction, including bifurcations, in more general cases .
Edit intent: clarity